TRIC: an automated alignment strategy for reproducible protein quantification in targeted proteomics.

PubMed

Röst, Hannes L; Liu, Yansheng; D'Agostino, Giuseppe; Zanella, Matteo; Navarro, Pedro; Rosenberger, George; Collins, Ben C; Gillet, Ludovic; Testa, Giuseppe; Malmström, Lars; Aebersold, Ruedi

2016-09-01

Next-generation mass spectrometric (MS) techniques such as SWATH-MS have substantially increased the throughput and reproducibility of proteomic analysis, but ensuring consistent quantification of thousands of peptide analytes across multiple liquid chromatography-tandem MS (LC-MS/MS) runs remains a challenging and laborious manual process. To produce highly consistent and quantitatively accurate proteomics data matrices in an automated fashion, we developed TRIC (http://proteomics.ethz.ch/tric/), a software tool that utilizes fragment-ion data to perform cross-run alignment, consistent peak-picking and quantification for high-throughput targeted proteomics. TRIC reduced the identification error compared to a state-of-the-art SWATH-MS analysis without alignment by more than threefold at constant recall while correcting for highly nonlinear chromatographic effects. On a pulsed-SILAC experiment performed on human induced pluripotent stem cells, TRIC was able to automatically align and quantify thousands of light and heavy isotopic peak groups. Thus, TRIC fills a gap in the pipeline for automated analysis of massively parallel targeted proteomics data sets.

CrossCheck: an open-source web tool for high-throughput screen data analysis.

PubMed

Najafov, Jamil; Najafov, Ayaz

2017-07-19

Modern high-throughput screening methods allow researchers to generate large datasets that potentially contain important biological information. However, oftentimes, picking relevant hits from such screens and generating testable hypotheses requires training in bioinformatics and the skills to efficiently perform database mining. There are currently no tools available to general public that allow users to cross-reference their screen datasets with published screen datasets. To this end, we developed CrossCheck, an online platform for high-throughput screen data analysis. CrossCheck is a centralized database that allows effortless comparison of the user-entered list of gene symbols with 16,231 published datasets. These datasets include published data from genome-wide RNAi and CRISPR screens, interactome proteomics and phosphoproteomics screens, cancer mutation databases, low-throughput studies of major cell signaling mediators, such as kinases, E3 ubiquitin ligases and phosphatases, and gene ontological information. Moreover, CrossCheck includes a novel database of predicted protein kinase substrates, which was developed using proteome-wide consensus motif searches. CrossCheck dramatically simplifies high-throughput screen data analysis and enables researchers to dig deep into the published literature and streamline data-driven hypothesis generation. CrossCheck is freely accessible as a web-based application at http://proteinguru.com/crosscheck.

Five years later: the current status of the use of proteomics and transcriptomics in EMF research.

PubMed

Leszczynski, Dariusz; de Pomerai, David; Koczan, Dirk; Stoll, Dieter; Franke, Helmut; Albar, Juan Pablo

2012-08-01

The World Health Organization's and Radiation and Nuclear Safety Authority's "Workshop on Application of Proteomics and Transcriptomics in Electromagnetic Fields Research" was held in Helsinki in the October/November 2005. As a consequence of this meeting, Proteomics journal published in 2006 a special issue "Application of Proteomics and Transcriptomics in EMF Research" (Vol. 6 No. 17; Guest Editor: D. Leszczynski). This Proteomics issue presented the status of research, of the effects of electromagnetic fields (EMF) using proteomics and transcriptomics methods, present in 2005. The current overview/opinion article presents the status of research in this area by reviewing all studies that were published by the end of 2010. The review work was a part of the European Cooperation in the Field of Scientific and Technical Research (COST) Action BM0704 that created a structure in which researchers in the field of EMF and health shared knowledge and information. The review was prepared by the members of the COST Action BM0704 task group on the high-throughput screening techniques and electromagnetic fields (TG-HTST-EMF). © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Enhancing Bottom-up and Top-down Proteomic Measurements with Ion Mobility Separations

DOE PAGES

Baker, Erin Shammel; Burnum-Johnson, Kristin E.; Ibrahim, Yehia M.; ...

2015-07-03

Proteomic measurements with greater throughput, sensitivity and additional structural information enhance the in-depth characterization of complex mixtures and targeted studies with additional information and higher confidence. While liquid chromatography separation coupled with mass spectrometry (LC-MS) measurements have provided information on thousands of proteins in different sample types, the additional of another rapid separation stage providing structural information has many benefits for analyses. Technical advances in ion funnels and multiplexing have enabled ion mobility separations to be easily and effectively coupled with LC-MS proteomics to enhance the information content of measurements. Finally, herein, we report on applications illustrating increased sensitivity, throughput,more » and structural information by utilizing IMS-MS and LC-IMS-MS measurements for both bottom-up and top-down proteomics measurements.« less

Abundant Lysine Methylation and N-Terminal Acetylation in Sulfolobus islandicus Revealed by Bottom-Up and Top-Down Proteomics*

PubMed Central

Vorontsov, Egor A.; Rensen, Elena; Prangishvili, David; Krupovic, Mart; Chamot-Rooke, Julia

2016-01-01

Protein post-translational methylation has been reported to occur in archaea, including members of the genus Sulfolobus, but has never been characterized on a proteome-wide scale. Among important Sulfolobus proteins carrying such modification are the chromatin proteins that have been described to be methylated on lysine side chains, resembling eukaryotic histones in that aspect. To get more insight into the extent of this modification and its dynamics during the different growth steps of the thermoacidophylic archaeon S. islandicus LAL14/1, we performed a global and deep proteomic analysis using a combination of high-throughput bottom-up and top-down approaches on a single high-resolution mass spectrometer. 1,931 methylation sites on 751 proteins were found by the bottom-up analysis, with methylation sites on 526 proteins monitored throughout three cell culture growth stages: early-exponential, mid-exponential, and stationary. The top-down analysis revealed 3,978 proteoforms arising from 681 proteins, including 292 methylated proteoforms, 85 of which were comprehensively characterized. Methylated proteoforms of the five chromatin proteins (Alba1, Alba2, Cren7, Sul7d1, Sul7d2) were fully characterized by a combination of bottom-up and top-down data. The top-down analysis also revealed an increase of methylation during cell growth for two chromatin proteins, which had not been evidenced by bottom-up. These results shed new light on the ubiquitous lysine methylation throughout the S. islandicus proteome. Furthermore, we found that S. islandicus proteins are frequently acetylated at the N terminus, following the removal of the N-terminal methionine. This study highlights the great value of combining bottom-up and top-down proteomics for obtaining an unprecedented level of accuracy in detecting differentially modified intact proteoforms. The data have been deposited to the ProteomeXchange with identifiers PXD003074 and PXD004179. PMID:27555370

Combining high-throughput MALDI-TOF mass spectrometry and isoelectric focusing gel electrophoresis for virtual 2D gel-based proteomics.

PubMed

Lohnes, Karen; Quebbemann, Neil R; Liu, Kate; Kobzeff, Fred; Loo, Joseph A; Ogorzalek Loo, Rachel R

2016-07-15

The virtual two-dimensional gel electrophoresis/mass spectrometry (virtual 2D gel/MS) technology combines the premier, high-resolution capabilities of 2D gel electrophoresis with the sensitivity and high mass accuracy of mass spectrometry (MS). Intact proteins separated by isoelectric focusing (IEF) gel electrophoresis are imaged from immobilized pH gradient (IPG) polyacrylamide gels (the first dimension of classic 2D-PAGE) by matrix-assisted laser desorption/ionization (MALDI) MS. Obtaining accurate intact masses from sub-picomole-level proteins embedded in 2D-PAGE gels or in IPG strips is desirable to elucidate how the protein of one spot identified as protein 'A' on a 2D gel differs from the protein of another spot identified as the same protein, whenever tryptic peptide maps fail to resolve the issue. This task, however, has been extremely challenging. Virtual 2D gel/MS provides access to these intact masses. Modifications to our matrix deposition procedure improve the reliability with which IPG gels can be prepared; the new procedure is described. Development of this MALDI MS imaging (MSI) method for high-throughput MS with integrated 'top-down' MS to elucidate protein isoforms from complex biological samples is described and it is demonstrated that a 4-cm IPG gel segment can now be imaged in approximately 5min. Gel-wide chemical and enzymatic methods with further interrogation by MALDI MS/MS provide identifications, sequence-related information, and post-translational/transcriptional modification information. The MSI-based virtual 2D gel/MS platform may potentially link the benefits of 'top-down' and 'bottom-up' proteomics. Copyright © 2016 Elsevier Inc. All rights reserved.

Less is More: Membrane Protein Digestion Beyond Urea–Trypsin Solution for Next-level Proteomics*

PubMed Central

Zhang, Xi

2015-01-01

The goal of next-level bottom-up membrane proteomics is protein function investigation, via high-coverage high-throughput peptide-centric quantitation of expression, modifications and dynamic structures at systems scale. Yet efficient digestion of mammalian membrane proteins presents a daunting barrier, and prevalent day-long urea–trypsin in-solution digestion proved insufficient to reach this goal. Many efforts contributed incremental advances over past years, but involved protein denaturation that disconnected measurement from functional states. Beyond denaturation, the recent discovery of structure/proteomics omni-compatible detergent n-dodecyl-β-d-maltopyranoside, combined with pepsin and PNGase F columns, enabled breakthroughs in membrane protein digestion: a 2010 DDM-low-TCEP (DLT) method for H/D-exchange (HDX) using human G protein-coupled receptor, and a 2015 flow/detergent-facilitated protease and de-PTM digestions (FDD) for integrative deep sequencing and quantitation using full-length human ion channel complex. Distinguishing protein solubilization from denaturation, protease digestion reliability from theoretical specificity, and reduction from alkylation, these methods shifted day(s)-long paradigms into minutes, and afforded fully automatable (HDX)-protein-peptide-(tandem mass tag)-HPLC pipelines to instantly measure functional proteins at deep coverage, high peptide reproducibility, low artifacts and minimal leakage. Promoting—not destroying—structures and activities harnessed membrane proteins for the next-level streamlined functional proteomics. This review analyzes recent advances in membrane protein digestion methods and highlights critical discoveries for future proteomics. PMID:26081834

Development of Droplet Microfluidics Enabling High-Throughput Single-Cell Analysis.

PubMed

Wen, Na; Zhao, Zhan; Fan, Beiyuan; Chen, Deyong; Men, Dong; Wang, Junbo; Chen, Jian

2016-07-05

This article reviews recent developments in droplet microfluidics enabling high-throughput single-cell analysis. Five key aspects in this field are included in this review: (1) prototype demonstration of single-cell encapsulation in microfluidic droplets; (2) technical improvements of single-cell encapsulation in microfluidic droplets; (3) microfluidic droplets enabling single-cell proteomic analysis; (4) microfluidic droplets enabling single-cell genomic analysis; and (5) integrated microfluidic droplet systems enabling single-cell screening. We examine the advantages and limitations of each technique and discuss future research opportunities by focusing on key performances of throughput, multifunctionality, and absolute quantification.

HTAPP: High-Throughput Autonomous Proteomic Pipeline

PubMed Central

Yu, Kebing; Salomon, Arthur R.

2011-01-01

Recent advances in the speed and sensitivity of mass spectrometers and in analytical methods, the exponential acceleration of computer processing speeds, and the availability of genomic databases from an array of species and protein information databases have led to a deluge of proteomic data. The development of a lab-based automated proteomic software platform for the automated collection, processing, storage, and visualization of expansive proteomic datasets is critically important. The high-throughput autonomous proteomic pipeline (HTAPP) described here is designed from the ground up to provide critically important flexibility for diverse proteomic workflows and to streamline the total analysis of a complex proteomic sample. This tool is comprised of software that controls the acquisition of mass spectral data along with automation of post-acquisition tasks such as peptide quantification, clustered MS/MS spectral database searching, statistical validation, and data exploration within a user-configurable lab-based relational database. The software design of HTAPP focuses on accommodating diverse workflows and providing missing software functionality to a wide range of proteomic researchers to accelerate the extraction of biological meaning from immense proteomic data sets. Although individual software modules in our integrated technology platform may have some similarities to existing tools, the true novelty of the approach described here is in the synergistic and flexible combination of these tools to provide an integrated and efficient analysis of proteomic samples. PMID:20336676

Advanced proteomic liquid chromatography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xie, Fang; Smith, Richard D.; Shen, Yufeng

2012-10-26

Liquid chromatography coupled with mass spectrometry is the predominant platform used to analyze proteomics samples consisting of large numbers of proteins and their proteolytic products (e.g., truncated polypeptides) and spanning a wide range of relative concentrations. This review provides an overview of advanced capillary liquid chromatography techniques and methodologies that greatly improve separation resolving power and proteomics analysis coverage, sensitivity, and throughput.

LOCATE: a mouse protein subcellular localization database

PubMed Central

Fink, J. Lynn; Aturaliya, Rajith N.; Davis, Melissa J.; Zhang, Fasheng; Hanson, Kelly; Teasdale, Melvena S.; Kai, Chikatoshi; Kawai, Jun; Carninci, Piero; Hayashizaki, Yoshihide; Teasdale, Rohan D.

2006-01-01

We present here LOCATE, a curated, web-accessible database that houses data describing the membrane organization and subcellular localization of proteins from the FANTOM3 Isoform Protein Sequence set. Membrane organization is predicted by the high-throughput, computational pipeline MemO. The subcellular locations of selected proteins from this set were determined by a high-throughput, immunofluorescence-based assay and by manually reviewing >1700 peer-reviewed publications. LOCATE represents the first effort to catalogue the experimentally verified subcellular location and membrane organization of mammalian proteins using a high-throughput approach and provides localization data for ∼40% of the mouse proteome. It is available at . PMID:16381849

2D DIGE Does Not Reveal all: A Scotopic Report Suggests Differential Expression of a Single "Calponin Family Member" Protein for Tetany of Sphincters!

PubMed

Chaudhury, Arun

2015-01-01

Using 2D differential gel electrophoresis (DIGE) and mass spectrometry (MS), a recent report by Rattan and Ali (2015) compared proteome expression between tonically contracted sphincteric smooth muscles of the internal anal sphincter (IAS), in comparison to the adjacent rectum [rectal smooth muscles (RSM)] that contracts in a phasic fashion. The study showed the differential expression of a single 23 kDa protein SM22, which was 1.87 fold, overexpressed in RSM in comparison to IAS. Earlier studies have shown differences in expression of different proteins like Rho-associated protein kinase II, myosin light chain kinase, myosin phosphatase, and protein kinase C between IAS and RSM. The currently employed methods, despite its high-throughput potential, failed to identify these well-characterized differences between phasic and tonic muscles. This calls into question the fidelity and validatory potential of the otherwise powerful technology of 2D DIGE/MS. These discrepancies, when redressed in future studies, will evolve this recent report as an important baseline study of "sphincter proteome." Proteomics techniques are currently underutilized in examining pathophysiology of hypertensive/hypotensive disorders involving gastrointestinal sphincters, including achalasia, gastroesophageal reflux disease (GERD), spastic pylorus, seen during diabetes or chronic chemotherapy, intestinal pseudo-obstruction, and recto-anal incontinence. Global proteome mapping may provide instant snapshot of the complete repertoire of differential proteins, thus expediting to identify the molecular pathology of gastrointestinal motility disorders currently labeled "idiopathic" and facilitating practice of precision medicine.

Less is More: Membrane Protein Digestion Beyond Urea-Trypsin Solution for Next-level Proteomics.

PubMed

Zhang, Xi

2015-09-01

The goal of next-level bottom-up membrane proteomics is protein function investigation, via high-coverage high-throughput peptide-centric quantitation of expression, modifications and dynamic structures at systems scale. Yet efficient digestion of mammalian membrane proteins presents a daunting barrier, and prevalent day-long urea-trypsin in-solution digestion proved insufficient to reach this goal. Many efforts contributed incremental advances over past years, but involved protein denaturation that disconnected measurement from functional states. Beyond denaturation, the recent discovery of structure/proteomics omni-compatible detergent n-dodecyl-β-d-maltopyranoside, combined with pepsin and PNGase F columns, enabled breakthroughs in membrane protein digestion: a 2010 DDM-low-TCEP (DLT) method for H/D-exchange (HDX) using human G protein-coupled receptor, and a 2015 flow/detergent-facilitated protease and de-PTM digestions (FDD) for integrative deep sequencing and quantitation using full-length human ion channel complex. Distinguishing protein solubilization from denaturation, protease digestion reliability from theoretical specificity, and reduction from alkylation, these methods shifted day(s)-long paradigms into minutes, and afforded fully automatable (HDX)-protein-peptide-(tandem mass tag)-HPLC pipelines to instantly measure functional proteins at deep coverage, high peptide reproducibility, low artifacts and minimal leakage. Promoting-not destroying-structures and activities harnessed membrane proteins for the next-level streamlined functional proteomics. This review analyzes recent advances in membrane protein digestion methods and highlights critical discoveries for future proteomics. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Systems biology definition of the core proteome of metabolism and expression is consistent with high-throughput data.

PubMed

Yang, Laurence; Tan, Justin; O'Brien, Edward J; Monk, Jonathan M; Kim, Donghyuk; Li, Howard J; Charusanti, Pep; Ebrahim, Ali; Lloyd, Colton J; Yurkovich, James T; Du, Bin; Dräger, Andreas; Thomas, Alex; Sun, Yuekai; Saunders, Michael A; Palsson, Bernhard O

2015-08-25

Finding the minimal set of gene functions needed to sustain life is of both fundamental and practical importance. Minimal gene lists have been proposed by using comparative genomics-based core proteome definitions. A definition of a core proteome that is supported by empirical data, is understood at the systems-level, and provides a basis for computing essential cell functions is lacking. Here, we use a systems biology-based genome-scale model of metabolism and expression to define a functional core proteome consisting of 356 gene products, accounting for 44% of the Escherichia coli proteome by mass based on proteomics data. This systems biology core proteome includes 212 genes not found in previous comparative genomics-based core proteome definitions, accounts for 65% of known essential genes in E. coli, and has 78% gene function overlap with minimal genomes (Buchnera aphidicola and Mycoplasma genitalium). Based on transcriptomics data across environmental and genetic backgrounds, the systems biology core proteome is significantly enriched in nondifferentially expressed genes and depleted in differentially expressed genes. Compared with the noncore, core gene expression levels are also similar across genetic backgrounds (two times higher Spearman rank correlation) and exhibit significantly more complex transcriptional and posttranscriptional regulatory features (40% more transcription start sites per gene, 22% longer 5'UTR). Thus, genome-scale systems biology approaches rigorously identify a functional core proteome needed to support growth. This framework, validated by using high-throughput datasets, facilitates a mechanistic understanding of systems-level core proteome function through in silico models; it de facto defines a paleome.

Advanced proteomic liquid chromatography

PubMed Central

Xie, Fang; Smith, Richard D.; Shen, Yufeng

2012-01-01

Liquid chromatography coupled with mass spectrometry is the predominant platform used to analyze proteomics samples consisting of large numbers of proteins and their proteolytic products (e.g., truncated polypeptides) and spanning a wide range of relative concentrations. This review provides an overview of advanced capillary liquid chromatography techniques and methodologies that greatly improve separation resolving power and proteomics analysis coverage, sensitivity, and throughput. PMID:22840822

Potential for proteomic approaches in determining efficacy biomarkers following administration of fish oils rich in omega-3 fatty acids: application in pancreatic cancers.

PubMed

Runau, Franscois; Arshad, Ali; Isherwood, John; Norris, Leonie; Howells, Lynne; Metcalfe, Matthew; Dennison, Ashley

2015-06-01

Pancreatic cancer is a disease with a significantly poor prognosis. Despite modern advances in other medical, surgical, and oncologic therapy, the outcome from pancreatic cancer has improved little over the last 40 years. To improve the management of this difficult disease, trials investigating the use of dietary and parenteral fish oils rich in omega-3 (ω-3) fatty acids, exhibiting proven anti-inflammatory and anticarcinogenic properties, have revealed favorable results in pancreatic cancers. Proteomics is the large-scale study of proteins that attempts to characterize the complete set of proteins encoded by the genome of an organism and that, with the use of sensitive mass spectrometric-based techniques, has allowed high-throughput analysis of the proteome to aid identification of putative biomarkers pertinent to given disease states. These biomarkers provide useful insight into potentially discovering new markers for early detection or elucidating the efficacy of treatment on pancreatic cancers. Here, our review identifies potential proteomic-based biomarkers in pancreatic cancer relating to apoptosis, cell proliferation, angiogenesis, and metabolic regulation in clinical studies. We also reviewed proteomic biomarkers from the administration of ω-3 fatty acids that act on similar anticarcinogenic pathways as above and reflect that proteomic studies on the effect of ω-3 fatty acids in pancreatic cancer will yield favorable results. © 2015 American Society for Parenteral and Enteral Nutrition.

High throughput proteomic analysis of the secretome in an explant model of articular cartilage inflammation

PubMed Central

Clutterbuck, Abigail L.; Smith, Julia R.; Allaway, David; Harris, Pat; Liddell, Susan; Mobasheri, Ali

2011-01-01

This study employed a targeted high-throughput proteomic approach to identify the major proteins present in the secretome of articular cartilage. Explants from equine metacarpophalangeal joints were incubated alone or with interleukin-1beta (IL-1β, 10 ng/ml), with or without carprofen, a non-steroidal anti-inflammatory drug, for six days. After tryptic digestion of culture medium supernatants, resulting peptides were separated by HPLC and detected in a Bruker amaZon ion trap instrument. The five most abundant peptides in each MS scan were fragmented and the fragmentation patterns compared to mammalian entries in the Swiss-Prot database, using the Mascot search engine. Tryptic peptides originating from aggrecan core protein, cartilage oligomeric matrix protein (COMP), fibronectin, fibromodulin, thrombospondin-1 (TSP-1), clusterin (CLU), cartilage intermediate layer protein-1 (CILP-1), chondroadherin (CHAD) and matrix metalloproteinases MMP-1 and MMP-3 were detected. Quantitative western blotting confirmed the presence of CILP-1, CLU, MMP-1, MMP-3 and TSP-1. Treatment with IL-1β increased MMP-1, MMP-3 and TSP-1 and decreased the CLU precursor but did not affect CILP-1 and CLU levels. Many of the proteins identified have well-established extracellular matrix functions and are involved in early repair/stress responses in cartilage. This high throughput approach may be used to study the changes that occur in the early stages of osteoarthritis. PMID:21354348

Solid-Phase Extraction Strategies to Surmount Body Fluid Sample Complexity in High-Throughput Mass Spectrometry-Based Proteomics

PubMed Central

Bladergroen, Marco R.; van der Burgt, Yuri E. M.

2015-01-01

For large-scale and standardized applications in mass spectrometry- (MS-) based proteomics automation of each step is essential. Here we present high-throughput sample preparation solutions for balancing the speed of current MS-acquisitions and the time needed for analytical workup of body fluids. The discussed workflows reduce body fluid sample complexity and apply for both bottom-up proteomics experiments and top-down protein characterization approaches. Various sample preparation methods that involve solid-phase extraction (SPE) including affinity enrichment strategies have been automated. Obtained peptide and protein fractions can be mass analyzed by direct infusion into an electrospray ionization (ESI) source or by means of matrix-assisted laser desorption ionization (MALDI) without further need of time-consuming liquid chromatography (LC) separations. PMID:25692071

TRIC: an automated alignment strategy for reproducible protein quantification in targeted proteomics

PubMed Central

Röst, Hannes L.; Liu, Yansheng; D’Agostino, Giuseppe; Zanella, Matteo; Navarro, Pedro; Rosenberger, George; Collins, Ben C.; Gillet, Ludovic; Testa, Giuseppe; Malmström, Lars; Aebersold, Ruedi

2016-01-01

Large scale, quantitative proteomic studies have become essential for the analysis of clinical cohorts, large perturbation experiments and systems biology studies. While next-generation mass spectrometric techniques such as SWATH-MS have substantially increased throughput and reproducibility, ensuring consistent quantification of thousands of peptide analytes across multiple LC-MS/MS runs remains a challenging and laborious manual process. To produce highly consistent and quantitatively accurate proteomics data matrices in an automated fashion, we have developed the TRIC software which utilizes fragment ion data to perform cross-run alignment, consistent peak-picking and quantification for high throughput targeted proteomics. TRIC uses a graph-based alignment strategy based on non-linear retention time correction to integrate peak elution information from all LC-MS/MS runs acquired in a study. When compared to state-of-the-art SWATH-MS data analysis, the algorithm was able to reduce the identification error by more than 3-fold at constant recall, while correcting for highly non-linear chromatographic effects. On a pulsed-SILAC experiment performed on human induced pluripotent stem (iPS) cells, TRIC was able to automatically align and quantify thousands of light and heavy isotopic peak groups and substantially increased the quantitative completeness and biological information in the data, providing insights into protein dynamics of iPS cells. Overall, this study demonstrates the importance of consistent quantification in highly challenging experimental setups, and proposes an algorithm to automate this task, constituting the last missing piece in a pipeline for automated analysis of massively parallel targeted proteomics datasets. PMID:27479329

The Urine Proteome as a Biomarker of Radiation Injury: Submitted to Proteomics- Clinical Applications Special Issue: "Renal and Urinary Proteomics (Thongboonkerd)"

PubMed

Sharma, Mukut; Halligan, Brian D; Wakim, Bassam T; Savin, Virginia J; Cohen, Eric P; Moulder, John E

2008-06-18

Terrorist attacks or nuclear accidents could expose large numbers of people to ionizing radiation, and early biomarkers of radiation injury would be critical for triage, treatment and follow-up of such individuals. However, no such biomarkers have yet been proven to exist. We tested the potential of high throughput proteomics to identify protein biomarkers of radiation injury after total body X-ray irradiation in a rat model. Subtle functional changes in the kidney are suggested by an increased glomerular permeability for macromolecules measured within 24 hours after TBI. Ultrastructural changes in glomerular podocytes include partial loss of the interdigitating organization of foot processes. Analysis of urine by LC-MS/MS and 2D-GE showed significant changes in the urine proteome within 24 hours after TBI. Tissue kallikrein 1-related peptidase, cysteine proteinase inhibitor cystatin C and oxidized histidine were found to be increased while a number of proteinase inhibitors including kallikrein-binding protein and albumin were found to be decreased post-irradiation. Thus, TBI causes immediately detectable changes in renal structure and function and in the urinary protein profile. This suggests that both systemic and renal changes are induced by radiation and it may be possible to identify a set of biomarkers unique to radiation injury.

High-throughput proteomic characterization of plasma rich in growth factors (PRGF-Endoret)-derived fibrin clot interactome.

PubMed

Anitua, Eduardo; Prado, Roberto; Azkargorta, Mikel; Rodriguez-Suárez, Eva; Iloro, Ibon; Casado-Vela, Juan; Elortza, Felix; Orive, Gorka

2015-11-01

Plasma rich in growth factors (PRGF®-Endoret®) is an autologous technology that contains a set of proteins specifically addressed to wound healing and tissue regeneration. The scaffold formed by using this technology is a clot mainly composed of fibrin protein, forming a three-dimensional (3D) macroscopic network. This biomaterial is easily obtained by biotechnological means from blood and can be used in a range of situations to help wound healing and tissue regeneration. Although the main constituent of this clot is the fibrin scaffold, little is known about other proteins interacting in this clot that may act as adjuvants in the healing process. The aim of this study was to characterize the proteins enclosed by PRGF-Endoret scaffold, using a double-proteomic approach that combines 1D-SDS-PAGE approach followed by LC-MS/MS, and 2-DE followed by MALDI-TOF/TOF. The results presented here provide a description of the catalogue of key proteins in close contact with the fibrin scaffold. The obtained lists of proteins were grouped into families and networks according to gene ontology. Taken together, an enrichment of both proteins and protein families specifically involved in tissue regeneration and wound healing has been found. Copyright © 2013 John Wiley & Sons, Ltd.

Content Is King: Databases Preserve the Collective Information of Science.

PubMed

Yates, John R

2018-04-01

Databases store sequence information experimentally gathered to create resources that further science. In the last 20 years databases have become critical components of fields like proteomics where they provide the basis for large-scale and high-throughput proteomic informatics. Amos Bairoch, winner of the Association of Biomolecular Resource Facilities Frederick Sanger Award, has created some of the important databases proteomic research depends upon for accurate interpretation of data.

Proteomics Analysis of the Nucleolus in Adenovirus-infected Cells

PubMed Central

Lam, Yun W.; Evans, Vanessa C.; Heesom, Kate J.; Lamond, Angus I.; Matthews, David A.

2010-01-01

Adenoviruses replicate primarily in the host cell nucleus, and it is well established that adenovirus infection affects the structure and function of host cell nucleoli in addition to coding for a number of nucleolar targeted viral proteins. Here we used unbiased proteomics methods, including high throughput mass spectrometry coupled with stable isotope labeling by amino acids in cell culture (SILAC) and traditional two-dimensional gel electrophoresis, to identify quantitative changes in the protein composition of the nucleolus during adenovirus infection. Two-dimensional gel analysis revealed changes in six proteins. By contrast, SILAC-based approaches identified 351 proteins with 24 proteins showing at least a 2-fold change after infection. Of those, four were previously reported to have aberrant localization and/or functional relevance during adenovirus infection. In total, 15 proteins identified as changing in amount by proteomics methods were examined in infected cells using confocal microscopy. Eleven of these proteins showed altered patterns of localization in adenovirus-infected cells. Comparing our data with the effects of actinomycin D on the nucleolar proteome revealed that adenovirus infection apparently specifically targets a relatively small subset of nucleolar antigens at the time point examined. PMID:19812395

Proteomics analysis of the nucleolus in adenovirus-infected cells.

PubMed

Lam, Yun W; Evans, Vanessa C; Heesom, Kate J; Lamond, Angus I; Matthews, David A

2010-01-01

Adenoviruses replicate primarily in the host cell nucleus, and it is well established that adenovirus infection affects the structure and function of host cell nucleoli in addition to coding for a number of nucleolar targeted viral proteins. Here we used unbiased proteomics methods, including high throughput mass spectrometry coupled with stable isotope labeling by amino acids in cell culture (SILAC) and traditional two-dimensional gel electrophoresis, to identify quantitative changes in the protein composition of the nucleolus during adenovirus infection. Two-dimensional gel analysis revealed changes in six proteins. By contrast, SILAC-based approaches identified 351 proteins with 24 proteins showing at least a 2-fold change after infection. Of those, four were previously reported to have aberrant localization and/or functional relevance during adenovirus infection. In total, 15 proteins identified as changing in amount by proteomics methods were examined in infected cells using confocal microscopy. Eleven of these proteins showed altered patterns of localization in adenovirus-infected cells. Comparing our data with the effects of actinomycin D on the nucleolar proteome revealed that adenovirus infection apparently specifically targets a relatively small subset of nucleolar antigens at the time point examined.

Accounting for isotopic clustering in Fourier transform mass spectrometry data analysis for clinical diagnostic studies.

PubMed

Kakourou, Alexia; Vach, Werner; Nicolardi, Simone; van der Burgt, Yuri; Mertens, Bart

2016-10-01

Mass spectrometry based clinical proteomics has emerged as a powerful tool for high-throughput protein profiling and biomarker discovery. Recent improvements in mass spectrometry technology have boosted the potential of proteomic studies in biomedical research. However, the complexity of the proteomic expression introduces new statistical challenges in summarizing and analyzing the acquired data. Statistical methods for optimally processing proteomic data are currently a growing field of research. In this paper we present simple, yet appropriate methods to preprocess, summarize and analyze high-throughput MALDI-FTICR mass spectrometry data, collected in a case-control fashion, while dealing with the statistical challenges that accompany such data. The known statistical properties of the isotopic distribution of the peptide molecules are used to preprocess the spectra and translate the proteomic expression into a condensed data set. Information on either the intensity level or the shape of the identified isotopic clusters is used to derive summary measures on which diagnostic rules for disease status allocation will be based. Results indicate that both the shape of the identified isotopic clusters and the overall intensity level carry information on the class outcome and can be used to predict the presence or absence of the disease.

Proteome- and transcriptome-driven reconstruction of the human myocyte metabolic network and its use for identification of markers for diabetes.

PubMed

Väremo, Leif; Scheele, Camilla; Broholm, Christa; Mardinoglu, Adil; Kampf, Caroline; Asplund, Anna; Nookaew, Intawat; Uhlén, Mathias; Pedersen, Bente Klarlund; Nielsen, Jens

2015-05-12

Skeletal myocytes are metabolically active and susceptible to insulin resistance and are thus implicated in type 2 diabetes (T2D). This complex disease involves systemic metabolic changes, and their elucidation at the systems level requires genome-wide data and biological networks. Genome-scale metabolic models (GEMs) provide a network context for the integration of high-throughput data. We generated myocyte-specific RNA-sequencing data and investigated their correlation with proteome data. These data were then used to reconstruct a comprehensive myocyte GEM. Next, we performed a meta-analysis of six studies comparing muscle transcription in T2D versus healthy subjects. Transcriptional changes were mapped on the myocyte GEM, revealing extensive transcriptional regulation in T2D, particularly around pyruvate oxidation, branched-chain amino acid catabolism, and tetrahydrofolate metabolism, connected through the downregulated dihydrolipoamide dehydrogenase. Strikingly, the gene signature underlying this metabolic regulation successfully classifies the disease state of individual samples, suggesting that regulation of these pathways is a ubiquitous feature of myocytes in response to T2D. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Proteomic Analysis of Metabolic Responses to Biofuels and Chemicals in Photosynthetic Cyanobacteria.

PubMed

Sun, T; Chen, L; Zhang, W

2017-01-01

Recent progresses in various "omics" technologies have enabled quantitative measurements of biological molecules in a high-throughput manner. Among them, high-throughput proteomics is a rapidly advancing field that offers a new means to quantify metabolic changes at protein level, which has significantly facilitated our understanding of cellular process, such as protein synthesis, posttranslational modifications, and degradation in responding to environmental perturbations. Cyanobacteria are autotrophic prokaryotes that can perform oxygenic photosynthesis and have recently attracted significant attentions as one promising alternative to traditionally biomass-based "microbial cell factories" to produce green fuels and chemicals. However, early studies have shown that the low tolerance to toxic biofuels and chemicals represented one major hurdle for further improving productivity of the cyanobacterial production systems. To address the issue, metabolic responses and their regulation of cyanobacterial cells to toxic end-products need to be defined. In this chapter, we discuss recent progresses in interpreting cyanobacterial responses to biofuels and chemicals using high-throughput proteomics approach, aiming to provide insights and guidelines on how to enhance tolerance and productivity of biofuels or chemicals in the renewable cyanobacteria systems in the future. © 2017 Elsevier Inc. All rights reserved.

Detection of dysregulated protein-association networks by high-throughput proteomics predicts cancer vulnerabilities.

PubMed

Lapek, John D; Greninger, Patricia; Morris, Robert; Amzallag, Arnaud; Pruteanu-Malinici, Iulian; Benes, Cyril H; Haas, Wilhelm

2017-10-01

The formation of protein complexes and the co-regulation of the cellular concentrations of proteins are essential mechanisms for cellular signaling and for maintaining homeostasis. Here we use isobaric-labeling multiplexed proteomics to analyze protein co-regulation and show that this allows the identification of protein-protein associations with high accuracy. We apply this 'interactome mapping by high-throughput quantitative proteome analysis' (IMAHP) method to a panel of 41 breast cancer cell lines and show that deviations of the observed protein co-regulations in specific cell lines from the consensus network affects cellular fitness. Furthermore, these aberrant interactions serve as biomarkers that predict the drug sensitivity of cell lines in screens across 195 drugs. We expect that IMAHP can be broadly used to gain insight into how changing landscapes of protein-protein associations affect the phenotype of biological systems.

Three dimensional liquid chromatography coupling ion exchange chromatography/hydrophobic interaction chromatography/reverse phase chromatography for effective protein separation in top-down proteomics.

PubMed

Valeja, Santosh G; Xiu, Lichen; Gregorich, Zachery R; Guner, Huseyin; Jin, Song; Ge, Ying

2015-01-01

To address the complexity of the proteome in mass spectrometry (MS)-based top-down proteomics, multidimensional liquid chromatography (MDLC) strategies that can effectively separate proteins with high resolution and automation are highly desirable. Although various MDLC methods that can effectively separate peptides from protein digests exist, very few MDLC strategies, primarily consisting of 2DLC, are available for intact protein separation, which is insufficient to address the complexity of the proteome. We recently demonstrated that hydrophobic interaction chromatography (HIC) utilizing a MS-compatible salt can provide high resolution separation of intact proteins for top-down proteomics. Herein, we have developed a novel 3DLC strategy by coupling HIC with ion exchange chromatography (IEC) and reverse phase chromatography (RPC) for intact protein separation. We demonstrated that a 3D (IEC-HIC-RPC) approach greatly outperformed the conventional 2D IEC-RPC approach. For the same IEC fraction (out of 35 fractions) from a crude HEK 293 cell lysate, a total of 640 proteins were identified in the 3D approach (corresponding to 201 nonredundant proteins) as compared to 47 in the 2D approach, whereas simply prolonging the gradients in RPC in the 2D approach only led to minimal improvement in protein separation and identifications. Therefore, this novel 3DLC method has great potential for effective separation of intact proteins to achieve deep proteome coverage in top-down proteomics.

Computational approaches to protein inference in shotgun proteomics

PubMed Central

2012-01-01

Shotgun proteomics has recently emerged as a powerful approach to characterizing proteomes in biological samples. Its overall objective is to identify the form and quantity of each protein in a high-throughput manner by coupling liquid chromatography with tandem mass spectrometry. As a consequence of its high throughput nature, shotgun proteomics faces challenges with respect to the analysis and interpretation of experimental data. Among such challenges, the identification of proteins present in a sample has been recognized as an important computational task. This task generally consists of (1) assigning experimental tandem mass spectra to peptides derived from a protein database, and (2) mapping assigned peptides to proteins and quantifying the confidence of identified proteins. Protein identification is fundamentally a statistical inference problem with a number of methods proposed to address its challenges. In this review we categorize current approaches into rule-based, combinatorial optimization and probabilistic inference techniques, and present them using integer programing and Bayesian inference frameworks. We also discuss the main challenges of protein identification and propose potential solutions with the goal of spurring innovative research in this area. PMID:23176300

Synovial fluid proteomics in the pursuit of arthritis mediators: An evolving field of novel biomarker discovery.

PubMed

Mahendran, Shalini M; Oikonomopoulou, Katerina; Diamandis, Eleftherios P; Chandran, Vinod

Synovial fluid (SF) is a protein-rich fluid produced into the joint cavity by cells of the synovial membrane. Due to its direct contact with articular cartilage, surfaces of the bone, and the synoviocytes of the inner membrane, it provides a promising reflection of the biochemical state of the joint under varying physiological and pathophysiological conditions. This property of SF has been exploited within numerous studies in search of unique biomarkers of joint pathologies with the ultimate goal of developing minimally invasive clinical assays to detect and/or monitor disease states. Several proteomic methodologies have been employed to mine the SF proteome. From elementary immunoassays to high-throughput analyses using mass spectrometry-based techniques, each has demonstrated distinct advantages and disadvantages in the identification and quantification of SF proteins. This review will explore the role of SF in the elucidation of the arthritis proteome and the extent to which high-throughput techniques have facilitated the discovery and validation of protein biomarkers from osteoarthritis (OA), rheumatoid arthritis (RA), psoriatic arthritis (PsA), and juvenile idiopathic arthritis (JIA) patients.

Active site specificity profiling datasets of matrix metalloproteinases (MMPs) 1, 2, 3, 7, 8, 9, 12, 13 and 14.

PubMed

Eckhard, Ulrich; Huesgen, Pitter F; Schilling, Oliver; Bellac, Caroline L; Butler, Georgina S; Cox, Jennifer H; Dufour, Antoine; Goebeler, Verena; Kappelhoff, Reinhild; Auf dem Keller, Ulrich; Klein, Theo; Lange, Philipp F; Marino, Giada; Morrison, Charlotte J; Prudova, Anna; Rodriguez, David; Starr, Amanda E; Wang, Yili; Overall, Christopher M

2016-06-01

The data described provide a comprehensive resource for the family-wide active site specificity portrayal of the human matrix metalloproteinase family. We used the high-throughput proteomic technique PICS (Proteomic Identification of protease Cleavage Sites) to comprehensively assay 9 different MMPs. We identified more than 4300 peptide cleavage sites, spanning both the prime and non-prime sides of the scissile peptide bond allowing detailed subsite cooperativity analysis. The proteomic cleavage data were expanded by kinetic analysis using a set of 6 quenched-fluorescent peptide substrates designed using these results. These datasets represent one of the largest specificity profiling efforts with subsequent structural follow up for any protease family and put the spotlight on the specificity similarities and differences of the MMP family. A detailed analysis of this data may be found in Eckhard et al. (2015) [1]. The raw mass spectrometry data and the corresponding metadata have been deposited in PRIDE/ProteomeXchange with the accession number PXD002265.

The UniProtKB guide to the human proteome

PubMed Central

Breuza, Lionel; Poux, Sylvain; Estreicher, Anne; Famiglietti, Maria Livia; Magrane, Michele; Tognolli, Michael; Bridge, Alan; Baratin, Delphine; Redaschi, Nicole

2016-01-01

Advances in high-throughput and advanced technologies allow researchers to routinely perform whole genome and proteome analysis. For this purpose, they need high-quality resources providing comprehensive gene and protein sets for their organisms of interest. Using the example of the human proteome, we will describe the content of a complete proteome in the UniProt Knowledgebase (UniProtKB). We will show how manual expert curation of UniProtKB/Swiss-Prot is complemented by expert-driven automatic annotation to build a comprehensive, high-quality and traceable resource. We will also illustrate how the complexity of the human proteome is captured and structured in UniProtKB. Database URL: www.uniprot.org PMID:26896845

ms_lims, a simple yet powerful open source laboratory information management system for MS-driven proteomics.

PubMed

Helsens, Kenny; Colaert, Niklaas; Barsnes, Harald; Muth, Thilo; Flikka, Kristian; Staes, An; Timmerman, Evy; Wortelkamp, Steffi; Sickmann, Albert; Vandekerckhove, Joël; Gevaert, Kris; Martens, Lennart

2010-03-01

MS-based proteomics produces large amounts of mass spectra that require processing, identification and possibly quantification before interpretation can be undertaken. High-throughput studies require automation of these various steps, and management of the data in association with the results obtained. We here present ms_lims (http://genesis.UGent.be/ms_lims), a freely available, open-source system based on a central database to automate data management and processing in MS-driven proteomics analyses.

Quantitative proteomics in teleost fish: insights and challenges for neuroendocrine and neurotoxicology research.

PubMed

Martyniuk, Christopher J; Popesku, Jason T; Chown, Brittany; Denslow, Nancy D; Trudeau, Vance L

2012-05-01

Neuroendocrine systems integrate both extrinsic and intrinsic signals to regulate virtually all aspects of an animal's physiology. In aquatic toxicology, studies have shown that pollutants are capable of disrupting the neuroendocrine system of teleost fish, and many chemicals found in the environment can also have a neurotoxic mode of action. Omics approaches are now used to better understand cell signaling cascades underlying fish neurophysiology and the control of pituitary hormone release, in addition to identifying adverse effects of pollutants in the teleostean central nervous system. For example, both high throughput genomics and proteomic investigations of molecular signaling cascades for both neurotransmitter and nuclear receptor agonists/antagonists have been reported. This review highlights recent studies that have utilized quantitative proteomics methods such as 2D differential in-gel electrophoresis (DIGE) and isobaric tagging for relative and absolute quantitation (iTRAQ) in neuroendocrine regions and uses these examples to demonstrate the challenges of using proteomics in neuroendocrinology and neurotoxicology research. To begin to characterize the teleost neuroproteome, we functionally annotated 623 unique proteins found in the fish hypothalamus and telencephalon. These proteins have roles in biological processes that include synaptic transmission, ATP production, receptor activity, cell structure and integrity, and stress responses. The biological processes most represented by proteins detected in the teleost neuroendocrine brain included transport (8.4%), metabolic process (5.5%), and glycolysis (4.8%). We provide an example of using sub-network enrichment analysis (SNEA) to identify protein networks in the fish hypothalamus in response to dopamine receptor signaling. Dopamine signaling altered the abundance of proteins that are binding partners of microfilaments, integrins, and intermediate filaments, consistent with data suggesting dopaminergic regulation of neuronal stability and structure. Lastly, for fish neuroendocrine studies using both high-throughput genomics and proteomics, we compare gene and protein relationships in the hypothalamus and demonstrate that correlation is often poor for single time point experiments. These studies highlight the need for additional time course analyses to better understand gene-protein relationships and adverse outcome pathways. This is important if both transcriptomics and proteomics are to be used together to investigate neuroendocrine signaling pathways or as bio-monitoring tools in ecotoxicology. Copyright © 2011 Elsevier Inc. All rights reserved.

Combined comparative and chemical proteomics on the mechanisms of levo-tetrahydropalmatine-induced antinociception in the formalin test.

PubMed

Wang, Chen; Zhou, Jiangrui; Wang, Shuowen; Ye, Mingliang; Jiang, Chunlei; Fan, Guorong; Zou, Hanfa

2010-06-04

This study investigated the mechanisms involved in the antinociceptive action induced by levo-tetrahydropalmatine (l-THP) in the formalin test by combined comparative and chemical proteomics. Rats were pretreated with l-THP by the oral route (40 mg/kg) 1 h before formalin injection. The antinociceptive effect of l-THP was shown in the first and second phases of the formalin test. To address the mechanisms by which l-THP inhibits formalin-induced nociception in rats, the combined comparative and chemical proteomics were applied. A novel high-throughput comparative proteomic approach based on 2D-nano-LC-MS/MS was applied to simultaneously evaluate the deregulated proteins involved in the response of l-THP treatment in formalin-induced pain rats. Thousands of proteins were identified, among which 17 proteins survived the stringent filter criteria and were further included for functional discussion. Two proteins (Neurabin-1 and Calcium-dependent secretion activator 1) were randomly selected, and their expression levels were further confirmed by Western Blots. The results matched well with those of proteomics. In the present study, we also described the development and application of l-THP immobilized beads to bind the targets. Following incubation with cellular lysates, the proteome interacting with the fixed l-THP was identified. The results of comparative and chemical proteomics were quite complementary. Although the precise roles of these identified moleculars in l-THP-induced antinociception need further study, the combined results indicated that proteins associated with signal transduction, vesicular trafficking and neurotransmitter release, energy metabolism, and ion transport play important roles in l-THP-induced antinociception in the formalin test.

Serum Proteome Analysis for Profiling Predictive Protein Markers Associated with the Severity of Skin Lesions Induced by Ionizing Radiation.

PubMed

Chaze, Thibault; Hornez, Louis; Chambon, Christophe; Haddad, Iman; Vinh, Joelle; Peyrat, Jean-Philippe; Benderitter, Marc; Guipaud, Olivier

2013-07-10

The finding of new diagnostic and prognostic markers of local radiation injury, and particularly of the cutaneous radiation syndrome, is crucial for its medical management, in the case of both accidental exposure and radiotherapy side effects. Especially, a fast high-throughput method is still needed for triage of people accidentally exposed to ionizing radiation. In this study, we investigated the impact of localized irradiation of the skin on the early alteration of the serum proteome of mice in an effort to discover markers associated with the exposure and severity of impending damage. Using two different large-scale quantitative proteomic approaches, 2D-DIGE-MS and SELDI-TOF-MS, we performed global analyses of serum proteins collected in the clinical latency phase (days 3 and 7) from non-irradiated and locally irradiated mice exposed to high doses of 20, 40 and 80 Gy which will develop respectively erythema, moist desquamation and necrosis. Unsupervised and supervised multivariate statistical analyses (principal component analysis, partial-least square discriminant analysis and Random Forest analysis) using 2D-DIGE quantitative protein data allowed us to discriminate early between non-irradiated and irradiated animals, and between uninjured/slightly injured animals and animals that will develop severe lesions. On the other hand, despite a high number of animal replicates, PLS-DA and Random Forest analyses of SELDI-TOF-MS data failed to reveal sets of MS peaks able to discriminate between the different groups of animals. Our results show that, unlike SELDI-TOF-MS, the 2D-DIGE approach remains a powerful and promising method for the discovery of sets of proteins that could be used for the development of clinical tests for triage and the prognosis of the severity of radiation-induced skin lesions. We propose a list of 15 proteins which constitutes a set of candidate proteins for triage and prognosis of skin lesion outcomes.

Serum Proteome Analysis for Profiling Predictive Protein Markers Associated with the Severity of Skin Lesions Induced by Ionizing Radiation

PubMed Central

Chaze, Thibault; Hornez, Louis; Chambon, Christophe; Haddad, Iman; Vinh, Joelle; Peyrat, Jean-Philippe; Benderitter, Marc; Guipaud, Olivier

2013-01-01

The finding of new diagnostic and prognostic markers of local radiation injury, and particularly of the cutaneous radiation syndrome, is crucial for its medical management, in the case of both accidental exposure and radiotherapy side effects. Especially, a fast high-throughput method is still needed for triage of people accidentally exposed to ionizing radiation. In this study, we investigated the impact of localized irradiation of the skin on the early alteration of the serum proteome of mice in an effort to discover markers associated with the exposure and severity of impending damage. Using two different large-scale quantitative proteomic approaches, 2D-DIGE-MS and SELDI-TOF-MS, we performed global analyses of serum proteins collected in the clinical latency phase (days 3 and 7) from non-irradiated and locally irradiated mice exposed to high doses of 20, 40 and 80 Gy which will develop respectively erythema, moist desquamation and necrosis. Unsupervised and supervised multivariate statistical analyses (principal component analysis, partial-least square discriminant analysis and Random Forest analysis) using 2D-DIGE quantitative protein data allowed us to discriminate early between non-irradiated and irradiated animals, and between uninjured/slightly injured animals and animals that will develop severe lesions. On the other hand, despite a high number of animal replicates, PLS-DA and Random Forest analyses of SELDI-TOF-MS data failed to reveal sets of MS peaks able to discriminate between the different groups of animals. Our results show that, unlike SELDI-TOF-MS, the 2D-DIGE approach remains a powerful and promising method for the discovery of sets of proteins that could be used for the development of clinical tests for triage and the prognosis of the severity of radiation-induced skin lesions. We propose a list of 15 proteins which constitutes a set of candidate proteins for triage and prognosis of skin lesion outcomes. PMID:28250398

Strain-resolved microbial community proteomics reveals simultaneous aerobic and anaerobic function during gastrointestinal tract colonization of a preterm infant

DOE PAGES

Brooks, Brandon; Mueller, R. S.; Young, Jacque C.; ...

2015-07-01

While there has been growing interest in the gut microbiome in recent years, it remains unclear whether closely related species and strains have similar or distinct functional roles and if organisms capable of both aerobic and anaerobic growth do so simultaneously. To investigate these questions, we implemented a high-throughput mass spectrometry-based proteomics approach to identify proteins in fecal samples collected on days of life 13 21 from an infant born at 28 weeks gestation. No prior studies have coupled strain-resolved community metagenomics to proteomics for such a purpose. Sequences were manually curated to resolve the genomes of two strains ofmore » Citrobacter that were present during the later stage of colonization. Proteome extracts from fecal samples were processed via a nano-2D-LC-MS/MS and peptides were identified based on information predicted from the genome sequences for the dominant organisms, Serratia and the two Citrobacter strains. These organisms are facultative anaerobes, and proteomic information indicates the utilization of both aerobic and anaerobic metabolisms throughout the time series. This may indicate growth in distinct niches within the gastrointestinal tract. We uncovered differences in the physiology of coexisting Citrobacter strains, including differences in motility and chemotaxis functions. Additionally, for both Citrobacter strains we resolved a community-essential role in vitamin metabolism and a predominant role in propionate production. Finally, in this case study we detected differences between genome abundance and activity levels for the dominant populations. This underlines the value in layering proteomic information over genetic potential.« less

Trends in mass spectrometry instrumentation for proteomics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, Richard D.

2002-12-01

Mass spectrometry has become a primary tool for proteomics due to its capabilities for rapid and sensitive protein identification and quantitation. It is now possible to identify thousands of proteins from microgram sample quantities in a single day and to quantify relative protein abundances. However, the needs for increased capabilities for proteome measurements are immense and are now driving both new strategies and instrument advances. These developments include those based on integration with multi-dimensional liquid separations and high accuracy mass measurements, and promise more than order of magnitude improvements in sensitivity, dynamic range, and throughput for proteomic analyses in themore » near future.« less

Mass spectrometry-based proteomics for translational research: a technical overview.

PubMed

Paulo, Joao A; Kadiyala, Vivek; Banks, Peter A; Steen, Hanno; Conwell, Darwin L

2012-03-01

Mass spectrometry-based investigation of clinical samples enables the high-throughput identification of protein biomarkers. We provide an overview of mass spectrometry-based proteomic techniques that are applicable to the investigation of clinical samples. We address sample collection, protein extraction and fractionation, mass spectrometry modalities, and quantitative proteomics. Finally, we examine the limitations and further potential of such technologies. Liquid chromatography fractionation coupled with tandem mass spectrometry is well suited to handle mixtures of hundreds or thousands of proteins. Mass spectrometry-based proteome elucidation can reveal potential biomarkers and aid in the development of hypotheses for downstream investigation of the molecular mechanisms of disease.

Advances in Proteomics Data Analysis and Display Using an Accurate Mass and Time Tag Approach

PubMed Central

Zimmer, Jennifer S.D.; Monroe, Matthew E.; Qian, Wei-Jun; Smith, Richard D.

2007-01-01

Proteomics has recently demonstrated utility in understanding cellular processes on the molecular level as a component of systems biology approaches and for identifying potential biomarkers of various disease states. The large amount of data generated by utilizing high efficiency (e.g., chromatographic) separations coupled to high mass accuracy mass spectrometry for high-throughput proteomics analyses presents challenges related to data processing, analysis, and display. This review focuses on recent advances in nanoLC-FTICR-MS-based proteomics approaches and the accompanying data processing tools that have been developed to display and interpret the large volumes of data being produced. PMID:16429408

Mass Spectrometry-Based Proteomics for Translational Research: A Technical Overview

PubMed Central

Paulo, Joao A.; Kadiyala, Vivek; Banks, Peter A.; Steen, Hanno; Conwell, Darwin L.

2012-01-01

Mass spectrometry-based investigation of clinical samples enables the high-throughput identification of protein biomarkers. We provide an overview of mass spectrometry-based proteomic techniques that are applicable to the investigation of clinical samples. We address sample collection, protein extraction and fractionation, mass spectrometry modalities, and quantitative proteomics. Finally, we examine the limitations and further potential of such technologies. Liquid chromatography fractionation coupled with tandem mass spectrometry is well suited to handle mixtures of hundreds or thousands of proteins. Mass spectrometry-based proteome elucidation can reveal potential biomarkers and aid in the development of hypotheses for downstream investigation of the molecular mechanisms of disease. PMID:22461744

Proteome data to explore the impact of pBClin15 on Bacillus cereus ATCC 14579.

PubMed

Madeira, Jean-Paul; Alpha-Bazin, Béatrice; Armengaud, Jean; Omer, Hélène; Duport, Catherine

2016-09-01

This data article reports changes in the cellular and exoproteome of B. cereus cured from pBClin15.Time-course changes of proteins were assessed by high-throughput nanoLC-MS/MS. We report all the peptides and proteins identified and quantified in B. cereus with and without pBClin15. Proteins were classified into functional groups using the information available in the KEGG classification and we reported their abundance in term of normalized spectral abundance factor. The repertoire of experimentally confirmed proteins of B. cereus presented here is the largest ever reported, and provides new insights into the interplay between pBClin15 and its host B. cereus ATCC 14579. The data reported here is related to a published shotgun proteomics analysis regarding the role of pBClin15, "Deciphering the interactions between the Bacillus cereus linear plasmid, pBClin15, and its host by high-throughput comparative proteomics" Madeira et al. [1]. All the associated mass spectrometry data have been deposited in the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) via the PRIDE partner repository (http://www.ebi.ac.uk/pride/), with the dataset identifier PRIDE: PXD001568, PRIDE: PXD002788 and PRIDE: PXD002789.

Comparative Testis Tissue Proteomics Using 2-Dye Versus 3-Dye DIGE Analysis.

PubMed

Holland, Ashling

2018-01-01

Comparative tissue proteomics aims to analyze alterations of the proteome in response to a stimulus. Two-dimensional difference gel electrophoresis (2D-DIGE) is a modified and advanced form of 2D gel electrophoresis. DIGE is a powerful biochemical method that compares two or three protein samples on the same analytical gel, and can be used to establish differentially expressed protein levels between healthy normal and diseased pathological tissue sample groups. Minimal DIGE labeling can be used via a 2-dye system with Cy3 and Cy5 or a 3-dye system with Cy2, Cy3, and Cy5 to fluorescently label samples with CyDye flours pre-electrophoresis. DIGE circumvents gel-to-gel variability by multiplexing samples to a single gel and through the use of a pooled internal standard for normalization. This form of quantitative high-resolution proteomics facilitates the comparative analysis and evaluation of tissue protein compositions. Comparing tissue groups under different conditions is crucially important for advancing the biomedical field by characterization of cellular processes, understanding pathophysiological development and tissue biomarker discovery. This chapter discusses 2D-DIGE as a comparative tissue proteomic technique and describes in detail the experimental steps required for comparative proteomic analysis employing both options of 2-dye and 3-dye DIGE minimal labeling.

Methods, Tools and Current Perspectives in Proteogenomics *

PubMed Central

Ruggles, Kelly V.; Krug, Karsten; Wang, Xiaojing; Clauser, Karl R.; Wang, Jing; Payne, Samuel H.; Fenyö, David; Zhang, Bing; Mani, D. R.

2017-01-01

With combined technological advancements in high-throughput next-generation sequencing and deep mass spectrometry-based proteomics, proteogenomics, i.e. the integrative analysis of proteomic and genomic data, has emerged as a new research field. Early efforts in the field were focused on improving protein identification using sample-specific genomic and transcriptomic sequencing data. More recently, integrative analysis of quantitative measurements from genomic and proteomic studies have identified novel insights into gene expression regulation, cell signaling, and disease. Many methods and tools have been developed or adapted to enable an array of integrative proteogenomic approaches and in this article, we systematically classify published methods and tools into four major categories, (1) Sequence-centric proteogenomics; (2) Analysis of proteogenomic relationships; (3) Integrative modeling of proteogenomic data; and (4) Data sharing and visualization. We provide a comprehensive review of methods and available tools in each category and highlight their typical applications. PMID:28456751

Quantitative, multiplexed workflow for deep analysis of human blood plasma and biomarker discovery by mass spectrometry.

PubMed

Keshishian, Hasmik; Burgess, Michael W; Specht, Harrison; Wallace, Luke; Clauser, Karl R; Gillette, Michael A; Carr, Steven A

2017-08-01

Proteomic characterization of blood plasma is of central importance to clinical proteomics and particularly to biomarker discovery studies. The vast dynamic range and high complexity of the plasma proteome have, however, proven to be serious challenges and have often led to unacceptable tradeoffs between depth of coverage and sample throughput. We present an optimized sample-processing pipeline for analysis of the human plasma proteome that provides greatly increased depth of detection, improved quantitative precision and much higher sample analysis throughput as compared with prior methods. The process includes abundant protein depletion, isobaric labeling at the peptide level for multiplexed relative quantification and ultra-high-performance liquid chromatography coupled to accurate-mass, high-resolution tandem mass spectrometry analysis of peptides fractionated off-line by basic pH reversed-phase (bRP) chromatography. The overall reproducibility of the process, including immunoaffinity depletion, is high, with a process replicate coefficient of variation (CV) of <12%. Using isobaric tags for relative and absolute quantitation (iTRAQ) 4-plex, >4,500 proteins are detected and quantified per patient sample on average, with two or more peptides per protein and starting from as little as 200 μl of plasma. The approach can be multiplexed up to 10-plex using tandem mass tags (TMT) reagents, further increasing throughput, albeit with some decrease in the number of proteins quantified. In addition, we provide a rapid protocol for analysis of nonfractionated depleted plasma samples analyzed in 10-plex. This provides ∼600 quantified proteins for each of the ten samples in ∼5 h of instrument time.

Assessment of SRM, MRM(3) , and DIA for the targeted analysis of phosphorylation dynamics in non-small cell lung cancer.

PubMed

Schmidlin, Thierry; Garrigues, Luc; Lane, Catherine S; Mulder, T Celine; van Doorn, Sander; Post, Harm; de Graaf, Erik L; Lemeer, Simone; Heck, Albert J R; Altelaar, A F Maarten

2016-08-01

Hypothesis-driven MS-based targeted proteomics has gained great popularity in a relatively short timespan. Next to the widely established selected reaction monitoring (SRM) workflow, data-independent acquisition (DIA), also referred to as sequential window acquisition of all theoretical spectra (SWATH) was introduced as a high-throughput targeted proteomics method. DIA facilitates increased proteome coverage, however, does not yet reach the sensitivity obtained with SRM. Therefore, a well-informed method selection is crucial for designing a successful targeted proteomics experiment. This is especially the case when targeting less conventional peptides such as those that contain PTMs, as these peptides do not always adhere to the optimal fragmentation considerations for targeted assays. Here, we provide insight into the performance of DIA, SRM, and MRM cubed (MRM(3) ) in the analysis of phosphorylation dynamics throughout the phosphoinositide 3-kinase mechanistic target of rapamycin (PI3K-mTOR) and mitogen-activated protein kinase (MAPK) signaling network. We observe indeed that DIA is less sensitive when compared to SRM, however demonstrates increased flexibility, by postanalysis selection of alternative phosphopeptide precursors. Additionally, we demonstrate the added benefit of MRM(3) , allowing the quantification of two poorly accessible phosphosites. In total, targeted proteomics enabled the quantification of 42 PI3K-mTOR and MAPK phosphosites, gaining a so far unachieved in-depth view mTOR signaling events linked to tyrosine kinase inhibitor resistance in non-small cell lung cancer. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Studies of a biochemical factory: tomato trichome deep expressed sequence tag sequencing and proteomics.

PubMed

Schilmiller, Anthony L; Miner, Dennis P; Larson, Matthew; McDowell, Eric; Gang, David R; Wilkerson, Curtis; Last, Robert L

2010-07-01

Shotgun proteomics analysis allows hundreds of proteins to be identified and quantified from a single sample at relatively low cost. Extensive DNA sequence information is a prerequisite for shotgun proteomics, and it is ideal to have sequence for the organism being studied rather than from related species or accessions. While this requirement has limited the set of organisms that are candidates for this approach, next generation sequencing technologies make it feasible to obtain deep DNA sequence coverage from any organism. As part of our studies of specialized (secondary) metabolism in tomato (Solanum lycopersicum) trichomes, 454 sequencing of cDNA was combined with shotgun proteomics analyses to obtain in-depth profiles of genes and proteins expressed in leaf and stem glandular trichomes of 3-week-old plants. The expressed sequence tag and proteomics data sets combined with metabolite analysis led to the discovery and characterization of a sesquiterpene synthase that produces beta-caryophyllene and alpha-humulene from E,E-farnesyl diphosphate in trichomes of leaf but not of stem. This analysis demonstrates the utility of combining high-throughput cDNA sequencing with proteomics experiments in a target tissue. These data can be used for dissection of other biochemical processes in these specialized epidermal cells.

Studies of a Biochemical Factory: Tomato Trichome Deep Expressed Sequence Tag Sequencing and Proteomics1[W][OA

PubMed Central

Schilmiller, Anthony L.; Miner, Dennis P.; Larson, Matthew; McDowell, Eric; Gang, David R.; Wilkerson, Curtis; Last, Robert L.

2010-01-01

Shotgun proteomics analysis allows hundreds of proteins to be identified and quantified from a single sample at relatively low cost. Extensive DNA sequence information is a prerequisite for shotgun proteomics, and it is ideal to have sequence for the organism being studied rather than from related species or accessions. While this requirement has limited the set of organisms that are candidates for this approach, next generation sequencing technologies make it feasible to obtain deep DNA sequence coverage from any organism. As part of our studies of specialized (secondary) metabolism in tomato (Solanum lycopersicum) trichomes, 454 sequencing of cDNA was combined with shotgun proteomics analyses to obtain in-depth profiles of genes and proteins expressed in leaf and stem glandular trichomes of 3-week-old plants. The expressed sequence tag and proteomics data sets combined with metabolite analysis led to the discovery and characterization of a sesquiterpene synthase that produces β-caryophyllene and α-humulene from E,E-farnesyl diphosphate in trichomes of leaf but not of stem. This analysis demonstrates the utility of combining high-throughput cDNA sequencing with proteomics experiments in a target tissue. These data can be used for dissection of other biochemical processes in these specialized epidermal cells. PMID:20431087

Learning from Heterogeneous Data Sources: An Application in Spatial Proteomics

PubMed Central

Breckels, Lisa M.; Holden, Sean B.; Wojnar, David; Mulvey, Claire M.; Christoforou, Andy; Groen, Arnoud; Trotter, Matthew W. B.; Kohlbacher, Oliver; Lilley, Kathryn S.; Gatto, Laurent

2016-01-01

Sub-cellular localisation of proteins is an essential post-translational regulatory mechanism that can be assayed using high-throughput mass spectrometry (MS). These MS-based spatial proteomics experiments enable us to pinpoint the sub-cellular distribution of thousands of proteins in a specific system under controlled conditions. Recent advances in high-throughput MS methods have yielded a plethora of experimental spatial proteomics data for the cell biology community. Yet, there are many third-party data sources, such as immunofluorescence microscopy or protein annotations and sequences, which represent a rich and vast source of complementary information. We present a unique transfer learning classification framework that utilises a nearest-neighbour or support vector machine system, to integrate heterogeneous data sources to considerably improve on the quantity and quality of sub-cellular protein assignment. We demonstrate the utility of our algorithms through evaluation of five experimental datasets, from four different species in conjunction with four different auxiliary data sources to classify proteins to tens of sub-cellular compartments with high generalisation accuracy. We further apply the method to an experiment on pluripotent mouse embryonic stem cells to classify a set of previously unknown proteins, and validate our findings against a recent high resolution map of the mouse stem cell proteome. The methodology is distributed as part of the open-source Bioconductor pRoloc suite for spatial proteomics data analysis. PMID:27175778

Assembling proteomics data as a prerequisite for the analysis of large scale experiments

PubMed Central

Schmidt, Frank; Schmid, Monika; Thiede, Bernd; Pleißner, Klaus-Peter; Böhme, Martina; Jungblut, Peter R

2009-01-01

Background Despite the complete determination of the genome sequence of a huge number of bacteria, their proteomes remain relatively poorly defined. Beside new methods to increase the number of identified proteins new database applications are necessary to store and present results of large- scale proteomics experiments. Results In the present study, a database concept has been developed to address these issues and to offer complete information via a web interface. In our concept, the Oracle based data repository system SQL-LIMS plays the central role in the proteomics workflow and was applied to the proteomes of Mycobacterium tuberculosis, Helicobacter pylori, Salmonella typhimurium and protein complexes such as 20S proteasome. Technical operations of our proteomics labs were used as the standard for SQL-LIMS template creation. By means of a Java based data parser, post-processed data of different approaches, such as LC/ESI-MS, MALDI-MS and 2-D gel electrophoresis (2-DE), were stored in SQL-LIMS. A minimum set of the proteomics data were transferred in our public 2D-PAGE database using a Java based interface (Data Transfer Tool) with the requirements of the PEDRo standardization. Furthermore, the stored proteomics data were extractable out of SQL-LIMS via XML. Conclusion The Oracle based data repository system SQL-LIMS played the central role in the proteomics workflow concept. Technical operations of our proteomics labs were used as standards for SQL-LIMS templates. Using a Java based parser, post-processed data of different approaches such as LC/ESI-MS, MALDI-MS and 1-DE and 2-DE were stored in SQL-LIMS. Thus, unique data formats of different instruments were unified and stored in SQL-LIMS tables. Moreover, a unique submission identifier allowed fast access to all experimental data. This was the main advantage compared to multi software solutions, especially if personnel fluctuations are high. Moreover, large scale and high-throughput experiments must be managed in a comprehensive repository system such as SQL-LIMS, to query results in a systematic manner. On the other hand, these database systems are expensive and require at least one full time administrator and specialized lab manager. Moreover, the high technical dynamics in proteomics may cause problems to adjust new data formats. To summarize, SQL-LIMS met the requirements of proteomics data handling especially in skilled processes such as gel-electrophoresis or mass spectrometry and fulfilled the PSI standardization criteria. The data transfer into a public domain via DTT facilitated validation of proteomics data. Additionally, evaluation of mass spectra by post-processing using MS-Screener improved the reliability of mass analysis and prevented storage of data junk. PMID:19166578

High-Throughput Cancer Cell Sphere Formation for 3D Cell Culture.

PubMed

Chen, Yu-Chih; Yoon, Euisik

2017-01-01

Three-dimensional (3D) cell culture is critical in studying cancer pathology and drug response. Though 3D cancer sphere culture can be performed in low-adherent dishes or well plates, the unregulated cell aggregation may skew the results. On contrary, microfluidic 3D culture can allow precise control of cell microenvironments, and provide higher throughput by orders of magnitude. In this chapter, we will look into engineering innovations in a microfluidic platform for high-throughput cancer cell sphere formation and review the implementation methods in detail.

Remodeling Cildb, a popular database for cilia and links for ciliopathies

PubMed Central

2014-01-01

Background New generation technologies in cell and molecular biology generate large amounts of data hard to exploit for individual proteins. This is particularly true for ciliary and centrosomal research. Cildb is a multi–species knowledgebase gathering high throughput studies, which allows advanced searches to identify proteins involved in centrosome, basal body or cilia biogenesis, composition and function. Combined to localization of genetic diseases on human chromosomes given by OMIM links, candidate ciliopathy proteins can be compiled through Cildb searches. Methods Othology between recent versions of the whole proteomes was computed using Inparanoid and ciliary high throughput studies were remapped on these recent versions. Results Due to constant evolution of the ciliary and centrosomal field, Cildb has been recently upgraded twice, with new species whole proteomes and new ciliary studies, and the latter version displays a novel BioMart interface, much more intuitive than the previous ones. Conclusions This already popular database is designed now for easier use and is up to date in regard to high throughput ciliary studies. PMID:25422781

iAB-RBC-283: A proteomically derived knowledge-base of erythrocyte metabolism that can be used to simulate its physiological and patho-physiological states.

PubMed

Bordbar, Aarash; Jamshidi, Neema; Palsson, Bernhard O

2011-07-12

The development of high-throughput technologies capable of whole cell measurements of genes, proteins, and metabolites has led to the emergence of systems biology. Integrated analysis of the resulting omic data sets has proved to be hard to achieve. Metabolic network reconstructions enable complex relationships amongst molecular components to be represented formally in a biologically relevant manner while respecting physical constraints. In silico models derived from such reconstructions can then be queried or interrogated through mathematical simulations. Proteomic profiling studies of the mature human erythrocyte have shown more proteins present related to metabolic function than previously thought; however the significance and the causal consequences of these findings have not been explored. Erythrocyte proteomic data was used to reconstruct the most expansive description of erythrocyte metabolism to date, following extensive manual curation, assessment of the literature, and functional testing. The reconstruction contains 281 enzymes representing functions from glycolysis to cofactor and amino acid metabolism. Such a comprehensive view of erythrocyte metabolism implicates the erythrocyte as a potential biomarker for different diseases as well as a 'cell-based' drug-screening tool. The analysis shows that 94 erythrocyte enzymes are implicated in morbid single nucleotide polymorphisms, representing 142 pathologies. In addition, over 230 FDA-approved and experimental pharmaceuticals have enzymatic targets in the erythrocyte. The advancement of proteomic technologies and increased generation of high-throughput proteomic data have created the need for a means to analyze these data in a coherent manner. Network reconstructions provide a systematic means to integrate and analyze proteomic data in a biologically meaning manner. Analysis of the red cell proteome has revealed an unexpected level of complexity in the functional capabilities of human erythrocyte metabolism.

High-throughput screening with nanoimprinting 3D culture for efficient drug development by mimicking the tumor environment.

PubMed

Yoshii, Yukie; Furukawa, Takako; Waki, Atsuo; Okuyama, Hiroaki; Inoue, Masahiro; Itoh, Manabu; Zhang, Ming-Rong; Wakizaka, Hidekatsu; Sogawa, Chizuru; Kiyono, Yasushi; Yoshii, Hiroshi; Fujibayashi, Yasuhisa; Saga, Tsuneo

2015-05-01

Anti-cancer drug development typically utilizes high-throughput screening with two-dimensional (2D) cell culture. However, 2D culture induces cellular characteristics different from tumors in vivo, resulting in inefficient drug development. Here, we report an innovative high-throughput screening system using nanoimprinting 3D culture to simulate in vivo conditions, thereby facilitating efficient drug development. We demonstrated that cell line-based nanoimprinting 3D screening can more efficiently select drugs that effectively inhibit cancer growth in vivo as compared to 2D culture. Metabolic responses after treatment were assessed using positron emission tomography (PET) probes, and revealed similar characteristics between the 3D spheroids and in vivo tumors. Further, we developed an advanced method to adopt cancer cells from patient tumor tissues for high-throughput drug screening with nanoimprinting 3D culture, which we termed Cancer tissue-Originated Uniformed Spheroid Assay (COUSA). This system identified drugs that were effective in xenografts of the original patient tumors. Nanoimprinting 3D spheroids showed low permeability and formation of hypoxic regions inside, similar to in vivo tumors. Collectively, the nanoimprinting 3D culture provides easy-handling high-throughput drug screening system, which allows for efficient drug development by mimicking the tumor environment. The COUSA system could be a useful platform for drug development with patient cancer cells. Copyright © 2015 Elsevier Ltd. All rights reserved.

FunRich proteomics software analysis, let the fun begin!

PubMed

Benito-Martin, Alberto; Peinado, Héctor

2015-08-01

Protein MS analysis is the preferred method for unbiased protein identification. It is normally applied to a large number of both small-scale and high-throughput studies. However, user-friendly computational tools for protein analysis are still needed. In this issue, Mathivanan and colleagues (Proteomics 2015, 15, 2597-2601) report the development of FunRich software, an open-access software that facilitates the analysis of proteomics data, providing tools for functional enrichment and interaction network analysis of genes and proteins. FunRich is a reinterpretation of proteomic software, a standalone tool combining ease of use with customizable databases, free access, and graphical representations. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Image analysis tools and emerging algorithms for expression proteomics

PubMed Central

English, Jane A.; Lisacek, Frederique; Morris, Jeffrey S.; Yang, Guang-Zhong; Dunn, Michael J.

2012-01-01

Since their origins in academic endeavours in the 1970s, computational analysis tools have matured into a number of established commercial packages that underpin research in expression proteomics. In this paper we describe the image analysis pipeline for the established 2-D Gel Electrophoresis (2-DE) technique of protein separation, and by first covering signal analysis for Mass Spectrometry (MS), we also explain the current image analysis workflow for the emerging high-throughput ‘shotgun’ proteomics platform of Liquid Chromatography coupled to MS (LC/MS). The bioinformatics challenges for both methods are illustrated and compared, whilst existing commercial and academic packages and their workflows are described from both a user’s and a technical perspective. Attention is given to the importance of sound statistical treatment of the resultant quantifications in the search for differential expression. Despite wide availability of proteomics software, a number of challenges have yet to be overcome regarding algorithm accuracy, objectivity and automation, generally due to deterministic spot-centric approaches that discard information early in the pipeline, propagating errors. We review recent advances in signal and image analysis algorithms in 2-DE, MS, LC/MS and Imaging MS. Particular attention is given to wavelet techniques, automated image-based alignment and differential analysis in 2-DE, Bayesian peak mixture models and functional mixed modelling in MS, and group-wise consensus alignment methods for LC/MS. PMID:21046614

Proteome Studies of Filamentous Fungi

DOE Office of Scientific and Technical Information (OSTI.GOV)

Baker, Scott E.; Panisko, Ellen A.

2011-04-20

The continued fast pace of fungal genome sequence generation has enabled proteomic analysis of a wide breadth of organisms that span the breadth of the Kingdom Fungi. There is some phylogenetic bias to the current catalog of fungi with reasonable DNA sequence databases (genomic or EST) that could be analyzed at a global proteomic level. However, the rapid development of next generation sequencing platforms has lowered the cost of genome sequencing such that in the near future, having a genome sequence will no longer be a time or cost bottleneck for downstream proteomic (and transcriptomic) analyses. High throughput, non-gel basedmore » proteomics offers a snapshot of proteins present in a given sample at a single point in time. There are a number of different variations on the general method and technologies for identifying peptides in a given sample. We present a method that can serve as a “baseline” for proteomic studies of fungi.« less

Recent 5-year Findings and Technological Advances in the Proteomic Study of HIV-associated Disorders.

PubMed

Zhang, Lijun; Jia, Xiaofang; Jin, Jun-O; Lu, Hongzhou; Tan, Zhimi

2017-04-01

Human immunodeficiency virus-1 (HIV-1) mainly relies on host factors to complete its life cycle. Hence, it is very important to identify HIV-regulated host proteins. Proteomics is an excellent technique for this purpose because of its high throughput and sensitivity. In this review, we summarized current technological advances in proteomics, including general isobaric tags for relative and absolute quantitation (iTRAQ) and stable isotope labeling by amino acids in cell culture (SILAC), as well as subcellular proteomics and investigation of posttranslational modifications. Furthermore, we reviewed the applications of proteomics in the discovery of HIV-related diseases and HIV infection mechanisms. Proteins identified by proteomic studies might offer new avenues for the diagnosis and treatment of HIV infection and the related diseases. Copyright © 2017 The Authors. Production and hosting by Elsevier B.V. All rights reserved.

Systems Proteomics for Translational Network Medicine

PubMed Central

Arrell, D. Kent; Terzic, Andre

2012-01-01

Universal principles underlying network science, and their ever-increasing applications in biomedicine, underscore the unprecedented capacity of systems biology based strategies to synthesize and resolve massive high throughput generated datasets. Enabling previously unattainable comprehension of biological complexity, systems approaches have accelerated progress in elucidating disease prediction, progression, and outcome. Applied to the spectrum of states spanning health and disease, network proteomics establishes a collation, integration, and prioritization algorithm to guide mapping and decoding of proteome landscapes from large-scale raw data. Providing unparalleled deconvolution of protein lists into global interactomes, integrative systems proteomics enables objective, multi-modal interpretation at molecular, pathway, and network scales, merging individual molecular components, their plurality of interactions, and functional contributions for systems comprehension. As such, network systems approaches are increasingly exploited for objective interpretation of cardiovascular proteomics studies. Here, we highlight network systems proteomic analysis pipelines for integration and biological interpretation through protein cartography, ontological categorization, pathway and functional enrichment and complex network analysis. PMID:22896016

Clinical proteomics-driven precision medicine for targeted cancer therapy: current overview and future perspectives.

PubMed

Zhou, Li; Wang, Kui; Li, Qifu; Nice, Edouard C; Zhang, Haiyuan; Huang, Canhua

2016-01-01

Cancer is a common disease that is a leading cause of death worldwide. Currently, early detection and novel therapeutic strategies are urgently needed for more effective management of cancer. Importantly, protein profiling using clinical proteomic strategies, with spectacular sensitivity and precision, offer excellent promise for the identification of potential biomarkers that would direct the development of targeted therapeutic anticancer drugs for precision medicine. In particular, clinical sample sources, including tumor tissues and body fluids (blood, feces, urine and saliva), have been widely investigated using modern high-throughput mass spectrometry-based proteomic approaches combined with bioinformatic analysis, to pursue the possibilities of precision medicine for targeted cancer therapy. Discussed in this review are the current advantages and limitations of clinical proteomics, the available strategies of clinical proteomics for the management of precision medicine, as well as the challenges and future perspectives of clinical proteomics-driven precision medicine for targeted cancer therapy.

Proteome studies of filamentous fungi.

PubMed

Baker, Scott E; Panisko, Ellen A

2011-01-01

The continued fast pace of fungal genome sequence generation has enabled proteomic analysis of a wide variety of organisms that span the breadth of the Kingdom Fungi. There is some phylogenetic bias to the current catalog of fungi with reasonable DNA sequence databases (genomic or EST) that could be analyzed at a global proteomic level. However, the rapid development of next generation sequencing platforms has lowered the cost of genome sequencing such that in the near future, having a genome sequence will no longer be a time or cost bottleneck for downstream proteomic (and transcriptomic) analyses. High throughput, nongel-based proteomics offers a snapshot of proteins present in a given sample at a single point in time. There are a number of variations on the general methods and technologies for identifying peptides in a given sample. We present a method that can serve as a "baseline" for proteomic studies of fungi.

PeptideDepot: flexible relational database for visual analysis of quantitative proteomic data and integration of existing protein information.

