RedeR: R/Bioconductor package for representing modular structures, nested networks and multiple levels of hierarchical associations

PubMed Central

2012-01-01

Visualization and analysis of molecular networks are both central to systems biology. However, there still exists a large technological gap between them, especially when assessing multiple network levels or hierarchies. Here we present RedeR, an R/Bioconductor package combined with a Java core engine for representing modular networks. The functionality of RedeR is demonstrated in two different scenarios: hierarchical and modular organization in gene co-expression networks and nested structures in time-course gene expression subnetworks. Our results demonstrate RedeR as a new framework to deal with the multiple network levels that are inherent to complex biological systems. RedeR is available from http://bioconductor.org/packages/release/bioc/html/RedeR.html. PMID:22531049

The NCBI BioSystems database.

PubMed

Geer, Lewis Y; Marchler-Bauer, Aron; Geer, Renata C; Han, Lianyi; He, Jane; He, Siqian; Liu, Chunlei; Shi, Wenyao; Bryant, Stephen H

2010-01-01

The NCBI BioSystems database, found at http://www.ncbi.nlm.nih.gov/biosystems/, centralizes and cross-links existing biological systems databases, increasing their utility and target audience by integrating their pathways and systems into NCBI resources. This integration allows users of NCBI's Entrez databases to quickly categorize proteins, genes and small molecules by metabolic pathway, disease state or other BioSystem type, without requiring time-consuming inference of biological relationships from the literature or multiple experimental datasets.

Systems Biology-Based Investigation of Host-Plasmodium Interactions.

PubMed

Smith, Maren L; Styczynski, Mark P

2018-05-18

Malaria is a serious, complex disease caused by parasites of the genus Plasmodium. Plasmodium parasites affect multiple tissues as they evade immune responses, replicate, sexually reproduce, and transmit between vertebrate and invertebrate hosts. The explosion of omics technologies has enabled large-scale collection of Plasmodium infection data, revealing systems-scale patterns, mechanisms of pathogenesis, and the ways that host and pathogen affect each other. Here, we provide an overview of recent efforts using systems biology approaches to study host-Plasmodium interactions and the biological themes that have emerged from these efforts. We discuss some of the challenges in using systems biology for this goal, key research efforts needed to address those issues, and promising future malaria applications of systems biology. Copyright © 2018 Elsevier Ltd. All rights reserved.

Clinical and biological features of multiple myeloma involving the gastrointestinal system.

PubMed

Talamo, Giampaolo; Cavallo, Federica; Zangari, Maurizio; Barlogie, Bart; Lee, Choon-Kee; Pineda-Roman, Mauricio; Kiwan, Elias; Krishna, Somashekar; Tricot, Guido

2006-07-01

We report 24 cases of multiple myeloma (MM) with involvement of the gastrointestinal (GI) system. We found a strong association with high A lactate dehydrogenase levels, plasmablastic morphology, and A unfavorable karyotype. GI involvement at the time of initial diagnosis was much rarer than later in the course of the disease. The A median survival after diagnosis of GI involvement was 7 months. Among 13 patients treated with stem cell transplantation, the response rate was 92%, and median progression-free survival was 4 months. We conclude that MM involving the GI system is associated with adverse biological features and with short-lasting remissions, even after A high-dose chemotherapy.

Development of Multiple-Frequency Ultrasonic Imaging System Using Multiple Resonance Piezoelectric Transducer

NASA Astrophysics Data System (ADS)

Akiyama, Iwaki; Yoshizumi, Natsuki; Saito, Shigemi; Wada, Yuji; Koyama, Daisuke; Nakamura, Kentaro

2012-07-01

The authors have developed a multiple frequency imaging system using a multiple resonance transducer (MRT) consisting of 1-3 composite materials with a low mechanical quality factor Q bonded together. The MRT has a structure consisting of thin and thick piezoelectric plates, two matching layers, and a backing layer. This makes it possible to obtain B-mode images of satisfactory resolution using ultrasonic pulses owing to their short duration. In this paper, the vibration property of the MRT derived through equivalent-circuit analysis is first shown. By utilizing the result, an MRT capable of transmitting ultrasonic pulses for generation of the images of biological tissues with satisfactory resolution is designed and prototyped. Setting the prototype transducer in the mechanical sector probe of commercial ultrasonic diagnosis equipment, the speckle reduction effect is demonstrated using images of various phantoms to mimic biological tissues and a human thyroid.

Thinking Like a Wolf, a Sheep, or a Firefly: Learning Biology through Constructing and Testing Computational Theories--An Embodied Modeling Approach

ERIC Educational Resources Information Center

Wilensky, Uri; Reisman, Kenneth

2006-01-01

Biological phenomena can be investigated at multiple levels, from the molecular to the cellular to the organismic to the ecological. In typical biology instruction, these levels have been segregated. Yet, it is by examining the connections between such levels that many phenomena in biology, and complex systems in general, are best explained. We…

The NCBI BioSystems database

PubMed Central

Geer, Lewis Y.; Marchler-Bauer, Aron; Geer, Renata C.; Han, Lianyi; He, Jane; He, Siqian; Liu, Chunlei; Shi, Wenyao; Bryant, Stephen H.

2010-01-01

The NCBI BioSystems database, found at http://www.ncbi.nlm.nih.gov/biosystems/, centralizes and cross-links existing biological systems databases, increasing their utility and target audience by integrating their pathways and systems into NCBI resources. This integration allows users of NCBI’s Entrez databases to quickly categorize proteins, genes and small molecules by metabolic pathway, disease state or other BioSystem type, without requiring time-consuming inference of biological relationships from the literature or multiple experimental datasets. PMID:19854944

Systems biology of human atherosclerosis.

PubMed

Shalhoub, Joseph; Sikkel, Markus B; Davies, Kerry J; Vorkas, Panagiotis A; Want, Elizabeth J; Davies, Alun H

2014-01-01

Systems biology describes a holistic and integrative approach to understand physiology and pathology. The "omic" disciplines include genomics, transcriptomics, proteomics, and metabolic profiling (metabonomics and metabolomics). By adopting a stance, which is opposing (yet complimentary) to conventional research techniques, systems biology offers an overview by assessing the "net" biological effect imposed by a disease or nondisease state. There are a number of different organizational levels to be understood, from DNA to protein, metabolites, cells, organs and organisms, even beyond this to an organism's context. Systems biology relies on the existence of "nodes" and "edges." Nodes are the constituent part of the system being studied (eg, proteins in the proteome), while the edges are the way these constituents interact. In future, it will be increasingly important to collaborate, collating data from multiple studies to improve data sets, making them freely available and undertaking integrative analyses.

Synthetic biology: tools to design microbes for the production of chemicals and fuels.

PubMed

Seo, Sang Woo; Yang, Jina; Min, Byung Eun; Jang, Sungho; Lim, Jae Hyung; Lim, Hyun Gyu; Kim, Seong Cheol; Kim, Se Yeon; Jeong, Jun Hong; Jung, Gyoo Yeol

2013-11-01

The engineering of biological systems to achieve specific purposes requires design tools that function in a predictable and quantitative manner. Recent advances in the field of synthetic biology, particularly in the programmable control of gene expression at multiple levels of regulation, have increased our ability to efficiently design and optimize biological systems to perform designed tasks. Furthermore, implementation of these designs in biological systems highlights the potential of using these tools to build microbial cell factories for the production of chemicals and fuels. In this paper, we review current developments in the design of tools for controlling gene expression at transcriptional, post-transcriptional and post-translational levels, and consider potential applications of these tools. Copyright © 2013 Elsevier Inc. All rights reserved.

Anatomy and Physiology of Multiscale Modeling and Simulation in Systems Medicine.

PubMed

Mizeranschi, Alexandru; Groen, Derek; Borgdorff, Joris; Hoekstra, Alfons G; Chopard, Bastien; Dubitzky, Werner

2016-01-01

Systems medicine is the application of systems biology concepts, methods, and tools to medical research and practice. It aims to integrate data and knowledge from different disciplines into biomedical models and simulations for the understanding, prevention, cure, and management of complex diseases. Complex diseases arise from the interactions among disease-influencing factors across multiple levels of biological organization from the environment to molecules. To tackle the enormous challenges posed by complex diseases, we need a modeling and simulation framework capable of capturing and integrating information originating from multiple spatiotemporal and organizational scales. Multiscale modeling and simulation in systems medicine is an emerging methodology and discipline that has already demonstrated its potential in becoming this framework. The aim of this chapter is to present some of the main concepts, requirements, and challenges of multiscale modeling and simulation in systems medicine.

Epigenomics and the concept of degeneracy in biological systems

PubMed Central

Mason, Paul H.; Barron, Andrew B.

2014-01-01

Researchers in the field of epigenomics are developing more nuanced understandings of biological complexity, and exploring the multiple pathways that lead to phenotypic expression. The concept of degeneracy—referring to the multiple pathways that a system recruits to achieve functional plasticity—is an important conceptual accompaniment to the growing body of knowledge in epigenomics. Distinct from degradation, redundancy and dilapidation; degeneracy refers to the plasticity of traits whose function overlaps in some environments, but diverges in others. While a redundant system is composed of repeated identical elements performing the same function, a degenerate system is composed of different elements performing similar or overlapping functions. Here, we describe the degenerate structure of gene regulatory systems from the basic genetic code to flexible epigenomic modifications, and discuss how these structural features have contributed to organism complexity, robustness, plasticity and evolvability. PMID:24335757

Light microscopy applications in systems biology: opportunities and challenges

PubMed Central

2013-01-01

Biological systems present multiple scales of complexity, ranging from molecules to entire populations. Light microscopy is one of the least invasive techniques used to access information from various biological scales in living cells. The combination of molecular biology and imaging provides a bottom-up tool for direct insight into how molecular processes work on a cellular scale. However, imaging can also be used as a top-down approach to study the behavior of a system without detailed prior knowledge about its underlying molecular mechanisms. In this review, we highlight the recent developments on microscopy-based systems analyses and discuss the complementary opportunities and different challenges with high-content screening and high-throughput imaging. Furthermore, we provide a comprehensive overview of the available platforms that can be used for image analysis, which enable community-driven efforts in the development of image-based systems biology. PMID:23578051

cellPACK: A Virtual Mesoscope to Model and Visualize Structural Systems Biology

PubMed Central

Johnson, Graham T.; Autin, Ludovic; Al-Alusi, Mostafa; Goodsell, David S.; Sanner, Michel F.; Olson, Arthur J.

2014-01-01

cellPACK assembles computational models of the biological mesoscale, an intermediate scale (10−7–10−8m) between molecular and cellular biology. cellPACK’s modular architecture unites existing and novel packing algorithms to generate, visualize and analyze comprehensive 3D models of complex biological environments that integrate data from multiple experimental systems biology and structural biology sources. cellPACK is currently available as open source code, with tools for validation of models and with recipes and models for five biological systems: blood plasma, cytoplasm, synaptic vesicles, HIV and a mycoplasma cell. We have applied cellPACK to model distributions of HIV envelope protein to test several hypotheses for consistency with experimental observations. Biologists, educators, and outreach specialists can interact with cellPACK models, develop new recipes and perform packing experiments through scripting and graphical user interfaces at http://cellPACK.org. PMID:25437435

A Systems Biology Approach to Iron Metabolism

PubMed Central

Chifman, J.; Laubenbacher, R.; Torti, S.V.

2015-01-01

Iron is critical to the survival of almost all living organisms. However, inappropriately low or high levels of iron are detrimental and contribute to a wide range of diseases. Recent advances in the study of iron metabolism have revealed multiple intricate pathways that are essential to the maintenance of iron homeostasis. Further, iron regulation involves processes at several scales, ranging from the subcellular to the organismal. This complexity makes a systems biology approach crucial, with its enabling technology of computational models based on a mathematical description of regulatory systems. Systems biology may represent a new strategy for understanding imbalances in iron metabolism and their underlying causes. PMID:25480643

Using directed information for influence discovery in interconnected dynamical systems

NASA Astrophysics Data System (ADS)

Rao, Arvind; Hero, Alfred O.; States, David J.; Engel, James Douglas

2008-08-01

Structure discovery in non-linear dynamical systems is an important and challenging problem that arises in various applications such as computational neuroscience, econometrics, and biological network discovery. Each of these systems have multiple interacting variables and the key problem is the inference of the underlying structure of the systems (which variables are connected to which others) based on the output observations (such as multiple time trajectories of the variables). Since such applications demand the inference of directed relationships among variables in these non-linear systems, current methods that have a linear assumption on structure or yield undirected variable dependencies are insufficient. Hence, in this work, we present a methodology for structure discovery using an information-theoretic metric called directed time information (DTI). Using both synthetic dynamical systems as well as true biological datasets (kidney development and T-cell data), we demonstrate the utility of DTI in such problems.

SYNTHETIC BIOLOGY. Emergent genetic oscillations in a synthetic microbial consortium.

PubMed

Chen, Ye; Kim, Jae Kyoung; Hirning, Andrew J; Josić, Krešimir; Bennett, Matthew R

2015-08-28

A challenge of synthetic biology is the creation of cooperative microbial systems that exhibit population-level behaviors. Such systems use cellular signaling mechanisms to regulate gene expression across multiple cell types. We describe the construction of a synthetic microbial consortium consisting of two distinct cell types—an "activator" strain and a "repressor" strain. These strains produced two orthogonal cell-signaling molecules that regulate gene expression within a synthetic circuit spanning both strains. The two strains generated emergent, population-level oscillations only when cultured together. Certain network topologies of the two-strain circuit were better at maintaining robust oscillations than others. The ability to program population-level dynamics through the genetic engineering of multiple cooperative strains points the way toward engineering complex synthetic tissues and organs with multiple cell types. Copyright © 2015, American Association for the Advancement of Science.

Multi-agent-based bio-network for systems biology: protein-protein interaction network as an example.

PubMed

Ren, Li-Hong; Ding, Yong-Sheng; Shen, Yi-Zhen; Zhang, Xiang-Feng

2008-10-01

Recently, a collective effort from multiple research areas has been made to understand biological systems at the system level. This research requires the ability to simulate particular biological systems as cells, organs, organisms, and communities. In this paper, a novel bio-network simulation platform is proposed for system biology studies by combining agent approaches. We consider a biological system as a set of active computational components interacting with each other and with an external environment. Then, we propose a bio-network platform for simulating the behaviors of biological systems and modelling them in terms of bio-entities and society-entities. As a demonstration, we discuss how a protein-protein interaction (PPI) network can be seen as a society of autonomous interactive components. From interactions among small PPI networks, a large PPI network can emerge that has a remarkable ability to accomplish a complex function or task. We also simulate the evolution of the PPI networks by using the bio-operators of the bio-entities. Based on the proposed approach, various simulators with different functions can be embedded in the simulation platform, and further research can be done from design to development, including complexity validation of the biological system.

Materiomics: biological protein materials, from nano to macro.

PubMed

Cranford, Steven; Buehler, Markus J

2010-11-12

Materiomics is an emerging field of science that provides a basis for multiscale material system characterization, inspired in part by natural, for example, protein-based materials. Here we outline the scope and explain the motivation of the field of materiomics, as well as demonstrate the benefits of a materiomic approach in the understanding of biological and natural materials as well as in the design of de novo materials. We discuss recent studies that exemplify the impact of materiomics - discovering Nature's complexity through a materials science approach that merges concepts of material and structure throughout all scales and incorporates feedback loops that facilitate sensing and resulting structural changes at multiple scales. The development and application of materiomics is illustrated for the specific case of protein-based materials, which constitute the building blocks of a variety of biological systems such as tendon, bone, skin, spider silk, cells, and tissue, as well as natural composite material systems (a combination of protein-based and inorganic constituents) such as nacre and mollusk shells, and other natural multiscale systems such as cellulose-based plant and wood materials. An important trait of these materials is that they display distinctive hierarchical structures across multiple scales, where molecular details are exhibited in macroscale mechanical responses. Protein materials are intriguing examples of materials that balance multiple tasks, representing some of the most sustainable material solutions that integrate structure and function despite severe limitations in the quality and quantity of material building blocks. However, up until now, our attempts to analyze and replicate Nature's materials have been hindered by our lack of fundamental understanding of these materials' intricate hierarchical structures, scale-bridging mechanisms, and complex material components that bestow protein-based materials their unique properties. Recent advances in analytical tools and experimental methods allow a holistic view of such a hierarchical biological material system. The integration of these approaches and amalgamation of material properties at all scale levels to develop a complete description of a material system falls within the emerging field of materiomics. Materiomics is the result of the convergence of engineering and materials science with experimental and computational biology in the context of natural and synthetic materials. Through materiomics, fundamental advances in our understanding of structure-property-process relations of biological systems contribute to the mechanistic understanding of certain diseases and facilitate the development of novel biological, biologically inspired, and completely synthetic materials for applications in medicine (biomaterials), nanotechnology, and engineering.

Materiomics: biological protein materials, from nano to macro

PubMed Central

Cranford, Steven; Buehler, Markus J

2010-01-01

Materiomics is an emerging field of science that provides a basis for multiscale material system characterization, inspired in part by natural, for example, protein-based materials. Here we outline the scope and explain the motivation of the field of materiomics, as well as demonstrate the benefits of a materiomic approach in the understanding of biological and natural materials as well as in the design of de novo materials. We discuss recent studies that exemplify the impact of materiomics – discovering Nature’s complexity through a materials science approach that merges concepts of material and structure throughout all scales and incorporates feedback loops that facilitate sensing and resulting structural changes at multiple scales. The development and application of materiomics is illustrated for the specific case of protein-based materials, which constitute the building blocks of a variety of biological systems such as tendon, bone, skin, spider silk, cells, and tissue, as well as natural composite material systems (a combination of protein-based and inorganic constituents) such as nacre and mollusk shells, and other natural multiscale systems such as cellulose-based plant and wood materials. An important trait of these materials is that they display distinctive hierarchical structures across multiple scales, where molecular details are exhibited in macroscale mechanical responses. Protein materials are intriguing examples of materials that balance multiple tasks, representing some of the most sustainable material solutions that integrate structure and function despite severe limitations in the quality and quantity of material building blocks. However, up until now, our attempts to analyze and replicate Nature’s materials have been hindered by our lack of fundamental understanding of these materials’ intricate hierarchical structures, scale-bridging mechanisms, and complex material components that bestow protein-based materials their unique properties. Recent advances in analytical tools and experimental methods allow a holistic view of such a hierarchical biological material system. The integration of these approaches and amalgamation of material properties at all scale levels to develop a complete description of a material system falls within the emerging field of materiomics. Materiomics is the result of the convergence of engineering and materials science with experimental and computational biology in the context of natural and synthetic materials. Through materiomics, fundamental advances in our understanding of structure–property–process relations of biological systems contribute to the mechanistic understanding of certain diseases and facilitate the development of novel biological, biologically inspired, and completely synthetic materials for applications in medicine (biomaterials), nanotechnology, and engineering. PMID:24198478

The effect of multiple external representations (MERs) worksheets toward complex system reasoning achievement

NASA Astrophysics Data System (ADS)

Sumarno; Ibrahim, M.; Supardi, Z. A. I.

2018-03-01

The application of a systems approach to assessing biological systems provides hope for a coherent understanding of cell dynamics patterns and their relationship to plant life. This action required the reasoning about complex systems. In other sides, there were a lot of researchers who provided the proof about the instructional successions. They involved the multiple external representations which improved the biological learning. The researcher conducted an investigation using one shoot case study design which involved 30 students in proving that the MERs worksheets could affect the student's achievement of reasoning about complex system. The data had been collected based on test of reasoning about complex system and student's identification result who worked through MERs. The result showed that only partially students could achieve reasoning about system complex, but their MERs skill could support their reasoning ability of complex system. This study could bring a new hope to develop the MERs worksheet as a tool to facilitate the reasoning about complex system.

Quantification of biological aging in young adults

PubMed Central

Belsky, Daniel W.; Caspi, Avshalom; Houts, Renate; Cohen, Harvey J.; Corcoran, David L.; Danese, Andrea; Harrington, HonaLee; Israel, Salomon; Levine, Morgan E.; Schaefer, Jonathan D.; Sugden, Karen; Williams, Ben; Yashin, Anatoli I.; Poulton, Richie; Moffitt, Terrie E.

2015-01-01

Antiaging therapies show promise in model organism research. Translation to humans is needed to address the challenges of an aging global population. Interventions to slow human aging will need to be applied to still-young individuals. However, most human aging research examines older adults, many with chronic disease. As a result, little is known about aging in young humans. We studied aging in 954 young humans, the Dunedin Study birth cohort, tracking multiple biomarkers across three time points spanning their third and fourth decades of life. We developed and validated two methods by which aging can be measured in young adults, one cross-sectional and one longitudinal. Our longitudinal measure allows quantification of the pace of coordinated physiological deterioration across multiple organ systems (e.g., pulmonary, periodontal, cardiovascular, renal, hepatic, and immune function). We applied these methods to assess biological aging in young humans who had not yet developed age-related diseases. Young individuals of the same chronological age varied in their “biological aging” (declining integrity of multiple organ systems). Already, before midlife, individuals who were aging more rapidly were less physically able, showed cognitive decline and brain aging, self-reported worse health, and looked older. Measured biological aging in young adults can be used to identify causes of aging and evaluate rejuvenation therapies. PMID:26150497

Parallel excitation-emission multiplexed fluorescence lifetime confocal microscopy for live cell imaging.

PubMed

Zhao, Ming; Li, Yu; Peng, Leilei

2014-05-05

We present a novel excitation-emission multiplexed fluorescence lifetime microscopy (FLIM) method that surpasses current FLIM techniques in multiplexing capability. The method employs Fourier multiplexing to simultaneously acquire confocal fluorescence lifetime images of multiple excitation wavelength and emission color combinations at 44,000 pixels/sec. The system is built with low-cost CW laser sources and standard PMTs with versatile spectral configuration, which can be implemented as an add-on to commercial confocal microscopes. The Fourier lifetime confocal method allows fast multiplexed FLIM imaging, which makes it possible to monitor multiple biological processes in live cells. The low cost and compatibility with commercial systems could also make multiplexed FLIM more accessible to biological research community.

A Systems Approach to Exposure Modeling (ExpoCast)(FutureTox3)

EPA Science Inventory

Systems Biology might be described as the understanding of how interactions on multiple scales integrate into a homeostatic system. Systems Toxicology could then be the study of the impact of chemical perturbations of homeostasis. Systems exposure might then be the study of the i...

NEURODEVELOPMENTAL BIOLOGY ASSOCIATED WITH CHILDHOOD SEXUAL ABUSE

PubMed Central

De Bellis, Michael D.; Spratt, Eve G.; Hooper, Stephen R.

2013-01-01

Child maltreatment appears to be the single most preventable cause of mental illness and behavioral dysfunction in the US. There are few published studies examining the developmental and the psychobiological consequences of sexual abuse. There are multiple mechanisms through which sexual abuse can cause PTSD, activate biological stress response systems, and contribute to adverse brain development. This article will critically review the psychiatric problems associated with maltreatment and the emerging biologic stress system research with a special emphasis on what is known about victimization by sexual abuse. PMID:21970646

Agent-based models in translational systems biology

PubMed Central

An, Gary; Mi, Qi; Dutta-Moscato, Joyeeta; Vodovotz, Yoram

2013-01-01

Effective translational methodologies for knowledge representation are needed in order to make strides against the constellation of diseases that affect the world today. These diseases are defined by their mechanistic complexity, redundancy, and nonlinearity. Translational systems biology aims to harness the power of computational simulation to streamline drug/device design, simulate clinical trials, and eventually to predict the effects of drugs on individuals. The ability of agent-based modeling to encompass multiple scales of biological process as well as spatial considerations, coupled with an intuitive modeling paradigm, suggests that this modeling framework is well suited for translational systems biology. This review describes agent-based modeling and gives examples of its translational applications in the context of acute inflammation and wound healing. PMID:20835989

Knowledge Discovery from Biomedical Ontologies in Cross Domains.

PubMed

Shen, Feichen; Lee, Yugyung

2016-01-01

In recent years, there is an increasing demand for sharing and integration of medical data in biomedical research. In order to improve a health care system, it is required to support the integration of data by facilitating semantic interoperability systems and practices. Semantic interoperability is difficult to achieve in these systems as the conceptual models underlying datasets are not fully exploited. In this paper, we propose a semantic framework, called Medical Knowledge Discovery and Data Mining (MedKDD), that aims to build a topic hierarchy and serve the semantic interoperability between different ontologies. For the purpose, we fully focus on the discovery of semantic patterns about the association of relations in the heterogeneous information network representing different types of objects and relationships in multiple biological ontologies and the creation of a topic hierarchy through the analysis of the discovered patterns. These patterns are used to cluster heterogeneous information networks into a set of smaller topic graphs in a hierarchical manner and then to conduct cross domain knowledge discovery from the multiple biological ontologies. Thus, patterns made a greater contribution in the knowledge discovery across multiple ontologies. We have demonstrated the cross domain knowledge discovery in the MedKDD framework using a case study with 9 primary biological ontologies from Bio2RDF and compared it with the cross domain query processing approach, namely SLAP. We have confirmed the effectiveness of the MedKDD framework in knowledge discovery from multiple medical ontologies.

Knowledge Discovery from Biomedical Ontologies in Cross Domains

PubMed Central

Shen, Feichen; Lee, Yugyung

2016-01-01

In recent years, there is an increasing demand for sharing and integration of medical data in biomedical research. In order to improve a health care system, it is required to support the integration of data by facilitating semantic interoperability systems and practices. Semantic interoperability is difficult to achieve in these systems as the conceptual models underlying datasets are not fully exploited. In this paper, we propose a semantic framework, called Medical Knowledge Discovery and Data Mining (MedKDD), that aims to build a topic hierarchy and serve the semantic interoperability between different ontologies. For the purpose, we fully focus on the discovery of semantic patterns about the association of relations in the heterogeneous information network representing different types of objects and relationships in multiple biological ontologies and the creation of a topic hierarchy through the analysis of the discovered patterns. These patterns are used to cluster heterogeneous information networks into a set of smaller topic graphs in a hierarchical manner and then to conduct cross domain knowledge discovery from the multiple biological ontologies. Thus, patterns made a greater contribution in the knowledge discovery across multiple ontologies. We have demonstrated the cross domain knowledge discovery in the MedKDD framework using a case study with 9 primary biological ontologies from Bio2RDF and compared it with the cross domain query processing approach, namely SLAP. We have confirmed the effectiveness of the MedKDD framework in knowledge discovery from multiple medical ontologies. PMID:27548262

Immunoisolation Patch System for Cellular Transplantation

NASA Technical Reports Server (NTRS)

Wang, Taylor G. (Inventor)

2014-01-01

An immunoisolation patch system, and particularly a patch system comprising multiple immunoisolation microcapsules, each encapsulating biological material such as cells for transplantation, which can be used in the prophylactic and therapeutic treatment of disease in large animals and humans without the need for immunosuppression.

Nanoparticles that Communicate In Vivo to Amplify Tumour Targeting

PubMed Central

von Maltzahn, Geoffrey; Park, Ji-Ho; Lin, Kevin Y.; Singh, Neetu; Schwöppe, Christian; Mesters, Rolf; Berdel, Wolfgang E.; Ruoslahti, Erkki; Sailor, Michael J.; Bhatia, Sangeeta N.

2012-01-01

Nanomedicines have enormous potential to improve the precision of cancer therapy, yet our ability to efficiently home these materials to regions of disease in vivo remains very limited. Inspired by the ability for communication to improve targeting in biological systems, such inflammatory cell recruitment to sites of disease, we construct systems where synthetic biological and nanotechnological components communicate to amplify disease targeting in vivo. These systems are composed of ‘Signalling’ modules (nanoparticles or engineered proteins) that target tumours and then locally active the coagulation cascade to broadcast tumour location to clot-targeted ‘Receiving’ nanoparticles in circulation that carry a diagnostic or therapeutic cargo, thereby amplifying their delivery. We show that communicating nanoparticle systems can be composed from multiple types of Signalling and Receiving modules, can transmit information via multiple molecular pathways in coagulation, can operate autonomously, and can target over 40-fold higher doses of chemotherapeutics to tumours than non-communicating controls. PMID:21685903

Nanoparticles that communicate in vivo to amplify tumour targeting

NASA Astrophysics Data System (ADS)

von Maltzahn, Geoffrey; Park, Ji-Ho; Lin, Kevin Y.; Singh, Neetu; Schwöppe, Christian; Mesters, Rolf; Berdel, Wolfgang E.; Ruoslahti, Erkki; Sailor, Michael J.; Bhatia, Sangeeta N.

2011-07-01

Nanomedicines have enormous potential to improve the precision of cancer therapy, yet our ability to efficiently home these materials to regions of disease in vivo remains very limited. Inspired by the ability of communication to improve targeting in biological systems, such as inflammatory-cell recruitment to sites of disease, we construct systems where synthetic biological and nanotechnological components communicate to amplify disease targeting in vivo. These systems are composed of ‘signalling’ modules (nanoparticles or engineered proteins) that target tumours and then locally activate the coagulation cascade to broadcast tumour location to clot-targeted ‘receiving’ nanoparticles in circulation that carry a diagnostic or therapeutic cargo, thereby amplifying their delivery. We show that communicating nanoparticle systems can be composed of multiple types of signalling and receiving modules, can transmit information through multiple molecular pathways in coagulation, can operate autonomously and can target over 40 times higher doses of chemotherapeutics to tumours than non-communicating controls.

A methodology for global-sensitivity analysis of time-dependent outputs in systems biology modelling.

PubMed

Sumner, T; Shephard, E; Bogle, I D L

2012-09-07

One of the main challenges in the development of mathematical and computational models of biological systems is the precise estimation of parameter values. Understanding the effects of uncertainties in parameter values on model behaviour is crucial to the successful use of these models. Global sensitivity analysis (SA) can be used to quantify the variability in model predictions resulting from the uncertainty in multiple parameters and to shed light on the biological mechanisms driving system behaviour. We present a new methodology for global SA in systems biology which is computationally efficient and can be used to identify the key parameters and their interactions which drive the dynamic behaviour of a complex biological model. The approach combines functional principal component analysis with established global SA techniques. The methodology is applied to a model of the insulin signalling pathway, defects of which are a major cause of type 2 diabetes and a number of key features of the system are identified.

System and process for pulsed multiple reaction monitoring

DOEpatents

Belov, Mikhail E

2013-05-17

A new pulsed multiple reaction monitoring process and system are disclosed that uses a pulsed ion injection mode for use in conjunction with triple-quadrupole instruments. The pulsed injection mode approach reduces background ion noise at the detector, increases amplitude of the ion signal, and includes a unity duty cycle that provides a significant sensitivity increase for reliable quantitation of proteins/peptides present at attomole levels in highly complex biological mixtures.

Towards physical principles of biological evolution

NASA Astrophysics Data System (ADS)

Katsnelson, Mikhail I.; Wolf, Yuri I.; Koonin, Eugene V.

2018-03-01

Biological systems reach organizational complexity that far exceeds the complexity of any known inanimate objects. Biological entities undoubtedly obey the laws of quantum physics and statistical mechanics. However, is modern physics sufficient to adequately describe, model and explain the evolution of biological complexity? Detailed parallels have been drawn between statistical thermodynamics and the population-genetic theory of biological evolution. Based on these parallels, we outline new perspectives on biological innovation and major transitions in evolution, and introduce a biological equivalent of thermodynamic potential that reflects the innovation propensity of an evolving population. Deep analogies have been suggested to also exist between the properties of biological entities and processes, and those of frustrated states in physics, such as glasses. Such systems are characterized by frustration whereby local state with minimal free energy conflict with the global minimum, resulting in ‘emergent phenomena’. We extend such analogies by examining frustration-type phenomena, such as conflicts between different levels of selection, in biological evolution. These frustration effects appear to drive the evolution of biological complexity. We further address evolution in multidimensional fitness landscapes from the point of view of percolation theory and suggest that percolation at level above the critical threshold dictates the tree-like evolution of complex organisms. Taken together, these multiple connections between fundamental processes in physics and biology imply that construction of a meaningful physical theory of biological evolution might not be a futile effort. However, it is unrealistic to expect that such a theory can be created in one scoop; if it ever comes to being, this can only happen through integration of multiple physical models of evolutionary processes. Furthermore, the existing framework of theoretical physics is unlikely to suffice for adequate modeling of the biological level of complexity, and new developments within physics itself are likely to be required.

Biomedical imaging with THz waves

NASA Astrophysics Data System (ADS)

Nguyen, Andrew

2010-03-01

We discuss biomedical imaging using radio waves operating in the terahertz (THz) range between 300 GHz to 3 THz. Particularly, we present the concept for two THz imaging systems. One system employs single antenna, transmitter and receiver operating over multi-THz-frequency simultaneously for sensing and imaging small areas of the human body or biological samples. Another system consists of multiple antennas, a transmitter, and multiple receivers operating over multi-THz-frequency capable of sensing and imaging simultaneously the whole body or large biological samples. Using THz waves for biomedical imaging promises unique and substantial medical benefits including extremely small medical devices, extraordinarily fine spatial resolution, and excellent contrast between images of diseased and healthy tissues. THz imaging is extremely attractive for detection of cancer in the early stages, sensing and imaging of tissues near the skin, and study of disease and its growth versus time.

Multiple Replica Repulsion Technique for Efficient Conformational Sampling of Biological Systems

PubMed Central

Malevanets, Anatoly; Wodak, Shoshana J.

2011-01-01

Here, we propose a technique for sampling complex molecular systems with many degrees of freedom. The technique, termed “multiple replica repulsion” (MRR), does not suffer from poor scaling with the number of degrees of freedom associated with common replica exchange procedures and does not require sampling at high temperatures. The algorithm involves creation of multiple copies (replicas) of the system, which interact with one another through a repulsive potential that can be applied to the system as a whole or to portions of it. The proposed scheme prevents oversampling of the most populated states and provides accurate descriptions of conformational perturbations typically associated with sampling ground-state energy wells. The performance of MRR is illustrated for three systems of increasing complexity. A two-dimensional toy potential surface is used to probe the sampling efficiency as a function of key parameters of the procedure. MRR simulations of the Met-enkephalin pentapeptide, and the 76-residue protein ubiquitin, performed in presence of explicit water molecules and totaling 32 ns each, investigate the ability of MRR to characterize the conformational landscape of the peptide, and the protein native basin, respectively. Results obtained for the enkephalin peptide reflect more closely the extensive conformational flexibility of this peptide than previously reported simulations. Those obtained for ubiquitin show that conformational ensembles sampled by MRR largely encompass structural fluctuations relevant to biological recognition, which occur on the microsecond timescale, or are observed in crystal structures of ubiquitin complexes with other proteins. MRR thus emerges as a very promising simple and versatile technique for modeling the structural plasticity of complex biological systems. PMID:21843487

Parallel excitation-emission multiplexed fluorescence lifetime confocal microscopy for live cell imaging

PubMed Central

Zhao, Ming; Li, Yu; Peng, Leilei

2014-01-01

We present a novel excitation-emission multiplexed fluorescence lifetime microscopy (FLIM) method that surpasses current FLIM techniques in multiplexing capability. The method employs Fourier multiplexing to simultaneously acquire confocal fluorescence lifetime images of multiple excitation wavelength and emission color combinations at 44,000 pixels/sec. The system is built with low-cost CW laser sources and standard PMTs with versatile spectral configuration, which can be implemented as an add-on to commercial confocal microscopes. The Fourier lifetime confocal method allows fast multiplexed FLIM imaging, which makes it possible to monitor multiple biological processes in live cells. The low cost and compatibility with commercial systems could also make multiplexed FLIM more accessible to biological research community. PMID:24921725

WAVELENGTH AND ALIGNMENT TESTS FOR CONFOCAL SPECTRAL IMAGING SYSTEMS

EPA Science Inventory

Confocal spectral imaging (CSI) microscope systems now on the market delineate multiple fluorescent proteins, labels, or dyes within biological specimens by performing spectral characterizations. However, we find that some CSI present inconsistent spectral profiles of reference s...

Multiple network-constrained regressions expand insights into influenza vaccination responses.

PubMed

Avey, Stefan; Mohanty, Subhasis; Wilson, Jean; Zapata, Heidi; Joshi, Samit R; Siconolfi, Barbara; Tsang, Sui; Shaw, Albert C; Kleinstein, Steven H

2017-07-15

Systems immunology leverages recent technological advancements that enable broad profiling of the immune system to better understand the response to infection and vaccination, as well as the dysregulation that occurs in disease. An increasingly common approach to gain insights from these large-scale profiling experiments involves the application of statistical learning methods to predict disease states or the immune response to perturbations. However, the goal of many systems studies is not to maximize accuracy, but rather to gain biological insights. The predictors identified using current approaches can be biologically uninterpretable or present only one of many equally predictive models, leading to a narrow understanding of the underlying biology. Here we show that incorporating prior biological knowledge within a logistic modeling framework by using network-level constraints on transcriptional profiling data significantly improves interpretability. Moreover, incorporating different types of biological knowledge produces models that highlight distinct aspects of the underlying biology, while maintaining predictive accuracy. We propose a new framework, Logistic Multiple Network-constrained Regression (LogMiNeR), and apply it to understand the mechanisms underlying differential responses to influenza vaccination. Although standard logistic regression approaches were predictive, they were minimally interpretable. Incorporating prior knowledge using LogMiNeR led to models that were equally predictive yet highly interpretable. In this context, B cell-specific genes and mTOR signaling were associated with an effective vaccination response in young adults. Overall, our results demonstrate a new paradigm for analyzing high-dimensional immune profiling data in which multiple networks encoding prior knowledge are incorporated to improve model interpretability. The R source code described in this article is publicly available at https://bitbucket.org/kleinstein/logminer . steven.kleinstein@yale.edu or stefan.avey@yale.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Review of S100A9 Biology and its Role in Cancer

PubMed Central

Markowitz, Joseph; Carson, William E.

2013-01-01

S100A9 is a calcium binding protein with multiple ligands and post-translation modifications that is involved in inflammatory events and the initial development of the cancer cell through to the development of metastatic disease. This review has a threefold purpose: 1) describe S100A9 structural elements important for its biological activity, 2) describe S100A9 biology in the context of the immune system, and 3) illustrate the role of S100A9 in the development of malignancy via interactions with the immune system and other cellular processes. PMID:23123827

A highly tunable system for the simultaneous expression of multiple enzymes in Saccharomyces cerevisiae.

PubMed

Ito, Yoichiro; Yamanishi, Mamoru; Ikeuchi, Akinori; Matsuyama, Takashi

2015-01-16

Control of the expression levels of multiple enzymes in transgenic yeasts is essential for the effective production of complex molecules through fermentation. Here, we propose a tunable strategy for the control of expression levels based on the design of terminator regions and other gene-expression control elements in Saccharomyces cerevisiae. Our genome-integrated system, which is capable of producing high expression levels over a wide dynamic range, will broadly enable metabolic engineering and synthetic biology. We demonstrated that the activities of multiple cellulases and the production of ethanol were doubled in a transgenic yeast constructed with our system compared with those achieved with a standard expression system.

Systems Biology Approaches for Host–Fungal Interactions: An Expanding Multi-Omics Frontier

PubMed Central

Culibrk, Luka; Croft, Carys A.

2016-01-01

Abstract Opportunistic fungal infections are an increasing threat for global health, and for immunocompromised patients in particular. These infections are characterized by interaction between fungal pathogen and host cells. The exact mechanisms and the attendant variability in host and fungal pathogen interaction remain to be fully elucidated. The field of systems biology aims to characterize a biological system, and utilize this knowledge to predict the system's response to stimuli such as fungal exposures. A multi-omics approach, for example, combining data from genomics, proteomics, metabolomics, would allow a more comprehensive and pan-optic “two systems” biology of both the host and the fungal pathogen. In this review and literature analysis, we present highly specialized and nascent methods for analysis of multiple -omes of biological systems, in addition to emerging single-molecule visualization techniques that may assist in determining biological relevance of multi-omics data. We provide an overview of computational methods for modeling of gene regulatory networks, including some that have been applied towards the study of an interacting host and pathogen. In sum, comprehensive characterizations of host–fungal pathogen systems are now possible, and utilization of these cutting-edge multi-omics strategies may yield advances in better understanding of both host biology and fungal pathogens at a systems scale. PMID:26885725

Modern methods and systems for precise control of the quality of agricultural and food production

NASA Astrophysics Data System (ADS)

Bednarjevsky, Sergey S.; Veryasov, Yuri V.; Akinina, Evgeniya V.; Smirnov, Gennady I.

1999-01-01

The results on the modeling of non-linear dynamics of strong continuous and impulse radiation in the laser nephelometry of polydisperse biological systems, important from the viewpoint of applications in biotechnologies, are presented. The processes of nonlinear self-action of the laser radiation by the multiple scattering in the disperse biological agro-media are considered. The simplified algorithms of the calculation of the parameters of the biological media under investigation are indicated and the estimates of the errors of the laser-nephelometric measurements are given. The universal high-informative optical analyzers and the standard etalon specimens of agro- objects make the technological foundation of the considered methods and systems.

Systems modelling methodology for the analysis of apoptosis signal transduction and cell death decisions.

PubMed

Rehm, Markus; Prehn, Jochen H M

2013-06-01

Systems biology and systems medicine, i.e. the application of systems biology in a clinical context, is becoming of increasing importance in biology, drug discovery and health care. Systems biology incorporates knowledge and methods that are applied in mathematics, physics and engineering, but may not be part of classical training in biology. We here provide an introduction to basic concepts and methods relevant to the construction and application of systems models for apoptosis research. We present the key methods relevant to the representation of biochemical processes in signal transduction models, with a particular reference to apoptotic processes. We demonstrate how such models enable a quantitative and temporal analysis of changes in molecular entities in response to an apoptosis-inducing stimulus, and provide information on cell survival and cell death decisions. We introduce methods for analyzing the spatial propagation of cell death signals, and discuss the concepts of sensitivity analyses that enable a prediction of network responses to disturbances of single or multiple parameters. Copyright © 2013 Elsevier Inc. All rights reserved.

The Vitamin D Endocrine System.

ERIC Educational Resources Information Center

Norman, Anthony W.

1985-01-01

Discusses the physiology and biochemistry of the vitamin D endocrine system, including role of biological calcium and phosphorus, vitamin D metabolism, and related diseases. A 10-item, multiple-choice test which can be used to obtain continuing medical education credit is included. (JN)

Comparative systems biology between human and animal models based on next-generation sequencing methods.

PubMed

Zhao, Yu-Qi; Li, Gong-Hua; Huang, Jing-Fei

2013-04-01

Animal models provide myriad benefits to both experimental and clinical research. Unfortunately, in many situations, they fall short of expected results or provide contradictory results. In part, this can be the result of traditional molecular biological approaches that are relatively inefficient in elucidating underlying molecular mechanism. To improve the efficacy of animal models, a technological breakthrough is required. The growing availability and application of the high-throughput methods make systematic comparisons between human and animal models easier to perform. In the present study, we introduce the concept of the comparative systems biology, which we define as "comparisons of biological systems in different states or species used to achieve an integrated understanding of life forms with all their characteristic complexity of interactions at multiple levels". Furthermore, we discuss the applications of RNA-seq and ChIP-seq technologies to comparative systems biology between human and animal models and assess the potential applications for this approach in the future studies.

An efficient approach to ARMA modeling of biological systems with multiple inputs and delays

NASA Technical Reports Server (NTRS)

Perrott, M. H.; Cohen, R. J.

1996-01-01

This paper presents a new approach to AutoRegressive Moving Average (ARMA or ARX) modeling which automatically seeks the best model order to represent investigated linear, time invariant systems using their input/output data. The algorithm seeks the ARMA parameterization which accounts for variability in the output of the system due to input activity and contains the fewest number of parameters required to do so. The unique characteristics of the proposed system identification algorithm are its simplicity and efficiency in handling systems with delays and multiple inputs. We present results of applying the algorithm to simulated data and experimental biological data In addition, a technique for assessing the error associated with the impulse responses calculated from estimated ARMA parameterizations is presented. The mapping from ARMA coefficients to impulse response estimates is nonlinear, which complicates any effort to construct confidence bounds for the obtained impulse responses. Here a method for obtaining a linearization of this mapping is derived, which leads to a simple procedure to approximate the confidence bounds.

Leaf LIMS: A Flexible Laboratory Information Management System with a Synthetic Biology Focus.

PubMed

Craig, Thomas; Holland, Richard; D'Amore, Rosalinda; Johnson, James R; McCue, Hannah V; West, Anthony; Zulkower, Valentin; Tekotte, Hille; Cai, Yizhi; Swan, Daniel; Davey, Robert P; Hertz-Fowler, Christiane; Hall, Anthony; Caddick, Mark

2017-12-15

This paper presents Leaf LIMS, a flexible laboratory information management system (LIMS) designed to address the complexity of synthetic biology workflows. At the project's inception there was a lack of a LIMS designed specifically to address synthetic biology processes, with most systems focused on either next generation sequencing or biobanks and clinical sample handling. Leaf LIMS implements integrated project, item, and laboratory stock tracking, offering complete sample and construct genealogy, materials and lot tracking, and modular assay data capture. Hence, it enables highly configurable task-based workflows and supports data capture from project inception to completion. As such, in addition to it supporting synthetic biology it is ideal for many laboratory environments with multiple projects and users. The system is deployed as a web application through Docker and is provided under a permissive MIT license. It is freely available for download at https://leaflims.github.io .

Systems biology approach to developing S(2)RM-based "systems therapeutics" and naturally induced pluripotent stem cells.

PubMed

Maguire, Greg; Friedman, Peter

2015-05-26

The degree to, and the mechanisms through, which stem cells are able to build, maintain, and heal the body have only recently begun to be understood. Much of the stem cell's power resides in the release of a multitude of molecules, called stem cell released molecules (SRM). A fundamentally new type of therapeutic, namely "systems therapeutic", can be realized by reverse engineering the mechanisms of the SRM processes. Recent data demonstrates that the composition of the SRM is different for each type of stem cell, as well as for different states of each cell type. Although systems biology has been successfully used to analyze multiple pathways, the approach is often used to develop a small molecule interacting at only one pathway in the system. A new model is emerging in biology where systems biology is used to develop a new technology acting at multiple pathways called "systems therapeutics". A natural set of healing pathways in the human that uses SRM is instructive and of practical use in developing systems therapeutics. Endogenous SRM processes in the human body use a combination of SRM from two or more stem cell types, designated as S(2)RM, doing so under various state dependent conditions for each cell type. Here we describe our approach in using state-dependent SRM from two or more stem cell types, S(2)RM technology, to develop a new class of therapeutics called "systems therapeutics." Given the ubiquitous and powerful nature of innate S(2)RM-based healing in the human body, this "systems therapeutic" approach using S(2)RM technology will be important for the development of anti-cancer therapeutics, antimicrobials, wound care products and procedures, and a number of other therapeutics for many indications.

Microscopic video observation of capillary vessel systems using diffuse back lighting

NASA Astrophysics Data System (ADS)

Sakai, Minako; Arai, Hiroki; Iwai, Toshiaki

2017-04-01

We have been developing a simple and practical video microscopy system based on absorption spectra of biological substance to perform spectroscopic observation of living tissues. The diffuse backlighting effect is actively used in the developed system, which is generated by multiple light scattering in the tissue. It is demonstrated that the light specularly reflected from the skin surface can be completely suppressed in the microscopic observation and the biological activity of the capillary vessel systems distributed under the skin can be successfully observed. As a result, we can confirm the effectiveness of the video microscopy system using diffuse backlighting and the applicability of our developed system.

Integration of functional myotubes with a Bio-MEMS device for non-invasive interrogation.

PubMed

Wilson, Kerry; Molnar, Peter; Hickman, James

2007-07-01

We have developed a biological micro-electromechanical system (Bio-MEMS) device consisting of surface-modified microfabricated silicon cantilevers and an AFM detection apparatus for the study of cultured myotubes. With this system we are able to selectively stimulate the myotubes as well as report on a variety of physiological properties of the myotubes in real time and in a high-throughput manner. This system will serve as the foundation for future work integrating multiple tissue types for the creation of Bio-MEMS analogues of complex tissues and biological circuits.

Evolution of Bow-Tie Architectures in Biology

PubMed Central

Friedlander, Tamar; Mayo, Avraham E.; Tlusty, Tsvi; Alon, Uri

2015-01-01

Bow-tie or hourglass structure is a common architectural feature found in many biological systems. A bow-tie in a multi-layered structure occurs when intermediate layers have much fewer components than the input and output layers. Examples include metabolism where a handful of building blocks mediate between multiple input nutrients and multiple output biomass components, and signaling networks where information from numerous receptor types passes through a small set of signaling pathways to regulate multiple output genes. Little is known, however, about how bow-tie architectures evolve. Here, we address the evolution of bow-tie architectures using simulations of multi-layered systems evolving to fulfill a given input-output goal. We find that bow-ties spontaneously evolve when the information in the evolutionary goal can be compressed. Mathematically speaking, bow-ties evolve when the rank of the input-output matrix describing the evolutionary goal is deficient. The maximal compression possible (the rank of the goal) determines the size of the narrowest part of the network—that is the bow-tie. A further requirement is that a process is active to reduce the number of links in the network, such as product-rule mutations, otherwise a non-bow-tie solution is found in the evolutionary simulations. This offers a mechanism to understand a common architectural principle of biological systems, and a way to quantitate the effective rank of the goals under which they evolved. PMID:25798588

Cellular and Molecular Actions of Methylene Blue in the Nervous System

PubMed Central

Oz, Murat; Lorke, Dietrich E.; Hasan, Mohammed; Petroianu, George A.

2010-01-01

Methylene Blue (MB), following its introduction to biology in the 19th century by Ehrlich, has found uses in various areas of medicine and biology. At present, MB is the first line of treatment in methemoglobinemias, is used frequently in the treatment of ifosfamide-induced encephalopathy, and is routinely employed as a diagnostic tool in surgical procedures. Furthermore, recent studies suggest that MB has beneficial effects in Alzheimer's disease and memory improvement. Although the modulation of the cGMP pathway is considered the most significant effect of MB, mediating its pharmacological actions, recent studies indicate that it has multiple cellular and molecular targets. In the majority of cases, biological effects and clinical applications of MB are dictated by its unique physicochemical properties including its planar structure, redox chemistry, ionic charges, and light spectrum characteristics. In this review article, these physicochemical features and the actions of MB on multiple cellular and molecular targets are discussed with regard to their relevance to the nervous system. PMID:19760660

Fluorescent probes for the simultaneous detection of multiple analytes in biology.