PubMed

Yu, Kebing; Salomon, Arthur R

2009-12-01

Recently, dramatic progress has been achieved in expanding the sensitivity, resolution, mass accuracy, and scan rate of mass spectrometers able to fragment and identify peptides through MS/MS. Unfortunately, this enhanced ability to acquire proteomic data has not been accompanied by a concomitant increase in the availability of flexible tools allowing users to rapidly assimilate, explore, and analyze this data and adapt to various experimental workflows with minimal user intervention. Here we fill this critical gap by providing a flexible relational database called PeptideDepot for organization of expansive proteomic data sets, collation of proteomic data with available protein information resources, and visual comparison of multiple quantitative proteomic experiments. Our software design, built upon the synergistic combination of a MySQL database for safe warehousing of proteomic data with a FileMaker-driven graphical user interface for flexible adaptation to diverse workflows, enables proteomic end-users to directly tailor the presentation of proteomic data to the unique analysis requirements of the individual proteomics lab. PeptideDepot may be deployed as an independent software tool or integrated directly with our high throughput autonomous proteomic pipeline used in the automated acquisition and post-acquisition analysis of proteomic data.

pGlyco 2.0 enables precision N-glycoproteomics with comprehensive quality control and one-step mass spectrometry for intact glycopeptide identification.

PubMed

Liu, Ming-Qi; Zeng, Wen-Feng; Fang, Pan; Cao, Wei-Qian; Liu, Chao; Yan, Guo-Quan; Zhang, Yang; Peng, Chao; Wu, Jian-Qiang; Zhang, Xiao-Jin; Tu, Hui-Jun; Chi, Hao; Sun, Rui-Xiang; Cao, Yong; Dong, Meng-Qiu; Jiang, Bi-Yun; Huang, Jiang-Ming; Shen, Hua-Li; Wong, Catherine C L; He, Si-Min; Yang, Peng-Yuan

2017-09-05

The precise and large-scale identification of intact glycopeptides is a critical step in glycoproteomics. Owing to the complexity of glycosylation, the current overall throughput, data quality and accessibility of intact glycopeptide identification lack behind those in routine proteomic analyses. Here, we propose a workflow for the precise high-throughput identification of intact N-glycopeptides at the proteome scale using stepped-energy fragmentation and a dedicated search engine. pGlyco 2.0 conducts comprehensive quality control including false discovery rate evaluation at all three levels of matches to glycans, peptides and glycopeptides, improving the current level of accuracy of intact glycopeptide identification. The N-glycoproteome of samples metabolically labeled with 15 N/ 13 C were analyzed quantitatively and utilized to validate the glycopeptide identification, which could be used as a novel benchmark pipeline to compare different search engines. Finally, we report a large-scale glycoproteome dataset consisting of 10,009 distinct site-specific N-glycans on 1988 glycosylation sites from 955 glycoproteins in five mouse tissues.Protein glycosylation is a heterogeneous post-translational modification that generates greater proteomic diversity that is difficult to analyze. Here the authors describe pGlyco 2.0, a workflow for the precise one step identification of intact N-glycopeptides at the proteome scale.

G23D: Online tool for mapping and visualization of genomic variants on 3D protein structures.

PubMed

Solomon, Oz; Kunik, Vered; Simon, Amos; Kol, Nitzan; Barel, Ortal; Lev, Atar; Amariglio, Ninette; Somech, Raz; Rechavi, Gidi; Eyal, Eran

2016-08-26

Evaluation of the possible implications of genomic variants is an increasingly important task in the current high throughput sequencing era. Structural information however is still not routinely exploited during this evaluation process. The main reasons can be attributed to the partial structural coverage of the human proteome and the lack of tools which conveniently convert genomic positions, which are the frequent output of genomic pipelines, to proteins and structure coordinates. We present G23D, a tool for conversion of human genomic coordinates to protein coordinates and protein structures. G23D allows mapping of genomic positions/variants on evolutionary related (and not only identical) protein three dimensional (3D) structures as well as on theoretical models. By doing so it significantly extends the space of variants for which structural insight is feasible. To facilitate interpretation of the variant consequence, pathogenic variants, functional sites and polymorphism sites are displayed on protein sequence and structure diagrams alongside the input variants. G23D also provides modeling of the mutant structure, analysis of intra-protein contacts and instant access to functional predictions and predictions of thermo-stability changes. G23D is available at http://www.sheba-cancer.org.il/G23D . G23D extends the fraction of variants for which structural analysis is applicable and provides better and faster accessibility for structural data to biologists and geneticists who routinely work with genomic information.

Overview of proteomics studies in obstructive sleep apnea

PubMed Central

Feliciano, Amélia; Torres, Vukosava Milic; Vaz, Fátima; Carvalho, Ana Sofia; Matthiesen, Rune; Pinto, Paula; Malhotra, Atul; Bárbara, Cristina; Penque, Deborah

2015-01-01

Obstructive sleep apnea (OSA) is an underdiagnosed common public health concern causing deleterious effects on metabolic and cardiovascular health. Although much has been learned regarding the pathophysiology and consequences of OSA in the past decades, the molecular mechanisms associated with such processes remain poorly defined. The advanced high-throughput proteomics-based technologies have become a fundamental approach for identifying novel disease mediators as potential diagnostic and therapeutic targets for many diseases, including OSA. Here, we briefly review OSA pathophysiology and the technological advances in proteomics and the first results of its application to address critical issues in the OSA field. PMID:25770042

High-coverage quantitative proteomics using amine-specific isotopic labeling.

PubMed

Melanson, Jeremy E; Avery, Steven L; Pinto, Devanand M

2006-08-01

Peptide dimethylation with isotopically coded formaldehydes was evaluated as a potential alternative to techniques such as the iTRAQ method for comparative proteomics. The isotopic labeling strategy and custom-designed protein quantitation software were tested using protein standards and then applied to measure proteins levels associated with Alzheimer's disease (AD). The method provided high accuracy (10% error), precision (14% RSD) and coverage (70%) when applied to the analysis of a standard solution of BSA by LC-MS/MS. The technique was then applied to measure protein abundance levels in brain tissue afflicted with AD relative to normal brain tissue. 2-D LC-MS analysis identified 548 unique proteins (p<0.05). Of these, 349 were quantified with two or more peptides that met the statistical criteria used in this study. Several classes of proteins exhibited significant changes in abundance. For example, elevated levels of antioxidant proteins and decreased levels of mitochondrial electron transport proteins were observed. The results demonstrate the utility of the labeling method for high-throughput quantitative analysis.

DOGMA: domain-based transcriptome and proteome quality assessment.

PubMed

Dohmen, Elias; Kremer, Lukas P M; Bornberg-Bauer, Erich; Kemena, Carsten

2016-09-01

Genome studies have become cheaper and easier than ever before, due to the decreased costs of high-throughput sequencing and the free availability of analysis software. However, the quality of genome or transcriptome assemblies can vary a lot. Therefore, quality assessment of assemblies and annotations are crucial aspects of genome analysis pipelines. We developed DOGMA, a program for fast and easy quality assessment of transcriptome and proteome data based on conserved protein domains. DOGMA measures the completeness of a given transcriptome or proteome and provides information about domain content for further analysis. DOGMA provides a very fast way to do quality assessment within seconds. DOGMA is implemented in Python and published under GNU GPL v.3 license. The source code is available on https://ebbgit.uni-muenster.de/domainWorld/DOGMA/ CONTACTS: e.dohmen@wwu.de or c.kemena@wwu.de Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Nucleic Acids for Ultra-Sensitive Protein Detection

PubMed Central

Janssen, Kris P. F.; Knez, Karel; Spasic, Dragana; Lammertyn, Jeroen

2013-01-01

Major advancements in molecular biology and clinical diagnostics cannot be brought about strictly through the use of genomics based methods. Improved methods for protein detection and proteomic screening are an absolute necessity to complement to wealth of information offered by novel, high-throughput sequencing technologies. Only then will it be possible to advance insights into clinical processes and to characterize the importance of specific protein biomarkers for disease detection or the realization of “personalized medicine”. Currently however, large-scale proteomic information is still not as easily obtained as its genomic counterpart, mainly because traditional antibody-based technologies struggle to meet the stringent sensitivity and throughput requirements that are required whereas mass-spectrometry based methods might be burdened by significant costs involved. However, recent years have seen the development of new biodetection strategies linking nucleic acids with existing antibody technology or replacing antibodies with oligonucleotide recognition elements altogether. These advancements have unlocked many new strategies to lower detection limits and dramatically increase throughput of protein detection assays. In this review, an overview of these new strategies will be given. PMID:23337338

PeptideDepot: Flexible Relational Database for Visual Analysis of Quantitative Proteomic Data and Integration of Existing Protein Information

PubMed Central

Yu, Kebing; Salomon, Arthur R.

2010-01-01

Recently, dramatic progress has been achieved in expanding the sensitivity, resolution, mass accuracy, and scan rate of mass spectrometers able to fragment and identify peptides through tandem mass spectrometry (MS/MS). Unfortunately, this enhanced ability to acquire proteomic data has not been accompanied by a concomitant increase in the availability of flexible tools allowing users to rapidly assimilate, explore, and analyze this data and adapt to a variety of experimental workflows with minimal user intervention. Here we fill this critical gap by providing a flexible relational database called PeptideDepot for organization of expansive proteomic data sets, collation of proteomic data with available protein information resources, and visual comparison of multiple quantitative proteomic experiments. Our software design, built upon the synergistic combination of a MySQL database for safe warehousing of proteomic data with a FileMaker-driven graphical user interface for flexible adaptation to diverse workflows, enables proteomic end-users to directly tailor the presentation of proteomic data to the unique analysis requirements of the individual proteomics lab. PeptideDepot may be deployed as an independent software tool or integrated directly with our High Throughput Autonomous Proteomic Pipeline (HTAPP) used in the automated acquisition and post-acquisition analysis of proteomic data. PMID:19834895

PACOM: A Versatile Tool for Integrating, Filtering, Visualizing, and Comparing Multiple Large Mass Spectrometry Proteomics Data Sets.

PubMed

Martínez-Bartolomé, Salvador; Medina-Aunon, J Alberto; López-García, Miguel Ángel; González-Tejedo, Carmen; Prieto, Gorka; Navajas, Rosana; Salazar-Donate, Emilio; Fernández-Costa, Carolina; Yates, John R; Albar, Juan Pablo

2018-04-06

Mass-spectrometry-based proteomics has evolved into a high-throughput technology in which numerous large-scale data sets are generated from diverse analytical platforms. Furthermore, several scientific journals and funding agencies have emphasized the storage of proteomics data in public repositories to facilitate its evaluation, inspection, and reanalysis. (1) As a consequence, public proteomics data repositories are growing rapidly. However, tools are needed to integrate multiple proteomics data sets to compare different experimental features or to perform quality control analysis. Here, we present a new Java stand-alone tool, Proteomics Assay COMparator (PACOM), that is able to import, combine, and simultaneously compare numerous proteomics experiments to check the integrity of the proteomic data as well as verify data quality. With PACOM, the user can detect source of errors that may have been introduced in any step of a proteomics workflow and that influence the final results. Data sets can be easily compared and integrated, and data quality and reproducibility can be visually assessed through a rich set of graphical representations of proteomics data features as well as a wide variety of data filters. Its flexibility and easy-to-use interface make PACOM a unique tool for daily use in a proteomics laboratory. PACOM is available at https://github.com/smdb21/pacom .

A Proteomic Workflow Using High-Throughput De Novo Sequencing Towards Complementation of Genome Information for Improved Comparative Crop Science.

PubMed

Turetschek, Reinhard; Lyon, David; Desalegn, Getinet; Kaul, Hans-Peter; Wienkoop, Stefanie

2016-01-01

The proteomic study of non-model organisms, such as many crop plants, is challenging due to the lack of comprehensive genome information. Changing environmental conditions require the study and selection of adapted cultivars. Mutations, inherent to cultivars, hamper protein identification and thus considerably complicate the qualitative and quantitative comparison in large-scale systems biology approaches. With this workflow, cultivar-specific mutations are detected from high-throughput comparative MS analyses, by extracting sequence polymorphisms with de novo sequencing. Stringent criteria are suggested to filter for confidential mutations. Subsequently, these polymorphisms complement the initially used database, which is ready to use with any preferred database search algorithm. In our example, we thereby identified 26 specific mutations in two cultivars of Pisum sativum and achieved an increased number (17 %) of peptide spectrum matches.

Strong and oriented immobilization of single domain antibodies from crude bacterial lysates for high-throughput compatible cost-effective antibody array generation

PubMed Central

Even-Desrumeaux, Klervi; Baty, Daniel; Chames, Patrick

2010-01-01

Antibodies microarrays are among the novel class of rapidly emerging proteomic technologies that will allow us to efficiently perform specific diagnosis and proteome analysis. Recombinant antibody fragments are especially suited for this approach but their stability is often a limiting factor. Camelids produce functional antibodies devoid of light chains (HCAbs) of which the single N-terminal domain is fully capable of antigen binding. When produced as an independent domain, these so-called single domain antibody fragments (sdAbs) have several advantages for biotechnological applications thanks to their unique properties of size (15 kDa), stability, solubility, and expression yield. These features should allow sdAbs to outperform other antibody formats in a number of applications, notably as capture molecule for antibody arrays. In this study, we have produced antibody microarrays using direct and oriented immobilization of sdAbs produced in crude bacterial lysates to generate proof-of-principle of a high-throughput compatible array design. Several sdAb immobilization strategies have been explored. Immobilization of in vivo biotinylated sdAbs by direct spotting of bacterial lysate on streptavidin and sandwich detection was developed to achieve high sensitivity and specificity, whereas immobilization of “multi-tagged” sdAbs via anti-tag antibodies and direct labeled sample detection strategy was optimized for the design of high-density antibody arrays for high-throughput proteomics and identification of potential biomarkers. PMID:20859568

Automation, parallelism, and robotics for proteomics.

PubMed

Alterovitz, Gil; Liu, Jonathan; Chow, Jijun; Ramoni, Marco F

2006-07-01

The speed of the human genome project (Lander, E. S., Linton, L. M., Birren, B., Nusbaum, C. et al., Nature 2001, 409, 860-921) was made possible, in part, by developments in automation of sequencing technologies. Before these technologies, sequencing was a laborious, expensive, and personnel-intensive task. Similarly, automation and robotics are changing the field of proteomics today. Proteomics is defined as the effort to understand and characterize proteins in the categories of structure, function and interaction (Englbrecht, C. C., Facius, A., Comb. Chem. High Throughput Screen. 2005, 8, 705-715). As such, this field nicely lends itself to automation technologies since these methods often require large economies of scale in order to achieve cost and time-saving benefits. This article describes some of the technologies and methods being applied in proteomics in order to facilitate automation within the field as well as in linking proteomics-based information with other related research areas.

Proteomics of Plant Pathogenic Fungi

PubMed Central

González-Fernández, Raquel; Prats, Elena; Jorrín-Novo, Jesús V.

2010-01-01

Plant pathogenic fungi cause important yield losses in crops. In order to develop efficient and environmental friendly crop protection strategies, molecular studies of the fungal biological cycle, virulence factors, and interaction with its host are necessary. For that reason, several approaches have been performed using both classical genetic, cell biology, and biochemistry and the modern, holistic, and high-throughput, omic techniques. This work briefly overviews the tools available for studying Plant Pathogenic Fungi and is amply focused on MS-based Proteomics analysis, based on original papers published up to December 2009. At a methodological level, different steps in a proteomic workflow experiment are discussed. Separate sections are devoted to fungal descriptive (intracellular, subcellular, extracellular) and differential expression proteomics and interactomics. From the work published we can conclude that Proteomics, in combination with other techniques, constitutes a powerful tool for providing important information about pathogenicity and virulence factors, thus opening up new possibilities for crop disease diagnosis and crop protection. PMID:20589070

Proteomics of plant pathogenic fungi.

PubMed

González-Fernández, Raquel; Prats, Elena; Jorrín-Novo, Jesús V

2010-01-01

Plant pathogenic fungi cause important yield losses in crops. In order to develop efficient and environmental friendly crop protection strategies, molecular studies of the fungal biological cycle, virulence factors, and interaction with its host are necessary. For that reason, several approaches have been performed using both classical genetic, cell biology, and biochemistry and the modern, holistic, and high-throughput, omic techniques. This work briefly overviews the tools available for studying Plant Pathogenic Fungi and is amply focused on MS-based Proteomics analysis, based on original papers published up to December 2009. At a methodological level, different steps in a proteomic workflow experiment are discussed. Separate sections are devoted to fungal descriptive (intracellular, subcellular, extracellular) and differential expression proteomics and interactomics. From the work published we can conclude that Proteomics, in combination with other techniques, constitutes a powerful tool for providing important information about pathogenicity and virulence factors, thus opening up new possibilities for crop disease diagnosis and crop protection.

Multidimensional electrostatic repulsion-hydrophilic interaction chromatography (ERLIC) for quantitative analysis of the proteome and phosphoproteome in clinical and biomedical research.

PubMed

Loroch, Stefan; Schommartz, Tim; Brune, Wolfram; Zahedi, René Peiman; Sickmann, Albert

2015-05-01

Quantitative proteomics and phosphoproteomics have become key disciplines in understanding cellular processes. Fundamental research can be done using cell culture providing researchers with virtually infinite sample amounts. In contrast, clinical, pre-clinical and biomedical research is often restricted to minute sample amounts and requires an efficient analysis with only micrograms of protein. To address this issue, we generated a highly sensitive workflow for combined LC-MS-based quantitative proteomics and phosphoproteomics by refining an ERLIC-based 2D phosphoproteomics workflow into an ERLIC-based 3D workflow covering the global proteome as well. The resulting 3D strategy was successfully used for an in-depth quantitative analysis of both, the proteome and the phosphoproteome of murine cytomegalovirus-infected mouse fibroblasts, a model system for host cell manipulation by a virus. In a 2-plex SILAC experiment with 150 μg of a tryptic digest per condition, the 3D strategy enabled the quantification of ~75% more proteins and even ~134% more peptides compared to the 2D strategy. Additionally, we could quantify ~50% more phosphoproteins by non-phosphorylated peptides, concurrently yielding insights into changes on the levels of protein expression and phosphorylation. Beside its sensitivity, our novel three-dimensional ERLIC-strategy has the potential for semi-automated sample processing rendering it a suitable future perspective for clinical, pre-clinical and biomedical research. Copyright © 2015. Published by Elsevier B.V.

Microscale screening systems for 3D cellular microenvironments: platforms, advances, and challenges

PubMed Central

Montanez-Sauri, Sara I.; Beebe, David J.; Sung, Kyung Eun

2015-01-01

The increasing interest in studying cells using more in vivo-like three-dimensional (3D) microenvironments has created a need for advanced 3D screening platforms with enhanced functionalities and increased throughput. 3D screening platforms that better mimic in vivo microenvironments with enhanced throughput would provide more in-depth understanding of the complexity and heterogeneity of microenvironments. The platforms would also better predict the toxicity and efficacy of potential drugs in physiologically relevant conditions. Traditional 3D culture models (e.g. spinner flasks, gyratory rotation devices, non-adhesive surfaces, polymers) were developed to create 3D multicellular structures. However, these traditional systems require large volumes of reagents and cells, and are not compatible with high throughput screening (HTS) systems. Microscale technology offers the miniaturization of 3D cultures and allows efficient screening of various conditions. This review will discuss the development, most influential works, and current advantages and challenges of microscale culture systems for screening cells in 3D microenvironments. PMID:25274061

Wheat proteomics: proteome modulation and abiotic stress acclimation

PubMed Central

Komatsu, Setsuko; Kamal, Abu H. M.; Hossain, Zahed

2014-01-01

Cellular mechanisms of stress sensing and signaling represent the initial plant responses to adverse conditions. The development of high-throughput “Omics” techniques has initiated a new era of the study of plant molecular strategies for adapting to environmental changes. However, the elucidation of stress adaptation mechanisms in plants requires the accurate isolation and characterization of stress-responsive proteins. Because the functional part of the genome, namely the proteins and their post-translational modifications, are critical for plant stress responses, proteomic studies provide comprehensive information about the fine-tuning of cellular pathways that primarily involved in stress mitigation. This review summarizes the major proteomic findings related to alterations in the wheat proteomic profile in response to abiotic stresses. Moreover, the strengths and weaknesses of different sample preparation techniques, including subcellular protein extraction protocols, are discussed in detail. The continued development of proteomic approaches in combination with rapidly evolving bioinformatics tools and interactive databases will facilitate understanding of the plant mechanisms underlying stress tolerance. PMID:25538718

A Method for Label-Free, Differential Top-Down Proteomics.

PubMed

Ntai, Ioanna; Toby, Timothy K; LeDuc, Richard D; Kelleher, Neil L

2016-01-01

Biomarker discovery in the translational research has heavily relied on labeled and label-free quantitative bottom-up proteomics. Here, we describe a new approach to biomarker studies that utilizes high-throughput top-down proteomics and is the first to offer whole protein characterization and relative quantitation within the same experiment. Using yeast as a model, we report procedures for a label-free approach to quantify the relative abundance of intact proteins ranging from 0 to 30 kDa in two different states. In this chapter, we describe the integrated methodology for the large-scale profiling and quantitation of the intact proteome by liquid chromatography-mass spectrometry (LC-MS) without the need for metabolic or chemical labeling. This recent advance for quantitative top-down proteomics is best implemented with a robust and highly controlled sample preparation workflow before data acquisition on a high-resolution mass spectrometer, and the application of a hierarchical linear statistical model to account for the multiple levels of variance contained in quantitative proteomic comparisons of samples for basic and clinical research.

A high-throughput in vitro ring assay for vasoactivity using magnetic 3D bioprinting

PubMed Central

Tseng, Hubert; Gage, Jacob A.; Haisler, William L.; Neeley, Shane K.; Shen, Tsaiwei; Hebel, Chris; Barthlow, Herbert G.; Wagoner, Matthew; Souza, Glauco R.

2016-01-01

Vasoactive liabilities are typically assayed using wire myography, which is limited by its high cost and low throughput. To meet the demand for higher throughput in vitro alternatives, this study introduces a magnetic 3D bioprinting-based vasoactivity assay. The principle behind this assay is the magnetic printing of vascular smooth muscle cells into 3D rings that functionally represent blood vessel segments, whose contraction can be altered by vasodilators and vasoconstrictors. A cost-effective imaging modality employing a mobile device is used to capture contraction with high throughput. The goal of this study was to validate ring contraction as a measure of vasoactivity, using a small panel of known vasoactive drugs. In vitro responses of the rings matched outcomes predicted by in vivo pharmacology, and were supported by immunohistochemistry. Altogether, this ring assay robustly models vasoactivity, which could meet the need for higher throughput in vitro alternatives. PMID:27477945

The Urine Proteome as a Biomarker of Radiation Injury

PubMed Central

Sharma, Mukut; Halligan, Brian D.; Wakim, Bassam T.; Savin, Virginia J.; Cohen, Eric P.; Moulder, John E.

2009-01-01

Terrorist attacks or nuclear accidents could expose large numbers of people to ionizing radiation, and early biomarkers of radiation injury would be critical for triage, treatment and follow-up of such individuals. However, no such biomarkers have yet been proven to exist. We tested the potential of high throughput proteomics to identify protein biomarkers of radiation injury after total body X-ray irradiation in a rat model. Subtle functional changes in the kidney are suggested by an increased glomerular permeability for macromolecules measured within 24 hours after TBI. Ultrastructural changes in glomerular podocytes include partial loss of the interdigitating organization of foot processes. Analysis of urine by LC-MS/MS and 2D-GE showed significant changes in the urine proteome within 24 hours after TBI. Tissue kallikrein 1-related peptidase, cysteine proteinase inhibitor cystatin C and oxidized histidine were found to be increased while a number of proteinase inhibitors including kallikrein-binding protein and albumin were found to be decreased post-irradiation. Thus, TBI causes immediately detectable changes in renal structure and function and in the urinary protein profile. This suggests that both systemic and renal changes are induced by radiation and it may be possible to identify a set of biomarkers unique to radiation injury. PMID:19746194

Recent advances on multidimensional liquid chromatography-mass spectrometry for proteomics: from qualitative to quantitative analysis--a review.

PubMed

Wu, Qi; Yuan, Huiming; Zhang, Lihua; Zhang, Yukui

2012-06-20

With the acceleration of proteome research, increasing attention has been paid to multidimensional liquid chromatography-mass spectrometry (MDLC-MS) due to its high peak capacity and separation efficiency. Recently, many efforts have been put to improve MDLC-based strategies including "top-down" and "bottom-up" to enable highly sensitive qualitative and quantitative analysis of proteins, as well as accelerate the whole analytical procedure. Integrated platforms with combination of sample pretreatment, multidimensional separations and identification were also developed to achieve high throughput and sensitive detection of proteomes, facilitating highly accurate and reproducible quantification. This review summarized the recent advances of such techniques and their applications in qualitative and quantitative analysis of proteomes. Copyright © 2012 Elsevier B.V. All rights reserved.

Biofuels as a sustainable energy source: an update of the applications of proteomics in bioenergy crops and algae.

PubMed

Ndimba, Bongani Kaiser; Ndimba, Roya Janeen; Johnson, T Sudhakar; Waditee-Sirisattha, Rungaroon; Baba, Masato; Sirisattha, Sophon; Shiraiwa, Yoshihiro; Agrawal, Ganesh Kumar; Rakwal, Randeep

2013-11-20

Sustainable energy is the need of the 21st century, not because of the numerous environmental and political reasons but because it is necessary to human civilization's energy future. Sustainable energy is loosely grouped into renewable energy, energy conservation, and sustainable transport disciplines. In this review, we deal with the renewable energy aspect focusing on the biomass from bioenergy crops to microalgae to produce biofuels to the utilization of high-throughput omics technologies, in particular proteomics in advancing our understanding and increasing biofuel production. We look at biofuel production by plant- and algal-based sources, and the role proteomics has played therein. This article is part of a Special Issue entitled: Translational Plant Proteomics. Copyright © 2013 Elsevier B.V. All rights reserved.

Myeloperoxidase mediated HDL oxidation and HDL proteome changes do not contribute to dysfunctional HDL in Chinese subjects with coronary artery disease

PubMed Central

Yu, Haiyi; Li, Lei; He, Liyun; Gao, Wei; Liu, Xiaodan; Guo, Yanhong; Byun, Jaeman; Zhang, Jifeng; Chen, Y. Eugene

2018-01-01

High density lipoprotein (HDL) cholesterol levels and cholesterol efflux capacity (CEC) are inversely correlated with coronary artery disease (CAD) risk. Myeloperoxidase (MPO) derived oxidants and HDL proteome changes are implicated in HDL dysfunction in subjects with CAD in the United States; however, the effect of MPO on HDL function and HDL proteome in ethnic Chinese population is unknown. We recruited four matched ethnic Chinese groups (20 patients each): subjects with 1) low HDL levels (HDL levels in men <40mg/dL and women <50mg/dL) and non-CAD (identified by coronary angiography or cardiac CT angiography); 2) low HDL and CAD; 3) high HDL (men >50mg/dL; women >60mg/dL) with no CAD; and 4) high HDL with CAD. Serum cytokines, serum MPO levels, serum CEC, MPO-oxidized HDL tyrosine moieties, and HDL proteome were assessed by mass spectrometry individually in the four groups. The cytokines, MPO levels, and HDL proteome profiles were not significantly different between the four groups. As expected, CEC was depressed in the entire CAD group but more specifically in the CAD low-HDL group. HDL of CAD subjects had significantly higher 3-nitrotyrosine than non-CAD subjects, but the MPO-specific 3-chlorotyrosine was unchanged; CEC in the CAD low-HDL group did not correlate with either HDL 3-chlorotyrosine or 3-nitrotyrosine levels. Neither 3-chlorotyrosine, which is MPO-specific, nor 3-nitrotyrosine generated from MPO or other reactive nitrogen species was associated with CEC. MPO mediated oxidative stress and HDL proteome composition changes are not the primary cause HDL dysfunction in Chinese subjects with CAD. These studies highlight ethnic differences in HDL dysfunction between United States and Chinese cohorts raising possibility of unique pathways of HDL dysfunction in this cohort. PMID:29505607

Application of targeted quantitative proteomics analysis in human cerebrospinal fluid using a liquid chromatography matrix-assisted laser desorption/ionization time-of-flight tandem mass spectrometer (LC MALDI TOF/TOF) platform.

PubMed

Pan, Sheng; Rush, John; Peskind, Elaine R; Galasko, Douglas; Chung, Kathryn; Quinn, Joseph; Jankovic, Joseph; Leverenz, James B; Zabetian, Cyrus; Pan, Catherine; Wang, Yan; Oh, Jung Hun; Gao, Jean; Zhang, Jianpeng; Montine, Thomas; Zhang, Jing

2008-02-01

Targeted quantitative proteomics by mass spectrometry aims to selectively detect one or a panel of peptides/proteins in a complex sample and is particularly appealing for novel biomarker verification/validation because it does not require specific antibodies. Here, we demonstrated the application of targeted quantitative proteomics in searching, identifying, and quantifying selected peptides in human cerebrospinal spinal fluid (CSF) using a matrix-assisted laser desorption/ionization time-of-flight tandem mass spectrometer (MALDI TOF/TOF)-based platform. The approach involved two major components: the use of isotopic-labeled synthetic peptides as references for targeted identification and quantification and a highly selective mass spectrometric analysis based on the unique characteristics of the MALDI instrument. The platform provides high confidence for targeted peptide detection in a complex system and can potentially be developed into a high-throughput system. Using the liquid chromatography (LC) MALDI TOF/TOF platform and the complementary identification strategy, we were able to selectively identify and quantify a panel of targeted peptides in the whole proteome of CSF without prior depletion of abundant proteins. The effectiveness and robustness of the approach associated with different sample complexity, sample preparation strategies, as well as mass spectrometric quantification were evaluated. Other issues related to chromatography separation and the feasibility for high-throughput analysis were also discussed. Finally, we applied targeted quantitative proteomics to analyze a subset of previously identified candidate markers in CSF samples of patients with Parkinson's disease (PD) at different stages and Alzheimer's disease (AD) along with normal controls.

[Techniques for rapid production of monoclonal antibodies for use with antibody technology].

PubMed

Kamada, Haruhiko

2012-01-01

A monoclonal antibody (Mab), due to its specific binding ability to a target protein, can potentially be one of the most useful tools for the functional analysis of proteins in recent proteomics-based research. However, the production of Mab is a very time-consuming and laborious process (i.e., preparation of recombinant antigens, immunization of animals, preparation of hybridomas), making it the rate-limiting step in using Mabs in high-throughput proteomics research, which heavily relies on comprehensive and rapid methods. Therefore, there is a great demand for new methods to efficiently generate Mabs against a group of proteins identified by proteome analysis. Here, we describe a useful method called "Antibody proteomic technique" for the rapid generations of Mabs to pharmaceutical target, which were identified by proteomic analyses of disease samples (ex. tumor tissue, etc.). We also introduce another method to find profitable targets on vasculature, which is called "Vascular proteomic technique". Our results suggest that this method for the rapid generation of Mabs to proteins may be very useful in proteomics-based research as well as in clinical applications.

Respiratory Toxicity Biomarkers

EPA Science Inventory

The advancement in high throughput genomic, proteomic and metabolomic techniques have accelerated pace of lung biomarker discovery. A recent growth in the discovery of new lung toxicity/disease biomarkers have led to significant advances in our understanding of pathological proce...

The application of proteomics in different aspects of hepatocellular carcinoma research.

PubMed

Xing, Xiaohua; Liang, Dong; Huang, Yao; Zeng, Yongyi; Han, Xiao; Liu, Xiaolong; Liu, Jingfeng

2016-08-11

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors, which is causing the second leading cancer-related death worldwide. With the significant advances of high-throughput protein analysis techniques, the proteomics offered an extremely useful and versatile analytical platform for biomedical researches. In recent years, different proteomic strategies have been widely applied in the various aspects of HCC studies, ranging from screening the early diagnostic and prognostic biomarkers to in-depth investigating the underlying molecular mechanisms. In this review, we would like to systematically summarize the current applications of proteomics in hepatocellular carcinoma study, and discuss the challenges of applying proteomics in study clinical samples, as well as discuss the possible application of proteomics in precision medicine. In this review, we have systematically summarized the current applications of proteomics in hepatocellular carcinoma study, ranging from screening biomarkers to in-depth investigating the underlying molecular mechanisms. In addition, we have discussed the challenges of applying proteomics in study clinical samples, as well as the possible applications of proteomics in precision medicine. We believe that this review would help readers to be better familiar with the recent progresses of clinical proteomics, especially in the field of hepatocellular carcinoma research. Copyright © 2016 Elsevier B.V. All rights reserved.

Pressurized Pepsin Digestion in Proteomics

PubMed Central

López-Ferrer, Daniel; Petritis, Konstantinos; Robinson, Errol W.; Hixson, Kim K.; Tian, Zhixin; Lee, Jung Hwa; Lee, Sang-Won; Tolić, Nikola; Weitz, Karl K.; Belov, Mikhail E.; Smith, Richard D.; Paša-Tolić, Ljiljana

2011-01-01

Integrated top-down bottom-up proteomics combined with on-line digestion has great potential to improve the characterization of protein isoforms in biological systems and is amendable to high throughput proteomics experiments. Bottom-up proteomics ultimately provides the peptide sequences derived from the tandem MS analyses of peptides after the proteome has been digested. Top-down proteomics conversely entails the MS analyses of intact proteins for more effective characterization of genetic variations and/or post-translational modifications. Herein, we describe recent efforts toward efficient integration of bottom-up and top-down LC-MS-based proteomics strategies. Since most proteomics separations utilize acidic conditions, we exploited the compatibility of pepsin (where the optimal digestion conditions are at low pH) for integration into bottom-up and top-down proteomics work flows. Pressure-enhanced pepsin digestions were successfully performed and characterized with several standard proteins in either an off-line mode using a Barocycler or an on-line mode using a modified high pressure LC system referred to as a fast on-line digestion system (FOLDS). FOLDS was tested using pepsin and a whole microbial proteome, and the results were compared against traditional trypsin digestions on the same platform. Additionally, FOLDS was integrated with a RePlay configuration to demonstrate an ultrarapid integrated bottom-up top-down proteomics strategy using a standard mixture of proteins and a monkey pox virus proteome. PMID:20627868

Application of Large-Scale Aptamer-Based Proteomic Profiling to Planned Myocardial Infarctions.

PubMed

Jacob, Jaison; Ngo, Debby; Finkel, Nancy; Pitts, Rebecca; Gleim, Scott; Benson, Mark D; Keyes, Michelle J; Farrell, Laurie A; Morgan, Thomas; Jennings, Lori L; Gerszten, Robert E

2018-03-20

Emerging proteomic technologies using novel affinity-based reagents allow for efficient multiplexing with high-sample throughput. To identify early biomarkers of myocardial injury, we recently applied an aptamer-based proteomic profiling platform that measures 1129 proteins to samples from patients undergoing septal alcohol ablation for hypertrophic cardiomyopathy, a human model of planned myocardial injury. Here, we examined the scalability of this approach using a markedly expanded platform to study a far broader range of human proteins in the context of myocardial injury. We applied a highly multiplexed, expanded proteomic technique that uses single-stranded DNA aptamers to assay 4783 human proteins (4137 distinct human gene targets) to derivation and validation cohorts of planned myocardial injury, individuals with spontaneous myocardial infarction, and at-risk controls. We found 376 target proteins that significantly changed in the blood after planned myocardial injury in a derivation cohort (n=20; P <1.05E-05, 1-way repeated measures analysis of variance, Bonferroni threshold). Two hundred forty-seven of these proteins were validated in an independent planned myocardial injury cohort (n=15; P <1.33E-04, 1-way repeated measures analysis of variance); >90% were directionally consistent and reached nominal significance in the validation cohort. Among the validated proteins that were increased within 1 hour after planned myocardial injury, 29 were also elevated in patients with spontaneous myocardial infarction (n=63; P <6.17E-04). Many of the novel markers identified in our study are intracellular proteins not previously identified in the peripheral circulation or have functional roles relevant to myocardial injury. For example, the cardiac LIM protein, cysteine- and glycine-rich protein 3, is thought to mediate cardiac mechanotransduction and stress responses, whereas the mitochondrial ATP synthase F 0 subunit component is a vasoactive peptide on its release from cells. Last, we performed aptamer-affinity enrichment coupled with mass spectrometry to technically verify aptamer specificity for a subset of the new biomarkers. Our results demonstrate the feasibility of large-scale aptamer multiplexing at a level that has not previously been reported and with sample throughput that greatly exceeds other existing proteomic methods. The expanded aptamer-based proteomic platform provides a unique opportunity for biomarker and pathway discovery after myocardial injury. © 2017 American Heart Association, Inc.

Plasma proteomic changes during hypothermic and normothermic cardiopulmonary bypass in aortic surgeries

PubMed Central

ODA, TEIJI; YAMAGUCHI, AKANE; YOKOYAMA, MASAO; SHIMIZU, KOJI; TOYOTA, KOSAKU; NIKAI, TETSURO; MATSUMOTO, KEN-ICHI

2014-01-01

Deep hypothermic circulatory arrest (DHCA) is a protective method against brain ischemia in aortic surgery. However, the possible effects of DHCA on the plasma proteins remain to be determined. In the present study, we used novel high-throughput technology to compare the plasma proteomes during DHCA (22°C) with selective cerebral perfusion (SCP, n=7) to those during normothermic cardiopulmonary bypass (CPB, n=7). Three plasma samples per patient were obtained during CPB: T1, prior to cooling; T2, during hypothermia; T3, after rewarming for the DHCA group and three corresponding points for the normothermic group. A proteomic analysis was performed using isobaric tag for relative and absolute quantification (iTRAQ) labeling tandem mass spectrometry to assess quantitative protein changes. In total, the analysis identified 262 proteins. The bioinformatics analysis revealed a significant upregulation of complement activation at T2 in normothermic CPB, which was suppressed in DHCA. These findings were confirmed by the changes of the terminal complement complex (SC5b-9) levels. At T3, however, the level of SC5b-9 showed a greater increase in DHCA compared to normothermic CPB, while 48 proteins were significantly downregulated in DHCA. The results demonstrated that DHCA and rewarming potentially exert a significant effect on the plasma proteome in patients undergoing aortic surgery. PMID:25050567

Comparative and Quantitative Global Proteomics Approaches: An Overview

PubMed Central

Deracinois, Barbara; Flahaut, Christophe; Duban-Deweer, Sophie; Karamanos, Yannis

2013-01-01

Proteomics became a key tool for the study of biological systems. The comparison between two different physiological states allows unravelling the cellular and molecular mechanisms involved in a biological process. Proteomics can confirm the presence of proteins suggested by their mRNA content and provides a direct measure of the quantity present in a cell. Global and targeted proteomics strategies can be applied. Targeted proteomics strategies limit the number of features that will be monitored and then optimise the methods to obtain the highest sensitivity and throughput for a huge amount of samples. The advantage of global proteomics strategies is that no hypothesis is required, other than a measurable difference in one or more protein species between the samples. Global proteomics methods attempt to separate quantify and identify all the proteins from a given sample. This review highlights only the different techniques of separation and quantification of proteins and peptides, in view of a comparative and quantitative global proteomics analysis. The in-gel and off-gel quantification of proteins will be discussed as well as the corresponding mass spectrometry technology. The overview is focused on the widespread techniques while keeping in mind that each approach is modular and often recovers the other. PMID:28250403

OncoBinder facilitates interpretation of proteomic interaction data by capturing coactivation pairs in cancer.

PubMed

Van Coillie, Samya; Liang, Lunxi; Zhang, Yao; Wang, Huanbin; Fang, Jing-Yuan; Xu, Jie

2016-04-05

High-throughput methods such as co-immunoprecipitationmass spectrometry (coIP-MS) and yeast 2 hybridization (Y2H) have suggested a broad range of unannotated protein-protein interactions (PPIs), and interpretation of these PPIs remains a challenging task. The advancements in cancer genomic researches allow for the inference of "coactivation pairs" in cancer, which may facilitate the identification of PPIs involved in cancer. Here we present OncoBinder as a tool for the assessment of proteomic interaction data based on the functional synergy of oncoproteins in cancer. This decision tree-based method combines gene mutation, copy number and mRNA expression information to infer the functional status of protein-coding genes. We applied OncoBinder to evaluate the potential binders of EGFR and ERK2 proteins based on the gastric cancer dataset of The Cancer Genome Atlas (TCGA). As a result, OncoBinder identified high confidence interactions (annotated by Kyoto Encyclopedia of Genes and Genomes (KEGG) or validated by low-throughput assays) more efficiently than co-expression based method. Taken together, our results suggest that evaluation of gene functional synergy in cancer may facilitate the interpretation of proteomic interaction data. The OncoBinder toolbox for Matlab is freely accessible online.

Enhancing analysis throughput, sensitivity and specificity in LC/ESI-MS/MS assay of plasma 25-hydroxyvitamin D3 by derivatization with triplex 4-(4-dimethylaminophenyl)-1,2,4-triazoline-3,5-dione (DAPTAD) isotopologues.

PubMed

Ogawa, Shoujiro; Kittaka, Hiroki; Nakata, Akiho; Komatsu, Kenji; Sugiura, Takahiro; Satoh, Mamoru; Nomura, Fumio; Higashi, Tatsuya

2017-03-20

The plasma/serum concentration of 25-hydroxyvitamin D 3 [25(OH)D 3 ] is a diagnostic index for vitamin D deficiency/insufficiency, which is associated with a wide range of diseases, such as rickets, cancer and diabetes. We have reported that the derivatization with 4-(4-dimethylaminophenyl)-1,2,4-triazoline-3,5-dione (DAPTAD) works well in the liquid chromatography/electrospray ionization-tandem mass spectrometry (LC/ESI-MS/MS) assay of the serum/plasma 25(OH)D 3 for enhancing the sensitivity and the separation from a potent interfering metabolite, 3-epi-25-hydroxyvitamin D 3 [3-epi-25(OH)D 3 ]. However, enhancing the analysis throughput remains an issue in the LC/ESI-MS/MS assay of 25(OH)D 3 . The most obvious restriction of the LC/MS/MS throughput is the chromatographic run time. In this study, we developed an enhanced throughput method for the determination of the plasma 25(OH)D 3 by LC/ESI-MS/MS combined with the derivatization using the triplex ( 2 H 0 -, 2 H 3 - and 2 H 6 -) DAPTAD isotopologues. After separate derivatization with 1 of 3 different isotopologues, the 3 samples were combined and injected together into LC/ESI-MS/MS. Based on the mass differences between the isotopologues, the derivatized 25(OH)D 3 in the 3 different samples were quantified within a single run. The developed method tripled the hourly analysis throughput without sacrificing assay performance, i.e., ease of pretreatment of plasma sample (only deproteinization), limit of quantification (1.0ng/mL when a 5μL-plasma was used), precision (intra-assay RSD≤5.9% and inter-assay RSD≤5.5%), accuracy (98.7-102.2%), matrix effects, and capability of separating from an interfering metabolite, 3-epi-25(OH)D 3 . The multiplexing of samples by the isotopologue derivatization was applied to the analysis of plasma samples of healthy subjects and the developed method was proven to have a satisfactory applicability. Copyright © 2016 Elsevier B.V. All rights reserved.

The role of targeted chemical proteomics in pharmacology

PubMed Central

Sutton, Chris W

2012-01-01

Traditionally, proteomics is the high-throughput characterization of the global complement of proteins in a biological system using cutting-edge technologies (robotics and mass spectrometry) and bioinformatics tools (Internet-based search engines and databases). As the field of proteomics has matured, a diverse range of strategies have evolved to answer specific problems. Chemical proteomics is one such direction that provides the means to enrich and detect less abundant proteins (the ‘hidden’ proteome) from complex mixtures of wide dynamic range (the ‘deep’ proteome). In pharmacology, chemical proteomics has been utilized to determine the specificity of drugs and their analogues, for anticipated known targets, only to discover other proteins that bind and could account for side effects observed in preclinical and clinical trials. As a consequence, chemical proteomics provides a valuable accessory in refinement of second- and third-generation drug design for treatment of many diseases. However, determining definitive affinity capture of proteins by a drug immobilized on soft gel chromatography matrices has highlighted some of the challenges that remain to be addressed. Examples of the different strategies that have emerged using well-established drugs against pharmaceutically important enzymes, such as protein kinases, metalloproteases, PDEs, cytochrome P450s, etc., indicate the potential opportunity to employ chemical proteomics as an early-stage screening approach in the identification of new targets. PMID:22074351

NMR in the SPINE Structural Proteomics project.

PubMed

Ab, E; Atkinson, A R; Banci, L; Bertini, I; Ciofi-Baffoni, S; Brunner, K; Diercks, T; Dötsch, V; Engelke, F; Folkers, G E; Griesinger, C; Gronwald, W; Günther, U; Habeck, M; de Jong, R N; Kalbitzer, H R; Kieffer, B; Leeflang, B R; Loss, S; Luchinat, C; Marquardsen, T; Moskau, D; Neidig, K P; Nilges, M; Piccioli, M; Pierattelli, R; Rieping, W; Schippmann, T; Schwalbe, H; Travé, G; Trenner, J; Wöhnert, J; Zweckstetter, M; Kaptein, R

2006-10-01

This paper describes the developments, role and contributions of the NMR spectroscopy groups in the Structural Proteomics In Europe (SPINE) consortium. Focusing on the development of high-throughput (HTP) pipelines for NMR structure determinations of proteins, all aspects from sample preparation, data acquisition, data processing, data analysis to structure determination have been improved with respect to sensitivity, automation, speed, robustness and validation. Specific highlights are protonless (13)C-direct detection methods and inferential structure determinations (ISD). In addition to technological improvements, these methods have been applied to deliver over 60 NMR structures of proteins, among which are five that failed to crystallize. The inclusion of NMR spectroscopy in structural proteomics pipelines improves the success rate for protein structure determinations.

Microfluidic-Mass Spectrometry Interfaces for Translational Proteomics.

PubMed

Pedde, R Daniel; Li, Huiyan; Borchers, Christoph H; Akbari, Mohsen

2017-10-01

Interfacing mass spectrometry (MS) with microfluidic chips (μchip-MS) holds considerable potential to transform a clinician's toolbox, providing translatable methods for the early detection, diagnosis, monitoring, and treatment of noncommunicable diseases by streamlining and integrating laborious sample preparation workflows on high-throughput, user-friendly platforms. Overcoming the limitations of competitive immunoassays - currently the gold standard in clinical proteomics - μchip-MS can provide unprecedented access to complex proteomic assays having high sensitivity and specificity, but without the labor, costs, and complexities associated with conventional MS sample processing. This review surveys recent μchip-MS systems for clinical applications and examines their emerging role in streamlining the development and translation of MS-based proteomic assays by alleviating many of the challenges that currently inhibit widespread clinical adoption. Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.

Fusarium graminearum and Its Interactions with Cereal Heads: Studies in the Proteomics Era

PubMed Central

Yang, Fen; Jacobsen, Susanne; Jørgensen, Hans J. L.; Collinge, David B.; Svensson, Birte; Finnie, Christine

2013-01-01

The ascomycete fungal pathogen Fusarium graminearum (teleomorph stage: Gibberella zeae) is the causal agent of Fusarium head blight in wheat and barley. This disease leads to significant losses of crop yield, and especially quality through the contamination by diverse fungal mycotoxins, which constitute a significant threat to the health of humans and animals. In recent years, high-throughput proteomics, aiming at identifying a broad spectrum of proteins with a potential role in the pathogenicity and host resistance, has become a very useful tool in plant-fungus interaction research. In this review, we describe the progress in proteomics applications toward a better understanding of F. graminearum pathogenesis, virulence, and host defense mechanisms. The contribution of proteomics to the development of crop protection strategies against this pathogen is also discussed briefly. PMID:23450732

Integrative FourD omics approach profiles the target network of the carbon storage regulatory system

PubMed Central

Sowa, Steven W.; Gelderman, Grant; Leistra, Abigail N.; Buvanendiran, Aishwarya; Lipp, Sarah; Pitaktong, Areen; Vakulskas, Christopher A.; Romeo, Tony; Baldea, Michael

2017-01-01

Abstract Multi-target regulators represent a largely untapped area for metabolic engineering and anti-bacterial development. These regulators are complex to characterize because they often act at multiple levels, affecting proteins, transcripts and metabolites. Therefore, single omics experiments cannot profile their underlying targets and mechanisms. In this work, we used an Integrative FourD omics approach (INFO) that consists of collecting and analyzing systems data throughout multiple time points, using multiple genetic backgrounds, and multiple omics approaches (transcriptomics, proteomics and high throughput sequencing crosslinking immunoprecipitation) to evaluate simultaneous changes in gene expression after imposing an environmental stress that accentuates the regulatory features of a network. Using this approach, we profiled the targets and potential regulatory mechanisms of a global regulatory system, the well-studied carbon storage regulatory (Csr) system of Escherichia coli, which is widespread among bacteria. Using 126 sets of proteomics and transcriptomics data, we identified 136 potential direct CsrA targets, including 50 novel ones, categorized their behaviors into distinct regulatory patterns, and performed in vivo fluorescence-based follow up experiments. The results of this work validate 17 novel mRNAs as authentic direct CsrA targets and demonstrate a generalizable strategy to integrate multiple lines of omics data to identify a core pool of regulator targets. PMID:28126921

A three-dimensional in vitro ovarian cancer coculture model using a high-throughput cell patterning platform

PubMed Central

Rizvi, Imran; Moon, Sangjun; Hasan, Tayyaba; Demirci, Utkan

2013-01-01

In vitro 3D cancer models that provide a more accurate representation of disease in vivo are urgently needed to improve our understanding of cancer pathology and to develop better cancer therapies. However, development of 3D models that are based on manual ejection of cells from micropipettes suffer from inherent limitations such as poor control over cell density, limited repeatability, low throughput, and, in the case of coculture models, lack of reproducible control over spatial distance between cell types (e.g., cancer and stromal cells). In this study, we build on a recently introduced 3D model in which human ovarian cancer (OVCAR-5) cells overlaid on Matrigel™ spontaneously form multicellular acini. We introduce a high-throughput automated cell printing system to bioprint a 3D coculture model using cancer cells and normal fibroblasts micropatterned on Matrigel™. Two cell types were patterned within a spatially controlled microenvironment (e.g., cell density, cell-cell distance) in a high-throughput and reproducible manner; both cell types remained viable during printing and continued to proliferate following patterning. This approach enables the miniaturization of an established macro-scale 3D culture model and would allow systematic investigation into the multiple unknown regulatory feedback mechanisms between tumor and stromal cells and provide a tool for high-throughput drug screening. PMID:21298805

Crop 3D-a LiDAR based platform for 3D high-throughput crop phenotyping.

PubMed

Guo, Qinghua; Wu, Fangfang; Pang, Shuxin; Zhao, Xiaoqian; Chen, Linhai; Liu, Jin; Xue, Baolin; Xu, Guangcai; Li, Le; Jing, Haichun; Chu, Chengcai

2018-03-01

With the growing population and the reducing arable land, breeding has been considered as an effective way to solve the food crisis. As an important part in breeding, high-throughput phenotyping can accelerate the breeding process effectively. Light detection and ranging (LiDAR) is an active remote sensing technology that is capable of acquiring three-dimensional (3D) data accurately, and has a great potential in crop phenotyping. Given that crop phenotyping based on LiDAR technology is not common in China, we developed a high-throughput crop phenotyping platform, named Crop 3D, which integrated LiDAR sensor, high-resolution camera, thermal camera and hyperspectral imager. Compared with traditional crop phenotyping techniques, Crop 3D can acquire multi-source phenotypic data in the whole crop growing period and extract plant height, plant width, leaf length, leaf width, leaf area, leaf inclination angle and other parameters for plant biology and genomics analysis. In this paper, we described the designs, functions and testing results of the Crop 3D platform, and briefly discussed the potential applications and future development of the platform in phenotyping. We concluded that platforms integrating LiDAR and traditional remote sensing techniques might be the future trend of crop high-throughput phenotyping.

Protein 3-Nitrotyrosine in Complex Biological Samples: Quantification by High-Pressure Liquid Chromatography/Electrochemical Detection and Emergence of Proteomic Approaches for Unbiased Identification of Modification Sites

PubMed Central

Nuriel, Tal; Deeb, Ruba S.; Hajjar, David P.; Gross, Steven S.

2008-01-01

Nitration of tyrosine residues by nitric oxide (NO)-derived species results in the accumulation of 3-nitrotyrosine in proteins, a hallmark of nitrosative stress in cells and tissues. Tyrosine nitration is recognized as one of the multiple signaling modalities used by NO-derived species for the regulation of protein structure and function in health and disease. Various methods have been described for the quantification of protein 3-nitrotyrosine residues, and several strategies have been presented toward the goal of proteome-wide identification of protein tyrosine modification sites. This chapter details a useful protocol for the quantification of 3-nitrotyrosine in cells and tissues using high-pressure liquid chromatography with electrochemical detection. Additionally, this chapter describes a novel biotin-tagging strategy for specific enrichment of 3-nitrotyrosine-containing peptides. Application of this strategy, in conjunction with high-throughput MS/MS-based peptide sequencing, is anticipated to fuel efforts in developing comprehensive inventories of nitrosative stress-induced protein-tyrosine modification sites in cells and tissues. PMID:18554526

Translational Research and Plasma Proteomic in Cancer.

PubMed

Santini, Annamaria Chiara; Giovane, Giancarlo; Auletta, Adelaide; Di Carlo, Angelina; Fiorelli, Alfonso; Cito, Letizia; Astarita, Carlo; Giordano, Antonio; Alfano, Roberto; Feola, Antonia; Di Domenico, Marina

2016-04-01

Proteomics is a recent field of research in molecular biology that can help in the fight against cancer through the search for biomarkers that can detect this disease in the early stages of its development. Proteomic is a speedily growing technology, also thanks to the development of even more sensitive and fast mass spectrometry analysis. Although this technique is the most widespread for the discovery of new cancer biomarkers, it still suffers of a poor sensitivity and insufficient reproducibility, essentially due to the tumor heterogeneity. Common technical shortcomings include limitations in the sensitivity of detecting low abundant biomarkers and possible systematic biases in the observed data. Current research attempts are trying to develop high-resolution proteomic instrumentation for high-throughput monitoring of protein changes that occur in cancer. In this review, we describe the basic features of the proteomic tools which have proven to be useful in cancer research, showing their advantages and disadvantages. The application of these proteomic tools could provide early biomarkers detection in various cancer types and could improve the understanding the mechanisms of tumor growth and dissemination. © 2015 Wiley Periodicals, Inc.

Microchip-Based Single-Cell Functional Proteomics for Biomedical Applications

PubMed Central

Lu, Yao; Yang, Liu; Wei, Wei; Shi, Qihui

2017-01-01

Cellular heterogeneity has been widely recognized but only recently have single cell tools become available that allow characterizing heterogeneity at the genomic and proteomic levels. We review the technological advances in microchip-based toolkits for single-cell functional proteomics. Each of these tools has distinct advantages and limitations, and a few have advanced toward being applied to address biological or clinical problems that fail to be addressed by traditional population-based methods. High-throughput single-cell proteomic assays generate high-dimensional data sets that contain new information and thus require developing new analytical framework to extract new biology. In this review article, we highlight a few biological and clinical applications in which the microchip-based single-cell proteomic tools provide unique advantages. The examples include resolving functional heterogeneity and dynamics of immune cells, dissecting cell-cell interaction by creating well-contolled on-chip microenvironment, capturing high-resolution snapshots of immune system functions in patients for better immunotherapy and elucidating phosphoprotein signaling networks in cancer cells for guiding effective molecularly targeted therapies. PMID:28280819

Applicability of a high-throughput shotgun plasma protein screening approach in understanding maternal biological pathways relevant to infant birth weight outcome.

PubMed

Kumarathasan, P; Vincent, R; Das, D; Mohottalage, S; Blais, E; Blank, K; Karthikeyan, S; Vuong, N Q; Arbuckle, T E; Fraser, W D

2014-04-04

There are reports linking maternal nutritional status, smoking and environmental chemical exposures to adverse pregnancy outcomes. However, biological bases for association between some of these factors and birth outcomes are yet to be established. The objective of this preliminary work is to test the capability of a new high-throughput shotgun plasma proteomic screening in identifying maternal changes relevant to pregnancy outcome. A subset of third trimester plasma samples (N=12) associated with normal and low-birth weight infants were fractionated, tryptic-digested and analyzed for global proteomic changes using a MALDI-TOF-TOF-MS methodology. Mass spectral data were mined for candidate biomarkers using bioinformatic and statistical tools. Maternal plasma profiles of cytokines (e.g. IL8, TNF-α), chemokines (e.g. MCP-1) and cardiovascular endpoints (e.g. ET-1, MMP-9) were analyzed by a targeted approach using multiplex protein array and HPLC-Fluorescence methods. Target and global plasma proteomic markers were used to identify protein interaction networks and maternal biological pathways relevant to low infant birth weight. Our results exhibited the potential to discriminate specific maternal physiologies relevant to risk of adverse birth outcomes. This proteomic approach can be valuable in understanding the impacts of maternal factors such as environmental contaminant exposures and nutrition on birth outcomes in future work. We demonstrate here the fitness of mass spectrometry-based shot-gun proteomics for surveillance of biological changes in mothers, and for adverse pathway analysis in combination with target biomarker information. This approach has potential for enabling early detection of mothers at risk for low infant birth weight and preterm birth, and thus early intervention for mitigation and prevention of adverse pregnancy outcomes. This article is part of a Special Issue entitled: Can Proteomics Fill the Gap Between Genomics and Phenotypes? Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.

Factors Affecting Cis-Dichloroethene and Vinyl Chloride Biological Transformation Under Anaerobic Conditions

DTIC Science & Technology

2006-05-01

410. 3. Baek, J-M, and C. M. Kenerley. 1998. Detection and enumeration of a genetically modified fungus in soil environments by quantitative...deduced proteome of D. ethenogenes using the complete sequence of the alcohol dehydrogenase with the most similar N-terminus (accession number ZP_00128696...chlorophenol respiration (3 1). Four orfs similru· to VcrC were also found in the deduced proteome of D. ethenogenes (38 - 47 % identity). Two of those are

ABCD2 identifies a subclass of peroxisomes in mouse adipose tissue

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Xiaoxi, E-mail: xiaoxi.liu@uky.edu; Liu, Jingjing, E-mail: jingjing.liu0@gmail.com; Lester, Joshua D., E-mail: joshua.lester@uky.edu

2015-01-02

Highlights: • We examined the D2 localization and the proteome of D2-containing compartment in mouse adipose tissue. • We confirmed the presence of D2 on a subcellular compartment that has typical structure as a microperoxisome. • We demonstrated the scarcity of peroxisome markers on D2-containing compartment. • The D2-containing compartment may be a subpopulation of peroxisome in mouse adipose tissue. • Proteomic data suggests potential association between D2-containing compartment and mitochondria and ER. - Abstract: ATP-binding cassette transporter D2 (D2) is an ABC half transporter that is thought to promote the transport of very long-chain fatty acyl-CoAs into peroxisomes. Bothmore » D2 and peroxisomes increase during adipogenesis. Although peroxisomes are essential to both catabolic and anabolic lipid metabolism, their function, and that of D2, in adipose tissues remain largely unknown. Here, we investigated the D2 localization and the proteome of D2-containing organelles, in adipose tissue. Centrifugation of mouse adipose homogenates generated a fraction enriched with D2, but deficient in peroxisome markers including catalase, PEX19, and ABCD3 (D3). Electron microscopic imaging of this fraction confirmed the presence of D2 protein on an organelle with a dense matrix and a diameter of ∼200 nm, the typical structure and size of a microperoxisome. D2 and PEX19 antibodies recognized distinct structures in mouse adipose. Immunoisolation of the D2-containing compartment confirmed the scarcity of PEX19 and proteomic profiling revealed the presence of proteins associated with peroxisome, endoplasmic reticulum (ER), and mitochondria. D2 is localized to a distinct class of peroxisomes that lack many peroxisome proteins, and may associate physically with mitochondria and the ER.« less

Standard Reporting Requirements for Biological Samples in Metabolomics Experiments: Environmental Context

EPA Science Inventory

Metabolomic technologies are increasingly being applied to study biological questions in a range of different settings from clinical through to environmental. As with other high-throughput technologies, such as those used in transcriptomics and proteomics, metabolomics continues...

Accurate, Sensitive, and Precise Multiplexed Proteomics Using the Complement Reporter Ion Cluster

DOE PAGES

Sonnett, Matthew; Yeung, Eyan; Wuhr, Martin

2018-03-09

We present that quantitative analysis of proteomes across multiple time points, organelles, and perturbations is essential for understanding both fundamental biology and disease states. The development of isobaric tags (e.g. TMT) have enabled the simultaneous measurement of peptide abundances across several different conditions. These multiplexed approaches are promising in principle because of advantages in throughput and measurement quality. However, in practice existing multiplexing approaches suffer from key limitations. In its simple implementation (TMT-MS2), measurements are distorted by chemical noise leading to poor measurement accuracy. The current state-of-the-art (TMT-MS3) addresses this, but requires specialized quadrupole-iontrap-Orbitrap instrumentation. The complement reporter ion approachmore » (TMTc) produces high accuracy measurements and is compatible with many more instruments, like quadrupole-Orbitraps. However, the required deconvolution of the TMTc cluster leads to poor measurement precision. Here, we introduce TMTc+, which adds the modeling of the MS2-isolation step into the deconvolution algorithm. The resulting measurements are comparable in precision to TMT-MS3/MS2. The improved duty cycle, and lower filtering requirements make TMTc+ more sensitive than TMT-MS3 and comparable with TMT-MS2. At the same time, unlike TMT-MS2, TMTc+ is exquisitely able to distinguish signal from chemical noise even outperforming TMT-MS3. Lastly, we compare TMTc+ to quantitative label-free proteomics of total HeLa lysate and find that TMTc+ quantifies 7.8k versus 3.9k proteins in a 5-plex sample. At the same time the median coefficient of variation improves from 13% to 4%. Furthermore, TMTc+ advances quantitative proteomics by enabling accurate, sensitive, and precise multiplexed experiments on more commonly used instruments.« less

Accurate, Sensitive, and Precise Multiplexed Proteomics Using the Complement Reporter Ion Cluster

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sonnett, Matthew; Yeung, Eyan; Wuhr, Martin

We present that quantitative analysis of proteomes across multiple time points, organelles, and perturbations is essential for understanding both fundamental biology and disease states. The development of isobaric tags (e.g. TMT) have enabled the simultaneous measurement of peptide abundances across several different conditions. These multiplexed approaches are promising in principle because of advantages in throughput and measurement quality. However, in practice existing multiplexing approaches suffer from key limitations. In its simple implementation (TMT-MS2), measurements are distorted by chemical noise leading to poor measurement accuracy. The current state-of-the-art (TMT-MS3) addresses this, but requires specialized quadrupole-iontrap-Orbitrap instrumentation. The complement reporter ion approachmore » (TMTc) produces high accuracy measurements and is compatible with many more instruments, like quadrupole-Orbitraps. However, the required deconvolution of the TMTc cluster leads to poor measurement precision. Here, we introduce TMTc+, which adds the modeling of the MS2-isolation step into the deconvolution algorithm. The resulting measurements are comparable in precision to TMT-MS3/MS2. The improved duty cycle, and lower filtering requirements make TMTc+ more sensitive than TMT-MS3 and comparable with TMT-MS2. At the same time, unlike TMT-MS2, TMTc+ is exquisitely able to distinguish signal from chemical noise even outperforming TMT-MS3. Lastly, we compare TMTc+ to quantitative label-free proteomics of total HeLa lysate and find that TMTc+ quantifies 7.8k versus 3.9k proteins in a 5-plex sample. At the same time the median coefficient of variation improves from 13% to 4%. Furthermore, TMTc+ advances quantitative proteomics by enabling accurate, sensitive, and precise multiplexed experiments on more commonly used instruments.« less

Mass spectrometry-assisted gel-based proteomics in cancer biomarker discovery: approaches and application

PubMed Central

Huang, Rongrong; Chen, Zhongsi; He, Lei; He, Nongyue; Xi, Zhijiang; Li, Zhiyang; Deng, Yan; Zeng, Xin

2017-01-01

There is a critical need for the discovery of novel biomarkers for early detection and targeted therapy of cancer, a major cause of deaths worldwide. In this respect, proteomic technologies, such as mass spectrometry (MS), enable the identification of pathologically significant proteins in various types of samples. MS is capable of high-throughput profiling of complex biological samples including blood, tissues, urine, milk, and cells. MS-assisted proteomics has contributed to the development of cancer biomarkers that may form the foundation for new clinical tests. It can also aid in elucidating the molecular mechanisms underlying cancer. In this review, we discuss MS principles and instrumentation as well as approaches in MS-based proteomics, which have been employed in the development of potential biomarkers. Furthermore, the challenges in validation of MS biomarkers for their use in clinical practice are also reviewed. PMID:28912895

Proteomic Profiling of Mitochondrial Enzymes during Skeletal Muscle Aging.

PubMed

Staunton, Lisa; O'Connell, Kathleen; Ohlendieck, Kay

2011-03-07

Mitochondria are of central importance for energy generation in skeletal muscles. Expression changes or functional alterations in mitochondrial enzymes play a key role during myogenesis, fibre maturation, and various neuromuscular pathologies, as well as natural fibre aging. Mass spectrometry-based proteomics suggests itself as a convenient large-scale and high-throughput approach to catalogue the mitochondrial protein complement and determine global changes during health and disease. This paper gives a brief overview of the relatively new field of mitochondrial proteomics and discusses the findings from recent proteomic surveys of mitochondrial elements in aged skeletal muscles. Changes in the abundance, biochemical activity, subcellular localization, and/or posttranslational modifications in key mitochondrial enzymes might be useful as novel biomarkers of aging. In the long term, this may advance diagnostic procedures, improve the monitoring of disease progression, help in the testing of side effects due to new drug regimes, and enhance our molecular understanding of age-related muscle degeneration.

Maize-Pathogen Interactions: An Ongoing Combat from a Proteomics Perspective.

PubMed

Pechanova, Olga; Pechan, Tibor

2015-11-30

Maize (Zea mays L.) is a host to numerous pathogenic species that impose serious diseases to its ear and foliage, negatively affecting the yield and the quality of the maize crop. A considerable amount of research has been carried out to elucidate mechanisms of maize-pathogen interactions with a major goal to identify defense-associated proteins. In this review, we summarize interactions of maize with its agriculturally important pathogens that were assessed at the proteome level. Employing differential analyses, such as the comparison of pathogen-resistant and susceptible maize varieties, as well as changes in maize proteomes after pathogen challenge, numerous proteins were identified as possible candidates in maize resistance. We describe findings of various research groups that used mainly mass spectrometry-based, high through-put proteomic tools to investigate maize interactions with fungal pathogens Aspergillus flavus, Fusarium spp., and Curvularia lunata, and viral agents Rice Black-streaked Dwarf Virus and Sugarcane Mosaic Virus.

Maize-Pathogen Interactions: An Ongoing Combat from a Proteomics Perspective

PubMed Central

Pechanova, Olga; Pechan, Tibor

2015-01-01

Maize (Zea mays L.) is a host to numerous pathogenic species that impose serious diseases to its ear and foliage, negatively affecting the yield and the quality of the maize crop. A considerable amount of research has been carried out to elucidate mechanisms of maize-pathogen interactions with a major goal to identify defense-associated proteins. In this review, we summarize interactions of maize with its agriculturally important pathogens that were assessed at the proteome level. Employing differential analyses, such as the comparison of pathogen-resistant and susceptible maize varieties, as well as changes in maize proteomes after pathogen challenge, numerous proteins were identified as possible candidates in maize resistance. We describe findings of various research groups that used mainly mass spectrometry-based, high through-put proteomic tools to investigate maize interactions with fungal pathogens Aspergillus flavus, Fusarium spp., and Curvularia lunata, and viral agents Rice Black-streaked Dwarf Virus and Sugarcane Mosaic Virus. PMID:26633370

A continuous high-throughput bioparticle sorter based on 3D traveling-wave dielectrophoresis.

PubMed

Cheng, I-Fang; Froude, Victoria E; Zhu, Yingxi; Chang, Hsueh-Chia; Chang, Hsien-Chang

2009-11-21

We present a high throughput (maximum flow rate approximately 10 microl/min or linear velocity approximately 3 mm/s) continuous bio-particle sorter based on 3D traveling-wave dielectrophoresis (twDEP) at an optimum AC frequency of 500 kHz. The high throughput sorting is achieved with a sustained twDEP particle force normal to the continuous through-flow, which is applied over the entire chip by a single 3D electrode array. The design allows continuous fractionation of micron-sized particles into different downstream sub-channels based on differences in their twDEP mobility on both sides of the cross-over. Conventional DEP is integrated upstream to focus the particles into a single levitated queue to allow twDEP sorting by mobility difference and to minimize sedimentation and field-induced lysis. The 3D electrode array design minimizes the offsetting effect of nDEP (negative DEP with particle force towards regions with weak fields) on twDEP such that both forces increase monotonically with voltage to further increase the throughput. Effective focusing and separation of red blood cells from debris-filled heterogeneous samples are demonstrated, as well as size-based separation of poly-dispersed liposome suspensions into two distinct bands at 2.3 to 4.6 microm and 1.5 to 2.7 microm, at the highest throughput recorded in hand-held chips of 6 microl/min.

An improved stable isotope N-terminal labeling approach with light/heavy TMPP to automate proteogenomics data validation: dN-TOP.

PubMed

Bertaccini, Diego; Vaca, Sebastian; Carapito, Christine; Arsène-Ploetze, Florence; Van Dorsselaer, Alain; Schaeffer-Reiss, Christine

2013-06-07

In silico gene prediction has proven to be prone to errors, especially regarding precise localization of start codons that spread in subsequent biological studies. Therefore, the high throughput characterization of protein N-termini is becoming an emerging challenge in the proteomics and especially proteogenomics fields. The trimethoxyphenyl phosphonium (TMPP) labeling approach (N-TOP) is an efficient N-terminomic approach that allows the characterization of both N-terminal and internal peptides in a single experiment. Due to its permanent positive charge, TMPP labeling strongly affects MS/MS fragmentation resulting in unadapted scoring of TMPP-derivatized peptide spectra by classical search engines. This behavior has led to difficulties in validating TMPP-derivatized peptide identifications with usual score filtering and thus to low/underestimated numbers of identified N-termini. We present herein a new strategy (dN-TOP) that overwhelmed the previous limitation allowing a confident and automated N-terminal peptide validation thanks to a combined labeling with light and heavy TMPP reagents. We show how this double labeling allows increasing the number of validated N-terminal peptides. This strategy represents a considerable improvement to the well-established N-TOP method with an enhanced and accelerated data processing making it now fully compatible with high-throughput proteogenomics studies.

Astragaloside IV Attenuates Glutamate-Induced Neurotoxicity in PC12 Cells through Raf-MEK-ERK Pathway.

PubMed

Yue, Rongcai; Li, Xia; Chen, Bingyang; Zhao, Jing; He, Weiwei; Yuan, Hu; Yuan, Xing; Gao, Na; Wu, Guozhen; Jin, Huizi; Shan, Lei; Zhang, Weidong

2015-01-01

Astragaloside IV (AGS-IV) is a main active ingredient of Astragalus membranaceus Bunge, a medicinal herb prescribed as an immunostimulant, hepatoprotective, antiperspirant, a diuretic or a tonic as documented in Chinese Materia Medica. In the present study, we employed a high-throughput comparative proteomic approach based on 2D-nano-LC-MS/MS to investigate the possible mechanism of action involved in the neuroprotective effect of AGS-IV against glutamate-induced neurotoxicity in PC12 cells. Differential proteins were identified, among which 13 proteins survived the stringent filter criteria and were further included for functional discussion. Two proteins (vimentin and Gap43) were randomly selected, and their expression levels were further confirmed by western blots analysis. The results matched well with those of proteomics. Furthermore, network analysis of protein-protein interactions (PPI) and pathways enrichment with AGS-IV associated proteins were carried out to illustrate its underlying molecular mechanism. Proteins associated with signal transduction, immune system, signaling molecules and interaction, and energy metabolism play important roles in neuroprotective effect of AGS-IV and Raf-MEK-ERK pathway was involved in the neuroprotective effect of AGS-IV against glutamate-induced neurotoxicity in PC12 cells. This study demonstrates that comparative proteomics based on shotgun approach is a valuable tool for molecular mechanism studies, since it allows the simultaneously evaluate the global proteins alterations.

Highly Efficient Proteolysis Accelerated by Electromagnetic Waves for Peptide Mapping

PubMed Central

Chen, Qiwen; Liu, Ting; Chen, Gang

2011-01-01

Proteomics will contribute greatly to the understanding of gene functions in the post-genomic era. In proteome research, protein digestion is a key procedure prior to mass spectrometry identification. During the past decade, a variety of electromagnetic waves have been employed to accelerate proteolysis. This review focuses on the recent advances and the key strategies of these novel proteolysis approaches for digesting and identifying proteins. The subjects covered include microwave-accelerated protein digestion, infrared-assisted proteolysis, ultraviolet-enhanced protein digestion, laser-assisted proteolysis, and future prospects. It is expected that these novel proteolysis strategies accelerated by various electromagnetic waves will become powerful tools in proteome research and will find wide applications in high throughput protein digestion and identification. PMID:22379392

Selected reaction monitoring mass spectrometry: a methodology overview.

PubMed

Ebhardt, H Alexander

2014-01-01

Moving past the discovery phase of proteomics, the term targeted proteomics combines multiple approaches investigating a certain set of proteins in more detail. One such targeted proteomics approach is the combination of liquid chromatography and selected or multiple reaction monitoring mass spectrometry (SRM, MRM). SRM-MS requires prior knowledge of the fragmentation pattern of peptides, as the presence of the analyte in a sample is determined by measuring the m/z values of predefined precursor and fragment ions. Using scheduled SRM-MS, many analytes can robustly be monitored allowing for high-throughput sample analysis of the same set of proteins over many conditions. In this chapter, fundaments of SRM-MS are explained as well as an optimized SRM pipeline from assay generation to data analyzed.

Emerging proteomics biomarkers and prostate cancer burden in Africa

PubMed Central

Adeola, Henry A.; Blackburn, Jonathan M.; Rebbeck, Timothy R.; Zerbini, Luiz F.

2017-01-01

Various biomarkers have emerged via high throughput omics-based approaches for use in diagnosis, treatment, and monitoring of prostate cancer. Many of these have yet to be demonstrated as having value in routine clinical practice. Moreover, there is a dearth of information on validation of these emerging prostate biomarkers within African cohorts, despite the huge burden and aggressiveness of prostate cancer in men of African descent. This review focusses of the global landmark achievements in prostate cancer proteomics biomarker discovery and the potential for clinical implementation of these biomarkers in Africa. Biomarker validation processes at the preclinical, translational and clinical research level are discussed here, as are the challenges and prospects for the evaluation and use of novel proteomic prostate cancer biomarkers. PMID:28388542

Emerging proteomics biomarkers and prostate cancer burden in Africa.

PubMed

Adeola, Henry A; Blackburn, Jonathan M; Rebbeck, Timothy R; Zerbini, Luiz F

2017-06-06

Various biomarkers have emerged via high throughput omics-based approaches for use in diagnosis, treatment, and monitoring of prostate cancer. Many of these have yet to be demonstrated as having value in routine clinical practice. Moreover, there is a dearth of information on validation of these emerging prostate biomarkers within African cohorts, despite the huge burden and aggressiveness of prostate cancer in men of African descent. This review focusses of the global landmark achievements in prostate cancer proteomics biomarker discovery and the potential for clinical implementation of these biomarkers in Africa. Biomarker validation processes at the preclinical, translational and clinical research level are discussed here, as are the challenges and prospects for the evaluation and use of novel proteomic prostate cancer biomarkers.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kolker, Eugene

Our project focused primarily on analysis of different types of data produced by global high-throughput technologies, data integration of gene annotation, and gene and protein expression information, as well as on getting a better functional annotation of Shewanella genes. Specifically, four of our numerous major activities and achievements include the development of: statistical models for identification and expression proteomics, superior to currently available approaches (including our own earlier ones); approaches to improve gene annotations on the whole-organism scale; standards for annotation, transcriptomics and proteomics approaches; and generalized approaches for data integration of gene annotation, gene and protein expression information.

VESPA: Software to Facilitate Genomic Annotation of Prokaryotic Organisms Through Integration of Proteomic and Transcriptomic Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Peterson, Elena S.; McCue, Lee Ann; Rutledge, Alexandra C.

2012-04-25

Visual Exploration and Statistics to Promote Annotation (VESPA) is an interactive visual analysis software tool that facilitates the discovery of structural mis-annotations in prokaryotic genomes. VESPA integrates high-throughput peptide-centric proteomics data and oligo-centric or RNA-Seq transcriptomics data into a genomic context. The data may be interrogated via visual analysis across multiple levels of genomic resolution, linked searches, exports and interaction with BLAST to rapidly identify location of interest within the genome and evaluate potential mis-annotations.

Subnuclear foci quantification using high-throughput 3D image cytometry

NASA Astrophysics Data System (ADS)

Wadduwage, Dushan N.; Parrish, Marcus; Choi, Heejin; Engelward, Bevin P.; Matsudaira, Paul; So, Peter T. C.

2015-07-01

Ionising radiation causes various types of DNA damages including double strand breaks (DSBs). DSBs are often recognized by DNA repair protein ATM which forms gamma-H2AX foci at the site of the DSBs that can be visualized using immunohistochemistry. However most of such experiments are of low throughput in terms of imaging and image analysis techniques. Most of the studies still use manual counting or classification. Hence they are limited to counting a low number of foci per cell (5 foci per nucleus) as the quantification process is extremely labour intensive. Therefore we have developed a high throughput instrumentation and computational pipeline specialized for gamma-H2AX foci quantification. A population of cells with highly clustered foci inside nuclei were imaged, in 3D with submicron resolution, using an in-house developed high throughput image cytometer. Imaging speeds as high as 800 cells/second in 3D were achieved by using HiLo wide-field depth resolved imaging and a remote z-scanning technique. Then the number of foci per cell nucleus were quantified using a 3D extended maxima transform based algorithm. Our results suggests that while most of the other 2D imaging and manual quantification studies can count only up to about 5 foci per nucleus our method is capable of counting more than 100. Moreover we show that 3D analysis is significantly superior compared to the 2D techniques.

New approaches to high-throughput structure characterization of SH3 complexes: the example of Myosin-3 and Myosin-5 SH3 domains from S. cerevisiae.

PubMed

Musi, Valeria; Birdsall, Berry; Fernandez-Ballester, Gregorio; Guerrini, Remo; Salvatori, Severo; Serrano, Luis; Pastore, Annalisa

2006-04-01

SH3 domains are small protein modules that are involved in protein-protein interactions in several essential metabolic pathways. The availability of the complete genome and the limited number of clearly identifiable SH3 domains make the yeast Saccharomyces cerevisae an ideal proteomic-based model system to investigate the structural rules dictating the SH3-mediated protein interactions and to develop new tools to assist these studies. In the present work, we have determined the solution structure of the SH3 domain from Myo3 and modeled by homology that of the highly homologous Myo5, two myosins implicated in actin polymerization. We have then implemented an integrated approach that makes use of experimental and computational methods to characterize their binding properties. While accommodating their targets in the classical groove, the two domains have selectivity in both orientation and sequence specificity of the target peptides. From our study, we propose a consensus sequence that may provide a useful guideline to identify new natural partners and suggest a strategy of more general applicability that may be of use in other structural proteomic studies.

A high-throughput, multi-channel photon-counting detector with picosecond timing

NASA Astrophysics Data System (ADS)

Lapington, J. S.; Fraser, G. W.; Miller, G. M.; Ashton, T. J. R.; Jarron, P.; Despeisse, M.; Powolny, F.; Howorth, J.; Milnes, J.

2009-06-01

High-throughput photon counting with high time resolution is a niche application area where vacuum tubes can still outperform solid-state devices. Applications in the life sciences utilizing time-resolved spectroscopies, particularly in the growing field of proteomics, will benefit greatly from performance enhancements in event timing and detector throughput. The HiContent project is a collaboration between the University of Leicester Space Research Centre, the Microelectronics Group at CERN, Photek Ltd., and end-users at the Gray Cancer Institute and the University of Manchester. The goal is to develop a detector system specifically designed for optical proteomics, capable of high content (multi-parametric) analysis at high throughput. The HiContent detector system is being developed to exploit this niche market. It combines multi-channel, high time resolution photon counting in a single miniaturized detector system with integrated electronics. The combination of enabling technologies; small pore microchannel plate devices with very high time resolution, and high-speed multi-channel ASIC electronics developed for the LHC at CERN, provides the necessary building blocks for a high-throughput detector system with up to 1024 parallel counting channels and 20 ps time resolution. We describe the detector and electronic design, discuss the current status of the HiContent project and present the results from a 64-channel prototype system. In the absence of an operational detector, we present measurements of the electronics performance using a pulse generator to simulate detector events. Event timing results from the NINO high-speed front-end ASIC captured using a fast digital oscilloscope are compared with data taken with the proposed electronic configuration which uses the multi-channel HPTDC timing ASIC.

CPTAC Investigators Discuss Research Insights and Perspectives as part of ASBMB Journal Club - 12 Nov | Office of Cancer Clinical Proteomics Research

Cancer.gov

On Wednesday, November 12, 2014 from 2:00 PM to 3:00 PM EST, Daniel Liebler, PhD (Vanderbilt University) and Karin Rodland, PhD (Pacific Northwestern National Laboratory) and Ruedi Aebersold, PhD (Swiss Federal Institute of Technology) will share their research insight as part of the ASBMB Journal Club.  Both Doctors Liebler and Rodland are Principal Investigators in the NCI’s Clinical Proteomic Tumor Analysis Consortium.

3D pulsed laser-triggered high-speed microfluidic fluorescence-activated cell sorter

PubMed Central

Chen, Yue; Wu, Ting-Hsiang; Kung, Yu-Chun; Teitell, Michael A.; Chiou, Pei-Yu

2014-01-01

We report a 3D microfluidic pulsed laser-triggered fluorescence-activated cell sorter capable of sorting at a throughput of 23,000 cells sec−1 with 90% purity in high-purity mode and at a throughput of 45,000 cells sec−1 with 45% purity in enrichment mode in one stage and in a single channel. This performance is realized by exciting laser-induced cavitation bubbles in a 3D PDMS microfluidic channel to generate high-speed liquid jets that deflect detected fluorescent cells and particles focused by 3D sheath flows. The ultrafast switching mechanism (20 μsec complete on-off cycle), small liquid jet perturbation volume, and three-dimensional sheath flow focusing for accurate timing control of fast (1.5 m sec−1) passing cells and particles are three critical factors enabling high-purity sorting at high-throughput in this sorter. PMID:23844418

PROTEOMICS IN ECOTOXICOLOGY: PROTEIN EXPRESSION PROFILING TO SCREEN CHEMICALS FOR ENDOCRINE ACTIVITY

EPA Science Inventory

Abstract for poster.

Current endocrine testing methods are animal intensive and lack the throughput necessary to screen large numbers of environmental chemicals for adverse effects. In this study, Matrix Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry...

Global analysis of the rat and human platelet proteome – the molecular blueprint for illustrating multi-functional platelets and cross-species function evolution

PubMed Central

Yu, Yanbao; Leng, Taohua; Yun, Dong; Liu, Na; Yao, Jun; Dai, Ying; Yang, Pengyuan; Chen, Xian

2013-01-01

Emerging evidences indicate that blood platelets function in multiple biological processes including immune response, bone metastasis and liver regeneration in addition to their known roles in hemostasis and thrombosis. Global elucidation of platelet proteome will provide the molecular base of these platelet functions. Here, we set up a high throughput platform for maximum exploration of the rat/human platelet proteome using integrated proteomics technologies, and then applied to identify the largest number of the proteins expressed in both rat and human platelets. After stringent statistical filtration, a total of 837 unique proteins matched with at least two unique peptides were precisely identified, making it the first comprehensive protein database so far for rat platelets. Meanwhile, quantitative analyses of the thrombin-stimulated platelets offered great insights into the biological functions of platelet proteins and therefore confirmed our global profiling data. A comparative proteomic analysis between rat and human platelets was also conducted, which revealed not only a significant similarity, but also an across-species evolutionary link that the orthologous proteins representing ‘core proteome’, and the ‘evolutionary proteome’ is actually a relatively static proteome. PMID:20443191

Analyzing large-scale proteomics projects with latent semantic indexing.

PubMed

Klie, Sebastian; Martens, Lennart; Vizcaíno, Juan Antonio; Côté, Richard; Jones, Phil; Apweiler, Rolf; Hinneburg, Alexander; Hermjakob, Henning

2008-01-01

Since the advent of public data repositories for proteomics data, readily accessible results from high-throughput experiments have been accumulating steadily. Several large-scale projects in particular have contributed substantially to the amount of identifications available to the community. Despite the considerable body of information amassed, very few successful analyses have been performed and published on this data, leveling off the ultimate value of these projects far below their potential. A prominent reason published proteomics data is seldom reanalyzed lies in the heterogeneous nature of the original sample collection and the subsequent data recording and processing. To illustrate that at least part of this heterogeneity can be compensated for, we here apply a latent semantic analysis to the data contributed by the Human Proteome Organization's Plasma Proteome Project (HUPO PPP). Interestingly, despite the broad spectrum of instruments and methodologies applied in the HUPO PPP, our analysis reveals several obvious patterns that can be used to formulate concrete recommendations for optimizing proteomics project planning as well as the choice of technologies used in future experiments. It is clear from these results that the analysis of large bodies of publicly available proteomics data by noise-tolerant algorithms such as the latent semantic analysis holds great promise and is currently underexploited.

Integrative FourD omics approach profiles the target network of the carbon storage regulatory system.

PubMed

Sowa, Steven W; Gelderman, Grant; Leistra, Abigail N; Buvanendiran, Aishwarya; Lipp, Sarah; Pitaktong, Areen; Vakulskas, Christopher A; Romeo, Tony; Baldea, Michael; Contreras, Lydia M

2017-02-28

Multi-target regulators represent a largely untapped area for metabolic engineering and anti-bacterial development. These regulators are complex to characterize because they often act at multiple levels, affecting proteins, transcripts and metabolites. Therefore, single omics experiments cannot profile their underlying targets and mechanisms. In this work, we used an Integrative FourD omics approach (INFO) that consists of collecting and analyzing systems data throughout multiple time points, using multiple genetic backgrounds, and multiple omics approaches (transcriptomics, proteomics and high throughput sequencing crosslinking immunoprecipitation) to evaluate simultaneous changes in gene expression after imposing an environmental stress that accentuates the regulatory features of a network. Using this approach, we profiled the targets and potential regulatory mechanisms of a global regulatory system, the well-studied carbon storage regulatory (Csr) system of Escherichia coli, which is widespread among bacteria. Using 126 sets of proteomics and transcriptomics data, we identified 136 potential direct CsrA targets, including 50 novel ones, categorized their behaviors into distinct regulatory patterns, and performed in vivo fluorescence-based follow up experiments. The results of this work validate 17 novel mRNAs as authentic direct CsrA targets and demonstrate a generalizable strategy to integrate multiple lines of omics data to identify a core pool of regulator targets. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Quantitative proteomic analysis for high-throughput screening of differential glycoproteins in hepatocellular carcinoma serum

PubMed Central

Gao, Hua-Jun; Chen, Ya-Jing; Zuo, Duo; Xiao, Ming-Ming; Li, Ying; Guo, Hua; Zhang, Ning; Chen, Rui-Bing

2015-01-01

Objective Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths. Novel serum biomarkers are required to increase the sensitivity and specificity of serum screening for early HCC diagnosis. This study employed a quantitative proteomic strategy to analyze the differential expression of serum glycoproteins between HCC and normal control serum samples. Methods Lectin affinity chromatography (LAC) was used to enrich glycoproteins from the serum samples. Quantitative mass spectrometric analysis combined with stable isotope dimethyl labeling and 2D liquid chromatography (LC) separations were performed to examine the differential levels of the detected proteins between HCC and control serum samples. Western blot was used to analyze the differential expression levels of the three serum proteins. Results A total of 2,280 protein groups were identified in the serum samples from HCC patients by using the 2D LC-MS/MS method. Up to 36 proteins were up-regulated in the HCC serum, whereas 19 proteins were down-regulated. Three differential glycoproteins, namely, fibrinogen gamma chain (FGG), FOS-like antigen 2 (FOSL2), and α-1,6-mannosylglycoprotein 6-β-N-acetylglucosaminyltransferase B (MGAT5B) were validated by Western blot. All these three proteins were up-regulated in the HCC serum samples. Conclusion A quantitative glycoproteomic method was established and proven useful to determine potential novel biomarkers for HCC. PMID:26487969

High throughput LC-MS/MS method for the simultaneous analysis of multiple vitamin D analytes in serum.

PubMed

Jenkinson, Carl; Taylor, Angela E; Hassan-Smith, Zaki K; Adams, John S; Stewart, Paul M; Hewison, Martin; Keevil, Brian G

2016-03-01

Recent studies suggest that vitamin D-deficiency is linked to increased risk of common human health problems. To define vitamin D 'status' most routine analytical methods quantify one particular vitamin D metabolite, 25-hydroxyvitamin D3 (25OHD3). However, vitamin D is characterized by complex metabolic pathways, and simultaneous measurement of multiple vitamin D metabolites may provide a more accurate interpretation of vitamin D status. To address this we developed a high-throughput liquid chromatography-tandem mass spectrometry (LC-MS/MS) method to analyse multiple vitamin D analytes, with particular emphasis on the separation of epimer metabolites. A supportive liquid-liquid extraction (SLE) and LC-MS/MS method was developed to quantify 10 vitamin D metabolites as well as separation of an interfering 7α-hydroxy-4-cholesten-3-one (7αC4) isobar (precursor of bile acid), and validated by analysis of human serum samples. In a cohort of 116 healthy subjects, circulating concentrations of 25-hydroxyvitamin D3 (25OHD3), 3-epi-25-hydroxyvitamin D3 (3-epi-25OHD3), 24,25-dihydroxyvitamin D3 (24R,25(OH)2D3), 1,25-dihydroxyvitamin D3 (1α,25(OH)2D3), and 25-hydroxyvitamin D2 (25OHD2) were quantifiable using 220μL of serum, with 25OHD3 and 24R,25(OH)2D3 showing significant seasonal variations. This high-throughput LC-MS/MS method provides a novel strategy for assessing the impact of vitamin D on human health and disease. Copyright © 2016 Elsevier B.V. All rights reserved.

Interclonal proteomic responses to predator exposure in Daphnia magna may depend on predator composition of habitats.

PubMed

Otte, Kathrin A; Schrank, Isabella; Fröhlich, Thomas; Arnold, Georg J; Laforsch, Christian

2015-08-01

Phenotypic plasticity, the ability of one genotype to express different phenotypes in response to changing environmental conditions, is one of the most common phenomena characterizing the living world and is not only relevant for the ecology but also for the evolution of species. Daphnia, the water flea, is a textbook example for predator-induced phenotypic plastic defences; however, the analysis of molecular mechanisms underlying these inducible defences is still in its early stages. We exposed Daphnia magna to chemical cues of the predator Triops cancriformis to identify key processes underlying plastic defensive trait formation. To get a more comprehensive idea of this phenomenon, we studied four genotypes with five biological replicates each, originating from habitats characterized by different predator composition, ranging from predator-free habitats to habitats containing T. cancriformis. We analysed the morphologies as well as proteomes of predator-exposed and control animals. Three genotypes showed morphological changes when the predator was present. Using a high-throughput proteomics approach, we found 294 proteins which were significantly altered in their abundance after predator exposure in a general or genotype-dependent manner. Proteins connected to genotype-dependent responses were related to the cuticle, protein synthesis and calcium binding, whereas the yolk protein vitellogenin increased in abundance in all genotypes, indicating their involvement in a more general response. Furthermore, genotype-dependent responses at the proteome level were most distinct for the only genotype that shares its habitat with Triops. Altogether, our study provides new insights concerning genotype-dependent and general molecular processes involved in predator-induced phenotypic plasticity in D. magna. © 2015 John Wiley & Sons Ltd.

A complete mass spectrometric map for the analysis of the yeast proteome and its application to quantitative trait analysis

PubMed Central

Picotti, Paola; Clement-Ziza, Mathieu; Lam, Henry; Campbell, David S.; Schmidt, Alexander; Deutsch, Eric W.; Röst, Hannes; Sun, Zhi; Rinner, Oliver; Reiter, Lukas; Shen, Qin; Michaelson, Jacob J.; Frei, Andreas; Alberti, Simon; Kusebauch, Ulrike; Wollscheid, Bernd; Moritz, Robert; Beyer, Andreas; Aebersold, Ruedi

2013-01-01

Complete reference maps or datasets, like the genomic map of an organism, are highly beneficial tools for biological and biomedical research. Attempts to generate such reference datasets for a proteome so far failed to reach complete proteome coverage, with saturation apparent at approximately two thirds of the proteomes tested, even for the most thoroughly characterized proteomes. Here, we used a strategy based on high-throughput peptide synthesis and mass spectrometry to generate a close to complete reference map (97% of the genome-predicted proteins) of the S. cerevisiae proteome. We generated two versions of this mass spectrometric map one supporting discovery- (shotgun) and the other hypothesis-driven (targeted) proteomic measurements. The two versions of the map, therefore, constitute a complete set of proteomic assays to support most studies performed with contemporary proteomic technologies. The reference libraries can be browsed via a web-based repository and associated navigation tools. To demonstrate the utility of the reference libraries we applied them to a protein quantitative trait locus (pQTL) analysis, which requires measurement of the same peptides over a large number of samples with high precision. Protein measurements over a set of 78 S. cerevisiae strains revealed a complex relationship between independent genetic loci, impacting on the levels of related proteins. Our results suggest that selective pressure favors the acquisition of sets of polymorphisms that maintain the stoichiometry of protein complexes and pathways. PMID:23334424

A New Mass Spectrometry-compatible Degradable Surfactant for Tissue Proteomics

PubMed Central

Chang, Ying-Hua; Gregorich, Zachery R.; Chen, Albert J.; Hwang, Leekyoung; Guner, Huseyin; Yu, Deyang; Zhang, Jianyi; Ge, Ying

2015-01-01

Tissue proteomics is increasingly recognized for its role in biomarker discovery and disease mechanism investigation. However, protein solubility remains a significant challenge in mass spectrometry (MS)-based tissue proteomics. Conventional surfactants such as sodium dodecyl sulfate (SDS), the preferred surfactant for protein solubilization, are not compatible with MS. Herein, we have screened a library of surfactant-like compounds and discovered an MS-compatible degradable surfactant (MaSDeS) for tissue proteomics that solubilizes all categories of proteins with performance comparable to SDS. The use of MaSDeS in the tissue extraction significantly improves the total number of protein identifications from commonly used tissues, including tissue from the heart, liver, and lung. Notably, MaSDeS significantly enriches membrane proteins, which are often under-represented in proteomics studies. The acid degradable nature of MaSDeS makes it amenable for high-throughput mass spectrometry-based proteomics. In addition, the thermostability of MaSDeS allows for its use in experiments requiring high temperature to facilitate protein extraction and solubilization. Furthermore, we have shown that MaSDeS outperforms the other MS-compatible surfactants in terms of overall protein solubility and the total number of identified proteins in tissue proteomics. Thus, the use of MaSDeS will greatly advance tissue proteomics and realize its potential in basic biomedical and clinical research. MaSDeS could be utilized in a variety of proteomics studies as well as general biochemical and biological experiments that employ surfactants for protein solubilization. PMID:25589168

Quantifying protein-protein interactions in high throughput using protein domain microarrays.

PubMed

Kaushansky, Alexis; Allen, John E; Gordus, Andrew; Stiffler, Michael A; Karp, Ethan S; Chang, Bryan H; MacBeath, Gavin

2010-04-01

Protein microarrays provide an efficient way to identify and quantify protein-protein interactions in high throughput. One drawback of this technique is that proteins show a broad range of physicochemical properties and are often difficult to produce recombinantly. To circumvent these problems, we have focused on families of protein interaction domains. Here we provide protocols for constructing microarrays of protein interaction domains in individual wells of 96-well microtiter plates, and for quantifying domain-peptide interactions in high throughput using fluorescently labeled synthetic peptides. As specific examples, we will describe the construction of microarrays of virtually every human Src homology 2 (SH2) and phosphotyrosine binding (PTB) domain, as well as microarrays of mouse PDZ domains, all produced recombinantly in Escherichia coli. For domains that mediate high-affinity interactions, such as SH2 and PTB domains, equilibrium dissociation constants (K(D)s) for their peptide ligands can be measured directly on arrays by obtaining saturation binding curves. For weaker binding domains, such as PDZ domains, arrays are best used to identify candidate interactions, which are then retested and quantified by fluorescence polarization. Overall, protein domain microarrays provide the ability to rapidly identify and quantify protein-ligand interactions with minimal sample consumption. Because entire domain families can be interrogated simultaneously, they provide a powerful way to assess binding selectivity on a proteome-wide scale and provide an unbiased perspective on the connectivity of protein-protein interaction networks.

Isobaric Tags for Relative and Absolute Quantitation-Based Proteomic Analysis of Patent and Constricted Ductus Arteriosus Tissues Confirms the Systemic Regulation of Ductus Arteriosus Closure.

PubMed

Hong, Haifa; Ye, Lincai; Chen, Huiwen; Xia, Yu; Liu, Yue; Liu, Jinfen; Lu, Yanan; Zhang, Haibo

2015-08-01

We aimed to evaluate global changes in protein expression associated with patency by undertaking proteomic analysis of human constricted and patent ductus arteriosus (DA). Ten constricted and 10 patent human DAs were excised from infants with ductal-dependent heart disease during surgery. Using isobaric tags for relative and absolute quantitation-based quantitative proteomics, 132 differentially expressed proteins were identified. Of 132 proteins, voltage-gated sodium channel 1.3 (SCN3A), myosin 1d (Myo1d), Rho GTPase activating protein 26 (ARHGAP26), and retinitis pigmentosa 1 (RP1) were selected for validation by Western blot and quantitative real-time polymerase chain reaction analyses. Significant upregulation of SCN3A, Myo1d, and RP1 messenger RNA, and protein levels was observed in the patent DA group (all P ≤ 0.048). ARHGAP26 messenger RNA and protein levels were decreased in patent DA tissue (both P ≤ 0.018). Immunohistochemistry analysis revealed that Myo1d, ARHGAP26, and RP1 were specifically expressed in the subendothelial region of constricted DAs; however, diffuse expression of these proteins was noted in the patent group. Proteomic analysis revealed global changes in the expression of proteins that regulate oxygen sensing, ion channels, smooth muscle cell migration, nervous system, immune system, and metabolism, suggesting a basis for the systemic regulation of DA patency by diverse signaling pathways, which will be confirmed in further studies.

Differential Denaturation of Serum Proteome Reveals a Significant Amount of Hidden Information in Complex Mixtures of Proteins

PubMed Central

Polci, Maria Letizia; Rossi, Stefania; Cordella, Martina; Carlucci, Giuseppe; Marchetti, Paolo; Antonini-Cappellini, Giancarlo; Facchiano, Antonio; D'Arcangelo, Daniela; Facchiano, Francesco

2013-01-01

Recently developed proteomic technologies allow to profile thousands of proteins within a high-throughput approach towards biomarker discovery, although results are not as satisfactory as expected. In the present study we demonstrate that serum proteome denaturation is a key underestimated feature; in fact, a new differential denaturation protocol better discriminates serum proteins according to their electrophoretic mobility as compared to single-denaturation protocols. Sixty nine different denaturation treatments were tested and the 3 most discriminating ones were selected (TRIDENT analysis) and applied to human sera, showing a significant improvement of serum protein discrimination as confirmed by MALDI-TOF/MS and LC-MS/MS identification, depending on the type of denaturation applied. Thereafter sera from mice and patients carrying cutaneous melanoma were analyzed through TRIDENT. Nine and 8 protein bands were found differentially expressed in mice and human melanoma sera, compared to healthy controls (p<0.05); three of them were found, for the first time, significantly modulated: α2macroglobulin (down-regulated in melanoma, p<0.001), Apolipoprotein-E and Apolipoprotein-A1 (both up-regulated in melanoma, p<0.04), both in mice and humans. The modulation was confirmed by immunological methods. Other less abundant proteins (e.g. gelsolin) were found significantly modulated (p<0.05). Conclusions: i) serum proteome contains a large amount of information, still neglected, related to proteins folding; ii) a careful serum denaturation may significantly improve analytical procedures involving complex protein mixtures; iii) serum differential denaturation protocol highlights interesting proteomic differences between cancer and healthy sera. PMID:23533572

The Monkey King: a personal view of the long journey towards a proteomic Nirvana.

PubMed

Righetti, Pier Giorgio

2014-07-31

The review covers about fifty years of progress in "proteome" analysis, starting from primitive two-dimensional (2D) map attempts in the early sixties of last century. The polar star in 2D mapping arose in 1975 with the classic paper by O'Farrell in J Biol. Chem. It became the compass for all proteome navigators. Perfection came, though, only with the introduction of immobilized pH gradients, which fixed the polypeptide spots in the 2D plane. Great impetus in proteome analysis came with the introduction of informatic tools and creating databases, among which Swiss Prot remains the site of excellence. Towards the end of the nineties, 2D chromatography, epitomized by coupling strong cation exchangers with C18 resins, began to be a serious challenge to electrophoretic 2D mapping, although up to the present both techniques are still much in vogue and appear to give complementary results. Yet the migration of "proteomics" into the third millennium was made possible only by mass spectrometry (MS), which today represents the standard analytical tool in any lab dealing with proteomic analysis. Another major improvement has been the introduction of combinatorial peptide ligand libraries (CPLL), which, when properly used, enhance the visibility of low-abundance species by 3 to 4 orders of magnitude. Coupling MS to CPLLs permits the exploration of at least 8 orders of magnitude in dynamic range on any proteome. The present review is a personal recollection highlighting the developments that led to present-day proteomics on a long march that lasted about 50years. It is meant to give to young scientists an overview on how science grows, which ones are the quantum jumps in science and which research is of particular significance in general and in the field of proteomics in particular. It also gives some real-life episodes of greater-than-life figures. As such, it can be viewed as a tutorial to stimulate the young generation to be creative (and use their imagination too!).This article is part of a Special Issue entitled: 20years of Proteomics in memory of Viatliano Pallini. Guest Editors: Luca Bini, Juan J. Calvete, Natacha Turck, Denis Hochstrasser and Jean-Charles Sanchez. Copyright © 2013 Elsevier B.V. All rights reserved.

Protein identification and quantification from riverbank grape, Vitis riparia: Comparing SDS-PAGE and FASP-GPF techniques for shotgun proteomic analysis.

PubMed

George, Iniga S; Fennell, Anne Y; Haynes, Paul A

2015-09-01

Protein sample preparation optimisation is critical for establishing reproducible high throughput proteomic analysis. In this study, two different fractionation sample preparation techniques (in-gel digestion and in-solution digestion) for shotgun proteomics were used to quantitatively compare proteins identified in Vitis riparia leaf samples. The total number of proteins and peptides identified were compared between filter aided sample preparation (FASP) coupled with gas phase fractionation (GPF) and SDS-PAGE methods. There was a 24% increase in the total number of reproducibly identified proteins when FASP-GPF was used. FASP-GPF is more reproducible, less expensive and a better method than SDS-PAGE for shotgun proteomics of grapevine samples as it significantly increases protein identification across biological replicates. Total peptide and protein information from the two fractionation techniques is available in PRIDE with the identifier PXD001399 (http://proteomecentral.proteomexchange.org/dataset/PXD001399). © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The proteomic landscape of triple-negative breast cancer.

PubMed

Lawrence, Robert T; Perez, Elizabeth M; Hernández, Daniel; Miller, Chris P; Haas, Kelsey M; Irie, Hanna Y; Lee, Su-In; Blau, C Anthony; Villén, Judit

2015-04-28

Triple-negative breast cancer is a heterogeneous disease characterized by poor clinical outcomes and a shortage of targeted treatment options. To discover molecular features of triple-negative breast cancer, we performed quantitative proteomics analysis of twenty human-derived breast cell lines and four primary breast tumors to a depth of more than 12,000 distinct proteins. We used this data to identify breast cancer subtypes at the protein level and demonstrate the precise quantification of biomarkers, signaling proteins, and biological pathways by mass spectrometry. We integrated proteomics data with exome sequence resources to identify genomic aberrations that affect protein expression. We performed a high-throughput drug screen to identify protein markers of drug sensitivity and understand the mechanisms of drug resistance. The genome and proteome provide complementary information that, when combined, yield a powerful engine for therapeutic discovery. This resource is available to the cancer research community to catalyze further analysis and investigation. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Monitoring Peptidase Activities in Complex Proteomes by MALDI-TOF Mass Spectrometry

PubMed Central

Villanueva, Josep; Nazarian, Arpi; Lawlor, Kevin; Tempst, Paul

2009-01-01

Measuring enzymatic activities in biological fluids is a form of activity-based proteomics and may be utilized as a means of developing disease biomarkers. Activity-based assays allow amplification of output signals, thus potentially visualizing low-abundant enzymes on a virtually transparent whole-proteome background. The protocol presented here describes a semi-quantitative in vitro assay of proteolytic activities in complex proteomes by monitoring breakdown of designer peptide-substrates using robotic extraction and a MALDI-TOF mass spectrometric read-out. Relative quantitation of the peptide metabolites is done by comparison with spiked internal standards, followed by statistical analysis of the resulting mini-peptidome. Partial automation provides reproducibility and throughput essential for comparing large sample sets. The approach may be employed for diagnostic or predictive purposes and enables profiling of 96 samples in 30 hours. It could be tailored to many diagnostic and pharmaco-dynamic purposes, as a read-out of catalytic and metabolic activities in body fluids or tissues. PMID:19617888

Characterisation of the Manduca sexta sperm proteome: Genetic novelty underlying sperm composition in Lepidoptera.

PubMed

Whittington, Emma; Zhao, Qian; Borziak, Kirill; Walters, James R; Dorus, Steve

2015-07-01

The application of mass spectrometry based proteomics to sperm biology has greatly accelerated progress in understanding the molecular composition and function of spermatozoa. To date, these approaches have been largely restricted to model organisms, all of which produce a single sperm morph capable of oocyte fertilisation. Here we apply high-throughput mass spectrometry proteomic analysis to characterise sperm composition in Manduca sexta, the tobacco hornworm moth, which produce heteromorphic sperm, including one fertilisation competent (eupyrene) and one incompetent (apyrene) sperm type. This resulted in the high confidence identification of 896 proteins from a co-mixed sample of both sperm types, of which 167 are encoded by genes with strict one-to-one orthology in Drosophila melanogaster. Importantly, over half (55.1%) of these orthologous proteins have previously been identified in the D. melanogaster sperm proteome and exhibit significant conservation in quantitative protein abundance in sperm between the two species. Despite the complex nature of gene expression across spermatogenic stages, a significant correlation was also observed between sperm protein abundance and testis gene expression. Lepidopteran-specific sperm proteins (e.g., proteins with no homology to proteins in non-Lepidopteran taxa) were present in significantly greater abundance on average than those with homology outside the Lepidoptera. Given the disproportionate production of apyrene sperm (96% of all mature sperm in Manduca) relative to eupyrene sperm, these evolutionarily novel and highly abundant proteins are candidates for possessing apyrene-specific functions. Lastly, comparative genomic analyses of testis-expressed, ovary-expressed and sperm genes identified a concentration of novel sperm proteins shared amongst Lepidoptera of potential relevance to the evolutionary origin of heteromorphic spermatogenesis. As the first published Lepidopteran sperm proteome, this whole-cell proteomic characterisation will facilitate future evolutionary genetic and developmental studies of heteromorphic sperm production and parasperm function. Furthermore, the analyses presented here provide useful annotation information regarding sex-biased gene expression, novel Lepidopteran genes and gene function in the male gamete to complement the newly sequenced and annotated Manduca genome. Copyright © 2015 Elsevier Ltd. All rights reserved.

High throughput profile-profile based fold recognition for the entire human proteome.

PubMed

McGuffin, Liam J; Smith, Richard T; Bryson, Kevin; Sørensen, Søren-Aksel; Jones, David T

2006-06-07

In order to maintain the most comprehensive structural annotation databases we must carry out regular updates for each proteome using the latest profile-profile fold recognition methods. The ability to carry out these updates on demand is necessary to keep pace with the regular updates of sequence and structure databases. Providing the highest quality structural models requires the most intensive profile-profile fold recognition methods running with the very latest available sequence databases and fold libraries. However, running these methods on such a regular basis for every sequenced proteome requires large amounts of processing power. In this paper we describe and benchmark the JYDE (Job Yield Distribution Environment) system, which is a meta-scheduler designed to work above cluster schedulers, such as Sun Grid Engine (SGE) or Condor. We demonstrate the ability of JYDE to distribute the load of genomic-scale fold recognition across multiple independent Grid domains. We use the most recent profile-profile version of our mGenTHREADER software in order to annotate the latest version of the Human proteome against the latest sequence and structure databases in as short a time as possible. We show that our JYDE system is able to scale to large numbers of intensive fold recognition jobs running across several independent computer clusters. Using our JYDE system we have been able to annotate 99.9% of the protein sequences within the Human proteome in less than 24 hours, by harnessing over 500 CPUs from 3 independent Grid domains. This study clearly demonstrates the feasibility of carrying out on demand high quality structural annotations for the proteomes of major eukaryotic organisms. Specifically, we have shown that it is now possible to provide complete regular updates of profile-profile based fold recognition models for entire eukaryotic proteomes, through the use of Grid middleware such as JYDE.

A software suite for the generation and comparison of peptide arrays from sets of data collected by liquid chromatography-mass spectrometry.

PubMed

Li, Xiao-jun; Yi, Eugene C; Kemp, Christopher J; Zhang, Hui; Aebersold, Ruedi

2005-09-01

There is an increasing interest in the quantitative proteomic measurement of the protein contents of substantially similar biological samples, e.g. for the analysis of cellular response to perturbations over time or for the discovery of protein biomarkers from clinical samples. Technical limitations of current proteomic platforms such as limited reproducibility and low throughput make this a challenging task. A new LC-MS-based platform is able to generate complex peptide patterns from the analysis of proteolyzed protein samples at high throughput and represents a promising approach for quantitative proteomics. A crucial component of the LC-MS approach is the accurate evaluation of the abundance of detected peptides over many samples and the identification of peptide features that can stratify samples with respect to their genetic, physiological, or environmental origins. We present here a new software suite, SpecArray, that generates a peptide versus sample array from a set of LC-MS data. A peptide array stores the relative abundance of thousands of peptide features in many samples and is in a format identical to that of a gene expression microarray. A peptide array can be subjected to an unsupervised clustering analysis to stratify samples or to a discriminant analysis to identify discriminatory peptide features. We applied the SpecArray to analyze two sets of LC-MS data: one was from four repeat LC-MS analyses of the same glycopeptide sample, and another was from LC-MS analysis of serum samples of five male and five female mice. We demonstrate through these two study cases that the SpecArray software suite can serve as an effective software platform in the LC-MS approach for quantitative proteomics.

Protein Biomarkers for Insulin Resistance and Type 2 Diabetes Risk in Two Large Community Cohorts

PubMed Central

Nowak, Christoph; Sundström, Johan; Gustafsson, Stefan; Giedraitis, Vilmantas; Lind, Lars; Ingelsson, Erik; Fall, Tove

2016-01-01

Insulin resistance (IR) is a precursor of type 2 diabetes (T2D), and improved risk prediction and understanding of the pathogenesis are needed. We used a novel high-throughput 92-protein assay to identify circulating biomarkers for HOMA of IR in two cohorts of community residents without diabetes (n = 1,367) (mean age 73 ± 3.6 years). Adjusted linear regression identified cathepsin D and confirmed six proteins (leptin, renin, interleukin-1 receptor antagonist [IL-1ra], hepatocyte growth factor, fatty acid–binding protein 4, and tissue plasminogen activator [t-PA]) as IR biomarkers. Mendelian randomization analysis indicated a positive causal effect of IR on t-PA concentrations. Two biomarkers, IL-1ra (hazard ratio [HR] 1.28, 95% CI 1.03–1.59) and t-PA (HR 1.30, 1.02–1.65) were associated with incident T2D, and t-PA predicted 5-year transition to hyperglycemia (odds ratio 1.30, 95% CI 1.02–1.65). Additional adjustment for fasting glucose rendered both coefficients insignificant and revealed an association between renin and T2D (HR 0.79, 0.62–0.99). LASSO regression suggested a risk model including IL-1ra, t-PA, and the Framingham Offspring Study T2D score, but prediction improvement was nonsignificant (difference in C-index 0.02, 95% CI −0.08 to 0.12) over the T2D score only. In conclusion, proteomic blood profiling indicated cathepsin D as a new IR biomarker and suggested a causal effect of IR on t-PA. PMID:26420861

CIAN - Cell Imaging and Analysis Network at the Biology Department of McGill University

PubMed Central

Lacoste, J.; Lesage, G.; Bunnell, S.; Han, H.; Küster-Schöck, E.

2010-01-01

CF-31 The Cell Imaging and Analysis Network (CIAN) provides services and tools to researchers in the field of cell biology from within or outside Montreal's McGill University community. CIAN is composed of six scientific platforms: Cell Imaging (confocal and fluorescence microscopy), Proteomics (2-D protein gel electrophoresis and DiGE, fluorescent protein analysis), Automation and High throughput screening (Pinning robot and liquid handler), Protein Expression for Antibody Production, Genomics (real-time PCR), and Data storage and analysis (cluster, server, and workstations). Users submit project proposals, and can obtain training and consultation in any aspect of the facility, or initiate projects with the full-service platforms. CIAN is designed to facilitate training, enhance interactions, as well as share and maintain resources and expertise.

Determination of burn patient outcome by large-scale quantitative discovery proteomics

PubMed Central

Finnerty, Celeste C.; Jeschke, Marc G.; Qian, Wei-Jun; Kaushal, Amit; Xiao, Wenzhong; Liu, Tao; Gritsenko, Marina A.; Moore, Ronald J.; Camp, David G.; Moldawer, Lyle L.; Elson, Constance; Schoenfeld, David; Gamelli, Richard; Gibran, Nicole; Klein, Matthew; Arnoldo, Brett; Remick, Daniel; Smith, Richard D.; Davis, Ronald; Tompkins, Ronald G.; Herndon, David N.

2013-01-01

Objective Emerging proteomics techniques can be used to establish proteomic outcome signatures and to identify candidate biomarkers for survival following traumatic injury. We applied high-resolution liquid chromatography-mass spectrometry (LC-MS) and multiplex cytokine analysis to profile the plasma proteome of survivors and non-survivors of massive burn injury to determine the proteomic survival signature following a major burn injury. Design Proteomic discovery study. Setting Five burn hospitals across the U.S. Patients Thirty-two burn patients (16 non-survivors and 16 survivors), 19–89 years of age, were admitted within 96 h of injury to the participating hospitals with burns covering >20% of the total body surface area and required at least one surgical intervention. Interventions None. Measurements and Main Results We found differences in circulating levels of 43 proteins involved in the acute phase response, hepatic signaling, the complement cascade, inflammation, and insulin resistance. Thirty-two of the proteins identified were not previously known to play a role in the response to burn. IL-4, IL-8, GM-CSF, MCP-1, and β2-microglobulin correlated well with survival and may serve as clinical biomarkers. Conclusions These results demonstrate the utility of these techniques for establishing proteomic survival signatures and for use as a discovery tool to identify candidate biomarkers for survival. This is the first clinical application of a high-throughput, large-scale LC-MS-based quantitative plasma proteomic approach for biomarker discovery for the prediction of patient outcome following burn, trauma or critical illness. PMID:23507713

Development of proteome-wide binding reagents for research and diagnostics.

PubMed

Taussig, Michael J; Schmidt, Ronny; Cook, Elizabeth A; Stoevesandt, Oda

2013-12-01

Alongside MS, antibodies and other specific protein-binding molecules have a special place in proteomics as affinity reagents in a toolbox of applications for determining protein location, quantitative distribution and function (affinity proteomics). The realisation that the range of research antibodies available, while apparently vast is nevertheless still very incomplete and frequently of uncertain quality, has stimulated projects with an objective of raising comprehensive, proteome-wide sets of protein binders. With progress in automation and throughput, a remarkable number of recent publications refer to the practical possibility of selecting binders to every protein encoded in the genome. Here we review the requirements of a pipeline of production of protein binders for the human proteome, including target prioritisation, antigen design, 'next generation' methods, databases and the approaches taken by ongoing projects in Europe and the USA. While the task of generating affinity reagents for all human proteins is complex and demanding, the benefits of well-characterised and quality-controlled pan-proteome binder resources for biomedical research, industry and life sciences in general would be enormous and justify the effort. Given the technical, personnel and financial resources needed to fulfil this aim, expansion of current efforts may best be addressed through large-scale international collaboration. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

USING PROTEOMICS TO IMPROVE RISK ASSESSMENT OF HUMAN EXPOSURE TO ENVIRONMENTAL AGENTS

EPA Science Inventory

Using Proteomics to Improve Risk Assessment of Human Exposure to Environmental Agents.
Authors: Witold M. Winnik
Key Words (4): Proteomics, LC/MS, Western Blots, 1D and 2D gel electrophoresis, toxicity

The goal of this project is to use proteomics for the character...

A DATABASE FOR TRACKING TOXICOGENOMIC SAMPLES AND PROCEDURES WITH GENOMIC, PROTEOMIC AND METABONOMIC COMPONENTS

EPA Science Inventory

A Database for Tracking Toxicogenomic Samples and Procedures with Genomic, Proteomic and Metabonomic Components
Wenjun Bao1, Jennifer Fostel2, Michael D. Waters2, B. Alex Merrick2, Drew Ekman3, Mitchell Kostich4, Judith Schmid1, David Dix1
Office of Research and Developmen...

Proteomic Analysis to Identify Functional Molecules in Drug Resistance Caused by E-Cadherin Knockdown in 3D-Cultured Colorectal Cancer Models

DTIC Science & Technology

2014-09-01

total number of 538 phosphopeptides were identified, among which 350 phosphopeptides had been identified with the first round of TiO2 enrichment and 430...year research and the collection of proteomic and phosphoproteomic data is still in process. PRODUCTS Manuscripts: Yue XS , Hummon AB. Combining...of IMAC and TiO2 enrichment methods to increase phosphoproteomic identifications, manuscript in preparation. Yue XS , Hummon AB. Proteomic and

Subnanogram proteomics: impact of LC column selection, MS instrumentation and data analysis strategy on proteome coverage for trace samples

DOE PAGES

Zhu, Ying; Zhao, Rui; Piehowski, Paul D.; ...

2017-09-01

One of the greatest challenges for mass spectrometry (MS)-based proteomics is the limited ability to analyze small samples. Here in this study, we investigate the relative contributions of liquid chromatography (LC), MS instrumentation and data analysis methods with the aim of improving proteome coverage for sample sizes ranging from 0.5 ng to 50 ng. We show that the LC separations utilizing 30-μm-i.d. columns increase signal intensity by >3-fold relative to those using 75-μm-i.d. columns, leading to 32% increase in peptide identifications. The Orbitrap Fusion Lumos MS significantly boosted both sensitivity and sequencing speed relative to earlier generation Orbitraps (e.g., LTQ-Orbitrap),more » leading to a ~3-fold increase in peptide identifications and 1.7-fold increase in identified protein groups for 2 ng tryptic digests of the bacterium S. oneidensis. The Match Between Runs algorithm of open-source MaxQuant software further increased proteome coverage by ~95% for 0.5 ng samples and by ~42% for 2 ng samples. Using the best combination of the above variables, we were able to identify >3,000 proteins from 10 ng tryptic digests from both HeLa and THP-1 mammalian cell lines. We also identified >950 proteins from subnanogram archaeal/bacterial cocultures. Finally, the present ultrasensitive LC-MS platform achieves a level of proteome coverage not previously realized for ultra-small sample loadings, and is expected to facilitate the analysis of subnanogram samples, including single mammalian cells.« less

A Robust Two-Dimensional Separation of Intact Proteins for Bottom-Up Tandem Mass Spectrometry of the Human CSF Proteome

PubMed Central

Bora, Adriana; Anderson, Carol; Bachani, Muznabanu; Nath, Avindra; Cotter, Robert J.

2012-01-01

The cerebrospinal fluid (CSF) is produced in the brain by cells in the choroid plexus at a rate of 500mL/day. It is the only body fluid in direct contact with the brain. Thus, any changes in the CSF composition will reflect pathological processes and make CSF a potential source of biomarkers for different disease states. Proteomics offers a comprehensive view of the proteins found in CSF. In this study, we use a recently developed non-gel based method of sample preparation of CSF followed by liquid chromatography high accuracy mass spectrometry (LC-MS) for MS and MS/MS analyses, allowing unambiguous identification of peptides/proteins. Gel-eluted liquid fraction entrapment electrophoresis (Gelfree) is used to separate a CSF complex protein mixture in 12 user-selectable liquid-phase molecular weight fractions. Using this high throughput workflow we have been able to separate CSF intact proteins over a broad mass range 3.5 kDa-100 kDa with high resolution between 15 kDa and 100 kDa in 2 hours and 40 min. We have completely eliminated albumin and were able to interrogate the low abundance CSF proteins in a highly reproducible manner from different CSF samples in the same time. Using LC-MS as a downstream analysis, we identified 368 proteins using MidiTrap G-10 desalting columns and 166 proteins (including 57 unique proteins) using Zeba spin columns with 5% false discovery rate (FDR). Prostaglandin D2 synthase, Chromogranin A, Apolipoprotein E, Chromogranin B, Secretogranin III, Cystatin C, VGF nerve growth factor, Cadherin 2 are a few of the proteins that were characterized. The Gelfree-LC-MS is a robust method for the analysis of the human proteome that we will use to develop biomarkers for several neurodegenerative diseases and to quantitate these markers using multiple reaction monitoring. PMID:22537003

Universal Solid-phase Reversible Sample-Prep for Concurrent Proteome and N-glycome Characterization

PubMed Central

Zhou, Hui; Morley, Samantha; Kostel, Stephen; Freeman, Michael R.; Joshi, Vivek; Brewster, David; Lee, Richard S.

2017-01-01

SUMMARY We describe a novel Solid-phase Reversible Sample-Prep (SRS) platform, which enables rapid sample preparation for concurrent proteome and N-glycome characterization by mass spectrometry. SRS utilizes a uniquely functionalized, silica-based bead that has strong affinity toward proteins with minimal-to-no affinity for peptides and other small molecules. By leveraging the inherent size difference between, SRS permits high-capacity binding of proteins, rapid removal of small molecules (detergents, metabolites, salts, etc.), extensive manipulation including enzymatic and chemical treatments on beads-bound proteins, and easy recovery of N-glycans and peptides. The efficacy of SRS was evaluated in a wide range of biological samples including single glycoprotein, whole cell lysate, murine tissues, and human urine. To further demonstrate the SRS platform, we coupled a quantitative strategy to SRS to investigate the differences between DU145 prostate cancer cells and its DIAPH3-silenced counterpart. Our previous studies suggested that DIAPH3 silencing in DU145 prostate cancer cells induced transition to an amoeboid phenotype that correlated with tumor progression and metastasis. In this analysis we identified distinct proteomic and N-glycomic alterations between the two cells. Intriguingly, a metastasis-associated tyrosine kinase receptor ephrin-type-A receptor (EPHA2) was highly upregulated in DIAPH3-silenced cells, indicating underling connection between EPHA2 and DIAPH3. Moreover, distinct alterations in the N-glycome were identified, suggesting a cross-link between DIAPH3 and glycosyltransferase networks. Overall, SRS is an enabling universal sample preparation strategy that is not size limited and has the capability to efficiently prepare and clean peptides and N-glycans concurrently from nearly all sample types. Conceptually, SRS can be utilized for the analysis of other posttranslational modifications, and the unique surface chemistry can be further transformed for high-throughput automation. The technical simplicity, robustness, and modularity of SRS make it a highly promising technology with great potential in proteomic-based research. PMID:26791391

Highlights of the Biology and Disease-driven Human Proteome Project, 2015-2016.

PubMed

Van Eyk, Jennifer E; Corrales, Fernando J; Aebersold, Ruedi; Cerciello, Ferdinando; Deutsch, Eric W; Roncada, Paola; Sanchez, Jean-Charles; Yamamoto, Tadashi; Yang, Pengyuan; Zhang, Hui; Omenn, Gilbert S

2016-11-04

The Biology and Disease-driven Human Proteome Project (B/D-HPP) is aimed at supporting and enhancing the broad use of state-of-the-art proteomic methods to characterize and quantify proteins for in-depth understanding of the molecular mechanisms of biological processes and human disease. Based on a foundation of the pre-existing HUPO initiatives begun in 2002, the B/D-HPP is designed to provide standardized methods and resources for mass spectrometry and specific protein affinity reagents and facilitate accessibility of these resources to the broader life sciences research and clinical communities. Currently there are 22 B/D-HPP initiatives and 3 closely related HPP resource pillars. The B/D-HPP groups are working to define sets of protein targets that are highly relevant to each particular field to deliver relevant assays for the measurement of these selected targets and to disseminate and make publicly accessible the information and tools generated. Major developments are the 2016 publications of the Human SRM Atlas and of "popular protein sets" for six organ systems. Here we present the current activities and plans of the BD-HPP initiatives as highlighted in numerous B/D-HPP workshops at the 14th annual HUPO 2015 World Congress of Proteomics in Vancouver, Canada.

TimeXNet Web: Identifying cellular response networks from diverse omics time-course data.

PubMed

Tan, Phit Ling; López, Yosvany; Nakai, Kenta; Patil, Ashwini

2018-05-14

Condition-specific time-course omics profiles are frequently used to study cellular response to stimuli and identify associated signaling pathways. However, few online tools allow users to analyze multiple types of high-throughput time-course data. TimeXNet Web is a web server that extracts a time-dependent gene/protein response network from time-course transcriptomic, proteomic or phospho-proteomic data, and an input interaction network. It classifies the given genes/proteins into time-dependent groups based on the time of their highest activity and identifies the most probable paths connecting genes/proteins in consecutive groups. The response sub-network is enriched in activated genes/proteins and contains novel regulators that do not show any observable change in the input data. Users can view the resultant response network and analyze it for functional enrichment. TimeXNet Web supports the analysis of high-throughput data from multiple species by providing high quality, weighted protein-protein interaction networks for 12 model organisms. http://txnet.hgc.jp/. ashwini@hgc.jp. Supplementary data are available at Bioinformatics online.

Open source libraries and frameworks for mass spectrometry based proteomics: A developer's perspective☆

PubMed Central

Perez-Riverol, Yasset; Wang, Rui; Hermjakob, Henning; Müller, Markus; Vesada, Vladimir; Vizcaíno, Juan Antonio

2014-01-01

Data processing, management and visualization are central and critical components of a state of the art high-throughput mass spectrometry (MS)-based proteomics experiment, and are often some of the most time-consuming steps, especially for labs without much bioinformatics support. The growing interest in the field of proteomics has triggered an increase in the development of new software libraries, including freely available and open-source software. From database search analysis to post-processing of the identification results, even though the objectives of these libraries and packages can vary significantly, they usually share a number of features. Common use cases include the handling of protein and peptide sequences, the parsing of results from various proteomics search engines output files, and the visualization of MS-related information (including mass spectra and chromatograms). In this review, we provide an overview of the existing software libraries, open-source frameworks and also, we give information on some of the freely available applications which make use of them. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan. PMID:23467006

Open source libraries and frameworks for mass spectrometry based proteomics: a developer's perspective.

PubMed

Perez-Riverol, Yasset; Wang, Rui; Hermjakob, Henning; Müller, Markus; Vesada, Vladimir; Vizcaíno, Juan Antonio

2014-01-01

Data processing, management and visualization are central and critical components of a state of the art high-throughput mass spectrometry (MS)-based proteomics experiment, and are often some of the most time-consuming steps, especially for labs without much bioinformatics support. The growing interest in the field of proteomics has triggered an increase in the development of new software libraries, including freely available and open-source software. From database search analysis to post-processing of the identification results, even though the objectives of these libraries and packages can vary significantly, they usually share a number of features. Common use cases include the handling of protein and peptide sequences, the parsing of results from various proteomics search engines output files, and the visualization of MS-related information (including mass spectra and chromatograms). In this review, we provide an overview of the existing software libraries, open-source frameworks and also, we give information on some of the freely available applications which make use of them. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan. Copyright © 2013 Elsevier B.V. All rights reserved.

Advances in Quantitative Proteomics of Microbes and Microbial Communities

NASA Astrophysics Data System (ADS)

Waldbauer, J.; Zhang, L.; Rizzo, A. I.

2015-12-01

Quantitative measurements of gene expression are key to developing a mechanistic, predictive understanding of how microbial metabolism drives many biogeochemical fluxes and responds to environmental change. High-throughput RNA-sequencing can afford a wealth of information about transcript-level expression patterns, but it is becoming clear that expression dynamics are often very different at the protein level where biochemistry actually occurs. These divergent dynamics between levels of biological organization necessitate quantitative proteomic measurements to address many biogeochemical questions. The protein-level expression changes that underlie shifts in the magnitude, or even the direction, of metabolic and biogeochemical fluxes can be quite subtle and test the limits of current quantitative proteomics techniques. Here we describe methodologies for high-precision, whole-proteome quantification that are applicable to both model organisms of biogeochemical interest that may not be genetically tractable, and to complex community samples from natural environments. Employing chemical derivatization of peptides with multiple isotopically-coded tags, this strategy is rapid and inexpensive, can be implemented on a wide range of mass spectrometric instrumentation, and is relatively insensitive to chromatographic variability. We demonstrate the utility of this quantitative proteomics approach in application to both isolates and natural communities of sulfur-metabolizing and photosynthetic microbes.

Proteomics technique opens new frontiers in mobilome research.

PubMed

Davidson, Andrew D; Matthews, David A; Maringer, Kevin

2017-01-01

A large proportion of the genome of most eukaryotic organisms consists of highly repetitive mobile genetic elements. The sum of these elements is called the "mobilome," which in eukaryotes is made up mostly of transposons. Transposable elements contribute to disease, evolution, and normal physiology by mediating genetic rearrangement, and through the "domestication" of transposon proteins for cellular functions. Although 'omics studies of mobilome genomes and transcriptomes are common, technical challenges have hampered high-throughput global proteomics analyses of transposons. In a recent paper, we overcame these technical hurdles using a technique called "proteomics informed by transcriptomics" (PIT), and thus published the first unbiased global mobilome-derived proteome for any organism (using cell lines derived from the mosquito Aedes aegypti ). In this commentary, we describe our methods in more detail, and summarise our major findings. We also use new genome sequencing data to show that, in many cases, the specific genomic element expressing a given protein can be identified using PIT. This proteomic technique therefore represents an important technological advance that will open new avenues of research into the role that proteins derived from transposons and other repetitive and sequence diverse genetic elements, such as endogenous retroviruses, play in health and disease.

Recent advances in micro-scale and nano-scale high-performance liquid-phase chromatography for proteome research.

PubMed

Tao, Dingyin; Zhang, Lihua; Shan, Yichu; Liang, Zhen; Zhang, Yukui

2011-01-01

High-performance liquid chromatography-electrospray ionization tandem mass spectrometry (HPLC-ESI-MS-MS) is regarded as one of the most powerful techniques for separation and identification of proteins. Recently, much effort has been made to improve the separation capacity, detection sensitivity, and analysis throughput of micro- and nano-HPLC, by increasing column length, reducing column internal diameter, and using integrated techniques. Development of HPLC columns has also been rapid, as a result of the use of submicrometer packing materials and monolithic columns. All these innovations result in clearly improved performance of micro- and nano-HPLC for proteome research.

File formats commonly used in mass spectrometry proteomics.

PubMed

Deutsch, Eric W

2012-12-01

The application of mass spectrometry (MS) to the analysis of proteomes has enabled the high-throughput identification and abundance measurement of hundreds to thousands of proteins per experiment. However, the formidable informatics challenge associated with analyzing MS data has required a wide variety of data file formats to encode the complex data types associated with MS workflows. These formats encompass the encoding of input instruction for instruments, output products of the instruments, and several levels of information and results used by and produced by the informatics analysis tools. A brief overview of the most common file formats in use today is presented here, along with a discussion of related topics.

Beyond the Natural Proteome: Nondegenerate Saturation Mutagenesis-Methodologies and Advantages.

PubMed

Ferreira Amaral, M M; Frigotto, L; Hine, A V

2017-01-01

Beyond the natural proteome, high-throughput mutagenesis offers the protein engineer an opportunity to "tweak" the wild-type activity of a protein to create a recombinant protein with required attributes. Of the various approaches available, saturation mutagenesis is one of the core techniques employed by protein engineers, and in recent times, nondegenerate saturation mutagenesis is emerging as the approach of choice. This review compares the current methodologies available for conducting nondegenerate saturation mutagenesis with traditional, degenerate saturation and briefly outlines the options available for screening the resulting libraries, to discover a novel protein with the required activity and/or specificity. © 2017 Elsevier Inc. All rights reserved.

MS-REDUCE: an ultrafast technique for reduction of big mass spectrometry data for high-throughput processing.

PubMed

Awan, Muaaz Gul; Saeed, Fahad

2016-05-15

Modern proteomics studies utilize high-throughput mass spectrometers which can produce data at an astonishing rate. These big mass spectrometry (MS) datasets can easily reach peta-scale level creating storage and analytic problems for large-scale systems biology studies. Each spectrum consists of thousands of peaks which have to be processed to deduce the peptide. However, only a small percentage of peaks in a spectrum are useful for peptide deduction as most of the peaks are either noise or not useful for a given spectrum. This redundant processing of non-useful peaks is a bottleneck for streaming high-throughput processing of big MS data. One way to reduce the amount of computation required in a high-throughput environment is to eliminate non-useful peaks. Existing noise removing algorithms are limited in their data-reduction capability and are compute intensive making them unsuitable for big data and high-throughput environments. In this paper we introduce a novel low-complexity technique based on classification, quantization and sampling of MS peaks. We present a novel data-reductive strategy for analysis of Big MS data. Our algorithm, called MS-REDUCE, is capable of eliminating noisy peaks as well as peaks that do not contribute to peptide deduction before any peptide deduction is attempted. Our experiments have shown up to 100× speed up over existing state of the art noise elimination algorithms while maintaining comparable high quality matches. Using our approach we were able to process a million spectra in just under an hour on a moderate server. The developed tool and strategy has been made available to wider proteomics and parallel computing community and the code can be found at https://github.com/pcdslab/MSREDUCE CONTACT: : fahad.saeed@wmich.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Stage-specific Proteomes from Onchocerca ochengi, Sister Species of the Human River Blindness Parasite, Uncover Adaptations to a Nodular Lifestyle.

PubMed

Armstrong, Stuart D; Xia, Dong; Bah, Germanus S; Krishna, Ritesh; Ngangyung, Henrietta F; LaCourse, E James; McSorley, Henry J; Kengne-Ouafo, Jonas A; Chounna-Ndongmo, Patrick W; Wanji, Samuel; Enyong, Peter A; Taylor, David W; Blaxter, Mark L; Wastling, Jonathan M; Tanya, Vincent N; Makepeace, Benjamin L

2016-08-01

Despite 40 years of control efforts, onchocerciasis (river blindness) remains one of the most important neglected tropical diseases, with 17 million people affected. The etiological agent, Onchocerca volvulus, is a filarial nematode with a complex lifecycle involving several distinct stages in the definitive host and blackfly vector. The challenges of obtaining sufficient material have prevented high-throughput studies and the development of novel strategies for disease control and diagnosis. Here, we utilize the closest relative of O. volvulus, the bovine parasite Onchocerca ochengi, to compare stage-specific proteomes and host-parasite interactions within the secretome. We identified a total of 4260 unique O. ochengi proteins from adult males and females, infective larvae, intrauterine microfilariae, and fluid from intradermal nodules. In addition, 135 proteins were detected from the obligate Wolbachia symbiont. Observed protein families that were enriched in all whole body extracts relative to the complete search database included immunoglobulin-domain proteins, whereas redox and detoxification enzymes and proteins involved in intracellular transport displayed stage-specific overrepresentation. Unexpectedly, the larval stages exhibited enrichment for several mitochondrial-related protein families, including members of peptidase family M16 and proteins which mediate mitochondrial fission and fusion. Quantification of proteins across the lifecycle using the Hi-3 approach supported these qualitative analyses. In nodule fluid, we identified 94 O. ochengi secreted proteins, including homologs of transforming growth factor-β and a second member of a novel 6-ShK toxin domain family, which was originally described from a model filarial nematode (Litomosoides sigmodontis). Strikingly, the 498 bovine proteins identified in nodule fluid were strongly dominated by antimicrobial proteins, especially cathelicidins. This first high-throughput analysis of an Onchocerca spp. proteome across the lifecycle highlights its profound complexity and emphasizes the extremely close relationship between O. ochengi and O. volvulus The insights presented here provide new candidates for vaccine development, drug targeting and diagnostic biomarkers. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Stage-specific Proteomes from Onchocerca ochengi, Sister Species of the Human River Blindness Parasite, Uncover Adaptations to a Nodular Lifestyle*

PubMed Central

Armstrong, Stuart D.; Xia, Dong; Bah, Germanus S.; Krishna, Ritesh; Ngangyung, Henrietta F.; LaCourse, E. James; McSorley, Henry J.; Kengne-Ouafo, Jonas A.; Chounna-Ndongmo, Patrick W.; Wanji, Samuel; Enyong, Peter A.; Taylor, David W.; Blaxter, Mark L.; Wastling, Jonathan M.; Tanya, Vincent N.; Makepeace, Benjamin L.

2016-01-01

Despite 40 years of control efforts, onchocerciasis (river blindness) remains one of the most important neglected tropical diseases, with 17 million people affected. The etiological agent, Onchocerca volvulus, is a filarial nematode with a complex lifecycle involving several distinct stages in the definitive host and blackfly vector. The challenges of obtaining sufficient material have prevented high-throughput studies and the development of novel strategies for disease control and diagnosis. Here, we utilize the closest relative of O. volvulus, the bovine parasite Onchocerca ochengi, to compare stage-specific proteomes and host-parasite interactions within the secretome. We identified a total of 4260 unique O. ochengi proteins from adult males and females, infective larvae, intrauterine microfilariae, and fluid from intradermal nodules. In addition, 135 proteins were detected from the obligate Wolbachia symbiont. Observed protein families that were enriched in all whole body extracts relative to the complete search database included immunoglobulin-domain proteins, whereas redox and detoxification enzymes and proteins involved in intracellular transport displayed stage-specific overrepresentation. Unexpectedly, the larval stages exhibited enrichment for several mitochondrial-related protein families, including members of peptidase family M16 and proteins which mediate mitochondrial fission and fusion. Quantification of proteins across the lifecycle using the Hi-3 approach supported these qualitative analyses. In nodule fluid, we identified 94 O. ochengi secreted proteins, including homologs of transforming growth factor-β and a second member of a novel 6-ShK toxin domain family, which was originally described from a model filarial nematode (Litomosoides sigmodontis). Strikingly, the 498 bovine proteins identified in nodule fluid were strongly dominated by antimicrobial proteins, especially cathelicidins. This first high-throughput analysis of an Onchocerca spp. proteome across the lifecycle highlights its profound complexity and emphasizes the extremely close relationship between O. ochengi and O. volvulus. The insights presented here provide new candidates for vaccine development, drug targeting and diagnostic biomarkers. PMID:27226403

A set of ligation-independent in vitro translation vectors for eukaryotic protein production.

PubMed

Bardóczy, Viola; Géczi, Viktória; Sawasaki, Tatsuya; Endo, Yaeta; Mészáros, Tamás

2008-03-27

The last decade has brought the renaissance of protein studies and accelerated the development of high-throughput methods in all aspects of proteomics. Presently, most protein synthesis systems exploit the capacity of living cells to translate proteins, but their application is limited by several factors. A more flexible alternative protein production method is the cell-free in vitro protein translation. Currently available in vitro translation systems are suitable for high-throughput robotic protein production, fulfilling the requirements of proteomics studies. Wheat germ extract based in vitro translation system is likely the most promising method, since numerous eukaryotic proteins can be cost-efficiently synthesized in their native folded form. Although currently available vectors for wheat embryo in vitro translation systems ensure high productivity, they do not meet the requirements of state-of-the-art proteomics. Target genes have to be inserted using restriction endonucleases and the plasmids do not encode cleavable affinity purification tags. We designed four ligation independent cloning (LIC) vectors for wheat germ extract based in vitro protein translation. In these constructs, the RNA transcription is driven by T7 or SP6 phage polymerase and two TEV protease cleavable affinity tags can be added to aid protein purification. To evaluate our improved vectors, a plant mitogen activated protein kinase was cloned in all four constructs. Purification of this eukaryotic protein kinase demonstrated that all constructs functioned as intended: insertion of PCR fragment by LIC worked efficiently, affinity purification of translated proteins by GST-Sepharose or MagneHis particles resulted in high purity kinase, and the affinity tags could efficiently be removed under different reaction conditions. Furthermore, high in vitro kinase activity testified of proper folding of the purified protein. Four newly designed in vitro translation vectors have been constructed which allow fast and parallel cloning and protein purification, thus representing useful molecular tools for high-throughput production of eukaryotic proteins.

Subnanogram proteomics: Impact of LC column selection, MS instrumentation and data analysis strategy on proteome coverage for trace samples

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhu, Ying; Zhao, Rui; Piehowski, Paul D.

One of the greatest challenges for mass spectrometry (MS)-based proteomics is the limited ability to analyze small samples. Here we investigate the relative contributions of liquid chromatography (LC), MS instrumentation and data analysis methods with the aim of improving proteome coverage for sample sizes ranging from 0.5 ng to 50 ng. We show that the LC separations utilizing 30-µm-i.d. columns increase signal intensity by >3-fold relative to those using 75-µm-i.d. columns, leading to 32% increase in peptide identifications. The Orbitrap Fusion Lumos mass spectrometer significantly boosted both sensitivity and sequencing speed relative to earlier generation Orbitraps (e.g., LTQ-Orbitrap), leading tomore » a ~3× increase in peptide identifications and 1.7× increase in identified protein groups for 2 ng tryptic digests of bacterial lysate. The Match Between Runs algorithm of open-source MaxQuant software further increased proteome coverage by ~ 95% for 0.5 ng samples and by ~42% for 2 ng samples. The present platform is capable of identifying >3000 protein groups from tryptic digestion of cell lysates equivalent to 50 HeLa cells and 100 THP-1 cells (~10 ng total proteins), respectively, and >950 proteins from subnanogram bacterial and archaeal cell lysates. The present ultrasensitive LC-MS platform is expected to enable deep proteome coverage for subnanogram samples, including single mammalian cells.« less

2D-Difference Gel Electrophoretic Proteomic Analysis of a Cell Culture Model of Alveolar Rhabdomyosarcoma

PubMed Central

Pressey, Joseph G.; Pressey, Christine S.; Robinson, Gloria; Herring, Richie; Wilson, Landon; Kelly, David R.; Kim, Helen

2011-01-01

To evaluate the consequences of expression of the protein encoded by PAX3-FOXO1 (P3F) in the pediatric malignancy alveolar rhabdomyosarcoma (A-RMS), we developed and evaluated a genetically defined in vitro model of A-RMS tumorigenesis. The expression of P3F in cooperation with simian virus 40 (SV40) Large-T (LT) antigen in murine C3H10T1/2 fibroblasts led to robust malignant transformation. Using 2 dimensional difference gel electrophoresis (2D-DIGE) we compared proteomes from lysates from cells that express P3F + LT versus from cells that express LT alone. Analysis of 2D gel spot patterns by DeCyder™ image analysis software indicated 93 spots that were different in abundance. Peptide mass fingerprint analysis of the 93 spots by matrix assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) analysis identified 37 non-redundant proteins. 2D DIGE analysis of cell culture media conditioned by cells transduced by P3F + LT versus by LT alone found 29 spots in the P3F + LT cells leading to the identification of 11 non-redundant proteins. A substantial number of proteins with potential roles in tumorigenesis and myogenesis were detected, most of which have not been identified in previous wide-scale expression studies of RMS experimental models or tumors. We validated the 2D gel image analysis findings by western blot analysis and immunohistochemistry (IHC). Thus, the 2D DIGE proteomics methodology described here provided an important discovery approach to the study of RMS biology and complements the findings of previous mRNA expression studies. PMID:21110518

2D-difference gel electrophoretic proteomic analysis of a cell culture model of alveolar rhabdomyosarcoma.

PubMed

Pressey, Joseph G; Pressey, Christine S; Robinson, Gloria; Herring, Richie; Wilson, Landon; Kelly, David R; Kim, Helen

2011-02-04

To evaluate the consequences of expression of the protein encoded by PAX3-FOXO1 (P3F) in the pediatric malignancy alveolar rhabdomyosarcoma (A-RMS), we developed and evaluated a genetically defined in vitro model of A-RMS tumorigenesis. The expression of P3F in cooperation with simian virus 40 (SV40) Large-T (LT) antigen in murine C3H10T1/2 fibroblasts led to robust malignant transformation. Using 2-dimensional-difference gel electrophoresis (2D-DIGE), we compared proteomes from lysates from cells that express P3F + LT versus from cells that express LT alone. Analysis of 2D gel spot patterns by DeCyder image analysis software indicated 93 spots that were different in abundance. Peptide mass fingerprint analysis of the 93 spots by matrix assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) analysis identified 37 nonredundant proteins. 2D-DIGE analysis of cell culture media conditioned by cells transduced by P3F + LT versus by LT alone found 29 spots in the P3F + LT cells leading to the identification of 11 nonredundant proteins. A substantial number of proteins with potential roles in tumorigenesis and myogenesis were detected, most of which have not been identified in previous wide-scale expression studies of RMS experimental models or tumors. We validated the 2D gel image analysis findings by Western blot analysis and immunohistochemistry (IHC). Thus, the 2D-DIGE proteomics methodology described here provided an important discovery approach to the study of RMS biology and complements the findings of previous mRNA expression studies.

Increased Depth and Breadth of Plasma Protein Quantitation via Two-Dimensional Liquid Chromatography/Multiple Reaction Monitoring-Mass Spectrometry with Labeled Peptide Standards.

PubMed

Percy, Andrew J; Yang, Juncong; Chambers, Andrew G; Borchers, Christoph H

2016-01-01

Absolute quantitative strategies are emerging as a powerful and preferable means of deriving concentrations in biological samples for systems biology applications. Method development is driven by the need to establish new-and validate current-protein biomarkers of high-to-low abundance for clinical utility. In this chapter, we describe a methodology involving two-dimensional (2D) reversed-phase liquid chromatography (RPLC), operated under alkaline and acidic pH conditions, combined with multiple reaction monitoring (MRM)-mass spectrometry (MS) (also called selected reaction monitoring (SRM)-MS) and a complex mixture of stable isotope-labeled standard (SIS) peptides, to quantify a broad and diverse panel of 253 proteins in human blood plasma. The quantitation range spans 8 orders of magnitude-from 15 mg/mL (for vitamin D-binding protein) to 450 pg/mL (for protein S100-B)-and includes 31 low-abundance proteins (defined as being <10 ng/mL) of potential disease relevance. The method is designed to assess candidates at the discovery and/or verification phases of the biomarker pipeline and can be adapted to examine smaller or alternate panels of proteins for higher sample throughput. Also detailed here is the application of our recently developed software tool-Qualis-SIS-for protein quantitation (via regression analysis of standard curves) and quality assessment of the resulting data. Overall, this chapter provides the blueprint for the replication of this quantitative proteomic method by proteomic scientists of all skill levels.

Proteomic Workflows for Biomarker Identification Using Mass Spectrometry — Technical and Statistical Considerations during Initial Discovery

PubMed Central

Orton, Dennis J.; Doucette, Alan A.

2013-01-01

Identification of biomarkers capable of differentiating between pathophysiological states of an individual is a laudable goal in the field of proteomics. Protein biomarker discovery generally employs high throughput sample characterization by mass spectrometry (MS), being capable of identifying and quantifying thousands of proteins per sample. While MS-based technologies have rapidly matured, the identification of truly informative biomarkers remains elusive, with only a handful of clinically applicable tests stemming from proteomic workflows. This underlying lack of progress is attributed in large part to erroneous experimental design, biased sample handling, as well as improper statistical analysis of the resulting data. This review will discuss in detail the importance of experimental design and provide some insight into the overall workflow required for biomarker identification experiments. Proper balance between the degree of biological vs. technical replication is required for confident biomarker identification. PMID:28250400

Sperm Proteome: What Is on the Horizon?

PubMed

Mohanty, Gayatri; Swain, Nirlipta; Samanta, Luna

2015-06-01

As the mammalian spermatozoa transcends from the testis to the end of the epididymal tubule, the functionally incompetent spermatozoa acquires its fertilizing capability. Molecular changes in the spermatozoa at the posttesticular level concern qualitative and quantitative modifications of proteins along with their sugar moieties and membranous lipids mostly associated with motility, egg binding, and penetration processes. Proteomic studies have identified numerous sperm-specific proteins, and recent reports have provided a further understanding of their function with respect to male fertility. High-throughput techniques such as mass spectrometry have shown drastic potential for the identification and study of sperm proteins. In fact, compelling evidence has provided that proteins are critically important in cellular remodeling event and that aberrant expression is associated with pronounced defects in sperm function. This review highlights the posttesticular functional transformation in the epididymis and female reproductive tract with due emphasis on proteomics. © The Author(s) 2014.

Approaches for Defining the Hsp90-dependent Proteome

PubMed Central

Hartson, Steven D.; Matts, Robert L.

2011-01-01

Hsp90 is the target of ongoing drug discovery studies seeking new compounds to treat cancer, neurodegenerative diseases, and protein folding disorders. To better understand Hsp90’s roles in cellular pathologies and in normal cells, numerous studies have utilized proteomics assays and related high-throughput tools to characterize its physical and functional protein partnerships. This review surveys these studies, and summarizes the strengths and limitations of the individual attacks. We also include downloadable spreadsheets compiling all of the Hsp90-interacting proteins identified in more than 23 studies. These tools include cross-references among gene aliases, human homologues of yeast Hsp90-interacting proteins, hyperlinks to database entries, summaries of canonical pathways that are enriched in the Hsp90 interactome, and additional bioinformatic annotations. In addition to summarizing Hsp90 proteomics studies performed to date and the insights they have provided, we identify gaps in our current understanding of Hsp90-mediated proteostasis. PMID:21906632

Accelerating the design of biomimetic materials by integrating RNA-seq with proteomics and materials science.

PubMed

Guerette, Paul A; Hoon, Shawn; Seow, Yiqi; Raida, Manfred; Masic, Admir; Wong, Fong T; Ho, Vincent H B; Kong, Kiat Whye; Demirel, Melik C; Pena-Francesch, Abdon; Amini, Shahrouz; Tay, Gavin Z; Ding, Dawei; Miserez, Ali

2013-10-01

Efforts to engineer new materials inspired by biological structures are hampered by the lack of genomic data from many model organisms studied in biomimetic research. Here we show that biomimetic engineering can be accelerated by integrating high-throughput RNA-seq with proteomics and advanced materials characterization. This approach can be applied to a broad range of systems, as we illustrate by investigating diverse high-performance biological materials involved in embryo protection, adhesion and predation. In one example, we rapidly engineer recombinant squid sucker ring teeth proteins into a range of structural and functional materials, including nanopatterned surfaces and photo-cross-linked films that exceed the mechanical properties of most natural and synthetic polymers. Integrating RNA-seq with proteomics and materials science facilitates the molecular characterization of natural materials and the effective translation of their molecular designs into a wide range of bio-inspired materials.

System-Wide Quantitative Proteomics of the Metabolic Syndrome in Mice: Genotypic and Dietary Effects.

PubMed

Terfve, Camille; Sabidó, Eduard; Wu, Yibo; Gonçalves, Emanuel; Choi, Meena; Vaga, Stefania; Vitek, Olga; Saez-Rodriguez, Julio; Aebersold, Ruedi

2017-02-03

Advances in mass spectrometry have made the quantitative measurement of proteins across multiple samples a reality, allowing for the study of complex biological systems such as the metabolic syndrome. Although the deregulation of lipid metabolism and increased hepatic storage of triacylglycerides are known to play a part in the onset of the metabolic syndrome, its molecular basis and dependency on dietary and genotypic factors are poorly characterized. Here, we used an experimental design with two different mouse strains and dietary and metabolic perturbations to generate a compendium of quantitative proteome data using three mass spectrometric techniques. The data reproduce known properties of the metabolic system and indicate differential molecular adaptation of the two mouse strains to perturbations, contributing to a better understanding of the metabolic syndrome. We show that high-quality, high-throughput proteomic data sets provide an unbiased broad overview of the behavior of complex systems after perturbation.

High-throughput 3D spheroid culture and drug testing using a 384 hanging drop array.

PubMed

Tung, Yi-Chung; Hsiao, Amy Y; Allen, Steven G; Torisawa, Yu-suke; Ho, Mitchell; Takayama, Shuichi

2011-02-07

Culture of cells as three-dimensional (3D) aggregates can enhance in vitro tests for basic biological research as well as for therapeutics development. Such 3D culture models, however, are often more complicated, cumbersome, and expensive than two-dimensional (2D) cultures. This paper describes a 384-well format hanging drop culture plate that makes spheroid formation, culture, and subsequent drug testing on the obtained 3D cellular constructs as straightforward to perform and adapt to existing high-throughput screening (HTS) instruments as conventional 2D cultures. Using this platform, we show that drugs with different modes of action produce distinct responses in the physiological 3D cell spheroids compared to conventional 2D cell monolayers. Specifically, the anticancer drug 5-fluorouracil (5-FU) has higher anti-proliferative effects on 2D cultures whereas the hypoxia activated drug commonly referred to as tirapazamine (TPZ) are more effective against 3D cultures. The multiplexed 3D hanging drop culture and testing plate provides an efficient way to obtain biological insights that are often lost in 2D platforms.

Exploration of Panviral Proteome: High-Throughput Cloning and Functional Implications in Virus-host Interactions

PubMed Central

Yu, Xiaobo; Bian, Xiaofang; Throop, Andrea; Song, Lusheng; Moral, Lerys Del; Park, Jin; Seiler, Catherine; Fiacco, Michael; Steel, Jason; Hunter, Preston; Saul, Justin; Wang, Jie; Qiu, Ji; Pipas, James M.; LaBaer, Joshua

2014-01-01

Throughout the long history of virus-host co-evolution, viruses have developed delicate strategies to facilitate their invasion and replication of their genome, while silencing the host immune responses through various mechanisms. The systematic characterization of viral protein-host interactions would yield invaluable information in the understanding of viral invasion/evasion, diagnosis and therapeutic treatment of a viral infection, and mechanisms of host biology. With more than 2,000 viral genomes sequenced, only a small percent of them are well investigated. The access of these viral open reading frames (ORFs) in a flexible cloning format would greatly facilitate both in vitro and in vivo virus-host interaction studies. However, the overall progress of viral ORF cloning has been slow. To facilitate viral studies, we are releasing the initiation of our panviral proteome collection of 2,035 ORF clones from 830 viral genes in the Gateway® recombinational cloning system. Here, we demonstrate several uses of our viral collection including highly efficient production of viral proteins using human cell-free expression system in vitro, global identification of host targets for rubella virus using Nucleic Acid Programmable Protein Arrays (NAPPA) containing 10,000 unique human proteins, and detection of host serological responses using micro-fluidic multiplexed immunoassays. The studies presented here begin to elucidate host-viral protein interactions with our systemic utilization of viral ORFs, high-throughput cloning, and proteomic technologies. These valuable plasmid resources will be available to the research community to enable continued viral functional studies. PMID:24955142

Exploration of panviral proteome: high-throughput cloning and functional implications in virus-host interactions.

PubMed

Yu, Xiaobo; Bian, Xiaofang; Throop, Andrea; Song, Lusheng; Moral, Lerys Del; Park, Jin; Seiler, Catherine; Fiacco, Michael; Steel, Jason; Hunter, Preston; Saul, Justin; Wang, Jie; Qiu, Ji; Pipas, James M; LaBaer, Joshua

2014-01-01

Throughout the long history of virus-host co-evolution, viruses have developed delicate strategies to facilitate their invasion and replication of their genome, while silencing the host immune responses through various mechanisms. The systematic characterization of viral protein-host interactions would yield invaluable information in the understanding of viral invasion/evasion, diagnosis and therapeutic treatment of a viral infection, and mechanisms of host biology. With more than 2,000 viral genomes sequenced, only a small percent of them are well investigated. The access of these viral open reading frames (ORFs) in a flexible cloning format would greatly facilitate both in vitro and in vivo virus-host interaction studies. However, the overall progress of viral ORF cloning has been slow. To facilitate viral studies, we are releasing the initiation of our panviral proteome collection of 2,035 ORF clones from 830 viral genes in the Gateway® recombinational cloning system. Here, we demonstrate several uses of our viral collection including highly efficient production of viral proteins using human cell-free expression system in vitro, global identification of host targets for rubella virus using Nucleic Acid Programmable Protein Arrays (NAPPA) containing 10,000 unique human proteins, and detection of host serological responses using micro-fluidic multiplexed immunoassays. The studies presented here begin to elucidate host-viral protein interactions with our systemic utilization of viral ORFs, high-throughput cloning, and proteomic technologies. These valuable plasmid resources will be available to the research community to enable continued viral functional studies.

Proteomic analysis in peritoneal dialysis patients with different peritoneal transport characteristics.

PubMed

Wen, Qiong; Zhang, Li; Mao, Hai-Ping; Tang, Xue-Qing; Rong, Rong; Fan, Jin-Jin; Yu, Xue-Qing

2013-08-30

Peritoneal membranes can be categorized as high, high average, low average, and low transporters, based on the removal or transport rate of solutes. In this study, we used proteomic analysis to determine the differences in proteins removed by different types of peritoneal membranes. Peritoneal transport characteristics in patients who received peritoneal dialysis therapy were assessed by a peritoneal equilibration test. Two-dimensional differential gel electrophoresis technology followed by quantitative analysis was performed to study the variation in protein expression from peritoneal dialysis effluents (PDE) among different groups. Proteins were identified by MALDI-TOF-MS/MS analyses. Further validation in PDE or serum was performed utilizing ELISA analysis. Proteomics analysis revealed ten protein spots with significant differences in intensity levels among different groups, including vitamin D-binding protein, complement C3, apolipoprotein-A1, complement factor C4A, haptoglobin, alpha-1 antitrypsin, immunoglobulin kappa light chain, alpha-2-microglobulin, retinol-binding protein 4 and transthyretin. The levels of vitamin D-binding protein, complement C3, and apolipoprotein-A1 in PDE derived from different groups were greatly varied (P<0.05). However, no significant difference was found in the serum levels of these proteins among different groups (P>0.05 for all groups). This study provides a novel overview of the differences in PDE proteomes of four types of peritoneal membranes. Vitamin D-binding protein, complement C3, and apolipoprotein-A1 showed enhanced expression in PDE of patients with high transporter. Copyright © 2013 Elsevier Inc. All rights reserved.

SwellGel: an affinity chromatography technology for high-capacity and high-throughput purification of recombinant-tagged proteins.

PubMed

Draveling, C; Ren, L; Haney, P; Zeisse, D; Qoronfleh, M W

2001-07-01

The revolution in genomics and proteomics is having a profound impact on drug discovery. Today's protein scientist demands a faster, easier, more reliable way to purify proteins. A high capacity, high-throughput new technology has been developed in Perbio Sciences for affinity protein purification. This technology utilizes selected chromatography media that are dehydrated to form uniform aggregates. The SwellGel aggregates will instantly rehydrate upon addition of the protein sample, allowing purification and direct performance of multiple assays in a variety of formats. SwellGel technology has greater stability and is easier to handle than standard wet chromatography resins. The microplate format of this technology provides high-capacity, high-throughput features, recovering milligram quantities of protein suitable for high-throughput screening or biophysical/structural studies. Data will be presented applying SwellGel technology to recombinant 6x His-tagged protein and glutathione-S-transferase (GST) fusion protein purification. Copyright 2001 Academic Press.

Proteomic analysis of three gonad types of swamp eel reveals genes differentially expressed during sex reversal.

PubMed

Sheng, Yue; Zhao, Wei; Song, Ying; Li, Zhigang; Luo, Majing; Lei, Quan; Cheng, Hanhua; Zhou, Rongjia

2015-05-18

A variety of mechanisms are engaged in sex determination in vertebrates. The teleost fish swamp eel undergoes sex reversal naturally and is an ideal model for vertebrate sexual development. However, the importance of proteome-wide scanning for gonad reversal was not previously determined. We report a 2-D electrophoresis analysis of three gonad types of proteomes during sex reversal. MS/MS analysis revealed a group of differentially expressed proteins during ovary to ovotestis to testis transformation. Cbx3 is up-regulated during gonad reversal and is likely to have a role in spermatogenesis. Rab37 is down-regulated during the reversal and is mainly associated with oogenesis. Both Cbx3 and Rab37 are linked up in a protein network. These datasets in gonadal proteomes provide a new resource for further studies in gonadal development.

Label-free proteomic analysis to confirm the predicted proteome of Corynebacterium pseudotuberculosis under nitrosative stress mediated by nitric oxide.

PubMed

Silva, Wanderson M; Carvalho, Rodrigo D; Soares, Siomar C; Bastos, Isabela Fs; Folador, Edson L; Souza, Gustavo Hmf; Le Loir, Yves; Miyoshi, Anderson; Silva, Artur; Azevedo, Vasco

2014-12-04

Corynebacterium pseudotuberculosis biovar ovis is a facultative intracellular pathogen, and the etiological agent of caseous lymphadenitis in small ruminants. During the infection process, the bacterium is subjected to several stress conditions, including nitrosative stress, which is caused by nitric oxide (NO). In silico analysis of the genome of C. pseudotuberculosis ovis 1002 predicted several genes that could influence the resistance of this pathogen to nitrosative stress. Here, we applied high-throughput proteomics using high definition mass spectrometry to characterize the functional genome of C. pseudotuberculosis ovis 1002 in the presence of NO-donor Diethylenetriamine/nitric oxide adduct (DETA/NO), with the aim of identifying proteins involved in nitrosative stress resistance. We characterized 835 proteins, representing approximately 41% of the predicted proteome of C. pseudotuberculosis ovis 1002, following exposure to nitrosative stress. In total, 102 proteins were exclusive to the proteome of DETA/NO-induced cells, and a further 58 proteins were differentially regulated between the DETA/NO and control conditions. An interactomic analysis of the differential proteome of C. pseudotuberculosis in response to nitrosative stress was also performed. Our proteomic data set suggested the activation of both a general stress response and a specific nitrosative stress response, as well as changes in proteins involved in cellular metabolism, detoxification, transcriptional regulation, and DNA synthesis and repair. Our proteomic analysis validated previously-determined in silico data for C. pseudotuberculosis ovis 1002. In addition, proteomic screening performed in the presence of NO enabled the identification of a set of factors that can influence the resistance and survival of C. pseudotuberculosis during exposure to nitrosative stress.