PubMed

Kolanowski, Jacek L; Liu, Fei; New, Elizabeth J

2018-01-02

Many of the key questions facing cellular biology concern the location and concentration of chemical species, from signalling molecules to metabolites to exogenous toxins. Fluorescent sensors (probes) have revolutionised the understanding of biological systems through their exquisite sensitivity to specific analytes. Probe design has focussed on selective sensors for individual analytes, but many of the most pertinent biological questions are related to the interaction of more than one chemical species. While it is possible to simultaneously use multiple sensors for such applications, data interpretation will be confounded by the fact that sensors will have different uptake, localisation and metabolism profiles. An alternative solution is to instead use a single probe that responds to two analytes, termed a dual-responsive probe. Recent progress in this field has yielded exciting probes, some of which have demonstrated biological application. Here we review work that has been carried out to date, and suggest future research directions that will harness the considerable potential of dual-responsive fluorescent probes.

Estimating the dilemma strength for game systems. Comment on "Universal scaling for the dilemma strength in evolutionary games", by Z. Wang et al.

NASA Astrophysics Data System (ADS)

Chen, Xiaojie

2015-09-01

The puzzle of cooperation exists widely in the realistic world, including biological, social, and engineering systems. How to solve the cooperation puzzle has received considerable attention in recent years [1]. Evolutionary game theory provides a common mathematical framework to study the problem of cooperation. In principle, these practical biological, social, or engineering systems can be described by complex game models composed of multiple autonomous individuals with mutual interactions. And generally there exists a dilemma for the evolution of cooperation in the game systems.

MultiFocus Polarization Microscope (MF-PolScope) for 3D polarization imaging of up to 25 focal planes simultaneously

PubMed Central

Abrahamsson, Sara; McQuilken, Molly; Mehta, Shalin B.; Verma, Amitabh; Larsch, Johannes; Ilic, Rob; Heintzmann, Rainer; Bargmann, Cornelia I.; Gladfelter, Amy S.; Oldenbourg, Rudolf

2015-01-01

We have developed an imaging system for 3D time-lapse polarization microscopy of living biological samples. Polarization imaging reveals the position, alignment and orientation of submicroscopic features in label-free as well as fluorescently labeled specimens. Optical anisotropies are calculated from a series of images where the sample is illuminated by light of different polarization states. Due to the number of images necessary to collect both multiple polarization states and multiple focal planes, 3D polarization imaging is most often prohibitively slow. Our MF-PolScope system employs multifocus optics to form an instantaneous 3D image of up to 25 simultaneous focal-planes. We describe this optical system and show examples of 3D multi-focus polarization imaging of biological samples, including a protein assembly study in budding yeast cells. PMID:25837112

SPARK: A Framework for Multi-Scale Agent-Based Biomedical Modeling.

PubMed

Solovyev, Alexey; Mikheev, Maxim; Zhou, Leming; Dutta-Moscato, Joyeeta; Ziraldo, Cordelia; An, Gary; Vodovotz, Yoram; Mi, Qi

2010-01-01

Multi-scale modeling of complex biological systems remains a central challenge in the systems biology community. A method of dynamic knowledge representation known as agent-based modeling enables the study of higher level behavior emerging from discrete events performed by individual components. With the advancement of computer technology, agent-based modeling has emerged as an innovative technique to model the complexities of systems biology. In this work, the authors describe SPARK (Simple Platform for Agent-based Representation of Knowledge), a framework for agent-based modeling specifically designed for systems-level biomedical model development. SPARK is a stand-alone application written in Java. It provides a user-friendly interface, and a simple programming language for developing Agent-Based Models (ABMs). SPARK has the following features specialized for modeling biomedical systems: 1) continuous space that can simulate real physical space; 2) flexible agent size and shape that can represent the relative proportions of various cell types; 3) multiple spaces that can concurrently simulate and visualize multiple scales in biomedical models; 4) a convenient graphical user interface. Existing ABMs of diabetic foot ulcers and acute inflammation were implemented in SPARK. Models of identical complexity were run in both NetLogo and SPARK; the SPARK-based models ran two to three times faster.

Synthetic biology: applying biological circuits beyond novel therapies.

PubMed

Dobrin, Anton; Saxena, Pratik; Fussenegger, Martin

2016-04-18

Synthetic biology, an engineering, circuit-driven approach to biology, has developed whole new classes of therapeutics. Unfortunately, these advances have thus far been undercapitalized upon by basic researchers. As discussed herein, using synthetic circuits, one can undertake exhaustive investigations of the endogenous circuitry found in nature, develop novel detectors and better temporally and spatially controlled inducers. One could detect changes in DNA, RNA, protein or even transient signaling events, in cell-based systems, in live mice, and in humans. Synthetic biology has also developed inducible systems that can be induced chemically, optically or using radio waves. This induction has been re-wired to lead to changes in gene expression, RNA stability and splicing, protein stability and splicing, and signaling via endogenous pathways. Beyond simple detectors and inducible systems, one can combine these modalities and develop novel signal integration circuits that can react to a very precise pre-programmed set of conditions or even to multiple sets of precise conditions. In this review, we highlight some tools that were developed in which these circuits were combined such that the detection of a particular event automatically triggered a specific output. Furthermore, using novel circuit-design strategies, circuits have been developed that can integrate multiple inputs together in Boolean logic gates composed of up to 6 inputs. We highlight the tools available and what has been developed thus far, and highlight how some clinical tools can be very useful in basic science. Most of the systems that are presented can be integrated together; and the possibilities far exceed the number of currently developed strategies.

Small RNA biology is systems biology.

PubMed

Jost, Daniel; Nowojewski, Andrzej; Levine, Erel

2011-01-01

During the last decade small regulatory RNA (srRNA) emerged as central players in the regulation of gene expression in all kingdoms of life. Multiple pathways for srRNA biogenesis and diverse mechanisms of gene regulation may indicate that srRNA regulation evolved independently multiple times. However, small RNA pathways share numerous properties, including the ability of a single srRNA to regulate multiple targets. Some of the mechanisms of gene regulation by srRNAs have significant effect on the abundance of free srRNAs that are ready to interact with new targets. This results in indirect interactions among seemingly unrelated genes, as well as in a crosstalk between different srRNA pathways. Here we briefly review and compare the major srRNA pathways, and argue that the impact of srRNA is always at the system level. We demonstrate how a simple mathematical model can ease the discussion of governing principles. To demonstrate these points we review a few examples from bacteria and animals.

AlexSys: a knowledge-based expert system for multiple sequence alignment construction and analysis

PubMed Central

Aniba, Mohamed Radhouene; Poch, Olivier; Marchler-Bauer, Aron; Thompson, Julie Dawn

2010-01-01

Multiple sequence alignment (MSA) is a cornerstone of modern molecular biology and represents a unique means of investigating the patterns of conservation and diversity in complex biological systems. Many different algorithms have been developed to construct MSAs, but previous studies have shown that no single aligner consistently outperforms the rest. This has led to the development of a number of ‘meta-methods’ that systematically run several aligners and merge the output into one single solution. Although these methods generally produce more accurate alignments, they are inefficient because all the aligners need to be run first and the choice of the best solution is made a posteriori. Here, we describe the development of a new expert system, AlexSys, for the multiple alignment of protein sequences. AlexSys incorporates an intelligent inference engine to automatically select an appropriate aligner a priori, depending only on the nature of the input sequences. The inference engine was trained on a large set of reference multiple alignments, using a novel machine learning approach. Applying AlexSys to a test set of 178 alignments, we show that the expert system represents a good compromise between alignment quality and running time, making it suitable for high throughput projects. AlexSys is freely available from http://alnitak.u-strasbg.fr/∼aniba/alexsys. PMID:20530533

Joining Forces: The Chemical Biology-Medicinal Chemistry Continuum.

PubMed

Plowright, Alleyn T; Ottmann, Christian; Arkin, Michelle; Auberson, Yves P; Timmerman, Henk; Waldmann, Herbert

2017-09-21

The scientific advances being made across all disciplines are creating ever-increasing opportunities to enhance our knowledge of biological systems and how they relate to human disease. One of the central driving forces in discovering new medicines is medicinal chemistry, where the design and synthesis of novel compounds has led to multiple drugs. Chemical biology, sitting at the interface of many disciplines, has now emerged as a major contributor to the understanding of biological systems and is becoming an integral part of drug discovery. Bringing chemistry and biology much closer and blurring the boundaries between disciplines is creating new opportunities to probe and understand biology; both disciplines play key roles and need to join forces and work together effectively to synergize their impact. The power of chemical biology will then reach its full potential and drive innovation, leading to the discovery of transformative medicines to treat patients. Advances in cancer biology and drug discovery highlight this potential. Copyright © 2017 Elsevier Ltd. All rights reserved.

End-to-End Data System Architecture for the Space Station Biological Research Project

NASA Technical Reports Server (NTRS)

Mian, Arshad; Scimemi, Sam; Adeni, Kaiser; Picinich, Lou; Ramos, Rubin (Technical Monitor)

1998-01-01

The Space Station Biological Research Project (SSBRP) Is developing hardware referred to as the "facility" for providing life sciences research capability on the International Space Station. This hardware includes several biological specimen habitats, habitat holding racks, a centrifuge and a glovebox. An SSBRP end to end data system architecture has been developed to allow command and control of the facility from the ground, either with crew assistance or autonomously. The data system will be capable of handling commands, sensor data, and video from multiple cameras. The data will traverse through several onboard and ground networks and processing entities including the SSBRP and Space Station onboard and ground data systems. A large number of onboard and ground (,entities of the data system are being developed by the Space Station Program, other NASA centers and the International Partners. The SSBRP part of the system which includes the habitats, holding racks, and the ground operations center, User Operations Facility (UOF) will be developed by a multitude of geographically distributed development organizations. The SSBRP has the responsibility to define the end to end data and communications systems to make the interfaces manageable and verifiable with multiple contractors with widely varying development constraints and schedules. This paper provides an overview of the SSBRP end-to-end data system. Specifically, it describes the hardware, software and functional interactions of individual systems, and interface requirements among various entities of the end-to-end system.

Systems biology of personalized nutrition

PubMed Central

van Ommen, Ben; van den Broek, Tim; de Hoogh, Iris; van Erk, Marjan; van Someren, Eugene; Rouhani-Rankouhi, Tanja; Anthony, Joshua C; Hogenelst, Koen; Pasman, Wilrike; Boorsma, André; Wopereis, Suzan

2017-01-01

Abstract Personalized nutrition is fast becoming a reality due to a number of technological, scientific, and societal developments that complement and extend current public health nutrition recommendations. Personalized nutrition tailors dietary recommendations to specific biological requirements on the basis of a person’s health status and goals. The biology underpinning these recommendations is complex, and thus any recommendations must account for multiple biological processes and subprocesses occurring in various tissues and must be formed with an appreciation for how these processes interact with dietary nutrients and environmental factors. Therefore, a systems biology–based approach that considers the most relevant interacting biological mechanisms is necessary to formulate the best recommendations to help people meet their wellness goals. Here, the concept of “systems flexibility” is introduced to personalized nutrition biology. Systems flexibility allows the real-time evaluation of metabolism and other processes that maintain homeostasis following an environmental challenge, thereby enabling the formulation of personalized recommendations. Examples in the area of macro- and micronutrients are reviewed. Genetic variations and performance goals are integrated into this systems approach to provide a strategy for a balanced evaluation and an introduction to personalized nutrition. Finally, modeling approaches that combine personalized diagnosis and nutritional intervention into practice are reviewed. PMID:28969366

Effect of multiplicative noise on stationary stochastic process

NASA Astrophysics Data System (ADS)

Kargovsky, A. V.; Chikishev, A. Yu.; Chichigina, O. A.

2018-03-01

An open system that can be analyzed using the Langevin equation with multiplicative noise is considered. The stationary state of the system results from a balance of deterministic damping and random pumping simulated as noise with controlled periodicity. The dependence of statistical moments of the variable that characterizes the system on parameters of the problem is studied. A nontrivial decrease in the mean value of the main variable with an increase in noise stochasticity is revealed. Applications of the results in several physical, chemical, biological, and technical problems of natural and humanitarian sciences are discussed.

Circadian systems biology in Metazoa.

PubMed

Lin, Li-Ling; Huang, Hsuan-Cheng; Juan, Hsueh-Fen

2015-11-01

Systems biology, which can be defined as integrative biology, comprises multistage processes that can be used to understand components of complex biological systems of living organisms and provides hierarchical information to decoding life. Using systems biology approaches such as genomics, transcriptomics and proteomics, it is now possible to delineate more complicated interactions between circadian control systems and diseases. The circadian rhythm is a multiscale phenomenon existing within the body that influences numerous physiological activities such as changes in gene expression, protein turnover, metabolism and human behavior. In this review, we describe the relationships between the circadian control system and its related genes or proteins, and circadian rhythm disorders in systems biology studies. To maintain and modulate circadian oscillation, cells possess elaborative feedback loops composed of circadian core proteins that regulate the expression of other genes through their transcriptional activities. The disruption of these rhythms has been reported to be associated with diseases such as arrhythmia, obesity, insulin resistance, carcinogenesis and disruptions in natural oscillations in the control of cell growth. This review demonstrates that lifestyle is considered as a fundamental factor that modifies circadian rhythm, and the development of dysfunctions and diseases could be regulated by an underlying expression network with multiple circadian-associated signals. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Stress Effects on Multiple Memory System Interactions

PubMed Central

Ness, Deborah; Calabrese, Pasquale

2016-01-01

Extensive behavioural, pharmacological, and neurological research reports stress effects on mammalian memory processes. While stress effects on memory quantity have been known for decades, the influence of stress on multiple memory systems and their distinct contributions to the learning process have only recently been described. In this paper, after summarizing the fundamental biological aspects of stress/emotional arousal and recapitulating functionally and anatomically distinct memory systems, we review recent animal and human studies exploring the effects of stress on multiple memory systems. Apart from discussing the interaction between distinct memory systems in stressful situations, we will also outline the fundamental role of the amygdala in mediating such stress effects. Additionally, based on the methods applied in the herein discussed studies, we will discuss how memory translates into behaviour. PMID:27034845

An integrated cell-free metabolic platform for protein production and synthetic biology

PubMed Central

Jewett, Michael C; Calhoun, Kara A; Voloshin, Alexei; Wuu, Jessica J; Swartz, James R

2008-01-01

Cell-free systems offer a unique platform for expanding the capabilities of natural biological systems for useful purposes, i.e. synthetic biology. They reduce complexity, remove structural barriers, and do not require the maintenance of cell viability. Cell-free systems, however, have been limited by their inability to co-activate multiple biochemical networks in a single integrated platform. Here, we report the assessment of biochemical reactions in an Escherichia coli cell-free platform designed to activate natural metabolism, the Cytomim system. We reveal that central catabolism, oxidative phosphorylation, and protein synthesis can be co-activated in a single reaction system. Never before have these complex systems been shown to be simultaneously activated without living cells. The Cytomim system therefore promises to provide the metabolic foundation for diverse ab initio cell-free synthetic biology projects. In addition, we describe an improved Cytomim system with enhanced protein synthesis yields (up to 1200 mg/l in 2 h) and lower costs to facilitate production of protein therapeutics and biochemicals that are difficult to make in vivo because of their toxicity, complexity, or unusual cofactor requirements. PMID:18854819

Generation of the Dimensional Embryology Application (App) for Visualization of Early Chick and Frog Embryonic Development

ERIC Educational Resources Information Center

Webb, Rebecca L.; Bilitski, James; Zerbee, Alyssa; Symans, Alexandra; Chop, Alexandra; Seitz, Brianne; Tran, Cindy

2015-01-01

The study of embryonic development of multiple organisms, including model organisms such as frogs and chicks, is included in many undergraduate biology programs, as well as in a variety of graduate programs. As our knowledge of biological systems increases and the amount of material to be taught expands, the time spent instructing students about…

SBML-PET-MPI: a parallel parameter estimation tool for Systems Biology Markup Language based models.

PubMed

Zi, Zhike

2011-04-01

Parameter estimation is crucial for the modeling and dynamic analysis of biological systems. However, implementing parameter estimation is time consuming and computationally demanding. Here, we introduced a parallel parameter estimation tool for Systems Biology Markup Language (SBML)-based models (SBML-PET-MPI). SBML-PET-MPI allows the user to perform parameter estimation and parameter uncertainty analysis by collectively fitting multiple experimental datasets. The tool is developed and parallelized using the message passing interface (MPI) protocol, which provides good scalability with the number of processors. SBML-PET-MPI is freely available for non-commercial use at http://www.bioss.uni-freiburg.de/cms/sbml-pet-mpi.html or http://sites.google.com/site/sbmlpetmpi/.

How protein materials balance strength, robustness, and adaptability

PubMed Central

Buehler, Markus J.; Yung, Yu Ching

2010-01-01

Proteins form the basis of a wide range of biological materials such as hair, skin, bone, spider silk, or cells, which play an important role in providing key functions to biological systems. The focus of this article is to discuss how protein materials are capable of balancing multiple, seemingly incompatible properties such as strength, robustness, and adaptability. To illustrate this, we review bottom-up materiomics studies focused on the mechanical behavior of protein materials at multiple scales, from nano to macro. We focus on alpha-helix based intermediate filament proteins as a model system to explain why the utilization of hierarchical structural features is vital to their ability to combine strength, robustness, and adaptability. Experimental studies demonstrating the activation of angiogenesis, the growth of new blood vessels, are presented as an example of how adaptability of structure in biological tissue is achieved through changes in gene expression that result in an altered material structure. We analyze the concepts in light of the universality and diversity of the structural makeup of protein materials and discuss the findings in the context of potential fundamental evolutionary principles that control their nanoscale structure. We conclude with a discussion of multiscale science in biology and de novo materials design. PMID:20676305

Biana: a software framework for compiling biological interactions and analyzing networks

PubMed Central

2010-01-01

Background The analysis and usage of biological data is hindered by the spread of information across multiple repositories and the difficulties posed by different nomenclature systems and storage formats. In particular, there is an important need for data unification in the study and use of protein-protein interactions. Without good integration strategies, it is difficult to analyze the whole set of available data and its properties. Results We introduce BIANA (Biologic Interactions and Network Analysis), a tool for biological information integration and network management. BIANA is a Python framework designed to achieve two major goals: i) the integration of multiple sources of biological information, including biological entities and their relationships, and ii) the management of biological information as a network where entities are nodes and relationships are edges. Moreover, BIANA uses properties of proteins and genes to infer latent biomolecular relationships by transferring edges to entities sharing similar properties. BIANA is also provided as a plugin for Cytoscape, which allows users to visualize and interactively manage the data. A web interface to BIANA providing basic functionalities is also available. The software can be downloaded under GNU GPL license from http://sbi.imim.es/web/BIANA.php. Conclusions BIANA's approach to data unification solves many of the nomenclature issues common to systems dealing with biological data. BIANA can easily be extended to handle new specific data repositories and new specific data types. The unification protocol allows BIANA to be a flexible tool suitable for different user requirements: non-expert users can use a suggested unification protocol while expert users can define their own specific unification rules. PMID:20105306

Biana: a software framework for compiling biological interactions and analyzing networks.

PubMed

Garcia-Garcia, Javier; Guney, Emre; Aragues, Ramon; Planas-Iglesias, Joan; Oliva, Baldo

2010-01-27

The analysis and usage of biological data is hindered by the spread of information across multiple repositories and the difficulties posed by different nomenclature systems and storage formats. In particular, there is an important need for data unification in the study and use of protein-protein interactions. Without good integration strategies, it is difficult to analyze the whole set of available data and its properties. We introduce BIANA (Biologic Interactions and Network Analysis), a tool for biological information integration and network management. BIANA is a Python framework designed to achieve two major goals: i) the integration of multiple sources of biological information, including biological entities and their relationships, and ii) the management of biological information as a network where entities are nodes and relationships are edges. Moreover, BIANA uses properties of proteins and genes to infer latent biomolecular relationships by transferring edges to entities sharing similar properties. BIANA is also provided as a plugin for Cytoscape, which allows users to visualize and interactively manage the data. A web interface to BIANA providing basic functionalities is also available. The software can be downloaded under GNU GPL license from http://sbi.imim.es/web/BIANA.php. BIANA's approach to data unification solves many of the nomenclature issues common to systems dealing with biological data. BIANA can easily be extended to handle new specific data repositories and new specific data types. The unification protocol allows BIANA to be a flexible tool suitable for different user requirements: non-expert users can use a suggested unification protocol while expert users can define their own specific unification rules.

End-to-end automated microfluidic platform for synthetic biology: from design to functional analysis

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

Linshiz, Gregory; Jensen, Erik; Stawski, Nina

Synthetic biology aims to engineer biological systems for desired behaviors. The construction of these systems can be complex, often requiring genetic reprogramming, extensive de novo DNA synthesis, and functional screening. Here, we present a programmable, multipurpose microfluidic platform and associated software and apply the platform to major steps of the synthetic biology research cycle: design, construction, testing, and analysis. We show the platform’s capabilities for multiple automated DNA assembly methods, including a new method for Isothermal Hierarchical DNA Construction, and for Escherichia coli and Saccharomyces cerevisiae transformation. The platform enables the automated control of cellular growth, gene expression induction, andmore » proteogenic and metabolic output analysis. Finally, taken together, we demonstrate the microfluidic platform’s potential to provide end-to-end solutions for synthetic biology research, from design to functional analysis.« less

End-to-end automated microfluidic platform for synthetic biology: from design to functional analysis

DOE PAGES

Linshiz, Gregory; Jensen, Erik; Stawski, Nina; ...

2016-02-02

Synthetic biology aims to engineer biological systems for desired behaviors. The construction of these systems can be complex, often requiring genetic reprogramming, extensive de novo DNA synthesis, and functional screening. Here, we present a programmable, multipurpose microfluidic platform and associated software and apply the platform to major steps of the synthetic biology research cycle: design, construction, testing, and analysis. We show the platform’s capabilities for multiple automated DNA assembly methods, including a new method for Isothermal Hierarchical DNA Construction, and for Escherichia coli and Saccharomyces cerevisiae transformation. The platform enables the automated control of cellular growth, gene expression induction, andmore » proteogenic and metabolic output analysis. Finally, taken together, we demonstrate the microfluidic platform’s potential to provide end-to-end solutions for synthetic biology research, from design to functional analysis.« less

Approaches to Quality Risk Management When Using Single-Use Systems in the Manufacture of Biologics.

PubMed

Ishii-Watabe, Akiko; Hirose, Akihiko; Katori, Noriko; Hashii, Norikata; Arai, Susumu; Awatsu, Hirotoshi; Eiza, Akira; Hara, Yoshiaki; Hattori, Hideshi; Inoue, Tomomi; Isono, Tetsuya; Iwakura, Masahiro; Kajihara, Daisuke; Kasahara, Nobuo; Matsuda, Hiroyuki; Murakami, Sei; Nakagawa, Taishiro; Okumura, Takehiro; Omasa, Takeshi; Takuma, Shinya; Terashima, Iyo; Tsukahara, Masayoshi; Tsutsui, Maiko; Yano, Takahiro; Kawasaki, Nana

2015-10-01

Biologics manufacturing technology has made great progress in the last decade. One of the most promising new technologies is the single-use system, which has improved the efficiency of biologics manufacturing processes. To ensure safety of biologics when employing such single-use systems in the manufacturing process, various issues need to be considered including possible extractables/leachables and particles arising from the components used in single-use systems. Japanese pharmaceutical manufacturers, together with single-use suppliers, members of the academia and regulatory authorities have discussed the risks of using single-use systems and established control strategies for the quality assurance of biologics. In this study, we describe approaches for quality risk management when employing single-use systems in the manufacturing of biologics. We consider the potential impact of impurities related to single-use components on drug safety and the potential impact of the single-use system on other critical quality attributes as well as the stable supply of biologics. We also suggest a risk-mitigating strategy combining multiple control methods which includes the selection of appropriate single-use components, their inspections upon receipt and before releasing for use and qualification of single-use systems. Communication between suppliers of single-use systems and the users, as well as change controls in the facilities both of suppliers and users, are also important in risk-mitigating strategies. Implementing these control strategies can mitigate the risks attributed to the use of single-use systems. This study will be useful in promoting the development of biologics as well as in ensuring their safety, quality and stable supply.

36 CFR 219.1 - Purpose.

Code of Federal Regulations, 2011 CFR

2011-07-01

... System include: The Organic Administration Act of 1897, as amended (16 U.S.C. 473 et seq.); the Multiple..., forage, timber, wildlife and fish, biological diversity, productive soils, clean air and water, and...

36 CFR 219.1 - Purpose.

Code of Federal Regulations, 2010 CFR

2010-07-01

... System include: The Organic Administration Act of 1897, as amended (16 U.S.C. 473 et seq.); the Multiple..., forage, timber, wildlife and fish, biological diversity, productive soils, clean air and water, and...

Leveraging non-targeted metabolite profiling via statistical genomics

USDA-ARS?s Scientific Manuscript database

One of the challenges of systems biology is to integrate multiple sources of data in order to build a cohesive view of the system of study. Here we describe the mass spectrometry based profiling of maize kernels, a model system for genomic studies and a cornerstone of the agroeconomy. Using a networ...

Set membership experimental design for biological systems.

PubMed

Marvel, Skylar W; Williams, Cranos M

2012-03-21

Experimental design approaches for biological systems are needed to help conserve the limited resources that are allocated for performing experiments. The assumptions used when assigning probability density functions to characterize uncertainty in biological systems are unwarranted when only a small number of measurements can be obtained. In these situations, the uncertainty in biological systems is more appropriately characterized in a bounded-error context. Additionally, effort must be made to improve the connection between modelers and experimentalists by relating design metrics to biologically relevant information. Bounded-error experimental design approaches that can assess the impact of additional measurements on model uncertainty are needed to identify the most appropriate balance between the collection of data and the availability of resources. In this work we develop a bounded-error experimental design framework for nonlinear continuous-time systems when few data measurements are available. This approach leverages many of the recent advances in bounded-error parameter and state estimation methods that use interval analysis to generate parameter sets and state bounds consistent with uncertain data measurements. We devise a novel approach using set-based uncertainty propagation to estimate measurement ranges at candidate time points. We then use these estimated measurements at the candidate time points to evaluate which candidate measurements furthest reduce model uncertainty. A method for quickly combining multiple candidate time points is presented and allows for determining the effect of adding multiple measurements. Biologically relevant metrics are developed and used to predict when new data measurements should be acquired, which system components should be measured and how many additional measurements should be obtained. The practicability of our approach is illustrated with a case study. This study shows that our approach is able to 1) identify candidate measurement time points that maximize information corresponding to biologically relevant metrics and 2) determine the number at which additional measurements begin to provide insignificant information. This framework can be used to balance the availability of resources with the addition of one or more measurement time points to improve the predictability of resulting models.

Set membership experimental design for biological systems

PubMed Central

2012-01-01

Background Experimental design approaches for biological systems are needed to help conserve the limited resources that are allocated for performing experiments. The assumptions used when assigning probability density functions to characterize uncertainty in biological systems are unwarranted when only a small number of measurements can be obtained. In these situations, the uncertainty in biological systems is more appropriately characterized in a bounded-error context. Additionally, effort must be made to improve the connection between modelers and experimentalists by relating design metrics to biologically relevant information. Bounded-error experimental design approaches that can assess the impact of additional measurements on model uncertainty are needed to identify the most appropriate balance between the collection of data and the availability of resources. Results In this work we develop a bounded-error experimental design framework for nonlinear continuous-time systems when few data measurements are available. This approach leverages many of the recent advances in bounded-error parameter and state estimation methods that use interval analysis to generate parameter sets and state bounds consistent with uncertain data measurements. We devise a novel approach using set-based uncertainty propagation to estimate measurement ranges at candidate time points. We then use these estimated measurements at the candidate time points to evaluate which candidate measurements furthest reduce model uncertainty. A method for quickly combining multiple candidate time points is presented and allows for determining the effect of adding multiple measurements. Biologically relevant metrics are developed and used to predict when new data measurements should be acquired, which system components should be measured and how many additional measurements should be obtained. Conclusions The practicability of our approach is illustrated with a case study. This study shows that our approach is able to 1) identify candidate measurement time points that maximize information corresponding to biologically relevant metrics and 2) determine the number at which additional measurements begin to provide insignificant information. This framework can be used to balance the availability of resources with the addition of one or more measurement time points to improve the predictability of resulting models. PMID:22436240

HAlign-II: efficient ultra-large multiple sequence alignment and phylogenetic tree reconstruction with distributed and parallel computing.

PubMed

Wan, Shixiang; Zou, Quan

2017-01-01

Multiple sequence alignment (MSA) plays a key role in biological sequence analyses, especially in phylogenetic tree construction. Extreme increase in next-generation sequencing results in shortage of efficient ultra-large biological sequence alignment approaches for coping with different sequence types. Distributed and parallel computing represents a crucial technique for accelerating ultra-large (e.g. files more than 1 GB) sequence analyses. Based on HAlign and Spark distributed computing system, we implement a highly cost-efficient and time-efficient HAlign-II tool to address ultra-large multiple biological sequence alignment and phylogenetic tree construction. The experiments in the DNA and protein large scale data sets, which are more than 1GB files, showed that HAlign II could save time and space. It outperformed the current software tools. HAlign-II can efficiently carry out MSA and construct phylogenetic trees with ultra-large numbers of biological sequences. HAlign-II shows extremely high memory efficiency and scales well with increases in computing resource. THAlign-II provides a user-friendly web server based on our distributed computing infrastructure. HAlign-II with open-source codes and datasets was established at http://lab.malab.cn/soft/halign.

Control of Oscillation Patterns in a Symmetric Coupled Biological Oscillator System

NASA Astrophysics Data System (ADS)

Takamatsu, Atsuko; Tanaka, Reiko; Yamamoto, Takatoki; Fujii, Teruo

2003-08-01

A chain of three-oscillator system was constructed with living biological oscillators of phasmodial slime mold, Physarum polycehalum and the oscillation patterns were analyzed by the symmetric Hopf bifurcation theory using group theory. Multi-stability of oscillation patterns was observed, even when the coupling strength was fixed. This suggests that the coupling strength is not an effective parameter to obtain a desired oscillation pattern among the multiple patterns. Here we propose a method to control oscillation patterns using resonance to external stimulus and demonstrate pattern switching induced by frequency resonance given to only one of oscillators in the system.

Root Systems Biology: Integrative Modeling across Scales, from Gene Regulatory Networks to the Rhizosphere1

PubMed Central

Hill, Kristine; Porco, Silvana; Lobet, Guillaume; Zappala, Susan; Mooney, Sacha; Draye, Xavier; Bennett, Malcolm J.

2013-01-01

Genetic and genomic approaches in model organisms have advanced our understanding of root biology over the last decade. Recently, however, systems biology and modeling have emerged as important approaches, as our understanding of root regulatory pathways has become more complex and interpreting pathway outputs has become less intuitive. To relate root genotype to phenotype, we must move beyond the examination of interactions at the genetic network scale and employ multiscale modeling approaches to predict emergent properties at the tissue, organ, organism, and rhizosphere scales. Understanding the underlying biological mechanisms and the complex interplay between systems at these different scales requires an integrative approach. Here, we describe examples of such approaches and discuss the merits of developing models to span multiple scales, from network to population levels, and to address dynamic interactions between plants and their environment. PMID:24143806

Mathematical modeling of physiological systems: an essential tool for discovery.

PubMed

Glynn, Patric; Unudurthi, Sathya D; Hund, Thomas J

2014-08-28

Mathematical models are invaluable tools for understanding the relationships between components of a complex system. In the biological context, mathematical models help us understand the complex web of interrelations between various components (DNA, proteins, enzymes, signaling molecules etc.) in a biological system, gain better understanding of the system as a whole, and in turn predict its behavior in an altered state (e.g. disease). Mathematical modeling has enhanced our understanding of multiple complex biological processes like enzyme kinetics, metabolic networks, signal transduction pathways, gene regulatory networks, and electrophysiology. With recent advances in high throughput data generation methods, computational techniques and mathematical modeling have become even more central to the study of biological systems. In this review, we provide a brief history and highlight some of the important applications of modeling in biological systems with an emphasis on the study of excitable cells. We conclude with a discussion about opportunities and challenges for mathematical modeling going forward. In a larger sense, the review is designed to help answer a simple but important question that theoreticians frequently face from interested but skeptical colleagues on the experimental side: "What is the value of a model?" Copyright © 2014 Elsevier Inc. All rights reserved.

Blueprints for green biotech: development and application of standards for plant synthetic biology.

PubMed

Patron, Nicola J

2016-06-15

Synthetic biology aims to apply engineering principles to the design and modification of biological systems and to the construction of biological parts and devices. The ability to programme cells by providing new instructions written in DNA is a foundational technology of the field. Large-scale de novo DNA synthesis has accelerated synthetic biology by offering custom-made molecules at ever decreasing costs. However, for large fragments and for experiments in which libraries of DNA sequences are assembled in different combinations, assembly in the laboratory is still desirable. Biological assembly standards allow DNA parts, even those from multiple laboratories and experiments, to be assembled together using the same reagents and protocols. The adoption of such standards for plant synthetic biology has been cohesive for the plant science community, facilitating the application of genome editing technologies to plant systems and streamlining progress in large-scale, multi-laboratory bioengineering projects. © 2016 The Author(s). published by Portland Press Limited on behalf of the Biochemical Society.

Moving forward with imperfect information: chapter 19

USGS Publications Warehouse

Averyt, Kristen; Brekke, Levi D.; Kaatz, Laurna; Welling, Leigh; Hartge, Eric H.; Iseman, Tom

2013-01-01

- Climate change is one of multiple stresses affecting the physical, biological, social, and economic systems of the Southwest, with population growth (and its related resource consumption, pollution, and land-sue changes) being particularly important.

A New Era for Cancer Target Therapies: Applying Systems Biology and Computer-Aided Drug Design to Cancer Therapies.

PubMed

Wong, Yung-Hao; Chiu, Chia-Chiun; Lin, Chih-Lung; Chen, Ting-Shou; Jheng, Bo-Ren; Lee, Yu-Ching; Chen, Jeremy; Chen, Bor-Sen

In recent years, many systems biology approaches have been used with various cancers. The materials described here can be used to build bases to discover novel cancer therapy targets in connection with computer-aided drug design (CADD). A deeper understanding of the mechanisms of cancer will provide more choices and correct strategies in the development of multiple target drug therapies, which is quite different from the traditional cancer single target therapy. Targeted therapy is one of the most powerful strategies against cancer and can also be applied to other diseases. Due to the large amount of progress in computer hardware and the theories of computational chemistry and physics, CADD has been the main strategy for developing novel drugs for cancer therapy. In contrast to traditional single target therapies, in this review we will emphasize the future direction of the field, i.e., multiple target therapies. Structure-based and ligand-based drug designs are the two main topics of CADD. The former needs both 3D protein structures and ligand structures, while the latter only needs ligand structures. Ordinarily it is estimated to take more than 14 years and 800 million dollars to develop a new drug. Many new CADD software programs and techniques have been developed in recent decades. We conclude with an example where we combined and applied systems biology and CADD to the core networks of four cancers and successfully developed a novel cocktail for drug therapy that treats multiple targets.

Impact of environmental inputs on reverse-engineering approach to network structures.

PubMed

Wu, Jianhua; Sinfield, James L; Buchanan-Wollaston, Vicky; Feng, Jianfeng

2009-12-04

Uncovering complex network structures from a biological system is one of the main topic in system biology. The network structures can be inferred by the dynamical Bayesian network or Granger causality, but neither techniques have seriously taken into account the impact of environmental inputs. With considerations of natural rhythmic dynamics of biological data, we propose a system biology approach to reveal the impact of environmental inputs on network structures. We first represent the environmental inputs by a harmonic oscillator and combine them with Granger causality to identify environmental inputs and then uncover the causal network structures. We also generalize it to multiple harmonic oscillators to represent various exogenous influences. This system approach is extensively tested with toy models and successfully applied to a real biological network of microarray data of the flowering genes of the model plant Arabidopsis Thaliana. The aim is to identify those genes that are directly affected by the presence of the sunlight and uncover the interactive network structures associating with flowering metabolism. We demonstrate that environmental inputs are crucial for correctly inferring network structures. Harmonic causal method is proved to be a powerful technique to detect environment inputs and uncover network structures, especially when the biological data exhibit periodic oscillations.

Understanding the immune response to seasonal influenza vaccination in older adults: a systems biology approach.

PubMed

Lambert, Nathaniel D; Ovsyannikova, Inna G; Pankratz, V Shane; Jacobson, Robert M; Poland, Gregory A

2012-08-01

Annual vaccination against seasonal influenza is recommended to decrease disease-related mortality and morbidity. However, one population that responds suboptimally to influenza vaccine is adults over the age of 65 years. The natural aging process is associated with a complex deterioration of multiple components of the host immune system. Research into this phenomenon, known as immunosenescence, has shown that aging alters both the innate and adaptive branches of the immune system. The intricate mechanisms involved in immune response to influenza vaccine, and how these responses are altered with age, have led us to adopt a more encompassing systems biology approach to understand exactly why the response to vaccination diminishes with age. Here, the authors review what changes occur with immunosenescence, and some immunogenetic factors that influence response, and outline the systems biology approach to understand the immune response to seasonal influenza vaccination in older adults.

Integrated data analysis for genome-wide research.

PubMed

Steinfath, Matthias; Repsilber, Dirk; Scholz, Matthias; Walther, Dirk; Selbig, Joachim

2007-01-01

Integrated data analysis is introduced as the intermediate level of a systems biology approach to analyse different 'omics' datasets, i.e., genome-wide measurements of transcripts, protein levels or protein-protein interactions, and metabolite levels aiming at generating a coherent understanding of biological function. In this chapter we focus on different methods of correlation analyses ranging from simple pairwise correlation to kernel canonical correlation which were recently applied in molecular biology. Several examples are presented to illustrate their application. The input data for this analysis frequently originate from different experimental platforms. Therefore, preprocessing steps such as data normalisation and missing value estimation are inherent to this approach. The corresponding procedures, potential pitfalls and biases, and available software solutions are reviewed. The multiplicity of observations obtained in omics-profiling experiments necessitates the application of multiple testing correction techniques.

Neuromorphic neural interfaces: from neurophysiological inspiration to biohybrid coupling with nervous systems

NASA Astrophysics Data System (ADS)

Broccard, Frédéric D.; Joshi, Siddharth; Wang, Jun; Cauwenberghs, Gert

2017-08-01

Objective. Computation in nervous systems operates with different computational primitives, and on different hardware, than traditional digital computation and is thus subjected to different constraints from its digital counterpart regarding the use of physical resources such as time, space and energy. In an effort to better understand neural computation on a physical medium with similar spatiotemporal and energetic constraints, the field of neuromorphic engineering aims to design and implement electronic systems that emulate in very large-scale integration (VLSI) hardware the organization and functions of neural systems at multiple levels of biological organization, from individual neurons up to large circuits and networks. Mixed analog/digital neuromorphic VLSI systems are compact, consume little power and operate in real time independently of the size and complexity of the model. Approach. This article highlights the current efforts to interface neuromorphic systems with neural systems at multiple levels of biological organization, from the synaptic to the system level, and discusses the prospects for future biohybrid systems with neuromorphic circuits of greater complexity. Main results. Single silicon neurons have been interfaced successfully with invertebrate and vertebrate neural networks. This approach allowed the investigation of neural properties that are inaccessible with traditional techniques while providing a realistic biological context not achievable with traditional numerical modeling methods. At the network level, populations of neurons are envisioned to communicate bidirectionally with neuromorphic processors of hundreds or thousands of silicon neurons. Recent work on brain-machine interfaces suggests that this is feasible with current neuromorphic technology. Significance. Biohybrid interfaces between biological neurons and VLSI neuromorphic systems of varying complexity have started to emerge in the literature. Primarily intended as a computational tool for investigating fundamental questions related to neural dynamics, the sophistication of current neuromorphic systems now allows direct interfaces with large neuronal networks and circuits, resulting in potentially interesting clinical applications for neuroengineering systems, neuroprosthetics and neurorehabilitation.

Epidemiology and population biology of pseudoperonospora cubensis: a model system for management of downy mildews

USDA-ARS?s Scientific Manuscript database

The resurgence of cucurbit downy mildew has dramatically influenced production of cucurbits and disease management systems at multiple scales. Long-distance dispersal is a fundamental aspect of epidemic development that influences the timing and extent of disease outbreaks. Dispersal potential of th...

Radar remote sensing in biology

USGS Publications Warehouse

Moore, Richard K.; Simonett, David S.

1967-01-01

The present status of research on discrimination of natural and cultivated vegetation using radar imaging systems is sketched. The value of multiple polarization radar in improved discrimination of vegetation types over monoscopic radars is also documented. Possible future use of multi-frequency, multi-polarization radar systems for all weather agricultural survey is noted.

Allostatic load and biological anthropology.

PubMed

Edes, Ashley N; Crews, Douglas E

2017-01-01

Multiple stressors affect developing and adult organisms, thereby partly structuring their phenotypes. Determining how stressors influence health, well-being, and longevity in human and nonhuman primate populations are major foci within biological anthropology. Although much effort has been devoted to examining responses to multiple environmental and sociocultural stressors, no holistic metric to measure stress-related physiological dysfunction has been widely applied within biological anthropology. Researchers from disciplines outside anthropology are using allostatic load indices (ALIs) to estimate such dysregulation and examine life-long outcomes of stressor exposures, including morbidity and mortality. Following allostasis theory, allostatic load represents accumulated physiological and somatic damage secondary to stressors and senescent processes experienced over the lifespan. ALIs estimate this wear-and-tear using a composite of biomarkers representing neuroendocrine, cardiovascular, metabolic, and immune systems. Across samples, ALIs are associated significantly with multiple individual characteristics (e.g., age, sex, education, DNA variation) of interest within biological anthropology. They also predict future outcomes, including aspects of life history variation (e.g., survival, lifespan), mental and physical health, morbidity and mortality, and likely health disparities between groups, by stressor exposures, ethnicity, occupations, and degree of departure from local indigenous life ways and integration into external and commodified ones. ALIs also may be applied to similar stress-related research areas among nonhuman primates. Given the reports from multiple research endeavors, here we propose ALIs may be useful for assessing stressors, stress responses, and stress-related dysfunction, current and long-term cognitive function, health and well-being, and risk of early mortality across many research programs within biological anthropology. © 2017 American Association of Physical Anthropologists.

Unraveling flp-11/flp-32 dichotomy in nematodes.

PubMed

Atkinson, Louise E; Miskelly, Iain R; Moffett, Christy L; McCoy, Ciaran J; Maule, Aaron G; Marks, Nikki J; Mousley, Angela

2016-10-01

FMRFamide-like peptide (FLP) signalling systems are core to nematode neuromuscular function. Novel drug discovery efforts associated with nematode FLP/FLP receptor biology are advanced through the accumulation of basic biological data that can reveal subtle complexities within the neuropeptidergic system. This study reports the characterisation of FMRFamide-like peptide encoding gene-11 (flp-11) and FMRFamide-like peptide encoding gene-32 (flp-32), two distinct flp genes which encode the analogous peptide, AMRN(A/S)LVRFamide, in multiple nematode species - the only known example of this phenomenon within the FLPergic system of nematodes. Using bioinformatics, in situ hybridisation, immunocytochemistry and behavioural assays we show that: (i) flp-11 and -32 are distinct flp genes expressed individually or in tandem across multiple nematode species, where they encode a highly similar peptide; (ii) flp-11 does not appear to be the most widely expressed flp in Caenorhabditis elegans; (iii) in species expressing both flp-11 and flp-32, flp-11 displays a conserved, restricted expression pattern across nematode clades and lifestyles; (iv) in species expressing both flp-11 and flp-32, flp-32 expression is more widespread and less conserved than flp-11; (v) in species expressing only flp-11, the flp-11 expression profile is more similar to the flp-32 profile observed in species expressing both; and (vi) FLP-11 peptides inhibit motor function in multiple nematode species. The biological significance and evolutionary origin of flp-11 and -32 peptide duplication remains unclear despite attempts to identify a common ancestor; this may become clearer as the availability of genomic data improves. This work provides insight into the complexity of the neuropeptidergic system in nematodes, and begins to examine how nematodes may compensate for structural neuronal simplicity. From a parasite control standpoint, this work underscores the importance of basic biological data, and has wider implications for the utility of C. elegans as a model for parasite neurobiology. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Systems Epidemiology: What’s in a Name?

PubMed Central

Dammann, O.; Gray, P.; Gressens, P.; Wolkenhauer, O.; Leviton, A.

2014-01-01

Systems biology is an interdisciplinary effort to integrate molecular, cellular, tissue, organ, and organism levels of function into computational models that facilitate the identification of general principles. Systems medicine adds a disease focus. Systems epidemiology adds yet another level consisting of antecedents that might contribute to the disease process in populations. In etiologic and prevention research, systems-type thinking about multiple levels of causation will allow epidemiologists to identify contributors to disease at multiple levels as well as their interactions. In public health, systems epidemiology will contribute to the improvement of syndromic surveillance methods. We encourage the creation of computational simulation models that integrate information about disease etiology, pathogenetic data, and the expertise of investigators from different disciplines. PMID:25598870

Biological data warehousing system for identifying transcriptional regulatory sites from gene expressions of microarray data.

PubMed

Tsou, Ann-Ping; Sun, Yi-Ming; Liu, Chia-Lin; Huang, Hsien-Da; Horng, Jorng-Tzong; Tsai, Meng-Feng; Liu, Baw-Juine

2006-07-01

Identification of transcriptional regulatory sites plays an important role in the investigation of gene regulation. For this propose, we designed and implemented a data warehouse to integrate multiple heterogeneous biological data sources with data types such as text-file, XML, image, MySQL database model, and Oracle database model. The utility of the biological data warehouse in predicting transcriptional regulatory sites of coregulated genes was explored using a synexpression group derived from a microarray study. Both of the binding sites of known transcription factors and predicted over-represented (OR) oligonucleotides were demonstrated for the gene group. The potential biological roles of both known nucleotides and one OR nucleotide were demonstrated using bioassays. Therefore, the results from the wet-lab experiments reinforce the power and utility of the data warehouse as an approach to the genome-wide search for important transcription regulatory elements that are the key to many complex biological systems.

Disparities in breast cancer treatment and outcomes: biological, social, and health system determinants and opportunities for research.

PubMed

Wheeler, Stephanie B; Reeder-Hayes, Katherine E; Carey, Lisa A

2013-01-01

Racial disparities in breast cancer mortality have been widely documented for several decades and persist despite advances in receipt of mammography across racial groups. This persistence leads to questions about the roles of biological, social, and health system determinants of poor outcomes. Cancer outcomes are a function not only of innate biological factors but also of modifiable characteristics of individual behavior and decision making as well as characteristics of patient-health system interaction and the health system itself. Attempts to explain persistent racial disparities have mostly been limited to discussion of differences in insurance coverage, socioeconomic status, tumor stage at diagnosis, comorbidity, and molecular subtype of the tumor. This article summarizes existing literature exploring reasons for racial disparities in breast cancer mortality, with an emphasis on treatment disparities and opportunities for future research. Because breast cancer care requires a high degree of multidisciplinary team collaboration, ensuring that guideline recommended treatment (such as endocrine therapy for hormone receptor positive patients) is received by all racial/ethnic groups is critical and requires coordination across multiple providers and health care settings. Recognition that variation in cancer care quality may be correlated with race (and socioeconomic and health system factors) may assist policy makers in identifying strategies to more equally distribute clinical expertise and health infrastructure across multiple user populations.

Spiking neural P systems with multiple channels.

PubMed

Peng, Hong; Yang, Jinyu; Wang, Jun; Wang, Tao; Sun, Zhang; Song, Xiaoxiao; Luo, Xiaohui; Huang, Xiangnian

2017-11-01

Spiking neural P systems (SNP systems, in short) are a class of distributed parallel computing systems inspired from the neurophysiological behavior of biological spiking neurons. In this paper, we investigate a new variant of SNP systems in which each neuron has one or more synaptic channels, called spiking neural P systems with multiple channels (SNP-MC systems, in short). The spiking rules with channel label are introduced to handle the firing mechanism of neurons, where the channel labels indicate synaptic channels of transmitting the generated spikes. The computation power of SNP-MC systems is investigated. Specifically, we prove that SNP-MC systems are Turing universal as both number generating and number accepting devices. Copyright © 2017 Elsevier Ltd. All rights reserved.

A sense of life: computational and experimental investigations with models of biochemical and evolutionary processes.

PubMed

Mishra, Bud; Daruwala, Raoul-Sam; Zhou, Yi; Ugel, Nadia; Policriti, Alberto; Antoniotti, Marco; Paxia, Salvatore; Rejali, Marc; Rudra, Archisman; Cherepinsky, Vera; Silver, Naomi; Casey, William; Piazza, Carla; Simeoni, Marta; Barbano, Paolo; Spivak, Marina; Feng, Jiawu; Gill, Ofer; Venkatesh, Mysore; Cheng, Fang; Sun, Bing; Ioniata, Iuliana; Anantharaman, Thomas; Hubbard, E Jane Albert; Pnueli, Amir; Harel, David; Chandru, Vijay; Hariharan, Ramesh; Wigler, Michael; Park, Frank; Lin, Shih-Chieh; Lazebnik, Yuri; Winkler, Franz; Cantor, Charles R; Carbone, Alessandra; Gromov, Mikhael

2003-01-01

We collaborate in a research program aimed at creating a rigorous framework, experimental infrastructure, and computational environment for understanding, experimenting with, manipulating, and modifying a diverse set of fundamental biological processes at multiple scales and spatio-temporal modes. The novelty of our research is based on an approach that (i) requires coevolution of experimental science and theoretical techniques and (ii) exploits a certain universality in biology guided by a parsimonious model of evolutionary mechanisms operating at the genomic level and manifesting at the proteomic, transcriptomic, phylogenic, and other higher levels. Our current program in "systems biology" endeavors to marry large-scale biological experiments with the tools to ponder and reason about large, complex, and subtle natural systems. To achieve this ambitious goal, ideas and concepts are combined from many different fields: biological experimentation, applied mathematical modeling, computational reasoning schemes, and large-scale numerical and symbolic simulations. From a biological viewpoint, the basic issues are many: (i) understanding common and shared structural motifs among biological processes; (ii) modeling biological noise due to interactions among a small number of key molecules or loss of synchrony; (iii) explaining the robustness of these systems in spite of such noise; and (iv) cataloging multistatic behavior and adaptation exhibited by many biological processes.

Systems and precision medicine approaches to diabetes heterogeneity: a Big Data perspective.

PubMed

Capobianco, Enrico

2017-12-01

Big Data, and in particular Electronic Health Records, provide the medical community with a great opportunity to analyze multiple pathological conditions at an unprecedented depth for many complex diseases, including diabetes. How can we infer on diabetes from large heterogeneous datasets? A possible solution is provided by invoking next-generation computational methods and data analytics tools within systems medicine approaches. By deciphering the multi-faceted complexity of biological systems, the potential of emerging diagnostic tools and therapeutic functions can be ultimately revealed. In diabetes, a multidimensional approach to data analysis is needed to better understand the disease conditions, trajectories and the associated comorbidities. Elucidation of multidimensionality comes from the analysis of factors such as disease phenotypes, marker types, and biological motifs while seeking to make use of multiple levels of information including genetics, omics, clinical data, and environmental and lifestyle factors. Examining the synergy between multiple dimensions represents a challenge. In such regard, the role of Big Data fuels the rise of Precision Medicine by allowing an increasing number of descriptions to be captured from individuals. Thus, data curations and analyses should be designed to deliver highly accurate predicted risk profiles and treatment recommendations. It is important to establish linkages between systems and precision medicine in order to translate their principles into clinical practice. Equivalently, to realize their full potential, the involved multiple dimensions must be able to process information ensuring inter-exchange, reducing ambiguities and redundancies, and ultimately improving health care solutions by introducing clinical decision support systems focused on reclassified phenotypes (or digital biomarkers) and community-driven patient stratifications.

GENESIS 1.1: A hybrid-parallel molecular dynamics simulator with enhanced sampling algorithms on multiple computational platforms.

PubMed

Kobayashi, Chigusa; Jung, Jaewoon; Matsunaga, Yasuhiro; Mori, Takaharu; Ando, Tadashi; Tamura, Koichi; Kamiya, Motoshi; Sugita, Yuji

2017-09-30

GENeralized-Ensemble SImulation System (GENESIS) is a software package for molecular dynamics (MD) simulation of biological systems. It is designed to extend limitations in system size and accessible time scale by adopting highly parallelized schemes and enhanced conformational sampling algorithms. In this new version, GENESIS 1.1, new functions and advanced algorithms have been added. The all-atom and coarse-grained potential energy functions used in AMBER and GROMACS packages now become available in addition to CHARMM energy functions. The performance of MD simulations has been greatly improved by further optimization, multiple time-step integration, and hybrid (CPU + GPU) computing. The string method and replica-exchange umbrella sampling with flexible collective variable choice are used for finding the minimum free-energy pathway and obtaining free-energy profiles for conformational changes of a macromolecule. These new features increase the usefulness and power of GENESIS for modeling and simulation in biological research. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Enzyme-regulated the changes of pH values for assembling a colorimetric and multistage interconnection logic network with multiple readouts.

PubMed

Huang, Yanyan; Ran, Xiang; Lin, Youhui; Ren, Jinsong; Qu, Xiaogang

2015-04-22

Based on enzymatic reactions-triggered changes of pH values and biocomputing, a novel and multistage interconnection biological network with multiple easy-detectable signal outputs has been developed. Compared with traditional chemical computing, the enzyme-based biological system could overcome the interference between reactions or the incompatibility of individual computing gates and offer a unique opportunity to assemble multicomponent/multifunctional logic circuitries. Our system included four enzyme inputs: β-galactosidase (β-gal), glucose oxidase (GOx), esterase (Est) and urease (Ur). With the assistance of two signal transducers (gold nanoparticles and acid-base indicators) or pH meter, the outputs of the biological network could be conveniently read by the naked eyes. In contrast to current methods, the approach present here could realize cost-effective, label-free and colorimetric logic operations without complicated instrument. By designing a series of Boolean logic operations, we could logically make judgment of the compositions of the samples on the basis of visual output signals. Our work offered a promising paradigm for future biological computing technology and might be highly useful in future intelligent diagnostics, prodrug activation, smart drug delivery, process control, and electronic applications. Copyright © 2015 Elsevier B.V. All rights reserved.

[Establishment and Management of Multiple Myeloma Specimen Bank Applied for Molecular Biological Researches].

PubMed

Li, Han-Qing; Mei, Jian-Gang; Cao, Hong-Qin; Shao, Liang-Jing; Zhai, Yong-Ping

2017-12-01

To establish a multiple myeloma specimen bank applied for molecular biological researches and to explore the methods of specimen collection, transportation, storage, quality control and the management of specimen bank. Bone marrow and blood samples were collected from multiple myeloma patients, plasma cell sorting were operated after the separation of mononuclear cells from bone marrow specimens. The plasma cells were divided into 2 parts, one was added with proper amount of TRIzol and then kept in -80 °C refrigerator for subsequent RNA extraction, the other was added with proper amount of calf serum cell frozen liquid and then kept in -80 °C refrigerator for subsequent cryopreservation of DNA extraction after numbered respectively. Serum and plasma were separated from peripheral blood, specimens of serum and plasma were then stored at -80 °C refrigerator after registration. Meantime, the myeloma specimen information management system was established, managed and maintained by specially-assigned persons and continuous modification and improvement in the process of use as to facilitate the rapid collection, management, query of the effective samples and clinical data. A total of 244 portions plasma cells, 564 portions of serum, and 1005 portions of plasma were collected, clinical characters were documented. A multiple myeloma specimen bank have been established initially, which can provide quality samples and related clinical information for molecular biological research on multiple myeloma.

Parasites, proteomes and systems: has Descartes' clock run out of time?

PubMed

Wastling, J M; Armstrong, S D; Krishna, R; Xia, D

2012-08-01

Systems biology aims to integrate multiple biological data types such as genomics, transcriptomics and proteomics across different levels of structure and scale; it represents an emerging paradigm in the scientific process which challenges the reductionism that has dominated biomedical research for hundreds of years. Systems biology will nevertheless only be successful if the technologies on which it is based are able to deliver the required type and quality of data. In this review we discuss how well positioned is proteomics to deliver the data necessary to support meaningful systems modelling in parasite biology. We summarise the current state of identification proteomics in parasites, but argue that a new generation of quantitative proteomics data is now needed to underpin effective systems modelling. We discuss the challenges faced to acquire more complete knowledge of protein post-translational modifications, protein turnover and protein-protein interactions in parasites. Finally we highlight the central role of proteome-informatics in ensuring that proteomics data is readily accessible to the user-community and can be translated and integrated with other relevant data types.

Parasites, proteomes and systems: has Descartes’ clock run out of time?

PubMed Central

WASTLING, J. M.; ARMSTRONG, S. D.; KRISHNA, R.; XIA, D.

2012-01-01

SUMMARY Systems biology aims to integrate multiple biological data types such as genomics, transcriptomics and proteomics across different levels of structure and scale; it represents an emerging paradigm in the scientific process which challenges the reductionism that has dominated biomedical research for hundreds of years. Systems biology will nevertheless only be successful if the technologies on which it is based are able to deliver the required type and quality of data. In this review we discuss how well positioned is proteomics to deliver the data necessary to support meaningful systems modelling in parasite biology. We summarise the current state of identification proteomics in parasites, but argue that a new generation of quantitative proteomics data is now needed to underpin effective systems modelling. We discuss the challenges faced to acquire more complete knowledge of protein post-translational modifications, protein turnover and protein-protein interactions in parasites. Finally we highlight the central role of proteome-informatics in ensuring that proteomics data is readily accessible to the user-community and can be translated and integrated with other relevant data types. PMID:22828391

Potential control of multiple sclerosis by cannabis and the endocannabinoid system.

PubMed

Pryce, Gareth; Baker, David

2012-08-01

For many years, multiple sclerosis (MS) patients have been self-medicating with illegal street cannabis to alleviate symptoms associated with MS. Data from animal models of MS and clinical studies have supported the anecdotal data that cannabis can improve symptoms such as limb spasticity, which are commonly associated with progressive MS, by the modulation of excessive neuronal signalling. This has lead to cannabis-based medicines being approved for the treatment of pain and spasticity in MS for the first time. Experimental studies into the biology of the endocannabinoid system have revealed that cannabinoids have activity, not only in symptom relief but also potentially in neuroprotective strategies which may slow disease progression and thus delay the onset of symptoms such as spasticity. This review appraises the current knowledge of cannabinoid biology particularly as it pertains to MS and outlines potential future therapeutic strategies for the treatment of disease progression in MS.

The centrifuge facility - A life sciences research laboratory for Space Station Freedom

NASA Technical Reports Server (NTRS)

Fuller, Charles A.; Johnson, Catherine C.; Hargens, Alan R.

1991-01-01

The paper describes the centrifugal facility that is presently being developed by NASA for studies aboard the Space Station Freedom on the role of gravity, or its absence, at varying intensities for varying periods of time and with multiple model systems. Special attention is given to the design of the centrifuge system, the habitats designed to hold plants and animals, the glovebox system designed for experimental manipulations of the specimens, and the service unit. Studies planned for the facility will include experiments in the following disciplines: cell and developmental biology, plant biology, regulatory physiology, musculoskeletal physiology, behavior and performance, neurosciences, cardiopulmonary physiology, and environmental health and radiation.

Multiscale modeling of mucosal immune responses

PubMed Central

2015-01-01

Computational modeling techniques are playing increasingly important roles in advancing a systems-level mechanistic understanding of biological processes. Computer simulations guide and underpin experimental and clinical efforts. This study presents ENteric Immune Simulator (ENISI), a multiscale modeling tool for modeling the mucosal immune responses. ENISI's modeling environment can simulate in silico experiments from molecular signaling pathways to tissue level events such as tissue lesion formation. ENISI's architecture integrates multiple modeling technologies including ABM (agent-based modeling), ODE (ordinary differential equations), SDE (stochastic modeling equations), and PDE (partial differential equations). This paper focuses on the implementation and developmental challenges of ENISI. A multiscale model of mucosal immune responses during colonic inflammation, including CD4+ T cell differentiation and tissue level cell-cell interactions was developed to illustrate the capabilities, power and scope of ENISI MSM. Background Computational techniques are becoming increasingly powerful and modeling tools for biological systems are of greater needs. Biological systems are inherently multiscale, from molecules to tissues and from nano-seconds to a lifespan of several years or decades. ENISI MSM integrates multiple modeling technologies to understand immunological processes from signaling pathways within cells to lesion formation at the tissue level. This paper examines and summarizes the technical details of ENISI, from its initial version to its latest cutting-edge implementation. Implementation Object-oriented programming approach is adopted to develop a suite of tools based on ENISI. Multiple modeling technologies are integrated to visualize tissues, cells as well as proteins; furthermore, performance matching between the scales is addressed. Conclusion We used ENISI MSM for developing predictive multiscale models of the mucosal immune system during gut inflammation. Our modeling predictions dissect the mechanisms by which effector CD4+ T cell responses contribute to tissue damage in the gut mucosa following immune dysregulation. PMID:26329787

Multiscale modeling of mucosal immune responses.

PubMed

Mei, Yongguo; Abedi, Vida; Carbo, Adria; Zhang, Xiaoying; Lu, Pinyi; Philipson, Casandra; Hontecillas, Raquel; Hoops, Stefan; Liles, Nathan; Bassaganya-Riera, Josep

2015-01-01

Computational techniques are becoming increasingly powerful and modeling tools for biological systems are of greater needs. Biological systems are inherently multiscale, from molecules to tissues and from nano-seconds to a lifespan of several years or decades. ENISI MSM integrates multiple modeling technologies to understand immunological processes from signaling pathways within cells to lesion formation at the tissue level. This paper examines and summarizes the technical details of ENISI, from its initial version to its latest cutting-edge implementation. Object-oriented programming approach is adopted to develop a suite of tools based on ENISI. Multiple modeling technologies are integrated to visualize tissues, cells as well as proteins; furthermore, performance matching between the scales is addressed. We used ENISI MSM for developing predictive multiscale models of the mucosal immune system during gut inflammation. Our modeling predictions dissect the mechanisms by which effector CD4+ T cell responses contribute to tissue damage in the gut mucosa following immune dysregulation.Computational modeling techniques are playing increasingly important roles in advancing a systems-level mechanistic understanding of biological processes. Computer simulations guide and underpin experimental and clinical efforts. This study presents ENteric Immune Simulator (ENISI), a multiscale modeling tool for modeling the mucosal immune responses. ENISI's modeling environment can simulate in silico experiments from molecular signaling pathways to tissue level events such as tissue lesion formation. ENISI's architecture integrates multiple modeling technologies including ABM (agent-based modeling), ODE (ordinary differential equations), SDE (stochastic modeling equations), and PDE (partial differential equations). This paper focuses on the implementation and developmental challenges of ENISI. A multiscale model of mucosal immune responses during colonic inflammation, including CD4+ T cell differentiation and tissue level cell-cell interactions was developed to illustrate the capabilities, power and scope of ENISI MSM.

PeTTSy: a computational tool for perturbation analysis of complex systems biology models.

PubMed

Domijan, Mirela; Brown, Paul E; Shulgin, Boris V; Rand, David A

2016-03-10

Over the last decade sensitivity analysis techniques have been shown to be very useful to analyse complex and high dimensional Systems Biology models. However, many of the currently available toolboxes have either used parameter sampling, been focused on a restricted set of model observables of interest, studied optimisation of a objective function, or have not dealt with multiple simultaneous model parameter changes where the changes can be permanent or temporary. Here we introduce our new, freely downloadable toolbox, PeTTSy (Perturbation Theory Toolbox for Systems). PeTTSy is a package for MATLAB which implements a wide array of techniques for the perturbation theory and sensitivity analysis of large and complex ordinary differential equation (ODE) based models. PeTTSy is a comprehensive modelling framework that introduces a number of new approaches and that fully addresses analysis of oscillatory systems. It examines sensitivity analysis of the models to perturbations of parameters, where the perturbation timing, strength, length and overall shape can be controlled by the user. This can be done in a system-global setting, namely, the user can determine how many parameters to perturb, by how much and for how long. PeTTSy also offers the user the ability to explore the effect of the parameter perturbations on many different types of outputs: period, phase (timing of peak) and model solutions. PeTTSy can be employed on a wide range of mathematical models including free-running and forced oscillators and signalling systems. To enable experimental optimisation using the Fisher Information Matrix it efficiently allows one to combine multiple variants of a model (i.e. a model with multiple experimental conditions) in order to determine the value of new experiments. It is especially useful in the analysis of large and complex models involving many variables and parameters. PeTTSy is a comprehensive tool for analysing large and complex models of regulatory and signalling systems. It allows for simulation and analysis of models under a variety of environmental conditions and for experimental optimisation of complex combined experiments. With its unique set of tools it makes a valuable addition to the current library of sensitivity analysis toolboxes. We believe that this software will be of great use to the wider biological, systems biology and modelling communities.

Rebooting Bioresilience: A Multi-OMICS Approach to Tackle Global Catastrophic Biological Risks and Next-Generation Biothreats.

PubMed

Kambouris, Manousos E; Manoussopoulos, Yiannis; Kantzanou, Maria; Velegraki, Aristea; Gaitanis, Georgios; Arabatzis, Michalis; Patrinos, George P

2018-01-01

Global Catastrophic Biological Risks (GCBRs) refer to biological events-natural, deliberate, and accidental-of a global and lasting impact. This challenges the life scientists to raise their game on two hitherto neglected innovation frontiers: a veritable "futures" thinking to "think the unthinkable," and "systems thinking" so as to see both the trees and the forest when it comes to GCBRs. This innovation analysis article outlines the promise of Omics systems science biotechnologies, for example, to deploy rapid fire diagnostics for health security crises at GCBR level, possibly involving neopathogens and/or incurring epidemics (e.g., severe acute respiratory syndrome [SARS] and Ebola) that collectively threaten the lives of global society and interdependent biological ecosystems. Moreover, Omics encourages thinking beyond immediacy and in long-term strategies for biopreparedness and response innovation when the timelines are aggressive and compressed in response to crises such as GCBRs, but also to non-global but surging, multiple threats occurring as successive, overlapping, or distinct events, rather than as distinct entities-a prospect enforcing a reboot in Bioresilience. We define Next-Generation Bioresilience as "a systems approach against natural, accidental and perpetrated GCBRs using Omics technologies, and a shift in mentality, whereby the systems approach is expanded to include multiple plausible futures and expose unchecked assumptions attendant to risks, beyond technological determinism." In sum, it is time to think about the realistic potential of Omics biotechnologies beyond clinical practice and precision medicine so as to harness the opportunities and address the uncertainties associated not only with GCBRs but also with other emerging Omics applications in health and society.

UML as a cell and biochemistry modeling language.

PubMed

Webb, Ken; White, Tony

2005-06-01

The systems biology community is building increasingly complex models and simulations of cells and other biological entities, and are beginning to look at alternatives to traditional representations such as those provided by ordinary differential equations (ODE). The lessons learned over the years by the software development community in designing and building increasingly complex telecommunication and other commercial real-time reactive systems, can be advantageously applied to the problems of modeling in the biology domain. Making use of the object-oriented (OO) paradigm, the unified modeling language (UML) and Real-Time Object-Oriented Modeling (ROOM) visual formalisms, and the Rational Rose RealTime (RRT) visual modeling tool, we describe a multi-step process we have used to construct top-down models of cells and cell aggregates. The simple example model described in this paper includes membranes with lipid bilayers, multiple compartments including a variable number of mitochondria, substrate molecules, enzymes with reaction rules, and metabolic pathways. We demonstrate the relevance of abstraction, reuse, objects, classes, component and inheritance hierarchies, multiplicity, visual modeling, and other current software development best practices. We show how it is possible to start with a direct diagrammatic representation of a biological structure such as a cell, using terminology familiar to biologists, and by following a process of gradually adding more and more detail, arrive at a system with structure and behavior of arbitrary complexity that can run and be observed on a computer. We discuss our CellAK (Cell Assembly Kit) approach in terms of features found in SBML, CellML, E-CELL, Gepasi, Jarnac, StochSim, Virtual Cell, and membrane computing systems.

Evolution of natural history information in the 21st century – developing an integrated framework for biological and geographical data

USGS Publications Warehouse

Reusser, Deborah A.; Lee, Henry

2011-01-01

Threats to marine and estuarine species operate over many spatial scales, from nutrient enrichment at the watershed/estuarine scale to invasive species and climate change at regional and global scales. To help address research questions across these scales, we provide here a standardized framework for a biogeographical information system containing queriable biological data that allows extraction of information on multiple species, across a variety of spatial scales based on species distributions, natural history attributes and habitat requirements. As scientists shift from research on localized impacts on individual species to regional and global scale threats, macroecological approaches of studying multiple species over broad geographical areas are becoming increasingly important. The standardized framework described here for capturing and integrating biological and geographical data is a critical first step towards addressing these macroecological questions and we urge organizations capturing biogeoinformatics data to consider adopting this framework.

An online model composition tool for system biology models

PubMed Central

2013-01-01

Background There are multiple representation formats for Systems Biology computational models, and the Systems Biology Markup Language (SBML) is one of the most widely used. SBML is used to capture, store, and distribute computational models by Systems Biology data sources (e.g., the BioModels Database) and researchers. Therefore, there is a need for all-in-one web-based solutions that support advance SBML functionalities such as uploading, editing, composing, visualizing, simulating, querying, and browsing computational models. Results We present the design and implementation of the Model Composition Tool (Interface) within the PathCase-SB (PathCase Systems Biology) web portal. The tool helps users compose systems biology models to facilitate the complex process of merging systems biology models. We also present three tools that support the model composition tool, namely, (1) Model Simulation Interface that generates a visual plot of the simulation according to user’s input, (2) iModel Tool as a platform for users to upload their own models to compose, and (3) SimCom Tool that provides a side by side comparison of models being composed in the same pathway. Finally, we provide a web site that hosts BioModels Database models and a separate web site that hosts SBML Test Suite models. Conclusions Model composition tool (and the other three tools) can be used with little or no knowledge of the SBML document structure. For this reason, students or anyone who wants to learn about systems biology will benefit from the described functionalities. SBML Test Suite models will be a nice starting point for beginners. And, for more advanced purposes, users will able to access and employ models of the BioModels Database as well. PMID:24006914

cuTauLeaping: A GPU-Powered Tau-Leaping Stochastic Simulator for Massive Parallel Analyses of Biological Systems

PubMed Central

Besozzi, Daniela; Pescini, Dario; Mauri, Giancarlo

2014-01-01

Tau-leaping is a stochastic simulation algorithm that efficiently reconstructs the temporal evolution of biological systems, modeled according to the stochastic formulation of chemical kinetics. The analysis of dynamical properties of these systems in physiological and perturbed conditions usually requires the execution of a large number of simulations, leading to high computational costs. Since each simulation can be executed independently from the others, a massive parallelization of tau-leaping can bring to relevant reductions of the overall running time. The emerging field of General Purpose Graphic Processing Units (GPGPU) provides power-efficient high-performance computing at a relatively low cost. In this work we introduce cuTauLeaping, a stochastic simulator of biological systems that makes use of GPGPU computing to execute multiple parallel tau-leaping simulations, by fully exploiting the Nvidia's Fermi GPU architecture. We show how a considerable computational speedup is achieved on GPU by partitioning the execution of tau-leaping into multiple separated phases, and we describe how to avoid some implementation pitfalls related to the scarcity of memory resources on the GPU streaming multiprocessors. Our results show that cuTauLeaping largely outperforms the CPU-based tau-leaping implementation when the number of parallel simulations increases, with a break-even directly depending on the size of the biological system and on the complexity of its emergent dynamics. In particular, cuTauLeaping is exploited to investigate the probability distribution of bistable states in the Schlögl model, and to carry out a bidimensional parameter sweep analysis to study the oscillatory regimes in the Ras/cAMP/PKA pathway in S. cerevisiae. PMID:24663957

Evolving Relevance of Neuroproteomics in Alzheimer's Disease.

PubMed

Lista, Simone; Zetterberg, Henrik; O'Bryant, Sid E; Blennow, Kaj; Hampel, Harald

2017-01-01

Substantial progress in the understanding of the biology of Alzheimer's disease (AD) has been achieved over the past decades. The early detection and diagnosis of AD and other age-related neurodegenerative diseases, however, remain a challenging scientific frontier. Therefore, the comprehensive discovery (relating to all individual, converging or diverging biochemical disease mechanisms), development, validation, and qualification of standardized biological markers with diagnostic and prognostic functions with a precise performance profile regarding specificity, sensitivity, and positive and negative predictive value are warranted.Methodological innovations in the area of exploratory high-throughput technologies, such as sequencing, microarrays, and mass spectrometry-based analyses of proteins/peptides, have led to the generation of large global molecular datasets from a multiplicity of biological systems, such as biological fluids, cells, tissues, and organs. Such methodological progress has shifted the attention to the execution of hypothesis-independent comprehensive exploratory analyses (opposed to the classical hypothesis-driven candidate approach), with the aim of fully understanding the biological systems in physiology and disease as a whole. The systems biology paradigm integrates experimental biology with accurate and rigorous computational modelling to describe and foresee the dynamic features of biological systems. The use of dynamically evolving technological platforms, including mass spectrometry, in the area of proteomics has enabled to rush the process of biomarker discovery and validation for refining significantly the diagnosis of AD. Currently, proteomics-which is part of the systems biology paradigm-is designated as one of the dominant matured sciences needed for the effective exploratory discovery of prospective biomarker candidates expected to play an effective role in aiding the early detection, diagnosis, prognosis, and therapy development in AD.

Directed area search using socio-biological vision algorithms and cognitive Bayesian reasoning

NASA Astrophysics Data System (ADS)

Medasani, S.; Owechko, Y.; Allen, D.; Lu, T. C.; Khosla, D.

2010-04-01

Volitional search systems that assist the analyst by searching for specific targets or objects such as vehicles, factories, airports, etc in wide area overhead imagery need to overcome multiple problems present in current manual and automatic approaches. These problems include finding targets hidden in terabytes of information, relatively few pixels on targets, long intervals between interesting regions, time consuming analysis requiring many analysts, no a priori representative examples or templates of interest, detecting multiple classes of objects, and the need for very high detection rates and very low false alarm rates. This paper describes a conceptual analyst-centric framework that utilizes existing technology modules to search and locate occurrences of targets of interest (e.g., buildings, mobile targets of military significance, factories, nuclear plants, etc.), from video imagery of large areas. Our framework takes simple queries from the analyst and finds the queried targets with relatively minimum interaction from the analyst. It uses a hybrid approach that combines biologically inspired bottom up attention, socio-biologically inspired object recognition for volitionally recognizing targets, and hierarchical Bayesian networks for modeling and representing the domain knowledge. This approach has the benefits of high accuracy, low false alarm rate and can handle both low-level visual information and high-level domain knowledge in a single framework. Such a system would be of immense help for search and rescue efforts, intelligence gathering, change detection systems, and other surveillance systems.

Emergent properties of interacting populations of spiking neurons.

PubMed

Cardanobile, Stefano; Rotter, Stefan

2011-01-01

Dynamic neuronal networks are a key paradigm of increasing importance in brain research, concerned with the functional analysis of biological neuronal networks and, at the same time, with the synthesis of artificial brain-like systems. In this context, neuronal network models serve as mathematical tools to understand the function of brains, but they might as well develop into future tools for enhancing certain functions of our nervous system. Here, we present and discuss our recent achievements in developing multiplicative point processes into a viable mathematical framework for spiking network modeling. The perspective is that the dynamic behavior of these neuronal networks is faithfully reflected by a set of non-linear rate equations, describing all interactions on the population level. These equations are similar in structure to Lotka-Volterra equations, well known by their use in modeling predator-prey relations in population biology, but abundant applications to economic theory have also been described. We present a number of biologically relevant examples for spiking network function, which can be studied with the help of the aforementioned correspondence between spike trains and specific systems of non-linear coupled ordinary differential equations. We claim that, enabled by the use of multiplicative point processes, we can make essential contributions to a more thorough understanding of the dynamical properties of interacting neuronal populations.

Emergent Properties of Interacting Populations of Spiking Neurons

PubMed Central

Cardanobile, Stefano; Rotter, Stefan

2011-01-01

Dynamic neuronal networks are a key paradigm of increasing importance in brain research, concerned with the functional analysis of biological neuronal networks and, at the same time, with the synthesis of artificial brain-like systems. In this context, neuronal network models serve as mathematical tools to understand the function of brains, but they might as well develop into future tools for enhancing certain functions of our nervous system. Here, we present and discuss our recent achievements in developing multiplicative point processes into a viable mathematical framework for spiking network modeling. The perspective is that the dynamic behavior of these neuronal networks is faithfully reflected by a set of non-linear rate equations, describing all interactions on the population level. These equations are similar in structure to Lotka-Volterra equations, well known by their use in modeling predator-prey relations in population biology, but abundant applications to economic theory have also been described. We present a number of biologically relevant examples for spiking network function, which can be studied with the help of the aforementioned correspondence between spike trains and specific systems of non-linear coupled ordinary differential equations. We claim that, enabled by the use of multiplicative point processes, we can make essential contributions to a more thorough understanding of the dynamical properties of interacting neuronal populations. PMID:22207844

NASA Space Biology Plant Research for 2010-2020

NASA Technical Reports Server (NTRS)

Levine, H. G.; Tomko, D. L.; Porterfield, D. M.

2012-01-01

The U.S. National Research Council (NRC) recently published "Recapturing a Future for Space Exploration: Life and Physical Sciences Research for a New Era" (http://www.nap.edu/catalog.php?record id=13048), and NASA completed a Space Biology Science Plan to develop a strategy for implementing its recommendations ( http://www.nasa.gov/exploration/library/esmd documents.html). The most important recommendations of the NRC report on plant biology in space were that NASA should: (1) investigate the roles of microbial-plant systems in long-term bioregenerative life support systems, and (2) establish a robust spaceflight program of research analyzing plant growth and physiological responses to the multiple stimuli encountered in spaceflight environments. These efforts should take advantage of recently emerged analytical technologies (genomics, transcriptomics, proteomics, metabolomics) and apply modern cellular and molecular approaches in the development of a vigorous flight-based and ground-based research program. This talk will describe NASA's strategy and plans for implementing these NRC Plant Space Biology recommendations. New research capabilities for Plant Biology, optimized by providing state-of-the-art automated technology and analytical techniques to maximize scientific return, will be described. Flight experiments will use the most appropriate platform to achieve science results (e.g., ISS, free flyers, sub-orbital flights) and NASA will work closely with its international partners and other U.S. agencies to achieve its objectives. One of NASA's highest priorities in Space Biology is the development research capabilities for use on the International Space Station and other flight platforms for studying multiple generations of large plants. NASA will issue recurring NASA Research Announcements (NRAs) that include a rapid turn-around model to more fully engage the biology community in designing experiments to respond to the NRC recommendations. In doing so, NASA's Space Biology research will optimize ISS research utilization, develop and demonstrate technology and hardware that will enable new science, and contribute to the base of fundamental knowledge that will facilitate development of new tools for human space exploration and Earth applications. By taking these steps, NASA will energize the Space Biology user community and advance our knowledge of the effect of the space flight environment on living systems.

Strategies for efficient numerical implementation of hybrid multi-scale agent-based models to describe biological systems

PubMed Central

Cilfone, Nicholas A.; Kirschner, Denise E.; Linderman, Jennifer J.

2015-01-01

Biologically related processes operate across multiple spatiotemporal scales. For computational modeling methodologies to mimic this biological complexity, individual scale models must be linked in ways that allow for dynamic exchange of information across scales. A powerful methodology is to combine a discrete modeling approach, agent-based models (ABMs), with continuum models to form hybrid models. Hybrid multi-scale ABMs have been used to simulate emergent responses of biological systems. Here, we review two aspects of hybrid multi-scale ABMs: linking individual scale models and efficiently solving the resulting model. We discuss the computational choices associated with aspects of linking individual scale models while simultaneously maintaining model tractability. We demonstrate implementations of existing numerical methods in the context of hybrid multi-scale ABMs. Using an example model describing Mycobacterium tuberculosis infection, we show relative computational speeds of various combinations of numerical methods. Efficient linking and solution of hybrid multi-scale ABMs is key to model portability, modularity, and their use in understanding biological phenomena at a systems level. PMID:26366228

Multiple lymphomatous polyposis.

PubMed

Kadayifçi, A; Benekli, M; Savaş, M C; Arslan, S; Uzunalimoğlu, B; Barişta, I; Güllü, I H; Tekuzman, G

1997-04-01

Multiple lymphomatous polyposis (MLP) is a distinctive and particularly rare clinical type of malignant gastrointestinal lymphoma, which is classified as B-cell centrocytic non-Hodgkin's lymphoma. this rare entity has been recently reclassified as mantle cell lymphoma. We herein report three additional cases of MLP involving various segments of the gastrointestinal tract. MLP has an aggressive biologic behavior and a relatively poor prognosis and must be treated accordingly as a high-grade lymphoma with systemic chemotherapy.

The Effect of Multiple Intelligences Theory (MIT)-based Instruction on Attitudes towards the Course, Academic Success, and Permanence of Teaching on the Topic of "Respiratory Systems"

ERIC Educational Resources Information Center

Koksal, Mustafa Serdar; Yel, Mustafa

2007-01-01

Studies on the effective teaching of biology have been continuously increasing since the 1800s. New teaching approaches have been purposed and tried out along the way. The multiple intelligences theory (MIT)-based approaches which give more importance to individual in educational settings can provide alternatives for meeting this requirement. An…

6th Institute for Systems Biology International Symposium: Systems Biology and the Environment

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

Galitski, Timothy P.

2007-04-23

Systems biology recognizes the complex multi-scale organization of biological systems, from molecules to ecosystems. The International Symposium on Systems Biology is an annual two-day event gathering the most influential researchers transforming biology into an integrative discipline investigating complex systems. In recognition of the fundamental similarity between the scientific problems addressed in environmental science and systems biology studies at the molecular, cellular, and organismal levels, the 2007 Symposium featured global leaders in “Systems Biology and the Environment.” The objective of the 2007 “Systems Biology and the Environment” International Symposium was to stimulate interdisciplinary thinking and research that spans systems biology andmore » environmental science. This Symposium was well aligned with the DOE’s Genomics: GTL program efforts to achieve scientific objectives for each of the three DOE missions: Develop biofuels as a major secure energy source for this century; Develop biological solutions for intractable environmental problems; Understand biosystems’ climate impacts and assess sequestration strategies. Our scientific program highlighted world-class research exemplifying these priorities. The Symposium featured 45 minute lectures from 12 researchers including: Penny/Sallie Chisholm of MIT gave the keynote address “Tiny Cells, Global Impact: What Prochlorococcus Can Teach Us About Systems Biology”, plus Jim Fredrickson of PNNL, Nitin Baliga of ISB, Steve Briggs of UCSD, David Cox of Perlegen Sciences, Antoine Danchin of Institut Pasteur, John Delaney of the U of Washington, John Groopman of Johns Hopkins, Ben Kerr of the U of Washington, Steve Koonin of BP, Elliott Meyerowitz of Caltech, and Ed Rubin of LBNL. The 2007 Symposium promoted DOE’s three mission areas among scientists from multiple disciplines representing academia, non-profit research institutions, and the private sector. As in all previous Symposia, we had excellent attendance of participants representing 20-30 academic or research-oriented facilities along with 25-30 private corporations from 5-10 countries. To broaden the audience for the Symposium and ensure the continued accessibility of the presentations, we made the presentation videos available afterward on the ISB’s website.« less

Network motifs – recurring circuitry components in biological systems

EPA Science Inventory

Environmental perturbations, elicited by chemicals, dietary supplements, and drugs, can alter the dynamics of the molecular circuits and networks operating in cells, leading to multiple disease endpoints. Multi-component signal transduction pathways and gene regulatory circuits u...

Engineered Living Materials: Prospects and Challenges for Using Biological Systems to Direct the Assembly of Smart Materials.

PubMed

Nguyen, Peter Q; Courchesne, Noémie-Manuelle Dorval; Duraj-Thatte, Anna; Praveschotinunt, Pichet; Joshi, Neel S

2018-05-01

Vast potential exists for the development of novel, engineered platforms that manipulate biology for the production of programmed advanced materials. Such systems would possess the autonomous, adaptive, and self-healing characteristics of living organisms, but would be engineered with the goal of assembling bulk materials with designer physicochemical or mechanical properties, across multiple length scales. Early efforts toward such engineered living materials (ELMs) are reviewed here, with an emphasis on engineered bacterial systems, living composite materials which integrate inorganic components, successful examples of large-scale implementation, and production methods. In addition, a conceptual exploration of the fundamental criteria of ELM technology and its future challenges is presented. Cradled within the rich intersection of synthetic biology and self-assembling materials, the development of ELM technologies allows the power of biology to be leveraged to grow complex structures and objects using a palette of bio-nanomaterials. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Advances on plant-pathogen interactions from molecular toward systems biology perspectives.

PubMed

Peyraud, Rémi; Dubiella, Ullrich; Barbacci, Adelin; Genin, Stéphane; Raffaele, Sylvain; Roby, Dominique

2017-05-01

In the past 2 decades, progress in molecular analyses of the plant immune system has revealed key elements of a complex response network. Current paradigms depict the interaction of pathogen-secreted molecules with host target molecules leading to the activation of multiple plant response pathways. Further research will be required to fully understand how these responses are integrated in space and time, and exploit this knowledge in agriculture. In this review, we highlight systems biology as a promising approach to reveal properties of molecular plant-pathogen interactions and predict the outcome of such interactions. We first illustrate a few key concepts in plant immunity with a network and systems biology perspective. Next, we present some basic principles of systems biology and show how they allow integrating multiomics data and predict cell phenotypes. We identify challenges for systems biology of plant-pathogen interactions, including the reconstruction of multiscale mechanistic models and the connection of host and pathogen models. Finally, we outline studies on resistance durability through the robustness of immune system networks, the identification of trade-offs between immunity and growth and in silico plant-pathogen co-evolution as exciting perspectives in the field. We conclude that the development of sophisticated models of plant diseases incorporating plant, pathogen and climate properties represent a major challenge for agriculture in the future. © 2016 The Authors. The Plant Journal published by John Wiley & Sons Ltd and Society for Experimental Biology.

Declarative and nondeclarative memory: multiple brain systems supporting learning and memory.

PubMed

Squire, L R

1992-01-01

Abstract The topic of multiple forms of memory is considered from a biological point of view. Fact-and-event (declarative, explicit) memory is contrasted with a collection of non conscious (non-declarative, implicit) memory abilities including skills and habits, priming, and simple conditioning. Recent evidence is reviewed indicating that declarative and non declarative forms of memory have different operating characteristics and depend on separate brain systems. A brain-systems framework for understanding memory phenomena is developed in light of lesion studies involving rats, monkeys, and humans, as well as recent studies with normal humans using the divided visual field technique, event-related potentials, and positron emission tomography (PET).

Quantification of Degeneracy in Biological Systems for Characterization of Functional Interactions Between Modules

PubMed Central

Li, Yao; Dwivedi, Gaurav; Huang, Wen; Yi, Yingfei

2012-01-01

There is an evolutionary advantage in having multiple components with overlapping functionality (i.e degeneracy) in organisms. While theoretical considerations of degeneracy have been well established in neural networks using information theory, the same concepts have not been developed for differential systems, which form the basis of many biochemical reaction network descriptions in systems biology. Here we establish mathematical definitions of degeneracy, complexity and robustness that allow for the quantification of these properties in a system. By exciting a dynamical system with noise, the mutual information associated with a selected observable output and the interacting subspaces of input components can be used to define both complexity and degeneracy. The calculation of degeneracy in a biological network is a useful metric for evaluating features such as the sensitivity of a biological network to environmental evolutionary pressure. Using a two-receptor signal transduction network, we find that redundant components will not yield high degeneracy whereas compensatory mechanisms established by pathway crosstalk will. This form of analysis permits interrogation of large-scale differential systems for non-identical, functionally equivalent features that have evolved to maintain homeostasis during disruption of individual components. PMID:22619750

[Development and Application of Metabonomics in Forensic Toxicology].

PubMed

Yan, Hui; Shen, Min

2015-06-01

Metabonomics is an important branch of system biology following the development of genomics, transcriptomics and proteomics. It can perform high-throughput detection and data processing with multiple parameters, potentially enabling the identification and quantification of all small metabolites in a biological system. It can be used to provide comprehensive information on the toxicity effects, toxicological mechanisms and biomarkers, sensitively finding the unusual metabolic changes caused by poison. This article mainly reviews application of metabonomics in toxicological studies of abused drugs, pesticides, poisonous plants and poisonous animals, and also illustrates the new direction of forensic toxicology research.

Systemic lupus erythematosus diagnostics in the ‘omics’ era

PubMed Central

Arriens, Cristina; Mohan, Chandra

2014-01-01

Systemic lupus erythematosus is a complex autoimmune disease affecting multiple organ systems. Currently, diagnosis relies upon meeting at least four out of eleven criteria outlined by the ACR. The scientific community actively pursues discovery of novel diagnostics in the hope of better identifying susceptible individuals in early stages of disease. Comprehensive studies have been conducted at multiple biological levels including: DNA (or genomics), mRNA (or transcriptomics), protein (or proteomics) and metabolites (or metabolomics). The ‘omics’ platforms allow us to re-examine systemic lupus erythematosus at a greater degree of molecular resolution. More importantly, one is hopeful that these ‘omics’ platforms may yield newer biomarkers for systemic lupus erythematosus that can help clinicians track the disease course with greater sensitivity and specificity. PMID:24860621

The micronutrient genomics project: a community-driven knowledge base for micronutrient research

USDA-ARS?s Scientific Manuscript database

Micronutrients influence multiple metabolic pathways including oxidative and inflammatory processes. Optimum micronutrient supply is important for the maintenance of homeostasis in metabolism and, ultimately, for maintaining good health. With advances in systems biology and genomics technologies, it...

A standard-enabled workflow for synthetic biology.

PubMed

Myers, Chris J; Beal, Jacob; Gorochowski, Thomas E; Kuwahara, Hiroyuki; Madsen, Curtis; McLaughlin, James Alastair; Mısırlı, Göksel; Nguyen, Tramy; Oberortner, Ernst; Samineni, Meher; Wipat, Anil; Zhang, Michael; Zundel, Zach

2017-06-15

A synthetic biology workflow is composed of data repositories that provide information about genetic parts, sequence-level design tools to compose these parts into circuits, visualization tools to depict these designs, genetic design tools to select parts to create systems, and modeling and simulation tools to evaluate alternative design choices. Data standards enable the ready exchange of information within such a workflow, allowing repositories and tools to be connected from a diversity of sources. The present paper describes one such workflow that utilizes, among others, the Synthetic Biology Open Language (SBOL) to describe genetic designs, the Systems Biology Markup Language to model these designs, and SBOL Visual to visualize these designs. We describe how a standard-enabled workflow can be used to produce types of design information, including multiple repositories and software tools exchanging information using a variety of data standards. Recently, the ACS Synthetic Biology journal has recommended the use of SBOL in their publications. © 2017 The Author(s); published by Portland Press Limited on behalf of the Biochemical Society.

Mass Spectrometry: A Technique of Many Faces

PubMed Central

Olshina, Maya A.; Sharon, Michal

2016-01-01

Protein complexes form the critical foundation for a wide range of biological process, however understanding the intricate details of their activities is often challenging. In this review we describe how mass spectrometry plays a key role in the analysis of protein assemblies and the cellular pathways which they are involved in. Specifically, we discuss how the versatility of mass spectrometric approaches provides unprecedented information on multiple levels. We demonstrate this on the ubiquitin-proteasome proteolytic pathway, a process that is responsible for protein turnover. We follow the various steps of this degradation route and illustrate the different mass spectrometry workflows that were applied for elucidating molecular information. Overall, this review aims to stimulate the integrated use of multiple mass spectrometry approaches for analyzing complex biological systems. PMID:28100928

Distributed computation: the new wave of synthetic biology devices.

PubMed

Macía, Javier; Posas, Francesc; Solé, Ricard V

2012-06-01

Synthetic biology (SB) offers a unique opportunity for designing complex molecular circuits able to perform predefined functions. But the goal of achieving a flexible toolbox of reusable molecular components has been shown to be limited due to circuit unpredictability, incompatible parts or random fluctuations. Many of these problems arise from the challenges posed by engineering the molecular circuitry: multiple wires are usually difficult to implement reliably within one cell and the resulting systems cannot be reused in other modules. These problems are solved by means of a nonstandard approach to single cell devices, using cell consortia and allowing the output signal to be distributed among different cell types, which can be combined in multiple, reusable and scalable ways. Copyright © 2012 Elsevier Ltd. All rights reserved.

'Fish matters': the relevance of fish skin biology to investigative dermatology.

PubMed

Rakers, Sebastian; Gebert, Marina; Uppalapati, Sai; Meyer, Wilfried; Maderson, Paul; Sell, Anne F; Kruse, Charli; Paus, Ralf

2010-04-01

Fish skin is a multi-purpose tissue that serves numerous vital functions including chemical and physical protection, sensory activity, behavioural purposes or hormone metabolism. Further, it is an important first-line defense system against pathogens, as fish are continuously exposed to multiple microbial challenges in their aquatic habitat. Fish skin excels in highly developed antimicrobial features, many of which have been preserved throughout evolution, and infection defense principles employed by piscine skin are still operative in human skin. This review argues that it is both rewarding and important for investigative dermatologists to revive their interest in fish skin biology, as it provides insights into numerous fundamental issues that are of major relevance to mammalian skin. The basic molecular insights provided by zebrafish in vivo-genomics for genetic, regeneration and melanoma research, the complex antimicrobial defense systems of fish skin and the molecular controls of melanocyte stem cells are just some of the fascinating examples that illustrate the multiple potential uses of fish skin models in investigative dermatology. We synthesize the essentials of fish skin biology and highlight selected aspects that are of particular comparative interest to basic and clinically applied human skin research.

Dispatches from the Interface of Salivary Bioscience and Neonatal Research

PubMed Central

Voegtline, Kristin M.; Granger, Douglas A.

2014-01-01

The emergence of the interdisciplinary field of salivary bioscience has created opportunity for neonatal researchers to measure multiple components of biological systems non-invasively in oral fluids. The implications are profound and potentially high impact. From a single oral fluid specimen, information can be obtained about a vast array of biological systems (e.g., endocrine, immune, autonomic nervous system) and the genetic polymorphisms related to individual differences in their function. The purpose of this review is to describe the state of the art for investigators interested in integrating these unique measurement tools into the current and next generation of research on gonadal steroid exposure during the prenatal and neonatal developmental periods. PMID:24624119

Epsilon-Q: An Automated Analyzer Interface for Mass Spectral Library Search and Label-Free Protein Quantification.

PubMed

Cho, Jin-Young; Lee, Hyoung-Joo; Jeong, Seul-Ki; Paik, Young-Ki

2017-12-01

Mass spectrometry (MS) is a widely used proteome analysis tool for biomedical science. In an MS-based bottom-up proteomic approach to protein identification, sequence database (DB) searching has been routinely used because of its simplicity and convenience. However, searching a sequence DB with multiple variable modification options can increase processing time, false-positive errors in large and complicated MS data sets. Spectral library searching is an alternative solution, avoiding the limitations of sequence DB searching and allowing the detection of more peptides with high sensitivity. Unfortunately, this technique has less proteome coverage, resulting in limitations in the detection of novel and whole peptide sequences in biological samples. To solve these problems, we previously developed the "Combo-Spec Search" method, which uses manually multiple references and simulated spectral library searching to analyze whole proteomes in a biological sample. In this study, we have developed a new analytical interface tool called "Epsilon-Q" to enhance the functions of both the Combo-Spec Search method and label-free protein quantification. Epsilon-Q performs automatically multiple spectral library searching, class-specific false-discovery rate control, and result integration. It has a user-friendly graphical interface and demonstrates good performance in identifying and quantifying proteins by supporting standard MS data formats and spectrum-to-spectrum matching powered by SpectraST. Furthermore, when the Epsilon-Q interface is combined with the Combo-Spec search method, called the Epsilon-Q system, it shows a synergistic function by outperforming other sequence DB search engines for identifying and quantifying low-abundance proteins in biological samples. The Epsilon-Q system can be a versatile tool for comparative proteome analysis based on multiple spectral libraries and label-free quantification.

Reasoning from non-stationarity

NASA Astrophysics Data System (ADS)

Struzik, Zbigniew R.; van Wijngaarden, Willem J.; Castelo, Robert

2002-11-01

Complex real-world (biological) systems often exhibit intrinsically non-stationary behaviour of their temporal characteristics. We discuss local measures of scaling which can capture and reveal changes in a system's behaviour. Such measures offer increased insight into a system's behaviour and are superior to global, spectral characteristics like the multifractal spectrum. They are, however, often inadequate for fully understanding and modelling the phenomenon. We illustrate an attempt to capture complex model characteristics by analysing (multiple order) correlations in a high dimensional space of parameters of the (biological) system being studied. Both temporal information, among others local scaling information, and external descriptors/parameters, possibly influencing the system's state, are used to span the search space investigated for the presence of a (sub-)optimal model. As an example, we use fetal heartbeat monitored during labour.

How to integrate biological research into society and exclude errors in biomedical publications? Progress in theoretical and systems biology releases pressure on experimental research.

PubMed

Volkov, Vadim

2014-01-01

This brief opinion proposes measures to increase efficiency and exclude errors in biomedical research under the existing dynamic situation. Rapid changes in biology began with the description of the three dimensional structure of DNA 60 years ago; today biology has progressed by interacting with computer science and nanoscience together with the introduction of robotic stations for the acquisition of large-scale arrays of data. These changes have had an increasing influence on the entire research and scientific community. Future advance demands short-term measures to ensure error-proof and efficient development. They can include the fast publishing of negative results, publishing detailed methodical papers and excluding a strict connection between career progression and publication activity, especially for younger researchers. Further development of theoretical and systems biology together with the use of multiple experimental methods for biological experiments could also be helpful in the context of years and decades. With regards to the links between science and society, it is reasonable to compare both these systems, to find and describe specific features for biology and to integrate it into the existing stream of social life and financial fluxes. It will increase the level of scientific research and have mutual positive effects for both biology and society. Several examples are given for further discussion.

Father Involvement and Young, Rural African American Men's Engagement in Substance Misuse and Multiple Sexual Partnerships.

PubMed

Barton, Allen W; Kogan, Steven M; Cho, Junhan; Brown, Geoffrey L

2015-12-01

This study was designed to examine the associations of biological father and social father involvement during childhood with African American young men's development and engagement in risk behaviors. With a sample of 505 young men living in the rural South of the United States, a dual mediation model was tested in which retrospective reports of involvement from biological fathers and social fathers were linked to young men's substance misuse and multiple sexual partnerships through men's relational schemas and future expectations. Results from structural equation modeling indicated that levels of involvement from biological fathers and social fathers predicted young men's relational schemas; only biological fathers' involvement predicted future expectations. In turn, future expectations predicted levels of substance misuse, and negative relational schemas predicted multiple sexual partnerships. Biological fathers' involvement evinced significant indirect associations with young men's substance misuse and multiple sexual partnerships through both schemas and expectations; social fathers' involvement exhibited an indirect association with multiple sexual partnerships through relational schemas. Findings highlight the unique influences of biological fathers and social fathers on multiple domains of African American young men's psychosocial development that subsequently render young men more or less likely to engage in risk behaviors.

Evolving Concepts and Translational Relevance of Enteroendocrine Cell Biology.