SPIM-fluid: open source light-sheet based platform for high-throughput imaging

PubMed Central

Gualda, Emilio J.; Pereira, Hugo; Vale, Tiago; Estrada, Marta Falcão; Brito, Catarina; Moreno, Nuno

2015-01-01

Light sheet fluorescence microscopy has recently emerged as the technique of choice for obtaining high quality 3D images of whole organisms/embryos with low photodamage and fast acquisition rates. Here we present an open source unified implementation based on Arduino and Micromanager, which is capable of operating Light Sheet Microscopes for automatized 3D high-throughput imaging on three-dimensional cell cultures and model organisms like zebrafish, oriented to massive drug screening. PMID:26601007

Data-driven high-throughput prediction of the 3-D structure of small molecules: review and progress. A response to the letter by the Cambridge Crystallographic Data Centre.

PubMed

Baldi, Pierre

2011-12-27

A response is presented to sentiments expressed in "Data-Driven High-Throughput Prediction of the 3-D Structure of Small Molecules: Review and Progress. A Response from The Cambridge Crystallographic Data Centre", recently published in the Journal of Chemical Information and Modeling, (1) which may give readers a misleading impression regarding significant impediments to scientific research posed by the CCDC.

A Library of Phosphoproteomic and Chromatin Signatures for Characterizing Cellular Responses to Drug Perturbations.

PubMed

Litichevskiy, Lev; Peckner, Ryan; Abelin, Jennifer G; Asiedu, Jacob K; Creech, Amanda L; Davis, John F; Davison, Desiree; Dunning, Caitlin M; Egertson, Jarrett D; Egri, Shawn; Gould, Joshua; Ko, Tak; Johnson, Sarah A; Lahr, David L; Lam, Daniel; Liu, Zihan; Lyons, Nicholas J; Lu, Xiaodong; MacLean, Brendan X; Mungenast, Alison E; Officer, Adam; Natoli, Ted E; Papanastasiou, Malvina; Patel, Jinal; Sharma, Vagisha; Toder, Courtney; Tubelli, Andrew A; Young, Jennie Z; Carr, Steven A; Golub, Todd R; Subramanian, Aravind; MacCoss, Michael J; Tsai, Li-Huei; Jaffe, Jacob D

2018-04-25

Although the value of proteomics has been demonstrated, cost and scale are typically prohibitive, and gene expression profiling remains dominant for characterizing cellular responses to perturbations. However, high-throughput sentinel assays provide an opportunity for proteomics to contribute at a meaningful scale. We present a systematic library resource (90 drugs × 6 cell lines) of proteomic signatures that measure changes in the reduced-representation phosphoproteome (P100) and changes in epigenetic marks on histones (GCP). A majority of these drugs elicited reproducible signatures, but notable cell line- and assay-specific differences were observed. Using the "connectivity" framework, we compared signatures across cell types and integrated data across assays, including a transcriptional assay (L1000). Consistent connectivity among cell types revealed cellular responses that transcended lineage, and consistent connectivity among assays revealed unexpected associations between drugs. We further leveraged the resource against public data to formulate hypotheses for treatment of multiple myeloma and acute lymphocytic leukemia. This resource is publicly available at https://clue.io/proteomics. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

Intact mass detection, interpretation, and visualization to automate Top-Down proteomics on a large scale

PubMed Central

Durbin, Kenneth R.; Tran, John C.; Zamdborg, Leonid; Sweet, Steve M. M.; Catherman, Adam D.; Lee, Ji Eun; Li, Mingxi; Kellie, John F.; Kelleher, Neil L.

2011-01-01

Applying high-throughput Top-Down MS to an entire proteome requires a yet-to-be-established model for data processing. Since Top-Down is becoming possible on a large scale, we report our latest software pipeline dedicated to capturing the full value of intact protein data in automated fashion. For intact mass detection, we combine algorithms for processing MS1 data from both isotopically resolved (FT) and charge-state resolved (ion trap) LC-MS data, which are then linked to their fragment ions for database searching using ProSight. Automated determination of human keratin and tubulin isoforms is one result. Optimized for the intricacies of whole proteins, new software modules visualize proteome-scale data based on the LC retention time and intensity of intact masses and enable selective detection of PTMs to automatically screen for acetylation, phosphorylation, and methylation. Software functionality was demonstrated using comparative LC-MS data from yeast strains in addition to human cells undergoing chemical stress. We further these advances as a key aspect of realizing Top-Down MS on a proteomic scale. PMID:20848673

The amino acid's backup bone - storage solutions for proteomics facilities.

PubMed

Meckel, Hagen; Stephan, Christian; Bunse, Christian; Krafzik, Michael; Reher, Christopher; Kohl, Michael; Meyer, Helmut Erich; Eisenacher, Martin

2014-01-01

Proteomics methods, especially high-throughput mass spectrometry analysis have been continually developed and improved over the years. The analysis of complex biological samples produces large volumes of raw data. Data storage and recovery management pose substantial challenges to biomedical or proteomic facilities regarding backup and archiving concepts as well as hardware requirements. In this article we describe differences between the terms backup and archive with regard to manual and automatic approaches. We also introduce different storage concepts and technologies from transportable media to professional solutions such as redundant array of independent disks (RAID) systems, network attached storages (NAS) and storage area network (SAN). Moreover, we present a software solution, which we developed for the purpose of long-term preservation of large mass spectrometry raw data files on an object storage device (OSD) archiving system. Finally, advantages, disadvantages, and experiences from routine operations of the presented concepts and technologies are evaluated and discussed. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan. Copyright © 2013. Published by Elsevier B.V.

Mass spectrometry-based proteomics: from cancer biology to protein biomarkers, drug targets, and clinical applications.

PubMed

Jimenez, Connie R; Verheul, Henk M W

2014-01-01

Proteomics is optimally suited to bridge the gap between genomic information on the one hand and biologic functions and disease phenotypes at the other, since it studies the expression and/or post-translational modification (especially phosphorylation) of proteins--the major cellular players bringing about cellular functions--at a global level in biologic specimens. Mass spectrometry technology and (bio)informatic tools have matured to the extent that they can provide high-throughput, comprehensive, and quantitative protein inventories of cells, tissues, and biofluids in clinical samples at low level. In this article, we focus on next-generation proteomics employing nanoliquid chromatography coupled to high-resolution tandem mass spectrometry for in-depth (phospho)protein profiling of tumor tissues and (proximal) biofluids, with a focus on studies employing clinical material. In addition, we highlight emerging proteogenomic approaches for the identification of tumor-specific protein variants, and targeted multiplex mass spectrometry strategies for large-scale biomarker validation. Below we provide a discussion of recent progress, some research highlights, and challenges that remain for clinical translation of proteomic discoveries.

Computer aided manual validation of mass spectrometry-based proteomic data.

PubMed

Curran, Timothy G; Bryson, Bryan D; Reigelhaupt, Michael; Johnson, Hannah; White, Forest M

2013-06-15

Advances in mass spectrometry-based proteomic technologies have increased the speed of analysis and the depth provided by a single analysis. Computational tools to evaluate the accuracy of peptide identifications from these high-throughput analyses have not kept pace with technological advances; currently the most common quality evaluation methods are based on statistical analysis of the likelihood of false positive identifications in large-scale data sets. While helpful, these calculations do not consider the accuracy of each identification, thus creating a precarious situation for biologists relying on the data to inform experimental design. Manual validation is the gold standard approach to confirm accuracy of database identifications, but is extremely time-intensive. To palliate the increasing time required to manually validate large proteomic datasets, we provide computer aided manual validation software (CAMV) to expedite the process. Relevant spectra are collected, catalogued, and pre-labeled, allowing users to efficiently judge the quality of each identification and summarize applicable quantitative information. CAMV significantly reduces the burden associated with manual validation and will hopefully encourage broader adoption of manual validation in mass spectrometry-based proteomics. Copyright © 2013 Elsevier Inc. All rights reserved.

Integrated automation for continuous high-throughput synthetic chromosome assembly and transformation to identify improved yeast strains for industrial production of biofuels and bio-based chemicals

USDA-ARS?s Scientific Manuscript database

An exponential increase in our understanding of genomes, proteomes, and metabolomes provides greater impetus to address critical biotechnological issues such as sustainable production of biofuels and bio-based chemicals and, in particular, the development of improved microbial biocatalysts for use i...

Rapid formation of size-controllable multicellular spheroids via 3D acoustic tweezers.

PubMed

Chen, Kejie; Wu, Mengxi; Guo, Feng; Li, Peng; Chan, Chung Yu; Mao, Zhangming; Li, Sixing; Ren, Liqiang; Zhang, Rui; Huang, Tony Jun

2016-07-05

The multicellular spheroid is an important 3D cell culture model for drug screening, tissue engineering, and fundamental biological research. Although several spheroid formation methods have been reported, the field still lacks high-throughput and simple fabrication methods to accelerate its adoption in drug development industry. Surface acoustic wave (SAW) based cell manipulation methods, which are known to be non-invasive, flexible, and high-throughput, have not been successfully developed for fabricating 3D cell assemblies or spheroids, due to the limited understanding on SAW-based vertical levitation. In this work, we demonstrated the capability of fabricating multicellular spheroids in the 3D acoustic tweezers platform. Our method used drag force from microstreaming to levitate cells in the vertical direction, and used radiation force from Gor'kov potential to aggregate cells in the horizontal plane. After optimizing the device geometry and input power, we demonstrated the rapid and high-throughput nature of our method by continuously fabricating more than 150 size-controllable spheroids and transferring them to Petri dishes every 30 minutes. The spheroids fabricated by our 3D acoustic tweezers can be cultured for a week with good cell viability. We further demonstrated that spheroids fabricated by this method could be used for drug testing. Unlike the 2D monolayer model, HepG2 spheroids fabricated by the 3D acoustic tweezers manifested distinct drug resistance, which matched existing reports. The 3D acoustic tweezers based method can serve as a novel bio-manufacturing tool to fabricate complex 3D cell assembles for biological research, tissue engineering, and drug development.

Reversible and irreversible drought-induced changes in the anther proteome of rice (Oryza sativa L.) genotypes IR64 and Moroberekan.

PubMed

Liu, Jian-Xiang; Bennett, John

2011-01-01

Crop yield is most sensitive to water deficit during the reproductive stage. For rice, the most sensitive yield component is spikelet fertility and the most sensitive stage is immediately before heading. Here, we examined the effect of drought on the anther proteome of two rice genotypes: Moroberekan and IR64. Water was withheld for 3 d before heading (3DBH) in well watered controls for 5 d until the flag leaf relative water content (RWC) had declined to 45-50%. Plants were then re-watered and heading occurred 2-3 d later, representing a delay of 4-5 d relative to controls. The anther proteins were separated at 3 DBH, at the end of the stress period, and at heading in stressed/re-watered plants and controls by two-dimensional (2-D) gel electrophoresis, and 93 protein spots were affected reproducibly in abundance by drought during the experiment across two rice genotypes. After drought stress, upon re-watering, expressions of 24 protein spots were irreversible in both genotypes, 60 protein spots were irreversible in IR64 but reversible in Moroberekan, only nine protein spots were irreversible in Moroberekan while reversible in IR64. Among them, there were 14 newly drought-induced protein spots in IR64; none of them was reversible on re-watering. However, there were 13 newly drought-induced protein spots in Moroberekan, 10 of them were reversible on re-watering, including six drought-induced protein spots that were not reversed in IR64. Taken together, our proteomics data reveal that drought-tolerant genotype Moroberekan possessed better recovery capability following drought and re-watering at the anther proteome level than the drought-sensitive genotype IR64. The disruptions of drought to rice anther development and pollen cell functions are also discussed in the paper.

Quantitative proteomics analysis using 2D-PAGE to investigate the effects of cigarette smoke and aerosol of a prototypic modified risk tobacco product on the lung proteome in C57BL/6 mice.

PubMed

Elamin, Ashraf; Titz, Bjoern; Dijon, Sophie; Merg, Celine; Geertz, Marcel; Schneider, Thomas; Martin, Florian; Schlage, Walter K; Frentzel, Stefan; Talamo, Fabio; Phillips, Blaine; Veljkovic, Emilija; Ivanov, Nikolai V; Vanscheeuwijck, Patrick; Peitsch, Manuel C; Hoeng, Julia

2016-08-11

Smoking is associated with several serious diseases, such as lung cancer and chronic obstructive pulmonary disease (COPD). Within our systems toxicology framework, we are assessing whether potential modified risk tobacco products (MRTP) can reduce smoking-related health risks compared to conventional cigarettes. In this article, we evaluated to what extent 2D-PAGE/MALDI MS/MS (2D-PAGE) can complement the iTRAQ LC-MS/MS results from a previously reported mouse inhalation study, in which we assessed a prototypic MRTP (pMRTP). Selected differentially expressed proteins identified by both LC-MS/MS and 2D-PAGE approaches were further verified using reverse-phase protein microarrays. LC-MS/MS captured the effects of cigarette smoke (CS) on the lung proteome more comprehensively than 2D-PAGE. However, an integrated analysis of both proteomics data sets showed that 2D-PAGE data complement the LC-MS/MS results by supporting the overall trend of lower effects of pMRTP aerosol than CS on the lung proteome. Biological effects of CS exposure supported by both methods included increases in immune-related, surfactant metabolism, proteasome, and actin cytoskeleton protein clusters. Overall, while 2D-PAGE has its value, especially as a complementary method for the analysis of effects on intact proteins, LC-MS/MS approaches will likely be the method of choice for proteome analysis in systems toxicology investigations. Quantitative proteomics is anticipated to play a growing role within systems toxicology assessment frameworks in the future. To further understand how different proteomics technologies can contribute to toxicity assessment, we conducted a quantitative proteomics analysis using 2D-PAGE and isobaric tag-based LC-MS/MS approaches and compared the results produced from the 2 approaches. Using a prototypic modified risk tobacco product (pMRTP) as our test item, we show compared with cigarette smoke, how 2D-PAGE results can complement and support LC-MS/MS data, demonstrating the much lower effects of pMRTP aerosol than cigarette smoke on the mouse lung proteome. The combined analysis of 2D-PAGE and LC-MS/MS data identified an effect of cigarette smoke on the proteasome and actin cytoskeleton in the lung. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

YPED: An Integrated Bioinformatics Suite and Database for Mass Spectrometry-based Proteomics Research

PubMed Central

Colangelo, Christopher M.; Shifman, Mark; Cheung, Kei-Hoi; Stone, Kathryn L.; Carriero, Nicholas J.; Gulcicek, Erol E.; Lam, TuKiet T.; Wu, Terence; Bjornson, Robert D.; Bruce, Can; Nairn, Angus C.; Rinehart, Jesse; Miller, Perry L.; Williams, Kenneth R.

2015-01-01

We report a significantly-enhanced bioinformatics suite and database for proteomics research called Yale Protein Expression Database (YPED) that is used by investigators at more than 300 institutions worldwide. YPED meets the data management, archival, and analysis needs of a high-throughput mass spectrometry-based proteomics research ranging from a single laboratory, group of laboratories within and beyond an institution, to the entire proteomics community. The current version is a significant improvement over the first version in that it contains new modules for liquid chromatography–tandem mass spectrometry (LC–MS/MS) database search results, label and label-free quantitative proteomic analysis, and several scoring outputs for phosphopeptide site localization. In addition, we have added both peptide and protein comparative analysis tools to enable pairwise analysis of distinct peptides/proteins in each sample and of overlapping peptides/proteins between all samples in multiple datasets. We have also implemented a targeted proteomics module for automated multiple reaction monitoring (MRM)/selective reaction monitoring (SRM) assay development. We have linked YPED’s database search results and both label-based and label-free fold-change analysis to the Skyline Panorama repository for online spectra visualization. In addition, we have built enhanced functionality to curate peptide identifications into an MS/MS peptide spectral library for all of our protein database search identification results. PMID:25712262

Advances in targeted proteomics and applications to biomedical research

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shi, Tujin; Song, Ehwang; Nie, Song

Targeted proteomics technique has emerged as a powerful protein quantification tool in systems biology, biomedical research, and increasing for clinical applications. The most widely used targeted proteomics approach, selected reaction monitoring (SRM), also known as multiple reaction monitoring (MRM), can be used for quantification of cellular signaling networks and preclinical verification of candidate protein biomarkers. As an extension to our previous review on advances in SRM sensitivity (Shi et al., Proteomics, 12, 1074–1092, 2012) herein we review recent advances in the method and technology for further enhancing SRM sensitivity (from 2012 to present), and highlighting its broad biomedical applications inmore » human bodily fluids, tissue and cell lines. Furthermore, we also review two recently introduced targeted proteomics approaches, parallel reaction monitoring (PRM) and data-independent acquisition (DIA) with targeted data extraction on fast scanning high-resolution accurate-mass (HR/AM) instruments. Such HR/AM targeted quantification with monitoring all target product ions addresses SRM limitations effectively in specificity and multiplexing; whereas when compared to SRM, PRM and DIA are still in the infancy with a limited number of applications. Thus, for HR/AM targeted quantification we focus our discussion on method development, data processing and analysis, and its advantages and limitations in targeted proteomics. Finally, general perspectives on the potential of achieving both high sensitivity and high sample throughput for large-scale quantification of hundreds of target proteins are discussed.« less

YPED: an integrated bioinformatics suite and database for mass spectrometry-based proteomics research.

PubMed

Colangelo, Christopher M; Shifman, Mark; Cheung, Kei-Hoi; Stone, Kathryn L; Carriero, Nicholas J; Gulcicek, Erol E; Lam, TuKiet T; Wu, Terence; Bjornson, Robert D; Bruce, Can; Nairn, Angus C; Rinehart, Jesse; Miller, Perry L; Williams, Kenneth R

2015-02-01

We report a significantly-enhanced bioinformatics suite and database for proteomics research called Yale Protein Expression Database (YPED) that is used by investigators at more than 300 institutions worldwide. YPED meets the data management, archival, and analysis needs of a high-throughput mass spectrometry-based proteomics research ranging from a single laboratory, group of laboratories within and beyond an institution, to the entire proteomics community. The current version is a significant improvement over the first version in that it contains new modules for liquid chromatography-tandem mass spectrometry (LC-MS/MS) database search results, label and label-free quantitative proteomic analysis, and several scoring outputs for phosphopeptide site localization. In addition, we have added both peptide and protein comparative analysis tools to enable pairwise analysis of distinct peptides/proteins in each sample and of overlapping peptides/proteins between all samples in multiple datasets. We have also implemented a targeted proteomics module for automated multiple reaction monitoring (MRM)/selective reaction monitoring (SRM) assay development. We have linked YPED's database search results and both label-based and label-free fold-change analysis to the Skyline Panorama repository for online spectra visualization. In addition, we have built enhanced functionality to curate peptide identifications into an MS/MS peptide spectral library for all of our protein database search identification results. Copyright © 2015 The Authors. Production and hosting by Elsevier Ltd.. All rights reserved.

High-throughput image analysis of tumor spheroids: a user-friendly software application to measure the size of spheroids automatically and accurately.

PubMed

Chen, Wenjin; Wong, Chung; Vosburgh, Evan; Levine, Arnold J; Foran, David J; Xu, Eugenia Y

2014-07-08

The increasing number of applications of three-dimensional (3D) tumor spheroids as an in vitro model for drug discovery requires their adaptation to large-scale screening formats in every step of a drug screen, including large-scale image analysis. Currently there is no ready-to-use and free image analysis software to meet this large-scale format. Most existing methods involve manually drawing the length and width of the imaged 3D spheroids, which is a tedious and time-consuming process. This study presents a high-throughput image analysis software application - SpheroidSizer, which measures the major and minor axial length of the imaged 3D tumor spheroids automatically and accurately; calculates the volume of each individual 3D tumor spheroid; then outputs the results in two different forms in spreadsheets for easy manipulations in the subsequent data analysis. The main advantage of this software is its powerful image analysis application that is adapted for large numbers of images. It provides high-throughput computation and quality-control workflow. The estimated time to process 1,000 images is about 15 min on a minimally configured laptop, or around 1 min on a multi-core performance workstation. The graphical user interface (GUI) is also designed for easy quality control, and users can manually override the computer results. The key method used in this software is adapted from the active contour algorithm, also known as Snakes, which is especially suitable for images with uneven illumination and noisy background that often plagues automated imaging processing in high-throughput screens. The complimentary "Manual Initialize" and "Hand Draw" tools provide the flexibility to SpheroidSizer in dealing with various types of spheroids and diverse quality images. This high-throughput image analysis software remarkably reduces labor and speeds up the analysis process. Implementing this software is beneficial for 3D tumor spheroids to become a routine in vitro model for drug screens in industry and academia.

High-throughput sperm differential proteomics suggests that epigenetic alterations contribute to failed assisted reproduction.

PubMed

Azpiazu, Rubén; Amaral, Alexandra; Castillo, Judit; Estanyol, Josep Maria; Guimerà, Marta; Ballescà, Josep Lluís; Balasch, Juan; Oliva, Rafael

2014-06-01

Are there quantitative alterations in the proteome of normozoospermic sperm samples that are able to complete IVF but whose female partner does not achieve pregnancy? Normozoospermic sperm samples with different IVF outcomes (pregnancy versus no pregnancy) differed in the levels of at least 66 proteins. The analysis of the proteome of sperm samples with distinct fertilization capacity using low-throughput proteomic techniques resulted in the detection of a few differential proteins. Current high-throughput mass spectrometry approaches allow the identification and quantification of a substantially higher number of proteins. This was a case-control study including 31 men with normozoospermic sperm and their partners who underwent IVF with successful fertilization recruited between 2007 and 2008. Normozoospermic sperm samples from 15 men whose female partners did not achieve pregnancy after IVF (no pregnancy) and 16 men from couples that did achieve pregnancy after IVF (pregnancy) were included in this study. To perform the differential proteomic experiments, 10 no pregnancy samples and 10 pregnancy samples were separately pooled and subsequently used for tandem mass tags (TMT) protein labelling, sodium dodecyl sulphate-polyacrylamide gel electrophoresis, liquid chromatography tandem mass spectrometry (LC-MS/MS) identification and peak intensity relative protein quantification. Bioinformatic analyses were performed using UniProt Knowledgebase, DAVID and Reactome. Individual samples (n = 5 no pregnancy samples; n = 6 pregnancy samples) and aliquots from the above TMT pools were used for western blotting. By using TMT labelling and LC-MS/MS, we have detected 31 proteins present at lower abundance (ratio no pregnancy/pregnancy < 0.67) and 35 at higher abundance (ratio no pregnancy/pregnancy > 1.5) in the no pregnancy group. Bioinformatic analyses showed that the proteins with differing abundance are involved in chromatin assembly and lipoprotein metabolism (P values < 0.05). In addition, the differential abundance of one of the proteins (SRSF protein kinase 1) was further validated by western blotting using independent samples (P value < 0.01). For individual samples the amount of recovered sperm not used for IVF was low and in most of the cases insufficient for MS analysis, therefore pools of samples had to be used to this end. Alterations in the proteins involved in chromatin assembly and metabolism may result in epigenetic errors during spermatogenesis, leading to inaccurate sperm epigenetic signatures, which could ultimately prevent embryonic development. These sperm proteins may thus possibly have clinical relevance. This work was supported by the Spanish Ministry of Economy and Competitiveness (Ministerio de Economia y Competividad; FEDER BFU 2009-07118 and PI13/00699) and Fundación Salud 2000 SERONO13-015. There are no competing interests to declare.

VESPA: software to facilitate genomic annotation of prokaryotic organisms through integration of proteomic and transcriptomic data.

PubMed

Peterson, Elena S; McCue, Lee Ann; Schrimpe-Rutledge, Alexandra C; Jensen, Jeffrey L; Walker, Hyunjoo; Kobold, Markus A; Webb, Samantha R; Payne, Samuel H; Ansong, Charles; Adkins, Joshua N; Cannon, William R; Webb-Robertson, Bobbie-Jo M

2012-04-05

The procedural aspects of genome sequencing and assembly have become relatively inexpensive, yet the full, accurate structural annotation of these genomes remains a challenge. Next-generation sequencing transcriptomics (RNA-Seq), global microarrays, and tandem mass spectrometry (MS/MS)-based proteomics have demonstrated immense value to genome curators as individual sources of information, however, integrating these data types to validate and improve structural annotation remains a major challenge. Current visual and statistical analytic tools are focused on a single data type, or existing software tools are retrofitted to analyze new data forms. We present Visual Exploration and Statistics to Promote Annotation (VESPA) is a new interactive visual analysis software tool focused on assisting scientists with the annotation of prokaryotic genomes though the integration of proteomics and transcriptomics data with current genome location coordinates. VESPA is a desktop Java™ application that integrates high-throughput proteomics data (peptide-centric) and transcriptomics (probe or RNA-Seq) data into a genomic context, all of which can be visualized at three levels of genomic resolution. Data is interrogated via searches linked to the genome visualizations to find regions with high likelihood of mis-annotation. Search results are linked to exports for further validation outside of VESPA or potential coding-regions can be analyzed concurrently with the software through interaction with BLAST. VESPA is demonstrated on two use cases (Yersinia pestis Pestoides F and Synechococcus sp. PCC 7002) to demonstrate the rapid manner in which mis-annotations can be found and explored in VESPA using either proteomics data alone, or in combination with transcriptomic data. VESPA is an interactive visual analytics tool that integrates high-throughput data into a genomic context to facilitate the discovery of structural mis-annotations in prokaryotic genomes. Data is evaluated via visual analysis across multiple levels of genomic resolution, linked searches and interaction with existing bioinformatics tools. We highlight the novel functionality of VESPA and core programming requirements for visualization of these large heterogeneous datasets for a client-side application. The software is freely available at https://www.biopilot.org/docs/Software/Vespa.php.

VESPA: software to facilitate genomic annotation of prokaryotic organisms through integration of proteomic and transcriptomic data

PubMed Central

2012-01-01

Background The procedural aspects of genome sequencing and assembly have become relatively inexpensive, yet the full, accurate structural annotation of these genomes remains a challenge. Next-generation sequencing transcriptomics (RNA-Seq), global microarrays, and tandem mass spectrometry (MS/MS)-based proteomics have demonstrated immense value to genome curators as individual sources of information, however, integrating these data types to validate and improve structural annotation remains a major challenge. Current visual and statistical analytic tools are focused on a single data type, or existing software tools are retrofitted to analyze new data forms. We present Visual Exploration and Statistics to Promote Annotation (VESPA) is a new interactive visual analysis software tool focused on assisting scientists with the annotation of prokaryotic genomes though the integration of proteomics and transcriptomics data with current genome location coordinates. Results VESPA is a desktop Java™ application that integrates high-throughput proteomics data (peptide-centric) and transcriptomics (probe or RNA-Seq) data into a genomic context, all of which can be visualized at three levels of genomic resolution. Data is interrogated via searches linked to the genome visualizations to find regions with high likelihood of mis-annotation. Search results are linked to exports for further validation outside of VESPA or potential coding-regions can be analyzed concurrently with the software through interaction with BLAST. VESPA is demonstrated on two use cases (Yersinia pestis Pestoides F and Synechococcus sp. PCC 7002) to demonstrate the rapid manner in which mis-annotations can be found and explored in VESPA using either proteomics data alone, or in combination with transcriptomic data. Conclusions VESPA is an interactive visual analytics tool that integrates high-throughput data into a genomic context to facilitate the discovery of structural mis-annotations in prokaryotic genomes. Data is evaluated via visual analysis across multiple levels of genomic resolution, linked searches and interaction with existing bioinformatics tools. We highlight the novel functionality of VESPA and core programming requirements for visualization of these large heterogeneous datasets for a client-side application. The software is freely available at https://www.biopilot.org/docs/Software/Vespa.php. PMID:22480257

The Successful Diagnosis and Typing of Systemic Amyloidosis Using A Microwave-Assisted Filter-Aided Fast Sample Preparation Method and LC/MS/MS Analysis

PubMed Central

Zou, Lili; Shen, Kaini; Zhong, Dingrong; Zhou, Daobin; Sun, Wei; Li, Jian

2015-01-01

Laser microdissection followed by mass spectrometry has been successfully used for amyloid typing. However, sample contamination can interfere with proteomic analysis, and overnight digestion limits the analytical throughput. Moreover, current quantitative analysis methods are based on the spectrum count, which ignores differences in protein length and may lead to misdiagnoses. Here, we developed a microwave-assisted filter-aided sample preparation (maFASP) method that can efficiently remove contaminants with a 10-kDa cutoff ultrafiltration unit and can accelerate the digestion process with the assistance of a microwave. Additionally, two parameters (P- and D-scores) based on the exponentially modified protein abundance index were developed to define the existence of amyloid deposits and those causative proteins with the greatest abundance. Using our protocol, twenty cases of systemic amyloidosis that were well-typed according to clinical diagnostic standards (training group) and another twenty-four cases without subtype diagnoses (validation group) were analyzed. Using this approach, sample preparation could be completed within four hours. We successfully subtyped 100% of the cases in the training group, and the diagnostic success rate in the validation group was 91.7%. This maFASP-aided proteomic protocol represents an efficient approach for amyloid diagnosis and subtyping, particularly for serum-contaminated samples. PMID:25984759

High Dynamic Range Characterization of the Trauma Patient Plasma Proteome

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Tao; Qian, Weijun; Gritsenko, Marina A.

2006-06-08

While human plasma represents an attractive sample for disease biomarker discovery, the extreme complexity and large dynamic range in protein concentrations present significant challenges for characterization, candidate biomarker discovery, and validation. Herein, we describe a strategy that combines immunoaffinity subtraction and chemical fractionation based on cysteinyl peptide and N-glycopeptide captures with 2D-LC-MS/MS to increase the dynamic range of analysis for plasma. Application of this ''divide-and-conquer'' strategy to trauma patient plasma significantly improved the overall dynamic range of detection and resulted in confident identification of 22,267 unique peptides from four different peptide populations (cysteinyl peptides, non-cysteinyl peptides, N-glycopeptides, and non-glycopeptides) thatmore » covered 3654 nonredundant proteins. Numerous low-abundance proteins were identified, exemplified by 78 ''classic'' cytokines and cytokine receptors and by 136 human cell differentiation molecules. Additionally, a total of 2910 different N-glycopeptides that correspond to 662 N-glycoproteins and 1553 N-glycosylation sites were identified. A panel of the proteins identified in this study is known to be involved in inflammation and immune responses. This study established an extensive reference protein database for trauma patients, which provides a foundation for future high-throughput quantitative plasma proteomic studies designed to elucidate the mechanisms that underlie systemic inflammatory responses.« less

Photon-Counting H33D Detector for Biological Fluorescence Imaging

PubMed Central

Michalet, X.; Siegmund, O.H.W.; Vallerga, J.V.; Jelinsky, P.; Millaud, J.E.; Weiss, S.

2010-01-01

We have developed a photon-counting High-temporal and High-spatial resolution, High-throughput 3-Dimensional detector (H33D) for biological imaging of fluorescent samples. The design is based on a 25 mm diameter S20 photocathode followed by a 3-microchannel plate stack, and a cross delay line anode. We describe the bench performance of the H33D detector, as well as preliminary imaging results obtained with fluorescent beads, quantum dots and live cells and discuss applications of future generation detectors for single-molecule imaging and high-throughput study of biomolecular interactions. PMID:20151021

Curated protein information in the Saccharomyces genome database.

PubMed

Hellerstedt, Sage T; Nash, Robert S; Weng, Shuai; Paskov, Kelley M; Wong, Edith D; Karra, Kalpana; Engel, Stacia R; Cherry, J Michael

2017-01-01

Due to recent advancements in the production of experimental proteomic data, the Saccharomyces genome database (SGD; www.yeastgenome.org ) has been expanding our protein curation activities to make new data types available to our users. Because of broad interest in post-translational modifications (PTM) and their importance to protein function and regulation, we have recently started incorporating expertly curated PTM information on individual protein pages. Here we also present the inclusion of new abundance and protein half-life data obtained from high-throughput proteome studies. These new data types have been included with the aim to facilitate cellular biology research. : www.yeastgenome.org. © The Author(s) 2017. Published by Oxford University Press.

File Formats Commonly Used in Mass Spectrometry Proteomics*

PubMed Central

Deutsch, Eric W.

2012-01-01

The application of mass spectrometry (MS) to the analysis of proteomes has enabled the high-throughput identification and abundance measurement of hundreds to thousands of proteins per experiment. However, the formidable informatics challenge associated with analyzing MS data has required a wide variety of data file formats to encode the complex data types associated with MS workflows. These formats encompass the encoding of input instruction for instruments, output products of the instruments, and several levels of information and results used by and produced by the informatics analysis tools. A brief overview of the most common file formats in use today is presented here, along with a discussion of related topics. PMID:22956731

Proteomic comparison of 3D and 2D glioma models reveals increased HLA-E expression in 3D models is associated with resistance to NK cell-mediated cytotoxicity.

PubMed

He, Weiqi; Kuang, Yongqin; Xing, Xuemin; Simpson, Richard J; Huang, Haidong; Yang, Tao; Chen, Jingmin; Yang, Libin; Liu, Enyu; He, Weifeng; Gu, Jianwen

2014-05-02

Three-dimensional cell culture techniques can better reflect the in vivo characteristics of tumor cells compared with traditional monolayer cultures. Compared with their 2D counterparts, 3D-cultured tumor cells showed enhanced resistance to the cytotoxic T cell-mediated immune response. However, it remains unclear whether 3D-cultured tumor cells have an enhanced resistance to NK cell cytotoxicity. In this study, a total of 363 differentially expressed proteins were identified between the 2D- and 3D-cultured U251 cells by comparative proteomics, and an immune-associated protein-protein interaction (PPI) network based on these differential proteins was constructed by bioinformatics. Within the network, HLA-E, as a molecule for inhibiting NK cell activation, was significantly up-regulated in the 3D-cultured tumor cells. Then, we found that the 3D-cultured U251 cells exhibited potent resistance to NK cell cytotoxicity in vitro and were prone to tumor formation in vivo. The resistance of the 3D-cultured tumor cells to NK cell lysis was mediated by the HLA-E/NKG2A interaction because the administration of antibodies that block either HLA-E or NKG2A completely eliminated this resistance and significantly decreased tumor formation. Taken together, our findings indicate that HLA-E up-regulation in 3D-cultured cells may result in enhanced tumor resistance to NK cell-mediated immune response.

Quantitative Live-Cell Confocal Imaging of 3D Spheroids in a High-Throughput Format.

PubMed

Leary, Elizabeth; Rhee, Claire; Wilks, Benjamin T; Morgan, Jeffrey R

2018-06-01

Accurately predicting the human response to new compounds is critical to a wide variety of industries. Standard screening pipelines (including both in vitro and in vivo models) often lack predictive power. Three-dimensional (3D) culture systems of human cells, a more physiologically relevant platform, could provide a high-throughput, automated means to test the efficacy and/or toxicity of novel substances. However, the challenge of obtaining high-magnification, confocal z stacks of 3D spheroids and understanding their respective quantitative limitations must be overcome first. To address this challenge, we developed a method to form spheroids of reproducible size at precise spatial locations across a 96-well plate. Spheroids of variable radii were labeled with four different fluorescent dyes and imaged with a high-throughput confocal microscope. 3D renderings of the spheroid had a complex bowl-like appearance. We systematically analyzed these confocal z stacks to determine the depth of imaging and the effect of spheroid size and dyes on quantitation. Furthermore, we have shown that this loss of fluorescence can be addressed through the use of ratio imaging. Overall, understanding both the limitations of confocal imaging and the tools to correct for these limits is critical for developing accurate quantitative assays using 3D spheroids.

SpirPro: A Spirulina proteome database and web-based tools for the analysis of protein-protein interactions at the metabolic level in Spirulina (Arthrospira) platensis C1.

PubMed

Senachak, Jittisak; Cheevadhanarak, Supapon; Hongsthong, Apiradee

2015-07-29

Spirulina (Arthrospira) platensis is the only cyanobacterium that in addition to being studied at the molecular level and subjected to gene manipulation, can also be mass cultivated in outdoor ponds for commercial use as a food supplement. Thus, encountering environmental changes, including temperature stresses, is common during the mass production of Spirulina. The use of cyanobacteria as an experimental platform, especially for photosynthetic gene manipulation in plants and bacteria, is becoming increasingly important. Understanding the mechanisms and protein-protein interaction networks that underlie low- and high-temperature responses is relevant to Spirulina mass production. To accomplish this goal, high-throughput techniques such as OMICs analyses are used. Thus, large datasets must be collected, managed and subjected to information extraction. Therefore, databases including (i) proteomic analysis and protein-protein interaction (PPI) data and (ii) domain/motif visualization tools are required for potential use in temperature response models for plant chloroplasts and photosynthetic bacteria. A web-based repository was developed including an embedded database, SpirPro, and tools for network visualization. Proteome data were analyzed integrated with protein-protein interactions and/or metabolic pathways from KEGG. The repository provides various information, ranging from raw data (2D-gel images) to associated results, such as data from interaction and/or pathway analyses. This integration allows in silico analyses of protein-protein interactions affected at the metabolic level and, particularly, analyses of interactions between and within the affected metabolic pathways under temperature stresses for comparative proteomic analysis. The developed tool, which is coded in HTML with CSS/JavaScript and depicted in Scalable Vector Graphics (SVG), is designed for interactive analysis and exploration of the constructed network. SpirPro is publicly available on the web at http://spirpro.sbi.kmutt.ac.th . SpirPro is an analysis platform containing an integrated proteome and PPI database that provides the most comprehensive data on this cyanobacterium at the systematic level. As an integrated database, SpirPro can be applied in various analyses, such as temperature stress response networking analysis in cyanobacterial models and interacting domain-domain analysis between proteins of interest.

Integrated network analysis and effective tools in plant systems biology

PubMed Central

Fukushima, Atsushi; Kanaya, Shigehiko; Nishida, Kozo

2014-01-01

One of the ultimate goals in plant systems biology is to elucidate the genotype-phenotype relationship in plant cellular systems. Integrated network analysis that combines omics data with mathematical models has received particular attention. Here we focus on the latest cutting-edge computational advances that facilitate their combination. We highlight (1) network visualization tools, (2) pathway analyses, (3) genome-scale metabolic reconstruction, and (4) the integration of high-throughput experimental data and mathematical models. Multi-omics data that contain the genome, transcriptome, proteome, and metabolome and mathematical models are expected to integrate and expand our knowledge of complex plant metabolisms. PMID:25408696

Introducing the CPL/MUW proteome database: interpretation of human liver and liver cancer proteome profiles by referring to isolated primary cells.

PubMed

Wimmer, Helge; Gundacker, Nina C; Griss, Johannes; Haudek, Verena J; Stättner, Stefan; Mohr, Thomas; Zwickl, Hannes; Paulitschke, Verena; Baron, David M; Trittner, Wolfgang; Kubicek, Markus; Bayer, Editha; Slany, Astrid; Gerner, Christopher

2009-06-01

Interpretation of proteome data with a focus on biomarker discovery largely relies on comparative proteome analyses. Here, we introduce a database-assisted interpretation strategy based on proteome profiles of primary cells. Both 2-D-PAGE and shotgun proteomics are applied. We obtain high data concordance with these two different techniques. When applying mass analysis of tryptic spot digests from 2-D gels of cytoplasmic fractions, we typically identify several hundred proteins. Using the same protein fractions, we usually identify more than thousand proteins by shotgun proteomics. The data consistency obtained when comparing these independent data sets exceeds 99% of the proteins identified in the 2-D gels. Many characteristic differences in protein expression of different cells can thus be independently confirmed. Our self-designed SQL database (CPL/MUW - database of the Clinical Proteomics Laboratories at the Medical University of Vienna accessible via www.meduniwien.ac.at/proteomics/database) facilitates (i) quality management of protein identification data, which are based on MS, (ii) the detection of cell type-specific proteins and (iii) of molecular signatures of specific functional cell states. Here, we demonstrate, how the interpretation of proteome profiles obtained from human liver tissue and hepatocellular carcinoma tissue is assisted by the Clinical Proteomics Laboratories at the Medical University of Vienna-database. Therefore, we suggest that the use of reference experiments supported by a tailored database may substantially facilitate data interpretation of proteome profiling experiments.

Three-dimensional Imaging and Scanning: Current and Future Applications for Pathology

PubMed Central

Farahani, Navid; Braun, Alex; Jutt, Dylan; Huffman, Todd; Reder, Nick; Liu, Zheng; Yagi, Yukako; Pantanowitz, Liron

2017-01-01

Imaging is vital for the assessment of physiologic and phenotypic details. In the past, biomedical imaging was heavily reliant on analog, low-throughput methods, which would produce two-dimensional images. However, newer, digital, and high-throughput three-dimensional (3D) imaging methods, which rely on computer vision and computer graphics, are transforming the way biomedical professionals practice. 3D imaging has been useful in diagnostic, prognostic, and therapeutic decision-making for the medical and biomedical professions. Herein, we summarize current imaging methods that enable optimal 3D histopathologic reconstruction: Scanning, 3D scanning, and whole slide imaging. Briefly mentioned are emerging platforms, which combine robotics, sectioning, and imaging in their pursuit to digitize and automate the entire microscopy workflow. Finally, both current and emerging 3D imaging methods are discussed in relation to current and future applications within the context of pathology. PMID:28966836

3D-SURFER: software for high-throughput protein surface comparison and analysis

PubMed Central

La, David; Esquivel-Rodríguez, Juan; Venkatraman, Vishwesh; Li, Bin; Sael, Lee; Ueng, Stephen; Ahrendt, Steven; Kihara, Daisuke

2009-01-01

Summary: We present 3D-SURFER, a web-based tool designed to facilitate high-throughput comparison and characterization of proteins based on their surface shape. As each protein is effectively represented by a vector of 3D Zernike descriptors, comparison times for a query protein against the entire PDB take, on an average, only a couple of seconds. The web interface has been designed to be as interactive as possible with displays showing animated protein rotations, CATH codes and structural alignments using the CE program. In addition, geometrically interesting local features of the protein surface, such as pockets that often correspond to ligand binding sites as well as protrusions and flat regions can also be identified and visualized. Availability: 3D-SURFER is a web application that can be freely accessed from: http://dragon.bio.purdue.edu/3d-surfer Contact: dkihara@purdue.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:19759195

3D-SURFER: software for high-throughput protein surface comparison and analysis.

PubMed

La, David; Esquivel-Rodríguez, Juan; Venkatraman, Vishwesh; Li, Bin; Sael, Lee; Ueng, Stephen; Ahrendt, Steven; Kihara, Daisuke

2009-11-01

We present 3D-SURFER, a web-based tool designed to facilitate high-throughput comparison and characterization of proteins based on their surface shape. As each protein is effectively represented by a vector of 3D Zernike descriptors, comparison times for a query protein against the entire PDB take, on an average, only a couple of seconds. The web interface has been designed to be as interactive as possible with displays showing animated protein rotations, CATH codes and structural alignments using the CE program. In addition, geometrically interesting local features of the protein surface, such as pockets that often correspond to ligand binding sites as well as protrusions and flat regions can also be identified and visualized. 3D-SURFER is a web application that can be freely accessed from: http://dragon.bio.purdue.edu/3d-surfer dkihara@purdue.edu Supplementary data are available at Bioinformatics online.

Proteomic Analyses of the Unexplored Sea Anemone Bunodactis verrucosa

PubMed Central

Campos, Alexandre; Turkina, Maria V.; Ribeiro, Tiago; Osorio, Hugo; Vasconcelos, Vítor; Antunes, Agostinho

2018-01-01

Cnidarian toxic products, particularly peptide toxins, constitute a promising target for biomedicine research. Indeed, cnidarians are considered as the largest phylum of generally toxic animals. However, research on peptides and toxins of sea anemones is still limited. Moreover, most of the toxins from sea anemones have been discovered by classical purification approaches. Recently, high-throughput methodologies have been used for this purpose but in other Phyla. Hence, the present work was focused on the proteomic analyses of whole-body extract from the unexplored sea anemone Bunodactis verrucosa. The proteomic analyses applied were based on two methods: two-dimensional gel electrophoresis combined with MALDI-TOF/TOF and shotgun proteomic approach. In total, 413 proteins were identified, but only eight proteins were identified from gel-based analyses. Such proteins are mainly involved in basal metabolism and biosynthesis of antibiotics as the most relevant pathways. In addition, some putative toxins including metalloproteinases and neurotoxins were also identified. These findings reinforce the significance of the production of antimicrobial compounds and toxins by sea anemones, which play a significant role in defense and feeding. In general, the present study provides the first proteome map of the sea anemone B. verrucosa stablishing a reference for future studies in the discovery of new compounds. PMID:29364843

Proteomic Analyses of the Unexplored Sea Anemone Bunodactis verrucosa.

PubMed

Domínguez-Pérez, Dany; Campos, Alexandre; Alexei Rodríguez, Armando; Turkina, Maria V; Ribeiro, Tiago; Osorio, Hugo; Vasconcelos, Vítor; Antunes, Agostinho

2018-01-24

Cnidarian toxic products, particularly peptide toxins, constitute a promising target for biomedicine research. Indeed, cnidarians are considered as the largest phylum of generally toxic animals. However, research on peptides and toxins of sea anemones is still limited. Moreover, most of the toxins from sea anemones have been discovered by classical purification approaches. Recently, high-throughput methodologies have been used for this purpose but in other Phyla. Hence, the present work was focused on the proteomic analyses of whole-body extract from the unexplored sea anemone Bunodactis verrucosa . The proteomic analyses applied were based on two methods: two-dimensional gel electrophoresis combined with MALDI-TOF/TOF and shotgun proteomic approach. In total, 413 proteins were identified, but only eight proteins were identified from gel-based analyses. Such proteins are mainly involved in basal metabolism and biosynthesis of antibiotics as the most relevant pathways. In addition, some putative toxins including metalloproteinases and neurotoxins were also identified. These findings reinforce the significance of the production of antimicrobial compounds and toxins by sea anemones, which play a significant role in defense and feeding. In general, the present study provides the first proteome map of the sea anemone B. verrucosa stablishing a reference for future studies in the discovery of new compounds.

Proteomics technique opens new frontiers in mobilome research

PubMed Central

Davidson, Andrew D.; Matthews, David A.

2017-01-01

ABSTRACT A large proportion of the genome of most eukaryotic organisms consists of highly repetitive mobile genetic elements. The sum of these elements is called the “mobilome,” which in eukaryotes is made up mostly of transposons. Transposable elements contribute to disease, evolution, and normal physiology by mediating genetic rearrangement, and through the “domestication” of transposon proteins for cellular functions. Although ‘omics studies of mobilome genomes and transcriptomes are common, technical challenges have hampered high-throughput global proteomics analyses of transposons. In a recent paper, we overcame these technical hurdles using a technique called “proteomics informed by transcriptomics” (PIT), and thus published the first unbiased global mobilome-derived proteome for any organism (using cell lines derived from the mosquito Aedes aegypti). In this commentary, we describe our methods in more detail, and summarise our major findings. We also use new genome sequencing data to show that, in many cases, the specific genomic element expressing a given protein can be identified using PIT. This proteomic technique therefore represents an important technological advance that will open new avenues of research into the role that proteins derived from transposons and other repetitive and sequence diverse genetic elements, such as endogenous retroviruses, play in health and disease. PMID:28932623

Biphasic microreactor for efficient membrane protein pretreatment with a combination of formic acid assisted solubilization, on-column pH adjustment, reduction, alkylation, and tryptic digestion.

PubMed

Zhao, Qun; Liang, Yu; Yuan, Huiming; Sui, Zhigang; Wu, Qi; Liang, Zhen; Zhang, Lihua; Zhang, Yukui

2013-09-17

Combining good dissolving ability of formic acid (FA) for membrane proteins and excellent complementary retention behavior of proteins on strong cation exchange (SCX) and strong anion exchange (SAX) materials, a biphasic microreactor was established to pretreat membrane proteins at microgram and even nanogram levels. With membrane proteins solubilized by FA, all of the proteomics sample processing procedures, including protein preconcentration, pH adjustment, reduction, and alkylation, as well as tryptic digestion, were integrated into an "SCX-SAX" biphasic capillary column. To evaluate the performance of the developed microreactor, a mixture of bovine serum albumin, myoglobin, and cytochrome c was pretreated. Compared with the results obtained by the traditional in-solution process, the peptide recovery (93% vs 83%) and analysis throughput (3.5 vs 14 h) were obviously improved. The microreactor was further applied for the pretreatment of 14 μg of membrane proteins extracted from rat cerebellums, and 416 integral membrane proteins (IMPs) (43% of total protein groups) and 103 transmembrane peptides were identified by two-dimensional nanoliquid chromatography-electrospray ionization tandem mass spectrometry (2D nano-LC-ESI-MS/MS) in triplicate analysis. With the starting sample preparation amount decreased to as low as 50 ng, 64 IMPs and 17 transmembrane peptides were identified confidently, while those obtained by the traditional in-solution method were 10 and 1, respectively. All these results demonstrated that such an "SCX-SAX" based biphasic microreactor could offer a promising tool for the pretreatment of trace membrane proteins with high efficiency and throughput.

Quantitative Proteomics Analysis of Inborn Errors of Cholesterol Synthesis

PubMed Central

Jiang, Xiao-Sheng; Backlund, Peter S.; Wassif, Christopher A.; Yergey, Alfred L.; Porter, Forbes D.

2010-01-01

Smith-Lemli-Opitz syndrome (SLOS) and lathosterolosis are malformation syndromes with cognitive deficits caused by mutations of 7-dehydrocholesterol reductase (DHCR7) and lathosterol 5-desaturase (SC5D), respectively. DHCR7 encodes the last enzyme in the Kandutsch-Russel cholesterol biosynthetic pathway, and impaired DHCR7 activity leads to a deficiency of cholesterol and an accumulation of 7-dehydrocholesterol. SC5D catalyzes the synthesis of 7-dehydrocholesterol from lathosterol. Impaired SC5D activity leads to a similar deficiency of cholesterol but an accumulation of lathosterol. Although the genetic and biochemical causes underlying both syndromes are known, the pathophysiological processes leading to the developmental defects remain unclear. To study the pathophysiological mechanisms underlying SLOS and lathosterolosis neurological symptoms, we performed quantitative proteomics analysis of SLOS and lathosterolosis mouse brain tissue and identified multiple biological pathways affected in Dhcr7Δ3–5/Δ3–5 and Sc5d−/− E18.5 embryos. These include alterations in mevalonate metabolism, apoptosis, glycolysis, oxidative stress, protein biosynthesis, intracellular trafficking, and cytoskeleton. Comparison of proteome alterations in both Dhcr7Δ3–5/Δ3–5 and Sc5d−/− brain tissues helps elucidate whether perturbed protein expression was due to decreased cholesterol or a toxic effect of sterol precursors. Validation of the proteomics results confirmed increased expression of isoprenoid and cholesterol synthetic enzymes. This alteration of isoprenoid synthesis may underlie the altered posttranslational modification of Rab7, a small GTPase that is functionally dependent on prenylation with geranylgeranyl, that we identified and validated in this study. These data suggested that although cholesterol synthesis is impaired in both Dhcr7Δ3–5/Δ3–5 and Sc5d−/− embryonic brain tissues the synthesis of nonsterol isoprenoids may be increased and thus contribute to SLOS and lathosterolosis pathology. This proteomics study has provided insight into the pathophysiological mechanisms of SLOS and lathosterolosis, and understanding these pathophysiological changes will help guide clinical therapy for SLOS and lathosterolosis. PMID:20305089

High-resolution Antibody Array Analysis of Childhood Acute Leukemia Cells*

PubMed Central

Kanderova, Veronika; Kuzilkova, Daniela; Stuchly, Jan; Vaskova, Martina; Brdicka, Tomas; Fiser, Karel; Hrusak, Ondrej; Lund-Johansen, Fridtjof

2016-01-01

Acute leukemia is a disease pathologically manifested at both genomic and proteomic levels. Molecular genetic technologies are currently widely used in clinical research. In contrast, sensitive and high-throughput proteomic techniques for performing protein analyses in patient samples are still lacking. Here, we used a technology based on size exclusion chromatography followed by immunoprecipitation of target proteins with an antibody bead array (Size Exclusion Chromatography-Microsphere-based Affinity Proteomics, SEC-MAP) to detect hundreds of proteins from a single sample. In addition, we developed semi-automatic bioinformatics tools to adapt this technology for high-content proteomic screening of pediatric acute leukemia patients. To confirm the utility of SEC-MAP in leukemia immunophenotyping, we tested 31 leukemia diagnostic markers in parallel by SEC-MAP and flow cytometry. We identified 28 antibodies suitable for both techniques. Eighteen of them provided excellent quantitative correlation between SEC-MAP and flow cytometry (p < 0.05). Next, SEC-MAP was applied to examine 57 diagnostic samples from patients with acute leukemia. In this assay, we used 632 different antibodies and detected 501 targets. Of those, 47 targets were differentially expressed between at least two of the three acute leukemia subgroups. The CD markers correlated with immunophenotypic categories as expected. From non-CD markers, we found DBN1, PAX5, or PTK2 overexpressed in B-cell precursor acute lymphoblastic leukemias, LAT, SH2D1A, or STAT5A overexpressed in T-cell acute lymphoblastic leukemias, and HCK, GLUD1, or SYK overexpressed in acute myeloid leukemias. In addition, OPAL1 overexpression corresponded to ETV6-RUNX1 chromosomal translocation. In summary, we demonstrated that SEC-MAP technology is a powerful tool for detecting hundreds of proteins in clinical samples obtained from pediatric acute leukemia patients. It provides information about protein size and reveals differences in protein expression between particular leukemia subgroups. Forty-seven of SEC-MAP identified targets were validated by other conventional method in this study. PMID:26785729

Dr. Janie Merkel is interviewed by Ryan Blum and Janice Friend.

PubMed

Merkel, Janie

2007-12-01

Dr. Janie Merkel is the director of Yale's Chemical Genomics Screening Facility, a high-throughput screening laboratory that is part of the Yale University Center for Genomics and Proteomics. The Screening Facility connects Yale researchers with industry-quality robotic machinery and a diverse group of compound libraries, which have been used successfully to link therapeutic targets with potential therapies.

Multidimensional protein fractionation using ProteomeLab PF 2D™ for profiling amyotrophic lateral sclerosis immunity: A preliminary report

PubMed Central

Schlautman, Joshua D; Rozek, Wojciech; Stetler, Robert; Mosley, R Lee; Gendelman, Howard E; Ciborowski, Pawel

2008-01-01

Background The ProteomeLab™ PF 2D platform is a relatively new approach to global protein profiling. Herein, it was used for investigation of plasma proteome changes in amyotrophic lateral sclerosis (ALS) patients before and during immunization with glatiramer acetate (GA) in a clinical trial. Results The experimental design included immunoaffinity depletion of 12 most abundant proteins from plasma samples with the ProteomeLab™ IgY-12 LC10 column kit as first dimension separation, also referred to as immuno-partitioning. Second and third dimension separations of the enriched proteome were performed on the PF 2D platform utilizing 2D isoelectric focusing and RP-HPLC with the resulting fractions collected for analysis. 1D gel electrophoresis was added as a fourth dimension when sufficient protein was available. Protein identification from collected fractions was performed using nano-LC-MS/MS approach. Analysis of differences in the resulting two-dimensional maps of fractions obtained from the PF 2D and the ability to identify proteins from these fractions allowed sensitivity threshold measurements. Masked proteins in the PF 2D fractions are discussed. Conclusion We offer some insight into the strengths and limitations of this emerging proteomic platform. PMID:18789151

Comparative analysis of cerebrospinal fluid from the meningo-encephalitic stage of T. b. gambiense and rhodesiense sleeping sickness patients using TMT quantitative proteomics.

PubMed

Tiberti, Natalia; Sanchez, Jean-Charles

2015-09-01

The quantitative proteomics data here reported are part of a research article entitled "Increased acute immune response during the meningo-encephalitic stage of Trypanosoma brucei rhodesiense sleeping sickness compared to Trypanosoma brucei gambiense", published by Tiberti et al., 2015. Transl. Proteomics 6, 1-9. Sleeping sickness (human African trypanosomiasis - HAT) is a deadly neglected tropical disease affecting mainly rural communities in sub-Saharan Africa. This parasitic disease is caused by the Trypanosoma brucei (T. b.) parasite, which is transmitted to the human host through the bite of the tse-tse fly. Two parasite sub-species, T. b. rhodesiense and T. b. gambiense, are responsible for two clinically different and geographically separated forms of sleeping sickness. The objective of the present study was to characterise and compare the cerebrospinal fluid (CSF) proteome of stage 2 (meningo-encephalitic stage) HAT patients suffering from T. b. gambiense or T. b. rhodesiense disease using high-throughput quantitative proteomics and the Tandem Mass Tag (TMT(®)) isobaric labelling. In order to evaluate the CSF proteome in the context of HAT pathophysiology, the protein dataset was then submitted to gene ontology and pathway analysis. Two significantly differentially expressed proteins (C-reactive protein and orosomucoid 1) were further verified on a larger population of patients (n=185) by ELISA, confirming the mass spectrometry results. By showing a predominant involvement of the acute immune response in rhodesiense HAT, the proteomics results obtained in this work will contribute to further understand the mechanisms of pathology occurring in HAT and to propose new biomarkers of potential clinical utility. The mass spectrometry raw data are available in the Pride Archive via ProteomeXchange through the identifier PXD001082.

Proteogenomic insights into uranium tolerance of a Chernobyl's Microbacterium bacterial isolate.

PubMed

Gallois, Nicolas; Alpha-Bazin, Béatrice; Ortet, Philippe; Barakat, Mohamed; Piette, Laurie; Long, Justine; Berthomieu, Catherine; Armengaud, Jean; Chapon, Virginie

2018-04-15

Microbacterium oleivorans A9 is a uranium-tolerant actinobacteria isolated from the trench T22 located near the Chernobyl nuclear power plant. This site is contaminated with different radionuclides including uranium. To observe the molecular changes at the proteome level occurring in this strain upon uranyl exposure and understand molecular mechanisms explaining its uranium tolerance, we established its draft genome and used this raw information to perform an in-depth proteogenomics study. High-throughput proteomics were performed on cells exposed or not to 10μM uranyl nitrate sampled at three previously identified phases of uranyl tolerance. We experimentally detected and annotated 1532 proteins and highlighted a total of 591 proteins for which abundances were significantly differing between conditions. Notably, proteins involved in phosphate and iron metabolisms show high dynamics. A large ratio of proteins more abundant upon uranyl stress, are distant from functionally-annotated known proteins, highlighting the lack of fundamental knowledge regarding numerous key molecular players from soil bacteria. Microbacterium oleivorans A9 is an interesting environmental model to understand biological processes engaged in tolerance to radionuclides. Using an innovative proteogenomics approach, we explored its molecular mechanisms involved in uranium tolerance. We sequenced its genome, interpreted high-throughput proteomic data against a six-reading frame ORF database deduced from the draft genome, annotated the identified proteins and compared protein abundances from cells exposed or not to uranyl stress after a cascade search. These data show that a complex cellular response to uranium occurs in Microbacterium oleivorans A9, where one third of the experimental proteome is modified. In particular, the uranyl stress perturbed the phosphate and iron metabolic pathways. Furthermore, several transporters have been identified to be specifically associated to uranyl stress, paving the way to the development of biotechnological tools for uranium decontamination. Copyright © 2017. Published by Elsevier B.V.

Differential proteomics reveals the hallmarks of seed development in common bean (Phaseolus vulgaris L.).

PubMed

Parreira, J R; Bouraada, J; Fitzpatrick, M A; Silvestre, S; Bernardes da Silva, A; Marques da Silva, J; Almeida, A M; Fevereiro, P; Altelaar, A F M; Araújo, S S

2016-06-30

Common bean (Phaseolus vulgaris L.) is one of the most consumed staple foods worldwide. Little is known about the molecular mechanisms controlling seed development. This study aims to comprehensively describe proteome dynamics during seed development of common bean. A high-throughput gel-free proteomics approach (LC-MS/MS) was conducted on seeds at 10, 20, 30 and 40days after anthesis, spanning from late embryogenesis until desiccation. Of the 418 differentially accumulated proteins identified, 255 were characterized, most belonging to protein metabolism. An accumulation of proteins belonging to the MapMan functional categories of "protein", "glycolysis", "TCA", "DNA", "RNA", "cell" and "stress" were found at early seed development stages, reflecting an extensive metabolic activity. In the mid stages, accumulation of storage, signaling, starch synthesis and cell wall-related proteins stood out. In the later stages, an increase in proteins related to redox, protein degradation/modification/folding and nucleic acid metabolisms reflect that seed desiccation-resistance mechanisms were activated. Our study unveils new clues to understand the regulation of seed development mediated by post-translational modifications and maintenance of genome integrity. This knowledge enhances the understanding on seed development molecular mechanisms that may be used in the design and selection of common bean seeds with desired quality traits. Common bean (P. vulgaris) is an important source of proteins and carbohydrates worldwide. Despite the agronomic and economic importance of this pulse, knowledge on common bean seed development is limited. Herein, a gel-free high throughput methodology was used to describe the proteome changes during P. vulgaris seed development. Data obtained will enhance the knowledge on the molecular mechanisms controlling this grain legume seed development and may be used in the design and selection of common bean seeds with desired quality traits. Results may be extrapolated to other pulses. Copyright © 2016 Elsevier B.V. All rights reserved.

Analysis of the variability of human normal urine by 2D-GE reveals a "public" and a "private" proteome.

PubMed

Molina, Laurence; Salvetat, Nicolas; Ameur, Randa Ben; Peres, Sabine; Sommerer, Nicolas; Jarraya, Fayçal; Ayadi, Hammadi; Molina, Franck; Granier, Claude

2011-12-10

The characterization of the normal urinary proteome is steadily progressing and represents a major interest in the assessment of clinical urinary biomarkers. To estimate quantitatively the variability of the normal urinary proteome, urines of 20 healthy people were collected. We first evaluated the impact of the sample conservation temperature on urine proteome integrity. Keeping the urine sample at RT or at +4°C until storage at -80°C seems the best way for long-term storage of samples for 2D-GE analysis. The quantitative variability of the normal urinary proteome was estimated on the 20 urines mapped by 2D-GE. The occurrence of the 910 identified spots was analysed throughout the gels and represented in a virtual 2D gel. Sixteen percent of the spots were found to occur in all samples and 23% occurred in at least 90% of urines. About 13% of the protein spots were present only in 10% or less of the samples, thus representing the most variable part of the normal urinary proteome. Twenty proteins corresponding to a fraction of the fully conserved spots were identified by mass spectrometry. In conclusion, a "public" urinary proteome, common to healthy individuals, seems to coexist with a "private" urinary proteome, which is more specific to each individual. Copyright © 2011 Elsevier B.V. All rights reserved.

Construction of a nasopharyngeal carcinoma 2D/MS repository with Open Source XML database--Xindice.

PubMed

Li, Feng; Li, Maoyu; Xiao, Zhiqiang; Zhang, Pengfei; Li, Jianling; Chen, Zhuchu

2006-01-11

Many proteomics initiatives require integration of all information with uniformcriteria from collection of samples and data display to publication of experimental results. The integration and exchanging of these data of different formats and structure imposes a great challenge to us. The XML technology presents a promise in handling this task due to its simplicity and flexibility. Nasopharyngeal carcinoma (NPC) is one of the most common cancers in southern China and Southeast Asia, which has marked geographic and racial differences in incidence. Although there are some cancer proteome databases now, there is still no NPC proteome database. The raw NPC proteome experiment data were captured into one XML document with Human Proteome Markup Language (HUP-ML) editor and imported into native XML database Xindice. The 2D/MS repository of NPC proteome was constructed with Apache, PHP and Xindice to provide access to the database via Internet. On our website, two methods, keyword query and click query, were provided at the same time to access the entries of the NPC proteome database. Our 2D/MS repository can be used to share the raw NPC proteomics data that are generated from gel-based proteomics experiments. The database, as well as the PHP source codes for constructing users' own proteome repository, can be accessed at http://www.xyproteomics.org/.

A high-throughput three-dimensional cell migration assay for toxicity screening with mobile device-based macroscopic image analysis

PubMed Central

Timm, David M.; Chen, Jianbo; Sing, David; Gage, Jacob A.; Haisler, William L.; Neeley, Shane K.; Raphael, Robert M.; Dehghani, Mehdi; Rosenblatt, Kevin P.; Killian, T. C.; Tseng, Hubert; Souza, Glauco R.

2013-01-01

There is a growing demand for in vitro assays for toxicity screening in three-dimensional (3D) environments. In this study, 3D cell culture using magnetic levitation was used to create an assay in which cells were patterned into 3D rings that close over time. The rate of closure was determined from time-lapse images taken with a mobile device and related to drug concentration. Rings of human embryonic kidney cells (HEK293) and tracheal smooth muscle cells (SMCs) were tested with ibuprofen and sodium dodecyl sulfate (SDS). Ring closure correlated with the viability and migration of cells in two dimensions (2D). Images taken using a mobile device were similar in analysis to images taken with a microscope. Ring closure may serve as a promising label-free and quantitative assay for high-throughput in vivo toxicity in 3D cultures. PMID:24141454

Microfluidics for the analysis of membrane proteins: how do we get there?

PubMed

Battle, Katrina N; Uba, Franklin I; Soper, Steven A

2014-08-01

The development of fully automated and high-throughput systems for proteomics is now in demand because of the need to generate new protein-based disease biomarkers. Unfortunately, it is difficult to identify protein biomarkers that are low abundant when in the presence of highly abundant proteins, especially in complex biological samples such as serum, cell lysates, and other biological fluids. Membrane proteins, which are in many cases of low abundance compared to the cytosolic proteins, have various functions and can provide insight into the state of a disease and serve as targets for new drugs making them attractive biomarker candidates. Traditionally, proteins are identified through the use of gel electrophoretic techniques, which are not always suitable for particular protein samples such as membrane proteins. Microfluidics offers the potential as a fully automated platform for the efficient and high-throughput analysis of complex samples, such as membrane proteins, and do so with performance metrics that exceed their bench-top counterparts. In recent years, there have been various improvements to microfluidics and their use for proteomic analysis as reported in the literature. Consequently, this review presents an overview of the traditional proteomic-processing pipelines for membrane proteins and insights into new technological developments with a focus on the applicability of microfluidics for the analysis of membrane proteins. Sample preparation techniques will be discussed in detail and novel interfacing strategies as it relates to MS will be highlighted. Lastly, some general conclusions and future perspectives are presented. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

High Content Imaging (HCI) on Miniaturized Three-Dimensional (3D) Cell Cultures

PubMed Central

Joshi, Pranav; Lee, Moo-Yeal

2015-01-01

High content imaging (HCI) is a multiplexed cell staining assay developed for better understanding of complex biological functions and mechanisms of drug action, and it has become an important tool for toxicity and efficacy screening of drug candidates. Conventional HCI assays have been carried out on two-dimensional (2D) cell monolayer cultures, which in turn limit predictability of drug toxicity/efficacy in vivo; thus, there has been an urgent need to perform HCI assays on three-dimensional (3D) cell cultures. Although 3D cell cultures better mimic in vivo microenvironments of human tissues and provide an in-depth understanding of the morphological and functional features of tissues, they are also limited by having relatively low throughput and thus are not amenable to high-throughput screening (HTS). One attempt of making 3D cell culture amenable for HTS is to utilize miniaturized cell culture platforms. This review aims to highlight miniaturized 3D cell culture platforms compatible with current HCI technology. PMID:26694477

Effects of Perfluorooctanoic Acid on Metabolic Profiles in Brain and Liver of Mouse Revealed by a High-throughput Targeted Metabolomics Approach

NASA Astrophysics Data System (ADS)

Yu, Nanyang; Wei, Si; Li, Meiying; Yang, Jingping; Li, Kan; Jin, Ling; Xie, Yuwei; Giesy, John P.; Zhang, Xiaowei; Yu, Hongxia

2016-04-01

Perfluorooctanoic acid (PFOA), a perfluoroalkyl acid, can result in hepatotoxicity and neurobehavioral effects in animals. The metabolome, which serves as a connection among transcriptome, proteome and toxic effects, provides pathway-based insights into effects of PFOA. Since understanding of changes in the metabolic profile during hepatotoxicity and neurotoxicity were still incomplete, a high-throughput targeted metabolomics approach (278 metabolites) was used to investigate effects of exposure to PFOA for 28 d on brain and liver of male Balb/c mice. Results of multivariate statistical analysis indicated that PFOA caused alterations in metabolic pathways in exposed individuals. Pathway analysis suggested that PFOA affected metabolism of amino acids, lipids, carbohydrates and energetics. Ten and 18 metabolites were identified as potential unique biomarkers of exposure to PFOA in brain and liver, respectively. In brain, PFOA affected concentrations of neurotransmitters, including serotonin, dopamine, norepinephrine, and glutamate in brain, which provides novel insights into mechanisms of PFOA-induced neurobehavioral effects. In liver, profiles of lipids revealed involvement of β-oxidation and biosynthesis of saturated and unsaturated fatty acids in PFOA-induced hepatotoxicity, while alterations in metabolism of arachidonic acid suggesting potential of PFOA to cause inflammation response in liver. These results provide insight into the mechanism and biomarkers for PFOA-induced effects.

RNAi High-Throughput Screening of Single- and Multi-Cell-Type Tumor Spheroids: A Comprehensive Analysis in Two and Three Dimensions.

PubMed

Fu, Jiaqi; Fernandez, Daniel; Ferrer, Marc; Titus, Steven A; Buehler, Eugen; Lal-Nag, Madhu A

2017-06-01

The widespread use of two-dimensional (2D) monolayer cultures for high-throughput screening (HTS) to identify targets in drug discovery has led to attrition in the number of drug targets being validated. Solid tumors are complex, aberrantly growing microenvironments that harness structural components from stroma, nutrients fed through vasculature, and immunosuppressive factors. Increasing evidence of stromally-derived signaling broadens the complexity of our understanding of the tumor microenvironment while stressing the importance of developing better models that reflect these interactions. Three-dimensional (3D) models may be more sensitive to certain gene-silencing events than 2D models because of their components of hypoxia, nutrient gradients, and increased dependence on cell-cell interactions and therefore are more representative of in vivo interactions. Colorectal cancer (CRC) and breast cancer (BC) models composed of epithelial cells only, deemed single-cell-type tumor spheroids (SCTS) and multi-cell-type tumor spheroids (MCTS), containing fibroblasts were developed for RNAi HTS in 384-well microplates with flat-bottom wells for 2D screening and round-bottom, ultra-low-attachment wells for 3D screening. We describe the development of a high-throughput assay platform that can assess physiologically relevant phenotypic differences between screening 2D versus 3D SCTS, 3D SCTS, and MCTS in the context of different cancer subtypes. This assay platform represents a paradigm shift in how we approach drug discovery that can reduce the attrition rate of drugs that enter the clinic.

Proteomic analysis of mature soybean seeds from the Chernobyl area suggests plant adaptation to the contaminated environment.

PubMed

Danchenko, Maksym; Skultety, Ludovit; Rashydov, Namik M; Berezhna, Valentyna V; Mátel, L'ubomír; Salaj, Terézia; Pret'ová, Anna; Hajduch, Martin

2009-06-01

The explosion in one of the four reactors of the Chernobyl Nuclear Power Plant (CNPP, Chernobyl) caused the worst nuclear environmental disaster ever seen. Currently, 23 years after the accident, the soil in the close vicinity of CNPP is still significantly contaminated with long-living radioisotopes, such as (137)Cs. Despite this contamination, the plants growing in Chernobyl area were able to adapt to the radioactivity, and survive. The aim of this study was to investigate plant adaptation mechanisms toward permanently increased level of radiation using a quantitative high-throughput proteomics approach. Soybeans of a local variety (Soniachna) were sown in contaminated and control fields in the Chernobyl region. Mature seeds were harvested and the extracted proteins were subjected to two-dimensional gel electrophoresis (2-DE). In total, 9.2% of 698 quantified protein spots on 2-D gel were found to be differentially expressed with a p-value

Proteomics and Systems Biology: Current and Future Applications in the Nutritional Sciences1

PubMed Central

Moore, J. Bernadette; Weeks, Mark E.

2011-01-01

In the last decade, advances in genomics, proteomics, and metabolomics have yielded large-scale datasets that have driven an interest in global analyses, with the objective of understanding biological systems as a whole. Systems biology integrates computational modeling and experimental biology to predict and characterize the dynamic properties of biological systems, which are viewed as complex signaling networks. Whereas the systems analysis of disease-perturbed networks holds promise for identification of drug targets for therapy, equally the identified critical network nodes may be targeted through nutritional intervention in either a preventative or therapeutic fashion. As such, in the context of the nutritional sciences, it is envisioned that systems analysis of normal and nutrient-perturbed signaling networks in combination with knowledge of underlying genetic polymorphisms will lead to a future in which the health of individuals will be improved through predictive and preventative nutrition. Although high-throughput transcriptomic microarray data were initially most readily available and amenable to systems analysis, recent technological and methodological advances in MS have contributed to a linear increase in proteomic investigations. It is now commonplace for combined proteomic technologies to generate complex, multi-faceted datasets, and these will be the keystone of future systems biology research. This review will define systems biology, outline current proteomic methodologies, highlight successful applications of proteomics in nutrition research, and discuss the challenges for future applications of systems biology approaches in the nutritional sciences. PMID:22332076

Capillary electrophoresis interfaced with a mass spectrometer (CE-MS): technical considerations and applicability for biomarker studies in animals.

PubMed

Albalat, Amaya; Husi, Holger; Siwy, Justyna; Nally, Jarlath E; McLauglin, Mark; Eckersall, Peter D; Mullen, William

2014-02-01

Proteomics is a growing field that has the potential to be applied to many biology-related disciplines. However, the study of the proteome has proven to be very challenging due to its high level of complexity when compared to genome and transcriptome data. In order to analyse this level of complexity, high resolution separation of peptides/proteins are needed together with high resolution analysers. Currently, liquid chromatography and capillary electrophoresis (CE) are the two most widely used separation techniques that can be coupled on-line with a mass spectrometer (MS). In CE, proteins/ peptides are separated according to their size, charge and shape leading to high resolving power. Although further progress in the area of sensitivity, throughput and proteome coverage are expected, MS-based proteomics have developed to a level at which they are habitually applied to study a wide range of biological questions. The aim of this review is to present CE-MS as a proteomic analytical platform for biomarker research that could be used in farm animal and veterinary studies. This is a MS-analytical platform that has been widely used for biomarker research in the biomedical field but its application in animal proteomic studies is relatively novel. The review will focus on introducing the CE-MS platform and the primary considerations for its application to biomarker research. Furthermore, current applications but more importantly potential application in the field of farm animals and veterinary science will be presented and discussed.

Serum proteomic analysis of extracorporeal shock wave therapy-enhanced diabetic wound healing in a streptozotocin-induced diabetes model.

PubMed

Yang, Ming-Yu; Chiang, Yuan-Cheng; Huang, Yu-Ting; Chen, Chien-Chang; Wang, Feng-Sheng; Wang, Ching-Jen; Kuo, Yur-Ren

2014-01-01

Previous studies have demonstrated that extracorporeal shock wave therapy has a significant positive effect on accelerating diabetic wound healing. However, the systemic effect after therapy is still unclear. This study investigated the plasma protein expression in the extracorporeal shock wave therapy group and diabetic controls using proteomic study. A dorsal skin defect (6 × 5 cm) in a streptozotocin-induced diabetic Wistar rat model was used. Diabetic rats receiving either no therapy or extracorporeal shock wave therapy after wounding were analyzed. The spots of interest were subjected to in-gel trypsin digestion and matrix-assisted laser desorption ionization time-of-flight mass spectrometry to elucidate the peptide mass fingerprints. The mass spectrometric characteristics of the identified proteins, including their theoretical isoelectric points, molecular weights, sequence coverage, and Mascot score, were analyzed. Protein expression was validated using immunohistochemical analysis of topical periwounding tissues. The proteomic study revealed that at days 3 and 10 after therapy rats had significantly higher abundance of haptoglobin and significantly lower levels of the vitamin D-binding protein precursor as compared with the diabetic controls. Immunohistochemical staining of topical periwounding tissue also revealed significant upregulation of haptoglobin and downregulation of vitamin D-binding protein expression in the extracorporeal shock wave therapy group, which was consistent with the systemic proteome study. Proteome analyses demonstrated an upregulation of haptoglobin and a downregulation of vitamin D-binding protein in extracorporeal shock wave therapy-enhanced diabetic wound healing.

A new dimethyl labeling-based SID-MRM-MS method and its application to three proteases involved in insulin maturation.

PubMed

Cheng, Dongwan; Zheng, Li; Hou, Junjie; Wang, Jifeng; Xue, Peng; Yang, Fuquan; Xu, Tao

2015-01-01

The absolute quantification of target proteins in proteomics involves stable isotope dilution coupled with multiple reactions monitoring mass spectrometry (SID-MRM-MS). The successful preparation of stable isotope-labeled internal standard peptides is an important prerequisite for the SID-MRM absolute quantification methods. Dimethyl labeling has been widely used in relative quantitative proteomics and it is fast, simple, reliable, cost-effective, and applicable to any protein sample, making it an ideal candidate method for the preparation of stable isotope-labeled internal standards. MRM mass spectrometry is of high sensitivity, specificity, and throughput characteristics and can quantify multiple proteins simultaneously, including low-abundance proteins in precious samples such as pancreatic islets. In this study, a new method for the absolute quantification of three proteases involved in insulin maturation, namely PC1/3, PC2 and CPE, was developed by coupling a stable isotope dimethyl labeling strategy for internal standard peptide preparation with SID-MRM-MS quantitative technology. This method offers a new and effective approach for deep understanding of the functional status of pancreatic β cells and pathogenesis in diabetes.

COMPASS: a suite of pre- and post-search proteomics software tools for OMSSA

PubMed Central

Wenger, Craig D.; Phanstiel, Douglas H.; Lee, M. Violet; Bailey, Derek J.; Coon, Joshua J.

2011-01-01

Here we present the Coon OMSSA Proteomic Analysis Software Suite (COMPASS): a free and open-source software pipeline for high-throughput analysis of proteomics data, designed around the Open Mass Spectrometry Search Algorithm. We detail a synergistic set of tools for protein database generation, spectral reduction, peptide false discovery rate analysis, peptide quantitation via isobaric labeling, protein parsimony and protein false discovery rate analysis, and protein quantitation. We strive for maximum ease of use, utilizing graphical user interfaces and working with data files in the original instrument vendor format. Results are stored in plain text comma-separated values files, which are easy to view and manipulate with a text editor or spreadsheet program. We illustrate the operation and efficacy of COMPASS through the use of two LC–MS/MS datasets. The first is a dataset of a highly annotated mixture of standard proteins and manually validated contaminants that exhibits the identification workflow. The second is a dataset of yeast peptides, labeled with isobaric stable isotope tags and mixed in known ratios, to demonstrate the quantitative workflow. For these two datasets, COMPASS performs equivalently or better than the current de facto standard, the Trans-Proteomic Pipeline. PMID:21298793

Comparative proteome analysis of Milnesium tardigradum in early embryonic state versus adults in active and anhydrobiotic state.

PubMed

Schokraie, Elham; Warnken, Uwe; Hotz-Wagenblatt, Agnes; Grohme, Markus A; Hengherr, Steffen; Förster, Frank; Schill, Ralph O; Frohme, Marcus; Dandekar, Thomas; Schnölzer, Martina

2012-01-01

Tardigrades have fascinated researchers for more than 300 years because of their extraordinary capability to undergo cryptobiosis and survive extreme environmental conditions. However, the survival mechanisms of tardigrades are still poorly understood mainly due to the absence of detailed knowledge about the proteome and genome of these organisms. Our study was intended to provide a basis for the functional characterization of expressed proteins in different states of tardigrades. High-throughput, high-accuracy proteomics in combination with a newly developed tardigrade specific protein database resulted in the identification of more than 3000 proteins in three different states: early embryonic state and adult animals in active and anhydrobiotic state. This comprehensive proteome resource includes protein families such as chaperones, antioxidants, ribosomal proteins, cytoskeletal proteins, transporters, protein channels, nutrient reservoirs, and developmental proteins. A comparative analysis of protein families in the different states was performed by calculating the exponentially modified protein abundance index which classifies proteins in major and minor components. This is the first step to analyzing the proteins involved in early embryonic development, and furthermore proteins which might play an important role in the transition into the anhydrobiotic state.

Comparative proteome analysis of Milnesium tardigradum in early embryonic state versus adults in active and anhydrobiotic state

PubMed Central

Schokraie, Elham; Warnken, Uwe; Hotz-Wagenblatt, Agnes; Grohme, Markus A.; Hengherr, Steffen; Förster, Frank; Schill, Ralph O.; Frohme, Marcus; Dandekar, Thomas; Schnölzer, Martina

2012-01-01

Tardigrades have fascinated researchers for more than 300 years because of their extraordinary capability to undergo cryptobiosis and survive extreme environmental conditions. However, the survival mechanisms of tardigrades are still poorly understood mainly due to the absence of detailed knowledge about the proteome and genome of these organisms. Our study was intended to provide a basis for the functional characterization of expressed proteins in different states of tardigrades. High-throughput, high-accuracy proteomics in combination with a newly developed tardigrade specific protein database resulted in the identification of more than 3000 proteins in three different states: early embryonic state and adult animals in active and anhydrobiotic state. This comprehensive proteome resource includes protein families such as chaperones, antioxidants, ribosomal proteins, cytoskeletal proteins, transporters, protein channels, nutrient reservoirs, and developmental proteins. A comparative analysis of protein families in the different states was performed by calculating the exponentially modified protein abundance index which classifies proteins in major and minor components. This is the first step to analyzing the proteins involved in early embryonic development, and furthermore proteins which might play an important role in the transition into the anhydrobiotic state. PMID:23029181

Contribution of proteomics to the study of plant pathogenic fungi.

PubMed

Gonzalez-Fernandez, Raquel; Jorrin-Novo, Jesus V

2012-01-01

Phytopathogenic fungi are one of the most damaging plant parasitic organisms, and can cause serious diseases and important yield losses in crops. The study of the biology of these microorganisms and the interaction with their hosts has experienced great advances in recent years due to the development of moderm, holistic and high-throughput -omic techniques, together with the increasing number of genome sequencing projects and the development of mutants and reverse genetics tools. We highlight among these -omic techniques the importance of proteomics, which has become a relevant tool in plant-fungus pathosystem research. Proteomics intends to identify gene products with a key role in pathogenicity and virulence. These studies would help in the search of key protein targets and in the development of agrochemicals, which may open new ways for crop disease diagnosis and protection. In this review, we made an overview on the contribution of proteomics to the knowledge of life cycle, infection mechanisms, and virulence of the plant pathogenic fungi. Data from current, innovative literature, according to both methodological and experimental systems, were summarized and discussed. Specific sections were devoted to the most studied fungal phytopathogens: Botrytis cinerea, Sclerotinia sclerotiorum, and Fusarium graminearum.

Proteomic analysis of formalin-fixed paraffin embedded tissue by MALDI imaging mass spectrometry

PubMed Central

Casadonte, Rita; Caprioli, Richard M

2012-01-01

Archived formalin-fixed paraffin-embedded (FFPE) tissue collections represent a valuable informational resource for proteomic studies. Multiple FFPE core biopsies can be assembled in a single block to form tissue microarrays (TMAs). We describe a protocol for analyzing protein in FFPE -TMAs using matrix-assisted laser desorption/ionization (MAL DI) imaging mass spectrometry (IMS). The workflow incorporates an antigen retrieval step following deparaffinization, in situ trypsin digestion, matrix application and then mass spectrometry signal acquisition. The direct analysis of FFPE -TMA tissue using IMS allows direct analysis of multiple tissue samples in a single experiment without extraction and purification of proteins. The advantages of high speed and throughput, easy sample handling and excellent reproducibility make this technology a favorable approach for the proteomic analysis of clinical research cohorts with large sample numbers. For example, TMA analysis of 300 FFPE cores would typically require 6 h of total time through data acquisition, not including data analysis. PMID:22011652

MStern Blotting-High Throughput Polyvinylidene Fluoride (PVDF) Membrane-Based Proteomic Sample Preparation for 96-Well Plates.

PubMed

Berger, Sebastian T; Ahmed, Saima; Muntel, Jan; Cuevas Polo, Nerea; Bachur, Richard; Kentsis, Alex; Steen, Judith; Steen, Hanno

2015-10-01

We describe a 96-well plate compatible membrane-based proteomic sample processing method, which enables the complete processing of 96 samples (or multiples thereof) within a single workday. This method uses a large-pore hydrophobic PVDF membrane that efficiently adsorbs proteins, resulting in fast liquid transfer through the membrane and significantly reduced sample processing times. Low liquid transfer speeds have prevented the useful 96-well plate implementation of FASP as a widely used membrane-based proteomic sample processing method. We validated our approach on whole-cell lysate and urine and cerebrospinal fluid as clinically relevant body fluids. Without compromising peptide and protein identification, our method uses a vacuum manifold and circumvents the need for digest desalting, making our processing method compatible with standard liquid handling robots. In summary, our new method maintains the strengths of FASP and simultaneously overcomes one of the major limitations of FASP without compromising protein identification and quantification. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Comparison between Procedures using Sodium Dodecyl Sulfate for Shotgun Proteomic Analyses of Complex Samples

PubMed Central

Bereman, Michael S.; Egertson, Jarrett D.; MacCoss, Michael J.

2012-01-01

Filter aided sample preparation (FASP) and a new sample preparation method using a modified commercial SDS removal spin column are quantitatively compared in terms of their performance for shotgun proteomic experiments in three complex proteomic samples: a Saccharomyces cerevisiae lysate (insoluble fraction), a Caenorhabditis elegans lysate (soluble fraction), and a human embryonic kidney cell line (HEK293T). The characteristics and total number of peptides and proteins identified are compared between the two procedures. The SDS spin column procedure affords a conservative 4-fold improvement in throughput, is more reproducible, less expensive (i.e., requires less materials), and identifies between 30–107% more peptides at a q≤0.01, than the FASP procedure. The peptides identified by SDS spin column are more hydrophobic than species identified by the FASP procedure as indicated by the distribution of GRAVY scores. Ultimately, these improvements correlate to as great as a 50% increase in protein identifications with 2 or more peptides. PMID:21656683

Proteomic evaluation of genetically modified crops: current status and challenges

PubMed Central

Gong, Chun Yan; Wang, Tai

2013-01-01

Hectares of genetically modified (GM) crops have increased exponentially since 1996, when such crops began to be commercialized. GM biotechnology, together with conventional breeding, has become the main approach to improving agronomic traits of crops. However, people are concerned about the safety of GM crops, especially GM-derived food and feed. Many efforts have been made to evaluate the unintended effects caused by the introduction of exogenous genes. “Omics” techniques have advantages over targeted analysis in evaluating such crops because of their use of high-throughput screening. Proteins are key players in gene function and are directly involved in metabolism and cellular development or have roles as toxins, antinutrients, or allergens, which are essential for human health. Thus, proteomics can be expected to become one of the most useful tools in safety assessment. This review assesses the potential of proteomics in evaluating various GM crops. We further describe the challenges in ensuring homogeneity and sensitivity in detection techniques. PMID:23471542

Definitive screening design enables optimization of LC-ESI-MS/MS parameters in proteomics.

PubMed

Aburaya, Shunsuke; Aoki, Wataru; Minakuchi, Hiroyoshi; Ueda, Mitsuyoshi

2017-12-01

In proteomics, more than 100,000 peptides are generated from the digestion of human cell lysates. Proteome samples have a broad dynamic range in protein abundance; therefore, it is critical to optimize various parameters of LC-ESI-MS/MS to comprehensively identify these peptides. However, there are many parameters for LC-ESI-MS/MS analysis. In this study, we applied definitive screening design to simultaneously optimize 14 parameters in the operation of monolithic capillary LC-ESI-MS/MS to increase the number of identified proteins and/or the average peak area of MS1. The simultaneous optimization enabled the determination of two-factor interactions between LC and MS. Finally, we found two parameter sets of monolithic capillary LC-ESI-MS/MS that increased the number of identified proteins by 8.1% or the average peak area of MS1 by 67%. The definitive screening design would be highly useful for high-throughput analysis of the best parameter set in LC-ESI-MS/MS systems.

Proteomic evaluation of genetically modified crops: current status and challenges.

PubMed

Gong, Chun Yan; Wang, Tai

2013-01-01

Hectares of genetically modified (GM) crops have increased exponentially since 1996, when such crops began to be commercialized. GM biotechnology, together with conventional breeding, has become the main approach to improving agronomic traits of crops. However, people are concerned about the safety of GM crops, especially GM-derived food and feed. Many efforts have been made to evaluate the unintended effects caused by the introduction of exogenous genes. "Omics" techniques have advantages over targeted analysis in evaluating such crops because of their use of high-throughput screening. Proteins are key players in gene function and are directly involved in metabolism and cellular development or have roles as toxins, antinutrients, or allergens, which are essential for human health. Thus, proteomics can be expected to become one of the most useful tools in safety assessment. This review assesses the potential of proteomics in evaluating various GM crops. We further describe the challenges in ensuring homogeneity and sensitivity in detection techniques.

Characterization of Medium Conditioned by Irradiated Cells Using Proteome-Wide, High-Throughput Mass Spectrometry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Springer, David L.; Ahram, Mamoun; Adkins, Joshua N.

Shedding, the release of cell surface proteins by regulated proteolysis, is a general cellular response to injury and is responsible for generating numerous bioactive molecules including growth factors and cytokines. The purpose of our work is to determine whether low doses of low-linear energy transfer (LET) radiation induce shedding of bioactive molecules. Using a mass spectrometry-based global proteomics method, we tested this hypothesis by analyzing for shed proteins in medium from irradiated human mammary epithelial cells (HMEC). Several hundred proteins were identified, including transforming growth factor beta (TGFB); however, no changes in protein abundances attributable to radiation exposure, based onmore » immunoblotting methods, were observed. These results demonstrate that our proteomic-based approach has the sensitivity to identify the kinds of proteins believed to be released after low-dose radiation exposure but that improvements in mass spectrometry-based protein quantification will be required to detect the small changes in abundance associated with this type of insult.« less

MStern Blotting–High Throughput Polyvinylidene Fluoride (PVDF) Membrane-Based Proteomic Sample Preparation for 96-Well Plates*

PubMed Central

Berger, Sebastian T.; Ahmed, Saima; Muntel, Jan; Cuevas Polo, Nerea; Bachur, Richard; Kentsis, Alex; Steen, Judith; Steen, Hanno

2015-01-01

We describe a 96-well plate compatible membrane-based proteomic sample processing method, which enables the complete processing of 96 samples (or multiples thereof) within a single workday. This method uses a large-pore hydrophobic PVDF membrane that efficiently adsorbs proteins, resulting in fast liquid transfer through the membrane and significantly reduced sample processing times. Low liquid transfer speeds have prevented the useful 96-well plate implementation of FASP as a widely used membrane-based proteomic sample processing method. We validated our approach on whole-cell lysate and urine and cerebrospinal fluid as clinically relevant body fluids. Without compromising peptide and protein identification, our method uses a vacuum manifold and circumvents the need for digest desalting, making our processing method compatible with standard liquid handling robots. In summary, our new method maintains the strengths of FASP and simultaneously overcomes one of the major limitations of FASP without compromising protein identification and quantification. PMID:26223766

CypD(-/-) hearts have altered levels of proteins involved in Krebs cycle, branch chain amino acid degradation and pyruvate metabolism.

PubMed

Menazza, Sara; Wong, Renee; Nguyen, Tiffany; Wang, Guanghui; Gucek, Marjan; Murphy, Elizabeth

2013-03-01

Cyclophilin D (CypD) is a mitochondrial chaperone that has been shown to regulate the mitochondrial permeability transition pore (MPTP). MPTP opening is a major determinant of mitochondrial dysfunction and cardiomyocyte death during ischemia/reperfusion (I/R) injury. Mice lacking CypD have been widely used to study regulation of the MPTP, and it has been shown recently that genetic depletion of CypD correlates with elevated levels of mitochondrial Ca(2+). The present study aimed to characterize the metabolic changes in CypD(-/-) hearts. Initially, we used a proteomics approach to examine protein changes in CypD(-/-) mice. Using pathway analysis, we found that CypD(-/-) hearts have alterations in branched chain amino acid metabolism, pyruvate metabolism and the Krebs cycle. We tested whether these metabolic changes were due to inhibition of electron transfer from these metabolic pathways into the electron transport chain. As we found decreased levels of succinate dehydrogenase and electron transfer flavoprotein in the proteomics analysis, we examined whether activities of these enzymes might be altered. However, we found no alterations in their activities. The proteomics study also showed a 23% decrease in carnitine-palmitoyltransferase 1 (CPT1), which prompted us to perform a metabolomics analysis. Consistent with the decrease in CPT1, we found a significant decrease in C4/Ci4, C5-OH/C3-DC, C12:1, C14:1, C16:1, and C20:3 acyl carnitines in hearts from CypD(-/-) mice. In summary, CypD(-/-) hearts exhibit changes in many metabolic pathways and caution should be used when interpreting results from these mice as due solely to inhibition of the MPTP. Published by Elsevier Ltd.

Comparison of Normal and Breast Cancer Cell lines using Proteome, Genome and Interactome data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Patwardhan, Anil J.; Strittmatter, Eric F.; Camp, David G.

2005-12-01

Normal and cancer cell line proteomes were profiled using high throughput mass spectrometry techniques. Application of both protein-level and peptide-level sample fractionation combined with LC-MS/MS analysis enabled the confident identification of 2,235 unmodified proteins representing a broad range of functional and compartmental classes. An iterative multi-step search strategy was used to identify post-translational modifications and detected several proteins that are preferentially modified in cancer cells. Information regarding both unmodified and modified protein forms was combined with publicly available gene expression and protein-protein interaction data. The resulting integrated dataset revealed several functionally related proteins that are differentially regulated between normal andmore » cancer cell lines.« less

Development of an open source laboratory information management system for 2-D gel electrophoresis-based proteomics workflow

PubMed Central

Morisawa, Hiraku; Hirota, Mikako; Toda, Tosifusa

2006-01-01

Background In the post-genome era, most research scientists working in the field of proteomics are confronted with difficulties in management of large volumes of data, which they are required to keep in formats suitable for subsequent data mining. Therefore, a well-developed open source laboratory information management system (LIMS) should be available for their proteomics research studies. Results We developed an open source LIMS appropriately customized for 2-D gel electrophoresis-based proteomics workflow. The main features of its design are compactness, flexibility and connectivity to public databases. It supports the handling of data imported from mass spectrometry software and 2-D gel image analysis software. The LIMS is equipped with the same input interface for 2-D gel information as a clickable map on public 2DPAGE databases. The LIMS allows researchers to follow their own experimental procedures by reviewing the illustrations of 2-D gel maps and well layouts on the digestion plates and MS sample plates. Conclusion Our new open source LIMS is now available as a basic model for proteome informatics, and is accessible for further improvement. We hope that many research scientists working in the field of proteomics will evaluate our LIMS and suggest ways in which it can be improved. PMID:17018156

Simplifying the human serum proteome for discriminating patients with bipolar disorder of other psychiatry conditions.

PubMed

de Jesus, Jemmyson Romário; Galazzi, Rodrigo Moretto; de Lima, Tatiani Brenelli; Banzato, Cláudio Eduardo Muller; de Almeida Lima E Silva, Luiz Fernando; de Rosalmeida Dantas, Clarissa; Gozzo, Fábio Cézar; Arruda, Marco Aurélio Zezzi

2017-12-01

An exploratory analysis using proteomic strategies in blood serum of patients with bipolar disorder (BD), and with other psychiatric conditions such as Schizophrenia (SCZ), can provide a better understanding of this disorder, as well as their discrimination based on their proteomic profile. The proteomic profile of blood serum samples obtained from patients with BD using lithium or other drugs (N=14), healthy controls, including non-family (HCNF; N=3) and family (HCF; N=9), patients with schizophrenia (SCZ; N=23), and patients using lithium for other psychiatric conditions (OD; N=4) were compared. Four methods for simplifying the serum samples proteome were evaluated for both removing the most abundant proteins and for enriching those of lower-abundance: protein depletion with acetonitrile (ACN), dithiothreitol (DTT), sequential depletion using DTT and ACN, and protein equalization using commercial ProteoMiner® kit (PM). For proteomic evaluation, 2-D DIGE and nanoLC-MS/MS analysis were employed. PM method was the best strategy for removing proteins of high abundance. Through 2-D DIGE gel image comparison, 37 protein spots were found differentially abundant (p<0.05, Student's t-test), which exhibited ≥2.0-fold change of the average value of normalized spot intensities in the serum of SCZ, BD and OD patients compared to subject controls (HCF and HCNF). From these spots detected, 13 different proteins were identified: ApoA1, ApoE, ApoC3, ApoA4, Samp, SerpinA1, TTR, IgK, Alb, VTN, TR, C4A and C4B. Proteomic analysis allowed the discrimination of patients with BD from patients with other mental disorders, such as SCZ. The findings in this exploratory study may also contribute for better understanding the pathophysiology of these disorders and finding potential serum biomarkers for these conditions. Copyright © 2017 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

The biology/disease-driven human proteome project (B/D-HPP): enabling protein research for the life sciences community.

PubMed

Aebersold, Ruedi; Bader, Gary D; Edwards, Aled M; van Eyk, Jennifer E; Kussmann, Martin; Qin, Jun; Omenn, Gilbert S

2013-01-04

The biology and disease oriented branch of the Human Proteome Project (B/D-HPP) was established by the Human Proteome Organization (HUPO) with the main goal of supporting the broad application of state-of the-art measurements of proteins and proteomes by life scientists studying the molecular mechanisms of biological processes and human disease. This will be accomplished through the generation of research and informational resources that will support the routine and definitive measurement of the process or disease relevant proteins. The B/D-HPP is highly complementary to the C-HPP and will provide datasets and biological characterization useful to the C-HPP teams. In this manuscript we describe the goals, the plans, and the current status of the of the B/D-HPP.

Advances in targeted proteomics and applications to biomedical research

PubMed Central

Shi, Tujin; Song, Ehwang; Nie, Song; Rodland, Karin D.; Liu, Tao; Qian, Wei-Jun; Smith, Richard D.

2016-01-01

Targeted proteomics technique has emerged as a powerful protein quantification tool in systems biology, biomedical research, and increasing for clinical applications. The most widely used targeted proteomics approach, selected reaction monitoring (SRM), also known as multiple reaction monitoring (MRM), can be used for quantification of cellular signaling networks and preclinical verification of candidate protein biomarkers. As an extension to our previous review on advances in SRM sensitivity herein we review recent advances in the method and technology for further enhancing SRM sensitivity (from 2012 to present), and highlighting its broad biomedical applications in human bodily fluids, tissue and cell lines. Furthermore, we also review two recently introduced targeted proteomics approaches, parallel reaction monitoring (PRM) and data-independent acquisition (DIA) with targeted data extraction on fast scanning high-resolution accurate-mass (HR/AM) instruments. Such HR/AM targeted quantification with monitoring all target product ions addresses SRM limitations effectively in specificity and multiplexing; whereas when compared to SRM, PRM and DIA are still in the infancy with a limited number of applications. Thus, for HR/AM targeted quantification we focus our discussion on method development, data processing and analysis, and its advantages and limitations in targeted proteomics. Finally, general perspectives on the potential of achieving both high sensitivity and high sample throughput for large-scale quantification of hundreds of target proteins are discussed. PMID:27302376

Statistical Design for Biospecimen Cohort Size in Proteomics-based Biomarker Discovery and Verification Studies

PubMed Central

Skates, Steven J.; Gillette, Michael A.; LaBaer, Joshua; Carr, Steven A.; Anderson, N. Leigh; Liebler, Daniel C.; Ransohoff, David; Rifai, Nader; Kondratovich, Marina; Težak, Živana; Mansfield, Elizabeth; Oberg, Ann L.; Wright, Ian; Barnes, Grady; Gail, Mitchell; Mesri, Mehdi; Kinsinger, Christopher R.; Rodriguez, Henry; Boja, Emily S.

2014-01-01

Protein biomarkers are needed to deepen our understanding of cancer biology and to improve our ability to diagnose, monitor and treat cancers. Important analytical and clinical hurdles must be overcome to allow the most promising protein biomarker candidates to advance into clinical validation studies. Although contemporary proteomics technologies support the measurement of large numbers of proteins in individual clinical specimens, sample throughput remains comparatively low. This problem is amplified in typical clinical proteomics research studies, which routinely suffer from a lack of proper experimental design, resulting in analysis of too few biospecimens to achieve adequate statistical power at each stage of a biomarker pipeline. To address this critical shortcoming, a joint workshop was held by the National Cancer Institute (NCI), National Heart, Lung and Blood Institute (NHLBI), and American Association for Clinical Chemistry (AACC), with participation from the U.S. Food and Drug Administration (FDA). An important output from the workshop was a statistical framework for the design of biomarker discovery and verification studies. Herein, we describe the use of quantitative clinical judgments to set statistical criteria for clinical relevance, and the development of an approach to calculate biospecimen sample size for proteomic studies in discovery and verification stages prior to clinical validation stage. This represents a first step towards building a consensus on quantitative criteria for statistical design of proteomics biomarker discovery and verification research. PMID:24063748

Statistical design for biospecimen cohort size in proteomics-based biomarker discovery and verification studies.

PubMed

Skates, Steven J; Gillette, Michael A; LaBaer, Joshua; Carr, Steven A; Anderson, Leigh; Liebler, Daniel C; Ransohoff, David; Rifai, Nader; Kondratovich, Marina; Težak, Živana; Mansfield, Elizabeth; Oberg, Ann L; Wright, Ian; Barnes, Grady; Gail, Mitchell; Mesri, Mehdi; Kinsinger, Christopher R; Rodriguez, Henry; Boja, Emily S

2013-12-06

Protein biomarkers are needed to deepen our understanding of cancer biology and to improve our ability to diagnose, monitor, and treat cancers. Important analytical and clinical hurdles must be overcome to allow the most promising protein biomarker candidates to advance into clinical validation studies. Although contemporary proteomics technologies support the measurement of large numbers of proteins in individual clinical specimens, sample throughput remains comparatively low. This problem is amplified in typical clinical proteomics research studies, which routinely suffer from a lack of proper experimental design, resulting in analysis of too few biospecimens to achieve adequate statistical power at each stage of a biomarker pipeline. To address this critical shortcoming, a joint workshop was held by the National Cancer Institute (NCI), National Heart, Lung, and Blood Institute (NHLBI), and American Association for Clinical Chemistry (AACC) with participation from the U.S. Food and Drug Administration (FDA). An important output from the workshop was a statistical framework for the design of biomarker discovery and verification studies. Herein, we describe the use of quantitative clinical judgments to set statistical criteria for clinical relevance and the development of an approach to calculate biospecimen sample size for proteomic studies in discovery and verification stages prior to clinical validation stage. This represents a first step toward building a consensus on quantitative criteria for statistical design of proteomics biomarker discovery and verification research.

Design and Initial Characterization of the SC-200 Proteomics Standard Mixture

PubMed Central

Bauman, Andrew; Higdon, Roger; Rapson, Sean; Loiue, Brenton; Hogan, Jason; Stacy, Robin; Napuli, Alberto; Guo, Wenjin; van Voorhis, Wesley; Roach, Jared; Lu, Vincent; Landorf, Elizabeth; Stewart, Elizabeth; Kolker, Natali; Collart, Frank; Myler, Peter; van Belle, Gerald

2011-01-01

Abstract High-throughput (HTP) proteomics studies generate large amounts of data. Interpretation of these data requires effective approaches to distinguish noise from biological signal, particularly as instrument and computational capacity increase and studies become more complex. Resolving this issue requires validated and reproducible methods and models, which in turn requires complex experimental and computational standards. The absence of appropriate standards and data sets for validating experimental and computational workflows hinders the development of HTP proteomics methods. Most protein standards are simple mixtures of proteins or peptides, or undercharacterized reference standards in which the identity and concentration of the constituent proteins is unknown. The Seattle Children's 200 (SC-200) proposed proteomics standard mixture is the next step toward developing realistic, fully characterized HTP proteomics standards. The SC-200 exhibits a unique modular design to extend its functionality, and consists of 200 proteins of known identities and molar concentrations from 6 microbial genomes, distributed into 10 molar concentration tiers spanning a 1,000-fold range. We describe the SC-200's design, potential uses, and initial characterization. We identified 84% of SC-200 proteins with an LTQ-Orbitrap and 65% with an LTQ-Velos (false discovery rate = 1% for both). There were obvious trends in success rate, sequence coverage, and spectral counts with protein concentration; however, protein identification, sequence coverage, and spectral counts vary greatly within concentration levels. PMID:21250827

Design and initial characterization of the SC-200 proteomics standard mixture.

PubMed

Bauman, Andrew; Higdon, Roger; Rapson, Sean; Loiue, Brenton; Hogan, Jason; Stacy, Robin; Napuli, Alberto; Guo, Wenjin; van Voorhis, Wesley; Roach, Jared; Lu, Vincent; Landorf, Elizabeth; Stewart, Elizabeth; Kolker, Natali; Collart, Frank; Myler, Peter; van Belle, Gerald; Kolker, Eugene

2011-01-01

High-throughput (HTP) proteomics studies generate large amounts of data. Interpretation of these data requires effective approaches to distinguish noise from biological signal, particularly as instrument and computational capacity increase and studies become more complex. Resolving this issue requires validated and reproducible methods and models, which in turn requires complex experimental and computational standards. The absence of appropriate standards and data sets for validating experimental and computational workflows hinders the development of HTP proteomics methods. Most protein standards are simple mixtures of proteins or peptides, or undercharacterized reference standards in which the identity and concentration of the constituent proteins is unknown. The Seattle Children's 200 (SC-200) proposed proteomics standard mixture is the next step toward developing realistic, fully characterized HTP proteomics standards. The SC-200 exhibits a unique modular design to extend its functionality, and consists of 200 proteins of known identities and molar concentrations from 6 microbial genomes, distributed into 10 molar concentration tiers spanning a 1,000-fold range. We describe the SC-200's design, potential uses, and initial characterization. We identified 84% of SC-200 proteins with an LTQ-Orbitrap and 65% with an LTQ-Velos (false discovery rate = 1% for both). There were obvious trends in success rate, sequence coverage, and spectral counts with protein concentration; however, protein identification, sequence coverage, and spectral counts vary greatly within concentration levels.

P2P proteomics -- data sharing for enhanced protein identification

PubMed Central

2012-01-01

Background In order to tackle the important and challenging problem in proteomics of identifying known and new protein sequences using high-throughput methods, we propose a data-sharing platform that uses fully distributed P2P technologies to share specifications of peer-interaction protocols and service components. By using such a platform, information to be searched is no longer centralised in a few repositories but gathered from experiments in peer proteomics laboratories, which can subsequently be searched by fellow researchers. Methods The system distributively runs a data-sharing protocol specified in the Lightweight Communication Calculus underlying the system through which researchers interact via message passing. For this, researchers interact with the system through particular components that link to database querying systems based on BLAST and/or OMSSA and GUI-based visualisation environments. We have tested the proposed platform with data drawn from preexisting MS/MS data reservoirs from the 2006 ABRF (Association of Biomolecular Resource Facilities) test sample, which was extensively tested during the ABRF Proteomics Standards Research Group 2006 worldwide survey. In particular we have taken the data available from a subset of proteomics laboratories of Spain's National Institute for Proteomics, ProteoRed, a network for the coordination, integration and development of the Spanish proteomics facilities. Results and Discussion We performed queries against nine databases including seven ProteoRed proteomics laboratories, the NCBI Swiss-Prot database and the local database of the CSIC/UAB Proteomics Laboratory. A detailed analysis of the results indicated the presence of a protein that was supported by other NCBI matches and highly scored matches in several proteomics labs. The analysis clearly indicated that the protein was a relatively high concentrated contaminant that could be present in the ABRF sample. This fact is evident from the information that could be derived from the proposed P2P proteomics system, however it is not straightforward to arrive to the same conclusion by conventional means as it is difficult to discard organic contamination of samples. The actual presence of this contaminant was only stated after the ABRF study of all the identifications reported by the laboratories. PMID:22293032

Yeast proteome map (last update).

PubMed

Perrot, Michel; Moes, Suzette; Massoni, Aurélie; Jenoe, Paul; Boucherie, Hélian

2009-10-01

The identification of proteins separated on 2-D gels is essential to exploit the full potential of 2-D gel electrophoresis for proteomic investigations. For this purpose we have undertaken the systematic identification of Saccharomyces cerevisiae proteins separated on 2-D gels. We report here the identification by mass spectrometry of 100 novel yeast protein spots that have so far not been tackled due to their scarcity on our standard 2-D gels. These identifications extend the number of protein spots identified on our yeast 2-D proteome map to 716. They correspond to 485 unique proteins. Among these, 154 were resolved into several isoforms. The present data set can now be expanded to report for the first time a map of 363 protein isoforms that significantly deepens our knowledge of the yeast proteome. The reference map and a list of all identified proteins can be accessed on the Yeast Protein Map server (www.ibgc.u-bordeaux2.fr/YPM).

Identification of Novel "Inks" for 3D Printing Using High-Throughput Screening: Bioresorbable Photocurable Polymers for Controlled Drug Delivery.

PubMed

Louzao, Iria; Koch, Britta; Taresco, Vincenzo; Ruiz-Cantu, Laura; Irvine, Derek J; Roberts, Clive J; Tuck, Christopher; Alexander, Cameron; Hague, Richard; Wildman, Ricky; Alexander, Morgan R

2018-02-28

A robust methodology is presented to identify novel biomaterials suitable for three-dimensional (3D) printing. Currently, the application of additive manufacturing is limited by the availability of functional inks, especially in the area of biomaterials; this is the first time when this method is used to tackle this problem, allowing hundreds of formulations to be readily assessed. Several functional properties, including the release of an antidepressive drug (paroxetine), cytotoxicity, and printability, are screened for 253 new ink formulations in a high-throughput format as well as mechanical properties. The selected candidates with the desirable properties are successfully scaled up using 3D printing into a range of object architectures. A full drug release study and degradability and tensile modulus experiments are presented on a simple architecture to validating the suitability of this methodology to identify printable inks for 3D printing devices with bespoke properties.

Proteomic Analysis to Identify Functional Molecules in Drug Resistance Caused by E-Cadherin Knockdown in 3D-Cultured Colorectal Cancer Models

DTIC Science & Technology

2013-09-01

REFERENCES (1) Harsha, H. C.; Pandey, A. Phosphoproteomics in cancer. Mol. Oncol. 2010, 4 (6), 482−95. (2) Iliuk , A.; Liu, X. S.; Xue, L.; Liu, X...based proteomics and peptidomics for biomarker discovery in neurodegenerative diseases. Int. J. Clin. Exp. Pathol. 2009, 2 (2), 132−48. (4) Iliuk , A...phosphoproteins by immobilized metal (Fe3+) affinity chromatography. Anal. Biochem. 1986, 154 (1), 250−4. (6) Iliuk , A. B.; Martin, V. A.; Alicie, B. M

Identification of functional modules using network topology and high-throughput data.

PubMed

Ulitsky, Igor; Shamir, Ron

2007-01-26

With the advent of systems biology, biological knowledge is often represented today by networks. These include regulatory and metabolic networks, protein-protein interaction networks, and many others. At the same time, high-throughput genomics and proteomics techniques generate very large data sets, which require sophisticated computational analysis. Usually, separate and different analysis methodologies are applied to each of the two data types. An integrated investigation of network and high-throughput information together can improve the quality of the analysis by accounting simultaneously for topological network properties alongside intrinsic features of the high-throughput data. We describe a novel algorithmic framework for this challenge. We first transform the high-throughput data into similarity values, (e.g., by computing pairwise similarity of gene expression patterns from microarray data). Then, given a network of genes or proteins and similarity values between some of them, we seek connected sub-networks (or modules) that manifest high similarity. We develop algorithms for this problem and evaluate their performance on the osmotic shock response network in S. cerevisiae and on the human cell cycle network. We demonstrate that focused, biologically meaningful and relevant functional modules are obtained. In comparison with extant algorithms, our approach has higher sensitivity and higher specificity. We have demonstrated that our method can accurately identify functional modules. Hence, it carries the promise to be highly useful in analysis of high throughput data.

Microengineering methods for cell-based microarrays and high-throughput drug-screening applications.

PubMed

Xu, Feng; Wu, JinHui; Wang, ShuQi; Durmus, Naside Gozde; Gurkan, Umut Atakan; Demirci, Utkan

2011-09-01

Screening for effective therapeutic agents from millions of drug candidates is costly, time consuming, and often faces concerns due to the extensive use of animals. To improve cost effectiveness, and to minimize animal testing in pharmaceutical research, in vitro monolayer cell microarrays with multiwell plate assays have been developed. Integration of cell microarrays with microfluidic systems has facilitated automated and controlled component loading, significantly reducing the consumption of the candidate compounds and the target cells. Even though these methods significantly increased the throughput compared to conventional in vitro testing systems and in vivo animal models, the cost associated with these platforms remains prohibitively high. Besides, there is a need for three-dimensional (3D) cell-based drug-screening models which can mimic the in vivo microenvironment and the functionality of the native tissues. Here, we present the state-of-the-art microengineering approaches that can be used to develop 3D cell-based drug-screening assays. We highlight the 3D in vitro cell culture systems with live cell-based arrays, microfluidic cell culture systems, and their application to high-throughput drug screening. We conclude that among the emerging microengineering approaches, bioprinting holds great potential to provide repeatable 3D cell-based constructs with high temporal, spatial control and versatility.

Microengineering Methods for Cell Based Microarrays and High-Throughput Drug Screening Applications

PubMed Central

Xu, Feng; Wu, JinHui; Wang, ShuQi; Durmus, Naside Gozde; Gurkan, Umut Atakan; Demirci, Utkan

2011-01-01

Screening for effective therapeutic agents from millions of drug candidates is costly, time-consuming and often face ethical concerns due to extensive use of animals. To improve cost-effectiveness, and to minimize animal testing in pharmaceutical research, in vitro monolayer cell microarrays with multiwell plate assays have been developed. Integration of cell microarrays with microfluidic systems have facilitated automated and controlled component loading, significantly reducing the consumption of the candidate compounds and the target cells. Even though these methods significantly increased the throughput compared to conventional in vitro testing systems and in vivo animal models, the cost associated with these platforms remains prohibitively high. Besides, there is a need for three-dimensional (3D) cell based drug-screening models, which can mimic the in vivo microenvironment and the functionality of the native tissues. Here, we present the state-of-the-art microengineering approaches that can be used to develop 3D cell based drug screening assays. We highlight the 3D in vitro cell culture systems with live cell-based arrays, microfluidic cell culture systems, and their application to high-throughput drug screening. We conclude that among the emerging microengineering approaches, bioprinting holds a great potential to provide repeatable 3D cell based constructs with high temporal, spatial control and versatility. PMID:21725152

Identification of IGFBP2 and IGFBP3 As Compensatory Biomarkers for CA19-9 in Early-Stage Pancreatic Cancer Using a Combination of Antibody-Based and LC-MS/MS-Based Proteomics

PubMed Central

Yoneyama, Toshihiro; Ohtsuki, Sumio; Honda, Kazufumi; Kobayashi, Makoto; Iwasaki, Motoki; Uchida, Yasuo; Okusaka, Takuji; Nakamori, Shoji; Shimahara, Masashi; Ueno, Takaaki; Tsuchida, Akihiko; Sata, Naohiro; Ioka, Tatsuya; Yasunami, Yohichi; Kosuge, Tomoo; Kaneda, Takashi; Kato, Takao; Yagihara, Kazuhiro; Fujita, Shigeyuki; Huang, Wilber; Yamada, Tesshi; Tachikawa, Masanori; Terasaki, Tetsuya

2016-01-01

Pancreatic cancer is one of the most lethal tumors, and reliable detection of early-stage pancreatic cancer and risk diseases for pancreatic cancer is essential to improve the prognosis. As 260 genes were previously reported to be upregulated in invasive ductal adenocarcinoma of pancreas (IDACP) cells, quantification of the corresponding proteins in plasma might be useful for IDACP diagnosis. Therefore, the purpose of the present study was to identify plasma biomarkers for early detection of IDACP by using two proteomics strategies: antibody-based proteomics and liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based proteomics. Among the 260 genes, we focused on 130 encoded proteins with known function for which antibodies were available. Twenty-three proteins showed values of the area under the curve (AUC) of more than 0.8 in receiver operating characteristic (ROC) analysis of reverse-phase protein array (RPPA) data of IDACP patients compared with healthy controls, and these proteins were selected as biomarker candidates. We then used our high-throughput selected reaction monitoring or multiple reaction monitoring (SRM/MRM) methodology, together with an automated sample preparation system, micro LC and auto analysis system, to quantify these candidate proteins in plasma from healthy controls and IDACP patients on a large scale. The results revealed that insulin-like growth factor-binding protein (IGFBP)2 and IGFBP3 have the ability to discriminate IDACP patients at an early stage from healthy controls, and IGFBP2 appeared to be increased in risk diseases of pancreatic malignancy, such as intraductal papillary mucinous neoplasms (IPMNs). Furthermore, diagnosis of IDACP using the combination of carbohydrate antigen 19–9 (CA19-9), IGFBP2 and IGFBP3 is significantly more effective than CA19-9 alone. This suggests that IGFBP2 and IGFBP3 may serve as compensatory biomarkers for CA19-9. Early diagnosis with this marker combination may improve the prognosis of IDACP patients. PMID:27579675

An Assessment of Individualized Instruction in Navy Technical Training,

DTIC Science & Technology

1979-11-01

PAGE(Wh... D.i. Eni.r .d) 2O~ ’\\ ~management information systems , training of instructors and managers ,terminology , student —instructor incentives...Navy commitment to II is most visible in CMI. FY 78 data show an approximate student AOB and throughput for CMI courses of 7,000 and 65,000...respectively. There are an additional 3,000 student AOB and 59,000 student throughput for II courses which are not computer managed . CAl usage in technical

High-throughput sequencing of black pepper root transcriptome.

PubMed

Gordo, Sheila M C; Pinheiro, Daniel G; Moreira, Edith C O; Rodrigues, Simone M; Poltronieri, Marli C; de Lemos, Oriel F; da Silva, Israel Tojal; Ramos, Rommel T J; Silva, Artur; Schneider, Horacio; Silva, Wilson A; Sampaio, Iracilda; Darnet, Sylvain

2012-09-17

Black pepper (Piper nigrum L.) is one of the most popular spices in the world. It is used in cooking and the preservation of food and even has medicinal properties. Losses in production from disease are a major limitation in the culture of this crop. The major diseases are root rot and foot rot, which are results of root infection by Fusarium solani and Phytophtora capsici, respectively. Understanding the molecular interaction between the pathogens and the host's root region is important for obtaining resistant cultivars by biotechnological breeding. Genetic and molecular data for this species, though, are limited. In this paper, RNA-Seq technology has been employed, for the first time, to describe the root transcriptome of black pepper. The root transcriptome of black pepper was sequenced by the NGS SOLiD platform and assembled using the multiple-k method. Blast2Go and orthoMCL methods were used to annotate 10338 unigenes. The 4472 predicted proteins showed about 52% homology with the Arabidopsis proteome. Two root proteomes identified 615 proteins, which seem to define the plant's root pattern. Simple-sequence repeats were identified that may be useful in studies of genetic diversity and may have applications in biotechnology and ecology. This dataset of 10338 unigenes is crucially important for the biotechnological breeding of black pepper and the ecogenomics of the Magnoliids, a major group of basal angiosperms.

High-throughput sequencing of black pepper root transcriptome

PubMed Central

2012-01-01

Background Black pepper (Piper nigrum L.) is one of the most popular spices in the world. It is used in cooking and the preservation of food and even has medicinal properties. Losses in production from disease are a major limitation in the culture of this crop. The major diseases are root rot and foot rot, which are results of root infection by Fusarium solani and Phytophtora capsici, respectively. Understanding the molecular interaction between the pathogens and the host’s root region is important for obtaining resistant cultivars by biotechnological breeding. Genetic and molecular data for this species, though, are limited. In this paper, RNA-Seq technology has been employed, for the first time, to describe the root transcriptome of black pepper. Results The root transcriptome of black pepper was sequenced by the NGS SOLiD platform and assembled using the multiple-k method. Blast2Go and orthoMCL methods were used to annotate 10338 unigenes. The 4472 predicted proteins showed about 52% homology with the Arabidopsis proteome. Two root proteomes identified 615 proteins, which seem to define the plant’s root pattern. Simple-sequence repeats were identified that may be useful in studies of genetic diversity and may have applications in biotechnology and ecology. Conclusions This dataset of 10338 unigenes is crucially important for the biotechnological breeding of black pepper and the ecogenomics of the Magnoliids, a major group of basal angiosperms. PMID:22984782

Comparison of the adolescent and adult mouse prefrontal cortex proteome

PubMed Central

Small, Amanda T.; Spanos, Marina; Burrus, Brainard M.

2017-01-01

Adolescence is a developmental period characterized by unique behavioral phenotypes (increased novelty seeking, risk taking, sociability and impulsivity) and increased risk for destructive behaviors, impaired decision making and psychiatric illness. Adaptive and maladaptive adolescent traits have been associated with development of the medial prefrontal cortex (mPFC), a brain region that mediates regulatory control of behavior. However, the molecular changes that underlie brain development and behavioral vulnerability have not been fully characterized. Using high-throughput 2D DIGE spot profiling with identification by MALDI-TOF mass spectrometry, we identified 62 spots in the PFC that exhibited age-dependent differences in expression. Identified proteins were associated with diverse cellular functions, including intracellular signaling, synaptic plasticity, cellular organization and metabolism. Separate Western blot analyses confirmed age-related changes in DPYSL2, DNM1, STXBP1 and CFL1 in the mPFC and expanded these findings to the dorsal striatum, nucleus accumbens, motor cortex, amygdala and ventral tegmental area. Ingenuity Pathway Analysis (IPA) identified functional interaction networks enriched with proteins identified in the proteomics screen, linking age-related alterations in protein expression to cellular assembly and development, cell signaling and behavior, and psychiatric illness. These results provide insight into potential molecular components of adolescent cortical development, implicating structural processes that begin during embryonic development as well as plastic adaptations in signaling that may work in concert to bring the cortex, and other brain regions, into maturity. PMID:28570644

Vemurafenib resistance signature by proteome analysis offers new strategies and rational therapeutic concepts.

PubMed

Paulitschke, Verena; Berger, Walter; Paulitschke, Philipp; Hofstätter, Elisabeth; Knapp, Bernhard; Dingelmaier-Hovorka, Ruth; Födinger, Dagmar; Jäger, Walter; Szekeres, Thomas; Meshcheryakova, Anastasia; Bileck, Andrea; Pirker, Christine; Pehamberger, Hubert; Gerner, Christopher; Kunstfeld, Rainer

2015-03-01

The FDA-approved BRAF inhibitor vemurafenib achieves outstanding clinical response rates in patients with melanoma, but early resistance is common. Understanding the pathologic mechanisms of drug resistance and identification of effective therapeutic alternatives are key scientific challenges in the melanoma setting. Using proteomic techniques, including shotgun analysis and 2D-gel electrophoresis, we identified a comprehensive signature of the vemurafenib-resistant M24met in comparison with the vemurafenib-sensitive A375 melanoma cell line. The resistant cells were characterized by loss of differentiation, induction of transformation, enhanced expression of the lysosomal compartment, increased potential for metastasis, migration, adherence and Ca2(+) ion binding, enhanced expression of the MAPK pathway and extracellular matrix proteins, and epithelial-mesenchymal transformation. The main features were verified by shotgun analysis with QEXACTIVE orbitrap MS, electron microscopy, lysosomal staining, Western blotting, and adherence assay in a VM-1 melanoma cell line with acquired vemurafenib resistance. On the basis of the resistance profile, we were able to successfully predict that a novel resveratrol-derived COX-2 inhibitor, M8, would be active against the vemurafenib-resistant but not the vemurafenib-sensitive melanoma cells. Using high-throughput methods for cell line and drug characterization may thus offer a new way to identify key features of vemurafenib resistance, facilitating the design of effective rational therapeutic alternatives. ©2015 American Association for Cancer Research.

Comprehensive Analysis of Cancer-Proteogenome to Identify Biomarkers for the Early Diagnosis and Prognosis of Cancer.

PubMed

Shukla, Hem D

2017-10-25

During the past century, our understanding of cancer diagnosis and treatment has been based on a monogenic approach, and as a consequence our knowledge of the clinical genetic underpinnings of cancer is incomplete. Since the completion of the human genome in 2003, it has steered us into therapeutic target discovery, enabling us to mine the genome using cutting edge proteogenomics tools. A number of novel and promising cancer targets have emerged from the genome project for diagnostics, therapeutics, and prognostic markers, which are being used to monitor response to cancer treatment. The heterogeneous nature of cancer has hindered progress in understanding the underlying mechanisms that lead to abnormal cellular growth. Since, the start of The Cancer Genome Atlas (TCGA), and the International Genome consortium projects, there has been tremendous progress in genome sequencing and immense numbers of cancer genomes have been completed, and this approach has transformed our understanding of the diagnosis and treatment of different types of cancers. By employing Genomics and proteomics technologies, an immense amount of genomic data is being generated on clinical tumors, which has transformed the cancer landscape and has the potential to transform cancer diagnosis and prognosis. A complete molecular view of the cancer landscape is necessary for understanding the underlying mechanisms of cancer initiation to improve diagnosis and prognosis, which ultimately will lead to personalized treatment. Interestingly, cancer proteome analysis has also allowed us to identify biomarkers to monitor drug and radiation resistance in patients undergoing cancer treatment. Further, TCGA-funded studies have allowed for the genomic and transcriptomic characterization of targeted cancers, this analysis aiding the development of targeted therapies for highly lethal malignancy. High-throughput technologies, such as complete proteome, epigenome, protein-protein interaction, and pharmacogenomics data, are indispensable to glean into the cancer genome and proteome and these approaches have generated multidimensional universal studies of genes and proteins (OMICS) data which has the potential to facilitate precision medicine. However, due to slow progress in computational technologies, the translation of big omics data into their clinical aspects have been slow. In this review, attempts have been made to describe the role of high-throughput genomic and proteomic technologies in identifying a panel of biomarkers which could be used for the early diagnosis and prognosis of cancer.

Ion channel drug discovery and research: the automated Nano-Patch-Clamp technology.

PubMed

Brueggemann, A; George, M; Klau, M; Beckler, M; Steindl, J; Behrends, J C; Fertig, N

2004-01-01

Unlike the genomics revolution, which was largely enabled by a single technological advance (high throughput sequencing), rapid advancement in proteomics will require a broader effort to increase the throughput of a number of key tools for functional analysis of different types of proteins. In the case of ion channels -a class of (membrane) proteins of great physiological importance and potential as drug targets- the lack of adequate assay technologies is felt particularly strongly. The available, indirect, high throughput screening methods for ion channels clearly generate insufficient information. The best technology to study ion channel function and screen for compound interaction is the patch clamp technique, but patch clamping suffers from low throughput, which is not acceptable for drug screening. A first step towards a solution is presented here. The nano patch clamp technology, which is based on a planar, microstructured glass chip, enables automatic whole cell patch clamp measurements. The Port-a-Patch is an automated electrophysiology workstation, which uses planar patch clamp chips. This approach enables high quality and high content ion channel and compound evaluation on a one-cell-at-a-time basis. The presented automation of the patch process and its scalability to an array format are the prerequisites for any higher throughput electrophysiology instruments.

Fast liquid chromatography combined with mass spectrometry for the analysis of metabolites and proteins in human body fluids.

PubMed

Kortz, Linda; Helmschrodt, Christin; Ceglarek, Uta

2011-03-01

In the last decade various analytical strategies have been established to enhance separation speed and efficiency in high performance liquid chromatography applications. Chromatographic supports based on monolithic material, small porous particles, and porous layer beads have been developed and commercialized to improve throughput and separation efficiency. This paper provides an overview of current developments in fast chromatography combined with mass spectrometry for the analysis of metabolites and proteins in clinical applications. Advances and limitations of fast chromatography for the combination with mass spectrometry are discussed. Practical aspects of, recent developments in, and the present status of high-throughput analysis of human body fluids for therapeutic drug monitoring, toxicology, clinical metabolomics, and proteomics are presented.

A Comparison of Protein Extraction Methods Suitable for Gel-Based Proteomic Studies of Aphid Proteins

PubMed Central

Cilia, M.; Fish, T.; Yang, X.; Mclaughlin, M.; Thannhauser, T. W.

2009-01-01

Protein extraction methods can vary widely in reproducibility and in representation of the total proteome, yet there are limited data comparing protein isolation methods. The methodical comparison of protein isolation methods is the first critical step for proteomic studies. To address this, we compared three methods for isolation, purification, and solubilization of insect proteins. The aphid Schizaphis graminum, an agricultural pest, was the source of insect tissue. Proteins were extracted using TCA in acetone (TCA-acetone), phenol, or multi-detergents in a chaotrope solution. Extracted proteins were solubilized in a multiple chaotrope solution and examined using 1-D and 2-D electrophoresis and compared directly using 2-D Difference Gel Electrophoresis (2-D DIGE). Mass spectrometry was used to identify proteins from each extraction type. We were unable to ascribe the differences in the proteins extracted to particular physical characteristics, cell location, or biological function. The TCA-acetone extraction yielded the greatest amount of protein from aphid tissues. Each extraction method isolated a unique subset of the aphid proteome. The TCA-acetone method was explored further for its quantitative reliability using 2-D DIGE. Principal component analysis showed that little of the variation in the data was a result of technical issues, thus demonstrating that the TCA-acetone extraction is a reliable method for preparing aphid proteins for a quantitative proteomics experiment. These data suggest that although the TCA-acetone method is a suitable method for quantitative aphid proteomics, a combination of extraction approaches is recommended for increasing proteome coverage when using gel-based separation techniques. PMID:19721822

Domain selection combined with improved cloning strategy for high throughput expression of higher eukaryotic proteins

PubMed Central

Chen, Yunjia; Qiu, Shihong; Luan, Chi-Hao; Luo, Ming

2007-01-01

Background Expression of higher eukaryotic genes as soluble, stable recombinant proteins is still a bottleneck step in biochemical and structural studies of novel proteins today. Correct identification of stable domains/fragments within the open reading frame (ORF), combined with proper cloning strategies, can greatly enhance the success rate when higher eukaryotic proteins are expressed as these domains/fragments. Furthermore, a HTP cloning pipeline incorporated with bioinformatics domain/fragment selection methods will be beneficial to studies of structure and function genomics/proteomics. Results With bioinformatics tools, we developed a domain/domain boundary prediction (DDBP) method, which was trained by available experimental data. Combined with an improved cloning strategy, DDBP had been applied to 57 proteins from C. elegans. Expression and purification results showed there was a 10-fold increase in terms of obtaining purified proteins. Based on the DDBP method, the improved GATEWAY cloning strategy and a robotic platform, we constructed a high throughput (HTP) cloning pipeline, including PCR primer design, PCR, BP reaction, transformation, plating, colony picking and entry clones extraction, which have been successfully applied to 90 C. elegans genes, 88 Brucella genes, and 188 human genes. More than 97% of the targeted genes were obtained as entry clones. This pipeline has a modular design and can adopt different operations for a variety of cloning/expression strategies. Conclusion The DDBP method and improved cloning strategy were satisfactory. The cloning pipeline, combined with our recombinant protein HTP expression pipeline and the crystal screening robots, constitutes a complete platform for structure genomics/proteomics. This platform will increase the success rate of purification and crystallization dramatically and promote the further advancement of structure genomics/proteomics. PMID:17663785

Deciphering the functions of O-GlcNAc glycosylation in the brain: The role of site-specific quantitative O-GlcNAcomics.

PubMed

Thompson, John W; Sorum, Alexander W; Hsieh-Wilson, Linda C

2018-06-23

The dynamic posttranslational modification O-linked β-N-acetylglucosamine glycosylation (O-GlcNAcylation) is present on thousands of intracellular proteins in the brain. Like phosphorylation, O-GlcNAcylation is inducible and plays important functional roles in both physiology and disease. Recent advances in mass spectrometry (MS) and bioconjugation methods are now enabling the mapping of O-GlcNAcylation events to individual sites in proteins. However, our understanding of which glycosylation events are necessary for regulating protein function and controlling specific processes, phenotypes, or diseases remains in its infancy. Given the sheer number of O-GlcNAc sites, methods are greatly needed to identify promising sites and prioritize them for time- and resource-intensive functional studies. Revealing sites that are dynamically altered by different stimuli or disease states will likely to go a long way in this regard. Here, we describe advanced methods for identifying O-GlcNAc sites on individual proteins and across the proteome, and for determining their stoichiometry in vivo. We also highlight emerging technologies for quantitative, site-specific MS-based O-GlcNAc proteomics (O-GlcNAcomics), which allow proteome-wide tracking of O-GlcNAcylation dynamics at individual sites. These cutting-edge technologies are beginning to bridge the gap between the high-throughput cataloging of O-GlcNAcylated proteins and the relatively low-throughput study of individual proteins. By uncovering the O-GlcNAcylation events that change in specific physiological and disease contexts, these new approaches are providing key insights into the regulatory functions of O-GlcNAc in the brain, including their roles in neuroprotection, neuronal signaling, learning and memory, and neurodegenerative diseases.

Analysis of Protein Expression in Cell Microarrays: A Tool for Antibody-based Proteomics

PubMed Central

Andersson, Ann-Catrin; Strömberg, Sara; Bäckvall, Helena; Kampf, Caroline; Uhlen, Mathias; Wester, Kenneth; Pontén, Fredrik

2006-01-01

Tissue microarray (TMA) technology provides a possibility to explore protein expression patterns in a multitude of normal and disease tissues in a high-throughput setting. Although TMAs have been used for analysis of tissue samples, robust methods for studying in vitro cultured cell lines and cell aspirates in a TMA format have been lacking. We have adopted a technique to homogeneously distribute cells in an agarose gel matrix, creating an artificial tissue. This enables simultaneous profiling of protein expression in suspension- and adherent-grown cell samples assembled in a microarray. In addition, the present study provides an optimized strategy for the basic laboratory steps to efficiently produce TMAs. Presented modifications resulted in an improved quality of specimens and a higher section yield compared with standard TMA production protocols. Sections from the generated cell TMAs were tested for immunohistochemical staining properties using 20 well-characterized antibodies. Comparison of immunoreactivity in cultured dispersed cells and corresponding cells in tissue samples showed congruent results for all tested antibodies. We conclude that a modified TMA technique, including cell samples, provides a valuable tool for high-throughput analysis of protein expression, and that this technique can be used for global approaches to explore the human proteome. PMID:16957166

Generation and analyses of human synthetic antibody libraries and their application for protein microarrays.

PubMed

Säll, Anna; Walle, Maria; Wingren, Christer; Müller, Susanne; Nyman, Tomas; Vala, Andrea; Ohlin, Mats; Borrebaeck, Carl A K; Persson, Helena

2016-10-01

Antibody-based proteomics offers distinct advantages in the analysis of complex samples for discovery and validation of biomarkers associated with disease. However, its large-scale implementation requires tools and technologies that allow development of suitable antibody or antibody fragments in a high-throughput manner. To address this we designed and constructed two human synthetic antibody fragment (scFv) libraries denoted HelL-11 and HelL-13. By the use of phage display technology, in total 466 unique scFv antibodies specific for 114 different antigens were generated. The specificities of these antibodies were analyzed in a variety of immunochemical assays and a subset was further evaluated for functionality in protein microarray applications. This high-throughput approach demonstrates the ability to rapidly generate a wealth of reagents not only for proteome research, but potentially also for diagnostics and therapeutics. In addition, this work provides a great example on how a synthetic approach can be used to optimize library designs. By having precise control of the diversity introduced into the antigen-binding sites, synthetic libraries offer increased understanding of how different diversity contributes to antibody binding reactivity and stability, thereby providing the key to future library optimization. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

SteinerNet: a web server for integrating ‘omic’ data to discover hidden components of response pathways

PubMed Central

Tuncbag, Nurcan; McCallum, Scott; Huang, Shao-shan Carol; Fraenkel, Ernest

2012-01-01

High-throughput technologies including transcriptional profiling, proteomics and reverse genetics screens provide detailed molecular descriptions of cellular responses to perturbations. However, it is difficult to integrate these diverse data to reconstruct biologically meaningful signaling networks. Previously, we have established a framework for integrating transcriptional, proteomic and interactome data by searching for the solution to the prize-collecting Steiner tree problem. Here, we present a web server, SteinerNet, to make this method available in a user-friendly format for a broad range of users with data from any species. At a minimum, a user only needs to provide a set of experimentally detected proteins and/or genes and the server will search for connections among these data from the provided interactomes for yeast, human, mouse, Drosophila melanogaster and Caenorhabditis elegans. More advanced users can upload their own interactome data as well. The server provides interactive visualization of the resulting optimal network and downloadable files detailing the analysis and results. We believe that SteinerNet will be useful for researchers who would like to integrate their high-throughput data for a specific condition or cellular response and to find biologically meaningful pathways. SteinerNet is accessible at http://fraenkel.mit.edu/steinernet. PMID:22638579

Architecture Mapping of the Inner Mitochondrial Membrane Proteome by Chemical Tools in Live Cells.

PubMed

Lee, Song-Yi; Kang, Myeong-Gyun; Shin, Sanghee; Kwak, Chulhwan; Kwon, Taejoon; Seo, Jeong Kon; Kim, Jong-Seo; Rhee, Hyun-Woo

2017-03-15

The inner mitochondrial membrane (IMM) proteome plays a central role in maintaining mitochondrial physiology and cellular metabolism. Various important biochemical reactions such as oxidative phosphorylation, metabolite production, and mitochondrial biogenesis are conducted by the IMM proteome, and mitochondria-targeted therapeutics have been developed for IMM proteins, which is deeply related for various human metabolic diseases including cancer and neurodegenerative diseases. However, the membrane topology of the IMM proteome remains largely unclear because of the lack of methods to evaluate it in live cells in a high-throughput manner. In this article, we reveal the in vivo topological direction of 135 IMM proteins, using an in situ-generated radical probe with genetically targeted peroxidase (APEX). Owing to the short lifetime of phenoxyl radicals generated in situ by submitochondrial targeted APEX and the impermeability of the IMM to small molecules, the solvent-exposed tyrosine residues of both the matrix and intermembrane space (IMS) sides of IMM proteins were exclusively labeled with the radical probe in live cells by Matrix-APEX and IMS-APEX, respectively and identified by mass spectrometry. From this analysis, we confirmed 58 IMM protein topologies and we could determine the topological direction of 77 IMM proteins whose topology at the IMM has not been fully characterized. We also found several IMM proteins (e.g., LETM1 and OXA1) whose topological information should be revised on the basis of our results. Overall, our identification of structural information on the mitochondrial inner-membrane proteome can provide valuable insights for the architecture and connectome of the IMM proteome in live cells.

Top-down proteomics reveals a unique protein S-thiolation switch in Salmonella Typimurium in response to infection-like conditions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ansong, Charles; Wu, Si; Meng, Da

Characterization of the mature protein complement in cells is crucial for a better understanding of cellular processes on a systems-wide scale. Bottom-up proteomic approaches often lead to loss of critical information about an endogenous protein’s actual state due to post translational modifications (PTMs) and other processes. Top-down approaches that involve analysis of the intact protein can address this concern but present significant analytical challenges related to the separation quality needed, measurement sensitivity, and speed that result in low throughput and limited coverage. Here we used single-dimension ultra high pressure liquid chromatography mass spectrometry to investigate the comprehensive ‘intact’ proteome ofmore » the Gram negative bacterial pathogen Salmonella Typhimurium. Top-down proteomics analysis revealed 563 unique proteins including 1665 proteoforms generated by PTMs, representing the largest microbial top-down dataset reported to date. Our analysis not only confirmed several previously recognized aspects of Salmonella biology and bacterial PTMs in general, but also revealed several novel biological insights. Of particular interest was differential utilization of the protein S-thiolation forms S-glutathionylation and S-cysteinylation in response to infection-like conditions versus basal conditions, which was corroborated by changes in corresponding biosynthetic pathways. This differential utilization highlights underlying metabolic mechanisms that modulate changes in cellular signaling, and represents to our knowledge the first report of S-cysteinylation in Gram negative bacteria. The demonstrated utility of our simple proteome-wide intact protein level measurement strategy for gaining biological insight should promote broader adoption and applications of top-down proteomics approaches.« less

Simulation and fabrication of a new novel 3D injectable biosensor for high throughput genomics and proteomics in a lab-on-a-chip device.

PubMed

Esfandyarpour, Rahim; Esfandyarpour, Hesaam; Harris, James S; Davis, Ronald W

2013-11-22

Biosensors are used for the detection of biochemical molecules such as proteins and nucleic acids. Traditional techniques, such as enzyme-linked immuno-sorbent assay (ELISA), are sensitive but require several hours to yield a result and usually require the attachment of a fluorophore molecule to the target molecule. Micromachined biosensors that employ electrical detection are now being developed. Here we describe one such device, which is ultrasensitive, real-time, label free and localized. It is called the nanoneedle biosensor and shows promise to overcome some of the current limitations of biosensors. The key element of this device is a 10 nm wide annular gap at the end of the needle, which is the sensitive part of the sensor. The total diameter of the sensor is about 100 nm. Any change in the population of molecules in this gap results in a change of impedance across the gap. Single molecule detection should be possible because the sensory part of the sensor is in the range of bio-molecules of interest. To increase throughput we can flow the solution containing the target molecules over an array of such structures, each with its own integrated read-out circuitry to allow 'real-time' detection (i.e. several minutes) of label free molecules without sacrificing sensitivity. To fabricate the arrays we used electron beam lithography together with associated pattern transfer techniques. Preliminary measurements on individual needle structures in water are consistent with the design. Since the proposed sensor has a rigid nano-structure, this technology, once fully developed, could ultimately be used to directly monitor protein quantities within a single living cell, an application that would have significant utility for drug screening and studying various intracellular signaling pathways.

Simulation and fabrication of a new novel 3D injectable biosensor for high throughput genomics and proteomics in a lab-on-a-chip device

NASA Astrophysics Data System (ADS)

Esfandyarpour, Rahim; Esfandyarpour, Hesaam; Harris, James S.; Davis, Ronald W.

2013-11-01

Biosensors are used for the detection of biochemical molecules such as proteins and nucleic acids. Traditional techniques, such as enzyme-linked immuno-sorbent assay (ELISA), are sensitive but require several hours to yield a result and usually require the attachment of a fluorophore molecule to the target molecule. Micromachined biosensors that employ electrical detection are now being developed. Here we describe one such device, which is ultrasensitive, real-time, label free and localized. It is called the nanoneedle biosensor and shows promise to overcome some of the current limitations of biosensors. The key element of this device is a 10 nm wide annular gap at the end of the needle, which is the sensitive part of the sensor. The total diameter of the sensor is about 100 nm. Any change in the population of molecules in this gap results in a change of impedance across the gap. Single molecule detection should be possible because the sensory part of the sensor is in the range of bio-molecules of interest. To increase throughput we can flow the solution containing the target molecules over an array of such structures, each with its own integrated read-out circuitry to allow ‘real-time’ detection (i.e. several minutes) of label free molecules without sacrificing sensitivity. To fabricate the arrays we used electron beam lithography together with associated pattern transfer techniques. Preliminary measurements on individual needle structures in water are consistent with the design. Since the proposed sensor has a rigid nano-structure, this technology, once fully developed, could ultimately be used to directly monitor protein quantities within a single living cell, an application that would have significant utility for drug screening and studying various intracellular signaling pathways.

The Present and Future of Biomarkers in Prostate Cancer: Proteomics, Genomics, and Immunology Advancements

PubMed Central

Gaudreau, Pierre-Olivier; Stagg, John; Soulières, Denis; Saad, Fred

2016-01-01

Prostate cancer (PC) is the second most common form of cancer in men worldwide. Biomarkers have emerged as essential tools for treatment and assessment since the variability of disease behavior, the cost and diversity of treatments, and the related impairment of quality of life have given rise to a need for a personalized approach. High-throughput technology platforms in proteomics and genomics have accelerated the development of biomarkers. Furthermore, recent successes of several new agents in PC, including immunotherapy, have stimulated the search for predictors of response and resistance and have improved the understanding of the biological mechanisms at work. This review provides an overview of currently established biomarkers in PC, as well as a selection of the most promising biomarkers within these particular fields of development. PMID:27168728

The clinical impact of recent advances in LC-MS for cancer biomarker discovery and verification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Hui; Shi, Tujin; Qian, Wei-Jun

2015-12-04

Mass spectrometry-based proteomics has become an indispensable tool in biomedical research with broad applications ranging from fundamental biology, systems biology, and biomarker discovery. Recent advances in LC-MS have made it become a major technology in clinical applications, especially in cancer biomarker discovery and verification. To overcome the challenges associated with the analysis of clinical samples, such as extremely wide dynamic range of protein concentrations in biofluids and the need to perform high throughput and accurate quantification, significant efforts have been devoted to improve the overall performance of LC-MS bases clinical proteomics. In this review, we summarize the recent advances inmore » LC-MS in the aspect of cancer biomarker discovery and quantification, and discuss its potentials, limitations, and future perspectives.« less

Free Flow Zonal Electrophoresis for Fractionation of Plant Membrane Compartments Prior to Proteomic Analysis.

PubMed

Barkla, Bronwyn J

2018-01-01

Free flow zonal electrophoresis (FFZE) is a versatile, reproducible, and potentially high-throughput technique for the separation of plant organelles and membranes by differences in membrane surface charge. It offers considerable benefits over traditional fractionation techniques, such as density gradient centrifugation and two-phase partitioning, as it is relatively fast, sample recovery is high, and the method provides unparalleled sample purity. It has been used to successfully purify chloroplasts and mitochondria from plants but also, to obtain highly pure fractions of plasma membrane, tonoplast, ER, Golgi, and thylakoid membranes. Application of the technique can significantly improve protein coverage in large-scale proteomics studies by decreasing sample complexity. Here, we describe the method for the fractionation of plant cellular membranes from leaves by FFZE.

The diverse and expanding role of mass spectrometry in structural and molecular biology.

PubMed

Lössl, Philip; van de Waterbeemd, Michiel; Heck, Albert Jr

2016-12-15

The emergence of proteomics has led to major technological advances in mass spectrometry (MS). These advancements not only benefitted MS-based high-throughput proteomics but also increased the impact of mass spectrometry on the field of structural and molecular biology. Here, we review how state-of-the-art MS methods, including native MS, top-down protein sequencing, cross-linking-MS, and hydrogen-deuterium exchange-MS, nowadays enable the characterization of biomolecular structures, functions, and interactions. In particular, we focus on the role of mass spectrometry in integrated structural and molecular biology investigations of biological macromolecular complexes and cellular machineries, highlighting work on CRISPR-Cas systems and eukaryotic transcription complexes. © 2016 The Authors. Published under the terms of the CC BY NC ND 4.0 license.

The clinical impact of recent advances in LC-MS for cancer biomarker discovery and verification.

PubMed

Wang, Hui; Shi, Tujin; Qian, Wei-Jun; Liu, Tao; Kagan, Jacob; Srivastava, Sudhir; Smith, Richard D; Rodland, Karin D; Camp, David G

2016-01-01

Mass spectrometry (MS) -based proteomics has become an indispensable tool with broad applications in systems biology and biomedical research. With recent advances in liquid chromatography (LC) and MS instrumentation, LC-MS is making increasingly significant contributions to clinical applications, especially in the area of cancer biomarker discovery and verification. To overcome challenges associated with analyses of clinical samples (for example, a wide dynamic range of protein concentrations in bodily fluids and the need to perform high throughput and accurate quantification of candidate biomarker proteins), significant efforts have been devoted to improve the overall performance of LC-MS-based clinical proteomics platforms. Reviewed here are the recent advances in LC-MS and its applications in cancer biomarker discovery and quantification, along with the potentials, limitations and future perspectives.

HiCTMap: Detection and analysis of chromosome territory structure and position by high-throughput imaging.

PubMed

Jowhar, Ziad; Gudla, Prabhakar R; Shachar, Sigal; Wangsa, Darawalee; Russ, Jill L; Pegoraro, Gianluca; Ried, Thomas; Raznahan, Armin; Misteli, Tom

2018-06-01

The spatial organization of chromosomes in the nuclear space is an extensively studied field that relies on measurements of structural features and 3D positions of chromosomes with high precision and robustness. However, no tools are currently available to image and analyze chromosome territories in a high-throughput format. Here, we have developed High-throughput Chromosome Territory Mapping (HiCTMap), a method for the robust and rapid analysis of 2D and 3D chromosome territory positioning in mammalian cells. HiCTMap is a high-throughput imaging-based chromosome detection method which enables routine analysis of chromosome structure and nuclear position. Using an optimized FISH staining protocol in a 384-well plate format in conjunction with a bespoke automated image analysis workflow, HiCTMap faithfully detects chromosome territories and their position in 2D and 3D in a large population of cells per experimental condition. We apply this novel technique to visualize chromosomes 18, X, and Y in male and female primary human skin fibroblasts, and show accurate detection of the correct number of chromosomes in the respective genotypes. Given the ability to visualize and quantitatively analyze large numbers of nuclei, we use HiCTMap to measure chromosome territory area and volume with high precision and determine the radial position of chromosome territories using either centroid or equidistant-shell analysis. The HiCTMap protocol is also compatible with RNA FISH as demonstrated by simultaneous labeling of X chromosomes and Xist RNA in female cells. We suggest HiCTMap will be a useful tool for routine precision mapping of chromosome territories in a wide range of cell types and tissues. Published by Elsevier Inc.

Highlights of B/D-HPP and HPP Resource Pillar Workshops at 12th Annual HUPO World Congress of Proteomics: September 14-18, 2013, Yokohama, Japan.

PubMed

Aebersold, Ruedi; Bader, Gary D; Edwards, Aled M; van Eyk, Jennifer; Kussman, Martin; Qin, Jun; Omenn, Gilbert S

2014-05-01

At the 12th Annual HUPO World Congress of Proteomics in Japan, the Human Proteome Project (HPP) presented 16 scientific workshop sessions. Here we summarize highlights of ten workshops from the Biology and Disease-driven HPP (B/D-HPP) teams and three from the HPP Resource Pillars. Highlights of the three Chromosome-centric HPP sessions appeared in the many articles of the 2014 C-HPP special issue of the Journal of Proteome Research . © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Immunoproteomic Profiling of Antiviral Antibodies in New-Onset Type 1 Diabetes Using Protein Arrays

PubMed Central

Bian, Xiaofang; Wallstrom, Garrick; Davis, Amy; Wang, Jie; Park, Jin; Throop, Andrea; Steel, Jason; Yu, Xiaobo; Wasserfall, Clive; Schatz, Desmond; Atkinson, Mark

2016-01-01

The rapid rise in the incidence of type 1 diabetes (T1D) suggests the involvement of environmental factors including viral infections. We evaluated the association between viral infections and T1D by profiling antiviral antibodies using a high-throughput immunoproteomics approach in patients with new-onset T1D. We constructed a viral protein array comprising the complete proteomes of seven viruses associated with T1D and open reading frames from other common viruses. Antibody responses to 646 viral antigens were assessed in 42 patients with T1D and 42 age- and sex-matched healthy control subjects (mean age 12.7 years, 50% males). Prevalence of antiviral antibodies agreed with known infection rates for the corresponding virus based on epidemiological studies. Antibody responses to Epstein-Barr virus (EBV) were significantly higher in case than control subjects (odds ratio 6.6; 95% CI 2.0–25.7), whereas the other viruses showed no differences. The EBV and T1D association was significant in both sex and age subgroups (≤12 and >12 years), and there was a trend toward early EBV infections among the case subjects. These results suggest a potential role for EBV in T1D development. We believe our innovative immunoproteomics platform is useful for understanding the role of viral infections in T1D and other disorders where associations between viral infection and disease are unclear. PMID:26450993

The upcoming 3D-printing revolution in microfluidics.

PubMed

Bhattacharjee, Nirveek; Urrios, Arturo; Kang, Shawn; Folch, Albert

2016-05-21

In the last two decades, the vast majority of microfluidic systems have been built in poly(dimethylsiloxane) (PDMS) by soft lithography, a technique based on PDMS micromolding. A long list of key PDMS properties have contributed to the success of soft lithography: PDMS is biocompatible, elastomeric, transparent, gas-permeable, water-impermeable, fairly inexpensive, copyright-free, and rapidly prototyped with high precision using simple procedures. However, the fabrication process typically involves substantial human labor, which tends to make PDMS devices difficult to disseminate outside of research labs, and the layered molding limits the 3D complexity of the devices that can be produced. 3D-printing has recently attracted attention as a way to fabricate microfluidic systems due to its automated, assembly-free 3D fabrication, rapidly decreasing costs, and fast-improving resolution and throughput. Resins with properties approaching those of PDMS are being developed. Here we review past and recent efforts in 3D-printing of microfluidic systems. We compare the salient features of PDMS molding with those of 3D-printing and we give an overview of the critical barriers that have prevented the adoption of 3D-printing by microfluidic developers, namely resolution, throughput, and resin biocompatibility. We also evaluate the various forces that are persuading researchers to abandon PDMS molding in favor of 3D-printing in growing numbers.

Proteomic approaches in brain research and neuropharmacology.

PubMed

Vercauteren, Freya G G; Bergeron, John J M; Vandesande, Frans; Arckens, Lut; Quirion, Rémi

2004-10-01

Numerous applications of genomic technologies have enabled the assembly of unprecedented inventories of genes, expressed in cells under specific physiological and pathophysiological conditions. Complementing the valuable information generated through functional genomics with the integrative knowledge of protein expression and function should enable the development of more efficient diagnostic tools and therapeutic agents. Proteomic analyses are particularly suitable to elucidate posttranslational modifications, expression levels and protein-protein interactions of thousands of proteins at a time. In this review, two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) investigations of brain tissues in neurodegenerative diseases such as Alzheimer's disease, Down syndrome and schizophrenia, and the construction of 2D-PAGE proteome maps of the brain are discussed. The role of the Human Proteome Organization (HUPO) as an international coordinating organization for proteomic efforts, as well as challenges for proteomic technologies and data analysis are also addressed. It is expected that the use of proteomic strategies will have significant impact in neuropharmacology over the coming decade.

Suppressing the relaxation oscillation noise of injection-locked WRC-FPLD for directly modulated OFDM transmission.

PubMed

Cheng, Min-Chi; Chi, Yu-Chieh; Li, Yi-Cheng; Tsai, Cheng-Ting; Lin, Gong-Ru

2014-06-30

By up-shifting the relaxation oscillation peak and suppressing its relative intensity noise in a weak-resonant-cavity Fabry-Perot laser diode (WRC-FPLD) under intense injection-locking, the directly modulated transmission of optical 16 quadrature amplitude modulation (QAM) orthogonal frequency division multiplexing (OFDM) data-stream is demonstrated. The total bit rate of up to 20 Gbit/s within 5-GHz bandwidth is achieved by using the OFDM subcarrier pre-leveling technique. With increasing the injection-locking power from -12 to -3 dBm, the effective reduction on threshold current of the WRC-FPLD significantly shifts its relaxation oscillation frequency from 5 to 7.5 GHz. This concurrently induces an up-shift of the peak relative intensity noise (RIN) of the WRC-FPLD, and effectively suppresses the background RIN level to -104 dBc/Hz within the OFDM band between 3 and 6 GHz. The enhanced signal-to-noise ratio from 16 to 20 dB leads to a significant reduction of bit-error-rate (BER) of the back-to-back transmitted 16-QAM-OFDM data from 1.3 × 10(-3) to 5 × 10(-5), which slightly degrades to 1.1 × 10(-4) after 25-km single-mode fiber (SMF) transmission. However, the enlarged injection-locking power from -12 to -3 dBm inevitably declines the modulation throughput and increases its negative throughput slope from -0.8 to -1.9 dBm/GHz. After pre-leveling the peak amplitude of the OFDM subcarriers to compensate the throughput degradation of the directly modulated WRC-FPLD, the BER under 25-km SMF transmission can be further improved to 3 × 10(-5) under a receiving power of -3 dBm.

Multiplex High-Throughput Targeted Proteomic Assay To Identify Induced Pluripotent Stem Cells.

PubMed

Baud, Anna; Wessely, Frank; Mazzacuva, Francesca; McCormick, James; Camuzeaux, Stephane; Heywood, Wendy E; Little, Daniel; Vowles, Jane; Tuefferd, Marianne; Mosaku, Olukunbi; Lako, Majlinda; Armstrong, Lyle; Webber, Caleb; Cader, M Zameel; Peeters, Pieter; Gissen, Paul; Cowley, Sally A; Mills, Kevin

2017-02-21

Induced pluripotent stem cells have great potential as a human model system in regenerative medicine, disease modeling, and drug screening. However, their use in medical research is hampered by laborious reprogramming procedures that yield low numbers of induced pluripotent stem cells. For further applications in research, only the best, competent clones should be used. The standard assays for pluripotency are based on genomic approaches, which take up to 1 week to perform and incur significant cost. Therefore, there is a need for a rapid and cost-effective assay able to distinguish between pluripotent and nonpluripotent cells. Here, we describe a novel multiplexed, high-throughput, and sensitive peptide-based multiple reaction monitoring mass spectrometry assay, allowing for the identification and absolute quantitation of multiple core transcription factors and pluripotency markers. This assay provides simpler and high-throughput classification into either pluripotent or nonpluripotent cells in 7 min analysis while being more cost-effective than conventional genomic tests.

Microgravity-driven remodeling of the proteome reveals insights into molecular mechanisms and signal networks involved in response to the space flight environment.

PubMed

Rea, Giuseppina; Cristofaro, Francesco; Pani, Giuseppe; Pascucci, Barbara; Ghuge, Sandip A; Corsetto, Paola Antonia; Imbriani, Marcello; Visai, Livia; Rizzo, Angela M

2016-03-30

Space is a hostile environment characterized by high vacuum, extreme temperatures, meteoroids, space debris, ionospheric plasma, microgravity and space radiation, which all represent risks for human health. A deep understanding of the biological consequences of exposure to the space environment is required to design efficient countermeasures to minimize their negative impact on human health. Recently, proteomic approaches have received a significant amount of attention in the effort to further study microgravity-induced physiological changes. In this review, we summarize the current knowledge about the effects of microgravity on microorganisms (in particular Cupriavidus metallidurans CH34, Bacillus cereus and Rhodospirillum rubrum S1H), plants (whole plants, organs, and cell cultures), mammalian cells (endothelial cells, bone cells, chondrocytes, muscle cells, thyroid cancer cells, immune system cells) and animals (invertebrates, vertebrates and mammals). Herein, we describe their proteome's response to microgravity, focusing on proteomic discoveries and their future potential applications in space research. Space experiments and operational flight experience have identified detrimental effects on human health and performance because of exposure to weightlessness, even when currently available countermeasures are implemented. Many experimental tools and methods have been developed to study microgravity induced physiological changes. Recently, genomic and proteomic approaches have received a significant amount of attention. This review summarizes the recent research studies of the proteome response to microgravity inmicroorganisms, plants, mammalians cells and animals. Current proteomic tools allow large-scale, high-throughput analyses for the detection, identification, and functional investigation of all proteomes. Understanding gene and/or protein expression is the key to unlocking the mechanisms behind microgravity-induced problems and to finding effective countermeasures to spaceflight-induced alterations but also for the study of diseases on earth. Future perspectives are also highlighted. Copyright © 2015 Elsevier B.V. All rights reserved.

Mass spectrometry-based targeted quantitative proteomics: achieving sensitive and reproducible detection of proteins.

PubMed

Boja, Emily S; Rodriguez, Henry

2012-04-01

Traditional shotgun proteomics used to detect a mixture of hundreds to thousands of proteins through mass spectrometric analysis, has been the standard approach in research to profile protein content in a biological sample which could lead to the discovery of new (and all) protein candidates with diagnostic, prognostic, and therapeutic values. In practice, this approach requires significant resources and time, and does not necessarily represent the goal of the researcher who would rather study a subset of such discovered proteins (including their variations or posttranslational modifications) under different biological conditions. In this context, targeted proteomics is playing an increasingly important role in the accurate measurement of protein targets in biological samples in the hope of elucidating the molecular mechanism of cellular function via the understanding of intricate protein networks and pathways. One such (targeted) approach, selected reaction monitoring (or multiple reaction monitoring) mass spectrometry (MRM-MS), offers the capability of measuring multiple proteins with higher sensitivity and throughput than shotgun proteomics. Developing and validating MRM-MS-based assays, however, is an extensive and iterative process, requiring a coordinated and collaborative effort by the scientific community through the sharing of publicly accessible data and datasets, bioinformatic tools, standard operating procedures, and well characterized reagents. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Proteomic Screening of Antigenic Proteins from the Hard Tick, Haemaphysalis longicornis (Acari: Ixodidae)

PubMed Central

Kim, Young-Ha; slam, Mohammad Saiful; You, Myung-Jo

2015-01-01

Proteomic tools allow large-scale, high-throughput analyses for the detection, identification, and functional investigation of proteome. For detection of antigens from Haemaphysalis longicornis, 1-dimensional electrophoresis (1-DE) quantitative immunoblotting technique combined with 2-dimensional electrophoresis (2-DE) immunoblotting was used for whole body proteins from unfed and partially fed female ticks. Reactivity bands and 2-DE immunoblotting were performed following 2-DE electrophoresis to identify protein spots. The proteome of the partially fed female had a larger number of lower molecular weight proteins than that of the unfed female tick. The total number of detected spots was 818 for unfed and 670 for partially fed female ticks. The 2-DE immunoblotting identified 10 antigenic spots from unfed females and 8 antigenic spots from partially fed females. Matrix Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry (MALDI-TOF) of relevant spots identified calreticulin, putative secreted WC salivary protein, and a conserved hypothetical protein from the National Center for Biotechnology Information and Swiss Prot protein sequence databases. These findings indicate that most of the whole body components of these ticks are non-immunogenic. The data reported here will provide guidance in the identification of antigenic proteins to prevent infestation and diseases transmitted by H. longicornis. PMID:25748713

Proteomic Cinderella: Customized analysis of bulky MS/MS data in one night.