PubMed

Drucker, Daniel J

2016-03-01

Classical enteroenteroendocrine cell (EEC) biology evolved historically from identification of scattered hormone-producing endocrine cells within the epithelial mucosa of the stomach, small and large intestine. Purification of functional EEC hormones from intestinal extracts, coupled with molecular cloning of cDNAs and genes expressed within EECs has greatly expanded the complexity of EEC endocrinology, with implications for understanding the contribution of EECs to disease pathophysiology. Pubmed searches identified manuscripts highlighting new concepts illuminating the molecular biology, classification and functional role(s) of EECs and their hormonal products. Molecular interrogation of EECs has been transformed over the past decade, raising multiple new questions that challenge historical concepts of EEC biology. Evidence for evolution of the EEC from a unihormonal cell type with classical endocrine actions, to a complex plurihormonal dynamic cell with pleiotropic interactive functional networks within the gastrointestinal mucosa is critically assessed. We discuss gaps in understanding how EECs sense and respond to nutrients, cytokines, toxins, pathogens, the microbiota, and the microbial metabolome, and highlight the expanding translational relevance of EECs in the pathophysiology and therapy of metabolic and inflammatory disorders. The EEC system represents the largest specialized endocrine network in human physiology, integrating environmental and nutrient cues, enabling neural and hormonal control of metabolic homeostasis. Updating EEC classification systems will enable more accurate comparative analyses of EEC subpopulations and endocrine networks in multiple regions of the gastrointestinal tract.

Multiple Paternity in a Reintroduced Population of the Orinoco Crocodile (Crocodylus intermedius) at the El Frío Biological Station, Venezuela.

PubMed

Rossi Lafferriere, Natalia A; Antelo, Rafael; Alda, Fernando; Mårtensson, Dick; Hailer, Frank; Castroviejo-Fisher, Santiago; Ayarzagüena, José; Ginsberg, Joshua R; Castroviejo, Javier; Doadrio, Ignacio; Vilá, Carles; Amato, George

2016-01-01

The success of a reintroduction program is determined by the ability of individuals to reproduce and thrive. Hence, an understanding of the mating system and breeding strategies of reintroduced species can be critical to the success, evaluation and effective management of reintroduction programs. As one of the most threatened crocodile species in the world, the Orinoco crocodile (Crocodylus intermedius) has been reduced to only a few wild populations in the Llanos of Venezuela and Colombia. One of these populations was founded by reintroduction at Caño Macanillal and La Ramera lagoon within the El Frío Biological Station, Venezuela. Twenty egg clutches of C. intermedius were collected at the El Frío Biological Station for incubation in the lab and release of juveniles after one year. Analyzing 17 polymorphic microsatellite loci from 335 hatchlings we found multiple paternity in C. intermedius, with half of the 20 clutches fathered by two or three males. Sixteen mothers and 14 fathers were inferred by reconstruction of multilocus parental genotypes. Our findings showed skewed paternal contributions to multiple-sired clutches in four of the clutches (40%), leading to an overall unequal contribution of offspring among fathers with six of the 14 inferred males fathering 90% of the total offspring, and three of those six males fathering more than 70% of the total offspring. Our results provide the first evidence of multiple paternity occurring in the Orinoco crocodile and confirm the success of reintroduction efforts of this critically endangered species in the El Frío Biological Station, Venezuela.

Multiple Multi-Copper Oxidase Gene Families in Basidiomycetes – What for?

PubMed Central

Kües, Ursula; Rühl, Martin

2011-01-01

Genome analyses revealed in various basidiomycetes the existence of multiple genes for blue multi-copper oxidases (MCOs). Whole genomes are now available from saprotrophs, white rot and brown rot species, plant and animal pathogens and ectomycorrhizal species. Total numbers (from 1 to 17) and types of mco genes differ between analyzed species with no easy to recognize connection of gene distribution to fungal life styles. Types of mco genes might be present in one and absent in another fungus. Distinct types of genes have been multiplied at speciation in different organisms. Phylogenetic analysis defined different subfamilies of laccases sensu stricto (specific to Agaricomycetes), classical Fe2+-oxidizing Fet3-like ferroxidases, potential ferroxidases/laccases exhibiting either one or both of these enzymatic functions, enzymes clustering with pigment MCOs and putative ascorbate oxidases. Biochemically best described are laccases sensu stricto due to their proposed roles in degradation of wood, straw and plant litter and due to the large interest in these enzymes in biotechnology. However, biological functions of laccases and other MCOs are generally little addressed. Functions in substrate degradation, symbiontic and pathogenic intercations, development, pigmentation and copper homeostasis have been put forward. Evidences for biological functions are in most instances rather circumstantial by correlations of expression. Multiple factors impede research on biological functions such as difficulties of defining suitable biological systems for molecular research, the broad and overlapping substrate spectrum multi-copper oxidases usually possess, the low existent knowledge on their natural substrates, difficulties imposed by low expression or expression of multiple enzymes, and difficulties in expressing enzymes heterologously. PMID:21966246

Strong Ligand-Protein Interactions Derived from Diffuse Ligand Interactions with Loose Binding Sites.

PubMed

Marsh, Lorraine

2015-01-01

Many systems in biology rely on binding of ligands to target proteins in a single high-affinity conformation with a favorable ΔG. Alternatively, interactions of ligands with protein regions that allow diffuse binding, distributed over multiple sites and conformations, can exhibit favorable ΔG because of their higher entropy. Diffuse binding may be biologically important for multidrug transporters and carrier proteins. A fine-grained computational method for numerical integration of total binding ΔG arising from diffuse regional interaction of a ligand in multiple conformations using a Markov Chain Monte Carlo (MCMC) approach is presented. This method yields a metric that quantifies the influence on overall ligand affinity of ligand binding to multiple, distinct sites within a protein binding region. This metric is essentially a measure of dispersion in equilibrium ligand binding and depends on both the number of potential sites of interaction and the distribution of their individual predicted affinities. Analysis of test cases indicates that, for some ligand/protein pairs involving transporters and carrier proteins, diffuse binding contributes greatly to total affinity, whereas in other cases the influence is modest. This approach may be useful for studying situations where "nonspecific" interactions contribute to biological function.

Next-generation mammalian genetics toward organism-level systems biology.

PubMed

Susaki, Etsuo A; Ukai, Hideki; Ueda, Hiroki R

2017-01-01

Organism-level systems biology in mammals aims to identify, analyze, control, and design molecular and cellular networks executing various biological functions in mammals. In particular, system-level identification and analysis of molecular and cellular networks can be accelerated by next-generation mammalian genetics. Mammalian genetics without crossing, where all production and phenotyping studies of genome-edited animals are completed within a single generation drastically reduce the time, space, and effort of conducting the systems research. Next-generation mammalian genetics is based on recent technological advancements in genome editing and developmental engineering. The process begins with introduction of double-strand breaks into genomic DNA by using site-specific endonucleases, which results in highly efficient genome editing in mammalian zygotes or embryonic stem cells. By using nuclease-mediated genome editing in zygotes, or ~100% embryonic stem cell-derived mouse technology, whole-body knock-out and knock-in mice can be produced within a single generation. These emerging technologies allow us to produce multiple knock-out or knock-in strains in high-throughput manner. In this review, we discuss the basic concepts and related technologies as well as current challenges and future opportunities for next-generation mammalian genetics in organism-level systems biology.

Characterisation of minimalist co-assembled fluorenylmethyloxycarbonyl self-assembling peptide systems for presentation of multiple bioactive peptides.

PubMed

Horgan, Conor C; Rodriguez, Alexandra L; Li, Rui; Bruggeman, Kiara F; Stupka, Nicole; Raynes, Jared K; Day, Li; White, John W; Williams, Richard J; Nisbet, David R

2016-07-01

The nanofibrillar structures that underpin self-assembling peptide (SAP) hydrogels offer great potential for the development of finely tuned cellular microenvironments suitable for tissue engineering. However, biofunctionalisation without disruption of the assembly remains a key issue. SAPS present the peptide sequence within their structure, and studies to date have typically focused on including a single biological motif, resulting in chemically and biologically homogenous scaffolds. This limits the utility of these systems, as they cannot effectively mimic the complexity of the multicomponent extracellular matrix (ECM). In this work, we demonstrate the first successful co-assembly of two biologically active SAPs to form a coassembled scaffold of distinct two-component nanofibrils, and demonstrate that this approach is more bioactive than either of the individual systems alone. Here, we use two bioinspired SAPs from two key ECM proteins: Fmoc-FRGDF containing the RGD sequence from fibronectin and Fmoc-DIKVAV containing the IKVAV sequence from laminin. Our results demonstrate that these SAPs are able to co-assemble to form stable hybrid nanofibres containing dual epitopes. Comparison of the co-assembled SAP system to the individual SAP hydrogels and to a mixed system (composed of the two hydrogels mixed together post-assembly) demonstrates its superior stable, transparent, shear-thinning hydrogels at biological pH, ideal characteristics for tissue engineering applications. Importantly, we show that only the coassembled hydrogel is able to induce in vitro multinucleate myotube formation with C2C12 cells. This work illustrates the importance of tissue engineering scaffold functionalisation and the need to develop increasingly advanced multicomponent systems for effective ECM mimicry. Successful control of stem cell fate in tissue engineering applications requires the use of sophisticated scaffolds that deliver biological signals to guide growth and differentiation. The complexity of such processes necessitates the presentation of multiple signals in order to effectively mimic the native extracellular matrix (ECM). Here, we establish the use of two biofunctional, minimalist self-assembling peptides (SAPs) to construct the first co-assembled SAP scaffold. Our work characterises this construct, demonstrating that the physical, chemical, and biological properties of the peptides are maintained during the co-assembly process. Importantly, the coassembled system demonstrates superior biological performance relative to the individual SAPs, highlighting the importance of complex ECM mimicry. This work has important implications for future tissue engineering studies. Copyright © 2016 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

A systems-based approach to predict biological responses of aquatic organisms to complex environmental mixtures

EPA Science Inventory

Contaminants of emerging concern (CECs) such as new-generation pesticides, pharmaceuticals, household and personal care products, steroid hormones, and flame retardants enter the aquatic environment through multiple sources such as wastewater treatment plants and agricultural ope...

Applied statistics in agricultural, biological, and environmental sciences.

USDA-ARS?s Scientific Manuscript database

Agronomic research often involves measurement and collection of multiple response variables in an effort to understand the more complex nature of the system being studied. Multivariate statistical methods encompass the simultaneous analysis of all random variables measured on each experimental or s...

The rational parameterization theorem for multisite post-translational modification systems.

PubMed

Thomson, Matthew; Gunawardena, Jeremy

2009-12-21

Post-translational modification of proteins plays a central role in cellular regulation but its study has been hampered by the exponential increase in substrate modification forms ("modforms") with increasing numbers of sites. We consider here biochemical networks arising from post-translational modification under mass-action kinetics, allowing for multiple substrates, having different types of modification (phosphorylation, methylation, acetylation, etc.) on multiple sites, acted upon by multiple forward and reverse enzymes (in total number L), using general enzymatic mechanisms. These assumptions are substantially more general than in previous studies. We show that the steady-state modform concentrations constitute an algebraic variety that can be parameterized by rational functions of the L free enzyme concentrations, with coefficients which are rational functions of the rate constants. The parameterization allows steady states to be calculated by solving L algebraic equations, a dramatic reduction compared to simulating an exponentially large number of differential equations. This complexity collapse enables analysis in contexts that were previously intractable and leads to biological predictions that we review. Our results lay a foundation for the systems biology of post-translational modification and suggest deeper connections between biochemical networks and algebraic geometry.

Principal network analysis: identification of subnetworks representing major dynamics using gene expression data

PubMed Central

Kim, Yongsoo; Kim, Taek-Kyun; Kim, Yungu; Yoo, Jiho; You, Sungyong; Lee, Inyoul; Carlson, George; Hood, Leroy; Choi, Seungjin; Hwang, Daehee

2011-01-01

Motivation: Systems biology attempts to describe complex systems behaviors in terms of dynamic operations of biological networks. However, there is lack of tools that can effectively decode complex network dynamics over multiple conditions. Results: We present principal network analysis (PNA) that can automatically capture major dynamic activation patterns over multiple conditions and then generate protein and metabolic subnetworks for the captured patterns. We first demonstrated the utility of this method by applying it to a synthetic dataset. The results showed that PNA correctly captured the subnetworks representing dynamics in the data. We further applied PNA to two time-course gene expression profiles collected from (i) MCF7 cells after treatments of HRG at multiple doses and (ii) brain samples of four strains of mice infected with two prion strains. The resulting subnetworks and their interactions revealed network dynamics associated with HRG dose-dependent regulation of cell proliferation and differentiation and early PrPSc accumulation during prion infection. Availability: The web-based software is available at: http://sbm.postech.ac.kr/pna. Contact: dhhwang@postech.ac.kr; seungjin@postech.ac.kr Supplementary information: Supplementary data are available at Bioinformatics online. PMID:21193522

Denitrifying capabilities of Tetrasphaera and their contribution towards nitrous oxide production in enhanced biological phosphorus removal processes.

PubMed

Marques, Ricardo; Ribera-Guardia, Anna; Santos, Jorge; Carvalho, Gilda; Reis, Maria A M; Pijuan, Maite; Oehmen, Adrian

2018-06-15

Denitrifying enhanced biological phosphorus removal (EBPR) systems can be an efficient means of removing phosphate (P) and nitrate (NO 3 - ) with low carbon source and oxygen requirements. Tetrasphaera is one of the most abundant polyphosphate accumulating organisms present in EBPR systems, but their capacity to achieve denitrifying EBPR has not previously been determined. An enriched Tetrasphaera culture, comprising over 80% of the bacterial biovolume was obtained in this work. Despite the denitrification capacity of Tetrasphaera, this culture achieved only low levels of anoxic P-uptake. Batch tests with different combinations of NO 3 - , nitrite (NO 2 - ) and nitrous oxide (N 2 O) revealed lower N 2 O accumulation by Tetrasphaera as compared to Accumulibacter and Competibacter when multiple electron acceptors were added. Electron competition was observed during the addition of multiple nitrogen electron acceptors species, where P uptake appeared to be slightly favoured over glycogen production in these situations. This study increases our understanding of the role of Tetrasphaera-related organisms in denitrifying EBPR systems. Copyright © 2018 Elsevier Ltd. All rights reserved.

Sex Differences in Trauma-Related Psychopathology: a Critical Review of Neuroimaging Literature (2014-2017).

PubMed

Helpman, Liat; Zhu, Xi; Suarez-Jimenez, Benjamin; Lazarov, Amit; Monk, Catherine; Neria, Yuval

2017-11-08

Sex differences in the epidemiology and clinical presentation of trauma-related psychopathology have long been documented. Multiple underlying mechanisms have been examined, both psychosocial and biological. Among the most promising biological mechanisms are neural substrates of trauma-related psychopathology that have been uncovered in recent years. Neuroimaging studies of sex-related heterogeneity published over the past 3 years (2014-2017) demonstrate an interaction between sex and type, timing, and load of trauma exposure. These studies suggest that, for males, early trauma exposure may involve a loss of gray matter in the limbic system, including the prefrontal cortex (PFC), amygdala, and hippocampus, and an over-activity and increased connectivity of salience hubs, and particularly dorsal anterior cingulate cortex (dACC). For females, however, early trauma exposure may involve overactive and possibly an enlarged amygdala, as well as decreased connectivity of salience hubs such as the dACC. Underlying mechanisms may include interaction with several endocrine systems and result in differential neural response to naturally occurring and added endocrine ligands, as well as sex-specific genetic and epigenetic risk and resilience factors. This complex interaction between multiple biological systems may be associated with sex-specific behavioral patterns, in turn associated with trauma-related psychopathology. While substantial number of published studies present preliminary evidence for neural mechanisms of sex-specific posttraumatic responses, there is a paucity of research directly designed to examine sex as a biological factor in trauma-related psychopathology. Specific foci for future studies aiming to bridge current gaps in the literature are discussed.

Assessing signal-to-noise in quantitative proteomics: multivariate statistical analysis in DIGE experiments.

PubMed

Friedman, David B

2012-01-01

All quantitative proteomics experiments measure variation between samples. When performing large-scale experiments that involve multiple conditions or treatments, the experimental design should include the appropriate number of individual biological replicates from each condition to enable the distinction between a relevant biological signal from technical noise. Multivariate statistical analyses, such as principal component analysis (PCA), provide a global perspective on experimental variation, thereby enabling the assessment of whether the variation describes the expected biological signal or the unanticipated technical/biological noise inherent in the system. Examples will be shown from high-resolution multivariable DIGE experiments where PCA was instrumental in demonstrating biologically significant variation as well as sample outliers, fouled samples, and overriding technical variation that would not be readily observed using standard univariate tests.

Targeting receptor-mediated transport for delivery of biologics across the blood-brain barrier.

PubMed

Lajoie, Jason M; Shusta, Eric V

2015-01-01

Biologics are an emerging class of medicines with substantial promise to treat neurological disorders such as Alzheimer's disease, stroke, and multiple sclerosis. However, the blood-brain barrier (BBB) presents a formidable obstacle that appreciably limits brain uptake and hence the therapeutic potential of biologics following intravenous administration. One promising strategy for overcoming the BBB to deliver biologics is the targeting of endogenous receptor-mediated transport (RMT) systems that employ vesicular trafficking to transport ligands across the BBB endothelium. If a biologic is modified with an appropriate targeting ligand, it can gain improved access to the brain via RMT. Various RMT-targeting strategies have been developed over the past 20 years, and this review explores exciting recent advances, emphasizing studies that show brain targeting in vivo.

Metabolic pathways for the whole community.

PubMed

Hanson, Niels W; Konwar, Kishori M; Hawley, Alyse K; Altman, Tomer; Karp, Peter D; Hallam, Steven J

2014-07-22

A convergence of high-throughput sequencing and computational power is transforming biology into information science. Despite these technological advances, converting bits and bytes of sequence information into meaningful insights remains a challenging enterprise. Biological systems operate on multiple hierarchical levels from genomes to biomes. Holistic understanding of biological systems requires agile software tools that permit comparative analyses across multiple information levels (DNA, RNA, protein, and metabolites) to identify emergent properties, diagnose system states, or predict responses to environmental change. Here we adopt the MetaPathways annotation and analysis pipeline and Pathway Tools to construct environmental pathway/genome databases (ePGDBs) that describe microbial community metabolism using MetaCyc, a highly curated database of metabolic pathways and components covering all domains of life. We evaluate Pathway Tools' performance on three datasets with different complexity and coding potential, including simulated metagenomes, a symbiotic system, and the Hawaii Ocean Time-series. We define accuracy and sensitivity relationships between read length, coverage and pathway recovery and evaluate the impact of taxonomic pruning on ePGDB construction and interpretation. Resulting ePGDBs provide interactive metabolic maps, predict emergent metabolic pathways associated with biosynthesis and energy production and differentiate between genomic potential and phenotypic expression across defined environmental gradients. This multi-tiered analysis provides the user community with specific operating guidelines, performance metrics and prediction hazards for more reliable ePGDB construction and interpretation. Moreover, it demonstrates the power of Pathway Tools in predicting metabolic interactions in natural and engineered ecosystems.

SEEK: a systems biology data and model management platform.

PubMed

Wolstencroft, Katherine; Owen, Stuart; Krebs, Olga; Nguyen, Quyen; Stanford, Natalie J; Golebiewski, Martin; Weidemann, Andreas; Bittkowski, Meik; An, Lihua; Shockley, David; Snoep, Jacky L; Mueller, Wolfgang; Goble, Carole

2015-07-11

Systems biology research typically involves the integration and analysis of heterogeneous data types in order to model and predict biological processes. Researchers therefore require tools and resources to facilitate the sharing and integration of data, and for linking of data to systems biology models. There are a large number of public repositories for storing biological data of a particular type, for example transcriptomics or proteomics, and there are several model repositories. However, this silo-type storage of data and models is not conducive to systems biology investigations. Interdependencies between multiple omics datasets and between datasets and models are essential. Researchers require an environment that will allow the management and sharing of heterogeneous data and models in the context of the experiments which created them. The SEEK is a suite of tools to support the management, sharing and exploration of data and models in systems biology. The SEEK platform provides an access-controlled, web-based environment for scientists to share and exchange data and models for day-to-day collaboration and for public dissemination. A plug-in architecture allows the linking of experiments, their protocols, data, models and results in a configurable system that is available 'off the shelf'. Tools to run model simulations, plot experimental data and assist with data annotation and standardisation combine to produce a collection of resources that support analysis as well as sharing. Underlying semantic web resources additionally extract and serve SEEK metadata in RDF (Resource Description Format). SEEK RDF enables rich semantic queries, both within SEEK and between related resources in the web of Linked Open Data. The SEEK platform has been adopted by many systems biology consortia across Europe. It is a data management environment that has a low barrier of uptake and provides rich resources for collaboration. This paper provides an update on the functions and features of the SEEK software, and describes the use of the SEEK in the SysMO consortium (Systems biology for Micro-organisms), and the VLN (virtual Liver Network), two large systems biology initiatives with different research aims and different scientific communities.

A multi-scale approach to designing therapeutics for tuberculosis

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

Linderman, Jennifer J.; Cilfone, Nicholas A.; Pienaar, Elsje

Approximately one third of the world’s population is infected with Mycobacterium tuberculosis. Limited information about how the immune system fights M. tuberculosis and what constitutes protection from the bacteria impact our ability to develop effective therapies for tuberculosis. We present an in vivo systems biology approach that integrates data from multiple model systems and over multiple length and time scales into a comprehensive multi-scale and multi-compartment view of the in vivo immune response to M. tuberculosis. Lastly, we describe computational models that can be used to study (a) immunomodulation with the cytokines tumor necrosis factor and interleukin 10, (b) oralmore » and inhaled antibiotics, and (c) the effect of vaccination.« less

A multi-scale approach to designing therapeutics for tuberculosis

DOE PAGES

Linderman, Jennifer J.; Cilfone, Nicholas A.; Pienaar, Elsje; ...

2015-04-20

Approximately one third of the world’s population is infected with Mycobacterium tuberculosis. Limited information about how the immune system fights M. tuberculosis and what constitutes protection from the bacteria impact our ability to develop effective therapies for tuberculosis. We present an in vivo systems biology approach that integrates data from multiple model systems and over multiple length and time scales into a comprehensive multi-scale and multi-compartment view of the in vivo immune response to M. tuberculosis. Lastly, we describe computational models that can be used to study (a) immunomodulation with the cytokines tumor necrosis factor and interleukin 10, (b) oralmore » and inhaled antibiotics, and (c) the effect of vaccination.« less

Library of molecular associations: curating the complex molecular basis of liver diseases.

PubMed

Buchkremer, Stefan; Hendel, Jasmin; Krupp, Markus; Weinmann, Arndt; Schlamp, Kai; Maass, Thorsten; Staib, Frank; Galle, Peter R; Teufel, Andreas

2010-03-20

Systems biology approaches offer novel insights into the development of chronic liver diseases. Current genomic databases supporting systems biology analyses are mostly based on microarray data. Although these data often cover genome wide expression, the validity of single microarray experiments remains questionable. However, for systems biology approaches addressing the interactions of molecular networks comprehensive but also highly validated data are necessary. We have therefore generated the first comprehensive database for published molecular associations in human liver diseases. It is based on PubMed published abstracts and aimed to close the gap between genome wide coverage of low validity from microarray data and individual highly validated data from PubMed. After an initial text mining process, the extracted abstracts were all manually validated to confirm content and potential genetic associations and may therefore be highly trusted. All data were stored in a publicly available database, Library of Molecular Associations http://www.medicalgenomics.org/databases/loma/news, currently holding approximately 1260 confirmed molecular associations for chronic liver diseases such as HCC, CCC, liver fibrosis, NASH/fatty liver disease, AIH, PBC, and PSC. We furthermore transformed these data into a powerful resource for molecular liver research by connecting them to multiple biomedical information resources. Together, this database is the first available database providing a comprehensive view and analysis options for published molecular associations on multiple liver diseases.

MIDAS: A Modular DNA Assembly System for Synthetic Biology.

PubMed

van Dolleweerd, Craig J; Kessans, Sarah A; Van de Bittner, Kyle C; Bustamante, Leyla Y; Bundela, Rudranuj; Scott, Barry; Nicholson, Matthew J; Parker, Emily J

2018-04-20

A modular and hierarchical DNA assembly platform for synthetic biology based on Golden Gate (Type IIS restriction enzyme) cloning is described. This enabling technology, termed MIDAS (for Modular Idempotent DNA Assembly System), can be used to precisely assemble multiple DNA fragments in a single reaction using a standardized assembly design. It can be used to build genes from libraries of sequence-verified, reusable parts and to assemble multiple genes in a single vector, with full user control over gene order and orientation, as well as control of the direction of growth (polarity) of the multigene assembly, a feature that allows genes to be nested between other genes or genetic elements. We describe the detailed design and use of MIDAS, exemplified by the reconstruction, in the filamentous fungus Penicillium paxilli, of the metabolic pathway for production of paspaline and paxilline, key intermediates in the biosynthesis of a range of indole diterpenes-a class of secondary metabolites produced by several species of filamentous fungi. MIDAS was used to efficiently assemble a 25.2 kb plasmid from 21 different modules (seven genes, each composed of three basic parts). By using a parts library-based system for construction of complex assemblies, and a unique set of vectors, MIDAS can provide a flexible route to assembling tailored combinations of genes and other genetic elements, thereby supporting synthetic biology applications in a wide range of expression hosts.

Proof of Concept: A review on how network and systems biology approaches aid in the discovery of potent anticancer drug combinations

PubMed Central

Azmi, Asfar S.; Wang, Zhiwei; Philip, Philip A.; Mohammad, Ramzi M.; Sarkar, Fazlul H.

2010-01-01

Cancer therapies that target key molecules have not fulfilled expected promises for most common malignancies. Major challenges include the incomplete understanding and validation of these targets in patients, the multiplicity and complexity of genetic and epigenetic changes in the majority of cancers, and the redundancies and cross-talk found in key signaling pathways. Collectively, the uses of single-pathway targeted approaches are not effective therapies for human malignances. To overcome these barriers, it is important to understand the molecular cross-talk among key signaling pathways and how they may be altered by targeted agents. This requires innovative approaches such as understanding the global physiological environment of target proteins and the effects of modifying them without losing key molecular details. Such strategies will aid the design of novel therapeutics and their combinations against multifaceted diseases where efficacious combination therapies will focus on altering multiple pathways rather than single proteins. Integrated network modeling and systems biology has emerged as a powerful tool benefiting our understanding of drug mechanism of action in real time. This mini-review highlights the significance of the network and systems biology-based strategy and presents a “proof-of-concept” recently validated in our laboratory using the example of a combination treatment of oxaliplatin and the MDM2 inhibitor MI-219 in genetically complex and incurable pancreatic adenocarcinoma. PMID:21041384

Dupuytren's: a systems biology disease

PubMed Central

2011-01-01

Dupuytren's disease (DD) is an ill-defined fibroproliferative disorder of the palm of the hands leading to digital contracture. DD commonly occurs in individuals of northern European extraction. Cellular components and processes associated with DD pathogenesis include altered gene and protein expression of cytokines, growth factors, adhesion molecules, and extracellular matrix components. Histology has shown increased but varying levels of particular types of collagen, myofibroblasts and myoglobin proteins in DD tissue. Free radicals and localised ischaemia have been suggested to trigger the proliferation of DD tissue. Although the existing available biological information on DD may contain potentially valuable (though largely uninterpreted) information, the precise aetiology of DD remains unknown. Systems biology combines mechanistic modelling with quantitative experimentation in studies of networks and better understanding of the interaction of multiple components in disease processes. Adopting systems biology may be the ideal approach for future research in order to improve understanding of complex diseases of multifactorial origin. In this review, we propose that DD is a disease of several networks rather than of a single gene, and show that this accounts for the experimental observations obtained to date from a variety of sources. We outline how DD may be investigated more effectively by employing a systems biology approach that considers the disease network as a whole rather than focusing on any specific single molecule. PMID:21943049

The Promise of Systems Biology Approaches for Revealing Host Pathogen Interactions in Malaria

PubMed Central

Zuck, Meghan; Austin, Laura S.; Danziger, Samuel A.; Aitchison, John D.; Kaushansky, Alexis

2017-01-01

Despite global eradication efforts over the past century, malaria remains a devastating public health burden, causing almost half a million deaths annually (WHO, 2016). A detailed understanding of the mechanisms that control malaria infection has been hindered by technical challenges of studying a complex parasite life cycle in multiple hosts. While many interventions targeting the parasite have been implemented, the complex biology of Plasmodium poses a major challenge, and must be addressed to enable eradication. New approaches for elucidating key host-parasite interactions, and predicting how the parasite will respond in a variety of biological settings, could dramatically enhance the efficacy and longevity of intervention strategies. The field of systems biology has developed methodologies and principles that are well poised to meet these challenges. In this review, we focus our attention on the Liver Stage of the Plasmodium lifecycle and issue a “call to arms” for using systems biology approaches to forge a new era in malaria research. These approaches will reveal insights into the complex interplay between host and pathogen, and could ultimately lead to novel intervention strategies that contribute to malaria eradication. PMID:29201016

Impact of cover crops on soil nitrate, crop yield and quality

USDA-ARS?s Scientific Manuscript database

There are multiple benefits of incorporating cover crops into current production systems including decreasing erosion, improving water infiltration, increasing soil organic matter and biological activity but in water limited areas caution should be utilized. A field study was established in the fal...

Toward Scalable Fabrication of Hierarchical Silica Capsules with Integrated Micro-, Meso-, and Macropores.

PubMed

Zhou, Weizheng; Tong, Gangsheng; Wang, Dali; Zhu, Bangshang; Ren, Yu; Butler, Michael; Pelan, Eddie; Yan, Deyue; Zhu, Xinyuan; Stoyanov, Simeon D

2016-04-06

Hierarchical porous structures are ubiquitous in biological organisms and inorganic systems. Although such structures have been replicated, designed, and fabricated, they are often inferior to naturally occurring analogues. Apart from the complexity and multiple functionalities developed by the biological systems, the controllable and scalable production of hierarchically porous structures and building blocks remains a technological challenge. Herein, a facile and scalable approach is developed to fabricate hierarchical hollow spheres with integrated micro-, meso-, and macropores ranging from 1 nm to 100 μm (spanning five orders of magnitude). (Macro)molecules, micro-rods (which play a key role for the creation of robust capsules), and emulsion droplets have been successfully employed as multiple length scale templates, allowing the creation of hierarchical porous macrospheres. Thanks to their specific mechanical strength, these hierarchical porous spheres could be incorporated and assembled as higher level building blocks in various novel materials. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Epidemiology and population biology of Pseudoperonospora cubensis: a model system for management of downy mildews.

PubMed

Ojiambo, Peter S; Gent, David H; Quesada-Ocampo, Lina M; Hausbeck, Mary K; Holmes, Gerald J

2015-01-01

The resurgence of cucurbit downy mildew has dramatically influenced production of cucurbits and disease management systems at multiple scales. Long-distance dispersal is a fundamental aspect of epidemic development that influences the timing and extent of outbreaks of cucurbit downy mildew. The dispersal potential of Pseudoperonospora cubensis appears to be limited primarily by sporangia production in source fields and availability of susceptible hosts and less by sporangia survival during transport. Uncertainty remains regarding the role of locally produced inoculum in disease outbreaks, but evidence suggests multiple sources of primary inoculum could be important. Understanding pathogen diversity and population differentiation is a critical aspect of disease management and an active research area. Underpinning advances in our understanding of pathogen biology and disease management has been the research capacity and coordination of stakeholders, scientists, and extension personnel. Concepts and approaches developed in this pathosystem can guide future efforts when responding to incursions of new or reemerging downy mildew pathogens.

Quantitative Interpretation of Multifrequency Multimode EPR Spectra of Metal Containing Proteins, Enzymes, and Biomimetic Complexes.

PubMed

Petasis, Doros T; Hendrich, Michael P

2015-01-01

Electron paramagnetic resonance (EPR) spectroscopy has long been a primary method for characterization of paramagnetic centers in materials and biological complexes. Transition metals in biological complexes have valence d-orbitals that largely define the chemistry of the metal centers. EPR spectra are distinctive for metal type, oxidation state, protein environment, substrates, and inhibitors. The study of many metal centers in proteins, enzymes, and biomimetic complexes has led to the development of a systematic methodology for quantitative interpretation of EPR spectra from a wide array of metal containing complexes. The methodology is now contained in the computer program SpinCount. SpinCount allows simulation of EPR spectra from any sample containing multiple species composed of one or two metals in any spin state. The simulations are quantitative, thus allowing determination of all species concentrations in a sample directly from spectra. This chapter will focus on applications to transition metals in biological systems using EPR spectra from multiple microwave frequencies and modes. © 2015 Elsevier Inc. All rights reserved.

Infection-Related Death among Persons with Refractory Juvenile Idiopathic Arthritis

PubMed Central

Lane, Jonathan P.; Wood, Mark; Friswell, Mark; Flood, Terence J.; Foster, Helen E.

2016-01-01

Severe infections are emerging as major risk factors for death among children with juvenile idiopathic arthritis (JIA). In particular, children with refractory JIA treated with long-term, multiple, and often combined immunosuppressive and antiinflammatory agents, including the new biological disease-modifying antirheumatic drugs (DMARDs), are at increased risk for severe infections and death. We investigated 4 persons with JIA who died during 1994–2013, three of overwhelming central venous catheter–related bacterial sepsis caused by coagulase-negative Staphylococus or α-hemolytic Streptococcus infection and 1 of disseminated adenovirus and Epstein-Barr virus infection). All 4 had active JIA refractory to long-term therapy with multiple and combined conventional and biological DMARDs. Two died while receiving high-dose systemic corticosteroids, methotrexate, and after recent exposure to anti–tumor necrosis factor-α biological DMARDs, and 2 during hematopoietic stem cell transplantation procedure. Reporting all cases of severe infections and especially deaths in these children is of paramount importance for accurate surveillance. PMID:27648582

Photonic structures in biology

NASA Astrophysics Data System (ADS)

Vukusic, Pete; Sambles, J. Roy

2003-08-01

Millions of years before we began to manipulate the flow of light using synthetic structures, biological systems were using nanometre-scale architectures to produce striking optical effects. An astonishing variety of natural photonic structures exists: a species of Brittlestar uses photonic elements composed of calcite to collect light, Morpho butterflies use multiple layers of cuticle and air to produce their striking blue colour and some insects use arrays of elements, known as nipple arrays, to reduce reflectivity in their compound eyes. Natural photonic structures are providing inspiration for technological applications.

Metabolic engineering of Bacillus subtilis fueled by systems biology: Recent advances and future directions.

PubMed

Liu, Yanfeng; Li, Jianghua; Du, Guocheng; Chen, Jian; Liu, Long

By combining advanced omics technology and computational modeling, systems biologists have identified and inferred thousands of regulatory events and system-wide interactions of the bacterium Bacillus subtilis, which is commonly used both in the laboratory and in industry. This dissection of the multiple layers of regulatory networks and their interactions has provided invaluable information for unraveling regulatory mechanisms and guiding metabolic engineering. In this review, we discuss recent advances in the systems biology and metabolic engineering of B. subtilis and highlight current gaps in our understanding of global metabolism and global pathway engineering in this organism. We also propose future perspectives in the systems biology of B. subtilis and suggest ways that this approach can be used to guide metabolic engineering. Specifically, although hundreds of regulatory events have been identified or inferred via systems biology approaches, systematic investigation of the functionality of these events in vivo has lagged, thereby preventing the elucidation of regulatory mechanisms and further rational pathway engineering. In metabolic engineering, ignoring the engineering of multilayer regulation hinders metabolic flux redistribution. Post-translational engineering, allosteric engineering, and dynamic pathway analyses and control will also contribute to the modulation and control of the metabolism of engineered B. subtilis, ultimately producing the desired cellular traits. We hope this review will aid metabolic engineers in making full use of available systems biology datasets and approaches for the design and perfection of microbial cell factories through global metabolism optimization. Copyright © 2016 Elsevier Inc. All rights reserved.

TeleProbe: design and development of an efficient system for telepathology

NASA Astrophysics Data System (ADS)

Ahmed, Wamiq M.; Robinson, J. Paul; Ghafoor, Arif

2005-10-01

This paper describes an internet-based system for telepathology. This system provides support for multiple users and exploits the opportunities for optimization that arise in multi-user environment. Techniques for increasing system responsiveness by improving resource utilization and lowering network traffic are explored. Some of the proposed optimizations include an auto-focus module, client and server side caching, and request reordering. These systems can be an economic solution not only for remote pathology consultation but also for pathology and biology education.

Digital biology and chemistry.

PubMed

Witters, Daan; Sun, Bing; Begolo, Stefano; Rodriguez-Manzano, Jesus; Robles, Whitney; Ismagilov, Rustem F

2014-09-07

This account examines developments in "digital" biology and chemistry within the context of microfluidics, from a personal perspective. Using microfluidics as a frame of reference, we identify two areas of research within digital biology and chemistry that are of special interest: (i) the study of systems that switch between discrete states in response to changes in chemical concentration of signals, and (ii) the study of single biological entities such as molecules or cells. In particular, microfluidics accelerates analysis of switching systems (i.e., those that exhibit a sharp change in output over a narrow range of input) by enabling monitoring of multiple reactions in parallel over a range of concentrations of signals. Conversely, such switching systems can be used to create new kinds of microfluidic detection systems that provide "analog-to-digital" signal conversion and logic. Microfluidic compartmentalization technologies for studying and isolating single entities can be used to reconstruct and understand cellular processes, study interactions between single biological entities, and examine the intrinsic heterogeneity of populations of molecules, cells, or organisms. Furthermore, compartmentalization of single cells or molecules in "digital" microfluidic experiments can induce switching in a range of reaction systems to enable sensitive detection of cells or biomolecules, such as with digital ELISA or digital PCR. This "digitizing" offers advantages in terms of robustness, assay design, and simplicity because quantitative information can be obtained with qualitative measurements. While digital formats have been shown to improve the robustness of existing chemistries, we anticipate that in the future they will enable new chemistries to be used for quantitative measurements, and that digital biology and chemistry will continue to provide further opportunities for measuring biomolecules, understanding natural systems more deeply, and advancing molecular and cellular analysis. Microfluidics will impact digital biology and chemistry and will also benefit from them if it becomes massively distributed.

Harnessing the Power of Integrated Mitochondrial Biology and Physiology: A Special Report on the NHLBI Mitochondria in Heart Diseases Initiative

PubMed Central

Ping, Peipei; Gustafsson, Åsa B.; Bers, Don M.; Blatter, Lothar; Cai, Hua; Jahangir, Arshad; Kelly, Daniel; Muoio, Deborah; O'Rourke, Brian; Rabinovitch, Peter; Trayanova, Natalia; Van Eyk, Jennifer; Weiss, James N.; Wong, Renee; Longacre, Lisa Schwartz

2015-01-01

Summary Mitochondrial biology is the sum of diverse phenomena from molecular profiles to physiological functions. A mechanistic understanding of mitochondria in disease development, and hence the future prospect of clinical translations, relies on a systems-level integration of expertise from multiple fields of investigation. Upon the successful completion of a recent National Institutes of Health, National Heart, Lung, and Blood Institute initiative on integrative mitochondrial biology in cardiovascular diseases, we reflect on the accomplishments made possible by this unique interdisciplinary collaboration effort and exciting new fronts on the study of these remarkable organelles. PMID:26185209

Harnessing the Power of Integrated Mitochondrial Biology and Physiology: A Special Report on the NHLBI Mitochondria in Heart Diseases Initiative.

PubMed

Ping, Peipei; Gustafsson, Åsa B; Bers, Don M; Blatter, Lothar A; Cai, Hua; Jahangir, Arshad; Kelly, Daniel; Muoio, Deborah; O'Rourke, Brian; Rabinovitch, Peter; Trayanova, Natalia; Van Eyk, Jennifer; Weiss, James N; Wong, Renee; Schwartz Longacre, Lisa

2015-07-17

Mitochondrial biology is the sum of diverse phenomena from molecular profiles to physiological functions. A mechanistic understanding of mitochondria in disease development, and hence the future prospect of clinical translations, relies on a systems-level integration of expertise from multiple fields of investigation. Upon the successful conclusion of a recent National Institutes of Health, National Heart, Lung, and Blood Institute initiative on integrative mitochondrial biology in cardiovascular diseases, we reflect on the accomplishments made possible by this unique interdisciplinary collaboration effort and exciting new fronts on the study of these remarkable organelles. © 2015 American Heart Association, Inc.

Multilevel functional genomics data integration as a tool for understanding physiology: a network biology perspective.

PubMed

Davidsen, Peter K; Turan, Nil; Egginton, Stuart; Falciani, Francesco

2016-02-01

The overall aim of physiological research is to understand how living systems function in an integrative manner. Consequently, the discipline of physiology has since its infancy attempted to link multiple levels of biological organization. Increasingly this has involved mathematical and computational approaches, typically to model a small number of components spanning several levels of biological organization. With the advent of "omics" technologies, which can characterize the molecular state of a cell or tissue (intended as the level of expression and/or activity of its molecular components), the number of molecular components we can quantify has increased exponentially. Paradoxically, the unprecedented amount of experimental data has made it more difficult to derive conceptual models underlying essential mechanisms regulating mammalian physiology. We present an overview of state-of-the-art methods currently used to identifying biological networks underlying genomewide responses. These are based on a data-driven approach that relies on advanced computational methods designed to "learn" biology from observational data. In this review, we illustrate an application of these computational methodologies using a case study integrating an in vivo model representing the transcriptional state of hypoxic skeletal muscle with a clinical study representing muscle wasting in chronic obstructive pulmonary disease patients. The broader application of these approaches to modeling multiple levels of biological data in the context of modern physiology is discussed. Copyright © 2016 the American Physiological Society.

Ocean acidification in the coastal zone from an organism's perspective: multiple system parameters, frequency domains, and habitats.

PubMed

Waldbusser, George G; Salisbury, Joseph E

2014-01-01

Multiple natural and anthropogenic processes alter the carbonate chemistry of the coastal zone in ways that either exacerbate or mitigate ocean acidification effects. Freshwater inputs and multiple acid-base reactions change carbonate chemistry conditions, sometimes synergistically. The shallow nature of these systems results in strong benthic-pelagic coupling, and marine invertebrates at different life history stages rely on both benthic and pelagic habitats. Carbonate chemistry in coastal systems can be highly variable, responding to processes with temporal modes ranging from seconds to centuries. Identifying scales of variability relevant to levels of biological organization requires a fuller characterization of both the frequency and magnitude domains of processes contributing to or reducing acidification in pelagic and benthic habitats. We review the processes that contribute to coastal acidification with attention to timescales of variability and habitats relevant to marine bivalves.

Beyond the Cell: Using Multiscalar Topics to Bring Interdisciplinarity into Undergraduate Cellular Biology Courses

PubMed Central

Weber, Carolyn F.

2016-01-01

Western science has grown increasingly reductionistic and, in parallel, the undergraduate life sciences curriculum has become disciplinarily fragmented. While reductionistic approaches have led to landmark discoveries, many of the most exciting scientific advances in the late 20th century have occurred at disciplinary interfaces; work at these interfaces is necessary to manage the world’s looming problems, particularly those that are rooted in cellular-level processes but have ecosystem- and even global-scale ramifications (e.g., nonsustainable agriculture, emerging infectious diseases). Managing such problems requires comprehending whole scenarios and their emergent properties as sums of their multiple facets and complex interrelationships, which usually integrate several disciplines across multiple scales (e.g., time, organization, space). This essay discusses bringing interdisciplinarity into undergraduate cellular biology courses through the use of multiscalar topics. Discussing how cellular-level processes impact large-scale phenomena makes them relevant to everyday life and unites diverse disciplines (e.g., sociology, cell biology, physics) as facets of a single system or problem, emphasizing their connections to core concepts in biology. I provide specific examples of multiscalar topics and discuss preliminary evidence that using such topics may increase students’ understanding of the cell’s position within an ecosystem and how cellular biology interfaces with other disciplines. PMID:27146162

A Systems Biology Analysis Unfolds the Molecular Pathways and Networks of Two Proteobacteria in Spaceflight and Simulated Microgravity Conditions.

PubMed

Roy, Raktim; Shilpa, P Phani; Bagh, Sangram

2016-09-01

Bacteria are important organisms for space missions due to their increased pathogenesis in microgravity that poses risks to the health of astronauts and for projected synthetic biology applications at the space station. We understand little about the effect, at the molecular systems level, of microgravity on bacteria, despite their significant incidence. In this study, we proposed a systems biology pipeline and performed an analysis on published gene expression data sets from multiple seminal studies on Pseudomonas aeruginosa and Salmonella enterica serovar Typhimurium under spaceflight and simulated microgravity conditions. By applying gene set enrichment analysis on the global gene expression data, we directly identified a large number of new, statistically significant cellular and metabolic pathways involved in response to microgravity. Alteration of metabolic pathways in microgravity has rarely been reported before, whereas in this analysis metabolic pathways are prevalent. Several of those pathways were found to be common across studies and species, indicating a common cellular response in microgravity. We clustered genes based on their expression patterns using consensus non-negative matrix factorization. The genes from different mathematically stable clusters showed protein-protein association networks with distinct biological functions, suggesting the plausible functional or regulatory network motifs in response to microgravity. The newly identified pathways and networks showed connection with increased survival of pathogens within macrophages, virulence, and antibiotic resistance in microgravity. Our work establishes a systems biology pipeline and provides an integrated insight into the effect of microgravity at the molecular systems level. Systems biology-Microgravity-Pathways and networks-Bacteria. Astrobiology 16, 677-689.

The Histochemistry and Cell Biology compendium: a review of 2012.

PubMed

Taatjes, Douglas J; Roth, Jürgen

2013-06-01

The year 2012 was another exciting year for Histochemistry and Cell Biology. Innovations in immunohistochemical techniques and microscopy-based imaging have provided the means for advances in the field of cell biology. Over 130 manuscripts were published in the journal during 2012, representing methodological advancements, pathobiology of disease, and cell and tissue biology. This annual review of the manuscripts published in the previous year in Histochemistry and Cell Biology serves as an abbreviated reference for the readership to quickly peruse and discern trends in the field over the past year. The review has been broadly divided into multiple sections encompassing topics such as method advancements, subcellular components, extracellular matrix, and organ systems. We hope that the creation of this subdivision will serve to guide the reader to a specific topic of interest, while simultaneously providing a concise and easily accessible encapsulation of other topics in the broad area of Histochemistry and Cell Biology.

Droplet microfluidics for synthetic biology

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

Gach, Philip Charles; Iwai, Kosuke; Kim, Peter Wonhee

Here, synthetic biology is an interdisciplinary field that aims to engineer biological systems for useful purposes. Organism engineering often requires the optimization of individual genes and/or entire biological pathways (consisting of multiple genes). Advances in DNA sequencing and synthesis have recently begun to enable the possibility of evaluating thousands of gene variants and hundreds of thousands of gene combinations. However, such large-scale optimization experiments remain cost-prohibitive to researchers following traditional molecular biology practices, which are frequently labor-intensive and suffer from poor reproducibility. Liquid handling robotics may reduce labor and improve reproducibility, but are themselves expensive and thus inaccessible to mostmore » researchers. Microfluidic platforms offer a lower entry price point alternative to robotics, and maintain high throughput and reproducibility while further reducing operating costs through diminished reagent volume requirements. Droplet microfluidics have shown exceptional promise for synthetic biology experiments, including DNA assembly, transformation/transfection, culturing, cell sorting, phenotypic assays, artificial cells and genetic circuits.« less

Droplet microfluidics for synthetic biology

DOE PAGES

Gach, Philip Charles; Iwai, Kosuke; Kim, Peter Wonhee; ...

2017-08-10

Here, synthetic biology is an interdisciplinary field that aims to engineer biological systems for useful purposes. Organism engineering often requires the optimization of individual genes and/or entire biological pathways (consisting of multiple genes). Advances in DNA sequencing and synthesis have recently begun to enable the possibility of evaluating thousands of gene variants and hundreds of thousands of gene combinations. However, such large-scale optimization experiments remain cost-prohibitive to researchers following traditional molecular biology practices, which are frequently labor-intensive and suffer from poor reproducibility. Liquid handling robotics may reduce labor and improve reproducibility, but are themselves expensive and thus inaccessible to mostmore » researchers. Microfluidic platforms offer a lower entry price point alternative to robotics, and maintain high throughput and reproducibility while further reducing operating costs through diminished reagent volume requirements. Droplet microfluidics have shown exceptional promise for synthetic biology experiments, including DNA assembly, transformation/transfection, culturing, cell sorting, phenotypic assays, artificial cells and genetic circuits.« less

An Integrated Modeling Framework Forecasting Ecosystem Exposure— A Systems Approach to the Cumulative Impacts of Multiple Stressors

EPA Science Inventory

Freshwater habitats provide fishable, swimmable and drinkable resources and are a nexus of geophysical and biological processes. These processes in turn influence the persistence and sustainability of populations, communities and ecosystems. Climate change and landuse change enco...

The Biological Side of Social Determinants: Neural Costs of Childhood Poverty

ERIC Educational Resources Information Center

Lipina, Sebastián J.

2016-01-01

Interdisciplinary efforts to foster the development and education of children living in poverty require a comprehensive concept of multiple dimensions, within a systemic approach involving ecological and transactional perspectives. Constructing a common interdisciplinary language dealing with child development in ecological terms is a necessary…

Integrated Analysis of Genetic and Proteomic Data Identifies Biomarkers Associated with Adverse Events Following Smallpox Vaccination

EPA Science Inventory

Complex clinical outcomes, such as adverse reaction to vaccination, arise from the concerted interactions among the myriad components of a biological system. Therefore, comprehensive etiological models can be developed only through the integrated study of multiple types of experi...

Bridging the gap between clinicians and systems biologists: from network biology to translational biomedical research.

PubMed

Jinawath, Natini; Bunbanjerdsuk, Sacarin; Chayanupatkul, Maneerat; Ngamphaiboon, Nuttapong; Asavapanumas, Nithi; Svasti, Jisnuson; Charoensawan, Varodom

2016-11-22

With the wealth of data accumulated from completely sequenced genomes and other high-throughput experiments, global studies of biological systems, by simultaneously investigating multiple biological entities (e.g. genes, transcripts, proteins), has become a routine. Network representation is frequently used to capture the presence of these molecules as well as their relationship. Network biology has been widely used in molecular biology and genetics, where several network properties have been shown to be functionally important. Here, we discuss how such methodology can be useful to translational biomedical research, where scientists traditionally focus on one or a small set of genes, diseases, and drug candidates at any one time. We first give an overview of network representation frequently used in biology: what nodes and edges represent, and review its application in preclinical research to date. Using cancer as an example, we review how network biology can facilitate system-wide approaches to identify targeted small molecule inhibitors. These types of inhibitors have the potential to be more specific, resulting in high efficacy treatments with less side effects, compared to the conventional treatments such as chemotherapy. Global analysis may provide better insight into the overall picture of human diseases, as well as identify previously overlooked problems, leading to rapid advances in medicine. From the clinicians' point of view, it is necessary to bridge the gap between theoretical network biology and practical biomedical research, in order to improve the diagnosis, prevention, and treatment of the world's major diseases.