PubMed

Kiseleva, Olga; Poverennaya, Ekaterina; Shargunov, Alexander; Lisitsa, Andrey

2018-02-01

Proteomic challenges, stirred up by the advent of high-throughput technologies, produce large amount of MS data. Nowadays, the routine manual search does not satisfy the "speed" of modern science any longer. In our work, the necessity of single-thread analysis of bulky data emerged during interpretation of HepG2 proteome profiling results for proteoforms searching. We compared the contribution of each of the eight search engines (X!Tandem, MS-GF[Formula: see text], MS Amanda, MyriMatch, Comet, Tide, Andromeda, and OMSSA) integrated in an open-source graphical user interface SearchGUI ( http://searchgui.googlecode.com ) into total result of proteoforms identification and optimized set of engines working simultaneously. We also compared the results of our search combination with Mascot results using protein kit UPS2, containing 48 human proteins. We selected combination of X!Tandem, MS-GF[Formula: see text] and OMMSA as the most time-efficient and productive combination of search. We added homemade java-script to automatize pipeline from file picking to report generation. These settings resulted in rise of the efficiency of our customized pipeline unobtainable by manual scouting: the analysis of 192 files searched against human proteome (42153 entries) downloaded from UniProt took 11[Formula: see text]h.

Unlocking the proteomic information encoded in MALDI-TOF-MS data used for microbial identification and characterization.

PubMed

Fagerquist, Clifton K

2017-01-01

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) is increasingly utilized as a rapid technique to identify microorganisms including pathogenic bacteria. However, little attention has been paid to the significant proteomic information encoded in the MS peaks that collectively constitute the MS 'fingerprint'. This review/perspective is intended to explore this topic in greater detail in the hopes that it may spur interest and further research in this area. Areas covered: This paper examines the recent literature on utilizing MALDI-TOF for bacterial identification. Critical works highlighting protein biomarker identification of bacteria, arguments for and against protein biomarker identification, proteomic approaches to biomarker identification, emergence of MALDI-TOF-TOF platforms and their use for top-down proteomic identification of bacterial proteins, protein denaturation and its effect on protein ion fragmentation, collision cross-sections and energy deposition during desorption/ionization are also explored. Expert commentary: MALDI-TOF and TOF-TOF mass spectrometry platforms will continue to provide chemical analyses that are rapid, cost-effective and high throughput. These instruments have proven their utility in the taxonomic identification of pathogenic bacteria at the genus and species level and are poised to more fully characterize these microorganisms to the benefit of clinical microbiology, food safety and other fields.

Cloud CPFP: a shotgun proteomics data analysis pipeline using cloud and high performance computing.

PubMed

Trudgian, David C; Mirzaei, Hamid

2012-12-07

We have extended the functionality of the Central Proteomics Facilities Pipeline (CPFP) to allow use of remote cloud and high performance computing (HPC) resources for shotgun proteomics data processing. CPFP has been modified to include modular local and remote scheduling for data processing jobs. The pipeline can now be run on a single PC or server, a local cluster, a remote HPC cluster, and/or the Amazon Web Services (AWS) cloud. We provide public images that allow easy deployment of CPFP in its entirety in the AWS cloud. This significantly reduces the effort necessary to use the software, and allows proteomics laboratories to pay for compute time ad hoc, rather than obtaining and maintaining expensive local server clusters. Alternatively the Amazon cloud can be used to increase the throughput of a local installation of CPFP as necessary. We demonstrate that cloud CPFP allows users to process data at higher speed than local installations but with similar cost and lower staff requirements. In addition to the computational improvements, the web interface to CPFP is simplified, and other functionalities are enhanced. The software is under active development at two leading institutions and continues to be released under an open-source license at http://cpfp.sourceforge.net.

Fungal proteomics: from identification to function.

PubMed

Doyle, Sean

2011-08-01

Some fungi cause disease in humans and plants, while others have demonstrable potential for the control of insect pests. In addition, fungi are also a rich reservoir of therapeutic metabolites and industrially useful enzymes. Detailed analysis of fungal biochemistry is now enabled by multiple technologies including protein mass spectrometry, genome and transcriptome sequencing and advances in bioinformatics. Yet, the assignment of function to fungal proteins, encoded either by in silico annotated, or unannotated genes, remains problematic. The purpose of this review is to describe the strategies used by many researchers to reveal protein function in fungi, and more importantly, to consolidate the nomenclature of 'unknown function protein' as opposed to 'hypothetical protein' - once any protein has been identified by protein mass spectrometry. A combination of approaches including comparative proteomics, pathogen-induced protein expression and immunoproteomics are outlined, which, when used in combination with a variety of other techniques (e.g. functional genomics, microarray analysis, immunochemical and infection model systems), appear to yield comprehensive and definitive information on protein function in fungi. The relative advantages of proteomic, as opposed to transcriptomic-only, analyses are also described. In the future, combined high-throughput, quantitative proteomics, allied to transcriptomic sequencing, are set to reveal much about protein function in fungi. © 2011 Federation of European Microbiological Societies. Published by Blackwell Publishing Ltd. All rights reserved.

Quantitative proteomic analysis of microdissected oral epithelium for cancer biomarker discovery.

PubMed

Xiao, Hua; Langerman, Alexander; Zhang, Yan; Khalid, Omar; Hu, Shen; Cao, Cheng-Xi; Lingen, Mark W; Wong, David T W

2015-11-01

Specific biomarkers are urgently needed for the detection and progression of oral cancer. The objective of this study was to discover cancer biomarkers from oral epithelium through utilizing high throughput quantitative proteomics approaches. Morphologically malignant, epithelial dysplasia, and adjacent normal epithelial tissues were laser capture microdissected (LCM) from 19 patients and used for proteomics analysis. Total proteins from each group were extracted, digested and then labelled with corresponding isobaric tags for relative and absolute quantitation (iTRAQ). Labelled peptides from each sample were combined and analyzed by liquid chromatography-mass spectrometry (LC-MS/MS) for protein identification and quantification. In total, 500 proteins were identified and 425 of them were quantified. When compared with adjacent normal oral epithelium, 17 and 15 proteins were consistently up-regulated or down-regulated in malignant and epithelial dysplasia, respectively. Half of these candidate biomarkers were discovered for oral cancer for the first time. Cornulin was initially confirmed in tissue protein extracts and was further validated in tissue microarray. Its presence in the saliva of oral cancer patients was also explored. Myoglobin and S100A8 were pre-validated by tissue microarray. These data demonstrated that the proteomic biomarkers discovered through this strategy are potential targets for oral cancer detection and salivary diagnostics. Copyright © 2015 Elsevier Ltd. All rights reserved.

Urinary Collagen Fragments Are Significantly Altered in Diabetes: A Link to Pathophysiology

PubMed Central

Argilés, Àngel; Cerna, Marie; Delles, Christian; Dominiczak, Anna F.; Gayrard, Nathalie; Iphöfer, Alexander; Jänsch, Lothar; Jerums, George; Medek, Karel; Mischak, Harald; Navis, Gerjan J.; Roob, Johannes M.; Rossing, Kasper; Rossing, Peter; Rychlík, Ivan; Schiffer, Eric; Schmieder, Roland E.; Wascher, Thomas C.; Winklhofer-Roob, Brigitte M.; Zimmerli, Lukas U.; Zürbig, Petra; Snell-Bergeon, Janet K.

2010-01-01

Background The pathogenesis of diabetes mellitus (DM) is variable, comprising different inflammatory and immune responses. Proteome analysis holds the promise of delivering insight into the pathophysiological changes associated with diabetes. Recently, we identified and validated urinary proteomics biomarkers for diabetes. Based on these initial findings, we aimed to further validate urinary proteomics biomarkers specific for diabetes in general, and particularity associated with either type 1 (T1D) or type 2 diabetes (T2D). Methodology/Principal Findings Therefore, the low-molecular-weight urinary proteome of 902 subjects from 10 different centers, 315 controls and 587 patients with T1D (n = 299) or T2D (n = 288), was analyzed using capillary-electrophoresis mass-spectrometry. The 261 urinary biomarkers (100 were sequenced) previously discovered in 205 subjects were validated in an additional 697 subjects to distinguish DM subjects (n = 382) from control subjects (n = 315) with 94% (95% CI: 92–95) accuracy in this study. To identify biomarkers that differentiate T1D from T2D, a subset of normoalbuminuric patients with T1D (n = 68) and T2D (n = 42) was employed, enabling identification of 131 biomarker candidates (40 were sequenced) differentially regulated between T1D and T2D. These biomarkers distinguished T1D from T2D in an independent validation set of normoalbuminuric patients (n = 108) with 88% (95% CI: 81–94%) accuracy, and in patients with impaired renal function (n = 369) with 85% (95% CI: 81–88%) accuracy. Specific collagen fragments were associated with diabetes and type of diabetes indicating changes in collagen turnover and extracellular matrix as one hallmark of the molecular pathophysiology of diabetes. Additional biomarkers including inflammatory processes and pro-thrombotic alterations were observed. Conclusions/Significance These findings, based on the largest proteomic study performed to date on subjects with DM, validate the previously described biomarkers for DM, and pinpoint differences in the urinary proteome of T1D and T2D, indicating significant differences in extracellular matrix remodeling. PMID:20927192

Droplet Array-Based 3D Coculture System for High-Throughput Tumor Angiogenesis Assay.

PubMed

Du, Xiaohui; Li, Wanming; Du, Guansheng; Cho, Hansang; Yu, Min; Fang, Qun; Lee, Luke P; Fang, Jin

2018-03-06

Angiogenesis is critical for tumor progression and metastasis, and it progresses through orchestral multicellular interactions. Thus, there is urgent demand for high-throughput tumor angiogenesis assays for concurrent examination of multiple factors. For investigating tumor angiogenesis, we developed a microfluidic droplet array-based cell-coculture system comprising a two-layer polydimethylsiloxane chip featuring 6 × 9 paired-well arrays and an automated droplet-manipulation device. In each droplet-pair unit, tumor cells were cultured in 3D in one droplet by mixing cell suspensions with Matrigel, and in the other droplet, human umbilical vein endothelial cells (HUVECs) were cultured in 2D. Droplets were fused by a newly developed fusion method, and tumor angiogenesis was assayed by coculturing tumor cells and HUVECs in the fused droplet units. The 3D-cultured tumor cells formed aggregates harboring a hypoxic center-as observed in vivo-and secreted more vascular endothelial growth factor (VEGF) and more strongly induced HUVEC tubule formation than did 2D-cultured tumor cells. Our single array supported 54 assays in parallel. The angiogenic potentials of distinct tumor cells and their differential responses to antiangiogenesis agent, Fingolimod, could be investigated without mutual interference in a single array. Our droplet-based assay is convenient to evaluate multicellular interaction in high throughput in the context of tumor sprouting angiogenesis, and we envision that the assay can be extensively implementable for studying other cell-cell interactions.

Early Prediction of Lupus Nephritis Using Advanced Proteomics

DTIC Science & Technology

2011-06-01

spectroscopy-based metabolomic profiling , and apolipoprotein D, lipocalin-like prostaglandin D synthetase, hemopexin, ceruloplasmin, -1-B glycoprotein and...will be confirmed and enhanced using NMR- and MS-based metabonomics , by Dr. Michael Kennedy, Miami University. Changes in proteomic profiles will be...based metabolomic profiling , and apolipoprotein D, lipocalin-like prostaglandin D synthetase, hemopexin, ceruloplasmin, -1-B glycoprotein and

Low-molecular-weight color pI markers to monitor on-line the peptide focusing process in OFFGEL fractionation.

PubMed

Michelland, Sylvie; Bourgoin-Voillard, Sandrine; Cunin, Valérie; Tollance, Axel; Bertolino, Pascal; Slais, Karel; Seve, Michel

2017-08-01

High-throughput mass spectrometry-based proteomic analysis requires peptide fractionation to simplify complex biological samples and increase proteome coverage. OFFGEL fractionation technology became a common method to separate peptides or proteins using isoelectric focusing in an immobilized pH gradient. However, the OFFGEL focusing process may be further optimized and controlled in terms of separation time and pI resolution. Here we evaluated OFFGEL technology to separate peptides from different samples in the presence of low-molecular-weight (LMW) color pI markers to visualize the focusing process. LMW color pI markers covering a large pH range were added to the peptide mixture before OFFGEL fractionation using a 24-wells device encompassing the pH range 3-10. We also explored the impact of LMW color pI markers on peptide fractionation labeled previously for iTRAQ. Then, fractionated peptides were separated by RP_HPLC prior to MS analysis using MALDI-TOF/TOF mass spectrometry in MS and MS/MS modes. Here we report the performance of the peptide focusing process in the presence of LMW color pI markers as on-line trackers during the OFFGEL process and the possibility to use them as pI controls for peptide focusing. This method improves the workflow for peptide fractionation in a bottom-up proteomic approach with or without iTRAQ labeling. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Microfluidic liquid chromatography system for proteomic applications and biomarker screening.

PubMed

Lazar, Iulia M; Trisiripisal, Phichet; Sarvaiya, Hetal A

2006-08-01

A microfluidic liquid chromatography (LC) system for proteomic investigations that integrates all the necessary components for stand-alone operation, i.e., pump, valve, separation column, and electrospray interface, is described in this paper. The overall size of the LC device is small enough to enable the integration of two fully functional separation systems on a 3 in. x 1 in. glass microchip. A multichannel architecture that uses electroosmotic pumping principles provides the necessary functionality for eluent propulsion and sample valving. The flow rates generated within these chips are fully consistent with the requirements of nano-LC platforms that are routinely used in proteomic applications. The microfluidic device was evaluated for the analysis of a protein digest obtained from the MCF7 breast cancer cell line. The cytosolic protein extract was processed according to a shotgun protocol, and after tryptic digestion and prefractionation using strong cation exchange chromatography (SCX), selected sample subfractions were analyzed with conventional and microfluidic LC platforms. Using similar experimental conditions, the performance of the microchip LC was comparable to that obtained with benchtop instrumentation, providing an overlap of 75% in proteins that were identified by more than two unique peptides. The microfluidic LC analysis of a protein-rich SCX fraction enabled the confident identification of 77 proteins by using conventional data filtering parameters, of 39 proteins with p < 0.001, and of 5 proteins that are known to be cancer-specific biomarkers, demonstrating thus the potential applicability of these chips for future high-throughput biomarker screening applications.

Searching for microbial protein over-expression in a complex matrix using automated high throughput MS-based proteomics tools.

PubMed

Akeroyd, Michiel; Olsthoorn, Maurien; Gerritsma, Jort; Gutker-Vermaas, Diana; Ekkelkamp, Laurens; van Rij, Tjeerd; Klaassen, Paul; Plugge, Wim; Smit, Ed; Strupat, Kerstin; Wenzel, Thibaut; van Tilborg, Marcel; van der Hoeven, Rob

2013-03-10

In the discovery of new enzymes genomic and cDNA expression libraries containing thousands of differential clones are generated to obtain biodiversity. These libraries need to be screened for the activity of interest. Removing so-called empty and redundant clones significantly reduces the size of these expression libraries and therefore speeds up new enzyme discovery. Here, we present a sensitive, generic workflow for high throughput screening of successful microbial protein over-expression in microtiter plates containing a complex matrix based on mass spectrometry techniques. MALDI-LTQ-Orbitrap screening followed by principal component analysis and peptide mass fingerprinting was developed to obtain a throughput of ∼12,000 samples per week. Alternatively, a UHPLC-MS(2) approach including MS(2) protein identification was developed for microorganisms with a complex protein secretome with a throughput of ∼2000 samples per week. TCA-induced protein precipitation enhanced by addition of bovine serum albumin is used for protein purification prior to MS detection. We show that this generic workflow can effectively reduce large expression libraries from fungi and bacteria to their minimal size by detection of successful protein over-expression using MS. Copyright © 2012 Elsevier B.V. All rights reserved.

A Comparative Quantitative Proteomic Study Identifies New Proteins Relevant for Sulfur Oxidation in the Purple Sulfur Bacterium Allochromatium vinosum

PubMed Central

Weissgerber, Thomas; Sylvester, Marc; Kröninger, Lena

2014-01-01

In the present study, we compared the proteome response of Allochromatium vinosum when growing photoautotrophically in the presence of sulfide, thiosulfate, and elemental sulfur with the proteome response when the organism was growing photoheterotrophically on malate. Applying tandem mass tag analysis as well as two-dimensional (2D) PAGE, we detected 1,955 of the 3,302 predicted proteins by identification of at least two peptides (59.2%) and quantified 1,848 of the identified proteins. Altered relative protein amounts (≥1.5-fold) were observed for 385 proteins, corresponding to 20.8% of the quantified A. vinosum proteome. A significant number of the proteins exhibiting strongly enhanced relative protein levels in the presence of reduced sulfur compounds are well documented essential players during oxidative sulfur metabolism, e.g., the dissimilatory sulfite reductase DsrAB. Changes in protein levels generally matched those observed for the respective relative mRNA levels in a previous study and allowed identification of new genes/proteins participating in oxidative sulfur metabolism. One gene cluster (hyd; Alvin_2036-Alvin_2040) and one hypothetical protein (Alvin_2107) exhibiting strong responses on both the transcriptome and proteome levels were chosen for gene inactivation and phenotypic analyses of the respective mutant strains, which verified the importance of the so-called Isp hydrogenase supercomplex for efficient oxidation of sulfide and a crucial role of Alvin_2107 for the oxidation of sulfur stored in sulfur globules to sulfite. In addition, we analyzed the sulfur globule proteome and identified a new sulfur globule protein (SgpD; Alvin_2515). PMID:24487535

DOE Office of Scientific and Technical Information (OSTI.GOV)

Denef, Vincent; Shah, Manesh B; Verberkmoes, Nathan C

The recent surge in microbial genomic sequencing, combined with the development of high-throughput liquid chromatography-mass-spectrometry-based (LC/LC-MS/MS) proteomics, has raised the question of the extent to which genomic information of one strain or environmental sample can be used to profile proteomes of related strains or samples. Even with decreasing sequencing costs, it remains impractical to obtain genomic sequence for every strain or sample analyzed. Here, we evaluate how shotgun proteomics is affected by amino acid divergence between the sample and the genomic database using a probability-based model and a random mutation simulation model constrained by experimental data. To assess the effectsmore » of nonrandom distribution of mutations, we also evaluated identification levels using in silico peptide data from sequenced isolates with average amino acid identities (AAI) varying between 76 and 98%. We compared the predictions to experimental protein identification levels for a sample that was evaluated using a database that included genomic information for the dominant organism and for a closely related variant (95% AAI). The range of models set the boundaries at which half of the proteins in a proteomic experiment can be identified to be 77-92% AAI between orthologs in the sample and database. Consistent with this prediction, experimental data indicated loss of half the identifiable proteins at 90% AAI. Additional analysis indicated a 6.4% reduction of the initial protein coverage per 1% amino acid divergence and total identification loss at 86% AAI. Consequently, shotgun proteomics is capable of cross-strain identifications but avoids most crossspecies false positives.« less

A draft map of the human ovarian proteome for tissue engineering and clinical applications.

PubMed

Ouni, Emna; Vertommen, Didier; Chiti, Maria Costanza; Dolmans, Marie-Madeleine; Amorim, Christiani Andrade

2018-02-23

Fertility preservation research in women today is increasingly taking advantage of bioengineering techniques to develop new biomimetic materials and solutions to safeguard ovarian cell function and microenvironment in vitro and in vivo. However, available data on the human ovary are limited and fundamental differences between animal models and humans are hampering researchers in their quest for more extensive knowledge of human ovarian physiology and key reproductive proteins that need to be preserved. We therefore turned to multi-dimensional label-free mass spectrometry to analyze human ovarian cortex, as it is a high-throughput and conclusive technique providing information on the proteomic composition of complex tissues like the ovary. In-depth proteomic profiling through two-dimensional liquid chromatography-mass spectrometry, western blot, histological and immunohistochemical analyses, and data mining helped us to confidently identify 1,508 proteins. Moreover, our method allowed us to chart the most complete representation so far of the ovarian matrisome, defined as the ensemble of extracellular matrix proteins and associated factors, including more than 80 proteins. In conclusion, this study will provide a better understanding of ovarian proteomics, with a detailed characterization of the ovarian follicle microenvironment, in order to enable bioengineers to create biomimetic scaffolds for transplantation and three-dimensional in vitro culture. By publishing our proteomic data, we also hope to contribute to accelerating biomedical research into ovarian health and disease in general. Published under license by The American Society for Biochemistry and Molecular Biology, Inc.

A flexible statistical model for alignment of label-free proteomics data – incorporating ion mobility and product ion information

PubMed Central

2013-01-01

Background The goal of many proteomics experiments is to determine the abundance of proteins in biological samples, and the variation thereof in various physiological conditions. High-throughput quantitative proteomics, specifically label-free LC-MS/MS, allows rapid measurement of thousands of proteins, enabling large-scale studies of various biological systems. Prior to analyzing these information-rich datasets, raw data must undergo several computational processing steps. We present a method to address one of the essential steps in proteomics data processing - the matching of peptide measurements across samples. Results We describe a novel method for label-free proteomics data alignment with the ability to incorporate previously unused aspects of the data, particularly ion mobility drift times and product ion information. We compare the results of our alignment method to PEPPeR and OpenMS, and compare alignment accuracy achieved by different versions of our method utilizing various data characteristics. Our method results in increased match recall rates and similar or improved mismatch rates compared to PEPPeR and OpenMS feature-based alignment. We also show that the inclusion of drift time and product ion information results in higher recall rates and more confident matches, without increases in error rates. Conclusions Based on the results presented here, we argue that the incorporation of ion mobility drift time and product ion information are worthy pursuits. Alignment methods should be flexible enough to utilize all available data, particularly with recent advancements in experimental separation methods. PMID:24341404

A flexible statistical model for alignment of label-free proteomics data--incorporating ion mobility and product ion information.

PubMed

Benjamin, Ashlee M; Thompson, J Will; Soderblom, Erik J; Geromanos, Scott J; Henao, Ricardo; Kraus, Virginia B; Moseley, M Arthur; Lucas, Joseph E

2013-12-16

The goal of many proteomics experiments is to determine the abundance of proteins in biological samples, and the variation thereof in various physiological conditions. High-throughput quantitative proteomics, specifically label-free LC-MS/MS, allows rapid measurement of thousands of proteins, enabling large-scale studies of various biological systems. Prior to analyzing these information-rich datasets, raw data must undergo several computational processing steps. We present a method to address one of the essential steps in proteomics data processing--the matching of peptide measurements across samples. We describe a novel method for label-free proteomics data alignment with the ability to incorporate previously unused aspects of the data, particularly ion mobility drift times and product ion information. We compare the results of our alignment method to PEPPeR and OpenMS, and compare alignment accuracy achieved by different versions of our method utilizing various data characteristics. Our method results in increased match recall rates and similar or improved mismatch rates compared to PEPPeR and OpenMS feature-based alignment. We also show that the inclusion of drift time and product ion information results in higher recall rates and more confident matches, without increases in error rates. Based on the results presented here, we argue that the incorporation of ion mobility drift time and product ion information are worthy pursuits. Alignment methods should be flexible enough to utilize all available data, particularly with recent advancements in experimental separation methods.

Fabrication of Gold-coated 3-D Woodpile Structures for Mid-IR Thermal Emitters

NASA Astrophysics Data System (ADS)

Li, Shengkai; Moridani, Amir; Kothari, Rohit; Lee, Jae-Hwang; Watkins, James

3-D metallic woodpile nanostructures possess enhancements in thermal radiation that are both wavelength and polarization specific and are promising for thermal-optical devices for various applications including thermal photovoltaics, self-cooling devices, and chemical and bio-sensors. However, current fabrication techniques for such structures are limited by slow speed, small area capability, the need for expensive facilities and, in general, are not suitable for high-throughput mass production. Here we demonstrate a new strategy for the fabrication of 3D metallic woodpile structures. Well-defined TiO2 woodpile structures were fabricated using a layer-by-layer nanoimprint method using TiO2 nanoparticle ink dispersions. The TiO2 woodpile was then coated with a high purity, conformal gold film via reactive deposition in supercritical carbon dioxide. The final gold-coated woodpile structures exhibit strong spectral and polarization specific thermal emission enhancements. The fabrication method demonstrated here is promising for high-throughput, low-cost preparation of 3D metallic woodpile structures and other 3D nanostructures. Center for Hierarchical Manufacturing, NSF.

Proteomic analysis reveals strong mitochondrial involvement in cytoplasmic male sterility of pepper (Capsicum annuum L.).

PubMed

Guo, Jinju; Wang, Peng; Cheng, Qing; Sun, Limin; Wang, Hongyu; Wang, Yutong; Kao, Lina; Li, Yanan; Qiu, Tuoyu; Yang, Wencai; Shen, Huolin

2017-09-25

Although cytoplasmic male sterility (CMS) is widely used for developing pepper hybrids, its molecular mechanism remains unclear. In this study, we used a high-throughput proteomics method called label-free to compare protein abundance across a pepper CMS line (A-line) and its isogenic maintainer line (B-line). Data are available via ProteomeXchange with identifier PXD006104. Approximately 324 differentially abundant protein species were identified and quantified; among which, 47 were up-accumulated and 140 were down-accumulated in the A-line; additionally, 75 and 62 protein species were specifically accumulated in the A-line and B-line, respectively. Protein species involved in pollen exine formation, pyruvate metabolic processes, the tricarboxylic acid cycle, the mitochondrial electron transport chain, and oxidative stress response were observed to be differentially accumulated between A-line and B-line, suggesting their potential roles in the regulation of pepper pollen abortion. Based on our data, we proposed a potential regulatory network for pepper CMS that unifies these processes. Artificial emasculation is a major obstacle in pepper hybrid breeding for its high labor cost and poor seed purity. While the use of cytoplasmic male sterility (CMS) in hybrid system is seriously frustrated because a long time is needed to cultivate male sterility line and its isogenic restore line. Transgenic technology is an effective and rapid method to obtain male sterility lines and its widely application has very important significance in speeding up breeding process in pepper. Although numerous studies have been conducted to select the genes related to male sterility, the molecular mechanism of cytoplasmic male sterility in pepper remains unknown. In this study, we used the high-throughput proteomic method called "label-free", coupled with liquid chromatography-quadrupole mass spectrometry (LC-MS/MS), to perform a novel comparison of expression profiles in a CMS pepper line and its maintainer line. Based on our results, we proposed a potential regulated protein network involved in pollen development as a novel mechanism of pepper CMS. Copyright © 2017. Published by Elsevier B.V.

Quantitative Proteomics of Sleep-Deprived Mouse Brains Reveals Global Changes in Mitochondrial Proteins

PubMed Central

Li, Tie-Mei; Zhang, Ju-en; Lin, Rui; Chen, She; Luo, Minmin; Dong, Meng-Qiu

2016-01-01

Sleep is a ubiquitous, tightly regulated, and evolutionarily conserved behavior observed in almost all animals. Prolonged sleep deprivation can be fatal, indicating that sleep is a physiological necessity. However, little is known about its core function. To gain insight into this mystery, we used advanced quantitative proteomics technology to survey the global changes in brain protein abundance. Aiming to gain a comprehensive profile, our proteomics workflow included filter-aided sample preparation (FASP), which increased the coverage of membrane proteins; tandem mass tag (TMT) labeling, for relative quantitation; and high resolution, high mass accuracy, high throughput mass spectrometry (MS). In total, we obtained the relative abundance ratios of 9888 proteins encoded by 6070 genes. Interestingly, we observed significant enrichment for mitochondrial proteins among the differentially expressed proteins. This finding suggests that sleep deprivation strongly affects signaling pathways that govern either energy metabolism or responses to mitochondrial stress. Additionally, the differentially-expressed proteins are enriched in pathways implicated in age-dependent neurodegenerative diseases, including Parkinson’s, Huntington’s, and Alzheimer’s, hinting at possible connections between sleep loss, mitochondrial stress, and neurodegeneration. PMID:27684481

Elucidating structural and molecular mechanisms of β-arrestin-biased agonism at GPCRs via MS-based proteomics.

PubMed

Xiao, Kunhong; Sun, Jinpeng

2018-01-01

The discovery of β-arrestin-dependent GPCR signaling has led to an exciting new field in GPCR pharmacology: to develop "biased agonists" that can selectively target a specific downstream signaling pathway that elicits beneficial therapeutic effects without activating other pathways that elicit negative side effects. This new trend in GPCR drug discovery requires us to understand the structural and molecular mechanisms of β-arrestin-biased agonism, which largely remain unclear. We have used cutting-edge mass spectrometry (MS)-based proteomics, combined with systems, chemical and structural biology to study protein function, macromolecular interaction, protein expression and posttranslational modifications in the β-arrestin-dependent GPCR signaling. These high-throughput proteomic studies have provided a systems view of β-arrestin-biased agonism from several perspectives: distinct receptor phosphorylation barcode, multiple receptor conformations, distinct β-arrestin conformations, and ligand-specific signaling. The information obtained from these studies offers new insights into the molecular basis of GPCR regulation by β-arrestin and provides a potential platform for developing novel therapeutic interventions through GPCRs. Copyright © 2017 Elsevier Inc. All rights reserved.

Proteomics-based compositional analysis of complex cellulase-hemicellulase mixtures.

PubMed

Chundawat, Shishir P S; Lipton, Mary S; Purvine, Samuel O; Uppugundla, Nirmal; Gao, Dahai; Balan, Venkatesh; Dale, Bruce E

2011-10-07

Efficient deconstruction of cellulosic biomass to fermentable sugars for fuel and chemical production is accomplished by a complex mixture of cellulases, hemicellulases, and accessory enzymes (e.g., >50 extracellular proteins). Cellulolytic enzyme mixtures, produced industrially mostly using fungi like Trichoderma reesei, are poorly characterized in terms of their protein composition and its correlation to hydrolytic activity on cellulosic biomass. The secretomes of commercial glycosyl hydrolase-producing microbes was explored using a proteomics approach with high-throughput quantification using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Here, we show that proteomics-based spectral counting approach is a reasonably accurate and rapid analytical technique that can be used to determine protein composition of complex glycosyl hydrolase mixtures that also correlates with the specific activity of individual enzymes present within the mixture. For example, a strong linear correlation was seen between Avicelase activity and total cellobiohydrolase content. Reliable, quantitative and cheaper analytical methods that provide insight into the cellulosic biomass degrading fungal and bacterial secretomes would lead to further improvements toward commercialization of plant biomass-derived fuels and chemicals.

A Researcher's Guide to Mass Spectrometry-Based Proteomics

PubMed Central

Savaryn, John P.; Toby, Timothy K.; Kelleher, Neil L.

2016-01-01

Mass spectrometry (MS) is widely recognized as a powerful analytical tool for molecular research. MS is used by researchers around the globe to identify, quantify, and characterize biomolecules like proteins from any number of biological conditions or sample types. As instrumentation has advanced, and with the coupling of liquid chromatography (LC) for high-throughput LC-MS/MS, a proteomics experiment measuring hundreds to thousands of proteins/protein groups is now commonplace. While expert practitioners who best understand the operation of LC-MS systems tend to have strong backgrounds in physics and engineering, consumers of proteomics data and technology are not exposed to the physio-chemical principles underlying the information they seek. Since articles and reviews tend not to focus on bridging this divide, our goal here is to span this gap and translate MS ion physics into language intuitive to the general reader active in basic or applied biomedical research. Here, we visually describe what happens to ions as they enter and move around inside a mass spectrometer. We describe basic MS principles, including electric current, ion optics, ion traps, quadrupole mass filters, and Orbitrap FT-analyzers. PMID:27553853

Comparative proteomics reveals recruitment patterns of some protein families in the venoms of Cnidaria.

PubMed

Jaimes-Becerra, Adrian; Chung, Ray; Morandini, André C; Weston, Andrew J; Padilla, Gabriel; Gacesa, Ranko; Ward, Malcolm; Long, Paul F; Marques, Antonio C

2017-10-01

Cnidarians are probably the oldest group of animals to be venomous, yet our current picture of cnidarian venom evolution is highly imbalanced due to limited taxon sampling. High-throughput tandem mass spectrometry was used to determine venom composition of the scyphozoan Chrysaora lactea and two cubozoans Tamoya haplonema and Chiropsalmus quadrumanus. Protein recruitment patterns were then compared against 5 other cnidarian venom proteomes taken from the literature. A total of 28 putative toxin protein families were identified, many for the first time in Cnidaria. Character mapping analysis revealed that 17 toxin protein families with predominantly cytolytic biological activities were likely recruited into the cnidarian venom proteome before the lineage split between Anthozoa and Medusozoa. Thereafter, venoms of Medusozoa and Anthozoa differed during subsequent divergence of cnidarian classes. Recruitment and loss of toxin protein families did not correlate with accepted phylogenetic patterns of Cnidaria. Selective pressures that drive toxin diversification independent of taxonomic positioning have yet to be identified in Cnidaria and now warrant experimental consideration. Copyright © 2017 Elsevier Ltd. All rights reserved.

Unbiased Protein Association Study on the Public Human Proteome Reveals Biological Connections between Co-Occurring Protein Pairs

PubMed Central

2017-01-01

Mass-spectrometry-based, high-throughput proteomics experiments produce large amounts of data. While typically acquired to answer specific biological questions, these data can also be reused in orthogonal ways to reveal new biological knowledge. We here present a novel method for such orthogonal data reuse of public proteomics data. Our method elucidates biological relationships between proteins based on the co-occurrence of these proteins across human experiments in the PRIDE database. The majority of the significantly co-occurring protein pairs that were detected by our method have been successfully mapped to existing biological knowledge. The validity of our novel method is substantiated by the extremely few pairs that can be mapped to existing knowledge based on random associations between the same set of proteins. Moreover, using literature searches and the STRING database, we were able to derive meaningful biological associations for unannotated protein pairs that were detected using our method, further illustrating that as-yet unknown associations present highly interesting targets for follow-up analysis. PMID:28480704

3D Bioprinting for Engineering Complex Tissues

PubMed Central

Mandrycky, Christian; Wang, Zongjie; Kim, Keekyoung; Kim, Deok-Ho

2016-01-01

Bioprinting is a 3D fabrication technology used to precisely dispense cell-laden biomaterials for the construction of complex 3D functional living tissues or artificial organs. While still in its early stages, bioprinting strategies have demonstrated their potential use in regenerative medicine to generate a variety of transplantable tissues, including skin, cartilage, and bone. However, current bioprinting approaches still have technical challenges in terms of high-resolution cell deposition, controlled cell distributions, vascularization, and innervation within complex 3D tissues. While no one-size-fits-all approach to bioprinting has emerged, it remains an on-demand, versatile fabrication technique that may address the growing organ shortage as well as provide a high-throughput method for cell patterning at the micrometer scale for broad biomedical engineering applications. In this review, we introduce the basic principles, materials, integration strategies and applications of bioprinting. We also discuss the recent developments, current challenges and future prospects of 3D bioprinting for engineering complex tissues. Combined with recent advances in human pluripotent stem cell technologies, 3D-bioprinted tissue models could serve as an enabling platform for high-throughput predictive drug screening and more effective regenerative therapies. PMID:26724184

3D bioprinting for engineering complex tissues.

PubMed

Mandrycky, Christian; Wang, Zongjie; Kim, Keekyoung; Kim, Deok-Ho

2016-01-01

Bioprinting is a 3D fabrication technology used to precisely dispense cell-laden biomaterials for the construction of complex 3D functional living tissues or artificial organs. While still in its early stages, bioprinting strategies have demonstrated their potential use in regenerative medicine to generate a variety of transplantable tissues, including skin, cartilage, and bone. However, current bioprinting approaches still have technical challenges in terms of high-resolution cell deposition, controlled cell distributions, vascularization, and innervation within complex 3D tissues. While no one-size-fits-all approach to bioprinting has emerged, it remains an on-demand, versatile fabrication technique that may address the growing organ shortage as well as provide a high-throughput method for cell patterning at the micrometer scale for broad biomedical engineering applications. In this review, we introduce the basic principles, materials, integration strategies and applications of bioprinting. We also discuss the recent developments, current challenges and future prospects of 3D bioprinting for engineering complex tissues. Combined with recent advances in human pluripotent stem cell technologies, 3D-bioprinted tissue models could serve as an enabling platform for high-throughput predictive drug screening and more effective regenerative therapies. Copyright © 2015 Elsevier Inc. All rights reserved.

Comparative proteomic expression profile in all-trans retinoic acid differentiated neuroblastoma cell line.

PubMed

Cimmino, Flora; Spano, Daniela; Capasso, Mario; Zambrano, Nicola; Russo, Roberta; Zollo, Massimo; Iolascon, Achille

2007-07-01

Neuroblastoma (NB) is an infant tumor which frequently differentiates into neurons. We used two-dimensional differential in-gel electrophoresis (2D-DIGE) to analyze the cytosolic and nuclear protein expression patterns of LAN-5 cells following neuronal differentiating agent all-trans-retinoic acid treatment. We identified several candidate proteins, from which G beta2 and Prefoldin 3 may have a role on NB development. These results strength the use of proteomics to discover new putative protein targets in cancer.

Proteome-wide analysis and diel proteomic profiling of the cyanobacterium Arthrospira platensis PCC 8005.

PubMed

Matallana-Surget, Sabine; Derock, Jérémy; Leroy, Baptiste; Badri, Hanène; Deschoenmaeker, Frédéric; Wattiez, Ruddy

2014-01-01

The filamentous cyanobacterium Arthrospira platensis has a long history of use as a food supply and it has been used by the European Space Agency in the MELiSSA project, an artificial microecosystem which supports life during long-term manned space missions. This study assesses progress in the field of cyanobacterial shotgun proteomics and light/dark diurnal cycles by focusing on Arthrospira platensis. Several fractionation workflows including gel-free and gel-based protein/peptide fractionation procedures were used and combined with LC-MS/MS analysis, enabling the overall identification of 1306 proteins, which represents 21% coverage of the theoretical proteome. A total of 30 proteins were found to be significantly differentially regulated under light/dark growth transition. Interestingly, most of the proteins showing differential abundance were related to photosynthesis, the Calvin cycle and translation processes. A novel aspect and major achievement of this work is the successful improvement of the cyanobacterial proteome coverage using a 3D LC-MS/MS approach, based on an immobilized metal affinity chromatography, a suitable tool that enabled us to eliminate the most abundant protein, the allophycocyanin. We also demonstrated that cell growth follows a light/dark cycle in A. platensis. This preliminary proteomic study has highlighted new characteristics of the Arthrospira platensis proteome in terms of diurnal regulation.

Proteome-Wide Analysis and Diel Proteomic Profiling of the Cyanobacterium Arthrospira platensis PCC 8005

PubMed Central

Matallana-Surget, Sabine; Derock, Jérémy; Leroy, Baptiste; Badri, Hanène; Deschoenmaeker, Frédéric; Wattiez, Ruddy

2014-01-01

The filamentous cyanobacterium Arthrospira platensis has a long history of use as a food supply and it has been used by the European Space Agency in the MELiSSA project, an artificial microecosystem which supports life during long-term manned space missions. This study assesses progress in the field of cyanobacterial shotgun proteomics and light/dark diurnal cycles by focusing on Arthrospira platensis. Several fractionation workflows including gel-free and gel-based protein/peptide fractionation procedures were used and combined with LC-MS/MS analysis, enabling the overall identification of 1306 proteins, which represents 21% coverage of the theoretical proteome. A total of 30 proteins were found to be significantly differentially regulated under light/dark growth transition. Interestingly, most of the proteins showing differential abundance were related to photosynthesis, the Calvin cycle and translation processes. A novel aspect and major achievement of this work is the successful improvement of the cyanobacterial proteome coverage using a 3D LC-MS/MS approach, based on an immobilized metal affinity chromatography, a suitable tool that enabled us to eliminate the most abundant protein, the allophycocyanin. We also demonstrated that cell growth follows a light/dark cycle in A. platensis. This preliminary proteomic study has highlighted new characteristics of the Arthrospira platensis proteome in terms of diurnal regulation. PMID:24914774

Multi-component immunoaffinity subtraction chromatography: an innovative step towards a comprehensive survey of the human plasma proteome.

PubMed

Pieper, Rembert; Su, Qin; Gatlin, Christine L; Huang, Shih-Ting; Anderson, N Leigh; Steiner, Sandra

2003-04-01

In order to discover novel protein markers indicative of disease processes or drug effects, the proteomics technology platform most commonly used consists of high resolution protein separation by two-dimensional electrophoresis (2-DE), mass spectrometric identification of proteins from stained gel spots and a bioinformatic data analysis process supported by statistics. This approach has been more successful in profiling proteins and their disease- or treatment-related quantitative changes in tissue homogenates than in plasma samples. Plasma protein display and quantitation suffer from several disadvantages: very high abundance of a few proteins; high heterogeneity of many proteins resulting in long charge trains; crowding of 2-DE separated protein spots in the molecular mass range between 45-80 kD and in the isoelectric point range between 4.5 and 6. Therefore, proteomic technologies are needed that address these problems and particularly allow accurate quantitation of a larger number of less abundant proteins in plasma and other body fluids. The immunoaffinity-based protein subtraction chromatography (IASC) described here removes multiple proteins present in plasma and serum in high concentrations effectively and reproducibly. Applying IASC as an upfront plasma sample preparation process for 2-DE, the protein spot pattern observed in gels changes dramatically and at least 350 additional lower abundance proteins are visualized. Affinity-purified polyclonal antibodies (pAbs) are the immunoaffinity reagents used to specifically remove the abundant proteins such as albumin, immunoglobulin G, immunoglobulin A, transferrin, haptoglobin, alpha-1-antitrypsin, hemopexin, transthyretin, alpha-2-HS glycoprotein, alpha-1-acid glycoprotein, alpha-2-macroglobulin and fibrinogen from human plasma samples. To render the immunoaffinity subtraction procedure recyclable, the pAbs are immobilized and cross-linked on chromatographic matrices. Antibody-coupled matrices specific for one protein each can be pooled to form mixed-bed IASC columns. We show that up to ten affinity-bound plasma proteins with similar solubility characteristics are eluted from a mixed-bed column in one step. This facilitates automated chromatographic processing of plasma samples in high throughput, which is desirable in proteomic disease marker discovery projects.

High Throughput System for Plant Height and Hyperspectral Measurement

NASA Astrophysics Data System (ADS)

Zhao, H.; Xu, L.; Jiang, H.; Shi, S.; Chen, D.

2018-04-01

Hyperspectral and three-dimensional measurement can obtain the intrinsic physicochemical properties and external geometrical characteristics of objects, respectively. Currently, a variety of sensors are integrated into a system to collect spectral and morphological information in agriculture. However, previous experiments were usually performed with several commercial devices on a single platform. Inadequate registration and synchronization among instruments often resulted in mismatch between spectral and 3D information of the same target. And narrow field of view (FOV) extends the working hours in farms. Therefore, we propose a high throughput prototype that combines stereo vision and grating dispersion to simultaneously acquire hyperspectral and 3D information.

Rice proteome database: a step toward functional analysis of the rice genome.

PubMed

Komatsu, Setsuko

2005-09-01

The technique of proteome analysis using two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) has the power to monitor global changes that occur in the protein complement of tissues and subcellular compartments. In this study, the proteins of rice were cataloged, a rice proteome database was constructed, and a functional characterization of some of the identified proteins was undertaken. Proteins extracted from various tissues and subcellular compartments in rice were separated by 2D-PAGE and an image analyzer was used to construct a display of the proteins. The Rice Proteome Database contains 23 reference maps based on 2D-PAGE of proteins from various rice tissues and subcellular compartments. These reference maps comprise 13129 identified proteins, and the amino acid sequences of 5092 proteins are entered in the database. Major proteins involved in growth or stress responses were identified using the proteome approach. Some of these proteins, including a beta-tubulin, calreticulin, and ribulose-1,5-bisphosphate carboxylase/oxygenase activase in rice, have unexpected functions. The information obtained from the Rice Proteome Database will aid in cloning the genes for and predicting the function of unknown proteins.

High-Throughput Top-Down and Bottom-Up Processes for Forming Single-Nanotube Based Architectures for 3D Electronics

NASA Technical Reports Server (NTRS)

Kaul, Anupama B.; Megerian, Krikor G.; von Allmen, Paul; Kowalczyk, Robert; Baron, Richard

2009-01-01

We have developed manufacturable approaches to form single, vertically aligned carbon nanotubes, where the tubes are centered precisely, and placed within a few hundred nm of 1-1.5 micron deep trenches. These wafer-scale approaches were enabled by chemically amplified resists and inductively coupled Cryo-etchers for forming the 3D nanoscale architectures. The tube growth was performed using dc plasma-enhanced chemical vapor deposition (PECVD), and the materials used for the pre-fabricated 3D architectures were chemically and structurally compatible with the high temperature (700 C) PECVD synthesis of our tubes, in an ammonia and acetylene ambient. Tube characteristics were also engineered to some extent, by adjusting growth parameters, such as Ni catalyst thickness, pressure and plasma power during growth. Such scalable, high throughput top-down fabrication techniques, combined with bottom-up tube synthesis, should accelerate the development of PECVD tubes for applications such as interconnects, nano-electromechanical (NEMS), sensors or 3D electronics in general.

384 hanging drop arrays give excellent Z-factors and allow versatile formation of co-culture spheroids.

PubMed

Hsiao, Amy Y; Tung, Yi-Chung; Qu, Xianggui; Patel, Lalit R; Pienta, Kenneth J; Takayama, Shuichi

2012-05-01

We previously reported the development of a simple, user-friendly, and versatile 384 hanging drop array plate for 3D spheroid culture and the importance of utilizing 3D cellular models in anti-cancer drug sensitivity testing. The 384 hanging drop array plate allows for high-throughput capabilities and offers significant improvements over existing 3D spheroid culture methods. To allow for practical 3D cell-based high-throughput screening and enable broader use of the plate, we characterize the robustness of the 384 hanging drop array plate in terms of assay performance and demonstrate the versatility of the plate. We find that the 384 hanging drop array plate performance is robust in fluorescence- and colorimetric-based assays through Z-factor calculations. Finally, we demonstrate different plate capabilities and applications, including: spheroid transfer and retrieval for Janus spheroid formation, sequential addition of cells for concentric layer patterning of different cell types, and culture of a wide variety of cell types. Copyright © 2011 Wiley Periodicals, Inc.

384 Hanging Drop Arrays Give Excellent Z-factors and Allow Versatile Formation of Co-culture Spheroids

PubMed Central

Hsiao, Amy Y.; Tung, Yi-Chung; Qu, Xianggui; Patel, Lalit R.; Pienta, Kenneth J.; Takayama, Shuichi

2012-01-01

We previously reported the development of a simple, user-friendly, and versatile 384 hanging drop array plate for 3D spheroid culture and the importance of utilizing 3D cellular models in anti-cancer drug sensitivity testing. The 384 hanging drop array plate allows for high-throughput capabilities and offers significant improvements over existing 3D spheroid culture methods. To allow for practical 3D cell-based high-throughput screening and enable broader use of the plate, we characterize the robustness of the 384 hanging drop array plate in terms of assay performance and demonstrate the versatility of the plate. We find that the 384 hanging drop array plate performance is robust in fluorescence- and colorimetric-based assays through z-factor calculations. Finally, we demonstrate different plate capabilities and applications, including: spheroid transfer and retrieval for Janus spheroid formation, sequential addition of cells for concentric layer patterning of different cell types, and culture of a wide variety of cell types. PMID:22161651

MSX-3D: a tool to validate 3D protein models using mass spectrometry.

PubMed

Heymann, Michaël; Paramelle, David; Subra, Gilles; Forest, Eric; Martinez, Jean; Geourjon, Christophe; Deléage, Gilbert

2008-12-01

The technique of chemical cross-linking followed by mass spectrometry has proven to bring valuable information about the protein structure and interactions between proteic subunits. It is an effective and efficient way to experimentally investigate some aspects of a protein structure when NMR and X-ray crystallography data are lacking. We introduce MSX-3D, a tool specifically geared to validate protein models using mass spectrometry. In addition to classical peptides identifications, it allows an interactive 3D visualization of the distance constraints derived from a cross-linking experiment. Freely available at http://proteomics-pbil.ibcp.fr

Development of Biomarkers for Screening Hepatocellular Carcinoma Using Global Data Mining and Multiple Reaction Monitoring

PubMed Central

Yu, Su Jong; Jang, Eun Sun; Yu, Jiyoung; Cho, Geunhee; Yoon, Jung-Hwan; Kim, Youngsoo

2013-01-01

Hepatocellular carcinoma (HCC) is one of the most common and aggressive cancers and is associated with a poor survival rate. Clinically, the level of alpha-fetoprotein (AFP) has been used as a biomarker for the diagnosis of HCC. The discovery of useful biomarkers for HCC, focused solely on the proteome, has been difficult; thus, wide-ranging global data mining of genomic and proteomic databases from previous reports would be valuable in screening biomarker candidates. Further, multiple reaction monitoring (MRM), based on triple quadrupole mass spectrometry, has been effective with regard to high-throughput verification, complementing antibody-based verification pipelines. In this study, global data mining was performed using 5 types of HCC data to screen for candidate biomarker proteins: cDNA microarray, copy number variation, somatic mutation, epigenetic, and quantitative proteomics data. Next, we applied MRM to verify HCC candidate biomarkers in individual serum samples from 3 groups: a healthy control group, patients who have been diagnosed with HCC (Before HCC treatment group), and HCC patients who underwent locoregional therapy (After HCC treatment group). After determining the relative quantities of the candidate proteins by MRM, we compared their expression levels between the 3 groups, identifying 4 potential biomarkers: the actin-binding protein anillin (ANLN), filamin-B (FLNB), complementary C4-A (C4A), and AFP. The combination of 2 markers (ANLN, FLNB) improved the discrimination of the before HCC treatment group from the healthy control group compared with AFP. We conclude that the combination of global data mining and MRM verification enhances the screening and verification of potential HCC biomarkers. This efficacious integrative strategy is applicable to the development of markers for cancer and other diseases. PMID:23717429

Development of biomarkers for screening hepatocellular carcinoma using global data mining and multiple reaction monitoring.

PubMed

Kim, Hyunsoo; Kim, Kyunggon; Yu, Su Jong; Jang, Eun Sun; Yu, Jiyoung; Cho, Geunhee; Yoon, Jung-Hwan; Kim, Youngsoo

2013-01-01

Hepatocellular carcinoma (HCC) is one of the most common and aggressive cancers and is associated with a poor survival rate. Clinically, the level of alpha-fetoprotein (AFP) has been used as a biomarker for the diagnosis of HCC. The discovery of useful biomarkers for HCC, focused solely on the proteome, has been difficult; thus, wide-ranging global data mining of genomic and proteomic databases from previous reports would be valuable in screening biomarker candidates. Further, multiple reaction monitoring (MRM), based on triple quadrupole mass spectrometry, has been effective with regard to high-throughput verification, complementing antibody-based verification pipelines. In this study, global data mining was performed using 5 types of HCC data to screen for candidate biomarker proteins: cDNA microarray, copy number variation, somatic mutation, epigenetic, and quantitative proteomics data. Next, we applied MRM to verify HCC candidate biomarkers in individual serum samples from 3 groups: a healthy control group, patients who have been diagnosed with HCC (Before HCC treatment group), and HCC patients who underwent locoregional therapy (After HCC treatment group). After determining the relative quantities of the candidate proteins by MRM, we compared their expression levels between the 3 groups, identifying 4 potential biomarkers: the actin-binding protein anillin (ANLN), filamin-B (FLNB), complementary C4-A (C4A), and AFP. The combination of 2 markers (ANLN, FLNB) improved the discrimination of the before HCC treatment group from the healthy control group compared with AFP. We conclude that the combination of global data mining and MRM verification enhances the screening and verification of potential HCC biomarkers. This efficacious integrative strategy is applicable to the development of markers for cancer and other diseases.

Analysis of aromatic catabolic pathways in Pseudomonas putida KT 2440 using a combined proteomic approach: 2-DE/MS and cleavable isotope-coded affinity tag analysis.

PubMed

Kim, Young Hwan; Cho, Kun; Yun, Sung-Ho; Kim, Jin Young; Kwon, Kyung-Hoon; Yoo, Jong Shin; Kim, Seung Il

2006-02-01

Proteomic analysis of Pseudomonas putida KT2440 cultured in monocyclic aromatic compounds was performed using 2-DE/MS and cleavable isotope-coded affinity tag (ICAT) to determine whether proteins involved in aromatic compound degradation pathways were altered as predicted by genomic analysis (Jiménez et al., Environ Microbiol. 2002, 4, 824-841). Eighty unique proteins were identified by 2-DE/MS or MS/MS analysis from P. putida KT2440 cultured in the presence of six different organic compounds. Benzoate dioxygenase (BenA, BenD) and catechol 1,2-dioxygenase (CatA) were induced by benzoate. Protocatechuate 3,4-dixoygenase (PcaGH) was induced by p-hydroxybenzoate and vanilline. beta-Ketoadipyl CoA thiolase (PcaF) and 3-oxoadipate enol-lactone hydrolase (PcaD) were induced by benzoate, p-hydroxybenzoate and vanilline, suggesting that benzoate, p-hydroxybenzoate and vanilline were degraded by different dioxygenases and then converged in the same beta-ketoadipate degradation pathway. An additional 110 proteins, including 19 proteins from 2-DE analysis, were identified by cleavable ICAT analysis for benzoate-induced proteomes, which complemented the 2-DE results. Phenylethylamine exposure induced beta-ketoacyl CoA thiolase (PhaD) and ring-opening enzyme (PhaL), both enzymes of the phenylacetate (pha) biodegradation pathway. Phenylalanine induced 4-hydroxyphenyl-pyruvate dioxygenase (Hpd) and homogentisate 1,2-dioxygenase (HmgA), key enzymes in the homogentisate degradation pathway. Alkyl hydroperoxide reductase (AphC) was induced under all aromatic compounds conditions. These results suggest that proteome analysis complements and supports predictive information obtained by genomic sequence analysis.

mz5: space- and time-efficient storage of mass spectrometry data sets.

PubMed

Wilhelm, Mathias; Kirchner, Marc; Steen, Judith A J; Steen, Hanno

2012-01-01

Across a host of MS-driven-omics fields, researchers witness the acquisition of ever increasing amounts of high throughput MS data and face the need for their compact yet efficiently accessible storage. Addressing the need for an open data exchange format, the Proteomics Standards Initiative and the Seattle Proteome Center at the Institute for Systems Biology independently developed the mzData and mzXML formats, respectively. In a subsequent joint effort, they defined an ontology and associated controlled vocabulary that specifies the contents of MS data files, implemented as the newer mzML format. All three formats are based on XML and are thus not particularly efficient in either storage space requirements or read/write speed. This contribution introduces mz5, a complete reimplementation of the mzML ontology that is based on the efficient, industrial strength storage backend HDF5. Compared with the current mzML standard, this strategy yields an average file size reduction to ∼54% and increases linear read and write speeds ∼3-4-fold. The format is implemented as part of the ProteoWizard project and is available under a permissive Apache license. Additional information and download links are available from http://software.steenlab.org/mz5.

MinOmics, an Integrative and Immersive Tool for Multi-Omics Analysis.

PubMed

Maes, Alexandre; Martinez, Xavier; Druart, Karen; Laurent, Benoist; Guégan, Sean; Marchand, Christophe H; Lemaire, Stéphane D; Baaden, Marc

2018-06-21

Proteomic and transcriptomic technologies resulted in massive biological datasets, their interpretation requiring sophisticated computational strategies. Efficient and intuitive real-time analysis remains challenging. We use proteomic data on 1417 proteins of the green microalga Chlamydomonas reinhardtii to investigate physicochemical parameters governing selectivity of three cysteine-based redox post translational modifications (PTM): glutathionylation (SSG), nitrosylation (SNO) and disulphide bonds (SS) reduced by thioredoxins. We aim to understand underlying molecular mechanisms and structural determinants through integration of redox proteome data from gene- to structural level. Our interactive visual analytics approach on an 8.3 m2 display wall of 25 MPixel resolution features stereoscopic three dimensions (3D) representation performed by UnityMol WebGL. Virtual reality headsets complement the range of usage configurations for fully immersive tasks. Our experiments confirm that fast access to a rich cross-linked database is necessary for immersive analysis of structural data. We emphasize the possibility to display complex data structures and relationships in 3D, intrinsic to molecular structure visualization, but less common for omics-network analysis. Our setup is powered by MinOmics, an integrated analysis pipeline and visualization framework dedicated to multi-omics analysis. MinOmics integrates data from various sources into a materialized physical repository. We evaluate its performance, a design criterion for the framework.

A comparative proteomic strategy for subcellular proteome research: ICAT approach coupled with bioinformatics prediction to ascertain rat liver mitochondrial proteins and indication of mitochondrial localization for catalase.

PubMed

Jiang, Xiao-Sheng; Dai, Jie; Sheng, Quan-Hu; Zhang, Lei; Xia, Qi-Chang; Wu, Jia-Rui; Zeng, Rong

2005-01-01

Subcellular proteomics, as an important step to functional proteomics, has been a focus in proteomic research. However, the co-purification of "contaminating" proteins has been the major problem in all the subcellular proteomic research including all kinds of mitochondrial proteome research. It is often difficult to conclude whether these "contaminants" represent true endogenous partners or artificial associations induced by cell disruption or incomplete purification. To solve such a problem, we applied a high-throughput comparative proteome experimental strategy, ICAT approach performed with two-dimensional LC-MS/MS analysis, coupled with combinational usage of different bioinformatics tools, to study the proteome of rat liver mitochondria prepared with traditional centrifugation (CM) or further purified with a Nycodenz gradient (PM). A total of 169 proteins were identified and quantified convincingly in the ICAT analysis, in which 90 proteins have an ICAT ratio of PM:CM>1.0, while another 79 proteins have an ICAT ratio of PM:CM<1.0. Almost all the proteins annotated as mitochondrial according to Swiss-Prot annotation, bioinformatics prediction, and literature reports have a ratio of PM:CM>1.0, while proteins annotated as extracellular or secreted, cytoplasmic, endoplasmic reticulum, ribosomal, and so on have a ratio of PM:CM<1.0. Catalase and AP endonuclease 1, which have been known as peroxisomal and nuclear, respectively, have shown a ratio of PM:CM>1.0, confirming the reports about their mitochondrial location. Moreover, the 125 proteins with subcellular location annotation have been used as a testing dataset to evaluate the efficiency for ascertaining mitochondrial proteins by ICAT analysis and the bioinformatics tools such as PSORT, TargetP, SubLoc, MitoProt, and Predotar. The results indicated that ICAT analysis coupled with combinational usage of different bioinformatics tools could effectively ascertain mitochondrial proteins and distinguish contaminant proteins and even multilocation proteins. Using such a strategy, many novel proteins, known proteins without subcellular location annotation, and even known proteins that have been annotated as other locations have been strongly indicated for their mitochondrial location.

Plant Abiotic Stress Proteomics: The Major Factors Determining Alterations in Cellular Proteome

PubMed Central

Kosová, Klára; Vítámvás, Pavel; Urban, Milan O.; Prášil, Ilja T.; Renaut, Jenny

2018-01-01

HIGHLIGHTS: Major environmental and genetic factors determining stress-related protein abundance are discussed.Major aspects of protein biological function including protein isoforms and PTMs, cellular localization and protein interactions are discussed.Functional diversity of protein isoforms and PTMs is discussed. Abiotic stresses reveal profound impacts on plant proteomes including alterations in protein relative abundance, cellular localization, post-transcriptional and post-translational modifications (PTMs), protein interactions with other protein partners, and, finally, protein biological functions. The main aim of the present review is to discuss the major factors determining stress-related protein accumulation and their final biological functions. A dynamics of stress response including stress acclimation to altered ambient conditions and recovery after the stress treatment is discussed. The results of proteomic studies aimed at a comparison of stress response in plant genotypes differing in stress adaptability reveal constitutively enhanced levels of several stress-related proteins (protective proteins, chaperones, ROS scavenging- and detoxification-related enzymes) in the tolerant genotypes with respect to the susceptible ones. Tolerant genotypes can efficiently adjust energy metabolism to enhanced needs during stress acclimation. Stress tolerance vs. stress susceptibility are relative terms which can reflect different stress-coping strategies depending on the given stress treatment. The role of differential protein isoforms and PTMs with respect to their biological functions in different physiological constraints (cellular compartments and interacting partners) is discussed. The importance of protein functional studies following high-throughput proteome analyses is presented in a broader context of plant biology. In summary, the manuscript tries to provide an overview of the major factors which have to be considered when interpreting data from proteomic studies on stress-treated plants. PMID:29472941

Metabolomics and proteomics technologies to explore the herbal preparation affecting metabolic disorders using high resolution mass spectrometry.

PubMed

Zhang, Aihua; Zhou, Xiaohang; Zhao, Hongwei; Zou, Shiyu; Ma, Chung Wah; Liu, Qi; Sun, Hui; Liu, Liang; Wang, Xijun

2017-01-31

An integrative metabolomics and proteomics approach can provide novel insights in the understanding of biological systems. We have integrated proteome and metabolome data sets for a holistic view of the molecular mechanisms in disease. Using quantitative iTRAQ-LC-MS/MS proteomics coupled with UPLC-Q-TOF-HDMS based metabolomics, we determined the protein and metabolite expression changes in the kidney-yang deficiency syndrome (KYDS) rat model and further investigated the intervention effects of the Jinkui Shenqi Pill (JSP). The VIP-plot of the orthogonal PLS-DA (OPLS-DA) was used for discovering the potential biomarkers to clarify the therapeutic mechanisms of JSP in treating KYDS. The results showed that JSP can alleviate the kidney impairment induced by KYDS. Sixty potential biomarkers, including 5-l-glutamyl-taurine, phenylacetaldehyde, 4,6-dihydroxyquinoline, and xanthurenic acid etc., were definitely up- or down-regulated. The regulatory effect of JSP on the disturbed metabolic pathways was proved by the established metabonomic method. Using pathway analyses, we identified the disturbed metabolic pathways such as taurine and hypotaurine metabolism, pyrimidine metabolism, tyrosine metabolism, tryptophan metabolism, histidine metabolism, steroid hormone biosynthesis, etc. Furthermore, using iTRAQ-based quantitative proteomics analysis, seventeen differential proteins were identified and significantly altered by the JSP treatment. These proteins appear to be involved in Wnt, chemokine, PPAR, and MAPK signaling pathways, etc. Functional pathway analysis revealed that most of the proteins were found to play a key role in the regulation of metabolism pathways. Bioinformatics analysis with the IPA software found that these differentially-expressed moleculars had a strong correlation with the α-adrenergic signaling, FGF signaling, etc. Our data indicate that high-throughput metabolomics and proteomics can provide an insight on the herbal preparations affecting the metabolic disorders using high resolution mass spectrometry.

Extended Multiplexing of Tandem Mass Tags (TMT) Labeling Reveals Age and High Fat Diet Specific Proteome Changes in Mouse Epididymal Adipose Tissue*

PubMed Central

Plubell, Deanna L.; Wilmarth, Phillip A.; Zhao, Yuqi; Fenton, Alexandra M.; Minnier, Jessica; Reddy, Ashok P.; Klimek, John; Yang, Xia; David, Larry L.

2017-01-01

The lack of high-throughput methods to analyze the adipose tissue protein composition limits our understanding of the protein networks responsible for age and diet related metabolic response. We have developed an approach using multiple-dimension liquid chromatography tandem mass spectrometry and extended multiplexing (24 biological samples) with tandem mass tags (TMT) labeling to analyze proteomes of epididymal adipose tissues isolated from mice fed either low or high fat diet for a short or a long-term, and from mice that aged on low versus high fat diets. The peripheral metabolic health (as measured by body weight, adiposity, plasma fasting glucose, insulin, triglycerides, total cholesterol levels, and glucose and insulin tolerance tests) deteriorated with diet and advancing age, with long-term high fat diet exposure being the worst. In response to short-term high fat diet, 43 proteins representing lipid metabolism (e.g. AACS, ACOX1, ACLY) and red-ox pathways (e.g. CPD2, CYP2E, SOD3) were significantly altered (FDR < 10%). Long-term high fat diet significantly altered 55 proteins associated with immune response (e.g. IGTB2, IFIT3, LGALS1) and rennin angiotensin system (e.g. ENPEP, CMA1, CPA3, ANPEP). Age-related changes on low fat diet significantly altered only 18 proteins representing mainly urea cycle (e.g. OTC, ARG1, CPS1), and amino acid biosynthesis (e.g. GMT, AKR1C6). Surprisingly, high fat diet driven age-related changes culminated with alterations in 155 proteins involving primarily the urea cycle (e.g. ARG1, CPS1), immune response/complement activation (e.g. C3, C4b, C8, C9, CFB, CFH, FGA), extracellular remodeling (e.g. EFEMP1, FBN1, FBN2, LTBP4, FERMT2, ECM1, EMILIN2, ITIH3) and apoptosis (e.g. YAP1, HIP1, NDRG1, PRKCD, MUL1) pathways. Using our adipose tissue tailored approach we have identified both age-related and high fat diet specific proteomic signatures highlighting a pronounced involvement of arginine metabolism in response to advancing age, and branched chain amino acid metabolism in early response to high fat feeding. Data are available via ProteomeXchange with identifier PXD005953. PMID:28325852

3D imaging of optically cleared tissue using a simplified CLARITY method and on-chip microscopy

PubMed Central

Zhang, Yibo; Shin, Yoonjung; Sung, Kevin; Yang, Sam; Chen, Harrison; Wang, Hongda; Teng, Da; Rivenson, Yair; Kulkarni, Rajan P.; Ozcan, Aydogan

2017-01-01

High-throughput sectioning and optical imaging of tissue samples using traditional immunohistochemical techniques can be costly and inaccessible in resource-limited areas. We demonstrate three-dimensional (3D) imaging and phenotyping in optically transparent tissue using lens-free holographic on-chip microscopy as a low-cost, simple, and high-throughput alternative to conventional approaches. The tissue sample is passively cleared using a simplified CLARITY method and stained using 3,3′-diaminobenzidine to target cells of interest, enabling bright-field optical imaging and 3D sectioning of thick samples. The lens-free computational microscope uses pixel super-resolution and multi-height phase recovery algorithms to digitally refocus throughout the cleared tissue and obtain a 3D stack of complex-valued images of the sample, containing both phase and amplitude information. We optimized the tissue-clearing and imaging system by finding the optimal illumination wavelength, tissue thickness, sample preparation parameters, and the number of heights of the lens-free image acquisition and implemented a sparsity-based denoising algorithm to maximize the imaging volume and minimize the amount of the acquired data while also preserving the contrast-to-noise ratio of the reconstructed images. As a proof of concept, we achieved 3D imaging of neurons in a 200-μm-thick cleared mouse brain tissue over a wide field of view of 20.5 mm2. The lens-free microscope also achieved more than an order-of-magnitude reduction in raw data compared to a conventional scanning optical microscope imaging the same sample volume. Being low cost, simple, high-throughput, and data-efficient, we believe that this CLARITY-enabled computational tissue imaging technique could find numerous applications in biomedical diagnosis and research in low-resource settings. PMID:28819645

Common bean proteomics: Present status and future strategies.

PubMed

Zargar, Sajad Majeed; Mahajan, Reetika; Nazir, Muslima; Nagar, Preeti; Kim, Sun Tae; Rai, Vandna; Masi, Antonio; Ahmad, Syed Mudasir; Shah, Riaz Ahmad; Ganai, Nazir Ahmad; Agrawal, Ganesh K; Rakwal, Randeep

2017-10-03

Common bean (Phaseolus vulgaris L.) is a legume of appreciable importance and usefulness worldwide to the human population providing food and feed. It is rich in high-quality protein, energy, fiber and micronutrients especially iron, zinc, and pro-vitamin A; and possesses potentially disease-preventing and health-promoting compounds. The recently published genome sequence of common bean is an important landmark in common bean research, opening new avenues for understanding its genetics in depth. This legume crop is affected by diverse biotic and abiotic stresses severely limiting its productivity. Looking at the trend of increasing world population and the need for food crops best suited to the health of humankind, the legumes will be in great demand, including the common bean mostly for its nutritive values. Hence the need for new research in understanding the biology of this crop brings us to utilize and apply high-throughput omics approaches. In this mini-review our focus will be on the need for proteomics studies in common bean, potential of proteomics for understanding genetic regulation under abiotic and biotic stresses and how proteogenomics will lead to nutritional improvement. We will also discuss future proteomics-based strategies that must be adopted to mine new genomic resources by identifying molecular switches regulating various biological processes. Common bean is regarded as "grain of hope" for the poor, being rich in high-quality protein, energy, fiber and micronutrients (iron, zinc, pro-vitamin A); and possesses potentially disease-preventing and health-promoting compounds. Increasing world population and the need for food crops best suited to the health of humankind, puts legumes into great demand, which includes the common bean mostly. An important landmark in common bean research was the recent publication of its genome sequence, opening new avenues for understanding its genetics in depth. This legume crop is affected by diverse biotic and abiotic stresses severely limiting its productivity. Therefore, the need for new research in understanding the biology of this crop brings us to utilize and apply high-throughput omics approaches. Proteomics can be used to track all the candidate proteins/genes responsible for a biological process under specific conditions in a particular tissue. The potential of proteomics will not only help in determining the functions of a large number of genes in a single experiment but will also be a useful tool to mine new genes that can provide solution to various problems (abiotic stress, biotic stress, nutritional improvement, etc). We believe that a combined approach including breeding along with omics tools will lead towards attaining sustainability in legumes, including common bean. Copyright © 2017 Elsevier B.V. All rights reserved.

Heat-Responsive Photosynthetic and Signaling Pathways in Plants: Insight from Proteomics.

PubMed

Wang, Xiaoli; Xu, Chenxi; Cai, Xiaofeng; Wang, Quanhua; Dai, Shaojun

2017-10-20

Heat stress is a major abiotic stress posing a serious threat to plants. Heat-responsive mechanisms in plants are complicated and fine-tuned. Heat signaling transduction and photosynthesis are highly sensitive. Therefore, a thorough understanding of the molecular mechanism in heat stressed-signaling transduction and photosynthesis is necessary to protect crop yield. Current high-throughput proteomics investigations provide more useful information for underlying heat-responsive signaling pathways and photosynthesis modulation in plants. Several signaling components, such as guanosine triphosphate (GTP)-binding protein, nucleoside diphosphate kinase, annexin, and brassinosteroid-insensitive I-kinase domain interacting protein 114, were proposed to be important in heat signaling transduction. Moreover, diverse protein patterns of photosynthetic proteins imply that the modulations of stomatal CO₂ exchange, photosystem II, Calvin cycle, ATP synthesis, and chlorophyll biosynthesis are crucial for plant heat tolerance.

The Scottish Structural Proteomics Facility: targets, methods and outputs.

PubMed

Oke, Muse; Carter, Lester G; Johnson, Kenneth A; Liu, Huanting; McMahon, Stephen A; Yan, Xuan; Kerou, Melina; Weikart, Nadine D; Kadi, Nadia; Sheikh, Md Arif; Schmelz, Stefan; Dorward, Mark; Zawadzki, Michal; Cozens, Christopher; Falconer, Helen; Powers, Helen; Overton, Ian M; van Niekerk, C A Johannes; Peng, Xu; Patel, Prakash; Garrett, Roger A; Prangishvili, David; Botting, Catherine H; Coote, Peter J; Dryden, David T F; Barton, Geoffrey J; Schwarz-Linek, Ulrich; Challis, Gregory L; Taylor, Garry L; White, Malcolm F; Naismith, James H

2010-06-01

The Scottish Structural Proteomics Facility was funded to develop a laboratory scale approach to high throughput structure determination. The effort was successful in that over 40 structures were determined. These structures and the methods harnessed to obtain them are reported here. This report reflects on the value of automation but also on the continued requirement for a high degree of scientific and technical expertise. The efficiency of the process poses challenges to the current paradigm of structural analysis and publication. In the 5 year period we published ten peer-reviewed papers reporting structural data arising from the pipeline. Nevertheless, the number of structures solved exceeded our ability to analyse and publish each new finding. By reporting the experimental details and depositing the structures we hope to maximize the impact of the project by allowing others to follow up the relevant biology.

A Combined Proteomic and Transcriptomic Analysis on Sulfur Metabolism Pathways of Arabidopsis thaliana under Simulated Acid Rain

PubMed Central

Wang, Wenhua; Simon, Martin; Wu, Feihua; Hu, Wenjun; Chen, Juan B.; Zheng, Hailei

2014-01-01

With rapid economic development, most regions in southern China have suffered acid rain (AR) pollution. In our study, we analyzed the changes in sulfur metabolism in Arabidopsis under simulated AR stress which provide one of the first case studies, in which the systematic responses in sulfur metabolism were characterized by high-throughput methods at different levels including proteomic, genomic and physiological approaches. Generally, we found that all of the processes related to sulfur metabolism responded to AR stress, including sulfur uptake, activation and also synthesis of sulfur-containing amino acid and other secondary metabolites. Finally, we provided a catalogue of the detected sulfur metabolic changes and reconstructed the coordinating network of their mutual influences. This study can help us to understand the mechanisms of plants to adapt to AR stress. PMID:24595051

BIG: a large-scale data integration tool for renal physiology.

PubMed

Zhao, Yue; Yang, Chin-Rang; Raghuram, Viswanathan; Parulekar, Jaya; Knepper, Mark A

2016-10-01

Due to recent advances in high-throughput techniques, we and others have generated multiple proteomic and transcriptomic databases to describe and quantify gene expression, protein abundance, or cellular signaling on the scale of the whole genome/proteome in kidney cells. The existence of so much data from diverse sources raises the following question: "How can researchers find information efficiently for a given gene product over all of these data sets without searching each data set individually?" This is the type of problem that has motivated the "Big-Data" revolution in Data Science, which has driven progress in fields such as marketing. Here we present an online Big-Data tool called BIG (Biological Information Gatherer) that allows users to submit a single online query to obtain all relevant information from all indexed databases. BIG is accessible at http://big.nhlbi.nih.gov/.

The upcoming 3D-printing revolution in microfluidics

PubMed Central

Bhattacharjee, Nirveek; Urrios, Arturo; Kang, Shawn; Folch, Albert

2016-01-01

In the last two decades, the vast majority of microfluidic systems have been built in poly(dimethylsiloxane) (PDMS) by soft lithography, a technique based on PDMS micromolding. A long list of key PDMS properties have contributed to the success of soft lithography: PDMS is biocompatible, elastomeric, transparent, gas-permeable, water-impermeable, fairly inexpensive, copyright-free, and rapidly prototyped with high precision using simple procedures. However, the fabrication process typically involves substantial human labor, which tends to make PDMS devices difficult to disseminate outside of research labs, and the layered molding limits the 3D complexity of the devices that can be produced. 3D-printing has recently attracted attention as a way to fabricate microfluidic systems due to its automated, assembly-free 3D fabrication, rapidly decreasing costs, and fast-improving resolution and throughput. Resins with properties approaching those of PDMS are being developed. Here we review past and recent efforts in 3D-printing of microfluidic systems. We compare the salient features of PDMS molding with those of 3D-printing and we give an overview of the critical barriers that have prevented the adoption of 3D-printing by microfluidic developers, namely resolution, throughput, and resin biocompatibility. We also evaluate the various forces that are persuading researchers to abandon PDMS molding in favor of 3D-printing in growing numbers. PMID:27101171

A new fungal large subunit ribosomal RNA primer for high throughput sequencing surveys

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mueller, Rebecca C.; Gallegos-Graves, La Verne; Kuske, Cheryl R.

The inclusion of phylogenetic metrics in community ecology has provided insights into important ecological processes, particularly when combined with high-throughput sequencing methods; however, these approaches have not been widely used in studies of fungal communities relative to other microbial groups. Two obstacles have been considered: (1) the internal transcribed spacer (ITS) region has limited utility for constructing phylogenies and (2) most PCR primers that target the large subunit (LSU) ribosomal unit generate amplicons that exceed current limits of high-throughput sequencing platforms. We designed and tested a PCR primer (LR22R) to target approximately 300–400 bp region of the D2 hypervariable regionmore » of the fungal LSU for use with the Illumina MiSeq platform. Both in silico and empirical analyses showed that the LR22R–LR3 pair captured a broad range of fungal taxonomic groups with a small fraction of non-fungal groups. Phylogenetic placement of publically available LSU D2 sequences showed broad agreement with taxonomic classification. Comparisons of the LSU D2 and the ITS2 ribosomal regions from environmental samples and known communities showed similar discriminatory abilities of the two primer sets. Altogether, these findings show that the LR22R–LR3 primer pair has utility for phylogenetic analyses of fungal communities using high-throughput sequencing methods.« less

A new fungal large subunit ribosomal RNA primer for high throughput sequencing surveys

DOE PAGES

Mueller, Rebecca C.; Gallegos-Graves, La Verne; Kuske, Cheryl R.

2015-12-09

The inclusion of phylogenetic metrics in community ecology has provided insights into important ecological processes, particularly when combined with high-throughput sequencing methods; however, these approaches have not been widely used in studies of fungal communities relative to other microbial groups. Two obstacles have been considered: (1) the internal transcribed spacer (ITS) region has limited utility for constructing phylogenies and (2) most PCR primers that target the large subunit (LSU) ribosomal unit generate amplicons that exceed current limits of high-throughput sequencing platforms. We designed and tested a PCR primer (LR22R) to target approximately 300–400 bp region of the D2 hypervariable regionmore » of the fungal LSU for use with the Illumina MiSeq platform. Both in silico and empirical analyses showed that the LR22R–LR3 pair captured a broad range of fungal taxonomic groups with a small fraction of non-fungal groups. Phylogenetic placement of publically available LSU D2 sequences showed broad agreement with taxonomic classification. Comparisons of the LSU D2 and the ITS2 ribosomal regions from environmental samples and known communities showed similar discriminatory abilities of the two primer sets. Altogether, these findings show that the LR22R–LR3 primer pair has utility for phylogenetic analyses of fungal communities using high-throughput sequencing methods.« less

High-Throughput Platform for Patient-Derived, Small Cell Number, Three-Dimensional Ovarian Cancer Spheroids

DTIC Science & Technology

2014-09-01

these small cell number spheroids show 3-D morphology (Figure 3). We also observed differences in the expression of mesenchymal markers when...Scale bar =100 µm. Figure 3: Small cell number spheroids demonstrate 3-D morphology . 3-D reconstructions of confocal z-stacks are shown for...formation was observed with the addition of MSCs, and subsequent co-culture in hanging drop plates preserved spheroid morphology indicated in the phase

Establishing Substantial Equivalence: Proteomics

NASA Astrophysics Data System (ADS)

Lovegrove, Alison; Salt, Louise; Shewry, Peter R.

Wheat is a major crop in world agriculture and is consumed after processing into a range of food products. It is therefore of great importance to determine the consequences (intended and unintended) of transgenesis in wheat and whether genetically modified lines are substantially equivalent to those produced by conventional plant breeding. Proteomic analysis is one of several approaches which can be used to address these questions. Two-dimensional PAGE (2D PAGE) remains the most widely available method for proteomic analysis, but is notoriously difficult to reproduce between laboratories. We therefore describe methods which have been developed as standard operating procedures in our laboratory to ensure the reproducibility of proteomic analyses of wheat using 2D PAGE analysis of grain proteins.

Biomarker Discovery by Novel Sensors Based on Nanoproteomics Approaches

PubMed Central

Dasilva, Noelia; Díez, Paula; Matarraz, Sergio; González-González, María; Paradinas, Sara; Orfao, Alberto; Fuentes, Manuel

2012-01-01

During the last years, proteomics has facilitated biomarker discovery by coupling high-throughput techniques with novel nanosensors. In the present review, we focus on the study of label-based and label-free detection systems, as well as nanotechnology approaches, indicating their advantages and applications in biomarker discovery. In addition, several disease biomarkers are shown in order to display the clinical importance of the improvement of sensitivity and selectivity by using nanoproteomics approaches as novel sensors. PMID:22438764

SubCellProt: predicting protein subcellular localization using machine learning approaches.