Multiple Paternity in a Reintroduced Population of the Orinoco Crocodile (Crocodylus intermedius) at the El Frío Biological Station, Venezuela

PubMed Central

Alda, Fernando; Mårtensson, Dick; Hailer, Frank; Castroviejo-Fisher, Santiago; Ginsberg, Joshua R.; Castroviejo, Javier; Doadrio, Ignacio; Vilá, Carles; Amato, George

2016-01-01

The success of a reintroduction program is determined by the ability of individuals to reproduce and thrive. Hence, an understanding of the mating system and breeding strategies of reintroduced species can be critical to the success, evaluation and effective management of reintroduction programs. As one of the most threatened crocodile species in the world, the Orinoco crocodile (Crocodylus intermedius) has been reduced to only a few wild populations in the Llanos of Venezuela and Colombia. One of these populations was founded by reintroduction at Caño Macanillal and La Ramera lagoon within the El Frío Biological Station, Venezuela. Twenty egg clutches of C. intermedius were collected at the El Frío Biological Station for incubation in the lab and release of juveniles after one year. Analyzing 17 polymorphic microsatellite loci from 335 hatchlings we found multiple paternity in C. intermedius, with half of the 20 clutches fathered by two or three males. Sixteen mothers and 14 fathers were inferred by reconstruction of multilocus parental genotypes. Our findings showed skewed paternal contributions to multiple-sired clutches in four of the clutches (40%), leading to an overall unequal contribution of offspring among fathers with six of the 14 inferred males fathering 90% of the total offspring, and three of those six males fathering more than 70% of the total offspring. Our results provide the first evidence of multiple paternity occurring in the Orinoco crocodile and confirm the success of reintroduction efforts of this critically endangered species in the El Frío Biological Station, Venezuela. PMID:26982578

Notes on the Epidemiology of Multiple Sclerosis, with Special Reference to Dietary Habits

PubMed Central

Lauer, Klaus

2014-01-01

A hypothesis, based primarily on the occurrence of multiple sclerosis (MS) in the Faroe Islands and supported by numerous analytical epidemiological studies, is described. It proposes that MS is caused by the interaction of a virus disease with intestinal pathology, e.g., infectious mononucleosis, and application of smoked and nitrate/nitrite-cured meat products in the diet during circumscribed time intervals. The biological mechanisms might involve a break of tolerance by an alteration of self within the central nervous system, by nitrophenylated compounds conjugated to animal tissue, in particular to proteins occurring in the central nervous system. Further research is needed. PMID:24577315

A new statistical method for transfer coefficient calculations in the framework of the general multiple-compartment model of transport for radionuclides in biological systems.

PubMed

Garcia, F; Arruda-Neto, J D; Manso, M V; Helene, O M; Vanin, V R; Rodriguez, O; Mesa, J; Likhachev, V P; Filho, J W; Deppman, A; Perez, G; Guzman, F; de Camargo, S P

1999-10-01

A new and simple statistical procedure (STATFLUX) for the calculation of transfer coefficients of radionuclide transport to animals and plants is proposed. The method is based on the general multiple-compartment model, which uses a system of linear equations involving geometrical volume considerations. By using experimentally available curves of radionuclide concentrations versus time, for each animal compartment (organs), flow parameters were estimated by employing a least-squares procedure, whose consistency is tested. Some numerical results are presented in order to compare the STATFLUX transfer coefficients with those from other works and experimental data.

Hyperspectral imaging flow cytometer

DOEpatents

Sinclair, Michael B.; Jones, Howland D. T.

2017-10-25

A hyperspectral imaging flow cytometer can acquire high-resolution hyperspectral images of particles, such as biological cells, flowing through a microfluidic system. The hyperspectral imaging flow cytometer can provide detailed spatial maps of multiple emitting species, cell morphology information, and state of health. An optimized system can image about 20 cells per second. The hyperspectral imaging flow cytometer enables many thousands of cells to be characterized in a single session.

Programmable bio-nano-chip system for saliva diagnostics

NASA Astrophysics Data System (ADS)

Christodoulides, Nicolaos; De La Garza, Richard; Simmons, Glennon W.; McRae, Michael P.; Wong, Jorge; Kosten, Thomas R.; Miller, Craig S.; Ebersole, Jeffrey L.; McDevitt, John

2014-06-01

This manuscript describes programmable Bio-Nano-Chip (p-BNC) approach that serves as miniaturized assay platform designed for the rapid detection and quantitation of multiple analytes in biological fluids along with the specific applications in salivary diagnostics intended for the point of need (PON). Included here are oral fluid-based tests for local periodontal disease, systemic cardiac disease and multiplexed tests for drugs of abuse.

Screening Mammalian Cells on a Hydrogel: Functionalized Small Molecule Microarray.

PubMed

Zhu, Biwei; Jiang, Bo; Na, Zhenkun; Yao, Shao Q

2017-01-01

Mammalian cell-based microarray technology has gained wide attention, for its plethora of promising applications. The platform is able to provide simultaneous information on multiple parameters for a given target, or even multiple target proteins, in a complex biological system. Here we describe the preparation of mammalian cell-based microarrays using selectively captured of human prostate cancer cells (PC-3). This platform was then used in controlled drug release and measuring the associated drug effects on these cancer cells.

Electric and Magnetic Manipulation of Biological Systems

NASA Astrophysics Data System (ADS)

Lee, H.; Hunt, T. P.; Liu, Y.; Ham, D.; Westervelt, R. M.

2005-06-01

New types of biological cell manipulation systems, a micropost matrix, a microelectromagnet matrix, and a microcoil array, were developed. The micropost matrix consists of post-shaped electrodes embedded in an insulating layer. With a separate ac voltage applied to each electrode, the micropost matrix generates dielectrophoretic force to trap and move individual biological cells. The microelectromagnet matrix consists of two arrays of straight wires aligned perpendicular to each other, that are covered with insulating layers. By independently controlling the current in each wire, the microelectromagnet matrix creates versatile magnetic fields to manipulate individual biological cells attached to magnetic beads. The microcoil array is a set of coils implemented in a foundry using a standard silicon fabrication technology. Current sources to the coils, and control circuits are integrated on a single chip, making the device self-contained. Versatile manipulation of biological cells was demonstrated using these devices by generating optimized electric or magnetic field patterns. A single yeast cell was trapped and positioned with microscopic resolution, and multiple yeast cells were trapped and independently moved along the separate paths for cell-sorting.

Dissection of Biological Property of Chinese Acupuncture Point Zusanli Based on Long-Term Treatment via Modulating Multiple Metabolic Pathways.

PubMed

Yan, Guangli; Zhang, Aihua; Sun, Hui; Cheng, Weiping; Meng, Xiangcai; Liu, Li; Zhang, Yingzhi; Xie, Ning; Wang, Xijun

2013-01-01

Acupuncture has a history of over 3000 years and is a traditional Chinese medical therapy that uses hair-thin metal needles to puncture the skin at specific points on the body to promote wellbeing, while its molecular mechanism and ideal biological pathways are still not clear. High-throughput metabolomics is the global assessment of endogenous metabolites within a biologic system and can potentially provide a more accurate snap shot of the actual physiological state. We hypothesize that acupuncture-treated human would produce unique characterization of metabolic phenotypes. In this study, UPLC/ESI-HDMS coupled with pattern recognition methods and system analysis were carried out to investigate the mechanism and metabolite biomarkers for acupuncture treatment at "Zusanli" acupoint (ST-36) as a case study. The top 5 canonical pathways including alpha-linolenic acid metabolism, d-glutamine and d-glutamate metabolism, citrate cycle, alanine, aspartate, and glutamate metabolism, and vitamin B6 metabolism pathways were acutely perturbed, and 53 differential metabolites were identified by chemical profiling and may be useful to clarify the physiological basis and mechanism of ST-36. More importantly, network construction has led to the integration of metabolites associated with the multiple perturbation pathways. Urine metabolic profiling might be a promising method to investigate the molecular mechanism of acupuncture.

Adaptive force produced by stress-induced regulation of random variation intensity.

PubMed

Shimansky, Yury P

2010-08-01

The Darwinian theory of life evolution is capable of explaining the majority of related phenomena. At the same time, the mechanisms of optimizing traits beneficial to a population as a whole but not directly to an individual remain largely unclear. There are also significant problems with explaining the phenomenon of punctuated equilibrium. From another perspective, multiple mechanisms for the regulation of the rate of genetic mutations according to the environmental stress have been discovered, but their precise functional role is not well understood yet. Here a novel mathematical paradigm called a Kinetic-Force Principle (KFP), which can serve as a general basis for biologically plausible optimization methods, is introduced and its rigorous derivation is provided. Based on this principle, it is shown that, if the rate of random changes in a biological system is proportional, even only roughly, to the amount of environmental stress, a virtual force is created, acting in the direction of stress relief. It is demonstrated that KFP can provide important insights into solving the above problems. Evidence is presented in support of a hypothesis that the nature employs KFP for accelerating adaptation in biological systems. A detailed comparison between KFP and the principle of variation and natural selection is presented and their complementarity is revealed. It is concluded that KFP is not a competing alternative, but a powerful addition to the principle of variation and natural selection. It is also shown KFP can be used in multiple ways for adaptation of individual biological organisms.

Hyperspectral stimulated emission depletion microscopy and methods of use thereof

DOEpatents

Timlin, Jerilyn A; Aaron, Jesse S

2014-04-01

A hyperspectral stimulated emission depletion ("STED") microscope system for high-resolution imaging of samples labeled with multiple fluorophores (e.g., two to ten fluorophores). The hyperspectral STED microscope includes a light source, optical systems configured for generating an excitation light beam and a depletion light beam, optical systems configured for focusing the excitation and depletion light beams on a sample, and systems for collecting and processing data generated by interaction of the excitation and depletion light beams with the sample. Hyperspectral STED data may be analyzed using multivariate curve resolution analysis techniques to deconvolute emission from the multiple fluorophores. The hyperspectral STED microscope described herein can be used for multi-color, subdiffraction imaging of samples (e.g., materials and biological materials) and for analyzing a tissue by Forster Resonance Energy Transfer ("FRET").

Top-down models in biology: explanation and control of complex living systems above the molecular level.

PubMed

Pezzulo, Giovanni; Levin, Michael

2016-11-01

It is widely assumed in developmental biology and bioengineering that optimal understanding and control of complex living systems follows from models of molecular events. The success of reductionism has overshadowed attempts at top-down models and control policies in biological systems. However, other fields, including physics, engineering and neuroscience, have successfully used the explanations and models at higher levels of organization, including least-action principles in physics and control-theoretic models in computational neuroscience. Exploiting the dynamic regulation of pattern formation in embryogenesis and regeneration requires new approaches to understand how cells cooperate towards large-scale anatomical goal states. Here, we argue that top-down models of pattern homeostasis serve as proof of principle for extending the current paradigm beyond emergence and molecule-level rules. We define top-down control in a biological context, discuss the examples of how cognitive neuroscience and physics exploit these strategies, and illustrate areas in which they may offer significant advantages as complements to the mainstream paradigm. By targeting system controls at multiple levels of organization and demystifying goal-directed (cybernetic) processes, top-down strategies represent a roadmap for using the deep insights of other fields for transformative advances in regenerative medicine and systems bioengineering. © 2016 The Author(s).

Top-down models in biology: explanation and control of complex living systems above the molecular level

PubMed Central

2016-01-01

It is widely assumed in developmental biology and bioengineering that optimal understanding and control of complex living systems follows from models of molecular events. The success of reductionism has overshadowed attempts at top-down models and control policies in biological systems. However, other fields, including physics, engineering and neuroscience, have successfully used the explanations and models at higher levels of organization, including least-action principles in physics and control-theoretic models in computational neuroscience. Exploiting the dynamic regulation of pattern formation in embryogenesis and regeneration requires new approaches to understand how cells cooperate towards large-scale anatomical goal states. Here, we argue that top-down models of pattern homeostasis serve as proof of principle for extending the current paradigm beyond emergence and molecule-level rules. We define top-down control in a biological context, discuss the examples of how cognitive neuroscience and physics exploit these strategies, and illustrate areas in which they may offer significant advantages as complements to the mainstream paradigm. By targeting system controls at multiple levels of organization and demystifying goal-directed (cybernetic) processes, top-down strategies represent a roadmap for using the deep insights of other fields for transformative advances in regenerative medicine and systems bioengineering. PMID:27807271

The Future of the Gender System: An Interventionist Approach

ERIC Educational Resources Information Center

Harkness, Sarah K.; Hall, Deborah L.

2010-01-01

Gender is one of the primary organizers of social life. Given this importance, gender has been studied from multiple vantages, including biological, sociocognitive, interpersonal, network, and institutional perspectives. The diversity of these approaches illustrates the complex nature of gender as a multilevel social construction and that the…

Speciation analysis of arsenic in biological matrices by automated hydride generation-cryotrapping-atomic absorption spectrometry with multiple microflame quartz tube atomizer (multiatomizer).

EPA Science Inventory

This paper describes an automated system for the oxidation state specific speciation of inorganic and methylated arsenicals by selective hydride generation - cryotrapping- gas chromatography - atomic absorption spectrometry with the multiatomizer. The corresponding arsines are ge...

Bi-Fi: an embedded sensor/system architecture for REMOTE biological monitoring.

PubMed

Farshchi, Shahin; Pesterev, Aleksey; Nuyujukian, Paul H; Mody, Istvan; Judy, Jack W

2007-11-01

Wireless-enabled processor modules intended for communicating low-frequency phenomena (i.e., temperature, humidity, and ambient light) have been enabled to acquire and transmit multiple biological signals in real time, which has been achieved by using computationally efficient data acquisition, filtering, and compression algorithms, and interfacing the modules with biological interface hardware. The sensor modules can acquire and transmit raw biological signals at a rate of 32 kb/s, which is near the hardware limit of the modules. Furthermore, onboard signal processing enables one channel, sampled at a rate of 4000 samples/s at 12-bit resolution, to be compressed via adaptive differential-pulse-code modulation (ADPCM) and transmitted in real time. In addition, the sensors can be configured to filter and transmit individual time-referenced "spike" waveforms, or to transmit the spike height and width for alleviating network traffic and increasing battery life. The system is capable of acquiring eight channels of analog signals as well as data via an asynchronous serial connection. A back-end server archives the biological data received via networked gateway sensors, and hosts them to a client application that enables users to browse recorded data. The system also acquires, filters, and transmits oxygen saturation and pulse rate via a commercial-off-the-shelf interface board. The system architecture can be configured for performing real-time nonobtrusive biological monitoring of humans or rodents. This paper demonstrates that low-power, computational, and bandwidth-constrained wireless-enabled platforms can indeed be leveraged for wireless biosignal monitoring.

Modeling multisystem biological risk in young adults: The Coronary Artery Risk Development in Young Adults Study.

PubMed

Seeman, Teresa; Gruenewald, Tara; Karlamangla, Arun; Sidney, Steve; Liu, Kiang; McEwen, Bruce; Schwartz, Joseph

2010-01-01

Although much prior research has focused on identifying the roles of major regulatory systems in health risks, the concept of allostatic load (AL) focuses on the importance of a more multisystems view of health risks. How best to operationalize allostatic load, however, remains the subject of some debate. We sought to test a hypothesized metafactor model of allostatic load composed of a number of biological system factors, and to investigate model invariance across sex and ethnicity. Biological data from 782 men and women, aged 32-47, from the Oakland, CA and Chicago, IL sites of the Coronary Artery Risk Development in Young Adults Study (CARDIA) were collected as part of the Year 15exam in 2000. These include measures of blood pressure, metabolic parameters (glucose, insulin, lipid profiles, and waist circumference), markers of inflammation (interleukin-6, C-reactive protein, and fibrinogen), heart rate variability, sympathetic nervous system activity (12-hr urinary norepinephrine and epinephrine) and hypothalamic-pituitary-adrenal axis activity (diurnal salivary free cortisol). A "metafactor" model of AL as an aggregate measure of six underlying latent biological subfactors was found to fit the data, with the metafactor structure capturing 84% of variance of all pairwise associations among biological subsystems. There was little evidence of model variance across sex and/or ethnicity. These analyses extend work operationalizing AL as a multisystems index of biological dysregulation, providing initial support for a model of AL as a metaconstruct of inter-relationships among multiple biological regulatory systems, that varies little across sex or ethnicity.

Fundamental Biological Research on the International Space Station

NASA Technical Reports Server (NTRS)

Souza, K. A.; Yost, Bruce; Fletcher, L.; Dalton, Bonnie P. (Technical Monitor)

2000-01-01

The fundamental Biology Program of NASA's Life Sciences Division is chartered with enabling and sponsoring research on the International Space Station (ISS) in order to understand the effects of the space flight environment, particularly microgravity, on living systems. To accomplish this goal, NASA Ames Research Center (ARC) has been tasked with managing the development of a number of biological habitats, along with their support systems infrastructure. This integrated suite of habitats and support systems is being designed to support research requirements identified by the scientific community. As such, it will support investigations using cells and tissues, avian eggs, insects, plants, aquatic organisms and rodents. Studies following organisms through complete life cycles and over multiple generations will eventually be possible. As an adjunct to the development of these basic habitats, specific analytical and monitoring technologies are being targeted for maturation to complete the research cycle by transferring existing or emerging analytical techniques, sensors, and processes from the laboratory bench to the ISS research platform.

Vertically integrated photonic multichip module architecture for vision applications

NASA Astrophysics Data System (ADS)

Tanguay, Armand R., Jr.; Jenkins, B. Keith; von der Malsburg, Christoph; Mel, Bartlett; Holt, Gary; O'Brien, John D.; Biederman, Irving; Madhukar, Anupam; Nasiatka, Patrick; Huang, Yunsong

2000-05-01

The development of a truly smart camera, with inherent capability for low latency semi-autonomous object recognition, tracking, and optimal image capture, has remained an elusive goal notwithstanding tremendous advances in the processing power afforded by VLSI technologies. These features are essential for a number of emerging multimedia- based applications, including enhanced augmented reality systems. Recent advances in understanding of the mechanisms of biological vision systems, together with similar advances in hybrid electronic/photonic packaging technology, offer the possibility of artificial biologically-inspired vision systems with significantly different, yet complementary, strengths and weaknesses. We describe herein several system implementation architectures based on spatial and temporal integration techniques within a multilayered structure, as well as the corresponding hardware implementation of these architectures based on the hybrid vertical integration of multiple silicon VLSI vision chips by means of dense 3D photonic interconnections.

Quantitative volumetric Raman imaging of three dimensional cell cultures

NASA Astrophysics Data System (ADS)

Kallepitis, Charalambos; Bergholt, Mads S.; Mazo, Manuel M.; Leonardo, Vincent; Skaalure, Stacey C.; Maynard, Stephanie A.; Stevens, Molly M.

2017-03-01

The ability to simultaneously image multiple biomolecules in biologically relevant three-dimensional (3D) cell culture environments would contribute greatly to the understanding of complex cellular mechanisms and cell-material interactions. Here, we present a computational framework for label-free quantitative volumetric Raman imaging (qVRI). We apply qVRI to a selection of biological systems: human pluripotent stem cells with their cardiac derivatives, monocytes and monocyte-derived macrophages in conventional cell culture systems and mesenchymal stem cells inside biomimetic hydrogels that supplied a 3D cell culture environment. We demonstrate visualization and quantification of fine details in cell shape, cytoplasm, nucleus, lipid bodies and cytoskeletal structures in 3D with unprecedented biomolecular specificity for vibrational microspectroscopy.

A System Biology Perspective on Environment-Host-Microbe Interactions.

PubMed

Chen, Lianmin; Garmaeva, Sanzhima; Zherankova, Alexandra; Fu, Jingyuan; Wijmenga, Cisca

2018-04-16

A vast, complex and dynamic consortium of microorganisms known as the gut microbiome colonizes the human gut. Over the past few decades we have developed an increased awareness of its important role in human health. In this review we discuss the role of the gut microbiome in complex diseases and the possible causal scenarios behind its interactions with the host genome and environmental factors. We then propose a new analysis framework that combines a systems biology approach, cross-kingdom integration of multiple levels of omics data, and innovative in vitro models to yield an integrated picture of human host-microbe interactions. This new framework will lay the foundation for the development of the next phase in personalized medicine.

The Role of Interleukins 4 and/or 13 in the Pathophysiology and Treatment of Atopic Dermatitis.

PubMed

Silverberg, Jonathan I; Kantor, Robert

2017-07-01

Moderate to severe atopic dermatitis (AD) can be debilitating and often requires use of systemic immunosuppressant therapy to achieve adequate disease control. There are currently no US Food and Drug Administration-approved systemic agents for the long-term treatment of AD. Recent insight has identified the T helper 2 cytokines, interleukins 4 and 13, as playing a major role in the pathogenesis of AD. There are multiple novel biologic agents in development that target interleukins 4 and/or 13 for the treatment of moderate to severe AD. The age of targeted biologics for AD has arrived. Copyright © 2017 Elsevier Inc. All rights reserved.

Generalizing genetical genomics: getting added value from environmental perturbation.

PubMed

Li, Yang; Breitling, Rainer; Jansen, Ritsert C

2008-10-01

Genetical genomics is a useful approach for studying the effect of genetic perturbations on biological systems at the molecular level. However, molecular networks depend on the environmental conditions and, thus, a comprehensive understanding of biological systems requires studying them across multiple environments. We propose a generalization of genetical genomics, which combines genetic and sensibly chosen environmental perturbations, to study the plasticity of molecular networks. This strategy forms a crucial step toward understanding why individuals respond differently to drugs, toxins, pathogens, nutrients and other environmental influences. Here we outline a strategy for selecting and allocating individuals to particular treatments, and we discuss the promises and pitfalls of the generalized genetical genomics approach.

Quantitative proteomics in Giardia duodenalis-Achievements and challenges.

PubMed

Emery, Samantha J; Lacey, Ernest; Haynes, Paul A

2016-08-01

Giardia duodenalis (syn. G. lamblia and G. intestinalis) is a protozoan parasite of vertebrates and a major contributor to the global burden of diarrheal diseases and gastroenteritis. The publication of multiple genome sequences in the G. duodenalis species complex has provided important insights into parasite biology, and made post-genomic technologies, including proteomics, significantly more accessible. The aims of proteomics are to identify and quantify proteins present in a cell, and assign functions to them within the context of dynamic biological systems. In Giardia, proteomics in the post-genomic era has transitioned from reliance on gel-based systems to utilisation of a diverse array of techniques based on bottom-up LC-MS/MS technologies. Together, these have generated crucial foundations for subcellular proteomes, elucidated intra- and inter-assemblage isolate variation, and identified pathways and markers in differentiation, host-parasite interactions and drug resistance. However, in Giardia, proteomics remains an emerging field, with considerable shortcomings evident from the published research. These include a bias towards assemblage A, a lack of emphasis on quantitative analytical techniques, and limited information on post-translational protein modifications. Additionally, there are multiple areas of research for which proteomic data is not available to add value to published transcriptomic data. The challenge of amalgamating data in the systems biology paradigm necessitates the further generation of large, high-quality quantitative datasets to accurately model parasite biology. This review surveys the current proteomic research available for Giardia and evaluates their technical and quantitative approaches, while contextualising their biological insights into parasite pathology, isolate variation and eukaryotic evolution. Finally, we propose areas of priority for the generation of future proteomic data to explore fundamental questions in Giardia, including the analysis of post-translational modifications, and the design of MS-based assays for validation of differentially expressed proteins in large datasets. Copyright © 2016 Elsevier B.V. All rights reserved.

The Dominance Behavioral System and Psychopathology: Evidence from Self-Report, Observational, and Biological Studies

PubMed Central

Johnson, Sheri L.; Leedom, Liane J.; Muhtadie, Luma

2012-01-01

The dominance behavioral system (DBS) can be conceptualized as a biologically-based system which guides dominance motivation, dominant and subordinate behavior, and responsivity to perceptions of power and subordination. A growing body of research suggests that problems with the DBS are evident across a broad range of psychopathologies. We begin by describing psychological, social, and biological correlates of the dominance behavioral system (DBS). Extensive research suggests that externalizing disorders, mania-proneness, and narcissistic traits are related to heightened dominance motivation and behaviors. Mania and narcissistic traits also appear related to inflated self-perceptions of power. Anxiety and depression are related to subordination and submissiveness, as well as a desire to avoid subordination. Models of the DBS have received support from research with humans and animals; from self-report, observational, and biological methods; and using naturalistic and experimental paradigms. Limitations of available research include the relative lack of longitudinal studies using multiple measures of the DBS and the absence of relevant studies using diagnosed samples to study narcissistic personality disorder and bipolar disorder. We provide suggestions for future research on the DBS and psychopathology, including investigations of whether the DBS can be used to differentiate specific disorder outcomes; the need for more sophisticated biological research; and the value of longitudinal dynamical research. Implications of using the DBS as a tool in clinical assessment and treatment are discussed. PMID:22506751

Variability in seeds: biological, ecological, and agricultural implications.

PubMed

Mitchell, Jack; Johnston, Iain G; Bassel, George W

2017-02-01

Variability is observed in biology across multiple scales, ranging from populations, individuals, and cells to the molecular components within cells. This review explores the sources and roles of this variability across these scales, focusing on seeds. From a biological perspective, the role and the impact this variability has on seed behaviour and adaptation to the environment is discussed. The consequences of seed variability on agricultural production systems, which demand uniformity, are also examined. We suggest that by understanding the basis and underlying mechanisms of variability in seeds, strategies to increase seed population uniformity can be developed, leading to enhanced agricultural production across variable climatic conditions. © The Author 2016. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

A suggested approach to the selection of chemical and biological protective clothing--meeting industry and emergency response needs for protection against a variety of hazards.

PubMed

Stull, Jeffrey O

2004-01-01

The paper describes the development of a comprehensive decision logic for selection and use of biological and chemical protective clothing (BCPC). The decision logic recognizes the separate areas of BCPC use among emergency, biological, and chemical hazards. The proposed decision logic provides a system for type classifying BCPC in terms of its compliance with existing standards (for emergency applications), the overall clothing integrity, and the material barrier performance. Type classification is offered for garments, gloves, footwear, and eye/face protection devices. On the basis of multiple, but simply designed flowcharts, the type of BCPC appropriate for specific biological and chemical hazards can be selected. The decision logic also provides supplemental considerations for choosing appropriate BCPC features.

Using Temporal Correlations and Full Distributions to Separate Intrinsic and Extrinsic Fluctuations in Biological Systems

NASA Astrophysics Data System (ADS)

Hilfinger, Andreas; Chen, Mark; Paulsson, Johan

2012-12-01

Studies of stochastic biological dynamics typically compare observed fluctuations to theoretically predicted variances, sometimes after separating the intrinsic randomness of the system from the enslaving influence of changing environments. But variances have been shown to discriminate surprisingly poorly between alternative mechanisms, while for other system properties no approaches exist that rigorously disentangle environmental influences from intrinsic effects. Here, we apply the theory of generalized random walks in random environments to derive exact rules for decomposing time series and higher statistics, rather than just variances. We show for which properties and for which classes of systems intrinsic fluctuations can be analyzed without accounting for extrinsic stochasticity and vice versa. We derive two independent experimental methods to measure the separate noise contributions and show how to use the additional information in temporal correlations to detect multiplicative effects in dynamical systems.

A Systems Biology Approach for Identifying Hepatotoxicant Groups Based on Similarity in Mechanisms of Action and Chemical Structure.

PubMed

Hebels, Dennie G A J; Rasche, Axel; Herwig, Ralf; van Westen, Gerard J P; Jennen, Danyel G J; Kleinjans, Jos C S

2016-01-01

When evaluating compound similarity, addressing multiple sources of information to reach conclusions about common pharmaceutical and/or toxicological mechanisms of action is a crucial strategy. In this chapter, we describe a systems biology approach that incorporates analyses of hepatotoxicant data for 33 compounds from three different sources: a chemical structure similarity analysis based on the 3D Tanimoto coefficient, a chemical structure-based protein target prediction analysis, and a cross-study/cross-platform meta-analysis of in vitro and in vivo human and rat transcriptomics data derived from public resources (i.e., the diXa data warehouse). Hierarchical clustering of the outcome scores of the separate analyses did not result in a satisfactory grouping of compounds considering their known toxic mechanism as described in literature. However, a combined analysis of multiple data types may hypothetically compensate for missing or unreliable information in any of the single data types. We therefore performed an integrated clustering analysis of all three data sets using the R-based tool iClusterPlus. This indeed improved the grouping results. The compound clusters that were formed by means of iClusterPlus represent groups that show similar gene expression while simultaneously integrating a similarity in structure and protein targets, which corresponds much better with the known mechanism of action of these toxicants. Using an integrative systems biology approach may thus overcome the limitations of the separate analyses when grouping liver toxicants sharing a similar mechanism of toxicity.

New directions in the treatment of systemic lupus erythematosus.

PubMed

Kalunian, Kenneth; Merrill, Joan T

2009-06-01

The aim of this review is to provide an up-to-date overview of treatment approaches for systemic lupus erythematosus (SLE), highlighting the multiplicity and heterogeneity of clinical symptoms that underlie therapeutic decisions. Discussion will focus on the spectrum of currently available therapies, their mechanisms and associated side-effects. Finally, recent developments with biologic treatments including rituximab, epratuzumab, tumor necrosis factor (TNF) inhibitors, and belimumab, will be discussed. A MEDLINE literature search for 'systemic lupus erythematosus' and 'damage' and 'treatment' was undertaken for 1996-2008. Secondary citations were obtained from selected manuscripts. Individual case studies were excluded. SLE is an autoimmune disease involving multiple organ systems, a clinical pattern of flares and remissions, and the presence of anti-nuclear autoantibodies. Whereas early symptoms most frequently involve the skin and joints, disease morbidity and mortality are usually associated with cardiovascular events and damage to major organs, particularly the kidneys. Many of the current therapeutic options are considered to be inadequate because of toxicities, accrual of organ damage, and insufficient control of the underlying disease pathology. Improved understanding of SLE pathogenesis and immunology has led to the identification of new treatment targets. Current interest is mainly focused on the targeted immunosuppressive actions provided by biologic therapy. Although the potential long-term beneficial or harmful effects of the new molecular treatments are unclear, their precise molecular targeting may reveal key relationships within the immune system and advance the cause of individualized molecular medicine. Biologic compounds that target specific immunologic mechanisms offer a new paradigm in the treatment of SLE, one that may, at best, reverse the course of the disease and, at the very least, might provide some new alternatives to reduce symptoms and limit tissue damage without undue contribution to overall morbidity and mortality.

Identification of Modules in Protein-Protein Interaction Networks

NASA Astrophysics Data System (ADS)

Erten, Sinan; Koyutürk, Mehmet

In biological systems, most processes are carried out through orchestration of multiple interacting molecules. These interactions are often abstracted using network models. A key feature of cellular networks is their modularity, which contributes significantly to the robustness, as well as adaptability of biological systems. Therefore, modularization of cellular networks is likely to be useful in obtaining insights into the working principles of cellular systems, as well as building tractable models of cellular organization and dynamics. A common, high-throughput source of data on molecular interactions is in the form of physical interactions between proteins, which are organized into protein-protein interaction (PPI) networks. This chapter provides an overview on identification and analysis of functional modules in PPI networks, which has been an active area of research in the last decade.

Characteristic Variations and Similarities in Biochemical, Molecular, and Functional Properties of Glyoxalases across Prokaryotes and Eukaryotes.

PubMed

Kaur, Charanpreet; Sharma, Shweta; Hasan, Mohammad Rokebul; Pareek, Ashwani; Singla-Pareek, Sneh L; Sopory, Sudhir K

2017-03-30

The glyoxalase system is the ubiquitous pathway for the detoxification of methylglyoxal (MG) in the biological systems. It comprises two enzymes, glyoxalase I (GLYI) and glyoxalase II (GLYII), which act sequentially to convert MG into d-lactate, thereby helping living systems get rid of this otherwise cytotoxic byproduct of metabolism. In addition, a glutathione-independent GLYIII enzyme activity also exists in the biological systems that can directly convert MG to d-lactate. Humans and Escherichia coli possess a single copy of GLYI (encoding either the Ni- or Zn-dependent form) and GLYII genes, which through MG detoxification provide protection against various pathological and disease conditions. By contrast, the plant genome possesses multiple GLYI and GLYII genes with a role in abiotic stress tolerance. Plants possess both Ni 2+ - and Zn 2+ -dependent forms of GLYI, and studies on plant glyoxalases reveal the various unique features of these enzymes distinguishing them from prokaryotic and other eukaryotic glyoxalases. Through this review, we provide an overview of the plant glyoxalase family along with a comparative analysis of glyoxalases across various species, highlighting similarities as well as differences in the biochemical, molecular, and physiological properties of these enzymes. We believe that the evolution of multiple glyoxalases isoforms in plants is an important component of their robust defense strategies.

An integrative model of evolutionary covariance: a symposium on body shape in fishes.

PubMed

Walker, Jeffrey A

2010-12-01

A major direction of current and future biological research is to understand how multiple, interacting functional systems coordinate in producing a body that works. This understanding is complicated by the fact that organisms need to work well in multiple environments, with both predictable and unpredictable environmental perturbations. Furthermore, organismal design reflects a history of past environments and not a plan for future environments. How complex, interacting functional systems evolve, then, is a truly grand challenge. In accepting the challenge, an integrative model of evolutionary covariance is developed. The model combines quantitative genetics, functional morphology/physiology, and functional ecology. The model is used to convene scientists ranging from geneticists, to physiologists, to ecologists, to engineers to facilitate the emergence of body shape in fishes as a model system for understanding how complex, interacting functional systems develop and evolve. Body shape of fish is a complex morphology that (1) results from many developmental paths and (2) functions in many different behaviors. Understanding the coordination and evolution of the many paths from genes to body shape, body shape to function, and function to a working fish body in a dynamic environment is now possible given new technologies from genetics to engineering and new theoretical models that integrate the different levels of biological organization (from genes to ecology).

Metabolomics applied to the pancreatic islet.

PubMed

Gooding, Jessica R; Jensen, Mette V; Newgard, Christopher B

2016-01-01

Metabolomics, the characterization of the set of small molecules in a biological system, is advancing research in multiple areas of islet biology. Measuring a breadth of metabolites simultaneously provides a broad perspective on metabolic changes as the islets respond dynamically to metabolic fuels, hormones, or environmental stressors. As a result, metabolomics has the potential to provide new mechanistic insights into islet physiology and pathophysiology. Here we summarize advances in our understanding of islet physiology and the etiologies of type-1 and type-2 diabetes gained from metabolomics studies. Copyright © 2015 Elsevier Inc. All rights reserved.

Nonlinear interferometric vibrational imaging of biological tissue

NASA Astrophysics Data System (ADS)

Jiang, Zhi; Marks, Daniel L.; Geddes, Joseph B., III; Boppart, Stephen A.

2008-02-01

We demonstrate imaging with the technique of nonlinear interferometric vibrational imaging (NIVI). Experimental images using this instrumentation and method have been acquired from both phantom and biological tissues. In our system, coherent anti-Stokes Raman scattering (CARS) signals are detected by spectral interferometry, which is able to fully restore high resolution Raman spectrum on each focal spot of a sample covering multiple Raman bands using broadband pump and Stokes laser beams. Spectral-domain detection has been demonstrated and allows for a significant increase in image acquiring speed, in signal-to-noise, and in interferometric signal stability.

Augmenting Surgery via Multi-scale Modeling and Translational Systems Biology in the Era of Precision Medicine: A Multidisciplinary Perspective

PubMed Central

Kassab, Ghassan S.; An, Gary; Sander, Edward A.; Miga, Michael; Guccione, Julius M.; Ji, Songbai; Vodovotz, Yoram

2016-01-01

In this era of tremendous technological capabilities and increased focus on improving clinical outcomes, decreasing costs, and increasing precision, there is a need for a more quantitative approach to the field of surgery. Multiscale computational modeling has the potential to bridge the gap to the emerging paradigms of Precision Medicine and Translational Systems Biology, in which quantitative metrics and data guide patient care through improved stratification, diagnosis, and therapy. Achievements by multiple groups have demonstrated the potential for 1) multiscale computational modeling, at a biological level, of diseases treated with surgery and the surgical procedure process at the level of the individual and the population; along with 2) patient-specific, computationally-enabled surgical planning, delivery, and guidance and robotically-augmented manipulation. In this perspective article, we discuss these concepts, and cite emerging examples from the fields of trauma, wound healing, and cardiac surgery. PMID:27015816

At the Edge of Translation – Materials to Program Cells for Directed Differentiation

PubMed Central

Arany, Praveen R; Mooney, David J

2010-01-01

The rapid advancement in basic biology knowledge, especially in the stem cell field, has created new opportunities to develop biomaterials capable of orchestrating the behavior of transplanted and host cells. Based on our current understanding of cellular differentiation, a conceptual framework for the use of materials to program cells in situ is presented, namely a domino versus a switchboard model, to highlight the use of single versus multiple cues in a controlled manner to modulate biological processes. Further, specific design principles of material systems to present soluble and insoluble cues that are capable of recruiting, programming and deploying host cells for various applications are presented. The evolution of biomaterials from simple inert substances used to fill defects, to the recent development of sophisticated material systems capable of programming cells in situ is providing a platform to translate our understanding of basic biological mechanisms to clinical care. PMID:20860763

Shadows of complexity: what biological networks reveal about epistasis and pleiotropy

PubMed Central

Tyler, Anna L.; Asselbergs, Folkert W.; Williams, Scott M.; Moore, Jason H.

2011-01-01

Pleiotropy, in which one mutation causes multiple phenotypes, has traditionally been seen as a deviation from the conventional observation in which one gene affects one phenotype. Epistasis, or gene-gene interaction, has also been treated as an exception to the Mendelian one gene-one phenotype paradigm. This simplified perspective belies the pervasive complexity of biology and hinders progress toward a deeper understanding of biological systems. We assert that epistasis and pleiotropy are not isolated occurrences, but ubiquitous and inherent properties of biomolecular networks. These phenomena should not be treated as exceptions, but rather as fundamental components of genetic analyses. A systems level understanding of epistasis and pleiotropy is, therefore, critical to furthering our understanding of human genetics and its contribution to common human disease. Finally, graph theory offers an intuitive and powerful set of tools with which to study the network bases of these important genetic phenomena. PMID:19204994

Red blood cells aggregability measurement of coagulating blood in extracorporeal circulation system with multiple-frequency electrical impedance spectroscopy.

PubMed

Li, Jianping; Sapkota, Achyut; Kikuchi, Daisuke; Sakota, Daisuke; Maruyama, Osamu; Takei, Masahiro

2018-07-30

Red blood cells (RBCs) aggregability A G of coagulating blood in extracorporeal circulation system has been investigated under the condition of pulsatile flow. Relaxation frequency f c from the multiple-frequency electrical impedance spectroscopy is utilized to obtain RBCs aggregability A G . Compared with other methods, the proposed multiple-frequency electrical impedance method is much easier to obtain non-invasive measurement with high speed and good penetrability performance in biology tissues. Experimental results show that, RBCs aggregability A G in coagulating blood falls down with the thrombus formation while that in non-coagulation blood almost keeps the same value, which has a great agreement with the activated clotting time (ACT) fibrinogen concertation (F bg ) tests. Modified Hanai formula is proposed to quantitatively analyze the influence of RBCs aggregation on multiple-frequency electrical impedance measurement. The reduction of RBCs aggregability A G is associated with blood coagulation reaction, which indicates the feasibility of the high speed, compact and cheap on-line thrombus measurement biosensors in extracorporeal circulation systems. Copyright © 2018 Elsevier B.V. All rights reserved.

Central nervous system remyelination in culture--a tool for multiple sclerosis research.

PubMed

Zhang, Hui; Jarjour, Andrew A; Boyd, Amanda; Williams, Anna

2011-07-01

Multiple sclerosis is a demyelinating disease of the central nervous system which only affects humans. This makes it difficult to study at a molecular level, and to develop and test potential therapies that may change the course of the disease. The development of therapies to promote remyelination in multiple sclerosis is a key research aim, to both aid restoration of electrical impulse conduction in nerves and provide neuroprotection, reducing disability in patients. Testing a remyelination therapy in the many and various in vivo models of multiple sclerosis is expensive in terms of time, animals and money. We report the development and characterisation of an ex vivo slice culture system using mouse brain and spinal cord, allowing investigation of myelination, demyelination and remyelination, which can be used as an initial reliable screen to select the most promising remyelination strategies. We have automated the quantification of myelin to provide a high content and moderately-high-throughput screen for testing therapies for remyelination both by endogenous and exogenous means and as an invaluable way of studying the biology of remyelination. Copyright © 2011 Elsevier Inc. All rights reserved.

Central nervous system remyelination in culture — A tool for multiple sclerosis research

PubMed Central

Zhang, Hui; Jarjour, Andrew A.; Boyd, Amanda; Williams, Anna

2011-01-01

Multiple sclerosis is a demyelinating disease of the central nervous system which only affects humans. This makes it difficult to study at a molecular level, and to develop and test potential therapies that may change the course of the disease. The development of therapies to promote remyelination in multiple sclerosis is a key research aim, to both aid restoration of electrical impulse conduction in nerves and provide neuroprotection, reducing disability in patients. Testing a remyelination therapy in the many and various in vivo models of multiple sclerosis is expensive in terms of time, animals and money. We report the development and characterisation of an ex vivo slice culture system using mouse brain and spinal cord, allowing investigation of myelination, demyelination and remyelination, which can be used as an initial reliable screen to select the most promising remyelination strategies. We have automated the quantification of myelin to provide a high content and moderately-high-throughput screen for testing therapies for remyelination both by endogenous and exogenous means and as an invaluable way of studying the biology of remyelination. PMID:21515259

How Animal Models Inform Child and Adolescent Psychiatry

PubMed Central

Stevens, Hanna E.; Vaccarino, Flora M.

2015-01-01

Objective Every available approach should be utilized to advance the field of child and adolescent psychiatry. Biological systems are important for the behavioral problems of children. Close examination of non-human animals and the biology and behavior they share with humans is an approach that must be used to advance the clinical work of child psychiatry. Method We review here how model systems are used to contribute to significant insights into childhood psychiatric disorders. Model systems have not only demonstrated causality of risk factors for psychiatric pathophysiology but have also allowed child psychiatrists to think in different ways about risks for psychiatric disorders and multiple levels that might be the basis of recovery and prevention. Results We present examples of how animal systems are utilized to benefit child psychiatry, including through environmental, genetic, and acute biological manipulations. Animal model work has been essential in our current thinking about childhood disorders, including the importance of dose and timing of risk factors, specific features of risk factors that are significant, neurochemistry involved in brain functioning, molecular components of brain development, and the importance of cellular processes previously neglected in psychiatric theories. Conclusion Animal models have clear advantages and disadvantages that must both be considered for these systems to be useful. Coupled with increasingly sophisticated methods for investigating human behavior and biology, animal model systems will continue to make essential contributions to our field. PMID:25901771

Advancing Small Satellite Electronics Heritage for Microfluidic Biological Experiments

NASA Technical Reports Server (NTRS)

White, Bruce; Mazmanian, Edward; Tapio, Eric

2016-01-01

DLR's Eu:CROPIS (Euglena and Combined Regenerative Organic-Food Production in Space) mission, launching in 2017, will carry multiple biological payloads into a sun-synchronous orbit, including NASA Ames' PowerCell experiment. PowerCell will attempt to characterize the viability of synthetic biology at micro-g, Lunar, and Martian gravity levels. PowerCell experiment requirements demand an electronic system similar to previous microfluidic biology payloads, but with an expanded feature set. As such, the system was based on PharmaSat (Diaz-Aguado et al. 2009), a previous successful biology payload from NASA Ames, and improved upon. Newer, more miniaturized electronics allow for greater capability with a lower part count and smaller size. Two identical PowerCell enclosures will fly. Each enclosure contains two separate and identical experiments with a 48-segment optical density measurement system, grow light system, microfluidic system for nutrient delivery and waste flushing, plus thermal control and environmental sensing/housekeeping including temperature, pressure, humidity, and acceleration. Electronics consist of a single Master PCB that interfaces to the spacecraft bus and regulates power and communication, plus LED, Detector, and Valve Manifold PCBs for each experiment. To facilitate ease of reuse on future missions, experiment electronics were designed to be compatible with a standard 3U small sat form factor and power bus, or to interface with a Master power/comm PCB for use in a larger satellite as in the case of PowerCell's flight on Eu:CROPIS.

A Systems Biology Analysis Unfolds the Molecular Pathways and Networks of Two Proteobacteria in Spaceflight and Simulated Microgravity Conditions

NASA Astrophysics Data System (ADS)

Roy, Raktim; Phani Shilpa, P.; Bagh, Sangram

2016-09-01

Bacteria are important organisms for space missions due to their increased pathogenesis in microgravity that poses risks to the health of astronauts and for projected synthetic biology applications at the space station. We understand little about the effect, at the molecular systems level, of microgravity on bacteria, despite their significant incidence. In this study, we proposed a systems biology pipeline and performed an analysis on published gene expression data sets from multiple seminal studies on Pseudomonas aeruginosa and Salmonella enterica serovar Typhimurium under spaceflight and simulated microgravity conditions. By applying gene set enrichment analysis on the global gene expression data, we directly identified a large number of new, statistically significant cellular and metabolic pathways involved in response to microgravity. Alteration of metabolic pathways in microgravity has rarely been reported before, whereas in this analysis metabolic pathways are prevalent. Several of those pathways were found to be common across studies and species, indicating a common cellular response in microgravity. We clustered genes based on their expression patterns using consensus non-negative matrix factorization. The genes from different mathematically stable clusters showed protein-protein association networks with distinct biological functions, suggesting the plausible functional or regulatory network motifs in response to microgravity. The newly identified pathways and networks showed connection with increased survival of pathogens within macrophages, virulence, and antibiotic resistance in microgravity. Our work establishes a systems biology pipeline and provides an integrated insight into the effect of microgravity at the molecular systems level.

Systems biomarkers as acute diagnostics and chronic monitoring tools for traumatic brain injury

NASA Astrophysics Data System (ADS)

Wang, Kevin K. W.; Moghieb, Ahmed; Yang, Zhihui; Zhang, Zhiqun

2013-05-01

Traumatic brain injury (TBI) is a significant biomedical problem among military personnel and civilians. There exists an urgent need to develop and refine biological measures of acute brain injury and chronic recovery after brain injury. Such measures "biomarkers" can assist clinicians in helping to define and refine the recovery process and developing treatment paradigms for the acutely injured to reduce secondary injury processes. Recent biomarker studies in the acute phase of TBI have highlighted the importance and feasibilities of identifying clinically useful biomarkers. However, much less is known about the subacute and chronic phases of TBI. We propose here that for a complex biological problem such as TBI, multiple biomarker types might be needed to harness the wide range of pathological and systemic perturbations following injuries, including acute neuronal death, neuroinflammation, neurodegeneration and neuroregeneration to systemic responses. In terms of biomarker types, they range from brain-specific proteins, microRNA, genetic polymorphism, inflammatory cytokines and autoimmune markers and neuro-endocrine hormones. Furthermore, systems biology-driven biomarkers integration can help present a holistic approach to understanding scenarios and complexity pathways involved in brain injury.

A Novel Method to Verify Multilevel Computational Models of Biological Systems Using Multiscale Spatio-Temporal Meta Model Checking

PubMed Central

Gilbert, David

2016-01-01

Insights gained from multilevel computational models of biological systems can be translated into real-life applications only if the model correctness has been verified first. One of the most frequently employed in silico techniques for computational model verification is model checking. Traditional model checking approaches only consider the evolution of numeric values, such as concentrations, over time and are appropriate for computational models of small scale systems (e.g. intracellular networks). However for gaining a systems level understanding of how biological organisms function it is essential to consider more complex large scale biological systems (e.g. organs). Verifying computational models of such systems requires capturing both how numeric values and properties of (emergent) spatial structures (e.g. area of multicellular population) change over time and across multiple levels of organization, which are not considered by existing model checking approaches. To address this limitation we have developed a novel approximate probabilistic multiscale spatio-temporal meta model checking methodology for verifying multilevel computational models relative to specifications describing the desired/expected system behaviour. The methodology is generic and supports computational models encoded using various high-level modelling formalisms because it is defined relative to time series data and not the models used to generate it. In addition, the methodology can be automatically adapted to case study specific types of spatial structures and properties using the spatio-temporal meta model checking concept. To automate the computational model verification process we have implemented the model checking approach in the software tool Mule (http://mule.modelchecking.org). Its applicability is illustrated against four systems biology computational models previously published in the literature encoding the rat cardiovascular system dynamics, the uterine contractions of labour, the Xenopus laevis cell cycle and the acute inflammation of the gut and lung. Our methodology and software will enable computational biologists to efficiently develop reliable multilevel computational models of biological systems. PMID:27187178

A Novel Method to Verify Multilevel Computational Models of Biological Systems Using Multiscale Spatio-Temporal Meta Model Checking.

PubMed

Pârvu, Ovidiu; Gilbert, David

2016-01-01

Insights gained from multilevel computational models of biological systems can be translated into real-life applications only if the model correctness has been verified first. One of the most frequently employed in silico techniques for computational model verification is model checking. Traditional model checking approaches only consider the evolution of numeric values, such as concentrations, over time and are appropriate for computational models of small scale systems (e.g. intracellular networks). However for gaining a systems level understanding of how biological organisms function it is essential to consider more complex large scale biological systems (e.g. organs). Verifying computational models of such systems requires capturing both how numeric values and properties of (emergent) spatial structures (e.g. area of multicellular population) change over time and across multiple levels of organization, which are not considered by existing model checking approaches. To address this limitation we have developed a novel approximate probabilistic multiscale spatio-temporal meta model checking methodology for verifying multilevel computational models relative to specifications describing the desired/expected system behaviour. The methodology is generic and supports computational models encoded using various high-level modelling formalisms because it is defined relative to time series data and not the models used to generate it. In addition, the methodology can be automatically adapted to case study specific types of spatial structures and properties using the spatio-temporal meta model checking concept. To automate the computational model verification process we have implemented the model checking approach in the software tool Mule (http://mule.modelchecking.org). Its applicability is illustrated against four systems biology computational models previously published in the literature encoding the rat cardiovascular system dynamics, the uterine contractions of labour, the Xenopus laevis cell cycle and the acute inflammation of the gut and lung. Our methodology and software will enable computational biologists to efficiently develop reliable multilevel computational models of biological systems.

Voting systems for environmental decisions.

PubMed

Burgman, Mark A; Regan, Helen M; Maguire, Lynn A; Colyvan, Mark; Justus, James; Martin, Tara G; Rothley, Kris

2014-04-01

Voting systems aggregate preferences efficiently and are often used for deciding conservation priorities. Desirable characteristics of voting systems include transitivity, completeness, and Pareto optimality, among others. Voting systems that are common and potentially useful for environmental decision making include simple majority, approval, and preferential voting. Unfortunately, no voting system can guarantee an outcome, while also satisfying a range of very reasonable performance criteria. Furthermore, voting methods may be manipulated by decision makers and strategic voters if they have knowledge of the voting patterns and alliances of others in the voting populations. The difficult properties of voting systems arise in routine decision making when there are multiple criteria and management alternatives. Because each method has flaws, we do not endorse one method. Instead, we urge organizers to be transparent about the properties of proposed voting systems and to offer participants the opportunity to approve the voting system as part of the ground rules for operation of a group. © 2014 The Authors. Conservation Biology published by Wiley Periodicals, Inc., on behalf of the Society for Conservation Biology.

The messenger matters: Pollinator functional group influences mating system dynamics.

PubMed

Weber, Jennifer J

2017-08-01

The incredible diversity of plant mating systems has fuelled research in evolutionary biology for over a century. Currently, there is broad concern about the impact of rapidly changing pollinator communities on plant populations. Very few studies, however, examine patterns and mechanisms associated with multiple paternity from cross-pollen loads. Often, foraging pollinators collect a mixed pollen load that may result in the deposition of pollen from different sires to receptive stigmas. Coincident deposition of self- and cross-pollen leads to interesting mating system dynamics and has been investigated in numerous species. But, mixed pollen loads often consist of a diversity of cross-pollen and result in multiple sires of seeds within a fruit. In this issue of Molecular Ecology, Rhodes, Fant, and Skogen () examine how pollinator identity and spatial isolation influence multiple paternity within fruits of a self-incompatible evening primrose. The authors demonstrate that pollen pool diversity varies between two pollinator types, hawkmoths and diurnal solitary bees. Further, progeny from more isolated plants were less likely to have multiple sires regardless of the pollinator type. Moving forward, studies of mating system dynamics should consider the implications of multiple paternity and move beyond the self- and cross-pollination paradigm. Rhodes et al. () demonstrate the importance of understanding the roles that functionally diverse pollinators play in mating system dynamics. © 2017 John Wiley & Sons Ltd.

A group LASSO-based method for robustly inferring gene regulatory networks from multiple time-course datasets.

PubMed

Liu, Li-Zhi; Wu, Fang-Xiang; Zhang, Wen-Jun

2014-01-01

As an abstract mapping of the gene regulations in the cell, gene regulatory network is important to both biological research study and practical applications. The reverse engineering of gene regulatory networks from microarray gene expression data is a challenging research problem in systems biology. With the development of biological technologies, multiple time-course gene expression datasets might be collected for a specific gene network under different circumstances. The inference of a gene regulatory network can be improved by integrating these multiple datasets. It is also known that gene expression data may be contaminated with large errors or outliers, which may affect the inference results. A novel method, Huber group LASSO, is proposed to infer the same underlying network topology from multiple time-course gene expression datasets as well as to take the robustness to large error or outliers into account. To solve the optimization problem involved in the proposed method, an efficient algorithm which combines the ideas of auxiliary function minimization and block descent is developed. A stability selection method is adapted to our method to find a network topology consisting of edges with scores. The proposed method is applied to both simulation datasets and real experimental datasets. It shows that Huber group LASSO outperforms the group LASSO in terms of both areas under receiver operating characteristic curves and areas under the precision-recall curves. The convergence analysis of the algorithm theoretically shows that the sequence generated from the algorithm converges to the optimal solution of the problem. The simulation and real data examples demonstrate the effectiveness of the Huber group LASSO in integrating multiple time-course gene expression datasets and improving the resistance to large errors or outliers.

Speciation analysis of arsenic in biological matrices by automated hydride generation-cryotrapping-atomic absorption spectrometry with multiple microflame quartz tube atomizer (multiatomizer)

PubMed Central

Hernández-Zavala, Araceli; Matoušek, Tomáš; Drobná, Zuzana; Paul, David S.; Walton, Felecia; Adair, Blakely M.; Jiří, Dědina; Thomas, David J.

2008-01-01

Analyses of arsenic (As) species in tissues and body fluids of individuals chronically exposed to inorganic arsenic (iAs) provide essential information about the exposure level and pattern of iAs metabolism. We have previously described an oxidation state-specific analysis of As species in biological matrices by hydride-generation atomic absorption spectrometry (HG-AAS), using cryotrapping (CT) for preconcentration and separation of arsines. To improve performance and detection limits of the method, HG and CT steps are automated and a conventional flame-in-tube atomizer replaced with a recently developed multiple microflame quartz tube atomizer (multiatomizer). In this system, arsines from AsIII-species are generated in a mixture of Tris-HCl (pH 6) and sodium borohydride. For generation of arsines from both AsIII- and AsV-species, samples are pretreated with L-cysteine. Under these conditions, dimethylthioarsinic acid, a newly described metabolite of iAs, does not interfere significantly with detection and quantification of methylated trivalent arsenicals. Analytical performance of the automated HG-CT-AAS was characterized by analyses of cultured cells and mouse tissues that contained mono- and dimethylated metabolites of iAs. The capacity to detect methylated AsIII- and AsV-species was verified, using an in vitro methylation system containing recombinant rat arsenic (+3 oxidation state) methyltransferase and cultured rat hepatocytes treated with iAs. Compared with the previous HG-CT-AAS design, detection limits for iAs and its metabolites have improved significantly with the current system, ranging from 8 to 20 pg. Recoveries of As were between 78 and 117%. The precision of the method was better than 5% for all biological matrices examined. Thus, the automated HG-CT-AAS system provides an effective and sensitive tool for analysis of all major human metabolites of iAs in complex biological matrices. PMID:18677417

Breeding system and interaccessional hybridization of Purshia tridentata plants grown in a common garden

Treesearch

Rosemary L. Pendleton; E. Durant McArthur; Stewart C. Sanderson

2012-01-01

Purshia spp. (Rosaceae) comprise a widespread western North American species complex that is important as landscape dominants, wildlife habitat, browse for wild and domestic ungulates, and seed reserves for small mammals. This study examined aspects of the phenology, compatibility, pollination biology, and progeny fruit characteristics of multiple accessions of...

Identification of Absorption, Distribution, Metabolism, and Excretion (ADME) Genes Relevant to Steatosis Using a Systems Biology Approach

EPA Science Inventory

Ensuring chemical safety and sustainability form a main priority of the U.S. Environmental Protection Agency. This entails efforts on multiple fronts to characterize the potential hazard posed by chemicals currently in use and those to be commercialized in the future. The use of ...

SysBioCube: A Data Warehouse and Integrative Data Analysis Platform Facilitating Systems Biology Studies of Disorders of Military Relevance

DTIC Science & Technology

2013-12-18

include interactive gene and methylation profiles, interactive heatmaps, cytoscape network views, integrative genomics viewer ( IGV ), and protein-protein...single chart. The website also provides an option to include multiple genes. Integrative Genomics Viewer ( IGV )1, is a high-performance desktop tool for

Biodiversity and Ecosystem Functioning: Exploring Principles of Ecology with Agricultural Plants

ERIC Educational Resources Information Center

Ruesink, Jennifer; O'Connor, Eileen; Sparks, Grace

2006-01-01

To date, little of the ecological research on biological diversity and ecosystem functioning has been carried out in agricultural systems, despite the fact that agriculture is a major contributor to loss of native habitats and species. However, agricultural research has demonstrated that polycultures of multiple crop species can have higher total…

Ghrelin stimulates growth hormone release from the pituitary via hypothalamic growth hormone-releasing hormone neurons in the cichlid, Oreochromis niloticus

USDA-ARS?s Scientific Manuscript database

Ghrelin, a gastric peptide, is implicated in a multiplicity of biological functions, including energy homeostasis and reproduction. Neuronal systems that are involved in energy homeostasis as well as reproduction traverse the hypothalamus, however, the mechanism by which they control energy homeosta...

Hierarchical Feedback Modules and Reaction Hubs in Cell Signaling Networks

PubMed Central

Xu, Jianfeng; Lan, Yueheng

2015-01-01

Despite much effort, identification of modular structures and study of their organizing and functional roles remain a formidable challenge in molecular systems biology, which, however, is essential in reaching a systematic understanding of large-scale cell regulation networks and hence gaining capacity of exerting effective interference to cell activity. Combining graph theoretic methods with available dynamics information, we successfully retrieved multiple feedback modules of three important signaling networks. These feedbacks are structurally arranged in a hierarchical way and dynamically produce layered temporal profiles of output signals. We found that global and local feedbacks act in very different ways and on distinct features of the information flow conveyed by signal transduction but work highly coordinately to implement specific biological functions. The redundancy embodied with multiple signal-relaying channels and feedback controls bestow great robustness and the reaction hubs seated at junctions of different paths announce their paramount importance through exquisite parameter management. The current investigation reveals intriguing general features of the organization of cell signaling networks and their relevance to biological function, which may find interesting applications in analysis, design and control of bio-networks. PMID:25951347

Loading, Release, Biodegradation, and Biocompatibility of a Nanovector Delivery System

NASA Technical Reports Server (NTRS)

Ferrai, Mauro; Tasciotti, Ennio

2012-01-01

A nanovector multistage system has been created to overcome or bypass sequential barriers within the human body, in order to deliver a therapeutic or imaging agent to a specific location. This innovation consists of a composition that includes two or more stages of particles, such that smaller, later-stage particles are contained in the larger, early-stage particles. An active agent, such as a therapeutic agent or imaging agent, is preferentially delivered and/or localized to a particular target site in the body of a subject. The multistage composition overcomes multiple biological barriers in the body. The multistage composition also allows for simultaneous delivery and localization at the same or different target sites of multiple active agents.

A cell-based systems biology assessment of human blood to monitor immune responses after influenza vaccination.

PubMed

Hoek, Kristen L; Samir, Parimal; Howard, Leigh M; Niu, Xinnan; Prasad, Nripesh; Galassie, Allison; Liu, Qi; Allos, Tara M; Floyd, Kyle A; Guo, Yan; Shyr, Yu; Levy, Shawn E; Joyce, Sebastian; Edwards, Kathryn M; Link, Andrew J

2015-01-01

Systems biology is an approach to comprehensively study complex interactions within a biological system. Most published systems vaccinology studies have utilized whole blood or peripheral blood mononuclear cells (PBMC) to monitor the immune response after vaccination. Because human blood is comprised of multiple hematopoietic cell types, the potential for masking responses of under-represented cell populations is increased when analyzing whole blood or PBMC. To investigate the contribution of individual cell types to the immune response after vaccination, we established a rapid and efficient method to purify human T and B cells, natural killer (NK) cells, myeloid dendritic cells (mDC), monocytes, and neutrophils from fresh venous blood. Purified cells were fractionated and processed in a single day. RNA-Seq and quantitative shotgun proteomics were performed to determine expression profiles for each cell type prior to and after inactivated seasonal influenza vaccination. Our results show that transcriptomic and proteomic profiles generated from purified immune cells differ significantly from PBMC. Differential expression analysis for each immune cell type also shows unique transcriptomic and proteomic expression profiles as well as changing biological networks at early time points after vaccination. This cell type-specific information provides a more comprehensive approach to monitor vaccine responses.

Towards a Rigorous Assessment of Systems Biology Models: The DREAM3 Challenges

PubMed Central

Prill, Robert J.; Marbach, Daniel; Saez-Rodriguez, Julio; Sorger, Peter K.; Alexopoulos, Leonidas G.; Xue, Xiaowei; Clarke, Neil D.; Altan-Bonnet, Gregoire; Stolovitzky, Gustavo

2010-01-01

Background Systems biology has embraced computational modeling in response to the quantitative nature and increasing scale of contemporary data sets. The onslaught of data is accelerating as molecular profiling technology evolves. The Dialogue for Reverse Engineering Assessments and Methods (DREAM) is a community effort to catalyze discussion about the design, application, and assessment of systems biology models through annual reverse-engineering challenges. Methodology and Principal Findings We describe our assessments of the four challenges associated with the third DREAM conference which came to be known as the DREAM3 challenges: signaling cascade identification, signaling response prediction, gene expression prediction, and the DREAM3 in silico network challenge. The challenges, based on anonymized data sets, tested participants in network inference and prediction of measurements. Forty teams submitted 413 predicted networks and measurement test sets. Overall, a handful of best-performer teams were identified, while a majority of teams made predictions that were equivalent to random. Counterintuitively, combining the predictions of multiple teams (including the weaker teams) can in some cases improve predictive power beyond that of any single method. Conclusions DREAM provides valuable feedback to practitioners of systems biology modeling. Lessons learned from the predictions of the community provide much-needed context for interpreting claims of efficacy of algorithms described in the scientific literature. PMID:20186320

Knowledge discovery and system biology in molecular medicine: an application on neurodegenerative diseases.

PubMed

Fattore, Matteo; Arrigo, Patrizio

2005-01-01

The possibility to study an organism in terms of system theory has been proposed in the past, but only the advancement of molecular biology techniques allow us to investigate the dynamical properties of a biological system in a more quantitative and rational way than before . These new techniques can gave only the basic level view of an organisms functionality. The comprehension of its dynamical behaviour depends on the possibility to perform a multiple level analysis. Functional genomics has stimulated the interest in the investigation the dynamical behaviour of an organism as a whole. These activities are commonly known as System Biology, and its interests ranges from molecules to organs. One of the more promising applications is the 'disease modeling'. The use of experimental models is a common procedure in pharmacological and clinical researches; today this approach is supported by 'in silico' predictive methods. This investigation can be improved by a combination of experimental and computational tools. The Machine Learning (ML) tools are able to process different heterogeneous data sources, taking into account this peculiarity, they could be fruitfully applied to support a multilevel data processing (molecular, cellular and morphological) that is the prerequisite for the formal model design; these techniques can allow us to extract the knowledge for mathematical model development. The aim of our work is the development and implementation of a system that combines ML and dynamical models simulations. The program is addressed to the virtual analysis of the pathways involved in neurodegenerative diseases. These pathologies are multifactorial diseases and the relevance of the different factors has not yet been well elucidated. This is a very complex task; in order to test the integrative approach our program has been limited to the analysis of the effects of a specific protein, the Cyclin dependent kinase 5 (CDK5) which relies on the induction of neuronal apoptosis. The system has a modular structure centred on a textual knowledge discovery approach. The text mining is the only way to enhance the capability to extract ,from multiple data sources, the information required for the dynamical simulator. The user may access the publically available modules through the following site: http://biocomp.ge.ismac.cnr.it.

Improvement of Vivarium Biodecontamination through Data-acquisition Systems and Automation.

PubMed

Devan, Shakthi Rk; Vasu, Suresh; Mallikarjuna, Yogesha; Ponraj, Ramkumar; Kamath, Gireesh; Poosala, Suresh

2018-03-01

Biodecontamination is important for eliminating pathogens at research animal facilities, thereby preventing contamination within barrier systems. We enhanced our facility's standard biodecontamination method to replace the traditional foggers, and the new system was used effectively after creating bypass ducts in HVAC units so that individual rooms could be isolated. The entire system was controlled by inhouse-developed supervisory control and data-acquisition software that supported multiple cycles of decontamination by equipment, which had different decontamination capacities, operated in parallel, and used different agents, including H2O2 vapor and ClO2 gas. The process was validated according to facility mapping, and effectiveness was assessed by using biologic (Geobacillus stearothermophilus) and chemical indicator strips, which were positioned before decontamination, and by sampling contact plates after the completion of each cycle. The results of biologic indicators showed 6-log reduction in microbial counts after successful decontamination cycles for both agents and found to be compatible with clean-room panels including commonly used materials in vivarium such as racks, cages, trolleys, cage changing stations, biosafety cabinets, refrigerators and other equipment in both procedure and animal rooms. In conclusion, the automated process enabled users to perform effective decontamination through multiple cycles with realtime documentation and provided additional capability to deal with potential outbreaks. Enabling software integration of automation improved quality-control systems in our vivarium.

Methods for biological data integration: perspectives and challenges

PubMed Central

Gligorijević, Vladimir; Pržulj, Nataša

2015-01-01

Rapid technological advances have led to the production of different types of biological data and enabled construction of complex networks with various types of interactions between diverse biological entities. Standard network data analysis methods were shown to be limited in dealing with such heterogeneous networked data and consequently, new methods for integrative data analyses have been proposed. The integrative methods can collectively mine multiple types of biological data and produce more holistic, systems-level biological insights. We survey recent methods for collective mining (integration) of various types of networked biological data. We compare different state-of-the-art methods for data integration and highlight their advantages and disadvantages in addressing important biological problems. We identify the important computational challenges of these methods and provide a general guideline for which methods are suited for specific biological problems, or specific data types. Moreover, we propose that recent non-negative matrix factorization-based approaches may become the integration methodology of choice, as they are well suited and accurate in dealing with heterogeneous data and have many opportunities for further development. PMID:26490630

Multiple Drosophila Tracking System with Heading Direction

PubMed Central

Sirigrivatanawong, Pudith; Arai, Shogo; Thoma, Vladimiros; Hashimoto, Koichi

2017-01-01

Machine vision systems have been widely used for image analysis, especially that which is beyond human ability. In biology, studies of behavior help scientists to understand the relationship between sensory stimuli and animal responses. This typically requires the analysis and quantification of animal locomotion. In our work, we focus on the analysis of the locomotion of the fruit fly Drosophila melanogaster, a widely used model organism in biological research. Our system consists of two components: fly detection and tracking. Our system provides the ability to extract a group of flies as the objects of concern and furthermore determines the heading direction of each fly. As each fly moves, the system states are refined with a Kalman filter to obtain the optimal estimation. For the tracking step, combining information such as position and heading direction with assignment algorithms gives a successful tracking result. The use of heading direction increases the system efficiency when dealing with identity loss and flies swapping situations. The system can also operate with a variety of videos with different light intensities. PMID:28067800

APDS: Autonomous Pathogen Detection System

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

Langlois, R G; Brown, S; Burris, L

An early warning system to counter bioterrorism, the Autonomous Pathogen Detection System (APDS) continuously monitors the environment for the presence of biological pathogens (e.g., anthrax) and once detected, it sounds an alarm much like a smoke detector warns of a fire. Long before September 11, 2001, this system was being developed to protect domestic venues and events including performing arts centers, mass transit systems, major sporting and entertainment events, and other high profile situations in which the public is at risk of becoming a target of bioterrorist attacks. Customizing off-the-shelf components and developing new components, a multidisciplinary team developed APDS,more » a stand-alone system for rapid, continuous monitoring of multiple airborne biological threat agents in the environment. The completely automated APDS samples the air, prepares fluid samples in-line, and performs two orthogonal tests: immunoassay and nucleic acid detection. When compared to competing technologies, APDS is unprecedented in terms of flexibility and system performance.« less

Step by Step: Biology Undergraduates' Problem-Solving Procedures during Multiple-Choice Assessment

ERIC Educational Resources Information Center

Prevost, Luanna B.; Lemons, Paula P.

2016-01-01

This study uses the theoretical framework of domain-specific problem solving to explore the procedures students use to solve multiple-choice problems about biology concepts. We designed several multiple-choice problems and administered them on four exams. We trained students to produce written descriptions of how they solved the problem, and this…

Droplet microfluidics for synthetic biology

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

Gach, PC; Iwai, K; Kim, PW

2017-01-01

© 2017 The Royal Society of Chemistry. Synthetic biology is an interdisciplinary field that aims to engineer biological systems for useful purposes. Organism engineering often requires the optimization of individual genes and/or entire biological pathways (consisting of multiple genes). Advances in DNA sequencing and synthesis have recently begun to enable the possibility of evaluating thousands of gene variants and hundreds of thousands of gene combinations. However, such large-scale optimization experiments remain cost-prohibitive to researchers following traditional molecular biology practices, which are frequently labor-intensive and suffer from poor reproducibility. Liquid handling robotics may reduce labor and improve reproducibility, but are themselvesmore » expensive and thus inaccessible to most researchers. Microfluidic platforms offer a lower entry price point alternative to robotics, and maintain high throughput and reproducibility while further reducing operating costs through diminished reagent volume requirements. Droplet microfluidics have shown exceptional promise for synthetic biology experiments, including DNA assembly, transformation/transfection, culturing, cell sorting, phenotypic assays, artificial cells and genetic circuits.« less

Somatostatin signaling and the regulation of growth and metabolism in fish.

PubMed

Klein, Sarah E; Sheridan, Mark A

2008-05-14

The study of the somatostatins (SS) signaling system in fish has provided important information about the structure, function, and evolution of SSs and their receptors. The SS signaling system elicits widespread biological actions via multiple hormone variants, numerous receptor subtypes, and a variety of signal transduction pathways. SSs alter growth via both direct and indirect actions, including inhibiting growth hormone release at the pituitary, decreasing hepatic GH sensitivity, and lowering plasma IGF-I levels. Metabolism also is significantly influenced by SSs. SSs stimulate the breakdown of energy stores and influences digestion, food intake, nutrient absorption, and food conversion both directly and through the modulation of other hormonal systems. The study of fish, which display a diversity of habitat types and life history forms, reveals that the SS signaling system helps regulate energy partitioning and integrate metabolism with growth and other biological processes.

Advances of Molecular Imaging for Monitoring the Anatomical and Functional Architecture of the Olfactory System.

PubMed

Zhang, Xintong; Bi, Anyao; Gao, Quansheng; Zhang, Shuai; Huang, Kunzhu; Liu, Zhiguo; Gao, Tang; Zeng, Wenbin

2016-01-20

The olfactory system of organisms serves as a genetically and anatomically model for studying how sensory input can be translated into behavior output. Some neurologic diseases are considered to be related to olfactory disturbance, especially Alzheimer's disease, Parkinson's disease, multiple sclerosis, and so forth. However, it is still unclear how the olfactory system affects disease generation processes and olfaction delivery processes. Molecular imaging, a modern multidisciplinary technology, can provide valid tools for the early detection and characterization of diseases, evaluation of treatment, and study of biological processes in living subjects, since molecular imaging applies specific molecular probes as a novel approach to produce special data to study biological processes in cellular and subcellular levels. Recently, molecular imaging plays a key role in studying the activation of olfactory system, thus it could help to prevent or delay some diseases. Herein, we present a comprehensive review on the research progress of the imaging probes for visualizing olfactory system, which is classified on different imaging modalities, including PET, MRI, and optical imaging. Additionally, the probes' design, sensing mechanism, and biological application are discussed. Finally, we provide an outlook for future studies in this field.

Architecture effects on multivalent interactions by polypeptide-based multivalent ligands

NASA Astrophysics Data System (ADS)

Liu, Shuang

Multivalent interactions are characterized by the simultaneous binding between multiple ligands and multiple binding sites, either in solutions or at interfaces. In biological systems, most multivalent interactions occur between protein receptors and carbohydrate ligands through hydrogen-bonding and hydrophobic interactions. Compared with weak affinity binding between one ligand and one binding site, i.e. monovalent interaction, multivalent interactioins provide greater avidity and specificity, and therefore play unique roles in a broad range of biological activities. Moreover, the studies of multivalent interactions are also essential for producing effective inhibitors and effectors of biological processes that could have important therapeutic applications. Synthetic multivalent ligands have been designed to mimic the biological functions of natural multivalent interactions, and various types of scaffolds have been used to display multiple ligands, including small molecules, linear polymers, dendrimers, nanoparticle surfaces, monolayer surfaces and liposomes. Studies have shown that multivalent interactions can be highly affected by various architectural parameters of these multivalent ligands, including ligand identities, valencies, spacing, ligand densities, nature of linker arms, scaffold length and scaffold conformation. Most of these multivalent ligands are chemically synthesized and have limitations of controlling over sequence and conformation, which is a barrier for mimicking ordered and controlled natural biological systems. Therefore, multivalent ligands with precisely controlled architecture are required for improved structure-function relationship studies. Protein engineering methods with subsequent chemical coupling of ligands provide significant advantages of controlling over backbone conformation and functional group placement, and therefore have been used to synthesize recombinant protein-based materials with desired properties similar to natural protein materials, including structural as well as functional proteins. Therefore, polypeptide-based multivalent scaffolds are used to display ligands to assess the contribution of different architectural parameters to the multivalent binding events. In this work, a family of alanine-rich alpha-helical glycopolypeptides was designed and synthesized by a combination of protein engineering and chemical coupling, to display two types of saccharide ligands for two different multivalent binding systems. The valencies, chain length and spacing between adjacent ligands of these multivalent ligands were designed in order to study architecture effects on multivalent interactions. The polypeptides and their glycoconjugates were characterized via various methods, including SDS-PAGE, NMR, HPLC, amino acid analysis (AAA), MALDI, circular dichroism (CD) and GPC. In the first multivalent binding system, cholera toxin B pentamer (CT B5) was chosen to be the protein receptor due to its well-characterized structure, lack of significant steric interference of binding to multiple binding sites, and requirement of only simple monosaccharide as ligands. Galactopyranoside was incorporated into polypeptide scaffolds through amine-carboxylic acid coupling to the side chains of glutamic acid residues. The inhibition and binding to CT B5 of these glycopolypeptide ligands were evaluated by direct enzyme-linked assay (DELA). As a complement method, weak affinity chromatography (WAC) was also used to evaluate glycopolypeptides binding to a CT B5 immobilized column. The architecture effects on CT B 5 inhibition are discussed. In the second system, cell surface receptor L-selectin was targeted by polypeptide-based multivalent ligands containing disulfated galactopyranoside ligands, due to its important roles in various immunological activities. The effects of glycopolypeptide architectural variables L-selectin shedding were evaluated via ELISA-based assays. These polypeptide-based multivalent ligands are suggested to be useful for elucidating architecture effects on multivalent interactions, manipulating multivalent interactions and the subsequent cellular responses in different systems. These materials have great potential applications in therapeutics and could also provide guidelines for design of multivalent ligands for other protein receptors.

Engineering challenges of BioNEMS: the integration of microfluidics, micro- and nanodevices, models and external control for systems biology.

PubMed

Wikswo, J P; Prokop, A; Baudenbacher, F; Cliffel, D; Csukas, B; Velkovsky, M

2006-08-01

Systems biology, i.e. quantitative, postgenomic, postproteomic, dynamic, multiscale physiology, addresses in an integrative, quantitative manner the shockwave of genetic and proteomic information using computer models that may eventually have 10(6) dynamic variables with non-linear interactions. Historically, single biological measurements are made over minutes, suggesting the challenge of specifying 10(6) model parameters. Except for fluorescence and micro-electrode recordings, most cellular measurements have inadequate bandwidth to discern the time course of critical intracellular biochemical events. Micro-array expression profiles of thousands of genes cannot determine quantitative dynamic cellular signalling and metabolic variables. Major gaps must be bridged between the computational vision and experimental reality. The analysis of cellular signalling dynamics and control requires, first, micro- and nano-instruments that measure simultaneously multiple extracellular and intracellular variables with sufficient bandwidth; secondly, the ability to open existing internal control and signalling loops; thirdly, external BioMEMS micro-actuators that provide high bandwidth feedback and externally addressable intracellular nano-actuators; and, fourthly, real-time, closed-loop, single-cell control algorithms. The unravelling of the nested and coupled nature of cellular control loops requires simultaneous recording of multiple single-cell signatures. Externally controlled nano-actuators, needed to effect changes in the biochemical, mechanical and electrical environment both outside and inside the cell, will provide a major impetus for nanoscience.

Bayesian uncertainty analysis for complex systems biology models: emulation, global parameter searches and evaluation of gene functions.

PubMed

Vernon, Ian; Liu, Junli; Goldstein, Michael; Rowe, James; Topping, Jen; Lindsey, Keith

2018-01-02

Many mathematical models have now been employed across every area of systems biology. These models increasingly involve large numbers of unknown parameters, have complex structure which can result in substantial evaluation time relative to the needs of the analysis, and need to be compared to observed data of various forms. The correct analysis of such models usually requires a global parameter search, over a high dimensional parameter space, that incorporates and respects the most important sources of uncertainty. This can be an extremely difficult task, but it is essential for any meaningful inference or prediction to be made about any biological system. It hence represents a fundamental challenge for the whole of systems biology. Bayesian statistical methodology for the uncertainty analysis of complex models is introduced, which is designed to address the high dimensional global parameter search problem. Bayesian emulators that mimic the systems biology model but which are extremely fast to evaluate are embeded within an iterative history match: an efficient method to search high dimensional spaces within a more formal statistical setting, while incorporating major sources of uncertainty. The approach is demonstrated via application to a model of hormonal crosstalk in Arabidopsis root development, which has 32 rate parameters, for which we identify the sets of rate parameter values that lead to acceptable matches between model output and observed trend data. The multiple insights into the model's structure that this analysis provides are discussed. The methodology is applied to a second related model, and the biological consequences of the resulting comparison, including the evaluation of gene functions, are described. Bayesian uncertainty analysis for complex models using both emulators and history matching is shown to be a powerful technique that can greatly aid the study of a large class of systems biology models. It both provides insight into model behaviour and identifies the sets of rate parameters of interest.

ePlant and the 3D data display initiative: integrative systems biology on the world wide web.

PubMed

Fucile, Geoffrey; Di Biase, David; Nahal, Hardeep; La, Garon; Khodabandeh, Shokoufeh; Chen, Yani; Easley, Kante; Christendat, Dinesh; Kelley, Lawrence; Provart, Nicholas J

2011-01-10

Visualization tools for biological data are often limited in their ability to interactively integrate data at multiple scales. These computational tools are also typically limited by two-dimensional displays and programmatic implementations that require separate configurations for each of the user's computing devices and recompilation for functional expansion. Towards overcoming these limitations we have developed "ePlant" (http://bar.utoronto.ca/eplant) - a suite of open-source world wide web-based tools for the visualization of large-scale data sets from the model organism Arabidopsis thaliana. These tools display data spanning multiple biological scales on interactive three-dimensional models. Currently, ePlant consists of the following modules: a sequence conservation explorer that includes homology relationships and single nucleotide polymorphism data, a protein structure model explorer, a molecular interaction network explorer, a gene product subcellular localization explorer, and a gene expression pattern explorer. The ePlant's protein structure explorer module represents experimentally determined and theoretical structures covering >70% of the Arabidopsis proteome. The ePlant framework is accessed entirely through a web browser, and is therefore platform-independent. It can be applied to any model organism. To facilitate the development of three-dimensional displays of biological data on the world wide web we have established the "3D Data Display Initiative" (http://3ddi.org).

Social Disadvantage, Severe Child Abuse, and Biological Profiles in Adulthood.

PubMed

Lee, Chioun; Coe, Christopher L; Ryff, Carol D

2017-09-01

Guided by the stress process model and the life course perspective, we hypothesize: (1) that childhood abuse is concentrated, in terms of type and intensity, among socially disadvantaged individuals, and (2) that experiencing serious abuse contributes to poor biological profiles in multiple body systems in adulthood. Data came from the Biomarker subsample of Midlife in the United States (2004-2006). We used latent class analysis to identify distinct profiles of childhood abuse, each reflecting a combination of type and severity. Results indicate that disadvantaged groups, women, and those from disadvantaged families are at greater risk of experiencing more severe and multiple types of abuse. Those with more severe and multifaceted childhood abuse show greater physiological dysregulation. Childhood abuse experiences partially accounted for the social status differences in physiological profiles. Our findings underscore that differential exposure to serious childhood stressors plays a significant role in gender and class inequalities in adult health.

Cooperativity in Monomeric Enzymes with Single Ligand-Binding Sites

PubMed Central

Porter, Carol M.

2011-01-01

Cooperativity is widespread in biology. It empowers a variety of regulatory mechanisms and impacts both the kinetic and thermodynamic properties of macromolecular systems. Traditionally, cooperativity is viewed as requiring the participation of multiple, spatially distinct binding sites that communicate via ligand-induced structural rearrangements; however, cooperativity requires neither multiple ligand binding events nor multimeric assemblies. An underappreciated manifestation of cooperativity has been observed in the non-Michaelis-Menten kinetic response of certain monomeric enzymes that possess only a single ligand-binding site. In this review, we present an overview of kinetic cooperativity in monomeric enzymes. We discuss the primary mechanisms postulated to give rise to monomeric cooperativity and highlight modern experimental methods that could offer new insights into the nature of this phenomenon. We conclude with an updated list of single subunit enzymes that are suspected of displaying cooperativity, and a discussion of the biological significance of this unique kinetic response. PMID:22137502

Snapshot Hyperspectral Volumetric Microscopy

NASA Astrophysics Data System (ADS)

Wu, Jiamin; Xiong, Bo; Lin, Xing; He, Jijun; Suo, Jinli; Dai, Qionghai

2016-04-01

The comprehensive analysis of biological specimens brings about the demand for capturing the spatial, temporal and spectral dimensions of visual information together. However, such high-dimensional video acquisition faces major challenges in developing large data throughput and effective multiplexing techniques. Here, we report the snapshot hyperspectral volumetric microscopy that computationally reconstructs hyperspectral profiles for high-resolution volumes of ~1000 μm × 1000 μm × 500 μm at video rate by a novel four-dimensional (4D) deconvolution algorithm. We validated the proposed approach with both numerical simulations for quantitative evaluation and various real experimental results on the prototype system. Different applications such as biological component analysis in bright field and spectral unmixing of multiple fluorescence are demonstrated. The experiments on moving fluorescent beads and GFP labelled drosophila larvae indicate the great potential of our method for observing multiple fluorescent markers in dynamic specimens.

Complex, non-monotonic dose-response curves with multiple maxima: Do we (ever) sample densely enough?

PubMed

Cvrčková, Fatima; Luštinec, Jiří; Žárský, Viktor

2015-01-01

We usually expect the dose-response curves of biological responses to quantifiable stimuli to be simple, either monotonic or exhibiting a single maximum or minimum. Deviations are often viewed as experimental noise. However, detailed measurements in plant primary tissue cultures (stem pith explants of kale and tobacco) exposed to varying doses of sucrose, cytokinins (BA or kinetin) or auxins (IAA or NAA) revealed that growth and several biochemical parameters exhibit multiple reproducible, statistically significant maxima over a wide range of exogenous substance concentrations. This results in complex, non-monotonic dose-response curves, reminiscent of previous reports of analogous observations in both metazoan and plant systems responding to diverse pharmacological treatments. These findings suggest the existence of a hitherto neglected class of biological phenomena resulting in dose-response curves exhibiting periodic patterns of maxima and minima, whose causes remain so far uncharacterized, partly due to insufficient sampling frequency used in many studies.

Systems Toxicology: From Basic Research to Risk Assessment

PubMed Central

2014-01-01

Systems Toxicology is the integration of classical toxicology with quantitative analysis of large networks of molecular and functional changes occurring across multiple levels of biological organization. Society demands increasingly close scrutiny of the potential health risks associated with exposure to chemicals present in our everyday life, leading to an increasing need for more predictive and accurate risk-assessment approaches. Developing such approaches requires a detailed mechanistic understanding of the ways in which xenobiotic substances perturb biological systems and lead to adverse outcomes. Thus, Systems Toxicology approaches offer modern strategies for gaining such mechanistic knowledge by combining advanced analytical and computational tools. Furthermore, Systems Toxicology is a means for the identification and application of biomarkers for improved safety assessments. In Systems Toxicology, quantitative systems-wide molecular changes in the context of an exposure are measured, and a causal chain of molecular events linking exposures with adverse outcomes (i.e., functional and apical end points) is deciphered. Mathematical models are then built to describe these processes in a quantitative manner. The integrated data analysis leads to the identification of how biological networks are perturbed by the exposure and enables the development of predictive mathematical models of toxicological processes. This perspective integrates current knowledge regarding bioanalytical approaches, computational analysis, and the potential for improved risk assessment. PMID:24446777

Systems toxicology: from basic research to risk assessment.

PubMed

Sturla, Shana J; Boobis, Alan R; FitzGerald, Rex E; Hoeng, Julia; Kavlock, Robert J; Schirmer, Kristin; Whelan, Maurice; Wilks, Martin F; Peitsch, Manuel C

2014-03-17

Systems Toxicology is the integration of classical toxicology with quantitative analysis of large networks of molecular and functional changes occurring across multiple levels of biological organization. Society demands increasingly close scrutiny of the potential health risks associated with exposure to chemicals present in our everyday life, leading to an increasing need for more predictive and accurate risk-assessment approaches. Developing such approaches requires a detailed mechanistic understanding of the ways in which xenobiotic substances perturb biological systems and lead to adverse outcomes. Thus, Systems Toxicology approaches offer modern strategies for gaining such mechanistic knowledge by combining advanced analytical and computational tools. Furthermore, Systems Toxicology is a means for the identification and application of biomarkers for improved safety assessments. In Systems Toxicology, quantitative systems-wide molecular changes in the context of an exposure are measured, and a causal chain of molecular events linking exposures with adverse outcomes (i.e., functional and apical end points) is deciphered. Mathematical models are then built to describe these processes in a quantitative manner. The integrated data analysis leads to the identification of how biological networks are perturbed by the exposure and enables the development of predictive mathematical models of toxicological processes. This perspective integrates current knowledge regarding bioanalytical approaches, computational analysis, and the potential for improved risk assessment.

Catabolite regulation analysis of Escherichia coli for acetate overflow mechanism and co-consumption of multiple sugars based on systems biology approach using computer simulation.

PubMed

Matsuoka, Yu; Shimizu, Kazuyuki

2013-10-20

It is quite important to understand the basic principle embedded in the main metabolism for the interpretation of the fermentation data. For this, it may be useful to understand the regulation mechanism based on systems biology approach. In the present study, we considered the perturbation analysis together with computer simulation based on the models which include the effects of global regulators on the pathway activation for the main metabolism of Escherichia coli. Main focus is the acetate overflow metabolism and the co-fermentation of multiple carbon sources. The perturbation analysis was first made to understand the nature of the feed-forward loop formed by the activation of Pyk by FDP (F1,6BP), and the feed-back loop formed by the inhibition of Pfk by PEP in the glycolysis. Those together with the effect of transcription factor Cra caused by FDP level affected the glycolysis activity. The PTS (phosphotransferase system) acts as the feed-back system by repressing the glucose uptake rate for the increase in the glucose uptake rate. It was also shown that the increased PTS flux (or glucose consumption rate) causes PEP/PYR ratio to be decreased, and EIIA-P, Cya, cAMP-Crp decreased, where cAMP-Crp in turn repressed TCA cycle and more acetate is formed. This was further verified by the detailed computer simulation. In the case of multiple carbon sources such as glucose and xylose, it was shown that the sequential utilization of carbon sources was observed for wild type, while the co-consumption of multiple carbon sources with slow consumption rates were observed for the ptsG mutant by computer simulation, and this was verified by experiments. Moreover, the effect of a specific gene knockout such as Δpyk on the metabolic characteristics was also investigated based on the computer simulation. Copyright © 2013 Elsevier B.V. All rights reserved.

Maintenance of polygenic sex determination in a fluctuating environment: an individual-based model.

PubMed

Bateman, A W; Anholt, B R

2017-05-01

R. A. Fisher predicted that individuals should invest equally in offspring of both sexes, and that the proportion of males and females produced (the primary sex ratio) should evolve towards 1:1 when unconstrained. For many species, sex determination is dependent on sex chromosomes, creating a strong tendency for balanced sex ratios, but in other cases, multiple autosomal genes interact to determine sex. In such cases, the maintenance of multiple sex-determining alleles at multiple loci and the consequent among-family variability in sex ratios presents a puzzle, as theory predicts that such systems should be unstable. Theory also predicts that environmental influences on sex can complicate outcomes of genetic sex determination, and that population structure may play a role. Tigriopus californicus, a copepod that lives in splash-pool metapopulations and exhibits polygenic and environment-dependent sex determination, presents a test case for relevant theory. We use this species as a model for parameterizing an individual-based simulation to investigate conditions that could maintain polygenic sex determination. We find that metapopulation structure can delay the degradation of polygenic sex determination and that periods of alternating frequency-dependent selection, imposed by seasonal fluctuations in environmental conditions, can maintain polygenic sex determination indefinitely. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.

microRNA regulation of T lymphocyte immunity: modulation of molecular networks responsible for T cell activation, differentiation and development

PubMed Central

Podshivalova, Katie; Salomon, Daniel R.

2014-01-01

MicroRNAs (miRNA) are a class of small non-coding RNAs that constitute an essential and evolutionarily conserved mechanism for post-transcriptional gene regulation. Multiple miRNAs have been described to play key roles in T lymphocyte development, differentiation and function. In this review we highlight the current literature regarding the differential expression of miRNAs in various models of mouse and human T cell biology and emphasize mechanistic understandings of miRNA regulation of thymocyte development, T cell activation, and differentiation into effector and memory subsets. We describe the participation of miRNAs in complex regulatory circuits shaping T cell proteomes in a context-dependent manner. It is striking that some miRNAs regulate multiple processes, while others only appear in limited functional contexts. It is also evident that the expression and function of specific miRNAs can differ between mouse and human systems. Ultimately, it is not always correct to simplify the complex events of T cell biology into a model driven by only one or two master regulator miRNAs. In reality, T cell activation and differentiation involves the expression of multiple miRNAs with many mRNA targets and thus, the true extent of miRNA regulation of T cell biology is likely far more vast than currently appreciated. PMID:24099302

Systems Biology of Recombinant Protein Production in Bacillus megaterium

NASA Astrophysics Data System (ADS)

Biedendieck, Rebekka; Bunk, Boyke; Fürch, Tobias; Franco-Lara, Ezequiel; Jahn, Martina; Jahn, Dieter

Over the last two decades the Gram-positive bacterium Bacillus megaterium was systematically developed to a useful alternative protein production host. Multiple vector systems for high yield intra- and extracellular protein production were constructed. Strong inducible promoters were combined with DNA sequences for optimised ribosome binding sites, various leader peptides for protein export and N- as well as C-terminal affinity tags for affinity chromatographic purification of the desired protein. High cell density cultivation and recombinant protein production were successfully tested. For further system biology based control and optimisation of the production process the genomes of two B. megaterium strains were completely elucidated, DNA arrays designed, proteome, fluxome and metabolome analyses performed and all data integrated using the bioinformatics platform MEGABAC. Now, solid theoretical and experimental bases for primary modeling attempts of the production process are available.

Systems-Level Synthetic Biology for Advanced Biofuel Production

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

Ruffing, Anne; Jensen, Travis J.; Strickland, Lucas Marshall

2015-03-01

Cyanobacteria have been shown to be capable of producing a variety of advanced biofuels; however, product yields remain well below those necessary for large scale production. New genetic tools and high throughput metabolic engineering techniques are needed to optimize cyanobacterial metabolisms for enhanced biofuel production. Towards this goal, this project advances the development of a multiple promoter replacement technique for systems-level optimization of gene expression in a model cyanobacterial host: Synechococcus sp. PCC 7002. To realize this multiple-target approach, key capabilities were developed, including a high throughput detection method for advanced biofuels, enhanced transformation efficiency, and genetic tools for Synechococcusmore » sp. PCC 7002. Moreover, several additional obstacles were identified for realization of this multiple promoter replacement technique. The techniques and tools developed in this project will help to enable future efforts in the advancement of cyanobacterial biofuels.« less

Three-dimensional, automated, real-time video system for tracking limb motion in brain-machine interface studies.

PubMed

Peikon, Ian D; Fitzsimmons, Nathan A; Lebedev, Mikhail A; Nicolelis, Miguel A L

2009-06-15

Collection and analysis of limb kinematic data are essential components of the study of biological motion, including research into biomechanics, kinesiology, neurophysiology and brain-machine interfaces (BMIs). In particular, BMI research requires advanced, real-time systems capable of sampling limb kinematics with minimal contact to the subject's body. To answer this demand, we have developed an automated video tracking system for real-time tracking of multiple body parts in freely behaving primates. The system employs high-contrast markers painted on the animal's joints to continuously track the three-dimensional positions of their limbs during activity. Two-dimensional coordinates captured by each video camera are combined and converted to three-dimensional coordinates using a quadratic fitting algorithm. Real-time operation of the system is accomplished using direct memory access (DMA). The system tracks the markers at a rate of 52 frames per second (fps) in real-time and up to 100fps if video recordings are captured to be later analyzed off-line. The system has been tested in several BMI primate experiments, in which limb position was sampled simultaneously with chronic recordings of the extracellular activity of hundreds of cortical cells. During these recordings, multiple computational models were employed to extract a series of kinematic parameters from neuronal ensemble activity in real-time. The system operated reliably under these experimental conditions and was able to compensate for marker occlusions that occurred during natural movements. We propose that this system could also be extended to applications that include other classes of biological motion.

A Systems' Biology Approach to Study MicroRNA-Mediated Gene Regulatory Networks

PubMed Central

Kunz, Manfred; Vera, Julio; Wolkenhauer, Olaf

2013-01-01

MicroRNAs (miRNAs) are potent effectors in gene regulatory networks where aberrant miRNA expression can contribute to human diseases such as cancer. For a better understanding of the regulatory role of miRNAs in coordinating gene expression, we here present a systems biology approach combining data-driven modeling and model-driven experiments. Such an approach is characterized by an iterative process, including biological data acquisition and integration, network construction, mathematical modeling and experimental validation. To demonstrate the application of this approach, we adopt it to investigate mechanisms of collective repression on p21 by multiple miRNAs. We first construct a p21 regulatory network based on data from the literature and further expand it using algorithms that predict molecular interactions. Based on the network structure, a detailed mechanistic model is established and its parameter values are determined using data. Finally, the calibrated model is used to study the effect of different miRNA expression profiles and cooperative target regulation on p21 expression levels in different biological contexts. PMID:24350286

A biochemical network can control formation of a synthetic material by sensing numerous specific stimuli

NASA Astrophysics Data System (ADS)

Hun Yeon, Ju; Chan, Karen Y. T.; Wong, Ting-Chia; Chan, Kelvin; Sutherland, Michael R.; Ismagilov, Rustem F.; Pryzdial, Edward L. G.; Kastrup, Christian J.

2015-05-01

Developing bio-compatible smart materials that assemble in response to environmental cues requires strategies that can discriminate multiple specific stimuli in a complex milieu. Synthetic materials have yet to achieve this level of sensitivity, which would emulate the highly evolved and tailored reaction networks of complex biological systems. Here we show that the output of a naturally occurring network can be replaced with a synthetic material. Exploiting the blood coagulation system as an exquisite biological sensor, the fibrin clot end-product was replaced with a synthetic material under the biological control of a precisely regulated cross-linking enzyme. The functions of the coagulation network remained intact when the material was incorporated. Clot-like polymerization was induced in indirect response to distinct small molecules, phospholipids, enzymes, cells, viruses, an inorganic solid, a polyphenol, a polysaccharide, and a membrane protein. This strategy demonstrates for the first time that an existing stimulus-responsive biological network can be used to control the formation of a synthetic material by diverse classes of physiological triggers.

Integrative systems control approach for reactivating Kaposi's sarcoma-associated herpesvirus (KSHV) with combinatory drugs

PubMed Central

Sun, Chien-Pin; Usui, Takane; Yu, Fuqu; Al-Shyoukh, Ibrahim; Shamma, Jeff; Sun, Ren; Ho, Chih-Ming

2009-01-01

Cells serve as basic units of life and represent intricate biological molecular systems. The vast number of cellular molecules with their signaling and regulatory circuitries forms an intertwined network. In this network, each pathway interacts non-linearly with others through different intermediates. Thus, the challenge of manipulating cellular functions for desired outcomes, such as cancer eradication and controlling viral infection lies within the integrative system of regulatory circuitries. By using a closed-loop system control scheme, we can efficiently analyze biological signaling networks and manipulate their behavior through multiple stimulations on a collection of pathways. Specifically, we aimed to maximize the reactivation of Kaposi's Sarcoma-associated Herpesvirus (KSHV) in a Primary Effusion Lymphoma cell line. The advantage of this approach is that it is well-suited to study complex integrated systems; it circumvents the need for detailed information of individual signaling components; and it investigates the network as a whole by utilizing key systemic outputs as indicators. PMID:19851479

Integrative systems control approach for reactivating Kaposi's sarcoma-associated herpesvirus (KSHV) with combinatory drugs.

PubMed

Sun, Chien-Pin; Usui, Takane; Yu, Fuqu; Al-Shyoukh, Ibrahim; Shamma, Jeff; Sun, Ren; Ho, Chih-Ming

2009-01-01

Cells serve as basic units of life and represent intricate biological molecular systems. The vast number of cellular molecules with their signaling and regulatory circuitries forms an intertwined network. In this network, each pathway interacts non-linearly with others through different intermediates. Thus, the challenge of manipulating cellular functions for desired outcomes, such as cancer eradication and controlling viral infection lies within the integrative system of regulatory circuitries. By using a closed-loop system control scheme, we can efficiently analyze biological signaling networks and manipulate their behavior through multiple stimulations on a collection of pathways. Specifically, we aimed to maximize the reactivation of Kaposi's Sarcoma-associated Herpesvirus (KSHV) in a Primary Effusion Lymphoma cell line. The advantage of this approach is that it is well-suited to study complex integrated systems; it circumvents the need for detailed information of individual signaling components; and it investigates the network as a whole by utilizing key systemic outputs as indicators.