PubMed

Garg, Prabha; Sharma, Virag; Chaudhari, Pradeep; Roy, Nilanjan

2009-01-01

High-throughput genome sequencing projects continue to churn out enormous amounts of raw sequence data. However, most of this raw sequence data is unannotated and, hence, not very useful. Among the various approaches to decipher the function of a protein, one is to determine its localization. Experimental approaches for proteome annotation including determination of a protein's subcellular localizations are very costly and labor intensive. Besides the available experimental methods, in silico methods present alternative approaches to accomplish this task. Here, we present two machine learning approaches for prediction of the subcellular localization of a protein from the primary sequence information. Two machine learning algorithms, k Nearest Neighbor (k-NN) and Probabilistic Neural Network (PNN) were used to classify an unknown protein into one of the 11 subcellular localizations. The final prediction is made on the basis of a consensus of the predictions made by two algorithms and a probability is assigned to it. The results indicate that the primary sequence derived features like amino acid composition, sequence order and physicochemical properties can be used to assign subcellular localization with a fair degree of accuracy. Moreover, with the enhanced accuracy of our approach and the definition of a prediction domain, this method can be used for proteome annotation in a high throughput manner. SubCellProt is available at www.databases.niper.ac.in/SubCellProt.

Proteomics: from hypothesis to quantitative assay on a single platform. Guidelines for developing MRM assays using ion trap mass spectrometers.

PubMed

Han, Bomie; Higgs, Richard E

2008-09-01

High-throughput HPLC-mass spectrometry (HPLC-MS) is routinely used to profile biological samples for potential protein markers of disease, drug efficacy and toxicity. The discovery technology has advanced to the point where translating hypotheses from proteomic profiling studies into clinical use is the bottleneck to realizing the full potential of these approaches. The first step in this translation is the development and analytical validation of a higher throughput assay with improved sensitivity and selectivity relative to typical profiling assays. Multiple reaction monitoring (MRM) assays are an attractive approach for this stage of biomarker development given their improved sensitivity and specificity, the speed at which the assays can be developed and the quantitative nature of the assay. While the profiling assays are performed with ion trap mass spectrometers, MRM assays are traditionally developed in quadrupole-based mass spectrometers. Development of MRM assays from the same instrument used in the profiling analysis enables a seamless and rapid transition from hypothesis generation to validation. This report provides guidelines for rapidly developing an MRM assay using the same mass spectrometry platform used for profiling experiments (typically ion traps) and reviews methodological and analytical validation considerations. The analytical validation guidelines presented are drawn from existing practices on immunological assays and are applicable to any mass spectrometry platform technology.

High-throughput molecular analysis in lung cancer: insights into biology and potential clinical applications.

PubMed

Ocak, S; Sos, M L; Thomas, R K; Massion, P P

2009-08-01

During the last decade, high-throughput technologies including genomic, epigenomic, transcriptomic and proteomic have been applied to further our understanding of the molecular pathogenesis of this heterogeneous disease, and to develop strategies that aim to improve the management of patients with lung cancer. Ultimately, these approaches should lead to sensitive, specific and noninvasive methods for early diagnosis, and facilitate the prediction of response to therapy and outcome, as well as the identification of potential novel therapeutic targets. Genomic studies were the first to move this field forward by providing novel insights into the molecular biology of lung cancer and by generating candidate biomarkers of disease progression. Lung carcinogenesis is driven by genetic and epigenetic alterations that cause aberrant gene function; however, the challenge remains to pinpoint the key regulatory control mechanisms and to distinguish driver from passenger alterations that may have a small but additive effect on cancer development. Epigenetic regulation by DNA methylation and histone modifications modulate chromatin structure and, in turn, either activate or silence gene expression. Proteomic approaches critically complement these molecular studies, as the phenotype of a cancer cell is determined by proteins and cannot be predicted by genomics or transcriptomics alone. The present article focuses on the technological platforms available and some proposed clinical applications. We illustrate herein how the "-omics" have revolutionised our approach to lung cancer biology and hold promise for personalised management of lung cancer.

Serum proteome profiling in canine idiopathic dilated cardiomyopathy using TMT-based quantitative proteomics approach.

PubMed

Bilić, Petra; Guillemin, Nicolas; Kovačević, Alan; Beer Ljubić, Blanka; Jović, Ines; Galan, Asier; Eckersall, Peter David; Burchmore, Richard; Mrljak, Vladimir

2018-05-15

Idiopathic dilated cardiomyopathy (iDCM) is a primary myocardial disorder with an unknown aetiology, characterized by reduced contractility and ventricular dilation of the left or both ventricles. Naturally occurring canine iDCM was used herein to identify serum proteomic signature of the disease compared to the healthy state, providing an insight into underlying mechanisms and revealing proteins with biomarker potential. To achieve this, we used high-throughput label-based quantitative LC-MS/MS proteomics approach and bioinformatics analysis of the in silico inferred interactome protein network created from the initial list of differential proteins. To complement the proteomic analysis, serum biochemical parameters and levels of know biomarkers of cardiac function were measured. Several proteins with biomarker potential were identified, such as inter-alpha-trypsin inhibitor heavy chain H4, microfibril-associated glycoprotein 4 and apolipoprotein A-IV, which were validated using an independent method (Western blotting) and showed high specificity and sensitivity according to the receiver operating characteristic curve analysis. Bioinformatics analysis revealed involvement of different pathways in iDCM, such as complement cascade activation, lipoprotein particles dynamics, elastic fibre formation, GPCR signalling and respiratory electron transport chain. Idiopathic dilated cardiomyopathy is a severe primary myocardial disease of unknown cause, affecting both humans and dogs. This study is a contribution to the canine heart disease research by means of proteomic and bioinformatic state of the art analyses, following similar approach in human iDCM research. Importantly, we used serum as non-invasive and easily accessible biological source of information and contributed to the scarce data on biofluid proteome research on this topic. Bioinformatics analysis revealed biological pathways modulated in canine iDCM with potential of further targeted research. Also, several proteins with biomarker potential have been identified and successfully validated. Copyright © 2018 Elsevier B.V. All rights reserved.

Proteomics and Metabolomics: Two Emerging Areas for Legume Improvement

PubMed Central

Ramalingam, Abirami; Kudapa, Himabindu; Pazhamala, Lekha T.; Weckwerth, Wolfram; Varshney, Rajeev K.

2015-01-01

The crop legumes such as chickpea, common bean, cowpea, peanut, pigeonpea, soybean, etc. are important sources of nutrition and contribute to a significant amount of biological nitrogen fixation (>20 million tons of fixed nitrogen) in agriculture. However, the production of legumes is constrained due to abiotic and biotic stresses. It is therefore imperative to understand the molecular mechanisms of plant response to different stresses and identify key candidate genes regulating tolerance which can be deployed in breeding programs. The information obtained from transcriptomics has facilitated the identification of candidate genes for the given trait of interest and utilizing them in crop breeding programs to improve stress tolerance. However, the mechanisms of stress tolerance are complex due to the influence of multi-genes and post-transcriptional regulations. Furthermore, stress conditions greatly affect gene expression which in turn causes modifications in the composition of plant proteomes and metabolomes. Therefore, functional genomics involving various proteomics and metabolomics approaches have been obligatory for understanding plant stress tolerance. These approaches have also been found useful to unravel different pathways related to plant and seed development as well as symbiosis. Proteome and metabolome profiling using high-throughput based systems have been extensively applied in the model legume species, Medicago truncatula and Lotus japonicus, as well as in the model crop legume, soybean, to examine stress signaling pathways, cellular and developmental processes and nodule symbiosis. Moreover, the availability of protein reference maps as well as proteomics and metabolomics databases greatly support research and understanding of various biological processes in legumes. Protein-protein interaction techniques, particularly the yeast two-hybrid system have been advantageous for studying symbiosis and stress signaling in legumes. In this review, several studies on proteomics and metabolomics in model and crop legumes have been discussed. Additionally, applications of advanced proteomics and metabolomics approaches have also been included in this review for future applications in legume research. The integration of these “omics” approaches will greatly support the identification of accurate biomarkers in legume smart breeding programs. PMID:26734026

A comprehensive and scalable database search system for metaproteomics.

PubMed

Chatterjee, Sandip; Stupp, Gregory S; Park, Sung Kyu Robin; Ducom, Jean-Christophe; Yates, John R; Su, Andrew I; Wolan, Dennis W

2016-08-16

Mass spectrometry-based shotgun proteomics experiments rely on accurate matching of experimental spectra against a database of protein sequences. Existing computational analysis methods are limited in the size of their sequence databases, which severely restricts the proteomic sequencing depth and functional analysis of highly complex samples. The growing amount of public high-throughput sequencing data will only exacerbate this problem. We designed a broadly applicable metaproteomic analysis method (ComPIL) that addresses protein database size limitations. Our approach to overcome this significant limitation in metaproteomics was to design a scalable set of sequence databases assembled for optimal library querying speeds. ComPIL was integrated with a modified version of the search engine ProLuCID (termed "Blazmass") to permit rapid matching of experimental spectra. Proof-of-principle analysis of human HEK293 lysate with a ComPIL database derived from high-quality genomic libraries was able to detect nearly all of the same peptides as a search with a human database (~500x fewer peptides in the database), with a small reduction in sensitivity. We were also able to detect proteins from the adenovirus used to immortalize these cells. We applied our method to a set of healthy human gut microbiome proteomic samples and showed a substantial increase in the number of identified peptides and proteins compared to previous metaproteomic analyses, while retaining a high degree of protein identification accuracy and allowing for a more in-depth characterization of the functional landscape of the samples. The combination of ComPIL with Blazmass allows proteomic searches to be performed with database sizes much larger than previously possible. These large database searches can be applied to complex meta-samples with unknown composition or proteomic samples where unexpected proteins may be identified. The protein database, proteomic search engine, and the proteomic data files for the 5 microbiome samples characterized and discussed herein are open source and available for use and additional analysis.

Biomarkers for Cognitive Impairment in Parkinson Disease

PubMed Central

Shi, Min; Huber, Bertrand R.; Zhang, Jing

2010-01-01

Cognitive impairment, including dementia, is commonly seen in those afflicted with Parkinson disease (PD), particularly at advanced disease stages. Pathologically, PD with dementia (PD-D) is most often associated with the presence of cortical Lewy bodies, as is the closely related dementia with Lewy bodies (DLB). Both PD-D and DLB are also frequently complicated by the presence of neurofibrillary tangles and amyloid plaques, features most often attributed to Alzheimer disease. Biomarkers are urgently needed to differentiate among these disease processes and predict dementia in PD as well as monitor responses of patients to new therapies. A few clinical assessments, along with structural and functional neuroimaging, have been utilized in the last few years with some success in this area. Additionally, a number of other strategies have been employed to identify biochemical/molecular biomarkers associated with cognitive impairment and dementia in PD, e.g., targeted analysis of candidate proteins known to be important to PD pathogenesis and progression in cerebrospinal fluid or blood. Finally, interesting results are emerging from preliminary studies with unbiased and high throughput genomic, proteomic and metabolomic techniques. The current findings and perspectives of applying these strategies and techniques are reviewed in this article, together with potential areas of advancement. PMID:20522092

Statistical Methods for Proteomic Biomarker Discovery based on Feature Extraction or Functional Modeling Approaches.

PubMed

Morris, Jeffrey S

2012-01-01

In recent years, developments in molecular biotechnology have led to the increased promise of detecting and validating biomarkers, or molecular markers that relate to various biological or medical outcomes. Proteomics, the direct study of proteins in biological samples, plays an important role in the biomarker discovery process. These technologies produce complex, high dimensional functional and image data that present many analytical challenges that must be addressed properly for effective comparative proteomics studies that can yield potential biomarkers. Specific challenges include experimental design, preprocessing, feature extraction, and statistical analysis accounting for the inherent multiple testing issues. This paper reviews various computational aspects of comparative proteomic studies, and summarizes contributions I along with numerous collaborators have made. First, there is an overview of comparative proteomics technologies, followed by a discussion of important experimental design and preprocessing issues that must be considered before statistical analysis can be done. Next, the two key approaches to analyzing proteomics data, feature extraction and functional modeling, are described. Feature extraction involves detection and quantification of discrete features like peaks or spots that theoretically correspond to different proteins in the sample. After an overview of the feature extraction approach, specific methods for mass spectrometry ( Cromwell ) and 2D gel electrophoresis ( Pinnacle ) are described. The functional modeling approach involves modeling the proteomic data in their entirety as functions or images. A general discussion of the approach is followed by the presentation of a specific method that can be applied, wavelet-based functional mixed models, and its extensions. All methods are illustrated by application to two example proteomic data sets, one from mass spectrometry and one from 2D gel electrophoresis. While the specific methods presented are applied to two specific proteomic technologies, MALDI-TOF and 2D gel electrophoresis, these methods and the other principles discussed in the paper apply much more broadly to other expression proteomics technologies.

Computational efficient segmentation of cell nuclei in 2D and 3D fluorescent micrographs

NASA Astrophysics Data System (ADS)

De Vylder, Jonas; Philips, Wilfried

2011-02-01

This paper proposes a new segmentation technique developed for the segmentation of cell nuclei in both 2D and 3D fluorescent micrographs. The proposed method can deal with both blurred edges as with touching nuclei. Using a dual scan line algorithm its both memory as computational efficient, making it interesting for the analysis of images coming from high throughput systems or the analysis of 3D microscopic images. Experiments show good results, i.e. recall of over 0.98.

Quantitative targeted absolute proteomic analysis of transporters, receptors and junction proteins for validation of human cerebral microvascular endothelial cell line hCMEC/D3 as a human blood-brain barrier model.

PubMed

Ohtsuki, Sumio; Ikeda, Chiemi; Uchida, Yasuo; Sakamoto, Yumi; Miller, Florence; Glacial, Fabienne; Decleves, Xavier; Scherrmann, Jean-Michel; Couraud, Pierre-Olivier; Kubo, Yoshiyuki; Tachikawa, Masanori; Terasaki, Tetsuya

2013-01-07

Human cerebral microvascular endothelial cell line hCMEC/D3 is an established model of the human blood-brain barrier (BBB). The purpose of the present study was to determine, by means of quantitative targeted absolute proteomics, the protein expression levels in hCMEC/D3 cells of multiple transporters, receptors and junction proteins for comparison with our previously reported findings in isolated human brain microvessels. Among 91 target molecules, 12 transporters, 2 receptors, 1 junction protein and 1 membrane marker were present at quantifiable levels in plasma membrane fraction of hCMEC/D3 cells. ABCA2, MDR1, MRP4, BCRP, GLUT1, 4F2hc, MCT1, ENT1, transferrin and insulin receptors and claudin-5 were detected in both hCMEC/D3 cells and human brain microvessels. After normalization based on Na(+)/K(+) ATPase expression, the differences in protein expression levels between hCMEC/D3 cells and human brain microvessels were within 4-fold for these proteins, with the exceptions of ENT1, transferrin receptor and claudin-5. ABCA8, LAT1, LRP1 and γ-GTP were below the limit of quantification in the cells, but were found in human brain microvessels. ABCA3, ABCA6, MRP1 and ATA1 were found only in hCMEC/D3 cells. Furthermore, compared with human umbilical vein endothelial cells (HUVECs) as reference nonbrain endothelial cells, MDR1 was found only in hCMEC/D3 cells, and GLUT1 expression was 15-fold higher in hCMEC/D3 cells than in HUVECs. In conclusion, this is the first study to examine the suitability and limitations of the hCMEC/D3 cell line as a BBB functional model in terms of quantitative expression levels of transporters, receptors and tight junction proteins.

neXtProt: organizing protein knowledge in the context of human proteome projects.

PubMed

Gaudet, Pascale; Argoud-Puy, Ghislaine; Cusin, Isabelle; Duek, Paula; Evalet, Olivier; Gateau, Alain; Gleizes, Anne; Pereira, Mario; Zahn-Zabal, Monique; Zwahlen, Catherine; Bairoch, Amos; Lane, Lydie

2013-01-04

About 5000 (25%) of the ~20400 human protein-coding genes currently lack any experimental evidence at the protein level. For many others, there is only little information relative to their abundance, distribution, subcellular localization, interactions, or cellular functions. The aim of the HUPO Human Proteome Project (HPP, www.thehpp.org ) is to collect this information for every human protein. HPP is based on three major pillars: mass spectrometry (MS), antibody/affinity capture reagents (Ab), and bioinformatics-driven knowledge base (KB). To meet this objective, the Chromosome-Centric Human Proteome Project (C-HPP) proposes to build this catalog chromosome-by-chromosome ( www.c-hpp.org ) by focusing primarily on proteins that currently lack MS evidence or Ab detection. These are termed "missing proteins" by the HPP consortium. The lack of observation of a protein can be due to various factors including incorrect and incomplete gene annotation, low or restricted expression, or instability. neXtProt ( www.nextprot.org ) is a new web-based knowledge platform specific for human proteins that aims to complement UniProtKB/Swiss-Prot ( www.uniprot.org ) with detailed information obtained from carefully selected high-throughput experiments on genomic variation, post-translational modifications, as well as protein expression in tissues and cells. This article describes how neXtProt contributes to prioritize C-HPP efforts and integrates C-HPP results with other research efforts to create a complete human proteome catalog.

SwissPalm: Protein Palmitoylation database.

PubMed

Blanc, Mathieu; David, Fabrice; Abrami, Laurence; Migliozzi, Daniel; Armand, Florence; Bürgi, Jérôme; van der Goot, Françoise Gisou

2015-01-01

Protein S-palmitoylation is a reversible post-translational modification that regulates many key biological processes, although the full extent and functions of protein S-palmitoylation remain largely unexplored. Recent developments of new chemical methods have allowed the establishment of palmitoyl-proteomes of a variety of cell lines and tissues from different species.  As the amount of information generated by these high-throughput studies is increasing, the field requires centralization and comparison of this information. Here we present SwissPalm ( http://swisspalm.epfl.ch), our open, comprehensive, manually curated resource to study protein S-palmitoylation. It currently encompasses more than 5000 S-palmitoylated protein hits from seven species, and contains more than 500 specific sites of S-palmitoylation. SwissPalm also provides curated information and filters that increase the confidence in true positive hits, and integrates predictions of S-palmitoylated cysteine scores, orthologs and isoform multiple alignments. Systems analysis of the palmitoyl-proteome screens indicate that 10% or more of the human proteome is susceptible to S-palmitoylation. Moreover, ontology and pathway analyses of the human palmitoyl-proteome reveal that key biological functions involve this reversible lipid modification. Comparative analysis finally shows a strong crosstalk between S-palmitoylation and other post-translational modifications. Through the compilation of data and continuous updates, SwissPalm will provide a powerful tool to unravel the global importance of protein S-palmitoylation.

SwissPalm: Protein Palmitoylation database

PubMed Central

Abrami, Laurence; Migliozzi, Daniel; Armand, Florence; Bürgi, Jérôme; van der Goot, Françoise Gisou

2015-01-01

Protein S-palmitoylation is a reversible post-translational modification that regulates many key biological processes, although the full extent and functions of protein S-palmitoylation remain largely unexplored. Recent developments of new chemical methods have allowed the establishment of palmitoyl-proteomes of a variety of cell lines and tissues from different species.  As the amount of information generated by these high-throughput studies is increasing, the field requires centralization and comparison of this information. Here we present SwissPalm ( http://swisspalm.epfl.ch), our open, comprehensive, manually curated resource to study protein S-palmitoylation. It currently encompasses more than 5000 S-palmitoylated protein hits from seven species, and contains more than 500 specific sites of S-palmitoylation. SwissPalm also provides curated information and filters that increase the confidence in true positive hits, and integrates predictions of S-palmitoylated cysteine scores, orthologs and isoform multiple alignments. Systems analysis of the palmitoyl-proteome screens indicate that 10% or more of the human proteome is susceptible to S-palmitoylation. Moreover, ontology and pathway analyses of the human palmitoyl-proteome reveal that key biological functions involve this reversible lipid modification. Comparative analysis finally shows a strong crosstalk between S-palmitoylation and other post-translational modifications. Through the compilation of data and continuous updates, SwissPalm will provide a powerful tool to unravel the global importance of protein S-palmitoylation. PMID:26339475

Laser Capture Microdissection of Pancreatic Acinar Cells to Identify Proteomic Alterations in a Murine Model of Caerulein-Induced Pancreatitis

PubMed Central

Shapiro, John P; Komar, Hannah M; Hancioglu, Baris; Yu, Lianbo; Jin, Ming; Ogata, Yuko; Hart, Phil A; Cruz-Monserrate, Zobeida; Lesinski, Gregory B; Conwell, Darwin L

2017-01-01

Objectives: Chronic pancreatitis (CP) is characterized by inflammation and fibrosis of the pancreas, leading to pain, parenchymal damage, and loss of exocrine and endocrine function. There are currently no curative therapies; diagnosis remains difficult and aspects of pathogenesis remain unclear. Thus, there is a need to identify novel biomarkers to improve diagnosis and understand pathophysiology. We hypothesize that pancreatic acinar regions contain proteomic signatures relevant to disease processes, including secreted proteins that could be detected in biofluids. Methods: Acini from pancreata of mice injected with or without caerulein were collected using laser capture microdissection followed by mass spectrometry analysis. This protocol enabled high-throughput analysis that captured altered protein expression throughout the stages of CP. Results: Over 2,900 proteins were identified, whereas 331 were significantly changed ≥2-fold by mass spectrometry spectral count analysis. Consistent with pathogenesis, we observed increases in proteins related to fibrosis (e.g., collagen, P<0.001), several proteases (e.g., trypsin 1, P<0.001), and altered expression of proteins associated with diminished pancreas function (e.g., lipase, amylase, P<0.05). In comparison with proteomic data from a public data set of CP patients, a significant correlation was observed between proteomic changes in tissue from both the caerulein model and CP patients (r=0.725, P<0.001). CONCLUSIONS: This study illustrates the ability to characterize proteome changes of acinar cells isolated from pancreata of caerulein-treated mice and demonstrates a relationship between signatures from murine and human CP. PMID:28406494

Analysis of essential gene dynamics under antibiotic stress in Streptococcus sanguinis

PubMed Central

El-Rami, Fadi; Kong, Xiangzhen; Parikh, Hardik; Zhu, Bin; Stone, Victoria; Kitten, Todd; Xu, Ping

2018-01-01

The paradoxical response of Streptococcus sanguinis to drugs prescribed for dental and clinical practices has complicated treatment guidelines and raised the need for further investigation. We conducted a high throughput study on concomitant transcriptome and proteome dynamics in a time course to assess S. sanguinis behaviour under a sub-inhibitory concentration of ampicillin. Temporal changes at the transcriptome and proteome level were monitored to cover essential genes and proteins over a physiological map of intricate pathways. Our findings revealed that translation was the functional category in S. sanguinis that was most enriched in essential proteins. Moreover, essential proteins in this category demonstrated the greatest conservation across 2774 bacterial proteomes, in comparison to other essential functional categories like cell wall biosynthesis and energy production. In comparison to non-essential proteins, essential proteins were less likely to contain ‘degradation-prone’ amino acids at their N-terminal position, suggesting a longer half-life. Despite the ampicillin-induced stress, the transcriptional up-regulation of amino acid-tRNA synthetases and proteomic elevation of amino acid biosynthesis enzymes favoured the enriched components of essential proteins revealing ‘proteomic signatures’ that can be used to bridge the genotype–phenotype gap of S. sanguinis under ampicillin stress. Furthermore, we identified a significant correlation between the levels of mRNA and protein for essential genes and detected essential protein-enriched pathways differentially regulated through a persistent stress response pattern at late time points. We propose that the current findings will help characterize a bacterial model to study the dynamics of essential genes and proteins under clinically relevant stress conditions. PMID:29393020

3-Dimensional culture systems for anti-cancer compound profiling and high-throughput screening reveal increases in EGFR inhibitor-mediated cytotoxicity compared to monolayer culture systems.

PubMed

Howes, Amy L; Richardson, Robyn D; Finlay, Darren; Vuori, Kristiina

2014-01-01

3-dimensional (3D) culture models have the potential to bridge the gap between monolayer cell culture and in vivo studies. To benefit anti-cancer drug discovery from 3D models, new techniques are needed that enable their use in high-throughput (HT) screening amenable formats. We have established miniaturized 3D culture methods robust enough for automated HT screens. We have applied these methods to evaluate the sensitivity of normal and tumorigenic breast epithelial cell lines against a panel of oncology drugs when cultured as monolayers (2D) and spheroids (3D). We have identified two classes of compounds that exhibit preferential cytotoxicity against cancer cells over normal cells when cultured as 3D spheroids: microtubule-targeting agents and epidermal growth factor receptor (EGFR) inhibitors. Further improving upon our 3D model, superior differentiation of EC50 values in the proof-of-concept screens was obtained by co-culturing the breast cancer cells with normal human fibroblasts and endothelial cells. Further, the selective sensitivity of the cancer cells towards chemotherapeutics was observed in 3D co-culture conditions, rather than as 2D co-culture monolayers, highlighting the importance of 3D cultures. Finally, we examined the putative mechanisms that drive the differing potency displayed by EGFR inhibitors. In summary, our studies establish robust 3D culture models of human cells for HT assessment of tumor cell-selective agents. This methodology is anticipated to provide a useful tool for the study of biological differences within 2D and 3D culture conditions in HT format, and an important platform for novel anti-cancer drug discovery.

3-Dimensional Culture Systems for Anti-Cancer Compound Profiling and High-Throughput Screening Reveal Increases in EGFR Inhibitor-Mediated Cytotoxicity Compared to Monolayer Culture Systems

PubMed Central

Howes, Amy L.; Richardson, Robyn D.; Finlay, Darren; Vuori, Kristiina

2014-01-01

3-dimensional (3D) culture models have the potential to bridge the gap between monolayer cell culture and in vivo studies. To benefit anti-cancer drug discovery from 3D models, new techniques are needed that enable their use in high-throughput (HT) screening amenable formats. We have established miniaturized 3D culture methods robust enough for automated HT screens. We have applied these methods to evaluate the sensitivity of normal and tumorigenic breast epithelial cell lines against a panel of oncology drugs when cultured as monolayers (2D) and spheroids (3D). We have identified two classes of compounds that exhibit preferential cytotoxicity against cancer cells over normal cells when cultured as 3D spheroids: microtubule-targeting agents and epidermal growth factor receptor (EGFR) inhibitors. Further improving upon our 3D model, superior differentiation of EC50 values in the proof-of-concept screens was obtained by co-culturing the breast cancer cells with normal human fibroblasts and endothelial cells. Further, the selective sensitivity of the cancer cells towards chemotherapeutics was observed in 3D co-culture conditions, rather than as 2D co-culture monolayers, highlighting the importance of 3D cultures. Finally, we examined the putative mechanisms that drive the differing potency displayed by EGFR inhibitors. In summary, our studies establish robust 3D culture models of human cells for HT assessment of tumor cell-selective agents. This methodology is anticipated to provide a useful tool for the study of biological differences within 2D and 3D culture conditions in HT format, and an important platform for novel anti-cancer drug discovery. PMID:25247711

An Innovative Approach for The Integration of Proteomics and Metabolomics Data In Severe Septic Shock Patients Stratified for Mortality.

PubMed

Cambiaghi, Alice; Díaz, Ramón; Martinez, Julia Bauzá; Odena, Antonia; Brunelli, Laura; Caironi, Pietro; Masson, Serge; Baselli, Giuseppe; Ristagno, Giuseppe; Gattinoni, Luciano; de Oliveira, Eliandre; Pastorelli, Roberta; Ferrario, Manuela

2018-04-27

In this work, we examined plasma metabolome, proteome and clinical features in patients with severe septic shock enrolled in the multicenter ALBIOS study. The objective was to identify changes in the levels of metabolites involved in septic shock progression and to integrate this information with the variation occurring in proteins and clinical data. Mass spectrometry-based targeted metabolomics and untargeted proteomics allowed us to quantify absolute metabolites concentration and relative proteins abundance. We computed the ratio D7/D1 to take into account their variation from day 1 (D1) to day 7 (D7) after shock diagnosis. Patients were divided into two groups according to 28-day mortality. Three different elastic net logistic regression models were built: one on metabolites only, one on metabolites and proteins and one to integrate metabolomics and proteomics data with clinical parameters. Linear discriminant analysis and Partial least squares Discriminant Analysis were also implemented. All the obtained models correctly classified the observations in the testing set. By looking at the variable importance (VIP) and the selected features, the integration of metabolomics with proteomics data showed the importance of circulating lipids and coagulation cascade in septic shock progression, thus capturing a further layer of biological information complementary to metabolomics information.

Proteomic analysis of albumin and globulin fractions of pea (Pisum sativum L.) seeds.

PubMed

Dziuba, Jerzy; Szerszunowicz, Iwona; Nałęcz, Dorota; Dziuba, Marta

2014-01-01

Proteomic analysis is emerging as a highly useful tool in food research, including studies of food allergies. Two-dimensional gel electrophoresis involving isoelectric focusing and sodium dodecyl sulfate polyacrylamide gel electrophoresis is the most effective method of separating hundreds or even thousands of proteins. In this study, albumin and globulin tractions of pea seeds cv. Ramrod were subjected to proteomic analysis. Selected potentially alergenic proteins were identified based on their molecular weights and isoelectric points. Pea seeds (Pisum sativum L.) cv. Ramrod harvested over a period of two years (Plant Breeding Station in Piaski-Szelejewo) were used in the experiment. The isolated albumins, globulins and legumin and vicilin fractions of globulins were separated by two-dimensional gel electrophoresis. Proteomic images were analysed in the ImageMaster 2D Platinum program with the use of algorithms from the Melanie application. The relative content, isoelectric points and molecular weights were computed for all identified proteins. Electrophoregrams were analysed by matching spot positions from three independent replications. The proteomes of albumins, globulins and legumin and vicilin fractions of globulins produced up to several hundred spots (proteins). Spots most characteristic of a given fraction were identified by computer analysis and spot matching. The albumin proteome accumulated spots of relatively high intensity over a broad range of pi values of ~4.2-8.1 in 3 molecular weight (MW) ranges: I - high molecular-weight albumins with MW of ~50-110 kDa, II - average molecular-weight albumins with MW of ~20-35 kDa, and III - low molecular-weight albumins with MW of ~13-17 kDa. 2D gel electrophoregrams revealed the presence of 81 characteristic spots, including 24 characteristic of legumin and 14 - of vicilin. Two-dimensional gel electrophoresis proved to be a useful tool for identifying pea proteins. Patterns of spots with similar isoelectric points and different molecular weights or spots with different isoelectric points and similar molecular weights play an important role in proteome analysis. The regions characteristic of albumin, globulin and legumin and vicilin fractions of globulin with typical MW and pi values were identified as the results of performed 2D electrophoretic separations of pea proteins. 2D gel electrophoresis of albumins and the vicilin fraction of globulins revealed the presence of 4 and 2 spots, respectively, representing potentially allergenic proteins. They probably corresponded to vicilin fragments synthesized during post-translational modification of the analysed protein.

A high-throughput semi-automated preparation for filtered synaptoneurosomes.

PubMed

Murphy, Kathryn M; Balsor, Justin; Beshara, Simon; Siu, Caitlin; Pinto, Joshua G A

2014-09-30

Synaptoneurosomes have become an important tool for studying synaptic proteins. The filtered synaptoneurosomes preparation originally developed by Hollingsworth et al. (1985) is widely used and is an easy method to prepare synaptoneurosomes. The hand processing steps in that preparation, however, are labor intensive and have become a bottleneck for current proteomic studies using synaptoneurosomes. For this reason, we developed new steps for tissue homogenization and filtration that transform the preparation of synaptoneurosomes to a high-throughput, semi-automated process. We implemented a standardized protocol with easy to follow steps for homogenizing multiple samples simultaneously using a FastPrep tissue homogenizer (MP Biomedicals, LLC) and then filtering all of the samples in centrifugal filter units (EMD Millipore, Corp). The new steps dramatically reduce the time to prepare synaptoneurosomes from hours to minutes, increase sample recovery, and nearly double enrichment for synaptic proteins. These steps are also compatible with biosafety requirements for working with pathogen infected brain tissue. The new high-throughput semi-automated steps to prepare synaptoneurosomes are timely technical advances for studies of low abundance synaptic proteins in valuable tissue samples. Copyright © 2014 Elsevier B.V. All rights reserved.

Microfabrication of a platform to measure and manipulate the mechanics of engineered microtissues.

PubMed

Ramade, Alexandre; Legant, Wesley R; Picart, Catherine; Chen, Christopher S; Boudou, Thomas

2014-01-01

Engineered tissues can be used to understand fundamental features of biology, develop organotypic in vitro model systems, and as engineered tissue constructs for replacing damaged tissue in vivo. However, a key limitation is an inability to test the wide range of parameters that might impact the engineered tissue in a high-throughput manner and in an environment that mimics the three-dimensional (3D) native architecture. We developed a microfabricated platform to generate arrays of microtissues embedded within 3D micropatterned matrices. Microcantilevers simultaneously constrain microtissue formation and report forces generated by the microtissues in real time, opening the possibility to use high-throughput, low-volume screening for studies on engineered tissues. Thanks to the micrometer scale of the microtissues, this platform is also suitable for high-throughput monitoring of drug-induced effect on architecture and contractility in engineered tissues. Moreover, independent variations of the mechanical stiffness of the cantilevers and collagen matrix allow the measurement and manipulation of the mechanics of the microtissues. Thus, our approach will likely provide valuable opportunities to elucidate how biomechanical, electrical, biochemical, and genetic/epigenetic cues modulate the formation and maturation of 3D engineered tissues. In this chapter, we describe the microfabrication, preparation, and experimental use of such microfabricated tissue gauges. Copyright © 2014 Elsevier Inc. All rights reserved.

Machine learning in computational biology to accelerate high-throughput protein expression.

PubMed

Sastry, Anand; Monk, Jonathan; Tegel, Hanna; Uhlen, Mathias; Palsson, Bernhard O; Rockberg, Johan; Brunk, Elizabeth

2017-08-15

The Human Protein Atlas (HPA) enables the simultaneous characterization of thousands of proteins across various tissues to pinpoint their spatial location in the human body. This has been achieved through transcriptomics and high-throughput immunohistochemistry-based approaches, where over 40 000 unique human protein fragments have been expressed in E. coli. These datasets enable quantitative tracking of entire cellular proteomes and present new avenues for understanding molecular-level properties influencing expression and solubility. Combining computational biology and machine learning identifies protein properties that hinder the HPA high-throughput antibody production pipeline. We predict protein expression and solubility with accuracies of 70% and 80%, respectively, based on a subset of key properties (aromaticity, hydropathy and isoelectric point). We guide the selection of protein fragments based on these characteristics to optimize high-throughput experimentation. We present the machine learning workflow as a series of IPython notebooks hosted on GitHub (https://github.com/SBRG/Protein_ML). The workflow can be used as a template for analysis of further expression and solubility datasets. ebrunk@ucsd.edu or johanr@biotech.kth.se. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Lessons we learned from high-throughput and top-down systems biology analyses about glioma stem cells.

PubMed

Mock, Andreas; Chiblak, Sara; Herold-Mende, Christel

2014-01-01

A growing body of evidence suggests that glioma stem cells (GSCs) account for tumor initiation, therapy resistance, and the subsequent regrowth of gliomas. Thus, continuous efforts have been undertaken to further characterize this subpopulation of less differentiated tumor cells. Although we are able to enrich GSCs, we still lack a comprehensive understanding of GSC phenotypes and behavior. The advent of high-throughput technologies raised hope that incorporation of these newly developed platforms would help to tackle such questions. Since then a couple of comparative genome-, transcriptome- and proteome-wide studies on GSCs have been conducted giving new insights in GSC biology. However, lessons had to be learned in designing high-throughput experiments and some of the resulting conclusions fell short of expectations because they were performed on only a few GSC lines or at one molecular level instead of an integrative poly-omics approach. Despite these shortcomings, our knowledge of GSC biology has markedly expanded due to a number of survival-associated biomarkers as well as glioma-relevant signaling pathways and therapeutic targets being identified. In this article we review recent findings obtained by comparative high-throughput analyses of GSCs. We further summarize fundamental concepts of systems biology as well as its applications for glioma stem cell research.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Waltman, Peter H.; Guo, Jian; Reistetter, Emily Nahas

Micromonas is a unicellular green alga that belongs to the prasinophytes, a sister lineage to land plants. This picoeukaryotic (<2 μm diameter) alga is widespread in the marine environment but still not understood at the cellular level. Here, we examine the mRNA and protein level changes that take place over the course of the day-night cycle using mid-exponential nutrient replete cultures of Micromonas pusilla CCMP1545 grown and analyzed in biological triplicate. During the experiment, samples were collected at key transition points during the diel for evaluation using high-throughput LC-MS proteomics. We also sequenced matched mRNA samples from the same timemore » points, using pair-ended directional Illumina RNA-Seq to investigate the dynamics and relationship between the mRNA and protein expression programs of M. pusilla. Similar to a prior study of the marine cyanobacterium Prochlorococcus, we found significant divergence in the mRNA and proteomics expression dynamics in response to the light:dark cycle. Additionally, expressional responses of genes and the proteins they encoded could also be variable within the same metabolic pathway, such as the oxygenic photosynthesis pathway. A regression framework was used to predict protein levels using both mRNA expression and gene-specific sequence-based features. Several features in the genome sequence were found to influence protein abundance including the codon usage and the length of the 3’ UTR. Collectively, our studies provide insights into the regulation of the proteome over a diel as relationships between the transcriptional and translational programs in the widespread marine green alga Micromonas.« less

Quantitative high-throughput profiling of snake venom gland transcriptomes and proteomes (Ovophis okinavensis and Protobothrops flavoviridis)

PubMed Central

2013-01-01

Background Advances in DNA sequencing and proteomics have facilitated quantitative comparisons of snake venom composition. Most studies have employed one approach or the other. Here, both Illumina cDNA sequencing and LC/MS were used to compare the transcriptomes and proteomes of two pit vipers, Protobothrops flavoviridis and Ovophis okinavensis, which differ greatly in their biology. Results Sequencing of venom gland cDNA produced 104,830 transcripts. The Protobothrops transcriptome contained transcripts for 103 venom-related proteins, while the Ovophis transcriptome contained 95. In both, transcript abundances spanned six orders of magnitude. Mass spectrometry identified peptides from 100% of transcripts that occurred at higher than contaminant (e.g. human keratin) levels, including a number of proteins never before sequenced from snakes. These transcriptomes reveal fundamentally different envenomation strategies. Adult Protobothrops venom promotes hemorrhage, hypotension, incoagulable blood, and prey digestion, consistent with mammalian predation. Ovophis venom composition is less readily interpreted, owing to insufficient pharmacological data for venom serine and metalloproteases, which comprise more than 97.3% of Ovophis transcripts, but only 38.0% of Protobothrops transcripts. Ovophis venom apparently represents a hybrid strategy optimized for frogs and small mammals. Conclusions This study illustrates the power of cDNA sequencing combined with MS profiling. The former quantifies transcript composition, allowing detection of novel proteins, but cannot indicate which proteins are actually secreted, as does MS. We show, for the first time, that transcript and peptide abundances are correlated. This means that MS can be used for quantitative, non-invasive venom profiling, which will be beneficial for studies of endangered species. PMID:24224955

High performance computing environment for multidimensional image analysis

PubMed Central

Rao, A Ravishankar; Cecchi, Guillermo A; Magnasco, Marcelo

2007-01-01

Background The processing of images acquired through microscopy is a challenging task due to the large size of datasets (several gigabytes) and the fast turnaround time required. If the throughput of the image processing stage is significantly increased, it can have a major impact in microscopy applications. Results We present a high performance computing (HPC) solution to this problem. This involves decomposing the spatial 3D image into segments that are assigned to unique processors, and matched to the 3D torus architecture of the IBM Blue Gene/L machine. Communication between segments is restricted to the nearest neighbors. When running on a 2 Ghz Intel CPU, the task of 3D median filtering on a typical 256 megabyte dataset takes two and a half hours, whereas by using 1024 nodes of Blue Gene, this task can be performed in 18.8 seconds, a 478× speedup. Conclusion Our parallel solution dramatically improves the performance of image processing, feature extraction and 3D reconstruction tasks. This increased throughput permits biologists to conduct unprecedented large scale experiments with massive datasets. PMID:17634099

High performance computing environment for multidimensional image analysis.

PubMed

Rao, A Ravishankar; Cecchi, Guillermo A; Magnasco, Marcelo

2007-07-10

The processing of images acquired through microscopy is a challenging task due to the large size of datasets (several gigabytes) and the fast turnaround time required. If the throughput of the image processing stage is significantly increased, it can have a major impact in microscopy applications. We present a high performance computing (HPC) solution to this problem. This involves decomposing the spatial 3D image into segments that are assigned to unique processors, and matched to the 3D torus architecture of the IBM Blue Gene/L machine. Communication between segments is restricted to the nearest neighbors. When running on a 2 Ghz Intel CPU, the task of 3D median filtering on a typical 256 megabyte dataset takes two and a half hours, whereas by using 1024 nodes of Blue Gene, this task can be performed in 18.8 seconds, a 478x speedup. Our parallel solution dramatically improves the performance of image processing, feature extraction and 3D reconstruction tasks. This increased throughput permits biologists to conduct unprecedented large scale experiments with massive datasets.

3D Cultivation Techniques for Primary Human Hepatocytes

PubMed Central

Bachmann, Anastasia; Moll, Matthias; Gottwald, Eric; Nies, Cordula; Zantl, Roman; Wagner, Helga; Burkhardt, Britta; Sánchez, Juan J. Martínez; Ladurner, Ruth; Thasler, Wolfgang; Damm, Georg; Nussler, Andreas K.

2015-01-01

One of the main challenges in drug development is the prediction of in vivo toxicity based on in vitro data. The standard cultivation system for primary human hepatocytes is based on monolayer cultures, even if it is known that these conditions result in a loss of hepatocyte morphology and of liver-specific functions, such as drug-metabolizing enzymes and transporters. As it has been demonstrated that hepatocytes embedded between two sheets of collagen maintain their function, various hydrogels and scaffolds for the 3D cultivation of hepatocytes have been developed. To further improve or maintain hepatic functions, 3D cultivation has been combined with perfusion. In this manuscript, we discuss the benefits and drawbacks of different 3D microfluidic devices. For most systems that are currently available, the main issues are the requirement of large cell numbers, the low throughput, and expensive equipment, which render these devices unattractive for research and the drug-developing industry. A higher acceptance of these devices could be achieved by their simplification and their compatibility with high-throughput, as both aspects are of major importance for a user-friendly device. PMID:27600213

BIG: a large-scale data integration tool for renal physiology

PubMed Central

Zhao, Yue; Yang, Chin-Rang; Raghuram, Viswanathan; Parulekar, Jaya

2016-01-01

Due to recent advances in high-throughput techniques, we and others have generated multiple proteomic and transcriptomic databases to describe and quantify gene expression, protein abundance, or cellular signaling on the scale of the whole genome/proteome in kidney cells. The existence of so much data from diverse sources raises the following question: “How can researchers find information efficiently for a given gene product over all of these data sets without searching each data set individually?” This is the type of problem that has motivated the “Big-Data” revolution in Data Science, which has driven progress in fields such as marketing. Here we present an online Big-Data tool called BIG (Biological Information Gatherer) that allows users to submit a single online query to obtain all relevant information from all indexed databases. BIG is accessible at http://big.nhlbi.nih.gov/. PMID:27279488

Statistical characterization of multiple-reaction monitoring mass spectrometry (MRM-MS) assays for quantitative proteomics

PubMed Central

2012-01-01

Multiple reaction monitoring mass spectrometry (MRM-MS) with stable isotope dilution (SID) is increasingly becoming a widely accepted assay for the quantification of proteins and peptides. These assays have shown great promise in relatively high throughput verification of candidate biomarkers. While the use of MRM-MS assays is well established in the small molecule realm, their introduction and use in proteomics is relatively recent. As such, statistical and computational methods for the analysis of MRM-MS data from proteins and peptides are still being developed. Based on our extensive experience with analyzing a wide range of SID-MRM-MS data, we set forth a methodology for analysis that encompasses significant aspects ranging from data quality assessment, assay characterization including calibration curves, limits of detection (LOD) and quantification (LOQ), and measurement of intra- and interlaboratory precision. We draw upon publicly available seminal datasets to illustrate our methods and algorithms. PMID:23176545

Statistical characterization of multiple-reaction monitoring mass spectrometry (MRM-MS) assays for quantitative proteomics.

PubMed

Mani, D R; Abbatiello, Susan E; Carr, Steven A

2012-01-01

Multiple reaction monitoring mass spectrometry (MRM-MS) with stable isotope dilution (SID) is increasingly becoming a widely accepted assay for the quantification of proteins and peptides. These assays have shown great promise in relatively high throughput verification of candidate biomarkers. While the use of MRM-MS assays is well established in the small molecule realm, their introduction and use in proteomics is relatively recent. As such, statistical and computational methods for the analysis of MRM-MS data from proteins and peptides are still being developed. Based on our extensive experience with analyzing a wide range of SID-MRM-MS data, we set forth a methodology for analysis that encompasses significant aspects ranging from data quality assessment, assay characterization including calibration curves, limits of detection (LOD) and quantification (LOQ), and measurement of intra- and interlaboratory precision. We draw upon publicly available seminal datasets to illustrate our methods and algorithms.

Systematic cloning of an ORFeome using the Gateway system.

PubMed

Matsuyama, Akihisa; Yoshida, Minoru

2009-01-01

With the completion of the genome projects, there are increasing demands on the experimental systems that enable to exploit the entire set of protein-coding open reading frames (ORFs), viz. ORFeome, en masse. Systematic proteomic studies based on cloned ORFeomes are called "reverse proteomics," and have been launched in many organisms in recent years. Cloning of an ORFeome is such an attractive way for comprehensive understanding of biological phenomena, but is a challenging and daunting task. However, recent advances in techniques for DNA cloning using site-specific recombination and for high-throughput experimental techniques have made it feasible to clone an ORFeome with the minimum of exertion. The Gateway system is one of such the approaches, employing the recombination reaction of the bacteriophage lambda. Combining traditional DNA manipulation methods with modern technique of the recombination-based cloning system, it is possible to clone an ORFeome of an organism on an individual level.

Lignases and aldo-keto reductases for conversion of lignin-containing materials to fermentable products

DOEpatents

Scharf, Michael; Sethi, Amit

2016-09-13

Termites have specialized digestive systems that overcome the lignin barrier in wood to release fermentable simple sugars. Using the termite Reticulitermes flavipes and its gut symbionts, high-throughput titanium pyrosequencing and proteomics approaches experimentally compared the effects of lignin-containing diets on host-symbiont digestome composition. Proteomic investigations and functional digestive studies with recombinant lignocellulases conducted in parallel provided strong evidence of congruence at the transcription and translational levels and provide enzymatic strategies for overcoming recalcitrant lignin barriers in biofuel feedstocks. Briefly described, therefore, the disclosure provides a system for generating a fermentable product from a lignified plant material, the system comprising a cooperating series of at least two catalytically active polypeptides, where said catalytically active polypeptides are selected from the group consisting of: cellulase Cell-1, .beta.-glu cellulase, an aldo-keto-reductase, a catalase, a laccase, and an endo-xylanase.

Nucleic acid programmable protein array a just-in-time multiplexed protein expression and purification platform.

PubMed

Qiu, Ji; LaBaer, Joshua

2011-01-01

Systematic study of proteins requires the availability of thousands of proteins in functional format. However, traditional recombinant protein expression and purification methods have many drawbacks for such study at the proteome level. We have developed an innovative in situ protein expression and capture system, namely NAPPA (nucleic acid programmable protein array), where C-terminal tagged proteins are expressed using an in vitro expression system and efficiently captured/purified by antitag antibodies coprinted at each spot. The NAPPA technology presented in this chapter enable researchers to produce and display fresh proteins just in time in a multiplexed high-throughput fashion and utilize them for various downstream biochemical researches of interest. This platform could revolutionize the field of functional proteomics with it ability to produce thousands of spatially separated proteins in high density with narrow dynamic rand of protein concentrations, reproducibly and functionally. Copyright © 2011 Elsevier Inc. All rights reserved.

pyQms enables universal and accurate quantification of mass spectrometry data.

PubMed

Leufken, Johannes; Niehues, Anna; Sarin, L Peter; Wessel, Florian; Hippler, Michael; Leidel, Sebastian A; Fufezan, Christian

2017-10-01

Quantitative mass spectrometry (MS) is a key technique in many research areas (1), including proteomics, metabolomics, glycomics, and lipidomics. Because all of the corresponding molecules can be described by chemical formulas, universal quantification tools are highly desirable. Here, we present pyQms, an open-source software for accurate quantification of all types of molecules measurable by MS. pyQms uses isotope pattern matching that offers an accurate quality assessment of all quantifications and the ability to directly incorporate mass spectrometer accuracy. pyQms is, due to its universal design, applicable to every research field, labeling strategy, and acquisition technique. This opens ultimate flexibility for researchers to design experiments employing innovative and hitherto unexplored labeling strategies. Importantly, pyQms performs very well to accurately quantify partially labeled proteomes in large scale and high throughput, the most challenging task for a quantification algorithm. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Enrichment of plasma membrane proteins using nanoparticle pellicles: comparison between silica and higher density nanoparticles

PubMed Central

Choksawangkarn, Waeowalee; Kim, Sung-Kyoung; Cannon, Joe R.; Edwards, Nathan J.; Lee, Sang Bok; Fenselau, Catherine

2013-01-01

Proteomic and other characterization of plasma membrane proteins is made difficult by their low abundance, hydrophobicity, frequent carboxylation and dynamic population. We and others have proposed that underrepresentation in LC-MS/MS analysis can be partially compensated by enriching the plasma membrane and its proteins using cationic nanoparticle pellicles. The nanoparticles increase the density of plasma membrane sheets and thus enhance separation by centrifugation from other lysed cellular components. Herein we test the hypothesis that the use of nanoparticles with increased densities can provide enhanced enrichment of plasma membrane proteins for proteomic analysis. Multiple myeloma cells were grown and coated in suspension with three different pellicles of three different densities and both pellicle coated and uncoated suspensions analyzed by high-throughput LC-MS/MS. Enrichment was evaluated by the total number and the spectral counts of identified plasma membrane proteins. PMID:23289353

Development of Proteomics-Based Fungicides: New Strategies for Environmentally Friendly Control of Fungal Plant Diseases

PubMed Central

Acero, Francisco Javier Fernández; Carbú, María; El-Akhal, Mohamed Rabie; Garrido, Carlos; González-Rodríguez, Victoria E.; Cantoral, Jesús M.

2011-01-01

Proteomics has become one of the most relevant high-throughput technologies. Several approaches have been used for studying, for example, tumor development, biomarker discovery, or microbiology. In this “post-genomic” era, the relevance of these studies has been highlighted as the phenotypes determined by the proteins and not by the genotypes encoding them that is responsible for the final phenotypes. One of the most interesting outcomes of these technologies is the design of new drugs, due to the discovery of new disease factors that may be candidates for new therapeutic targets. To our knowledge, no commercial fungicides have been developed from targeted molecular research, this review will shed some light on future prospects. We will summarize previous research efforts and discuss future innovations, focused on the fight against one of the main agents causing a devastating crops disease, fungal phytopathogens. PMID:21340014

Seminal plasma proteome of electroejaculated Bos indicus bulls.

PubMed

Rego, J P A; Crisp, J M; Moura, A A; Nouwens, A S; Li, Y; Venus, B; Corbet, N J; Corbet, D H; Burns, B M; Boe-Hansen, G B; McGowan, M R

2014-07-01

The present study describes the seminal plasma proteome of Bos indicus bulls. Fifty-six, 24-month old Australian Brahman sires were evaluated and subjected to electroejaculation. Seminal plasma proteins were separated by 2-D SDS-PAGE and identified by mass spectrometry. The percentage of progressively motile and morphologically normal sperm of the bulls were 70.4 ± 2.3 and 64 ± 3.2%, respectively. A total of 108 spots were identified in the 2-D maps, corresponding to 46 proteins. Binder of sperm proteins accounted for 55.8% of all spots detected in the maps and spermadhesins comprised the second most abundant constituents. Other proteins of the Bos indicus seminal plasma include clusterin, albumin, transferrin, metalloproteinase inhibitor 2, osteopontin, epididymal secretory protein E1, apolipoprotein A-1, heat shock 70 kDa protein, glutathione peroxidase 3, cathelicidins, alpha-enolase, tripeptidyl-peptidase 1, zinc-alpha-2-glycoprotein, plasma serine protease inhibitor, beta 2-microglobulin, proteasome subunit beta type-4, actin, cathepsins, nucleobinding-1, protein S100-A9, hemoglobin subunit alpha, cadherin-1, angiogenin-1, fibrinogen alpha and beta chain, ephirin-A1, protein DJ-1, serpin A3-7, alpha-2-macroglobulin, annexin A1, complement factor B, polymeric immunoglobulin receptor, seminal ribonuclease, ribonuclease-4, prostaglandin-H2 d-isomerase, platelet-activating factor acetylhydrolase, and phosphoglycerate kinase 1. In conclusion, this work uniquely portrays the Bos indicus seminal fluid proteome, based on samples from a large set of animals representing the Brahman cattle of the tropical Northern Australia. Based on putative biochemical attributes, seminal proteins act during sperm maturation, protection, capacitation and fertilization. Copyright © 2014. Published by Elsevier B.V.

Simulating Local Area Network Protocols with the General Purpose Simulation System (GPSS)

DTIC Science & Technology

1990-03-01

generation 15 3.1.2 Frame delivery . 15 3.2 Model artifices 16 3.3 Model variables 17 3.4 Simulation results 18 4. EXTERNAL PROCEDURES USED IN SIMULATION 19...46 15. Token Ring: Frame generation process 47 16. Token Ring: Frame delivery process 48 17 . Token Ring: Mean transfer delay vs mean throughput 49...assumed to be zero were replaced by the maximum values specified in the ANSI 802.3 standard (viz &MI=6, &M2=3, &M3= 17 , &D1=18, &D2=3, &D4=4, &D7=3, and

Proteome Analysis of Cytoplasmatic and Plastidic β-Carotene Lipid Droplets in Dunaliella bardawil1[OPEN

PubMed Central

Davidi, Lital; Levin, Yishai; Ben-Dor, Shifra; Pick, Uri

2015-01-01

The halotolerant green alga Dunaliella bardawil is unique in that it accumulates under stress two types of lipid droplets: cytoplasmatic lipid droplets (CLD) and β-carotene-rich (βC) plastoglobuli. Recently, we isolated and analyzed the lipid and pigment compositions of these lipid droplets. Here, we describe their proteome analysis. A contamination filter and an enrichment filter were utilized to define core proteins. A proteome database of Dunaliella salina/D. bardawil was constructed to aid the identification of lipid droplet proteins. A total of 124 and 42 core proteins were identified in βC-plastoglobuli and CLD, respectively, with only eight common proteins. Dunaliella spp. CLD resemble cytoplasmic droplets from Chlamydomonas reinhardtii and contain major lipid droplet-associated protein and enzymes involved in lipid and sterol metabolism. The βC-plastoglobuli proteome resembles the C. reinhardtii eyespot and Arabidopsis (Arabidopsis thaliana) plastoglobule proteomes and contains carotene-globule-associated protein, plastid-lipid-associated protein-fibrillins, SOUL heme-binding proteins, phytyl ester synthases, β-carotene biosynthesis enzymes, and proteins involved in membrane remodeling/lipid droplet biogenesis: VESICLE-INDUCING PLASTID PROTEIN1, synaptotagmin, and the eyespot assembly proteins EYE3 and SOUL3. Based on these and previous results, we propose models for the biogenesis of βC-plastoglobuli and the biosynthesis of β-carotene within βC-plastoglobuli and hypothesize that βC-plastoglobuli evolved from eyespot lipid droplets. PMID:25404729

Efficient Exploitation of Separation Space in Two-Dimensional Liquid Chromatography System for Comprehensive and Efficient Proteomic Analyses.

PubMed

Lee, Hangyeore; Mun, Dong-Gi; So, Jeong Eun; Bae, Jingi; Kim, Hokeun; Masselon, Christophe; Lee, Sang-Won

2016-12-06

Proteomics aims to achieve complete profiling of the protein content and protein modifications in cells, tissues, and biofluids and to quantitatively determine changes in their abundances. This information serves to elucidate cellular processes and signaling pathways and to identify candidate protein biomarkers and/or therapeutic targets. Analyses must therefore be both comprehensive and efficient. Here, we present a novel online two-dimensional reverse-phase/reverse-phase liquid chromatography separation platform, which is based on a newly developed online noncontiguous fractionating and concatenating device (NCFC fractionator). In bottom-up proteomics analyses of a complex proteome, this system provided significantly improved exploitation of the separation space of the two RPs, considerably increasing the numbers of peptides identified compared to a contiguous 2D-RP/RPLC method. The fully automated online 2D-NCFC-RP/RPLC system bypassed a number of labor-intensive manual processes required with the previously described offline 2D-NCFC RP/RPLC method, and thus, it offers minimal sample loss in a context of highly reproducible 2D-RP/RPLC experiments.

2D-DIGE-based proteome expression changes in leaves of rice seedlings exposed to low-level gamma radiation at Iitate village, Fukushima

PubMed Central

Hayashi, Gohei; Moro, Carlo F; Rohila, Jai Singh; Shibato, Junko; Kubo, Akihiro; Imanaka, Tetsuji; Kimura, Shinzo; Ozawa, Shoji; Fukutani, Satoshi; Endo, Satoru; Ichikawa, Katsuki; Agrawal, Ganesh Kumar; Shioda, Seiji; Hori, Motohide; Fukumoto, Manabu; Rakwal, Randeep

2015-01-01

The present study continues our previous research on investigating the biological effects of low-level gamma radiation in rice at the heavily contaminated Iitate village in Fukushima, by extending the experiments to unraveling the leaf proteome. 14-days-old plants of Japonica rice (Oryza sativa L. cv. Nipponbare) were subjected to gamma radiation level of upto 4 µSv/h, for 72 h. Following exposure, leaf samples were taken from the around 190 µSv/3 d exposed seedling and total proteins were extracted. The gamma irradiated leaf and control leaf (harvested at the start of the experiment) protein lysates were used in a 2-D differential gel electrophoresis (2D-DIGE) experiment using CyDye labeling in order to asses which spots were differentially represented, a novelty of the study. 2D-DIGE analysis revealed 91 spots with significantly different expression between samples (60 positive, 31 negative). MALDI-TOF and TOF/TOF mass spectrometry analyses revealed those as comprising of 59 different proteins (50 up-accumulated, 9 down-accumulated). The identified proteins were subdivided into 10 categories, according to their biological function, which indicated that the majority of the differentially expressed proteins consisted of the general (non-energy) metabolism and stress response categories. Proteome-wide data point to some effects of low-level gamma radiation exposure on the metabolism of rice leaves. PMID:26451896

Proteome dynamics of cold-acclimating Rhododendron species contrasting in their freezing tolerance and thermonasty response

USDA-ARS?s Scientific Manuscript database

In the present study we used 2D-DIGE technique to document the Rhododendron proteome during the seasonal development of cold hardiness. We selected two genotypes with different cold hardiness levels. This enabled us to perform comparative analysis of their proteome profiles and screen differentially...

Simulation of Two Dimensional Electrophoresis and Tandem Mass Spectrometry for Teaching Proteomics

ERIC Educational Resources Information Center

Fisher, Amanda; Sekera, Emily; Payne, Jill; Craig, Paul

2012-01-01

In proteomics, complex mixtures of proteins are separated (usually by chromatography or electrophoresis) and identified by mass spectrometry. We have created 2DE Tandem MS, a computer program designed for use in the biochemistry, proteomics, or bioinformatics classroom. It contains two simulations--2D electrophoresis and tandem mass spectrometry.…

The effect of electroacupuncture on proteomic changes in the motor cortex of 6-OHDA Parkinsonian rats.

PubMed

Li, Min; Li, Lijuan; Wang, Ke; Su, Wenting; Jia, Jun; Wang, Xiaomin

2017-10-15

Electroacupuncture (EA) has been reported to alleviate motor deficits in Parkinson's disease (PD) patients, and PD animal models. However, the mechanisms by which EA improves motor function have not been investigated. We have employed a 6-hydroxydopamine (6-OHDA) unilateral injection induced PD model to investigate whether EA alters protein expression in the motor cortex. We found that 4weeks of EA treatment significantly improved spontaneous floor plane locomotion and rotarod performance. High-throughput proteomic analysis in the motor cortex was employed. The expression of 54 proteins were altered in the unlesioned motor cortex, and 102 protein expressions were altered in the lesioned motor cortex of 6-OHDA rats compared to sham rats. Compared to non-treatment PD control, EA treatment reversed 6 proteins in unlesioned and 19 proteins in lesioned motor cortex. The present study demonstrated that PD induces proteomic changes in the motor cortex, some of which are rescued by EA treatment. These targeted proteins were mainly involved in increasing autophagy, mRNA processing and ATP binding and maintaining the balance of neurotransmitters. Copyright © 2017 Elsevier B.V. All rights reserved.

Assessing the Exoproteome of Marine Bacteria, Lesson from a RTX-Toxin Abundantly Secreted by Phaeobacter Strain DSM 17395

PubMed Central

Durighello, Emie; Christie-Oleza, Joseph Alexander; Armengaud, Jean

2014-01-01

Bacteria from the Roseobacter clade are abundant in surface marine ecosystems as over 10% of bacterial cells in the open ocean and 20% in coastal waters belong to this group. In order to document how these marine bacteria interact with their environment, we analyzed the exoproteome of Phaeobacter strain DSM 17395. We grew the strain in marine medium, collected the exoproteome and catalogued its content with high-throughput nanoLC-MS/MS shotgun proteomics. The major component represented 60% of the total protein content but was refractory to either classical proteomic identification or proteogenomics. We de novo sequenced this abundant protein with high-resolution tandem mass spectra which turned out being the 53 kDa RTX-toxin ZP_02147451. It comprised a peptidase M10 serralysin domain. We explained its recalcitrance to trypsin proteolysis and proteomic identification by its unusual low number of basic residues. We found this is a conserved trait in RTX-toxins from Roseobacter strains which probably explains their persistence in the harsh conditions around bacteria. Comprehensive analysis of exoproteomes from environmental bacteria should take into account this proteolytic recalcitrance. PMID:24586966

Assessing the exoproteome of marine bacteria, lesson from a RTX-toxin abundantly secreted by Phaeobacter strain DSM 17395.

PubMed

Durighello, Emie; Christie-Oleza, Joseph Alexander; Armengaud, Jean

2014-01-01

Bacteria from the Roseobacter clade are abundant in surface marine ecosystems as over 10% of bacterial cells in the open ocean and 20% in coastal waters belong to this group. In order to document how these marine bacteria interact with their environment, we analyzed the exoproteome of Phaeobacter strain DSM 17395. We grew the strain in marine medium, collected the exoproteome and catalogued its content with high-throughput nanoLC-MS/MS shotgun proteomics. The major component represented 60% of the total protein content but was refractory to either classical proteomic identification or proteogenomics. We de novo sequenced this abundant protein with high-resolution tandem mass spectra which turned out being the 53 kDa RTX-toxin ZP_02147451. It comprised a peptidase M10 serralysin domain. We explained its recalcitrance to trypsin proteolysis and proteomic identification by its unusual low number of basic residues. We found this is a conserved trait in RTX-toxins from Roseobacter strains which probably explains their persistence in the harsh conditions around bacteria. Comprehensive analysis of exoproteomes from environmental bacteria should take into account this proteolytic recalcitrance.

Redox proteomics screening cellular factors associated with oxidative stress in hepatocarcinogenesis.

PubMed

Zhou, Li; Wen, Ji; Huang, Zhao; Nice, Edouard C; Huang, Canhua; Zhang, Haiyuan; Li, Qifu

2017-03-01

Liver cancer is a major global health problem being the sixth most common cancer and the third cause of cancer-related death, with hepatocellular carcinoma (HCC) representing more than 90% of primary liver cancers. Mounting evidence suggests that, compared with their normal counterparts, many types of cancer cell have increased levels of ROS. Therefore, cancer cells need to combat high levels of ROS, especially at early stages of tumor development. Recent studies have revealed that ROS-mediated regulation of redox-sensitive proteins (redox sensors) is involved in the pathogenesis and/or progression of many human diseases, including cancer. Unraveling the altered functions of redox sensors and the underlying mechanisms in hepatocarcinogenesis is critical for the development of novel cancer therapeutics. For this reason, redox proteomics has been developed for the high-throughput screening of redox sensors, which will benefit the development of novel therapeutic strategies for the treatment of HCC. In this review, we will briefly introduce several novel redox proteomics techniques that are currently available to study various oxidative modifications in hepatocarcinogenesis and summarize the most important discoveries in the study of redox processes related to the development and progression of HCC. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Display technologies: application for the discovery of drug and gene delivery agents

PubMed Central

Sergeeva, Anna; Kolonin, Mikhail G.; Molldrem, Jeffrey J.; Pasqualini, Renata; Arap, Wadih

2007-01-01

Recognition of molecular diversity of cell surface proteomes in disease is essential for the development of targeted therapies. Progress in targeted therapeutics requires establishing effective approaches for high-throughput identification of agents specific for clinically relevant cell surface markers. Over the past decade, a number of platform strategies have been developed to screen polypeptide libraries for ligands targeting receptors selectively expressed in the context of various cell surface proteomes. Streamlined procedures for identification of ligand-receptor pairs that could serve as targets in disease diagnosis, profiling, imaging and therapy have relied on the display technologies, in which polypeptides with desired binding profiles can be serially selected, in a process called biopanning, based on their physical linkage with the encoding nucleic acid. These technologies include virus/phage display, cell display, ribosomal display, mRNA display and covalent DNA display (CDT), with phage display being by far the most utilized. The scope of this review is the recent advancements in the display technologies with a particular emphasis on molecular mapping of cell surface proteomes with peptide phage display. Prospective applications of targeted compounds derived from display libraries in the discovery of targeted drugs and gene therapy vectors are discussed. PMID:17123658

Constraints imposed by non-functional protein–protein interactions on gene expression and proteome size

PubMed Central

Zhang, Jingshan; Maslov, Sergei; Shakhnovich, Eugene I

2008-01-01

Crowded intracellular environments present a challenge for proteins to form functional specific complexes while reducing non-functional interactions with promiscuous non-functional partners. Here we show how the need to minimize the waste of resources to non-functional interactions limits the proteome diversity and the average concentration of co-expressed and co-localized proteins. Using the results of high-throughput Yeast 2-Hybrid experiments, we estimate the characteristic strength of non-functional protein–protein interactions. By combining these data with the strengths of specific interactions, we assess the fraction of time proteins spend tied up in non-functional interactions as a function of their overall concentration. This allows us to sketch the phase diagram for baker's yeast cells using the experimentally measured concentrations and subcellular localization of their proteins. The positions of yeast compartments on the phase diagram are consistent with our hypothesis that the yeast proteome has evolved to operate closely to the upper limit of its size, whereas keeping individual protein concentrations sufficiently low to reduce non-functional interactions. These findings have implication for conceptual understanding of intracellular compartmentalization, multicellularity and differentiation. PMID:18682700

The Role of Proteomics in the Diagnosis and Treatment of Women's Cancers: Current Trends in Technology and Future Opportunities

PubMed Central

Breuer, Eun-Kyoung Yim; Murph, Mandi M.

2011-01-01

Technological and scientific innovations over the last decade have greatly contributed to improved diagnostics, predictive models, and prognosis among cancers affecting women. In fact, an explosion of information in these areas has almost assured future generations that outcomes in cancer will continue to improve. Herein we discuss the current status of breast, cervical, and ovarian cancers as it relates to screening, disease diagnosis, and treatment options. Among the differences in these cancers, it is striking that breast cancer has multiple predictive tests based upon tumor biomarkers and sophisticated, individualized options for prescription therapeutics while ovarian cancer lacks these tools. In addition, cervical cancer leads the way in innovative, cancer-preventative vaccines and multiple screening options to prevent disease progression. For each of these malignancies, emerging proteomic technologies based upon mass spectrometry, stable isotope labeling with amino acids, high-throughput ELISA, tissue or protein microarray techniques, and click chemistry in the pursuit of activity-based profiling can pioneer the next generation of discovery. We will discuss six of the latest techniques to understand proteomics in cancer and highlight research utilizing these techniques with the goal of improvement in the management of women's cancers. PMID:21886869

Study of cellular oncometabolism via multidimensional protein identification technology.

PubMed

Aukim-Hastie, Claire; Garbis, Spiros D

2014-01-01

Cellular proteomics is becoming a widespread clinical application, matching the definition of bench-to-bedside translation. Among various fields of investigation, this approach can be applied to the study of the metabolic alterations that accompany oncogenesis and tumor progression, which are globally referred to as oncometabolism. Here, we describe a multidimensional protein identification technology (MuDPIT)-based strategy that can be employed to study the cellular proteome of malignant cells and tissues. This method has previously been shown to be compatible with the reproducible, in-depth analysis of up to a thousand proteins in clinical samples. The possibility to employ this technique to study clinical specimens demonstrates its robustness. MuDPIT is advantageous as compared to other approaches because it is direct, highly sensitive, and reproducible, it provides high resolution with ultra-high mass accuracy, it allows for relative quantifications, and it is compatible with multiplexing (thus limiting costs).This method enables the direct assessment of the proteomic profile of neoplastic cells and tissues and could be employed in the near future as a high-throughput, rapid, quantitative, and cost-effective screening platform for clinical samples. © 2014 Elsevier Inc. All rights reserved.

Microbial genomics, transcriptomics and proteomics: new discoveries in decomposition research using complementary methods.

PubMed

Baldrian, Petr; López-Mondéjar, Rubén

2014-02-01

Molecular methods for the analysis of biomolecules have undergone rapid technological development in the last decade. The advent of next-generation sequencing methods and improvements in instrumental resolution enabled the analysis of complex transcriptome, proteome and metabolome data, as well as a detailed annotation of microbial genomes. The mechanisms of decomposition by model fungi have been described in unprecedented detail by the combination of genome sequencing, transcriptomics and proteomics. The increasing number of available genomes for fungi and bacteria shows that the genetic potential for decomposition of organic matter is widespread among taxonomically diverse microbial taxa, while expression studies document the importance of the regulation of expression in decomposition efficiency. Importantly, high-throughput methods of nucleic acid analysis used for the analysis of metagenomes and metatranscriptomes indicate the high diversity of decomposer communities in natural habitats and their taxonomic composition. Today, the metaproteomics of natural habitats is of interest. In combination with advanced analytical techniques to explore the products of decomposition and the accumulation of information on the genomes of environmentally relevant microorganisms, advanced methods in microbial ecophysiology should increase our understanding of the complex processes of organic matter transformation.

Linking Proteomic and Transcriptional Data through the Interactome and Epigenome Reveals a Map of Oncogene-induced Signaling

PubMed Central

Huang, Shao-shan Carol; Clarke, David C.; Gosline, Sara J. C.; Labadorf, Adam; Chouinard, Candace R.; Gordon, William; Lauffenburger, Douglas A.; Fraenkel, Ernest

2013-01-01

Cellular signal transduction generally involves cascades of post-translational protein modifications that rapidly catalyze changes in protein-DNA interactions and gene expression. High-throughput measurements are improving our ability to study each of these stages individually, but do not capture the connections between them. Here we present an approach for building a network of physical links among these data that can be used to prioritize targets for pharmacological intervention. Our method recovers the critical missing links between proteomic and transcriptional data by relating changes in chromatin accessibility to changes in expression and then uses these links to connect proteomic and transcriptome data. We applied our approach to integrate epigenomic, phosphoproteomic and transcriptome changes induced by the variant III mutation of the epidermal growth factor receptor (EGFRvIII) in a cell line model of glioblastoma multiforme (GBM). To test the relevance of the network, we used small molecules to target highly connected nodes implicated by the network model that were not detected by the experimental data in isolation and we found that a large fraction of these agents alter cell viability. Among these are two compounds, ICG-001, targeting CREB binding protein (CREBBP), and PKF118–310, targeting β-catenin (CTNNB1), which have not been tested previously for effectiveness against GBM. At the level of transcriptional regulation, we used chromatin immunoprecipitation sequencing (ChIP-Seq) to experimentally determine the genome-wide binding locations of p300, a transcriptional co-regulator highly connected in the network. Analysis of p300 target genes suggested its role in tumorigenesis. We propose that this general method, in which experimental measurements are used as constraints for building regulatory networks from the interactome while taking into account noise and missing data, should be applicable to a wide range of high-throughput datasets. PMID:23408876

Fast assembling of neuron fragments in serial 3D sections.

PubMed

Chen, Hanbo; Iascone, Daniel Maxim; da Costa, Nuno Maçarico; Lein, Ed S; Liu, Tianming; Peng, Hanchuan

2017-09-01

Reconstructing neurons from 3D image-stacks of serial sections of thick brain tissue is very time-consuming and often becomes a bottleneck in high-throughput brain mapping projects. We developed NeuronStitcher, a software suite for stitching non-overlapping neuron fragments reconstructed in serial 3D image sections. With its efficient algorithm and user-friendly interface, NeuronStitcher has been used successfully to reconstruct very large and complex human and mouse neurons.

The proteome: structure, function and evolution

PubMed Central

Fleming, Keiran; Kelley, Lawrence A; Islam, Suhail A; MacCallum, Robert M; Muller, Arne; Pazos, Florencio; Sternberg, Michael J.E

2006-01-01

This paper reports two studies to model the inter-relationships between protein sequence, structure and function. First, an automated pipeline to provide a structural annotation of proteomes in the major genomes is described. The results are stored in a database at Imperial College, London (3D-GENOMICS) that can be accessed at www.sbg.bio.ic.ac.uk. Analysis of the assignments to structural superfamilies provides evolutionary insights. 3D-GENOMICS is being integrated with related proteome annotation data at University College London and the European Bioinformatics Institute in a project known as e-protein (http://www.e-protein.org/). The second topic is motivated by the developments in structural genomics projects in which the structure of a protein is determined prior to knowledge of its function. We have developed a new approach PHUNCTIONER that uses the gene ontology (GO) classification to supervise the extraction of the sequence signal responsible for protein function from a structure-based sequence alignment. Using GO we can obtain profiles for a range of specificities described in the ontology. In the region of low sequence similarity (around 15%), our method is more accurate than assignment from the closest structural homologue. The method is also able to identify the specific residues associated with the function of the protein family. PMID:16524832

Proteomic analysis on roots of Oenothera glazioviana under copper-stress conditions.

PubMed

Wang, Chong; Wang, Jie; Wang, Xiao; Xia, Yan; Chen, Chen; Shen, Zhenguo; Chen, Yahua

2017-09-06

Proteomic studies were performed to identify proteins involved in the response of Oenothera glazioviana seedlings under Cu stress. Exposure of 28-d-old seedlings to 50 μM CuSO4 for 3 d led to inhibition of shoot and root growth as well as a considerable increase in the level of lipid peroxidation in the roots. Cu absorbed by O. glazioviana accumulated more easily in the root than in the shoot. Label-free proteomic analysis indicated 58 differentially abundant proteins (DAPs) of the total 3,149 proteins in the roots of O. glazioviana seedlings, of which 36 were upregulated and 22 were downregulated under Cu stress conditions. Gene Ontology analysis showed that most of the identified proteins could be annotated to signal transduction, detoxification, stress defence, carbohydrate, energy, and protein metabolism, development, and oxidoreduction. We also retrieved 13 proteins from the enriched Kyoto Encyclopaedia of Genes and Genomes and the protein-protein interaction databases related to various pathways, including the citric acid (CA) cycle. Application of exogenous CA to O. glazioviana seedlings exposed to Cu alleviated the stress symptoms. Overall, this study provided new insights into the molecular mechanisms of plant response to Cu at the protein level in relation to soil properties.

Identifying and quantifying proteolytic events and the natural N terminome by terminal amine isotopic labeling of substrates.

PubMed

Kleifeld, Oded; Doucet, Alain; Prudova, Anna; auf dem Keller, Ulrich; Gioia, Magda; Kizhakkedathu, Jayachandran N; Overall, Christopher M

2011-09-22

Analysis of the sequence and nature of protein N termini has many applications. Defining the termini of proteins for proteome annotation in the Human Proteome Project is of increasing importance. Terminomics analysis of protease cleavage sites in degradomics for substrate discovery is a key new application. Here we describe the step-by-step procedures for performing terminal amine isotopic labeling of substrates (TAILS), a 2- to 3-d (depending on method of labeling) high-throughput method to identify and distinguish protease-generated neo-N termini from mature protein N termini with all natural modifications with high confidence. TAILS uses negative selection to enrich for all N-terminal peptides and uses primary amine labeling-based quantification as the discriminating factor. Labeling is versatile and suited to many applications, including biochemical and cell culture analyses in vitro; in vivo analyses using tissue samples from animal and human sources can also be readily performed. At the protein level, N-terminal and lysine amines are blocked by dimethylation (formaldehyde/sodium cyanoborohydride) and isotopically labeled by incorporating heavy and light dimethylation reagents or stable isotope labeling with amino acids in cell culture labels. Alternatively, easy multiplex sample analysis can be achieved using amine blocking and labeling with isobaric tags for relative and absolute quantification, also known as iTRAQ. After tryptic digestion, N-terminal peptide separation is achieved using a high-molecular-weight dendritic polyglycerol aldehyde polymer that binds internal tryptic and C-terminal peptides that now have N-terminal alpha amines. The unbound naturally blocked (acetylation, cyclization, methylation and so on) or labeled mature N-terminal and neo-N-terminal peptides are recovered by ultrafiltration and analyzed by tandem mass spectrometry (MS/MS). Hierarchical substrate winnowing discriminates substrates from the background proteolysis products and non-cleaved proteins by peptide isotope quantification and bioinformatics search criteria.

Protein expression profiles of human lymph and plasma mapped by 2D-DIGE and 1D SDS–PAGE coupled with nanoLC–ESI–MS/MS bottom-up proteomics

PubMed Central

Clement, Cristina C.; Aphkhazava, David; Nieves, Edward; Callaway, Myrasol; Olszewski, Waldemar; Rotzschke, Olaf; Santambrogio, Laura

2013-01-01

In this study a proteomic approach was used to define the protein content of matched samples of afferent prenodal lymph and plasma derived from healthy volunteers. The analysis was performed using two analytical methodologies coupled with nanoliquid chromatography-tandem mass spectrometry: one-dimensional gel electrophoresis (1DEF nanoLC Orbitrap–ESI–MS/MS), and two-dimensional fluorescence difference-in-gel electrophoresis (2D-DIGE nanoLC–ESI–MS/MS). The 253 significantly identified proteins (p<0.05), obtained from the tandem mass spectrometry data, were further analyzed with pathway analysis (IPA) to define the functional signature of prenodal lymph and matched plasma. The 1DEF coupled with nanoLC–MS–MS revealed that the common proteome between the two biological fluids (144 out of 253 proteins) was dominated by complement activation and blood coagulation components, transporters and protease inhibitors. The enriched proteome of human lymph (72 proteins) consisted of products derived from the extracellular matrix, apoptosis and cellular catabolism. In contrast, the enriched proteome of human plasma (37 proteins) consisted of soluble molecules of the coagulation system and cell–cell signaling factors. The functional networks associated with both common and source-distinctive proteomes highlight the principal biological activity of these immunologically relevant body fluids. PMID:23202415

Detailed two-dimensional gel proteomic mapping of the feces of the house dust mite Dermatophagoides pteronyssinus and comparison with D. farinae: Reduced trypsin protease content in D. pteronyssinus and different isoforms.

PubMed

Erban, Tomas; Harant, Karel; Hubert, Jan

2017-06-06

Major domestic mite allergens are present in feces. We present a detailed 2D-E-MS/MS proteomic analysis of the Dermatophagoides pteronyssinus feces. Precise cultivation yielded a pure fecal extract. We detected differences in fecal allergens/digestive enzymes between D. pteronyssinus and D. farinae using 2D-E fingerprinting, including unique information on species-specific protease isoforms. Proteomic analysis was performed by 2D-E coupled with MALDI-TOF/TOF identification. The species-specific differences in the fecal extracts of the mites were attributed to trypsin-like proteases known as group 3 allergens. In D. farinae, Der f 3 exhibited high abundance with a pI similar (acidic) to that of the cysteine protease Der f 1 and the chymotrypsin protease Der f 6, whereas in D. pteronyssinus, Der p 3 was rarely detected and exhibited low abundance only at basic pI. Moreover, Der p 9 was detected at a pI of ~ 10, in contrast to Der p 1 and Der p 6, suggesting different compartmentalization in the body. Overall, in D. pteronyssinus feces, allergens of groups 1, 2, 6, and 15 were quantitatively similar to those of D. farinae with the exception of the group 3 and 9 allergens. This work provides novel insights into mite-defecated proteins/digestive enzymes, which are important allergens. Millions of people are affected by allergy and asthma, and their number is growing. In homes, the major triggers of allergy and asthma are the house dust mites Dermatophagoides farinae and D. pteronyssinus, and a clear understanding of the development of diseases caused by these mites is needed. The major sources of mite allergens are their feces, which are deposited in the environment and are easily inhaled as part of aeroplankton. However, descriptions of and comparisons between the major fecal allergens of these two mites are lacking. This study shows that similar group 1 (cysteine protease), 2 (NPC2 family), 6 (chymotrypsin) and 15 (chitinase-like) allergens are present in the feces of these two mite species, as determined by 2D-E mapping, whereas group 3 (trypsin) and 9 (collagenolytic protease) allergens in the feces of the two species are different. The results provide unique MS/MS mapped fingerprints of mite species-specific isoforms in feces. The presence of ubiquitin in mite feces suggests that these proteins participate in the post-translational modification of fecal proteins. The findings are essential for understanding differences between D. farinae and D. pteronyssinus with respect to immunoreactivity, protease activation mechanisms, association with microbes, and food utilization. Copyright © 2017 Elsevier B.V. All rights reserved.