Single-photon sensitive fast ebCMOS camera system for multiple-target tracking of single fluorophores: application to nano-biophotonics

NASA Astrophysics Data System (ADS)

Cajgfinger, Thomas; Chabanat, Eric; Dominjon, Agnes; Doan, Quang T.; Guerin, Cyrille; Houles, Julien; Barbier, Remi

2011-03-01

Nano-biophotonics applications will benefit from new fluorescent microscopy methods based essentially on super-resolution techniques (beyond the diffraction limit) on large biological structures (membranes) with fast frame rate (1000 Hz). This trend tends to push the photon detectors to the single-photon counting regime and the camera acquisition system to real time dynamic multiple-target tracing. The LUSIPHER prototype presented in this paper aims to give a different approach than those of Electron Multiplied CCD (EMCCD) technology and try to answer to the stringent demands of the new nano-biophotonics imaging techniques. The electron bombarded CMOS (ebCMOS) device has the potential to respond to this challenge, thanks to the linear gain of the accelerating high voltage of the photo-cathode, to the possible ultra fast frame rate of CMOS sensors and to the single-photon sensitivity. We produced a camera system based on a 640 kPixels ebCMOS with its acquisition system. The proof of concept for single-photon based tracking for multiple single-emitters is the main result of this paper.

Petunia, Your Next Supermodel?

PubMed Central

Vandenbussche, Michiel; Chambrier, Pierre; Rodrigues Bento, Suzanne; Morel, Patrice

2016-01-01

Plant biology in general, and plant evo–devo in particular would strongly benefit from a broader range of available model systems. In recent years, technological advances have facilitated the analysis and comparison of individual gene functions in multiple species, representing now a fairly wide taxonomic range of the plant kingdom. Because genes are embedded in gene networks, studying evolution of gene function ultimately should be put in the context of studying the evolution of entire gene networks, since changes in the function of a single gene will normally go together with further changes in its network environment. For this reason, plant comparative biology/evo–devo will require the availability of a defined set of ‘super’ models occupying key taxonomic positions, in which performing gene functional analysis and testing genetic interactions ideally is as straightforward as, e.g., in Arabidopsis. Here we review why petunia has the potential to become one of these future supermodels, as a representative of the Asterid clade. We will first detail its intrinsic qualities as a model system. Next, we highlight how the revolution in sequencing technologies will now finally allows exploitation of the petunia system to its full potential, despite that petunia has already a long history as a model in plant molecular biology and genetics. We conclude with a series of arguments in favor of a more diversified multi-model approach in plant biology, and we point out where the petunia model system may further play a role, based on its biological features and molecular toolkit. PMID:26870078

Finding novel pharmaceuticals in the systems biology era using multiple effective drug targets, phenotypic screening and knowledge of transporters: where drug discovery went wrong and how to fix it.

PubMed

Kell, Douglas B

2013-12-01

Despite the sequencing of the human genome, the rate of innovative and successful drug discovery in the pharmaceutical industry has continued to decrease. Leaving aside regulatory matters, the fundamental and interlinked intellectual issues proposed to be largely responsible for this are: (a) the move from 'function-first' to 'target-first' methods of screening and drug discovery; (b) the belief that successful drugs should and do interact solely with single, individual targets, despite natural evolution's selection for biochemical networks that are robust to individual parameter changes; (c) an over-reliance on the rule-of-5 to constrain biophysical and chemical properties of drug libraries; (d) the general abandoning of natural products that do not obey the rule-of-5; (e) an incorrect belief that drugs diffuse passively into (and presumably out of) cells across the bilayers portions of membranes, according to their lipophilicity; (f) a widespread failure to recognize the overwhelmingly important role of proteinaceous transporters, as well as their expression profiles, in determining drug distribution in and between different tissues and individual patients; and (g) the general failure to use engineering principles to model biology in parallel with performing 'wet' experiments, such that 'what if?' experiments can be performed in silico to assess the likely success of any strategy. These facts/ideas are illustrated with a reasonably extensive literature review. Success in turning round drug discovery consequently requires: (a) decent systems biology models of human biochemical networks; (b) the use of these (iteratively with experiments) to model how drugs need to interact with multiple targets to have substantive effects on the phenotype; (c) the adoption of polypharmacology and/or cocktails of drugs as a desirable goal in itself; (d) the incorporation of drug transporters into systems biology models, en route to full and multiscale systems biology models that incorporate drug absorption, distribution, metabolism and excretion; (e) a return to 'function-first' or phenotypic screening; and (f) novel methods for inferring modes of action by measuring the properties on system variables at all levels of the 'omes. Such a strategy offers the opportunity of achieving a state where we can hope to predict biological processes and the effect of pharmaceutical agents upon them. Consequently, this should both lower attrition rates and raise the rates of discovery of effective drugs substantially. © 2013 The Author Journal compilation © 2013 FEBS.

Chemistry meets biology in colitis-associated carcinogenesis

PubMed Central

Mangerich, Aswin; Dedon, Peter C.; Fox, James G.; Tannenbaum, Steven R.; Wogan, Gerald N.

2015-01-01

The intestine comprises an exceptional venue for a dynamic and complex interplay of numerous chemical and biological processes. Here, multiple chemical and biological systems, including the intestinal tissue itself, its associated immune system, the gut microbiota, xenobiotics, and metabolites meet and interact to form a sophisticated and tightly regulated state of tissue homoeostasis. Disturbance of this homeostasis can cause inflammatory bowel disease (IBD) – a chronic disease of multifactorial etiology that is strongly associated with increased risk for cancer development. This review addresses recent developments in research into chemical and biological mechanisms underlying the etiology of inflammation-induced colon cancer. Beginning with a general overview of reactive chemical species generated during colonic inflammation, the mechanistic interplay between chemical and biological mediators of inflammation, the role of genetic toxicology and microbial pathogenesis in disease development are discussed. When possible, we systematically compare evidence from studies utilizing human IBD patients with experimental investigations in mice. The comparison reveals that many strong pathological and mechanistic correlates exist between mouse models of colitis-associated cancer, and the clinically relevant situation in humans. We also summarize several emerging issues in the field, such as the carcinogenic potential of novel inflammation-related DNA adducts and genotoxic microbial factors, the systemic dimension of inflammation-induced genotoxicity, and the complex role of genome maintenance mechanisms during these processes. Taken together, current evidence points to the induction of genetic and epigenetic alterations by chemical and biological inflammatory stimuli ultimately leading to cancer formation. PMID:23926919

Prospective Elementary Science Teachers' Understanding of Photosynthesis and Cellular Respiration in the Context of Multiple Biological Levels as Nested Systems

ERIC Educational Resources Information Center

Akçay, Süleyman

2017-01-01

In this study, Turkish prospective elementary science teachers' understanding of photosynthesis and cellular respiration has been analysed within the contexts of ecosystem knowledge, organism knowledge and interconnection knowledge (IK). In the analysis, concept maps developed by 74 prospective teachers were used. The study was carried out with…

Pathogenesis-related proteins and peptides as promising tools for engineering plants with multiple stress tolerance.

PubMed

Ali, Sajad; Ganai, Bashir Ahmad; Kamili, Azra N; Bhat, Ajaz Ali; Mir, Zahoor Ahmad; Bhat, Javaid Akhter; Tyagi, Anshika; Islam, Sheikh Tajamul; Mushtaq, Muntazir; Yadav, Prashant; Rawat, Sandhya; Grover, Anita

Pathogenesis-related (PR) proteins and antimicrobial peptides (AMPs) are a group of diverse molecules that are induced by phytopathogens as well as defense related signaling molecules. They are the key components of plant innate immune system especially systemic acquired resistance (SAR), and are widely used as diagnostic molecular markers of defense signaling pathways. Although, PR proteins and peptides have been isolated much before but their biological function remains largely enigmatic despite the availability of new scientific tools. The earlier studies have demonstrated that PR genes provide enhanced resistance against both biotic and abiotic stresses, which make them one of the most promising candidates for developing multiple stress tolerant crop varieties. In this regard, plant genetic engineering technology is widely accepted as one of the most fascinating approach to develop the disease resistant transgenic crops using different antimicrobial genes like PR genes. Overexpression of PR genes (chitinase, glucanase, thaumatin, defensin and thionin) individually or in combination have greatly uplifted the level of defense response in plants against a wide range of pathogens. However, the detailed knowledge of signaling pathways that regulates the expression of these versatile proteins is critical for improving crop plants to multiple stresses, which is the future theme of plant stress biology. Hence, this review provides an overall overview on the PR proteins like their classification, role in multiple stresses (biotic and abiotic) as well as in various plant defense signaling cascades. We also highlight the success and snags of transgenic plants expressing PR proteins and peptides. Copyright © 2018 Elsevier GmbH. All rights reserved.

Examining the Effect of Multiple Writing Tasks on Year 10 Biology Students' Understandings of Cell and Molecular Biology Concepts

ERIC Educational Resources Information Center

Hand, Brian; Hohenshell, Liesl; Prain, Vaughan

2007-01-01

This paper reports on a study that examined the cumulative effects on students' learning of science, and perceptions of the role of writing in learning, when the students engaged in multiple writing tasks with planning strategy support. The study was conducted with Year 10 biology students who completed two consecutive units on Cells and Molecular…

Integration of ecological-biological thresholds in conservation decision making.

PubMed

Mavrommati, Georgia; Bithas, Kostas; Borsuk, Mark E; Howarth, Richard B

2016-12-01

In the Anthropocene, coupled human and natural systems dominate and only a few natural systems remain relatively unaffected by human influence. On the one hand, conservation criteria based on areas of minimal human impact are not relevant to much of the biosphere. On the other hand, conservation criteria based on economic factors are problematic with respect to their ability to arrive at operational indicators of well-being that can be applied in practice over multiple generations. Coupled human and natural systems are subject to economic development which, under current management structures, tends to affect natural systems and cross planetary boundaries. Hence, designing and applying conservation criteria applicable in real-world systems where human and natural systems need to interact and sustainably coexist is essential. By recognizing the criticality of satisfying basic needs as well as the great uncertainty over the needs and preferences of future generations, we sought to incorporate conservation criteria based on minimal human impact into economic evaluation. These criteria require the conservation of environmental conditions such that the opportunity for intergenerational welfare optimization is maintained. Toward this end, we propose the integration of ecological-biological thresholds into decision making and use as an example the planetary-boundaries approach. Both conservation scientists and economists must be involved in defining operational ecological-biological thresholds that can be incorporated into economic thinking and reflect the objectives of conservation, sustainability, and intergenerational welfare optimization. © 2016 Society for Conservation Biology.

How animal models inform child and adolescent psychiatry.

PubMed

Stevens, Hanna E; Vaccarino, Flora M

2015-05-01

Every available approach should be used to advance the field of child and adolescent psychiatry. Biological systems are important for the behavioral problems of children. Close examination of nonhuman animals and the biology and behavior that they share with humans is an approach that must be used to advance the clinical work of child psychiatry. We review here how model systems are used to contribute to significant insights into childhood psychiatric disorders. Model systems have not only demonstrated causality of risk factors for psychiatric pathophysiology, but have also allowed child psychiatrists to think in different ways about risks for psychiatric disorders and multiple levels that might be the basis of recovery and prevention. We present examples of how animal systems are used to benefit child psychiatry, including through environmental, genetic, and acute biological manipulations. Animal model work has been essential in our current thinking about childhood disorders, including the importance of dose and timing of risk factors, specific features of risk factors that are significant, neurochemistry involved in brain functioning, molecular components of brain development, and the importance of cellular processes previously neglected in psychiatric theories. Animal models have clear advantages and disadvantages that must be considered for these systems to be useful. Coupled with increasingly sophisticated methods for investigating human behavior and biology, animal model systems will continue to make essential contributions to our field. Copyright © 2015 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

BiologicalNetworks 2.0 - an integrative view of genome biology data

PubMed Central

2010-01-01

Background A significant problem in the study of mechanisms of an organism's development is the elucidation of interrelated factors which are making an impact on the different levels of the organism, such as genes, biological molecules, cells, and cell systems. Numerous sources of heterogeneous data which exist for these subsystems are still not integrated sufficiently enough to give researchers a straightforward opportunity to analyze them together in the same frame of study. Systematic application of data integration methods is also hampered by a multitude of such factors as the orthogonal nature of the integrated data and naming problems. Results Here we report on a new version of BiologicalNetworks, a research environment for the integral visualization and analysis of heterogeneous biological data. BiologicalNetworks can be queried for properties of thousands of different types of biological entities (genes/proteins, promoters, COGs, pathways, binding sites, and other) and their relations (interactions, co-expression, co-citations, and other). The system includes the build-pathways infrastructure for molecular interactions/relations and module discovery in high-throughput experiments. Also implemented in BiologicalNetworks are the Integrated Genome Viewer and Comparative Genomics Browser applications, which allow for the search and analysis of gene regulatory regions and their conservation in multiple species in conjunction with molecular pathways/networks, experimental data and functional annotations. Conclusions The new release of BiologicalNetworks together with its back-end database introduces extensive functionality for a more efficient integrated multi-level analysis of microarray, sequence, regulatory, and other data. BiologicalNetworks is freely available at http://www.biologicalnetworks.org. PMID:21190573

NASA Human Research Program Space Radiation Program Element

NASA Technical Reports Server (NTRS)

Chappell, Lori; Huff, Janice; Patel, Janapriya; Wang, Minli; Hu, Shaowwen; Kidane, Yared; Myung-Hee, Kim; Li, Yongfeng; Nounu, Hatem; Plante, Ianik;

Social relationships and their biological correlates: Coronary Artery Risk Development in Young Adults (CARDIA) study.

PubMed

Seeman, Teresa E; Gruenewald, Tara L; Cohen, Sheldon; Williams, David R; Matthews, Karen A

2014-05-01

Analyses test the hypothesis that aspects of social relationships (quantity of ties, social support and social strain) are associated with differences in levels of biological risk across multiple major physiological regulatory systems and consequently overall multi-systems risk (i.e., allostatic load [AL]). Data are from the Coronary Artery Risk Development in Young Adults (CARDIA) study--a bi-ethnic, prospective, multi-center epidemiological study, initiated in 1985-1986 to track the development of cardiovascular risk in young adulthood (N=5115). At the year 15 follow-up when participants were between 32 and 45 years of age, additional social and biological data were collected; biological data used to assess AL were collected at the Oakland, CA and Chicago, IL sites (N=844). Social strains were most strongly and positively related to overall AL (Cohen's d=.79 for highest vs. lowest quartile), and to each of its component biological subsystems, independent of social ties and support as well as sociodemographics and health behaviors. Social ties and emotional support were also negatively related to AL (Cohen's d=.33 and d=.44 for lowest vs. highest quartiles of ties and support, respectively) though controls for social strains reduced these associations to non-significance. Social support and social strain were more strongly related to overall AL than to any of its component subscales while social ties were less strongly related to AL and to its component subscales. There was no evidence that effects differed by sex, age or ethnicity. Findings focus attention on the particularly strong relationship between social strains and profiles of biological risk and support the cumulative impact of social factors on biological risks, showing larger effects for cumulative AL than for any of the individual biological systems. Copyright © 2014 Elsevier Ltd. All rights reserved.

Microscale Symmetrical Electroporator Array as a Versatile Molecular Delivery System

NASA Astrophysics Data System (ADS)

Ouyang, Mengxing; Hill, Winfield; Lee, Jung Hyun; Hur, Soojung Claire

2017-03-01

Successful developments of new therapeutic strategies often rely on the ability to deliver exogenous molecules into cytosol. We have developed a versatile on-chip vortex-assisted electroporation system, engineered to conduct sequential intracellular delivery of multiple molecules into various cell types at low voltage in a dosage-controlled manner. Micro-patterned planar electrodes permit substantial reduction in operational voltages and seamless integration with an existing microfluidic technology. Equipped with real-time process visualization functionality, the system enables on-chip optimization of electroporation parameters for cells with varying properties. Moreover, the system’s dosage control and multi-molecular delivery capabilities facilitate intracellular delivery of various molecules as a single agent or in combination and its utility in biological research has been demonstrated by conducting RNA interference assays. We envision the system to be a powerful tool, aiding a wide range of applications, requiring single-cell level co-administrations of multiple molecules with controlled dosages.

Connectivity as a multiple: In, with and as "nature".

PubMed

Hodgetts, Timothy

2018-03-01

Connectivity is a central concept in contemporary geographies of nature, but the concept is often understood and utilised in plural ways. This is problematic because of the separation, rather than the confusion, of these different approaches. While the various understandings of connectivity are rarely considered as working together, the connections between them have significant implications. This paper thus proposes re-thinking connectivity as a "multiple". It develops a taxonomy of existing connectivity concepts from the fields of biogeography and landscape ecology, conservation biology, socio-economic systems theory, political ecology and more-than-human geography. It then considers how these various understandings might be re-thought not as separate concerns, but (following Annemarie Mol) as "more than one, but less than many". The implications of using the connectivity multiple as an analytic for understanding conservation practices are demonstrated through considering the creation of wildlife corridors in conservation practice. The multiple does not just serve to highlight the practical and theoretical linkages between ecological theories, social inequities and affectual relationships in more-than-human worlds. It is also suggestive of a normative approach to environmental management that does not give temporal priority to biological theories, but considers these as always already situated in these social, often unequal, always more-than-human ecologies.

Reconstruction of apparent orthotropic conductivity tensor image using magnetic resonance electrical impedance tomography

NASA Astrophysics Data System (ADS)

Sajib, Saurav Z. K.; Kim, Ji Eun; Jeong, Woo Chul; Kim, Hyung Joong; Kwon, Oh In; Woo, Eung Je

2015-03-01

Magnetic resonance electrical impedance tomography visualizes current density and/or conductivity distributions inside an electrically conductive object. Injecting currents into the imaging object along at least two different directions, induced magnetic flux density data can be measured using a magnetic resonance imaging scanner. Without rotating the object inside the scanner, we can measure only one component of the magnetic flux density denoted as Bz. Since the biological tissues such as skeletal muscle and brain white matter show strong anisotropic properties, the reconstruction of anisotropic conductivity tensor is indispensable for the accurate observations in the biological systems. In this paper, we propose a direct method to reconstruct an axial apparent orthotropic conductivity tensor by using multiple Bz data subject to multiple injection currents. To investigate the anisotropic conductivity properties, we first recover the internal current density from the measured Bz data. From the recovered internal current density and the curl-free condition of the electric field, we derive an over-determined matrix system for determining the internal absolute orthotropic conductivity tensor. The over-determined matrix system is designed to use a combination of two loops around each pixel. Numerical simulations and phantom experimental results demonstrate that the proposed algorithm stably determines the orthotropic conductivity tensor.

When one model is not enough: combining epistemic tools in systems biology.

PubMed

Green, Sara

2013-06-01

In recent years, the philosophical focus of the modeling literature has shifted from descriptions of general properties of models to an interest in different model functions. It has been argued that the diversity of models and their correspondingly different epistemic goals are important for developing intelligible scientific theories (Leonelli, 2007; Levins, 2006). However, more knowledge is needed on how a combination of different epistemic means can generate and stabilize new entities in science. This paper will draw on Rheinberger's practice-oriented account of knowledge production. The conceptual repertoire of Rheinberger's historical epistemology offers important insights for an analysis of the modelling practice. I illustrate this with a case study on network modeling in systems biology where engineering approaches are applied to the study of biological systems. I shall argue that the use of multiple representational means is an essential part of the dynamic of knowledge generation. It is because of-rather than in spite of-the diversity of constraints of different models that the interlocking use of different epistemic means creates a potential for knowledge production. Copyright © 2013 Elsevier Ltd. All rights reserved.

Multi -omics and metabolic modelling pipelines: challenges and tools for systems microbiology.

PubMed

Fondi, Marco; Liò, Pietro

2015-02-01

Integrated -omics approaches are quickly spreading across microbiology research labs, leading to (i) the possibility of detecting previously hidden features of microbial cells like multi-scale spatial organization and (ii) tracing molecular components across multiple cellular functional states. This promises to reduce the knowledge gap between genotype and phenotype and poses new challenges for computational microbiologists. We underline how the capability to unravel the complexity of microbial life will strongly depend on the integration of the huge and diverse amount of information that can be derived today from -omics experiments. In this work, we present opportunities and challenges of multi -omics data integration in current systems biology pipelines. We here discuss which layers of biological information are important for biotechnological and clinical purposes, with a special focus on bacterial metabolism and modelling procedures. A general review of the most recent computational tools for performing large-scale datasets integration is also presented, together with a possible framework to guide the design of systems biology experiments by microbiologists. Copyright © 2015. Published by Elsevier GmbH.

Molecular Cooperativity Governs Diverse and Monoallelic Olfactory Receptor Expression

NASA Astrophysics Data System (ADS)

Xing, Jianhua; Tian, Xiaojun; Zhang, Hang; Sannerud, Jens

Multiple-objective optimization is common in biological systems. In the mammalian olfactory system, each sensory neuron stochastically expresses only one out of up to thousands of olfactory receptor (OR) gene alleles; at organism level the types of expressed ORs need to be maximized. The molecular mechanism of this Nobel-Prize winning puzzle remains unresolved after decades of extensive studies. Existing models focus only on monoallele activation, and cannot explain recent observations in mutants, especially the reduced global diversity of expressed ORs in G9a/GLP knockouts. In this work we integrated existing information on OR expression, and proposed an evolutionarily optimized three-layer regulation mechanism, which includes zonal segregation, epigenetic and enhancer competition coupled to a negative feedback loop. This model not only recapitulates monoallelic OR expression, but also elucidates how the olfactory system maximizes and maintains the diversity of OR expression. The model is validated by several experimental results, and particularly underscores cooperativity and synergy as a general design principle of multi-objective optimization in biology. The work is supported by the NIGMS/DMS Mathematical Biology program.

Cancer systems biology in the genome sequencing era: part 1, dissecting and modeling of tumor clones and their networks.

PubMed

Wang, Edwin; Zou, Jinfeng; Zaman, Naif; Beitel, Lenore K; Trifiro, Mark; Paliouras, Miltiadis

2013-08-01

Recent tumor genome sequencing confirmed that one tumor often consists of multiple cell subpopulations (clones) which bear different, but related, genetic profiles such as mutation and copy number variation profiles. Thus far, one tumor has been viewed as a whole entity in cancer functional studies. With the advances of genome sequencing and computational analysis, we are able to quantify and computationally dissect clones from tumors, and then conduct clone-based analysis. Emerging technologies such as single-cell genome sequencing and RNA-Seq could profile tumor clones. Thus, we should reconsider how to conduct cancer systems biology studies in the genome sequencing era. We will outline new directions for conducting cancer systems biology by considering that genome sequencing technology can be used for dissecting, quantifying and genetically characterizing clones from tumors. Topics discussed in Part 1 of this review include computationally quantifying of tumor subpopulations; clone-based network modeling, cancer hallmark-based networks and their high-order rewiring principles and the principles of cell survival networks of fast-growing clones. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

Translational systems biology: introduction of an engineering approach to the pathophysiology of the burn patient.

PubMed

An, Gary; Faeder, James; Vodovotz, Yoram

2008-01-01

The pathophysiology of the burn patient manifests the full spectrum of the complexity of the inflammatory response. In the acute phase, inflammation may have negative effects via capillary leak, the propagation of inhalation injury, and development of multiple organ failure. Attempts to mediate these processes remain a central subject of burn care research. Conversely, inflammation is a necessary prologue and component in the later stage processes of wound healing. Despite the volume of information concerning the cellular and molecular processes involved in inflammation, there exists a significant gap between the knowledge of mechanistic pathophysiology and the development of effective clinical therapeutic regimens. Translational systems biology (TSB) is the application of dynamic mathematical modeling and certain engineering principles to biological systems to integrate mechanism with phenomenon and, importantly, to revise clinical practice. This study will review the existing applications of TSB in the areas of inflammation and wound healing, relate them to specific areas of interest to the burn community, and present an integrated framework that links TSB with traditional burn research.

Diversified Control Paths: A Significant Way Disease Genes Perturb the Human Regulatory Network

PubMed Central

Wang, Bingbo; Gao, Lin; Zhang, Qingfang; Li, Aimin; Deng, Yue; Guo, Xingli

2015-01-01

Background The complexity of biological systems motivates us to use the underlying networks to provide deep understanding of disease etiology and the human diseases are viewed as perturbations of dynamic properties of networks. Control theory that deals with dynamic systems has been successfully used to capture systems-level knowledge in large amount of quantitative biological interactions. But from the perspective of system control, the ways by which multiple genetic factors jointly perturb a disease phenotype still remain. Results In this work, we combine tools from control theory and network science to address the diversified control paths in complex networks. Then the ways by which the disease genes perturb biological systems are identified and quantified by the control paths in a human regulatory network. Furthermore, as an application, prioritization of candidate genes is presented by use of control path analysis and gene ontology annotation for definition of similarities. We use leave-one-out cross-validation to evaluate the ability of finding the gene-disease relationship. Results have shown compatible performance with previous sophisticated works, especially in directed systems. Conclusions Our results inspire a deeper understanding of molecular mechanisms that drive pathological processes. Diversified control paths offer a basis for integrated intervention techniques which will ultimately lead to the development of novel therapeutic strategies. PMID:26284649

Characteristic Variations and Similarities in Biochemical, Molecular, and Functional Properties of Glyoxalases across Prokaryotes and Eukaryotes

PubMed Central

Kaur, Charanpreet; Sharma, Shweta; Hasan, Mohammad Rokebul; Pareek, Ashwani; Singla-Pareek, Sneh L.; Sopory, Sudhir K.

2017-01-01

The glyoxalase system is the ubiquitous pathway for the detoxification of methylglyoxal (MG) in the biological systems. It comprises two enzymes, glyoxalase I (GLYI) and glyoxalase II (GLYII), which act sequentially to convert MG into d-lactate, thereby helping living systems get rid of this otherwise cytotoxic byproduct of metabolism. In addition, a glutathione-independent GLYIII enzyme activity also exists in the biological systems that can directly convert MG to d-lactate. Humans and Escherichia coli possess a single copy of GLYI (encoding either the Ni- or Zn-dependent form) and GLYII genes, which through MG detoxification provide protection against various pathological and disease conditions. By contrast, the plant genome possesses multiple GLYI and GLYII genes with a role in abiotic stress tolerance. Plants possess both Ni2+- and Zn2+-dependent forms of GLYI, and studies on plant glyoxalases reveal the various unique features of these enzymes distinguishing them from prokaryotic and other eukaryotic glyoxalases. Through this review, we provide an overview of the plant glyoxalase family along with a comparative analysis of glyoxalases across various species, highlighting similarities as well as differences in the biochemical, molecular, and physiological properties of these enzymes. We believe that the evolution of multiple glyoxalases isoforms in plants is an important component of their robust defense strategies. PMID:28358304

High affinity ligands from in vitro selection: Complex targets

PubMed Central

Morris, Kevin N.; Jensen, Kirk B.; Julin, Carol M.; Weil, Michael; Gold, Larry

1998-01-01

Human red blood cell membranes were used as a model system to determine if the systematic evolution of ligands by exponential enrichment (SELEX) methodology, an in vitro protocol for isolating high-affinity oligonucleotides that bind specifically to virtually any single protein, could be used with a complex mixture of potential targets. Ligands to multiple targets were generated simultaneously during the selection process, and the binding affinities of these ligands for their targets are comparable to those found in similar experiments against pure targets. A secondary selection scheme, deconvolution-SELEX, facilitates rapid isolation of the ligands to targets of special interest within the mixture. SELEX provides high-affinity compounds for multiple targets in a mixture and might allow a means for dissecting complex biological systems. PMID:9501188

Investigating dye performance and crosstalk in fluorescence enabled bioimaging using a model system

PubMed Central

Arppe, Riikka; Carro-Temboury, Miguel R.; Hempel, Casper; Vosch, Tom

2017-01-01

Detailed imaging of biological structures, often smaller than the diffraction limit, is possible in fluorescence microscopy due to the molecular size and photophysical properties of fluorescent probes. Advances in hardware and multiple providers of high-end bioimaging makes comparing images between studies and between research groups very difficult. Therefore, we suggest a model system to benchmark instrumentation, methods and staining procedures. The system we introduce is based on doped zeolites in stained polyvinyl alcohol (PVA) films: a highly accessible model system which has the properties needed to act as a benchmark in bioimaging experiments. Rather than comparing molecular probes and imaging methods in complicated biological systems, we demonstrate that the model system can emulate this complexity and can be used to probe the effect of concentration, brightness, and cross-talk of fluorophores on the detected fluorescence signal. The described model system comprises of lanthanide (III) ion doped Linde Type A zeolites dispersed in a PVA film stained with fluorophores. We tested: F18, MitoTracker Red and ATTO647N. This model system allowed comparing performance of the fluorophores in experimental conditions. Importantly, we here report considerable cross-talk of the dyes when exchanging excitation and emission settings. Additionally, bleaching was quantified. The proposed model makes it possible to test and benchmark staining procedures before these dyes are applied to more complex biological systems. PMID:29176775

Spontaneous switching of frequency-locking by periodic stimulus in oscillators of plasmodium of the true slime mold.

PubMed

Takamatsu, A; Yamamoto, T; Fujii, T

2004-01-01

Microfabrication technique was used to construct a model system with a living cell of plasmodium of the true slime mold, Physarum polycephalum, a living coupled oscillator system. Its parameters can be systematically controlled as in computer simulations, so that results are directly comparable to those of general mathematical models. As the first step, we investigated responses in oscillatory cells, the oscillators of the plasmodium, to periodic stimuli by temperature changes to elucidate characteristics of the cells as nonlinear systems whose internal dynamics are unknown because of their complexity. We observed that the forced oscillator of the plasmodium show 1:1, 2:1, 3:1 frequency locking inside so-called Arnold tongues regions as well as in other nonlinear systems such as chemical systems and other biological systems. In addition, we found spontaneous switching behavior from certain frequency locking states to other states, even under certain fixed parameters. This technique can be applied to more complex systems with multiple elements, such as coupled oscillator systems, and would be useful to investigate complicated phenomena in biological systems such as information processing.

Morphomics: An integral part of systems biology of the human placenta.

PubMed

Mayhew, T M

2015-04-01

The placenta is a transient organ the functioning of which has health consequences far beyond the embryo/fetus. Understanding the biology of any system (organ, organism, single cell, etc) requires a comprehensive and inclusive approach which embraces all the biomedical disciplines and 'omic' technologies and then integrates information obtained from all of them. Among the latest 'omics' is morphomics. The terms morphome and morphomics have been applied incoherently in biology and biomedicine but, recently, they have been given clear and widescale definitions. Morphomics is placed in the context of other 'omics' and its pertinent technologies and tools for sampling and quantitation are reviewed. Emphasis is accorded to the importance of random sampling principles in systems biology and the value of combining 3D quantification with alternative imaging techniques to advance knowledge and understanding of the human placental morphome. By analogy to other 'omes', the morphome is the totality of morphological features within a system and morphomics is the systematic study of those structures. Information about structure is required at multiple levels of resolution in order to understand better the processes by which a given system alters with time, experimental treatment or environmental insult. Therefore, morphomics research includes all imaging techniques at all levels of achievable resolution from gross anatomy and medical imaging, via optical and electron microscopy, to molecular characterisation. Quantification is an important element of all 'omics' studies and, because biological systems exist and operate in 3-dimensional (3D) space, precise descriptions of form, content and spatial relationships require the quantification of structure in 3D. These considerations are relevant to future study contributions to the Human Placenta Project. Copyright © 2015 Elsevier Ltd. All rights reserved.

Vasoregression: A Shared Vascular Pathology Underlying Macrovascular And Microvascular Pathologies?

PubMed Central

Gupta, Akanksha

2015-01-01

Abstract Vasoregression is a common phenomenon underlying physiological vessel development as well as pathological microvascular diseases leading to peripheral neuropathy, nephropathy, and vascular oculopathies. In this review, we describe the hallmarks and pathways of vasoregression. We argue here that there is a parallel between characteristic features of vasoregression in the ocular microvessels and atherosclerosis in the larger vessels. Shared molecular pathways and molecular effectors in the two conditions are outlined, thus highlighting the possible systemic causes of local vascular diseases. Our review gives us a system-wide insight into factors leading to multiple synchronous vascular diseases. Because shared molecular pathways might usefully address the diagnostic and therapeutic needs of multiple common complex diseases, the literature analysis presented here is of broad interest to readership in integrative biology, rational drug development and systems medicine. PMID:26669709

Microarray profiling analysis uncovers common molecular mechanisms of rubella virus, human cytomegalovirus, and herpes simplex virus type 2 infections in ECV304 cells.

PubMed

Mo, X; Xu, L; Yang, Q; Feng, H; Peng, J; Zhang, Y; Yuan, W; Wang, Y; Li, Y; Deng, Y; Wan, Y; Chen, Z; Li, F; Wu, X

2011-08-01

To study the common molecular mechanisms of various viruses infections that might result in congential cardiovascular diseases in perinatal period, changes in mRNA expression levels of ECV304 cells infected by rubella virus (RUBV), human cytomegalovirus (HCMV), and herpes simplex virus type 2 (HSV-2) were analyzed using a microarray system representing 18,716 human genes. 99 genes were found to exhibit differential expression (80 up-regulated and 19 down-regulated). Biological process analysis showed that 33 signaling pathways including 22 genes were relevant significantly to RV, HCMV and HSV-II infections. Of these 33 biological processes, 28 belong to one-gene biological processes and 5 belong to multiple-gene biological processes. Gene annotation indicated that the 5 multiple-gene biological processes including regulation of cell growth, collagen fibril organization, mRNA transport, cell adhesion and regulation of cell shape, and seven down- or up-regulated genes [CRIM1 (cysteine rich transmembrane BMP regulator 1), WISP2 (WNT1 inducible signaling pathway protein 2), COL12A1 (collagen, type XII, alpha 1), COL11A2 (collagen, type XI, alpha 2), CNTN5 (contactin 5), DDR1 (discoidin domain receptor tyrosine kinase 1), VEGF (vascular endothelial growth factor precursor)], are significantly correlated to RUBV, HCMV and HSV-2 infections in ECV304 cells. The results obtained in this study suggested the common molecular mechanisms of viruses infections that might result in congential cardiovascular diseases.

Sphere based fluid systems

NASA Technical Reports Server (NTRS)

Elleman, Daniel D. (Inventor); Wang, Taylor G. (Inventor)

1989-01-01

Systems are described for using multiple closely-packed spheres. In one system for passing fluid, a multiplicity of spheres lie within a container, with all of the spheres having the same outside diameter and with the spheres being closely nested in one another to create multiple interstitial passages of a known size and configuration and smooth walls. The container has an inlet and outlet for passing fluid through the interstitial passages formed between the nested spheres. The small interstitial passages can be used to filter out material, especially biological material such as cells in a fluid, where the cells can be easily destroyed if passed across sharp edges. The outer surface of the spheres can contain a material that absorbs a constitutent in the flowing fluid, such as a particular contamination gas, or can contain a catalyst to chemically react the fluid passing therethrough, the use of multiple small spheres assuring a large area of contact of these surfaces of the spheres with the fluid. In a system for storing and releasing a fluid such as hydrogen as a fuel, the spheres can include a hollow shell containing the fluid to be stored, and located within a compressable container that can be compressed to break the shells and release the stored fluid.

Application of shift-and-add algorithms for imaging objects within biological media

NASA Astrophysics Data System (ADS)

Aizert, Avishai; Moshe, Tomer; Abookasis, David

2017-01-01

The Shift-and-Add (SAA) technique is a simple mathematical operation developed to reconstruct, at high spatial resolution, atmospherically degraded solar images obtained from stellar speckle interferometry systems. This method shifts and assembles individual degraded short-exposure images into a single average image with significantly improved contrast and detail. Since the inhomogeneous refractive indices of biological tissue causes light scattering similar to that induced by optical turbulence in the atmospheric layers, we assume that SAA methods can be successfully implemented to reconstruct the image of an object within a scattering biological medium. To test this hypothesis, five SAA algorithms were evaluated for reconstructing images acquired from multiple viewpoints. After successfully retrieving the hidden object's shape, quantitative image quality metrics were derived, enabling comparison of imaging error across a spectrum of layer thicknesses, demonstrating the relative efficacy of each SAA algorithm for biological imaging.

Systems biology as a conceptual framework for research in family medicine; use in predicting response to influenza vaccination.

PubMed

Majnarić-Trtica, Ljiljana; Vitale, Branko

2011-10-01

To introduce systems biology as a conceptual framework for research in family medicine, based on empirical data from a case study on the prediction of influenza vaccination outcomes. This concept is primarily oriented towards planning preventive interventions and includes systematic data recording, a multi-step research protocol and predictive modelling. Factors known to affect responses to influenza vaccination include older age, past exposure to influenza viruses, and chronic diseases; however, constructing useful prediction models remains a challenge, because of the need to identify health parameters that are appropriate for general use in modelling patients' responses. The sample consisted of 93 patients aged 50-89 years (median 69), with multiple medical conditions, who were vaccinated against influenza. Literature searches identified potentially predictive health-related parameters, including age, gender, diagnoses of the main chronic ageing diseases, anthropometric measures, and haematological and biochemical tests. By applying data mining algorithms, patterns were identified in the data set. Candidate health parameters, selected in this way, were then combined with information on past influenza virus exposure to build the prediction model using logistic regression. A highly significant prediction model was obtained, indicating that by using a systems biology approach it is possible to answer unresolved complex medical uncertainties. Adopting this systems biology approach can be expected to be useful in identifying the most appropriate target groups for other preventive programmes.

PathCase-SB architecture and database design

PubMed Central

2011-01-01

Background Integration of metabolic pathways resources and regulatory metabolic network models, and deploying new tools on the integrated platform can help perform more effective and more efficient systems biology research on understanding the regulation in metabolic networks. Therefore, the tasks of (a) integrating under a single database environment regulatory metabolic networks and existing models, and (b) building tools to help with modeling and analysis are desirable and intellectually challenging computational tasks. Description PathCase Systems Biology (PathCase-SB) is built and released. The PathCase-SB database provides data and API for multiple user interfaces and software tools. The current PathCase-SB system provides a database-enabled framework and web-based computational tools towards facilitating the development of kinetic models for biological systems. PathCase-SB aims to integrate data of selected biological data sources on the web (currently, BioModels database and KEGG), and to provide more powerful and/or new capabilities via the new web-based integrative framework. This paper describes architecture and database design issues encountered in PathCase-SB's design and implementation, and presents the current design of PathCase-SB's architecture and database. Conclusions PathCase-SB architecture and database provide a highly extensible and scalable environment with easy and fast (real-time) access to the data in the database. PathCase-SB itself is already being used by researchers across the world. PMID:22070889

Insect-gene-activity detection system for chemical and biological warfare agents and toxic industrial chemicals

NASA Astrophysics Data System (ADS)

Mackie, Ryan S.; Schilling, Amanda S.; Lopez, Arturo M.; Rayms-Keller, Alfredo

2002-02-01

Detection of multiple chemical and biological weapons (CBW) agents and/or complex mixtures of toxic industrial chemicals (TIC) is imperative for both the commercial and military sectors. In a military scenario, a multi-CBW attack would create confusion, thereby delaying decontamination and therapeutic efforts. In the commercial sector, polluted sites invariably contain a mixture of TIC. Novel detection systems capable of detecting CBW and TIC are sorely needed. While it may be impossible to build a detector capable of discriminating all the possible combinations of CBW, a detection system capable of statistically predicting the most likely composition of a given mixture is within the reach of current emerging technologies. Aquatic insect-gene activity may prove to be a sensitive, discriminating, and elegant paradigm for the detection of CBW and TIC. We propose to systematically establish the expression patterns of selected protein markers in insects exposed to specific mixtures of chemical and biological warfare agents to generate a library of biosignatures of exposure. The predicting capabilities of an operational library of biosignatures of exposures will allow the detection of emerging novel or genetically engineered agents, as well as complex mixtures of chemical and biological weapons agents. CBW and TIC are discussed in the context of war, terrorism, and pollution.

Evolution of the VEGF-regulated vascular network from a neural guidance system.

PubMed

Ponnambalam, Sreenivasan; Alberghina, Mario

2011-06-01

The vascular network is closely linked to the neural system, and an interdependence is displayed in healthy and in pathophysiological responses. How has close apposition of two such functionally different systems occurred? Here, we present a hypothesis for the evolution of the vascular network from an ancestral neural guidance system. Biological cornerstones of this hypothesis are the vascular endothelial growth factor (VEGF) protein family and cognate receptors. The primary sequences of such proteins are conserved from invertebrates, such as worms and flies that lack discernible vascular systems compared to mammals, but all these systems have sophisticated neuronal wiring involving such molecules. Ancestral VEGFs and receptors (VEGFRs) could have been used to develop and maintain the nervous system in primitive eukaryotes. During evolution, the demands of increased morphological complexity required systems for transporting molecules and cells, i.e., biological conductive tubes. We propose that the VEGF-VEGFR axis was subverted by evolution to mediate the formation of biological tubes necessary for transport of fluids, e.g., blood. Increasingly, there is evidence that aberrant VEGF-mediated responses are also linked to neuronal dysfunctions ranging from motor neuron disease, stroke, Parkinson's disease, Alzheimer's disease, ischemic brain disease, epilepsy, multiple sclerosis, and neuronal repair after injury, as well as common vascular diseases (e.g., retinal disease). Manipulation and correction of the VEGF response in different neural tissues could be an effective strategy to treat different neurological diseases.

Programmable chemical controllers made from DNA.

PubMed

Chen, Yuan-Jyue; Dalchau, Neil; Srinivas, Niranjan; Phillips, Andrew; Cardelli, Luca; Soloveichik, David; Seelig, Georg

2013-10-01

Biological organisms use complex molecular networks to navigate their environment and regulate their internal state. The development of synthetic systems with similar capabilities could lead to applications such as smart therapeutics or fabrication methods based on self-organization. To achieve this, molecular control circuits need to be engineered to perform integrated sensing, computation and actuation. Here we report a DNA-based technology for implementing the computational core of such controllers. We use the formalism of chemical reaction networks as a 'programming language' and our DNA architecture can, in principle, implement any behaviour that can be mathematically expressed as such. Unlike logic circuits, our formulation naturally allows complex signal processing of intrinsically analogue biological and chemical inputs. Controller components can be derived from biologically synthesized (plasmid) DNA, which reduces errors associated with chemically synthesized DNA. We implement several building-block reaction types and then combine them into a network that realizes, at the molecular level, an algorithm used in distributed control systems for achieving consensus between multiple agents.

Structure and formation of ant transportation networks

PubMed Central

Latty, Tanya; Ramsch, Kai; Ito, Kentaro; Nakagaki, Toshiyuki; Sumpter, David J. T.; Middendorf, Martin; Beekman, Madeleine

2011-01-01

Many biological systems use extensive networks for the transport of resources and information. Ants are no exception. How do biological systems achieve efficient transportation networks in the absence of centralized control and without global knowledge of the environment? Here, we address this question by studying the formation and properties of inter-nest transportation networks in the Argentine ant (Linepithema humile). We find that the formation of inter-nest networks depends on the number of ants involved in the construction process. When the number of ants is sufficient and networks do form, they tend to have short total length but a low level of robustness. These networks are topologically similar to either minimum spanning trees or Steiner networks. The process of network formation involves an initial construction of multiple links followed by a pruning process that reduces the number of trails. Our study thus illuminates the conditions under and the process by which minimal biological transport networks can be constructed. PMID:21288958

Programmable chemical controllers made from DNA

NASA Astrophysics Data System (ADS)

Chen, Yuan-Jyue; Dalchau, Neil; Srinivas, Niranjan; Phillips, Andrew; Cardelli, Luca; Soloveichik, David; Seelig, Georg

2013-10-01

Biological organisms use complex molecular networks to navigate their environment and regulate their internal state. The development of synthetic systems with similar capabilities could lead to applications such as smart therapeutics or fabrication methods based on self-organization. To achieve this, molecular control circuits need to be engineered to perform integrated sensing, computation and actuation. Here we report a DNA-based technology for implementing the computational core of such controllers. We use the formalism of chemical reaction networks as a 'programming language' and our DNA architecture can, in principle, implement any behaviour that can be mathematically expressed as such. Unlike logic circuits, our formulation naturally allows complex signal processing of intrinsically analogue biological and chemical inputs. Controller components can be derived from biologically synthesized (plasmid) DNA, which reduces errors associated with chemically synthesized DNA. We implement several building-block reaction types and then combine them into a network that realizes, at the molecular level, an algorithm used in distributed control systems for achieving consensus between multiple agents.

Programmable chemical controllers made from DNA

PubMed Central

Chen, Yuan-Jyue; Dalchau, Neil; Srinivas, Niranjan; Phillips, Andrew; Cardelli, Luca; Soloveichik, David; Seelig, Georg

2014-01-01

Biological organisms use complex molecular networks to navigate their environment and regulate their internal state. The development of synthetic systems with similar capabilities could lead to applications such as smart therapeutics or fabrication methods based on self-organization. To achieve this, molecular control circuits need to be engineered to perform integrated sensing, computation and actuation. Here we report a DNA-based technology for implementing the computational core of such controllers. We use the formalism of chemical reaction networks as a 'programming language', and our DNA architecture can, in principle, implement any behaviour that can be mathematically expressed as such. Unlike logic circuits, our formulation naturally allows complex signal processing of intrinsically analogue biological and chemical inputs. Controller components can be derived from biologically synthesized (plasmid) DNA, which reduces errors associated with chemically synthesized DNA. We implement several building-block reaction types and then combine them into a network that realizes, at the molecular level, an algorithm used in distributed control systems for achieving consensus between multiple agents. PMID:24077029

The cell biology of Tobacco mosaic virus replication and movement

PubMed Central

Liu, Chengke; Nelson, Richard S.

2013-01-01

Successful systemic infection of a plant by Tobacco mosaic virus (TMV) requires three processes that repeat over time: initial establishment and accumulation in invaded cells, intercellular movement, and systemic transport. Accumulation and intercellular movement of TMV necessarily involves intracellular transport by complexes containing virus and host proteins and virus RNA during a dynamic process that can be visualized. Multiple membranes appear to assist TMV accumulation, while membranes, microfilaments and microtubules appear to assist TMV movement. Here we review cell biological studies that describe TMV-membrane, -cytoskeleton, and -other host protein interactions which influence virus accumulation and movement in leaves and callus tissue. The importance of understanding the developmental phase of the infection in relationship to the observed virus-membrane or -host protein interaction is emphasized. Utilizing the latest observations of TMV-membrane and -host protein interactions within our evolving understanding of the infection ontogeny, a model for TMV accumulation and intracellular spread in a cell biological context is provided. PMID:23403525

Role of the β Common (βc) Family of Cytokines in Health and Disease.

PubMed

Hercus, Timothy R; Kan, Winnie L T; Broughton, Sophie E; Tvorogov, Denis; Ramshaw, Hayley S; Sandow, Jarrod J; Nero, Tracy L; Dhagat, Urmi; Thompson, Emma J; Shing, Karen S Cheung Tung; McKenzie, Duncan R; Wilson, Nicholas J; Owczarek, Catherine M; Vairo, Gino; Nash, Andrew D; Tergaonkar, Vinay; Hughes, Timothy; Ekert, Paul G; Samuel, Michael S; Bonder, Claudine S; Grimbaldeston, Michele A; Parker, Michael W; Lopez, Angel F

2018-06-01

The β common ([βc]/CD131) family of cytokines comprises granulocyte macrophage colony-stimulating factor (GM-CSF), interleukin (IL)-3, and IL-5, all of which use βc as their key signaling receptor subunit. This is a prototypic signaling subunit-sharing cytokine family that has unveiled many biological paradigms and structural principles applicable to the IL-2, IL-4, and IL-6 receptor families, all of which also share one or more signaling subunits. Originally identified for their functions in the hematopoietic system, the βc cytokines are now known to be truly pleiotropic, impacting on multiple cell types, organs, and biological systems, and thereby controlling the balance between health and disease. This review will focus on the emerging biological roles for the βc cytokines, our progress toward understanding the mechanisms of receptor assembly and signaling, and the application of this knowledge to develop exciting new therapeutic approaches against human disease. Copyright © 2018 Cold Spring Harbor Laboratory Press; all rights reserved.

The Need for Integrated Approaches in Metabolic Engineering

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

Lechner, Anna; Brunk, Elizabeth; Keasling, Jay D.

This review highlights state-of-the-art procedures for heterologous small-molecule biosynthesis, the associated bottlenecks, and new strategies that have the potential to accelerate future accomplishments in metabolic engineering. We emphasize that a combination of different approaches over multiple time and size scales must b e considered for successful pathway engineering in a heterologous host. We have classified these optimization procedures based on the "system" that is being manipulated: transcriptome, translatome, proteome, or reactome. By bridging multiple disciplines, including molecular biology, biochemistry, biophysics, and computational sciences, we can create an integral framework for the discovery and implementation of novel biosynthetic production routes.

Fighting fire with fire: attacking the complexity of human tumors with armed therapeutic viruses.

PubMed

Hermiston, Terry

2002-08-01

Cancer gene therapies have centered on the use of a single gene, directed against a particular property or single aspect of tumor biology, to treat neoplastic disease. These therapies have met with limited clinical success. This is, perhaps, not surprising given the complex and heterogeneous nature of solid tumors. Treatments targeted at confronting multiple dimensions of human tumors are needed. Armed therapeutic viruses (oncolytic viruses carrying therapeutic genes) represent a system where the concerted action of multiple therapeutics can be joined into a single agent, and represent a promising avenue for developing future cancer therapies.

NAP: The Network Analysis Profiler, a web tool for easier topological analysis and comparison of medium-scale biological networks.

PubMed

Theodosiou, Theodosios; Efstathiou, Georgios; Papanikolaou, Nikolas; Kyrpides, Nikos C; Bagos, Pantelis G; Iliopoulos, Ioannis; Pavlopoulos, Georgios A

2017-07-14

Nowadays, due to the technological advances of high-throughput techniques, Systems Biology has seen a tremendous growth of data generation. With network analysis, looking at biological systems at a higher level in order to better understand a system, its topology and the relationships between its components is of a great importance. Gene expression, signal transduction, protein/chemical interactions, biomedical literature co-occurrences, are few of the examples captured in biological network representations where nodes represent certain bioentities and edges represent the connections between them. Today, many tools for network visualization and analysis are available. Nevertheless, most of them are standalone applications that often (i) burden users with computing and calculation time depending on the network's size and (ii) focus on handling, editing and exploring a network interactively. While such functionality is of great importance, limited efforts have been made towards the comparison of the topological analysis of multiple networks. Network Analysis Provider (NAP) is a comprehensive web tool to automate network profiling and intra/inter-network topology comparison. It is designed to bridge the gap between network analysis, statistics, graph theory and partially visualization in a user-friendly way. It is freely available and aims to become a very appealing tool for the broader community. It hosts a great plethora of topological analysis methods such as node and edge rankings. Few of its powerful characteristics are: its ability to enable easy profile comparisons across multiple networks, find their intersection and provide users with simplified, high quality plots of any of the offered topological characteristics against any other within the same network. It is written in R and Shiny, it is based on the igraph library and it is able to handle medium-scale weighted/unweighted, directed/undirected and bipartite graphs. NAP is available at http://bioinformatics.med.uoc.gr/NAP .