3D pancreatic carcinoma spheroids induce a matrix-rich, chemoresistant phenotype offering a better model for drug testing.

PubMed

Longati, Paola; Jia, Xiaohui; Eimer, Johannes; Wagman, Annika; Witt, Michael-Robin; Rehnmark, Stefan; Verbeke, Caroline; Toftgård, Rune; Löhr, Matthias; Heuchel, Rainer L

2013-02-27

Pancreatic ductal adenocarcinoma (PDAC) is the fourth most common cause of cancer related death. It is lethal in nearly all patients, due to an almost complete chemoresistance. Most if not all drugs that pass preclinical tests successfully, fail miserably in the patient. This raises the question whether traditional 2D cell culture is the correct tool for drug screening. The objective of this study is to develop a simple, high-throughput 3D model of human PDAC cell lines, and to explore mechanisms underlying the transition from 2D to 3D that might be responsible for chemoresistance. Several established human PDAC and a KPC mouse cell lines were tested, whereby Panc-1 was studied in more detail. 3D spheroid formation was facilitated with methylcellulose. Spheroids were studied morphologically, electron microscopically and by qRT-PCR for selected matrix genes, related factors and miRNA. Metabolic studies were performed, and a panel of novel drugs was tested against gemcitabine. Comparing 3D to 2D cell culture, matrix proteins were significantly increased as were lumican, SNED1, DARP32, and miR-146a. Cell metabolism in 3D was shifted towards glycolysis. All drugs tested were less effective in 3D, except for allicin, MT100 and AX, which demonstrated effect. We developed a high-throughput 3D cell culture drug screening system for pancreatic cancer, which displays a strongly increased chemoresistance. Features associated to the 3D cell model are increased expression of matrix proteins and miRNA as well as stromal markers such as PPP1R1B and SNED1. This is supporting the concept of cell adhesion mediated drug resistance.

3D pancreatic carcinoma spheroids induce a matrix-rich, chemoresistant phenotype offering a better model for drug testing

PubMed Central

2013-01-01

Background Pancreatic ductal adenocarcinoma (PDAC) is the fourth most common cause of cancer related death. It is lethal in nearly all patients, due to an almost complete chemoresistance. Most if not all drugs that pass preclinical tests successfully, fail miserably in the patient. This raises the question whether traditional 2D cell culture is the correct tool for drug screening. The objective of this study is to develop a simple, high-throughput 3D model of human PDAC cell lines, and to explore mechanisms underlying the transition from 2D to 3D that might be responsible for chemoresistance. Methods Several established human PDAC and a KPC mouse cell lines were tested, whereby Panc-1 was studied in more detail. 3D spheroid formation was facilitated with methylcellulose. Spheroids were studied morphologically, electron microscopically and by qRT-PCR for selected matrix genes, related factors and miRNA. Metabolic studies were performed, and a panel of novel drugs was tested against gemcitabine. Results Comparing 3D to 2D cell culture, matrix proteins were significantly increased as were lumican, SNED1, DARP32, and miR-146a. Cell metabolism in 3D was shifted towards glycolysis. All drugs tested were less effective in 3D, except for allicin, MT100 and AX, which demonstrated effect. Conclusions We developed a high-throughput 3D cell culture drug screening system for pancreatic cancer, which displays a strongly increased chemoresistance. Features associated to the 3D cell model are increased expression of matrix proteins and miRNA as well as stromal markers such as PPP1R1B and SNED1. This is supporting the concept of cell adhesion mediated drug resistance. PMID:23446043

The First Genomic and Proteomic Characterization of a Deep-Sea Sulfate Reducer: Insights into the Piezophilic Lifestyle of Desulfovibrio piezophilus

PubMed Central

Pradel, Nathalie; Ji, Boyang; Gimenez, Grégory; Talla, Emmanuel; Lenoble, Patricia; Garel, Marc; Tamburini, Christian; Fourquet, Patrick; Lebrun, Régine; Bertin, Philippe; Denis, Yann; Pophillat, Matthieu; Barbe, Valérie; Ollivier, Bernard; Dolla, Alain

2013-01-01

Desulfovibrio piezophilus strain C1TLV30T is a piezophilic anaerobe that was isolated from wood falls in the Mediterranean deep-sea. D. piezophilus represents a unique model for studying the adaptation of sulfate-reducing bacteria to hydrostatic pressure. Here, we report the 3.6 Mbp genome sequence of this piezophilic bacterium. An analysis of the genome revealed the presence of seven genomic islands as well as gene clusters that are most likely linked to life at a high hydrostatic pressure. Comparative genomics and differential proteomics identified the transport of solutes and amino acids as well as amino acid metabolism as major cellular processes for the adaptation of this bacterium to hydrostatic pressure. In addition, the proteome profiles showed that the abundance of key enzymes that are involved in sulfate reduction was dependent on hydrostatic pressure. A comparative analysis of orthologs from the non-piezophilic marine bacterium D. salexigens and D. piezophilus identified aspartic acid, glutamic acid, lysine, asparagine, serine and tyrosine as the amino acids preferentially replaced by arginine, histidine, alanine and threonine in the piezophilic strain. This work reveals the adaptation strategies developed by a sulfate reducer to a deep-sea lifestyle. PMID:23383081

Near Real-Time Processing of Proteomics Data Using Hadoop.

PubMed

Hillman, Chris; Ahmad, Yasmeen; Whitehorn, Mark; Cobley, Andy

2014-03-01

This article presents a near real-time processing solution using MapReduce and Hadoop. The solution is aimed at some of the data management and processing challenges facing the life sciences community. Research into genes and their product proteins generates huge volumes of data that must be extensively preprocessed before any biological insight can be gained. In order to carry out this processing in a timely manner, we have investigated the use of techniques from the big data field. These are applied specifically to process data resulting from mass spectrometers in the course of proteomic experiments. Here we present methods of handling the raw data in Hadoop, and then we investigate a process for preprocessing the data using Java code and the MapReduce framework to identify 2D and 3D peaks.

The temporal analysis of yeast exponential phase using shotgun proteomics as a fermentation monitoring technique

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Eric L.; Orsat, Valerie; Shah, Manesh B

2012-01-01

System biology and bioprocess technology can be better understood using shotgun proteomics as a monitoring system during the fermentation. We demonstrated a shotgun proteomic method to monitor the temporal yeast proteome in early, middle and late exponential phases. Our study identified a total of 1389 proteins combining all 2D-LC-MS/MS runs. The temporal Saccharomyces cerevisiae proteome was enriched with proteolysis, radical detoxification, translation, one-carbon metabolism, glycolysis and TCA cycle. Heat shock proteins and proteins associated with oxidative stress response were found throughout the exponential phase. The most abundant proteins observed were translation elongation factors, ribosomal proteins, chaperones and glycolytic enzymes. Themore » high abundance of the H-protein of the glycine decarboxylase complex (Gcv3p) indicated the availability of glycine in the environment. We observed differentially expressed proteins and the induced proteins at mid-exponential phase were involved in ribosome biogenesis, mitochondria DNA binding/replication and transcriptional activator. Induction of tryptophan synthase (Trp5p) indicated the abundance of tryptophan during the fermentation. As fermentation progressed toward late exponential phase, a decrease in cell proliferation was implied from the repression of ribosomal proteins, transcription coactivators, methionine aminopeptidase and translation-associated proteins.« less

Custom Super-Resolution Microscope for the Structural Analysis of Nanostructures

DTIC Science & Technology

2018-05-29

research community. As part of our validation of the new design approach, we performed two - color imaging of pairs of adjacent oligo probes hybridized...nanostructures and biological targets. Our microscope features a large field of view and custom optics that facilitate 3D imaging and enhanced contrast in...our imaging throughput by creating two microscopy platforms for high-throughput, super-resolution materials characterization, with the AO set-up being

High Throughput, Polymeric Aqueous Two-Phase Printing of Tumor Spheroids

PubMed Central

Atefi, Ehsan; Lemmo, Stephanie; Fyffe, Darcy; Luker, Gary D.; Tavana, Hossein

2014-01-01

This paper presents a new 3D culture microtechnology for high throughput production of tumor spheroids and validates its utility for screening anti-cancer drugs. We use two immiscible polymeric aqueous solutions and microprint a submicroliter drop of the “patterning” phase containing cells into a bath of the “immersion” phase. Selecting proper formulations of biphasic systems using a panel of biocompatible polymers results in the formation of a round drop that confines cells to facilitate spontaneous formation of a spheroid without any external stimuli. Adapting this approach to robotic tools enables straightforward generation and maintenance of spheroids of well-defined size in standard microwell plates and biochemical analysis of spheroids in situ, which is not possible with existing techniques for spheroid culture. To enable high throughput screening, we establish a phase diagram to identify minimum cell densities within specific volumes of the patterning drop to result in a single spheroid. Spheroids show normal growth over long-term incubation and dose-dependent decrease in cellular viability when treated with drug compounds, but present significant resistance compared to monolayer cultures. The unprecedented ease of implementing this microtechnology and its robust performance will benefit high throughput studies of drug screening against cancer cells with physiologically-relevant 3D tumor models. PMID:25411577

A DIGE proteomic analysis for high-intensity exercise-trained rat skeletal muscle.

PubMed

Yamaguchi, Wataru; Fujimoto, Eri; Higuchi, Mitsuru; Tabata, Izumi

2010-09-01

Exercise training induces various adaptations in skeletal muscles. However, the mechanisms remain unclear. In this study, we conducted 2D-DIGE proteomic analysis, which has not yet been used for elucidating adaptations of skeletal muscle after high-intensity exercise training (HIT). For 5 days, rats performed HIT, which consisted of 14 20-s swimming exercise bouts carrying a weight (14% of the body weight), and 10-s pause between bouts. The 2D-DIGE analysis was conducted on epitrochlearis muscles excised 18 h after the final training exercise. Proteomic profiling revealed that out of 800 detected and matched spots, 13 proteins exhibited changed expression by HIT compared with sedentary rats. All proteins were identified by MALDI-TOF/MS. Furthermore, using western immunoblot analyses, significantly changed expressions of NDUFS1 and parvalbumin (PV) were validated in relation to HIT. In conclusion, the proteomic 2D-DIGE analysis following HIT-identified expressions of NDUFS1 and PV, previously unknown to have functions related to exercise-training adaptations.

Cephalosporin-3'-Diazeniumdiolate NO Donor Prodrug PYRRO-C3D Enhances Azithromycin Susceptibility of Nontypeable Haemophilus influenzae Biofilms.

PubMed

Collins, Samuel A; Kelso, Michael J; Rineh, Ardeshir; Yepuri, Nageshwar R; Coles, Janice; Jackson, Claire L; Halladay, Georgia D; Walker, Woolf T; Webb, Jeremy S; Hall-Stoodley, Luanne; Connett, Gary J; Feelisch, Martin; Faust, Saul N; Lucas, Jane S A; Allan, Raymond N

2017-02-01

PYRRO-C3D is a cephalosporin-3-diazeniumdiolate nitric oxide (NO) donor prodrug designed to selectively deliver NO to bacterial infection sites. The objective of this study was to assess the activity of PYRRO-C3D against nontypeable Haemophilus influenzae (NTHi) biofilms and examine the role of NO in reducing biofilm-associated antibiotic tolerance. The activity of PYRRO-C3D on in vitro NTHi biofilms was assessed through CFU enumeration and confocal microscopy. NO release measurements were performed using an ISO-NO probe. NTHi biofilms grown on primary ciliated respiratory epithelia at an air-liquid interface were used to investigate the effects of PYRRO-C3D in the presence of host tissue. Label-free liquid chromatography-mass spectrometry (LC/MS) proteomic analyses were performed to identify differentially expressed proteins following NO treatment. PYRRO-C3D specifically released NO in the presence of NTHi, while no evidence of spontaneous NO release was observed when the compound was exposed to primary epithelial cells. NTHi lacking β-lactamase activity failed to trigger NO release. Treatment significantly increased the susceptibility of in vitro NTHi biofilms to azithromycin, causing a log fold reduction (10-fold reduction or 1-log-unit reduction) in viability (P < 0.05) relative to azithromycin alone. The response was more pronounced for biofilms grown on primary respiratory epithelia, where a 2-log-unit reduction was observed (P < 0.01). Label-free proteomics showed that NO increased expression of 16 proteins involved in metabolic and transcriptional/translational functions. NO release from PYRRO-C3D enhances the efficacy of azithromycin against NTHi biofilms, putatively via modulation of NTHi metabolic activity. Adjunctive therapy with NO mediated through PYRRO-C3D represents a promising approach for reducing biofilm-associated antibiotic tolerance. Copyright © 2017 American Society for Microbiology.

Salt stress induces changes in the proteomic profile of micropropagated sugarcane shoots

PubMed Central

Reis, Ricardo S.; Heringer, Angelo S.; Rangel, Patricia L.; Santa-Catarina, Claudete; Grativol, Clícia; Veiga, Carlos F. M.; Souza-Filho, Gonçalo A.

2017-01-01

Salt stress is one of the most common stresses in agricultural regions worldwide. In particular, sugarcane is affected by salt stress conditions, and no sugarcane cultivar presently show high productivity accompanied by a tolerance to salt stress. Proteomic analysis allows elucidation of the important pathways involved in responses to various abiotic stresses at the biochemical and molecular levels. Thus, this study aimed to analyse the proteomic effects of salt stress in micropropagated shoots of two sugarcane cultivars (CB38-22 and RB855536) using a label-free proteomic approach. The mass spectrometry proteomics data are available via ProteomeXchange with identifier PXD006075. The RB855536 cultivar is more tolerant to salt stress than CB38-22. A quantitative label-free shotgun proteomic analysis identified 1172 non-redundant proteins, and 1160 of these were observed in both cultivars in the presence or absence of NaCl. Compared with CB38-22, the RB855536 cultivar showed a greater abundance of proteins involved in non-enzymatic antioxidant mechanisms, ion transport, and photosynthesis. Some proteins, such as calcium-dependent protein kinase, photosystem I, phospholipase D, and glyceraldehyde-3-phosphate dehydrogenase, were more abundant in the RB855536 cultivar under salt stress. Our results provide new insights into the response of sugarcane to salt stress, and the changes in the abundance of these proteins might be important for the acquisition of ionic and osmotic homeostasis during exposure to salt stress. PMID:28419154

mz5: Space- and Time-efficient Storage of Mass Spectrometry Data Sets*

PubMed Central

Wilhelm, Mathias; Kirchner, Marc; Steen, Judith A. J.; Steen, Hanno

2012-01-01

Across a host of MS-driven-omics fields, researchers witness the acquisition of ever increasing amounts of high throughput MS data and face the need for their compact yet efficiently accessible storage. Addressing the need for an open data exchange format, the Proteomics Standards Initiative and the Seattle Proteome Center at the Institute for Systems Biology independently developed the mzData and mzXML formats, respectively. In a subsequent joint effort, they defined an ontology and associated controlled vocabulary that specifies the contents of MS data files, implemented as the newer mzML format. All three formats are based on XML and are thus not particularly efficient in either storage space requirements or read/write speed. This contribution introduces mz5, a complete reimplementation of the mzML ontology that is based on the efficient, industrial strength storage backend HDF5. Compared with the current mzML standard, this strategy yields an average file size reduction to ∼54% and increases linear read and write speeds ∼3–4-fold. The format is implemented as part of the ProteoWizard project and is available under a permissive Apache license. Additional information and download links are available from http://software.steenlab.org/mz5. PMID:21960719

Expediting SRM assay development for large-scale targeted proteomics experiments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Chaochao; Shi, Tujin; Brown, Joseph N.

2014-08-22

Due to their high sensitivity and specificity, targeted proteomics measurements, e.g. selected reaction monitoring (SRM), are becoming increasingly popular for biological and translational applications. Selection of optimal transitions and optimization of collision energy (CE) are important assay development steps for achieving sensitive detection and accurate quantification; however, these steps can be labor-intensive, especially for large-scale applications. Herein, we explored several options for accelerating SRM assay development evaluated in the context of a relatively large set of 215 synthetic peptide targets. We first showed that HCD fragmentation is very similar to CID in triple quadrupole (QQQ) instrumentation, and by selection ofmore » top six y fragment ions from HCD spectra, >86% of top transitions optimized from direct infusion on QQQ instrument are covered. We also demonstrated that the CE calculated by existing prediction tools was less accurate for +3 precursors, and a significant increase in intensity for transitions could be obtained using a new CE prediction equation constructed from the present experimental data. Overall, our study illustrates the feasibility of expediting the development of larger numbers of high-sensitivity SRM assays through automation of transitions selection and accurate prediction of optimal CE to improve both SRM throughput and measurement quality.« less

High-Resolution Enabled 12-Plex DiLeu Isobaric Tags for Quantitative Proteomics

PubMed Central

2015-01-01

Multiplex isobaric tags (e.g., tandem mass tags (TMT) and isobaric tags for relative and absolute quantification (iTRAQ)) are a valuable tool for high-throughput mass spectrometry based quantitative proteomics. We have developed our own multiplex isobaric tags, DiLeu, that feature quantitative performance on par with commercial offerings but can be readily synthesized in-house as a cost-effective alternative. In this work, we achieve a 3-fold increase in the multiplexing capacity of the DiLeu reagent without increasing structural complexity by exploiting mass defects that arise from selective incorporation of 13C, 15N, and 2H stable isotopes in the reporter group. The inclusion of eight new reporter isotopologues that differ in mass from the existing four reporters by intervals of 6 mDa yields a 12-plex isobaric set that preserves the synthetic simplicity and quantitative performance of the original implementation. We show that the new reporter variants can be baseline-resolved in high-resolution higher-energy C-trap dissociation (HCD) spectra, and we demonstrate accurate 12-plex quantitation of a DiLeu-labeled Saccharomyces cerevisiae lysate digest via high-resolution nano liquid chromatography–tandem mass spectrometry (nanoLC–MS2) analysis on an Orbitrap Elite mass spectrometer. PMID:25405479

A hybrid 2D/3D inspection concept with smart routing optimisation for high throughput, high dynamic range and traceable critical dimension metrology

NASA Astrophysics Data System (ADS)

Jones, Christopher W.; O’Connor, Daniel

2018-07-01

Dimensional surface metrology is required to enable advanced manufacturing process control for products such as large-area electronics, microfluidic structures, and light management films, where performance is determined by micrometre-scale geometry or roughness formed over metre-scale substrates. While able to perform 100% inspection at a low cost, commonly used 2D machine vision systems are insufficient to assess all of the functionally relevant critical dimensions in such 3D products on their own. While current high-resolution 3D metrology systems are able to assess these critical dimensions, they have a relatively small field of view and are thus much too slow to keep up with full production speeds. A hybrid 2D/3D inspection concept is demonstrated, combining a small field of view, high-performance 3D topography-measuring instrument with a large field of view, high-throughput 2D machine vision system. In this concept, the location of critical dimensions and defects are first registered using the 2D system, then smart routing algorithms and high dynamic range (HDR) measurement strategies are used to efficiently acquire local topography using the 3D sensor. A motion control platform with a traceable position referencing system is used to recreate various sheet-to-sheet and roll-to-roll inline metrology scenarios. We present the artefacts and procedures used to calibrate this hybrid sensor system for traceable dimensional measurement, as well as exemplar measurement of optically challenging industrial test structures.

Ultra-High Throughput Synthesis of Nanoparticles with Homogeneous Size Distribution Using a Coaxial Turbulent Jet Mixer

PubMed Central

2015-01-01

High-throughput production of nanoparticles (NPs) with controlled quality is critical for their clinical translation into effective nanomedicines for diagnostics and therapeutics. Here we report a simple and versatile coaxial turbulent jet mixer that can synthesize a variety of NPs at high throughput up to 3 kg/d, while maintaining the advantages of homogeneity, reproducibility, and tunability that are normally accessible only in specialized microscale mixing devices. The device fabrication does not require specialized machining and is easy to operate. As one example, we show reproducible, high-throughput formulation of siRNA-polyelectrolyte polyplex NPs that exhibit effective gene knockdown but exhibit significant dependence on batch size when formulated using conventional methods. The coaxial turbulent jet mixer can accelerate the development of nanomedicines by providing a robust and versatile platform for preparation of NPs at throughputs suitable for in vivo studies, clinical trials, and industrial-scale production. PMID:24824296

FIB/SEM technology and high-throughput 3D reconstruction of dendritic spines and synapses in GFP-labeled adult-generated neurons.

PubMed

Bosch, Carles; Martínez, Albert; Masachs, Nuria; Teixeira, Cátia M; Fernaud, Isabel; Ulloa, Fausto; Pérez-Martínez, Esther; Lois, Carlos; Comella, Joan X; DeFelipe, Javier; Merchán-Pérez, Angel; Soriano, Eduardo

2015-01-01

The fine analysis of synaptic contacts is usually performed using transmission electron microscopy (TEM) and its combination with neuronal labeling techniques. However, the complex 3D architecture of neuronal samples calls for their reconstruction from serial sections. Here we show that focused ion beam/scanning electron microscopy (FIB/SEM) allows efficient, complete, and automatic 3D reconstruction of identified dendrites, including their spines and synapses, from GFP/DAB-labeled neurons, with a resolution comparable to that of TEM. We applied this technology to analyze the synaptogenesis of labeled adult-generated granule cells (GCs) in mice. 3D reconstruction of dendritic spines in GCs aged 3-4 and 8-9 weeks revealed two different stages of dendritic spine development and unexpected features of synapse formation, including vacant and branched dendritic spines and presynaptic terminals establishing synapses with up to 10 dendritic spines. Given the reliability, efficiency, and high resolution of FIB/SEM technology and the wide use of DAB in conventional EM, we consider FIB/SEM fundamental for the detailed characterization of identified synaptic contacts in neurons in a high-throughput manner.

FIB/SEM technology and high-throughput 3D reconstruction of dendritic spines and synapses in GFP-labeled adult-generated neurons

PubMed Central

Bosch, Carles; Martínez, Albert; Masachs, Nuria; Teixeira, Cátia M.; Fernaud, Isabel; Ulloa, Fausto; Pérez-Martínez, Esther; Lois, Carlos; Comella, Joan X.; DeFelipe, Javier; Merchán-Pérez, Angel; Soriano, Eduardo

2015-01-01

The fine analysis of synaptic contacts is usually performed using transmission electron microscopy (TEM) and its combination with neuronal labeling techniques. However, the complex 3D architecture of neuronal samples calls for their reconstruction from serial sections. Here we show that focused ion beam/scanning electron microscopy (FIB/SEM) allows efficient, complete, and automatic 3D reconstruction of identified dendrites, including their spines and synapses, from GFP/DAB-labeled neurons, with a resolution comparable to that of TEM. We applied this technology to analyze the synaptogenesis of labeled adult-generated granule cells (GCs) in mice. 3D reconstruction of dendritic spines in GCs aged 3–4 and 8–9 weeks revealed two different stages of dendritic spine development and unexpected features of synapse formation, including vacant and branched dendritic spines and presynaptic terminals establishing synapses with up to 10 dendritic spines. Given the reliability, efficiency, and high resolution of FIB/SEM technology and the wide use of DAB in conventional EM, we consider FIB/SEM fundamental for the detailed characterization of identified synaptic contacts in neurons in a high-throughput manner. PMID:26052271

The Opposing Roles of Nucleophosmin and the ARF Tumor Suppressor in Breast Cancer

DTIC Science & Technology

2005-04-01

3. Bertwistle, D ., M. Sugimoto, and C . J. Sherr. 2004. Physical and functional interactions of the Arf tumor suppressor protein with nucleophosmin...Kindbeiter, J. C . Sanchez, A. Greco, D . Hochstrasser, and J. J. Diaz. 2002. Functional proteomic analysis of human nucleolus. Mol Biol Cell 13:4100-9...21. Sherr, C . J., and J. D . Weber. 2000. The ARF/p53 pathway. Curr Opin Genet Dev 10:94-9. 22. Spector, D . L., R. L. Ochs, and H. Busch. 1984

Engineering a High-Throughput 3-D In Vitro Glioblastoma Model

PubMed Central

Fan, Yantao; Avci, Naze G.; Nguyen, Duong T.; Dragomir, Andrei; Xu, Feng; Akay, Metin

2015-01-01

Glioblastoma multiforme (GBM) is the most common and malignant primary brain tumor in adults because of its highly invasive behavior. The existing treatment for GBM, which involves a combination of resection, chemotherapy, and radiotherapy, has a very limited success rate with a median survival rate of <1 year. This is mainly because of the failure of early detection and effective treatment. We designed a novel 3-D GBM cell culture model based on microwells that could mimic in vitro environment and help to bypass the lack of suitable animal models for preclinical toxicity tests. Microwells were fabricated from simple and inexpensive polyethylene glycol material for the control of in vitro 3-D culture. We applied the 3-D micropatterning system to GBM (U-87) cells using the photolithography technique to control the cell spheroids’ shape, size, and thickness. Our preliminary results suggested that uniform GBM spheroids can be formed in 3-D, and the size of these GBM spheroids depends on the size of microwells. The viability of the spheroids generated in this manner was quantitatively evaluated using live/dead assay and shown to improve over 21 days. We believe that in vitro 3-D cell culture model could help to reduce the time of the preclinical brain tumor growth studies. The proposed novel platform could be useful and cost-effective for high-throughput screening of cancer drugs and assessment of treatment responses. PMID:27170911

LipidHome: a database of theoretical lipids optimized for high throughput mass spectrometry lipidomics.

PubMed

Foster, Joseph M; Moreno, Pablo; Fabregat, Antonio; Hermjakob, Henning; Steinbeck, Christoph; Apweiler, Rolf; Wakelam, Michael J O; Vizcaíno, Juan Antonio

2013-01-01

Protein sequence databases are the pillar upon which modern proteomics is supported, representing a stable reference space of predicted and validated proteins. One example of such resources is UniProt, enriched with both expertly curated and automatic annotations. Taken largely for granted, similar mature resources such as UniProt are not available yet in some other "omics" fields, lipidomics being one of them. While having a seasoned community of wet lab scientists, lipidomics lies significantly behind proteomics in the adoption of data standards and other core bioinformatics concepts. This work aims to reduce the gap by developing an equivalent resource to UniProt called 'LipidHome', providing theoretically generated lipid molecules and useful metadata. Using the 'FASTLipid' Java library, a database was populated with theoretical lipids, generated from a set of community agreed upon chemical bounds. In parallel, a web application was developed to present the information and provide computational access via a web service. Designed specifically to accommodate high throughput mass spectrometry based approaches, lipids are organised into a hierarchy that reflects the variety in the structural resolution of lipid identifications. Additionally, cross-references to other lipid related resources and papers that cite specific lipids were used to annotate lipid records. The web application encompasses a browser for viewing lipid records and a 'tools' section where an MS1 search engine is currently implemented. LipidHome can be accessed at http://www.ebi.ac.uk/apweiler-srv/lipidhome.

WholePathwayScope: a comprehensive pathway-based analysis tool for high-throughput data

PubMed Central

Yi, Ming; Horton, Jay D; Cohen, Jonathan C; Hobbs, Helen H; Stephens, Robert M

2006-01-01

Background Analysis of High Throughput (HTP) Data such as microarray and proteomics data has provided a powerful methodology to study patterns of gene regulation at genome scale. A major unresolved problem in the post-genomic era is to assemble the large amounts of data generated into a meaningful biological context. We have developed a comprehensive software tool, WholePathwayScope (WPS), for deriving biological insights from analysis of HTP data. Result WPS extracts gene lists with shared biological themes through color cue templates. WPS statistically evaluates global functional category enrichment of gene lists and pathway-level pattern enrichment of data. WPS incorporates well-known biological pathways from KEGG (Kyoto Encyclopedia of Genes and Genomes) and Biocarta, GO (Gene Ontology) terms as well as user-defined pathways or relevant gene clusters or groups, and explores gene-term relationships within the derived gene-term association networks (GTANs). WPS simultaneously compares multiple datasets within biological contexts either as pathways or as association networks. WPS also integrates Genetic Association Database and Partial MedGene Database for disease-association information. We have used this program to analyze and compare microarray and proteomics datasets derived from a variety of biological systems. Application examples demonstrated the capacity of WPS to significantly facilitate the analysis of HTP data for integrative discovery. Conclusion This tool represents a pathway-based platform for discovery integration to maximize analysis power. The tool is freely available at . PMID:16423281

Identification of widespread adenosine nucleotide binding in Mycobacterium tuberculosis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ansong, Charles; Ortega, Corrie; Payne, Samuel H.

The annotation of protein function is almost completely performed by in silico approaches. However, computational prediction of protein function is frequently incomplete and error prone. In Mycobacterium tuberculosis (Mtb), ~25% of all genes have no predicted function and are annotated as hypothetical proteins. This lack of functional information severely limits our understanding of Mtb pathogenicity. Current tools for experimental functional annotation are limited and often do not scale to entire protein families. Here, we report a generally applicable chemical biology platform to functionally annotate bacterial proteins by combining activity-based protein profiling (ABPP) and quantitative LC-MS-based proteomics. As an example ofmore » this approach for high-throughput protein functional validation and discovery, we experimentally annotate the families of ATP-binding proteins in Mtb. Our data experimentally validate prior in silico predictions of >250 ATPases and adenosine nucleotide-binding proteins, and reveal 73 hypothetical proteins as novel ATP-binding proteins. We identify adenosine cofactor interactions with many hypothetical proteins containing a diversity of unrelated sequences, providing a new and expanded view of adenosine nucleotide binding in Mtb. Furthermore, many of these hypothetical proteins are both unique to Mycobacteria and essential for infection, suggesting specialized functions in mycobacterial physiology and pathogenicity. Thus, we provide a generally applicable approach for high throughput protein function discovery and validation, and highlight several ways in which application of activity-based proteomics data can improve the quality of functional annotations to facilitate novel biological insights.« less

High-Throughput Quantitative Proteomic Analysis of Dengue Virus Type 2 Infected A549 Cells

PubMed Central

Chiu, Han-Chen; Hannemann, Holger; Heesom, Kate J.; Matthews, David A.; Davidson, Andrew D.

2014-01-01

Disease caused by dengue virus is a global health concern with up to 390 million individuals infected annually worldwide. There are no vaccines or antiviral compounds available to either prevent or treat dengue disease which may be fatal. To increase our understanding of the interaction of dengue virus with the host cell, we analyzed changes in the proteome of human A549 cells in response to dengue virus type 2 infection using stable isotope labelling in cell culture (SILAC) in combination with high-throughput mass spectrometry (MS). Mock and infected A549 cells were fractionated into nuclear and cytoplasmic extracts before analysis to identify proteins that redistribute between cellular compartments during infection and reduce the complexity of the analysis. We identified and quantified 3098 and 2115 proteins in the cytoplasmic and nuclear fractions respectively. Proteins that showed a significant alteration in amount during infection were examined using gene enrichment, pathway and network analysis tools. The analyses revealed that dengue virus infection modulated the amounts of proteins involved in the interferon and unfolded protein responses, lipid metabolism and the cell cycle. The SILAC-MS results were validated for a select number of proteins over a time course of infection by Western blotting and immunofluorescence microscopy. Our study demonstrates for the first time the power of SILAC-MS for identifying and quantifying novel changes in cellular protein amounts in response to dengue virus infection. PMID:24671231

A practical data processing workflow for multi-OMICS projects.

PubMed

Kohl, Michael; Megger, Dominik A; Trippler, Martin; Meckel, Hagen; Ahrens, Maike; Bracht, Thilo; Weber, Frank; Hoffmann, Andreas-Claudius; Baba, Hideo A; Sitek, Barbara; Schlaak, Jörg F; Meyer, Helmut E; Stephan, Christian; Eisenacher, Martin

2014-01-01

Multi-OMICS approaches aim on the integration of quantitative data obtained for different biological molecules in order to understand their interrelation and the functioning of larger systems. This paper deals with several data integration and data processing issues that frequently occur within this context. To this end, the data processing workflow within the PROFILE project is presented, a multi-OMICS project that aims on identification of novel biomarkers and the development of new therapeutic targets for seven important liver diseases. Furthermore, a software called CrossPlatformCommander is sketched, which facilitates several steps of the proposed workflow in a semi-automatic manner. Application of the software is presented for the detection of novel biomarkers, their ranking and annotation with existing knowledge using the example of corresponding Transcriptomics and Proteomics data sets obtained from patients suffering from hepatocellular carcinoma. Additionally, a linear regression analysis of Transcriptomics vs. Proteomics data is presented and its performance assessed. It was shown, that for capturing profound relations between Transcriptomics and Proteomics data, a simple linear regression analysis is not sufficient and implementation and evaluation of alternative statistical approaches are needed. Additionally, the integration of multivariate variable selection and classification approaches is intended for further development of the software. Although this paper focuses only on the combination of data obtained from quantitative Proteomics and Transcriptomics experiments, several approaches and data integration steps are also applicable for other OMICS technologies. Keeping specific restrictions in mind the suggested workflow (or at least parts of it) may be used as a template for similar projects that make use of different high throughput techniques. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan. Copyright © 2013 Elsevier B.V. All rights reserved.

Identifier mapping performance for integrating transcriptomics and proteomics experimental results

PubMed Central

2011-01-01

Background Studies integrating transcriptomic data with proteomic data can illuminate the proteome more clearly than either separately. Integromic studies can deepen understanding of the dynamic complex regulatory relationship between the transcriptome and the proteome. Integrating these data dictates a reliable mapping between the identifier nomenclature resultant from the two high-throughput platforms. However, this kind of analysis is well known to be hampered by lack of standardization of identifier nomenclature among proteins, genes, and microarray probe sets. Therefore data integration may also play a role in critiquing the fallible gene identifications that both platforms emit. Results We compared three freely available internet-based identifier mapping resources for mapping UniProt accessions (ACCs) to Affymetrix probesets identifications (IDs): DAVID, EnVision, and NetAffx. Liquid chromatography-tandem mass spectrometry analyses of 91 endometrial cancer and 7 noncancer samples generated 11,879 distinct ACCs. For each ACC, we compared the retrieval sets of probeset IDs from each mapping resource. We confirmed a high level of discrepancy among the mapping resources. On the same samples, mRNA expression was available. Therefore, to evaluate the quality of each ACC-to-probeset match, we calculated proteome-transcriptome correlations, and compared the resources presuming that better mapping of identifiers should generate a higher proportion of mapped pairs with strong inter-platform correlations. A mixture model for the correlations fitted well and supported regression analysis, providing a window into the performance of the mapping resources. The resources have added and dropped matches over two years, but their overall performance has not changed. Conclusions The methods presented here serve to achieve concrete context-specific insight, to support well-informed decisions in choosing an ID mapping strategy for "omic" data merging. PMID:21619611

Processing-in-Memory Enabled Graphics Processors for 3D Rendering

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xie, Chenhao; Song, Shuaiwen; Wang, Jing

2017-02-06

The performance of 3D rendering of Graphics Processing Unit that convents 3D vector stream into 2D frame with 3D image effects significantly impact users’ gaming experience on modern computer systems. Due to the high texture throughput in 3D rendering, main memory bandwidth becomes a critical obstacle for improving the overall rendering performance. 3D stacked memory systems such as Hybrid Memory Cube (HMC) provide opportunities to significantly overcome the memory wall by directly connecting logic controllers to DRAM dies. Based on the observation that texel fetches significantly impact off-chip memory traffic, we propose two architectural designs to enable Processing-In-Memory based GPUmore » for efficient 3D rendering.« less

Synthesis and high-throughput processing of polymeric hydrogels for 3D cell culture.

PubMed

Lowe, Stuart B; Tan, Vincent T G; Soeriyadi, Alexander H; Davis, Thomas P; Gooding, J Justin

2014-09-17

3D cell cultures have drawn a large amount of interest in the scientific community with their ability to closely mimic physiological conditions. Hydrogels have been used extensively in the development of extracellular matrix (ECM) mimics for 3D cell culture. Compounds such as collagen and fibrin are commonly used to synthesize natural ECM mimics; however they suffer from batch-to-batch variation. In this Review we explore the synthesis route of hydrogels; how they can be altered to give different chemical and physical properties; how different biomolecules such as arginylglycylaspartic acid (RGD) or vascular endothelial growth factor (VEGF) can be incorporated to give different biological cues; and how to create concentration gradients with UV light. There will also be emphasis on the types of techniques available in high-throughput processing such as nozzle and droplet-based biofabrication, photoenabled biofabrication, and microfluidics. The combination of these approaches and techniques allow the preparation of hydrogels which are capable of mimicking the ECM.

Multicapillary SDS-gel electrophoresis for the analysis of fluorescently labeled mAb preparations: a high throughput quality control process for the production of QuantiPlasma and PlasmaScan mAb libraries.

PubMed

Székely, Andrea; Szekrényes, Akos; Kerékgyártó, Márta; Balogh, Attila; Kádas, János; Lázár, József; Guttman, András; Kurucz, István; Takács, László

2014-08-01

Molecular heterogeneity of mAb preparations is the result of various co- and post-translational modifications and to contaminants related to the production process. Changes in molecular composition results in alterations of functional performance, therefore quality control and validation of therapeutic or diagnostic protein products is essential. A special case is the consistent production of mAb libraries (QuantiPlasma™ and PlasmaScan™) for proteome profiling, quality control of which represents a challenge because of high number of mAbs (>1000). Here, we devise a generally applicable multicapillary SDS-gel electrophoresis process for the analysis of fluorescently labeled mAb preparations for the high throughput quality control of mAbs of the QuantiPlasma™ and PlasmaScan™ libraries. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Genome-derived vaccines.

PubMed

De Groot, Anne S; Rappuoli, Rino

2004-02-01

Vaccine research entered a new era when the complete genome of a pathogenic bacterium was published in 1995. Since then, more than 97 bacterial pathogens have been sequenced and at least 110 additional projects are now in progress. Genome sequencing has also dramatically accelerated: high-throughput facilities can draft the sequence of an entire microbe (two to four megabases) in 1 to 2 days. Vaccine developers are using microarrays, immunoinformatics, proteomics and high-throughput immunology assays to reduce the truly unmanageable volume of information available in genome databases to a manageable size. Vaccines composed by novel antigens discovered from genome mining are already in clinical trials. Within 5 years we can expect to see a novel class of vaccines composed by genome-predicted, assembled and engineered T- and Bcell epitopes. This article addresses the convergence of three forces--microbial genome sequencing, computational immunology and new vaccine technologies--that are shifting genome mining for vaccines onto the forefront of immunology research.

AT_CHLORO, a comprehensive chloroplast proteome database with subplastidial localization and curated information on envelope proteins.

PubMed

Ferro, Myriam; Brugière, Sabine; Salvi, Daniel; Seigneurin-Berny, Daphné; Court, Magali; Moyet, Lucas; Ramus, Claire; Miras, Stéphane; Mellal, Mourad; Le Gall, Sophie; Kieffer-Jaquinod, Sylvie; Bruley, Christophe; Garin, Jérôme; Joyard, Jacques; Masselon, Christophe; Rolland, Norbert

2010-06-01

Recent advances in the proteomics field have allowed a series of high throughput experiments to be conducted on chloroplast samples, and the data are available in several public databases. However, the accurate localization of many chloroplast proteins often remains hypothetical. This is especially true for envelope proteins. We went a step further into the knowledge of the chloroplast proteome by focusing, in the same set of experiments, on the localization of proteins in the stroma, the thylakoids, and envelope membranes. LC-MS/MS-based analyses first allowed building the AT_CHLORO database (http://www.grenoble.prabi.fr/protehome/grenoble-plant-proteomics/), a comprehensive repertoire of the 1323 proteins, identified by 10,654 unique peptide sequences, present in highly purified chloroplasts and their subfractions prepared from Arabidopsis thaliana leaves. This database also provides extensive proteomics information (peptide sequences and molecular weight, chromatographic retention times, MS/MS spectra, and spectral count) for a unique chloroplast protein accurate mass and time tag database gathering identified peptides with their respective and precise analytical coordinates, molecular weight, and retention time. We assessed the partitioning of each protein in the three chloroplast compartments by using a semiquantitative proteomics approach (spectral count). These data together with an in-depth investigation of the literature were compiled to provide accurate subplastidial localization of previously known and newly identified proteins. A unique knowledge base containing extensive information on the proteins identified in envelope fractions was thus obtained, allowing new insights into this membrane system to be revealed. Altogether, the data we obtained provide unexpected information about plastidial or subplastidial localization of some proteins that were not suspected to be associated to this membrane system. The spectral counting-based strategy was further validated as the compartmentation of well known pathways (for instance, photosynthesis and amino acid, fatty acid, or glycerolipid biosynthesis) within chloroplasts could be dissected. It also allowed revisiting the compartmentation of the chloroplast metabolism and functions.

Efficient Site-Specific Labeling of Proteins via Cysteines

PubMed Central

Kim, Younggyu; Ho, Sam O.; Gassman, Natalie R.; Korlann, You; Landorf, Elizabeth V.; Collart, Frank R.; Weiss, Shimon

2011-01-01

Methods for chemical modifications of proteins have been crucial for the advancement of proteomics. In particular, site-specific covalent labeling of proteins with fluorophores and other moieties has permitted the development of a multitude of assays for proteome analysis. A common approach for such a modification is solvent-accessible cysteine labeling using thiol-reactive dyes. Cysteine is very attractive for site-specific conjugation due to its relative rarity throughout the proteome and the ease of its introduction into a specific site along the protein's amino acid chain. This is achieved by site-directed mutagenesis, most often without perturbing the protein's function. Bottlenecks in this reaction, however, include the maintenance of reactive thiol groups without oxidation before the reaction, and the effective removal of unreacted molecules prior to fluorescence studies. Here, we describe an efficient, specific, and rapid procedure for cysteine labeling starting from well-reduced proteins in the solid state. The efficacy and specificity of the improved procedure are estimated using a variety of single-cysteine proteins and thiol-reactive dyes. Based on UV/vis absorbance spectra, coupling efficiencies are typically in the range 70–90%, and specificities are better than ~95%. The labeled proteins are evaluated using fluorescence assays, proving that the covalent modification does not alter their function. In addition to maleimide-based conjugation, this improved procedure may be used for other thiol-reactive conjugations such as haloacetyl, alkyl halide, and disulfide interchange derivatives. This facile and rapid procedure is well suited for high throughput proteome analysis. PMID:18275130

Efficient site-specific labeling of proteins via cysteines.

PubMed

Kim, Younggyu; Ho, Sam O; Gassman, Natalie R; Korlann, You; Landorf, Elizabeth V; Collart, Frank R; Weiss, Shimon

2008-03-01

Methods for chemical modifications of proteins have been crucial for the advancement of proteomics. In particular, site-specific covalent labeling of proteins with fluorophores and other moieties has permitted the development of a multitude of assays for proteome analysis. A common approach for such a modification is solvent-accessible cysteine labeling using thiol-reactive dyes. Cysteine is very attractive for site-specific conjugation due to its relative rarity throughout the proteome and the ease of its introduction into a specific site along the protein's amino acid chain. This is achieved by site-directed mutagenesis, most often without perturbing the protein's function. Bottlenecks in this reaction, however, include the maintenance of reactive thiol groups without oxidation before the reaction, and the effective removal of unreacted molecules prior to fluorescence studies. Here, we describe an efficient, specific, and rapid procedure for cysteine labeling starting from well-reduced proteins in the solid state. The efficacy and specificity of the improved procedure are estimated using a variety of single-cysteine proteins and thiol-reactive dyes. Based on UV/vis absorbance spectra, coupling efficiencies are typically in the range 70-90%, and specificities are better than approximately 95%. The labeled proteins are evaluated using fluorescence assays, proving that the covalent modification does not alter their function. In addition to maleimide-based conjugation, this improved procedure may be used for other thiol-reactive conjugations such as haloacetyl, alkyl halide, and disulfide interchange derivatives. This facile and rapid procedure is well suited for high throughput proteome analysis.

Proteomics for the authentication of fish species.

PubMed

Mazzeo, Maria Fiorella; Siciliano, Rosa Anna

2016-09-16

Assessment of seafood authenticity and origin, mainly in the case of processed products (fillets, sticks, baby food) represents the crucial point to prevent fraudulent deceptions thus guaranteeing market transparency and consumers health. The most dangerous practice that jeopardies fish safety is intentional or unintentional mislabeling, originating from the substitution of valuable fish species with inferior ones. Conventional analytical methods for fish authentication are becoming inadequate to comply with the strict regulations issued by the European Union and with the increase of mislabeling due to the introduction on the market of new fish species and market globalization. This evidence prompts the development of high-throughput approaches suitable to identify unambiguous biomarkers of authenticity and screen a large number of samples with minimal time consumption. Proteomics provides suitable and powerful tools to investigate main aspects of food quality and safety and has given an important contribution in the field of biomarkers discovery applied to food authentication. This report describes the most relevant methods developed to assess fish identity and offers a perspective on their potential in the evaluation of fish quality and safety thus depicting the key role of proteomics in the authentication of fish species and processed products. The assessment of fishery products authenticity is a main issue in the control quality process as deceptive practices could imply severe health risks. Proteomics based methods could significantly contribute to detect falsification and frauds, thus becoming a reliable operative first-line testing resource in food authentication. Copyright © 2016 Elsevier B.V. All rights reserved.

Identifying the missing proteins in human proteome by biological language model.

PubMed

Dong, Qiwen; Wang, Kai; Liu, Xuan

2016-12-23

With the rapid development of high-throughput sequencing technology, the proteomics research becomes a trendy field in the post genomics era. It is necessary to identify all the native-encoding protein sequences for further function and pathway analysis. Toward that end, the Human Proteome Organization lunched the Human Protein Project in 2011. However many proteins are hard to be detected by experiment methods, which becomes one of the bottleneck in Human Proteome Project. In consideration of the complicatedness of detecting these missing proteins by using wet-experiment approach, here we use bioinformatics method to pre-filter the missing proteins. Since there are analogy between the biological sequences and natural language, the n-gram models from Natural Language Processing field has been used to filter the missing proteins. The dataset used in this study contains 616 missing proteins from the "uncertain" category of the neXtProt database. There are 102 proteins deduced by the n-gram model, which have high probability to be native human proteins. We perform a detail analysis on the predicted structure and function of these missing proteins and also compare the high probability proteins with other mass spectrum datasets. The evaluation shows that the results reported here are in good agreement with those obtained by other well-established databases. The analysis shows that 102 proteins may be native gene-coding proteins and some of the missing proteins are membrane or natively disordered proteins which are hard to be detected by experiment methods.

Urine Sample Preparation in 96-Well Filter Plates for Quantitative Clinical Proteomics

PubMed Central

2015-01-01

Urine is an important, noninvasively collected body fluid source for the diagnosis and prognosis of human diseases. Liquid chromatography mass spectrometry (LC-MS) based shotgun proteomics has evolved as a sensitive and informative technique to discover candidate disease biomarkers from urine specimens. Filter-aided sample preparation (FASP) generates peptide samples from protein mixtures of cell lysate or body fluid origin. Here, we describe a FASP method adapted to 96-well filter plates, named 96FASP. Soluble urine concentrates containing ∼10 μg of total protein were processed by 96FASP and LC-MS resulting in 700–900 protein identifications at a 1% false discovery rate (FDR). The experimental repeatability, as assessed by label-free quantification and Pearson correlation analysis for shared proteins among replicates, was high (R ≥ 0.97). Application to urinary pellet lysates which is of particular interest in the context of urinary tract infection analysis was also demonstrated. On average, 1700 proteins (±398) were identified in five experiments. In a pilot study using 96FASP for analysis of eight soluble urine samples, we demonstrated that protein profiles of technical replicates invariably clustered; the protein profiles for distinct urine donors were very different from each other. Robust, highly parallel methods to generate peptide mixtures from urine and other body fluids are critical to increase cost-effectiveness in clinical proteomics projects. This 96FASP method has potential to become a gold standard for high-throughput quantitative clinical proteomics. PMID:24797144

Proteomic analysis of grapevine resistance induced by Trichoderma harzianum T39 reveals specific defence pathways activated against downy mildew

PubMed Central

Perazzolli, Michele

2012-01-01

Downy mildew is caused by the oomycete Plasmopara viticola and is one of the most serious diseases of grapevine. The beneficial microorganism Trichoderma harzianum T39 (T39) has previously been shown to induce plant-mediated resistance and to reduce the severity of downy mildew in susceptible grapevines. In order to better understand the cellular processes associated with T39-induced resistance, the proteomic and histochemical changes activated by T39 in grapevine were investigated before and 1 day after P. viticola inoculation. A comprehensive proteomic analysis of T39-induced resistance in grapevine was performed using an eight-plex iTRAQ protocol, resulting in the identification and quantification of a total of 800 proteins. Most of the proteins directly affected by T39 were found to be involved in signal transduction, indicating activation of a complete microbial recognition machinery. Moreover, T39-induced resistance was associated with rapid accumulation of reactive oxygen species and callose at infection sites, as well as changes in abundance of proteins involved in response to stress and redox balance, indicating an active defence response to downy mildew. On the other hand, proteins affected by P. viticola in control plants mainly decreased in abundance, possibly reflecting the establishment of a compatible interaction. Finally, the high-throughput iTRAQ protocol allowed de novo peptide sequencing, which will be used to improve annotation of the Vitis vinifera cv. Pinot Noir proteome. PMID:23105132

Epigenetics and Proteomics Join Transcriptomics in the Quest for Tuberculosis Biomarkers

PubMed Central

Esterhuyse, Maria M.; Weiner, January; Caron, Etienne; Loxton, Andre G.; Iannaccone, Marco; Wagman, Chandre; Saikali, Philippe; Stanley, Kim; Wolski, Witold E.; Mollenkopf, Hans-Joachim; Schick, Matthias; Aebersold, Ruedi; Linhart, Heinz; Walzl, Gerhard

2015-01-01

ABSTRACT An estimated one-third of the world’s population is currently latently infected with Mycobacterium tuberculosis. Latent M. tuberculosis infection (LTBI) progresses into active tuberculosis (TB) disease in ~5 to 10% of infected individuals. Diagnostic and prognostic biomarkers to monitor disease progression are urgently needed to ensure better care for TB patients and to decrease the spread of TB. Biomarker development is primarily based on transcriptomics. Our understanding of biology combined with evolving technical advances in high-throughput techniques led us to investigate the possibility of additional platforms (epigenetics and proteomics) in the quest to (i) understand the biology of the TB host response and (ii) search for multiplatform biosignatures in TB. We engaged in a pilot study to interrogate the DNA methylome, transcriptome, and proteome in selected monocytes and granulocytes from TB patients and healthy LTBI participants. Our study provides first insights into the levels and sources of diversity in the epigenome and proteome among TB patients and LTBI controls, despite limitations due to small sample size. Functionally the differences between the infection phenotypes (LTBI versus active TB) observed in the different platforms were congruent, thereby suggesting regulation of function not only at the transcriptional level but also by DNA methylation and microRNA. Thus, our data argue for the development of a large-scale study of the DNA methylome, with particular attention to study design in accounting for variation based on gender, age, and cell type. PMID:26374119

Identification of lactoferricin B intracellular targets using an Escherichia coli proteome chip.

PubMed

Tu, Yu-Hsuan; Ho, Yu-Hsuan; Chuang, Ying-Chih; Chen, Po-Chung; Chen, Chien-Sheng

2011-01-01

Lactoferricin B (LfcinB) is a well-known antimicrobial peptide. Several studies have indicated that it can inhibit bacteria by affecting intracellular activities, but the intracellular targets of this antimicrobial peptide have not been identified. Therefore, we used E. coli proteome chips to identify the intracellular target proteins of LfcinB in a high-throughput manner. We probed LfcinB with E. coli proteome chips and further conducted normalization and Gene Ontology (GO) analyses. The results of the GO analyses showed that the identified proteins were associated with metabolic processes. Moreover, we validated the interactions between LfcinB and chip assay-identified proteins with fluorescence polarization (FP) assays. Sixteen proteins were identified, and an E. coli interaction database (EcID) analysis revealed that the majority of the proteins that interact with these 16 proteins affected the tricarboxylic acid (TCA) cycle. Knockout assays were conducted to further validate the FP assay results. These results showed that phosphoenolpyruvate carboxylase was a target of LfcinB, indicating that one of its mechanisms of action may be associated with pyruvate metabolism. Thus, we used pyruvate assays to conduct an in vivo validation of the relationship between LfcinB and pyruvate level in E. coli. These results showed that E. coli exposed to LfcinB had abnormal pyruvate amounts, indicating that LfcinB caused an accumulation of pyruvate. In conclusion, this study successfully revealed the intracellular targets of LfcinB using an E. coli proteome chip approach.

Identification of Lactoferricin B Intracellular Targets Using an Escherichia coli Proteome Chip

PubMed Central

Chen, Po-Chung; Chen, Chien-Sheng

2011-01-01

Lactoferricin B (LfcinB) is a well-known antimicrobial peptide. Several studies have indicated that it can inhibit bacteria by affecting intracellular activities, but the intracellular targets of this antimicrobial peptide have not been identified. Therefore, we used E. coli proteome chips to identify the intracellular target proteins of LfcinB in a high-throughput manner. We probed LfcinB with E. coli proteome chips and further conducted normalization and Gene Ontology (GO) analyses. The results of the GO analyses showed that the identified proteins were associated with metabolic processes. Moreover, we validated the interactions between LfcinB and chip assay-identified proteins with fluorescence polarization (FP) assays. Sixteen proteins were identified, and an E. coli interaction database (EcID) analysis revealed that the majority of the proteins that interact with these 16 proteins affected the tricarboxylic acid (TCA) cycle. Knockout assays were conducted to further validate the FP assay results. These results showed that phosphoenolpyruvate carboxylase was a target of LfcinB, indicating that one of its mechanisms of action may be associated with pyruvate metabolism. Thus, we used pyruvate assays to conduct an in vivo validation of the relationship between LfcinB and pyruvate level in E. coli. These results showed that E. coli exposed to LfcinB had abnormal pyruvate amounts, indicating that LfcinB caused an accumulation of pyruvate. In conclusion, this study successfully revealed the intracellular targets of LfcinB using an E. coli proteome chip approach. PMID:22164243

Characterization of the rat cerebrospinal fluid proteome following acute cerebral ischemia using an aptamer-based proteomic technology.

PubMed

Simats, Alba; García-Berrocoso, Teresa; Ramiro, Laura; Giralt, Dolors; Gill, Natalia; Penalba, Anna; Bustamante, Alejandro; Rosell, Anna; Montaner, Joan

2018-05-21

The limited accessibility to the brain has turned the cerebrospinal fluid (CSF) into a valuable source that may contribute to the complete understanding of the stroke pathophysiology. Here we have described the CSF proteome in the hyper-acute phase of cerebral ischemia by performing an aptamer-based proteomic assay (SOMAscan) in CSF samples collected before and 30 min after male Wistar rats had undergone a 90 min Middle Cerebral Artery Occlusion (MCAO) or sham-surgery. Proteomic results indicated that cerebral ischemia acutely increased the CSF levels of 716 proteins, mostly overrepresented in leukocyte chemotaxis and neuronal death processes. Seven promising candidates were further evaluated in rat plasma and brain (CKB, CaMK2A, CaMK2B, CaMK2D, PDXP, AREG, CMPK). The 3 CaMK2 family-members and CMPK early decreased in the infarcted brain area and, together with AREG, co-localized with neurons. Conversely, CKB levels remained consistent after the insult and specifically matched with astrocytes. Further exploration of these candidates in human plasma revealed the potential of CKB and CMPK to diagnose stroke, while CaMK2B and CMPK resulted feasible biomarkers of functional stroke outcome. Our findings provided insights into the CSF proteome following cerebral ischemia and identified new outstanding proteins that might be further considered as potential biomarkers of stroke.

Analysis of proteomic differences between liquefied after-cataracts and normal lenses using two-dimensional gel electrophoresis and mass spectrometry

PubMed Central

Ge, Jia-Jia; Huang, Yu-Sen

2017-01-01

AIM To analyze and identify the proteomic differences between liquefied after-cataracts and normal lenses by means of liquefied chromatography-tandem mass spectrometry (LC-MS/MS). METHODS Three normal lenses and three liquefied after-cataracts were exposed to depolymerizing reagents to extract the total proteins. Protein concentrations were separated using two-dimensional gel electrophoresis (2-DE). The digitized images obtained with a GS-800 scanner were then analyzed with PDQuest7.0 software to detect the differentially-expressed protein spots. These protein spots were cut from the gel using a proteome work spot cutter and subjected to in-gel digestion with trypsin. The digested peptide separation was conducted by LC-MS/MS. RESULTS The 2-DE maps showed that lens proteins were in a pH range of 3-10 with a relative molecular weight of 21-70 kD. The relative molecular weight of the more abundant proteins was localized at 25-50 kD, and the isoelectric points were found to lie between PI 4-9. The maps also showed that the protein level within the liquefied after-cataracts was at 29 points and significantly lower than in normal lenses. The 29 points were identified by LC-MS/MS, and ten of these proteins were identified by mass spectrometry and database queries: beta-crystallin B1, glyceraldehyde-3-phosphate dehydrogenase, carbonyl reductase (NADPH) 1, cDNA FLJ55253, gamma-crystallin D, GAS2-like protein 3, sorbitol dehydrogenase, DNA FLJ60282, phosphoglycerate kinase, and filensin. CONCLUSION The level of the ten proteins may play an important role in the development of liquefied after-cataracts. PMID:28944190

Elucidating the fungal stress response by proteomics.

PubMed

Kroll, Kristin; Pähtz, Vera; Kniemeyer, Olaf

2014-01-31

Fungal species need to cope with stress, both in the natural environment and during interaction of human- or plant pathogenic fungi with their host. Many regulatory circuits governing the fungal stress response have already been discovered. However, there are still large gaps in the knowledge concerning the changes of the proteome during adaptation to environmental stress conditions. With the application of proteomic methods, particularly 2D-gel and gel-free, LC/MS-based methods, first insights into the composition and dynamic changes of the fungal stress proteome could be obtained. Here, we review the recent proteome data generated for filamentous fungi and yeasts. This article is part of a Special Issue entitled: Trends in Microbial Proteomics. Copyright © 2013 Elsevier B.V. All rights reserved.

Improving Cardiac Action Potential Measurements: 2D and 3D Cell Culture.

PubMed

Daily, Neil J; Yin, Yue; Kemanli, Pinar; Ip, Brian; Wakatsuki, Tetsuro

2015-11-01

Progress in the development of assays for measuring cardiac action potential is crucial for the discovery of drugs for treating cardiac disease and assessing cardiotoxicity. Recently, high-throughput methods for assessing action potential using induced pluripotent stem cell (iPSC) derived cardiomyocytes in both two-dimensional monolayer cultures and three-dimensional tissues have been developed. We describe an improved method for assessing cardiac action potential using an ultra-fast cost-effective plate reader with commercially available dyes. Our methods improve dramatically the detection of the fluorescence signal from these dyes and make way for the development of more high-throughput methods for cardiac drug discovery and cardiotoxicity.

Immunoproteomic Profiling of Antiviral Antibodies in New-Onset Type 1 Diabetes Using Protein Arrays.

PubMed

Bian, Xiaofang; Wallstrom, Garrick; Davis, Amy; Wang, Jie; Park, Jin; Throop, Andrea; Steel, Jason; Yu, Xiaobo; Wasserfall, Clive; Schatz, Desmond; Atkinson, Mark; Qiu, Ji; LaBaer, Joshua

2016-01-01

The rapid rise in the incidence of type 1 diabetes (T1D) suggests the involvement of environmental factors including viral infections. We evaluated the association between viral infections and T1D by profiling antiviral antibodies using a high-throughput immunoproteomics approach in patients with new-onset T1D. We constructed a viral protein array comprising the complete proteomes of seven viruses associated with T1D and open reading frames from other common viruses. Antibody responses to 646 viral antigens were assessed in 42 patients with T1D and 42 age- and sex-matched healthy control subjects (mean age 12.7 years, 50% males). Prevalence of antiviral antibodies agreed with known infection rates for the corresponding virus based on epidemiological studies. Antibody responses to Epstein-Barr virus (EBV) were significantly higher in case than control subjects (odds ratio 6.6; 95% CI 2.0-25.7), whereas the other viruses showed no differences. The EBV and T1D association was significant in both sex and age subgroups (≤12 and >12 years), and there was a trend toward early EBV infections among the case subjects. These results suggest a potential role for EBV in T1D development. We believe our innovative immunoproteomics platform is useful for understanding the role of viral infections in T1D and other disorders where associations between viral infection and disease are unclear. © 2016 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.

NOVEL CONTINUOUS PH/SALT GRADIENT AND PEPTIDE SCORE FOR STRONG CATION EXCHANGE CHROMATOGRAPHY IN 2D-NANO-LC/MSMS PEPTIDE IDENTIFICATION FOR PROTEOMICS

EPA Science Inventory

Tryptic digests of human serum albumin (HSA) and human lung epithelial cell lysates were used as test samples in a novel proteomics study. Peptides were separated and analyzed using 2D-nano-LC/MSMS with strong cation exchange (SCX) and reverse phase (RP) chromatography and contin...

e-Drug3D: 3D structure collections dedicated to drug repurposing and fragment-based drug design.

PubMed

Pihan, Emilie; Colliandre, Lionel; Guichou, Jean-François; Douguet, Dominique

2012-06-01

In the drug discovery field, new uses for old drugs, selective optimization of side activities and fragment-based drug design (FBDD) have proved to be successful alternatives to high-throughput screening. e-Drug3D is a database of 3D chemical structures of drugs that provides several collections of ready-to-screen SD files of drugs and commercial drug fragments. They are natural inputs in studies dedicated to drug repurposing and FBDD. e-Drug3D collections are freely available at http://chemoinfo.ipmc.cnrs.fr/e-drug3d.html either for download or for direct in silico web-based screenings.

Composition, variation, expression and evolution of low-molecular-weight glutenin subunit genes in Triticum urartu.

PubMed

Luo, Guangbin; Zhang, Xiaofei; Zhang, Yanlin; Yang, Wenlong; Li, Yiwen; Sun, Jiazhu; Zhan, Kehui; Zhang, Aimin; Liu, Dongcheng

2015-02-28

Wheat (AABBDD, 2n = 6x = 42) is a major dietary component for many populations across the world. Bread-making quality of wheat is mainly determined by glutenin subunits, but it remains challenging to elucidate the composition and variation of low-molecular-weight glutenin subunits (LMW-GS) genes, the major components for glutenin subunits in hexaploid wheat. This problem, however, can be greatly simplified by characterizing the LMW-GS genes in Triticum urartu, the A-genome donor of hexaploid wheat. In the present study, we exploited the high-throughput molecular marker system, gene cloning, proteomic methods and molecular evolutionary genetic analysis to reveal the composition, variation, expression and evolution of LMW-GS genes in a T. urartu population from the Fertile Crescent region. Eight LMW-GS genes, including four m-type, one s-type and three i-type, were characterized in the T. urartu population. Six or seven genes, the highest number at the Glu-A3 locus, were detected in each accession. Three i-type genes, each containing more than six allelic variants, were tightly linked because of their co-segregation in every accession. Only 2-3 allelic variants were detected for each m- and s-type gene. The m-type gene, TuA3-385, for which homologs were previously characterized only at Glu-D3 locus in common wheat and Aegilops tauschii, was detected at Glu-A3 locus in T. urartu. TuA3-460 was the first s-type gene identified at Glu-A3 locus. Proteomic analysis showed 1-4 genes, mainly i-type, expressed in individual accessions. About 62% accessions had three active i-type genes, rather than one or two in common wheat. Southeastern Turkey might be the center of origin and diversity for T. urartu due to its abundance of LMW-GS genes/genotypes. Phylogenetic reconstruction demonstrated that the characterized T. urartu might be the direct donor of the Glu-A3 locus in common wheat varieties. Compared with the Glu-A3 locus in common wheat, a large number of highly diverse LMW-GS genes and active genes were characterized in T. urartu, demonstrating that this progenitor might provide valuable genetic resources for LMW-GS genes to improve the quality of common wheat. The phylogenetic analysis provided molecular evidence and confirmed that T. urartu was the A-genome donor of hexaploid wheat.

Multizone Paper Platform for 3D Cell Cultures

PubMed Central

Derda, Ratmir; Hong, Estrella; Mwangi, Martin; Mammoto, Akiko; Ingber, Donald E.; Whitesides, George M.

2011-01-01

In vitro 3D culture is an important model for tissues in vivo. Cells in different locations of 3D tissues are physiologically different, because they are exposed to different concentrations of oxygen, nutrients, and signaling molecules, and to other environmental factors (temperature, mechanical stress, etc). The majority of high-throughput assays based on 3D cultures, however, can only detect the average behavior of cells in the whole 3D construct. Isolation of cells from specific regions of 3D cultures is possible, but relies on low-throughput techniques such as tissue sectioning and micromanipulation. Based on a procedure reported previously (“cells-in-gels-in-paper” or CiGiP), this paper describes a simple method for culture of arrays of thin planar sections of tissues, either alone or stacked to create more complex 3D tissue structures. This procedure starts with sheets of paper patterned with hydrophobic regions that form 96 hydrophilic zones. Serial spotting of cells suspended in extracellular matrix (ECM) gel onto the patterned paper creates an array of 200 micron-thick slabs of ECM gel (supported mechanically by cellulose fibers) containing cells. Stacking the sheets with zones aligned on top of one another assembles 96 3D multilayer constructs. De-stacking the layers of the 3D culture, by peeling apart the sheets of paper, “sections” all 96 cultures at once. It is, thus, simple to isolate 200-micron-thick cell-containing slabs from each 3D culture in the 96-zone array. Because the 3D cultures are assembled from multiple layers, the number of cells plated initially in each layer determines the spatial distribution of cells in the stacked 3D cultures. This capability made it possible to compare the growth of 3D tumor models of different spatial composition, and to examine the migration of cells in these structures. PMID:21573103

Mathematical biodescriptors of proteomics maps: background and applications.

PubMed

Basak, Subhash C; Gute, Brian D

2008-05-01

This article reviews recent developments in the formulation and application of biodescriptors to characterize proteomics maps. Such biodescriptors can be derived by applying techniques from discrete mathematics (graph theory, linear algebra and information theory). This review focuses on the development of biodescriptors for proteomics maps derived from 2D gel electrophoresis. Preliminary results demonstrated that such descriptors have a reasonable ability to differentiate between proteomics patterns that result from exposure to closely related individual chemicals and complex mixtures, such as the jet fuel JP-8. Further research is required to evaluate the utility of these proteomics-based biodescriptors for drug discovery and predictive toxicology.

Broadband ion mobility deconvolution for rapid analysis of complex mixtures.

PubMed

Pettit, Michael E; Brantley, Matthew R; Donnarumma, Fabrizio; Murray, Kermit K; Solouki, Touradj

2018-05-04

High resolving power ion mobility (IM) allows for accurate characterization of complex mixtures in high-throughput IM mass spectrometry (IM-MS) experiments. We previously demonstrated that pure component IM-MS data can be extracted from IM unresolved post-IM/collision-induced dissociation (CID) MS data using automated ion mobility deconvolution (AIMD) software [Matthew Brantley, Behrooz Zekavat, Brett Harper, Rachel Mason, and Touradj Solouki, J. Am. Soc. Mass Spectrom., 2014, 25, 1810-1819]. In our previous reports, we utilized a quadrupole ion filter for m/z-isolation of IM unresolved monoisotopic species prior to post-IM/CID MS. Here, we utilize a broadband IM-MS deconvolution strategy to remove the m/z-isolation requirement for successful deconvolution of IM unresolved peaks. Broadband data collection has throughput and multiplexing advantages; hence, elimination of the ion isolation step reduces experimental run times and thus expands the applicability of AIMD to high-throughput bottom-up proteomics. We demonstrate broadband IM-MS deconvolution of two separate and unrelated pairs of IM unresolved isomers (viz., a pair of isomeric hexapeptides and a pair of isomeric trisaccharides) in a simulated complex mixture. Moreover, we show that broadband IM-MS deconvolution improves high-throughput bottom-up characterization of a proteolytic digest of rat brain tissue. To our knowledge, this manuscript is the first to report successful deconvolution of pure component IM and MS data from an IM-assisted data-independent analysis (DIA) or HDMSE dataset.

Tissue vascularization through 3D printing: Will technology bring us flow?

PubMed

Paulsen, S J; Miller, J S

2015-05-01

Though in vivo models provide the most physiologically relevant environment for studying tissue function, in vitro studies provide researchers with explicit control over experimental conditions and the potential to develop high throughput testing methods. In recent years, advancements in developmental biology research and imaging techniques have significantly improved our understanding of the processes involved in vascular development. However, the task of recreating the complex, multi-scale vasculature seen in in vivo systems remains elusive. 3D bioprinting offers a potential method to generate controlled vascular networks with hierarchical structure approaching that of in vivo networks. Bioprinting is an interdisciplinary field that relies on advances in 3D printing technology along with advances in imaging and computational modeling, which allow researchers to monitor cellular function and to better understand cellular environment within the printed tissue. As bioprinting technologies improve with regards to resolution, printing speed, available materials, and automation, 3D printing could be used to generate highly controlled vascularized tissues in a high throughput manner for use in regenerative medicine and the development of in vitro tissue models for research in developmental biology and vascular diseases. © 2015 Wiley Periodicals, Inc.

Comprehensive Analysis of Temporal Alterations in Cellular Proteome of Bacillus subtilis under Curcumin Treatment

PubMed Central

Reddy, Panga Jaipal; Sinha, Sneha; Ray, Sandipan; Sathe, Gajanan J.; Chatterjee, Aditi; Prasad, T. S. Keshava; Dhali, Snigdha; Srikanth, Rapole; Panda, Dulal; Srivastava, Sanjeeva

2015-01-01

Curcumin is a natural dietary compound with antimicrobial activity against various gram positive and negative bacteria. This study aims to investigate the proteome level alterations in Bacillus subtilis due to curcumin treatment and identification of its molecular/cellular targets to understand the mechanism of action. We have performed a comprehensive proteomic analysis of B. subtilis AH75 strain at different time intervals of curcumin treatment (20, 60 and 120 min after the drug exposure, three replicates) to compare the protein expression profiles using two complementary quantitative proteomic techniques, 2D-DIGE and iTRAQ. To the best of our knowledge, this is the first comprehensive longitudinal investigation describing the effect of curcumin treatment on B. subtilis proteome. The proteomics analysis revealed several interesting targets such UDP-N-acetylglucosamine 1-carboxyvinyltransferase 1, putative septation protein SpoVG and ATP-dependent Clp protease proteolytic subunit. Further, in silico pathway analysis using DAVID and KOBAS has revealed modulation of pathways related to the fatty acid metabolism and cell wall synthesis, which are crucial for cell viability. Our findings revealed that curcumin treatment lead to inhibition of the cell wall and fatty acid synthesis in addition to differential expression of many crucial proteins involved in modulation of bacterial metabolism. Findings obtained from proteomics analysis were further validated using 5-cyano-2,3-ditolyl tetrazolium chloride (CTC) assay for respiratory activity, resazurin assay for metabolic activity and membrane integrity assay by potassium and inorganic phosphate leakage measurement. The gene expression analysis of selected cell wall biosynthesis enzymes has strengthened the proteomics findings and indicated the major effect of curcumin on cell division. PMID:25874956

Comprehensive analysis of temporal alterations in cellular proteome of Bacillus subtilis under curcumin treatment.

PubMed

Reddy, Panga Jaipal; Sinha, Sneha; Ray, Sandipan; Sathe, Gajanan J; Chatterjee, Aditi; Prasad, T S Keshava; Dhali, Snigdha; Srikanth, Rapole; Panda, Dulal; Srivastava, Sanjeeva

2015-01-01

Curcumin is a natural dietary compound with antimicrobial activity against various gram positive and negative bacteria. This study aims to investigate the proteome level alterations in Bacillus subtilis due to curcumin treatment and identification of its molecular/cellular targets to understand the mechanism of action. We have performed a comprehensive proteomic analysis of B. subtilis AH75 strain at different time intervals of curcumin treatment (20, 60 and 120 min after the drug exposure, three replicates) to compare the protein expression profiles using two complementary quantitative proteomic techniques, 2D-DIGE and iTRAQ. To the best of our knowledge, this is the first comprehensive longitudinal investigation describing the effect of curcumin treatment on B. subtilis proteome. The proteomics analysis revealed several interesting targets such UDP-N-acetylglucosamine 1-carboxyvinyltransferase 1, putative septation protein SpoVG and ATP-dependent Clp protease proteolytic subunit. Further, in silico pathway analysis using DAVID and KOBAS has revealed modulation of pathways related to the fatty acid metabolism and cell wall synthesis, which are crucial for cell viability. Our findings revealed that curcumin treatment lead to inhibition of the cell wall and fatty acid synthesis in addition to differential expression of many crucial proteins involved in modulation of bacterial metabolism. Findings obtained from proteomics analysis were further validated using 5-cyano-2,3-ditolyl tetrazolium chloride (CTC) assay for respiratory activity, resazurin assay for metabolic activity and membrane integrity assay by potassium and inorganic phosphate leakage measurement. The gene expression analysis of selected cell wall biosynthesis enzymes has strengthened the proteomics findings and indicated the major effect of curcumin on cell division.

Proteome analysis reveals that de novo regenerated mucosa over fibula flap-reconstructed mandibles resembles mature keratinized oral mucosa.

PubMed

Kumar, Vinay V; James, Bonney L; Ruß, Manuela; Mikkat, Stefan; Suresh, Amritha; Kämmerer, Peer W; Glocker, Michael O

2018-03-01

The aim of this study was to determine whether intra-oral de novo regenerated mucosa (D) that grew over free fibula flap reconstructed-mandibles resembled the donor tissue i.e. external skin (S) of the lateral leg, or the recipient site tissue, i.e. keratinized oral mucosa (K). Differential proteome analysis was performed with ten tissue samples from each of the three groups: de novo regenerated mucosa (D), external skin (S), and keratinized oral mucosa (K). Expression differences of cornulin and involucrin were validated by Western blot analysis and their spatial distributions in the respective tissues were ascertained by immunohistochemistry. From all three investigated tissue types a total of 1188 proteins were identified, 930 of which were reproducibly and robustly quantified by proteome analysis. The best differentiating proteins were assembled in an oral mucosa proteome signature that encompasses 56 differentially expressed proteins. Principal component analysis of both, the 930 quantifiable proteins and the 56 oral mucosa signature proteins revealed that the de novo regenerated mucosa resembles keratinized oral mucosa much closer than extra-oral skin. Differentially expressed cornification-related proteins comprise proteins from all subclasses of the cornified cell envelope. Prominently expressed in intra-oral mucosa tissues were (i) cornifin-A, cornifin-B, SPRR3, and involucrin from the cornified-cell-envelope precursor group, (ii) S100A9, S100A8 and S100A2 from the S100 group, and (iii) cornulin which belongs to the fused-gene-protein group. According to its proteome signature de novo regenerated mucosa over the free fibula flap not only presents a passive structural surface layer but has adopted active tissue function. Copyright © 2018 Elsevier Ltd. All rights reserved.

The day/night proteome in the murine heart.

PubMed

Podobed, Peter; Pyle, W Glen; Ackloo, Suzanne; Alibhai, Faisal J; Tsimakouridze, Elena V; Ratcliffe, William F; Mackay, Allison; Simpson, Jeremy; Wright, David C; Kirby, Gordon M; Young, Martin E; Martino, Tami A

2014-07-15

Circadian rhythms are essential to cardiovascular health and disease. Temporal coordination of cardiac structure and function has focused primarily at the physiological and gene expression levels, but these analyses are invariably incomplete, not the least because proteins underlie many biological processes. The purpose of this study was to reveal the diurnal cardiac proteome and important contributions to cardiac function. The 24-h day-night murine cardiac proteome was assessed by two-dimensional difference in gel electrophoresis (2D-DIGE) and liquid chromatography-mass spectrometry. Daily variation was considerable, as ∼7.8% (90/1,147) of spots exhibited statistical changes at paired times across the 24-h light- (L) dark (D) cycle. JTK_CYCLE was used to investigate underlying diurnal rhythms in corresponding mRNA. We next revealed that disruption of the L:D cycle altered protein profiles and diurnal variation in cardiac function in Langendorff-perfused hearts, relative to the L:D cycle. To investigate the role of the circadian clock mechanism, we used cardiomyocyte clock mutant (CCM) mice. CCM myofilaments exhibited a loss of time-of-day-dependent maximal calcium-dependent ATP consumption, and altered phosphorylation rhythms. Moreover, the cardiac proteome was significantly altered in CCM hearts, especially enzymes regulating vital metabolic pathways. Lastly, we used a model of pressure overload cardiac hypertrophy to demonstrate the temporal proteome during heart disease. Our studies demonstrate that time of day plays a direct role in cardiac protein abundance and indicate a novel mechanistic contribution of circadian biology to cardiovascular structure and function.

The day/night proteome in the murine heart

PubMed Central

Podobed, Peter; Pyle, W. Glen; Ackloo, Suzanne; Alibhai, Faisal J.; Tsimakouridze, Elena V.; Ratcliffe, William F.; Mackay, Allison; Simpson, Jeremy; Wright, David C.; Kirby, Gordon M.; Young, Martin E.

2014-01-01

Circadian rhythms are essential to cardiovascular health and disease. Temporal coordination of cardiac structure and function has focused primarily at the physiological and gene expression levels, but these analyses are invariably incomplete, not the least because proteins underlie many biological processes. The purpose of this study was to reveal the diurnal cardiac proteome and important contributions to cardiac function. The 24-h day-night murine cardiac proteome was assessed by two-dimensional difference in gel electrophoresis (2D-DIGE) and liquid chromatography-mass spectrometry. Daily variation was considerable, as ∼7.8% (90/1,147) of spots exhibited statistical changes at paired times across the 24-h light- (L) dark (D) cycle. JTK_CYCLE was used to investigate underlying diurnal rhythms in corresponding mRNA. We next revealed that disruption of the L:D cycle altered protein profiles and diurnal variation in cardiac function in Langendorff-perfused hearts, relative to the L:D cycle. To investigate the role of the circadian clock mechanism, we used cardiomyocyte clock mutant (CCM) mice. CCM myofilaments exhibited a loss of time-of-day-dependent maximal calcium-dependent ATP consumption, and altered phosphorylation rhythms. Moreover, the cardiac proteome was significantly altered in CCM hearts, especially enzymes regulating vital metabolic pathways. Lastly, we used a model of pressure overload cardiac hypertrophy to demonstrate the temporal proteome during heart disease. Our studies demonstrate that time of day plays a direct role in cardiac protein abundance and indicate a novel mechanistic contribution of circadian biology to cardiovascular structure and function. PMID:24789993

High-throughput screening of metal-porphyrin-like graphenes for selective capture of carbon dioxide

PubMed Central

Bae, Hyeonhu; Park, Minwoo; Jang, Byungryul; Kang, Yura; Park, Jinwoo; Lee, Hosik; Chung, Haegeun; Chung, ChiHye; Hong, Suklyun; Kwon, Yongkyung; Yakobson, Boris I.; Lee, Hoonkyung

2016-01-01

Nanostructured materials, such as zeolites and metal-organic frameworks, have been considered to capture CO2. However, their application has been limited largely because they exhibit poor selectivity for flue gases and low capture capacity under low pressures. We perform a high-throughput screening for selective CO2 capture from flue gases by using first principles thermodynamics. We find that elements with empty d orbitals selectively attract CO2 from gaseous mixtures under low CO2 pressures (~10−3 bar) at 300 K and release it at ~450 K. CO2 binding to elements involves hybridization of the metal d orbitals with the CO2 π orbitals and CO2-transition metal complexes were observed in experiments. This result allows us to perform high-throughput screening to discover novel promising CO2 capture materials with empty d orbitals (e.g., Sc– or V–porphyrin-like graphene) and predict their capture performance under various conditions. Moreover, these findings provide physical insights into selective CO2 capture and open a new path to explore CO2 capture materials. PMID:26902156

High-throughput screening of metal-porphyrin-like graphenes for selective capture of carbon dioxide.

PubMed

Bae, Hyeonhu; Park, Minwoo; Jang, Byungryul; Kang, Yura; Park, Jinwoo; Lee, Hosik; Chung, Haegeun; Chung, ChiHye; Hong, Suklyun; Kwon, Yongkyung; Yakobson, Boris I; Lee, Hoonkyung

2016-02-23

Nanostructured materials, such as zeolites and metal-organic frameworks, have been considered to capture CO2. However, their application has been limited largely because they exhibit poor selectivity for flue gases and low capture capacity under low pressures. We perform a high-throughput screening for selective CO2 capture from flue gases by using first principles thermodynamics. We find that elements with empty d orbitals selectively attract CO2 from gaseous mixtures under low CO2 pressures (~10(-3) bar) at 300 K and release it at ~450 K. CO2 binding to elements involves hybridization of the metal d orbitals with the CO2 π orbitals and CO2-transition metal complexes were observed in experiments. This result allows us to perform high-throughput screening to discover novel promising CO2 capture materials with empty d orbitals (e.g., Sc- or V-porphyrin-like graphene) and predict their capture performance under various conditions. Moreover, these findings provide physical insights into selective CO2 capture and open a new path to explore CO2 capture materials.