Systematic reconstruction of autism biology from massive genetic mutation profiles

PubMed Central

Zhang, Chaolin; Jiang, Yong-hui

2018-01-01

Autism spectrum disorder (ASD) affects 1% of world population and has become a pressing medical and social problem worldwide. As a paradigmatic complex genetic disease, ASD has been intensively studied and thousands of gene mutations have been reported. Because these mutations rarely recur, it is difficult to (i) pinpoint the fewer disease-causing versus majority random events and (ii) replicate or verify independent studies. A coherent and systematic understanding of autism biology has not been achieved. We analyzed 3392 and 4792 autism-related mutations from two large-scale whole-exome studies across multiple resolution levels, that is, variants (single-nucleotide), genes (protein-coding unit), and pathways (molecular module). These mutations do not recur or replicate at the variant level, but significantly and increasingly do so at gene and pathway levels. Genetic association reveals a novel gene + pathway dual-hit model, where the mutation burden becomes less relevant. In multiple independent analyses, hundreds of variants or genes repeatedly converge to several canonical pathways, either novel or literature-supported. These pathways define recurrent and systematic ASD biology, distinct from previously reported gene groups or networks. They also present a catalog of novel ASD risk factors including 118 variants and 72 genes. At a subpathway level, most variants disrupt the pathway-related gene functions, and in the same gene, they tend to hit residues extremely close to each other and in the same domain. Multiple interacting variants spotlight key modules, including the cAMP (adenosine 3′,5′-monophosphate) second-messenger system and mGluR (metabotropic glutamate receptor) signaling regulation by GRKs (G protein–coupled receptor kinases). At a superpathway level, distinct pathways further interconnect and converge to three biology themes: synaptic function, morphology, and plasticity. PMID:29651456

Systematic reconstruction of autism biology from massive genetic mutation profiles.

PubMed

Luo, Weijun; Zhang, Chaolin; Jiang, Yong-Hui; Brouwer, Cory R

2018-04-01

Autism spectrum disorder (ASD) affects 1% of world population and has become a pressing medical and social problem worldwide. As a paradigmatic complex genetic disease, ASD has been intensively studied and thousands of gene mutations have been reported. Because these mutations rarely recur, it is difficult to (i) pinpoint the fewer disease-causing versus majority random events and (ii) replicate or verify independent studies. A coherent and systematic understanding of autism biology has not been achieved. We analyzed 3392 and 4792 autism-related mutations from two large-scale whole-exome studies across multiple resolution levels, that is, variants (single-nucleotide), genes (protein-coding unit), and pathways (molecular module). These mutations do not recur or replicate at the variant level, but significantly and increasingly do so at gene and pathway levels. Genetic association reveals a novel gene + pathway dual-hit model, where the mutation burden becomes less relevant. In multiple independent analyses, hundreds of variants or genes repeatedly converge to several canonical pathways, either novel or literature-supported. These pathways define recurrent and systematic ASD biology, distinct from previously reported gene groups or networks. They also present a catalog of novel ASD risk factors including 118 variants and 72 genes. At a subpathway level, most variants disrupt the pathway-related gene functions, and in the same gene, they tend to hit residues extremely close to each other and in the same domain. Multiple interacting variants spotlight key modules, including the cAMP (adenosine 3',5'-monophosphate) second-messenger system and mGluR (metabotropic glutamate receptor) signaling regulation by GRKs (G protein-coupled receptor kinases). At a superpathway level, distinct pathways further interconnect and converge to three biology themes: synaptic function, morphology, and plasticity.

Synthetic Biology: Putting Synthesis into Biology

PubMed Central

Liang, Jing; Luo, Yunzi; Zhao, Huimin

2010-01-01

The ability to manipulate living organisms is at the heart of a range of emerging technologies that serve to address important and current problems in environment, energy, and health. However, with all its complexity and interconnectivity, biology has for many years been recalcitrant to engineering manipulations. The recent advances in synthesis, analysis, and modeling methods have finally provided the tools necessary to manipulate living systems in meaningful ways, and have led to the coining of a field named synthetic biology. The scope of synthetic biology is as complicated as life itself – encompassing many branches of science, and across many scales of application. New DNA synthesis and assembly techniques have made routine the customization of very large DNA molecules. This in turn has allowed the incorporation of multiple genes and pathways. By coupling these with techniques that allow for the modeling and design of protein functions, scientists have now gained the tools to create completely novel biological machineries. Even the ultimate biological machinery – a self-replicating organism – is being pursued at this moment. It is the purpose of this review to dissect and organize these various components of synthetic biology into a coherent picture. PMID:21064036

Integrated multiscale biomaterials experiment and modelling: a perspective

PubMed Central

Buehler, Markus J.; Genin, Guy M.

2016-01-01

Advances in multiscale models and computational power have enabled a broad toolset to predict how molecules, cells, tissues and organs behave and develop. A key theme in biological systems is the emergence of macroscale behaviour from collective behaviours across a range of length and timescales, and a key element of these models is therefore hierarchical simulation. However, this predictive capacity has far outstripped our ability to validate predictions experimentally, particularly when multiple hierarchical levels are involved. The state of the art represents careful integration of multiscale experiment and modelling, and yields not only validation, but also insights into deformation and relaxation mechanisms across scales. We present here a sampling of key results that highlight both challenges and opportunities for integrated multiscale experiment and modelling in biological systems. PMID:28981126

Multiscale mechanobiology: computational models for integrating molecules to multicellular systems

PubMed Central

Mak, Michael; Kim, Taeyoon

2015-01-01

Mechanical signals exist throughout the biological landscape. Across all scales, these signals, in the form of force, stiffness, and deformations, are generated and processed, resulting in an active mechanobiological circuit that controls many fundamental aspects of life, from protein unfolding and cytoskeletal remodeling to collective cell motions. The multiple scales and complex feedback involved present a challenge for fully understanding the nature of this circuit, particularly in development and disease in which it has been implicated. Computational models that accurately predict and are based on experimental data enable a means to integrate basic principles and explore fine details of mechanosensing and mechanotransduction in and across all levels of biological systems. Here we review recent advances in these models along with supporting and emerging experimental findings. PMID:26019013

A journey from reductionist to systemic cell biology aboard the schooner Tara.

PubMed

Karsenti, Eric

2012-07-01

In this essay I describe my personal journey from reductionist to systems cell biology and describe how this in turn led to a 3-year sea voyage to explore complex ocean communities. In describing this journey, I hope to convey some important principles that I gleaned along the way. I realized that cellular functions emerge from multiple molecular interactions and that new approaches borrowed from statistical physics are required to understand the emergence of such complex systems. Then I wondered how such interaction networks developed during evolution. Because life first evolved in the oceans, it became a natural thing to start looking at the small organisms that compose the plankton in the world's oceans, of which 98% are … individual cells-hence the Tara Oceans voyage, which finished on 31 March 2012 in Lorient, France, after a 60,000-mile around-the-world journey that collected more than 30,000 samples from 153 sampling stations.

Spoken language achieves robustness and evolvability by exploiting degeneracy and neutrality.

PubMed

Winter, Bodo

2014-10-01

As with biological systems, spoken languages are strikingly robust against perturbations. This paper shows that languages achieve robustness in a way that is highly similar to many biological systems. For example, speech sounds are encoded via multiple acoustically diverse, temporally distributed and functionally redundant cues, characteristics that bear similarities to what biologists call "degeneracy". Speech is furthermore adequately characterized by neutrality, with many different tongue configurations leading to similar acoustic outputs, and different acoustic variants understood as the same by recipients. This highlights the presence of a large neutral network of acoustic neighbors for every speech sound. Such neutrality ensures that a steady backdrop of variation can be maintained without impeding communication, assuring that there is "fodder" for subsequent evolution. Thus, studying linguistic robustness is not only important for understanding how linguistic systems maintain their functioning upon the background of noise, but also for understanding the preconditions for language evolution. © 2014 WILEY Periodicals, Inc.

Social Determinants of Population Health: A Systems Sciences Approach

PubMed Central

Fink, David S.; Keyes, Katherine M.; Cerdá, Magdalena

2016-01-01

Population distributions of health emerge from the complex interplay of health-related factors at multiple levels, from the biological to the societal level. Individuals are aggregated within social networks, affected by their locations, and influenced differently across time. From aggregations of individuals, group properties can emerge, including some exposures that are ubiquitous within populations but variant across populations. By combining a focus on social determinants of health with a conceptual framework for understanding how genetics, biology, behavior, psychology, society, and environment interact, a systems science approach can inform our understanding of the underlying causes of the unequal distribution of health across generations and populations, and can help us identify promising approaches to reduce such inequalities. In this paper, we discuss how systems science approaches have already made several substantive and methodological contributions to the study of population health from a social epidemiology perspective. PMID:27642548

In vitro DNA SCRaMbLE.

PubMed

Wu, Yi; Zhu, Rui-Ying; Mitchell, Leslie A; Ma, Lu; Liu, Rui; Zhao, Meng; Jia, Bin; Xu, Hui; Li, Yun-Xiang; Yang, Zu-Ming; Ma, Yuan; Li, Xia; Liu, Hong; Liu, Duo; Xiao, Wen-Hai; Zhou, Xiao; Li, Bing-Zhi; Yuan, Ying-Jin; Boeke, Jef D

2018-05-22

The power of synthetic biology has enabled the expression of heterologous pathways in cells, as well as genome-scale synthesis projects. The complexity of biological networks makes rational de novo design a grand challenge. Introducing features that confer genetic flexibility is a powerful strategy for downstream engineering. Here we develop an in vitro method of DNA library construction based on structural variation to accomplish this goal. The "in vitro SCRaMbLE system" uses Cre recombinase mixed in a test tube with purified DNA encoding multiple loxPsym sites. Using a β-carotene pathway designed for expression in yeast as an example, we demonstrate top-down and bottom-up in vitro SCRaMbLE, enabling optimization of biosynthetic pathway flux via the rearrangement of relevant transcription units. We show that our system provides a straightforward way to correlate phenotype and genotype and is potentially amenable to biochemical optimization in ways that the in vivo system cannot achieve.

A reproducible approach to high-throughput biological data acquisition and integration

PubMed Central

Rahnavard, Gholamali; Waldron, Levi; McIver, Lauren; Shafquat, Afrah; Franzosa, Eric A.; Miropolsky, Larissa; Sweeney, Christopher

2015-01-01

Modern biological research requires rapid, complex, and reproducible integration of multiple experimental results generated both internally and externally (e.g., from public repositories). Although large systematic meta-analyses are among the most effective approaches both for clinical biomarker discovery and for computational inference of biomolecular mechanisms, identifying, acquiring, and integrating relevant experimental results from multiple sources for a given study can be time-consuming and error-prone. To enable efficient and reproducible integration of diverse experimental results, we developed a novel approach for standardized acquisition and analysis of high-throughput and heterogeneous biological data. This allowed, first, novel biomolecular network reconstruction in human prostate cancer, which correctly recovered and extended the NFκB signaling pathway. Next, we investigated host-microbiome interactions. In less than an hour of analysis time, the system retrieved data and integrated six germ-free murine intestinal gene expression datasets to identify the genes most influenced by the gut microbiota, which comprised a set of immune-response and carbohydrate metabolism processes. Finally, we constructed integrated functional interaction networks to compare connectivity of peptide secretion pathways in the model organisms Escherichia coli, Bacillus subtilis, and Pseudomonas aeruginosa. PMID:26157642

Advancing Risk Assessment through the Application of Systems Toxicology

PubMed Central

Sauer, John Michael; Kleensang, André; Peitsch, Manuel C.; Hayes, A. Wallace

2016-01-01

Risk assessment is the process of quantifying the probability of a harmful effect to individuals or populations from human activities. Mechanistic approaches to risk assessment have been generally referred to as systems toxicology. Systems toxicology makes use of advanced analytical and computational tools to integrate classical toxicology and quantitative analysis of large networks of molecular and functional changes occurring across multiple levels of biological organization. Three presentations including two case studies involving both in vitro and in vivo approaches described the current state of systems toxicology and the potential for its future application in chemical risk assessment. PMID:26977253

Comprehensive Thinking and Defense Analysis Transformation

DTIC Science & Technology

2011-06-01

that has taken two distinct forms: the biological evolution of cells , organs, animals and man; and the sociological evolution of groups...human systems learn and adapt as they deal with their Group Organization Community Societal Supranational Organism Organ Cell OOOOOOO oooooooo...better adapt on the fly, executing self synchronized movement towards a common goal. It requires stamina and endurance, in addition to multiple ball

40 CFR Appendix E to Part 63 - Monitoring Procedure for Nonthoroughly Mixed Open Biological Treatment Systems at Kraft Pulp...

Code of Federal Regulations, 2014 CFR

2014-07-01

... for each data set that is collected during the initial performance test. A single composite value of... Multiple Zone Concentrations Calculations Procedure based on inlet and outlet concentrations (Column A of... composite value of Ks discussed in section III.C of this appendix. This value of Ks is calculated during the...

AIM: a comprehensive Arabidopsis interactome module database and related interologs in plants.

PubMed

Wang, Yi; Thilmony, Roger; Zhao, Yunjun; Chen, Guoping; Gu, Yong Q

2014-01-01

Systems biology analysis of protein modules is important for understanding the functional relationships between proteins in the interactome. Here, we present a comprehensive database named AIM for Arabidopsis (Arabidopsis thaliana) interactome modules. The database contains almost 250,000 modules that were generated using multiple analysis methods and integration of microarray expression data. All the modules in AIM are well annotated using multiple gene function knowledge databases. AIM provides a user-friendly interface for different types of searches and offers a powerful graphical viewer for displaying module networks linked to the enrichment annotation terms. Both interactive Venn diagram and power graph viewer are integrated into the database for easy comparison of modules. In addition, predicted interologs from other plant species (homologous proteins from different species that share a conserved interaction module) are available for each Arabidopsis module. AIM is a powerful systems biology platform for obtaining valuable insights into the function of proteins in Arabidopsis and other plants using the modules of the Arabidopsis interactome. Database URL:http://probes.pw.usda.gov/AIM Published by Oxford University Press 2014. This work is written by US Government employees and is in the public domain in the US.

A Multidisciplinary, Open Access Platform for Research on Biomolecules.

PubMed

Bähler, Jürg

2011-08-22

I am pleased to introduce Biomolecules, a new journal to report on all aspects of science that focuses on biologically derived substances, from small molecules to complex polymers. Some examples are lipids, carbohydrates, vitamins, hormones, amino acids, nucleotides, peptides, RNA and polysaccharides, but this list is far from exhaustive. Research on biomolecules encompasses multiple fascinating questions. How are biomolecules synthesized and modified? What are their structures and interactions with other biomolecules? How do biomolecules function in biological processes, at the level of organelles, cells, organs, organisms, or even ecosystems? How do biomolecules affect either the organism that produces them or other organisms of the same or different species? How are biomolecules shaped by evolution, and how in turn do they affect cellular phenotypes? What is the systems-level contribution of biomolecules to biological function? [...].

Thin film bioreactors in space

NASA Technical Reports Server (NTRS)

Hughes-Fulford, M.; Scheld, H. W.

1989-01-01

Studies from the Skylab, SL-3 and D-1 missions have demonstrated that biological organisms grown in microgravity have changes in basic cellular functions such as DNA, mRNA and protein synthesis, cytoskeleton synthesis, glucose utilization, and cellular differentiation. Since microgravity could affect prokaryotic and eukaryotic cells at a subcellular and molecular level, space offers an opportunity to learn more about basic biological systems with one inmportant variable removed. The thin film bioreactor will facilitate the handling of fluids in microgravity, under constant temperature and will allow multiple samples of cells to be grown with variable conditions. Studies on cell cultures grown in microgravity would make it possible to identify and quantify changes in basic biological function in microgravity which are needed to develop new applications of orbital research and future biotechnology.

BIOSPIDA: A Relational Database Translator for NCBI.

PubMed

Hagen, Matthew S; Lee, Eva K

2010-11-13

As the volume and availability of biological databases continue widespread growth, it has become increasingly difficult for research scientists to identify all relevant information for biological entities of interest. Details of nucleotide sequences, gene expression, molecular interactions, and three-dimensional structures are maintained across many different databases. To retrieve all necessary information requires an integrated system that can query multiple databases with minimized overhead. This paper introduces a universal parser and relational schema translator that can be utilized for all NCBI databases in Abstract Syntax Notation (ASN.1). The data models for OMIM, Entrez-Gene, Pubmed, MMDB and GenBank have been successfully converted into relational databases and all are easily linkable helping to answer complex biological questions. These tools facilitate research scientists to locally integrate databases from NCBI without significant workload or development time.

Recombinant Collagenlike Proteins

NASA Technical Reports Server (NTRS)

Fertala, Andzej

2007-01-01

A group of collagenlike recombinant proteins containing high densities of biologically active sites has been invented. The method used to express these proteins is similar to a method of expressing recombinant procollagens and collagens described in U. S. Patent 5,593,859, "Synthesis of human procollagens and collagens in recombinant DNA systems." Customized collagenous proteins are needed for biomedical applications. In particular, fibrillar collagens are attractive for production of matrices needed for tissue engineering and drug delivery. Prior to this invention, there was no way of producing customized collagenous proteins for these and other applications. Heretofore, collagenous proteins have been produced by use of such biological systems as yeasts, bacteria, and transgenic animals and plants. These products are normal collagens that can also be extracted from such sources as tendons, bones, and hides. These products cannot be made to consist only of biologically active, specific amino acid sequences that may be needed for specific applications. Prior to this invention, it had been established that fibrillar collagens consist of domains that are responsible for such processes as interaction with cells, binding of growth factors, and interaction with a number of structural proteins present in the extracellular matrix. A normal collagen consists of a sequence of domains that can be represented by a corresponding sequence of labels, e.g., D1D2D3D4. A collagenlike protein of the present invention contains regions of collagen II that contain multiples of a single domain (e.g., D1D1D1D1 or D4D4D4D4) chosen for its specific biological activity. By virtue of the multiplicity of the chosen domain, the density of sites having that specific biological activity is greater than it is in a normal collagen. A collagenlike protein according to this invention can thus be made to have properties that are necessary for tissue engineering.

Super-resolution atomic force photoactivated microscopy of biological samples (Conference Presentation)

NASA Astrophysics Data System (ADS)

Lee, Seunghyun; Kim, Hyemin; Shin, Seungjun; Doh, Junsang; Kim, Chulhong

2017-03-01

Optical microscopy (OM) and photoacoustic microscopy (PAM) have previously been used to image the optical absorption of intercellular features of biological cells. However, the optical diffraction limit ( 200 nm) makes it difficult for these modalities to image nanoscale inner cell structures and the distribution of internal cell components. Although super-resolution fluorescence microscopy, such as stimulated emission depletion microscopy (STED) and stochastic optical reconstruction microscopy (STORM), has successfully performed nanoscale biological imaging, these modalities require the use of exogenous fluorescence agents, which are unfavorable for biological samples. Our newly developed atomic force photoactivated microscopy (AFPM) can provide optical absorption images with nanoscale lateral resolution without any exogenous contrast agents. AFPM combines conventional atomic force microscopy (AFM) and an optical excitation system, and simultaneously provides multiple contrasts, such as the topography and magnitude of optical absorption. AFPM can detect the intrinsic optical absorption of samples with 8 nm lateral resolution, easily overcoming the diffraction limit. Using the label-free AFPM system, we have successfully imaged the optical absorption properties of a single melanoma cell (B16F10) and a rosette leaf epidermal cell of Arabidopsis (ecotype Columbia (Col-0)) with nanoscale lateral resolution. The remarkable images show the melanosome distribution of a melanoma cell and the biological structures of a plant cell. AFPM provides superior imaging of optical absorption with a nanoscale lateral resolution, and it promises to become widely used in biological and chemical research.

Cancer Systems Biology Consortium | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

Cancer is a complex disease system involving multiple molecular, genetic, and cellular events. From its early initiation through progression and metastasis, cancer can adapt and evolve as a result of both internal and external signals. These properties make cancer difficult to predict, prevent, and treat. There has been significant progress in characterizing the genetics of cancer, as well as the downstream effects on the molecular and cellular pathways that are critical for the initiation and progression of cancer.

Propagation dynamics for a spatially periodic integrodifference competition model

NASA Astrophysics Data System (ADS)

Wu, Ruiwen; Zhao, Xiao-Qiang

2018-05-01

In this paper, we study the propagation dynamics for a class of integrodifference competition models in a periodic habitat. An interesting feature of such a system is that multiple spreading speeds can be observed, which biologically means different species may have different spreading speeds. We show that the model system admits a single spreading speed, and it coincides with the minimal wave speed of the spatially periodic traveling waves. A set of sufficient conditions for linear determinacy of the spreading speed is also given.

Testing primates with joystick-based automated apparatus - Lessons from the Language Research Center's Computerized Test System

NASA Technical Reports Server (NTRS)

Washburn, David A.; Rumbaugh, Duane M.

1992-01-01

Nonhuman primates provide useful models for studying a variety of medical, biological, and behavioral topics. Four years of joystick-based automated testing of monkeys using the Language Research Center's Computerized Test System (LRC-CTS) are examined to derive hints and principles for comparable testing with other species - including humans. The results of multiple parametric studies are reviewed, and reliability data are presented to reveal the surprises and pitfalls associated with video-task testing of performance.

Structured plant metabolomics for the simultaneous exploration of multiple factors.

PubMed

Vasilev, Nikolay; Boccard, Julien; Lang, Gerhard; Grömping, Ulrike; Fischer, Rainer; Goepfert, Simon; Rudaz, Serge; Schillberg, Stefan

2016-11-17

Multiple factors act simultaneously on plants to establish complex interaction networks involving nutrients, elicitors and metabolites. Metabolomics offers a better understanding of complex biological systems, but evaluating the simultaneous impact of different parameters on metabolic pathways that have many components is a challenging task. We therefore developed a novel approach that combines experimental design, untargeted metabolic profiling based on multiple chromatography systems and ionization modes, and multiblock data analysis, facilitating the systematic analysis of metabolic changes in plants caused by different factors acting at the same time. Using this method, target geraniol compounds produced in transgenic tobacco cell cultures were grouped into clusters based on their response to different factors. We hypothesized that our novel approach may provide more robust data for process optimization in plant cell cultures producing any target secondary metabolite, based on the simultaneous exploration of multiple factors rather than varying one factor each time. The suitability of our approach was verified by confirming several previously reported examples of elicitor-metabolite crosstalk. However, unravelling all factor-metabolite networks remains challenging because it requires the identification of all biochemically significant metabolites in the metabolomics dataset.

Genomic analysis of regulatory network dynamics reveals large topological changes

NASA Astrophysics Data System (ADS)

Luscombe, Nicholas M.; Madan Babu, M.; Yu, Haiyuan; Snyder, Michael; Teichmann, Sarah A.; Gerstein, Mark

2004-09-01

Network analysis has been applied widely, providing a unifying language to describe disparate systems ranging from social interactions to power grids. It has recently been used in molecular biology, but so far the resulting networks have only been analysed statically. Here we present the dynamics of a biological network on a genomic scale, by integrating transcriptional regulatory information and gene-expression data for multiple conditions in Saccharomyces cerevisiae. We develop an approach for the statistical analysis of network dynamics, called SANDY, combining well-known global topological measures, local motifs and newly derived statistics. We uncover large changes in underlying network architecture that are unexpected given current viewpoints and random simulations. In response to diverse stimuli, transcription factors alter their interactions to varying degrees, thereby rewiring the network. A few transcription factors serve as permanent hubs, but most act transiently only during certain conditions. By studying sub-network structures, we show that environmental responses facilitate fast signal propagation (for example, with short regulatory cascades), whereas the cell cycle and sporulation direct temporal progression through multiple stages (for example, with highly inter-connected transcription factors). Indeed, to drive the latter processes forward, phase-specific transcription factors inter-regulate serially, and ubiquitously active transcription factors layer above them in a two-tiered hierarchy. We anticipate that many of the concepts presented here-particularly the large-scale topological changes and hub transience-will apply to other biological networks, including complex sub-systems in higher eukaryotes.

How to Make a Synthetic Multicellular Computer

PubMed Central

Macia, Javier; Sole, Ricard

2014-01-01

Biological systems perform computations at multiple scales and they do so in a robust way. Engineering metaphors have often been used in order to provide a rationale for modeling cellular and molecular computing networks and as the basis for their synthetic design. However, a major constraint in this mapping between electronic and wet computational circuits is the wiring problem. Although wires are identical within electronic devices, they must be different when using synthetic biology designs. Moreover, in most cases the designed molecular systems cannot be reused for other functions. A new approximation allows us to simplify the problem by using synthetic cellular consortia where the output of the computation is distributed over multiple engineered cells. By evolving circuits in silico, we can obtain the minimal sets of Boolean units required to solve the given problem at the lowest cost using cellular consortia. Our analysis reveals that the basic set of logic units is typically non-standard. Among the most common units, the so called inverted IMPLIES (N-Implies) appears to be one of the most important elements along with the NOT and AND functions. Although NOR and NAND gates are widely used in electronics, evolved circuits based on combinations of these gates are rare, thus suggesting that the strategy of combining the same basic logic gates might be inappropriate in order to easily implement synthetic computational constructs. The implications for future synthetic designs, the general view of synthetic biology as a standard engineering domain, as well as potencial drawbacks are outlined. PMID:24586222

OmicsNet: a web-based tool for creation and visual analysis of biological networks in 3D space.

PubMed

Zhou, Guangyan; Xia, Jianguo

2018-06-07

Biological networks play increasingly important roles in omics data integration and systems biology. Over the past decade, many excellent tools have been developed to support creation, analysis and visualization of biological networks. However, important limitations remain: most tools are standalone programs, the majority of them focus on protein-protein interaction (PPI) or metabolic networks, and visualizations often suffer from 'hairball' effects when networks become large. To help address these limitations, we developed OmicsNet - a novel web-based tool that allows users to easily create different types of molecular interaction networks and visually explore them in a three-dimensional (3D) space. Users can upload one or multiple lists of molecules of interest (genes/proteins, microRNAs, transcription factors or metabolites) to create and merge different types of biological networks. The 3D network visualization system was implemented using the powerful Web Graphics Library (WebGL) technology that works natively in most major browsers. OmicsNet supports force-directed layout, multi-layered perspective layout, as well as spherical layout to help visualize and navigate complex networks. A rich set of functions have been implemented to allow users to perform coloring, shading, topology analysis, and enrichment analysis. OmicsNet is freely available at http://www.omicsnet.ca.

A Robust Unified Approach to Analyzing Methylation and Gene Expression Data

PubMed Central

Khalili, Abbas; Huang, Tim; Lin, Shili

2009-01-01

Microarray technology has made it possible to investigate expression levels, and more recently methylation signatures, of thousands of genes simultaneously, in a biological sample. Since more and more data from different biological systems or technological platforms are being generated at an incredible rate, there is an increasing need to develop statistical methods that are applicable to multiple data types and platforms. Motivated by such a need, a flexible finite mixture model that is applicable to methylation, gene expression, and potentially data from other biological systems, is proposed. Two major thrusts of this approach are to allow for a variable number of components in the mixture to capture non-biological variation and small biases, and to use a robust procedure for parameter estimation and probe classification. The method was applied to the analysis of methylation signatures of three breast cancer cell lines. It was also tested on three sets of expression microarray data to study its power and type I error rates. Comparison with a number of existing methods in the literature yielded very encouraging results; lower type I error rates and comparable/better power were achieved based on the limited study. Furthermore, the method also leads to more biologically interpretable results for the three breast cancer cell lines. PMID:20161265

Evolution of density-dependent movement during experimental range expansions.

PubMed

Fronhofer, E A; Gut, S; Altermatt, F

2017-12-01

Range expansions and biological invasions are prime examples of transient processes that are likely impacted by rapid evolutionary changes. As a spatial process, range expansions are driven by dispersal and movement behaviour. Although it is widely accepted that dispersal and movement may be context-dependent, for instance density-dependent, and best represented by reaction norms, the evolution of density-dependent movement during range expansions has received little experimental attention. We therefore tested current theory predicting the evolution of increased movement at low densities at range margins using highly replicated and controlled range expansion experiments across multiple genotypes of the protist model system Tetrahymena thermophila. Although rare, we found evolutionary changes during range expansions even in the absence of initial standing genetic variation. Range expansions led to the evolution of negatively density-dependent movement at range margins. In addition, we report the evolution of increased intrastrain competitive ability and concurrently decreased population growth rates in range cores. Our findings highlight the importance of understanding movement and dispersal as evolving reaction norms and plastic life-history traits of central relevance for range expansions, biological invasions and the dynamics of spatially structured systems in general. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.

MEIGO: an open-source software suite based on metaheuristics for global optimization in systems biology and bioinformatics.

PubMed

Egea, Jose A; Henriques, David; Cokelaer, Thomas; Villaverde, Alejandro F; MacNamara, Aidan; Danciu, Diana-Patricia; Banga, Julio R; Saez-Rodriguez, Julio

2014-05-10

Optimization is the key to solving many problems in computational biology. Global optimization methods, which provide a robust methodology, and metaheuristics in particular have proven to be the most efficient methods for many applications. Despite their utility, there is a limited availability of metaheuristic tools. We present MEIGO, an R and Matlab optimization toolbox (also available in Python via a wrapper of the R version), that implements metaheuristics capable of solving diverse problems arising in systems biology and bioinformatics. The toolbox includes the enhanced scatter search method (eSS) for continuous nonlinear programming (cNLP) and mixed-integer programming (MINLP) problems, and variable neighborhood search (VNS) for Integer Programming (IP) problems. Additionally, the R version includes BayesFit for parameter estimation by Bayesian inference. The eSS and VNS methods can be run on a single-thread or in parallel using a cooperative strategy. The code is supplied under GPLv3 and is available at http://www.iim.csic.es/~gingproc/meigo.html. Documentation and examples are included. The R package has been submitted to BioConductor. We evaluate MEIGO against optimization benchmarks, and illustrate its applicability to a series of case studies in bioinformatics and systems biology where it outperforms other state-of-the-art methods. MEIGO provides a free, open-source platform for optimization that can be applied to multiple domains of systems biology and bioinformatics. It includes efficient state of the art metaheuristics, and its open and modular structure allows the addition of further methods.

MEIGO: an open-source software suite based on metaheuristics for global optimization in systems biology and bioinformatics

PubMed Central

2014-01-01

Background Optimization is the key to solving many problems in computational biology. Global optimization methods, which provide a robust methodology, and metaheuristics in particular have proven to be the most efficient methods for many applications. Despite their utility, there is a limited availability of metaheuristic tools. Results We present MEIGO, an R and Matlab optimization toolbox (also available in Python via a wrapper of the R version), that implements metaheuristics capable of solving diverse problems arising in systems biology and bioinformatics. The toolbox includes the enhanced scatter search method (eSS) for continuous nonlinear programming (cNLP) and mixed-integer programming (MINLP) problems, and variable neighborhood search (VNS) for Integer Programming (IP) problems. Additionally, the R version includes BayesFit for parameter estimation by Bayesian inference. The eSS and VNS methods can be run on a single-thread or in parallel using a cooperative strategy. The code is supplied under GPLv3 and is available at http://www.iim.csic.es/~gingproc/meigo.html. Documentation and examples are included. The R package has been submitted to BioConductor. We evaluate MEIGO against optimization benchmarks, and illustrate its applicability to a series of case studies in bioinformatics and systems biology where it outperforms other state-of-the-art methods. Conclusions MEIGO provides a free, open-source platform for optimization that can be applied to multiple domains of systems biology and bioinformatics. It includes efficient state of the art metaheuristics, and its open and modular structure allows the addition of further methods. PMID:24885957

Emergence Processes up to Consciousness Using the Multiplicity Principle and Quantum Physics

NASA Astrophysics Data System (ADS)

Ehresmann, Andrée C.; Vanbremeersch, Jean-Paul

2002-09-01

Evolution is marked by the emergence of new objects and interactions. Pursuing our preceding work on Memory Evolutive Systems (MES; cf. our Internet site), we propose a general mathematical model for this process, based on Category Theory. Its main characteristics is the Multiplicity Principle (MP) which asserts the existence of complex objects with several possible configurations. The MP entails the emergence of non-reducible more and more complex objects (emergentist reductionism). From the laws of Quantum Physics, it follows that the MP is valid for the category of particles and atoms, hence, by complexification, for any natural autonomous anticipatory complex system, such as biological systems up to neural systems, or social systems. Applying the model to the MES of neurons, we describe the emergence of higher and higher cognitive processes and of a semantic memory. Consciousness is characterized by the development of a permanent `personal' memory, the archetypal core, which allows the formation of extended landscapes with an integration of the temporal dimensions.

Single cell multiplexed assay for proteolytic activity using droplet microfluidics.

PubMed

Ng, Ee Xien; Miller, Miles A; Jing, Tengyang; Chen, Chia-Hung

2016-07-15

Cellular enzymes interact in a post-translationally regulated fashion to govern individual cell behaviors, yet current platform technologies are limited in their ability to measure multiple enzyme activities simultaneously in single cells. Here, we developed multi-color Förster resonance energy transfer (FRET)-based enzymatic substrates and use them in a microfluidics platform to simultaneously measure multiple specific protease activities from water-in-oil droplets that contain single cells. By integrating the microfluidic platform with a computational analytical method, Proteolytic Activity Matrix Analysis (PrAMA), we are able to infer six different protease activity signals from individual cells in a high throughput manner (~100 cells/experimental run). We characterized protease activity profiles at single cell resolution for several cancer cell lines including breast cancer cell line MDA-MB-231, lung cancer cell line PC-9, and leukemia cell line K-562 using both live-cell and in-situ cell lysis assay formats, with special focus on metalloproteinases important in metastasis. The ability to measure multiple proteases secreted from or expressed in individual cells allows us to characterize cell heterogeneity and has potential applications including systems biology, pharmacology, cancer diagnosis and stem cell biology. Copyright © 2016 Elsevier B.V. All rights reserved.

FALDO: a semantic standard for describing the location of nucleotide and protein feature annotation.

PubMed

Bolleman, Jerven T; Mungall, Christopher J; Strozzi, Francesco; Baran, Joachim; Dumontier, Michel; Bonnal, Raoul J P; Buels, Robert; Hoehndorf, Robert; Fujisawa, Takatomo; Katayama, Toshiaki; Cock, Peter J A

2016-06-13

Nucleotide and protein sequence feature annotations are essential to understand biology on the genomic, transcriptomic, and proteomic level. Using Semantic Web technologies to query biological annotations, there was no standard that described this potentially complex location information as subject-predicate-object triples. We have developed an ontology, the Feature Annotation Location Description Ontology (FALDO), to describe the positions of annotated features on linear and circular sequences. FALDO can be used to describe nucleotide features in sequence records, protein annotations, and glycan binding sites, among other features in coordinate systems of the aforementioned "omics" areas. Using the same data format to represent sequence positions that are independent of file formats allows us to integrate sequence data from multiple sources and data types. The genome browser JBrowse is used to demonstrate accessing multiple SPARQL endpoints to display genomic feature annotations, as well as protein annotations from UniProt mapped to genomic locations. Our ontology allows users to uniformly describe - and potentially merge - sequence annotations from multiple sources. Data sources using FALDO can prospectively be retrieved using federalised SPARQL queries against public SPARQL endpoints and/or local private triple stores.

FALDO: a semantic standard for describing the location of nucleotide and protein feature annotation

DOE PAGES

Bolleman, Jerven T.; Mungall, Christopher J.; Strozzi, Francesco; ...

2016-06-13

Nucleotide and protein sequence feature annotations are essential to understand biology on the genomic, transcriptomic, and proteomic level. Using Semantic Web technologies to query biological annotations, there was no standard that described this potentially complex location information as subject-predicate-object triples. In this paper, we have developed an ontology, the Feature Annotation Location Description Ontology (FALDO), to describe the positions of annotated features on linear and circular sequences. FALDO can be used to describe nucleotide features in sequence records, protein annotations, and glycan binding sites, among other features in coordinate systems of the aforementioned “omics” areas. Using the same data formatmore » to represent sequence positions that are independent of file formats allows us to integrate sequence data from multiple sources and data types. The genome browser JBrowse is used to demonstrate accessing multiple SPARQL endpoints to display genomic feature annotations, as well as protein annotations from UniProt mapped to genomic locations. Our ontology allows users to uniformly describe – and potentially merge – sequence annotations from multiple sources. Finally, data sources using FALDO can prospectively be retrieved using federalised SPARQL queries against public SPARQL endpoints and/or local private triple stores.« less

FALDO: a semantic standard for describing the location of nucleotide and protein feature annotation

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

Bolleman, Jerven T.; Mungall, Christopher J.; Strozzi, Francesco

Nucleotide and protein sequence feature annotations are essential to understand biology on the genomic, transcriptomic, and proteomic level. Using Semantic Web technologies to query biological annotations, there was no standard that described this potentially complex location information as subject-predicate-object triples. In this paper, we have developed an ontology, the Feature Annotation Location Description Ontology (FALDO), to describe the positions of annotated features on linear and circular sequences. FALDO can be used to describe nucleotide features in sequence records, protein annotations, and glycan binding sites, among other features in coordinate systems of the aforementioned “omics” areas. Using the same data formatmore » to represent sequence positions that are independent of file formats allows us to integrate sequence data from multiple sources and data types. The genome browser JBrowse is used to demonstrate accessing multiple SPARQL endpoints to display genomic feature annotations, as well as protein annotations from UniProt mapped to genomic locations. Our ontology allows users to uniformly describe – and potentially merge – sequence annotations from multiple sources. Finally, data sources using FALDO can prospectively be retrieved using federalised SPARQL queries against public SPARQL endpoints and/or local private triple stores.« less

OpenBiodiv-O: ontology of the OpenBiodiv knowledge management system.

PubMed

Senderov, Viktor; Simov, Kiril; Franz, Nico; Stoev, Pavel; Catapano, Terry; Agosti, Donat; Sautter, Guido; Morris, Robert A; Penev, Lyubomir

2018-01-18

The biodiversity domain, and in particular biological taxonomy, is moving in the direction of semantization of its research outputs. The present work introduces OpenBiodiv-O, the ontology that serves as the basis of the OpenBiodiv Knowledge Management System. Our intent is to provide an ontology that fills the gaps between ontologies for biodiversity resources, such as DarwinCore-based ontologies, and semantic publishing ontologies, such as the SPAR Ontologies. We bridge this gap by providing an ontology focusing on biological taxonomy. OpenBiodiv-O introduces classes, properties, and axioms in the domains of scholarly biodiversity publishing and biological taxonomy and aligns them with several important domain ontologies (FaBiO, DoCO, DwC, Darwin-SW, NOMEN, ENVO). By doing so, it bridges the ontological gap across scholarly biodiversity publishing and biological taxonomy and allows for the creation of a Linked Open Dataset (LOD) of biodiversity information (a biodiversity knowledge graph) and enables the creation of the OpenBiodiv Knowledge Management System. A key feature of the ontology is that it is an ontology of the scientific process of biological taxonomy and not of any particular state of knowledge. This feature allows it to express a multiplicity of scientific opinions. The resulting OpenBiodiv knowledge system may gain a high level of trust in the scientific community as it does not force a scientific opinion on its users (e.g. practicing taxonomists, library researchers, etc.), but rather provides the tools for experts to encode different views as science progresses. OpenBiodiv-O provides a conceptual model of the structure of a biodiversity publication and the development of related taxonomic concepts. It also serves as the basis for the OpenBiodiv Knowledge Management System.

Comparative study of binding interactions between porphyrin systems and aromatic compounds of biological importance by multiple spectroscopic techniques: A review

NASA Astrophysics Data System (ADS)

Makarska-Bialokoz, Magdalena

2018-07-01

The specific spectroscopic and redox properties of porphyrins predestine them to fulfill the role of sensors during interacting with different biologically active substances. Monitoring of binding interactions in the systems porphyrin-biologically active compound is a key question not only in the field of physiological functions of living organisms, but also in environmental protection, notably in the light of the rapidly growing drug consumption and concurrently the production of drug effluents. Not always beneficial action of drugs on natural porphyrin systems induces to further studies, with commercially available porphyrins as the model systems. Therefore the binding process between several water-soluble porphyrins and a series of biologically active compounds (e.g. caffeine, guanine, theophylline, theobromine, xanthine, uric acid) has been studied in different aqueous solutions analyzing their absorption and steady-state fluorescence spectra, the porphyrin fluorescence lifetimes and their quantum yields. The magnitude of the binding and fluorescence quenching constants values for particular quenchers decreases in a series: uric acid > guanine > caffeine > theophylline > theobromine > xanthine. In all the systems studied there are characters of static quenching, as a consequence of the π-π-stacked non-covalent and non-fluorescent complexes formation between porphyrins and interacting compounds, accompanied simultaneously by the additional specific binding interactions. The porphyrin fluorescence quenching can be explain by the photoinduced intermolecular electron transfer from aromatic compound to the center of the porphyrin molecule, playing the role of the binding site. Presented results can be valuable for designing of new fluorescent porphyrin chemosensors or monitoring of drug traces in aqueous solutions. The obtained outcomes have also the toxicological and medical importance, providing insight into the interactions of the water-soluble porphyrins with biologically active substances.

What does systems biology mean for drug development?

PubMed

Schrattenholz, André; Soskić, Vukić

2008-01-01

The complexity and flexibility of cellular architectures is increasingly recognized by impressive progress on the side of molecular analytics, i.e. proteomics, genomics and metabolomics. One of the messages from systems biology is that the number of molecular species in cellular networks is orders of magnitude bigger than anticipated by genomic analysis, in particular by fast posttranslational modifications of proteins. The requirements to manage external signals, integrate spatiotemporal signal transduction inside an organism and at the same time optimizing networks of biochemical and chemical reactions result in chemically extremely fine tuned molecular entities. Chemical side reactions of enzymatic activity, like e.g. random oxidative damage of proteins by free radicals during aging constantly introduce epigenetic alterations of protein targets. These events gradually and on an individual stochastic scale, keep modifying activities of these targets, and their affinities and selectivities towards biological and pharmacological ligands. One further message is that many of the key reactions in living systems are essentially based on interactions of low affinities and even low selectivities. This principle is responsible for the enormous flexibility and redundancy of cellular circuitries. So, in complex disorders like cancer or neurodegenerative diseases, which are rooted in relatively subtle and multimodal dysfunction of important physiologic pathways, drug discovery programs based on the concept of high affinity/high specificity compounds ("one-target, one-disease"), which still dominate the pharmaceutical industry increasingly turn out to be unsuccessful. Despite improvements in rational drug design and high throughput screening methods, the number of novel, single-target drugs fell much behind expectations during the past decade and the treatment of "complex diseases" remains a most pressing medical need. Currently a change of paradigm can be observed with regard to a new focus on agents that modulate multiple targets simultaneously. Targeting cellular function as a system rather than on the level of the single protein molecule significantly increases the size of the drugable proteome and is expected to introduce novel classes of multi-target drugs with fewer adverse effects and toxicity. Multiple target approaches have recently been used to design medications against atherosclerosis, cancer, depression, psychosis and neurodegenerative diseases. A focussed approach towards "systemic" drugs will certainly require the development of novel computational and mathematical concepts for appropriate modelling of complex data and extraction of "screenable" information from biological systems essentially ruled by deterministic chaotic processes on a background of individual stochasticity.

National environmental observing system to mitigate the effects of nuclear-biological-chemical (NBC) attacks: strategic and tactical

NASA Astrophysics Data System (ADS)

Fleming, Rex J.

2003-09-01

The challenge of obtaining an adequate environmental support system to help mitigate the effects of various terrorist generated plumes is articulated and a fiscally responsible solution is presented. A substantially improved national system of upper air data observing systems serves as a powerful information source prior to a terrorist event. A mobile tactical observing system for measuring the environment and for measuring the composition and intensity of the plume is implemented immediately following an event. Only proven and tested technologies are used. Program costs, benefits for the fight against terrorism, and multiple benefits to other aspects of the economy are summarized.

Integrated Analysis of Pharmacologic, Clinical, and SNP Microarray Data using Projection onto the Most Interesting Statistical Evidence with Adaptive Permutation Testing

PubMed Central

Pounds, Stan; Cao, Xueyuan; Cheng, Cheng; Yang, Jun; Campana, Dario; Evans, William E.; Pui, Ching-Hon; Relling, Mary V.

2010-01-01

Powerful methods for integrated analysis of multiple biological data sets are needed to maximize interpretation capacity and acquire meaningful knowledge. We recently developed Projection Onto the Most Interesting Statistical Evidence (PROMISE). PROMISE is a statistical procedure that incorporates prior knowledge about the biological relationships among endpoint variables into an integrated analysis of microarray gene expression data with multiple biological and clinical endpoints. Here, PROMISE is adapted to the integrated analysis of pharmacologic, clinical, and genome-wide genotype data that incorporating knowledge about the biological relationships among pharmacologic and clinical response data. An efficient permutation-testing algorithm is introduced so that statistical calculations are computationally feasible in this higher-dimension setting. The new method is applied to a pediatric leukemia data set. The results clearly indicate that PROMISE is a powerful statistical tool for identifying genomic features that exhibit a biologically meaningful pattern of association with multiple endpoint variables. PMID:21516175

Response and adaptation of photosynthesis, respiration, and antioxidant systems to elevated CO2 with environmental stress in plants

PubMed Central

Xu, Zhenzhu; Jiang, Yanling; Zhou, Guangsheng

2015-01-01

It is well known that plant photosynthesis and respiration are two fundamental and crucial physiological processes, while the critical role of the antioxidant system in response to abiotic factors is still a focus point for investigating physiological stress. Although one key metabolic process and its response to climatic change have already been reported and reviewed, an integrative review, including several biological processes at multiple scales, has not been well reported. The current review will present a synthesis focusing on the underlying mechanisms in the responses to elevated CO2 at multiple scales, including molecular, cellular, biochemical, physiological, and individual aspects, particularly, for these biological processes under elevated CO2 with other key abiotic stresses, such as heat, drought, and ozone pollution, as well as nitrogen limitation. The present comprehensive review may add timely and substantial information about the topic in recent studies, while it presents what has been well established in previous reviews. First, an outline of the critical biological processes, and an overview of their roles in environmental regulation, is presented. Second, the research advances with regard to the individual subtopics are reviewed, including the response and adaptation of the photosynthetic capacity, respiration, and antioxidant system to CO2 enrichment alone, and its combination with other climatic change factors. Finally, the potential applications for plant responses at various levels to climate change are discussed. The above issue is currently of crucial concern worldwide, and this review may help in a better understanding of how plants deal with elevated CO2 using other mainstream abiotic factors, including molecular, cellular, biochemical, physiological, and whole individual processes, and the better management of the ecological environment, climate change, and sustainable development. PMID:26442017

Network Stability Is a Balancing Act of Personality, Power, and Conflict Dynamics in Rhesus Macaque Societies

PubMed Central

McCowan, Brenda; Beisner, Brianne A.; Capitanio, John P.; Jackson, Megan E.; Cameron, Ashley N.; Seil, Shannon; Atwill, Edward R.; Fushing, Hsieh

2011-01-01

Stability in biological systems requires evolved mechanisms that promote robustness. Cohesive primate social groups represent one example of a stable biological system, which persist in spite of frequent conflict. Multiple sources of stability likely exist for any biological system and such robustness, or lack thereof, should be reflected and thus detectable in the group's network structure, and likely at multiple levels. Here we show how network structure and group stability are linked to the fundamental characteristics of the individual agents in groups and to the environmental and social contexts in which these individuals interact. Both internal factors (e.g., personality, sex) and external factors (e.g., rank dynamics, sex ratio) were considered from the level of the individual to that of the group to examine the effects of network structure on group stability in a nonhuman primate species. The results yielded three main findings. First, successful third-party intervention behavior is a mechanism of group stability in rhesus macaques in that successful interventions resulted in less wounding in social groups. Second, personality is the primary factor that determines which individuals perform the role of key intervener, via its effect on social power and dominance discrepancy. Finally, individuals with high social power are not only key interveners but also key players in grooming networks and receive reconciliations from a higher diversity of individuals. The results from this study provide sound evidence that individual and group characteristics such as personality and sex ratio influence network structures such as patterns of reconciliation, grooming and conflict intervention that are indicators of network robustness and consequent health and well-being in rhesus macaque societies. Utilizing this network approach has provided greater insight into how behavioral and social processes influence social stability in nonhuman primate groups. PMID:21857922

Network stability is a balancing act of personality, power, and conflict dynamics in rhesus macaque societies.

PubMed

McCowan, Brenda; Beisner, Brianne A; Capitanio, John P; Jackson, Megan E; Cameron, Ashley N; Seil, Shannon; Atwill, Edward R; Fushing, Hsieh

2011-01-01

Stability in biological systems requires evolved mechanisms that promote robustness. Cohesive primate social groups represent one example of a stable biological system, which persist in spite of frequent conflict. Multiple sources of stability likely exist for any biological system and such robustness, or lack thereof, should be reflected and thus detectable in the group's network structure, and likely at multiple levels. Here we show how network structure and group stability are linked to the fundamental characteristics of the individual agents in groups and to the environmental and social contexts in which these individuals interact. Both internal factors (e.g., personality, sex) and external factors (e.g., rank dynamics, sex ratio) were considered from the level of the individual to that of the group to examine the effects of network structure on group stability in a nonhuman primate species. The results yielded three main findings. First, successful third-party intervention behavior is a mechanism of group stability in rhesus macaques in that successful interventions resulted in less wounding in social groups. Second, personality is the primary factor that determines which individuals perform the role of key intervener, via its effect on social power and dominance discrepancy. Finally, individuals with high social power are not only key interveners but also key players in grooming networks and receive reconciliations from a higher diversity of individuals. The results from this study provide sound evidence that individual and group characteristics such as personality and sex ratio influence network structures such as patterns of reconciliation, grooming and conflict intervention that are indicators of network robustness and consequent health and well-being in rhesus macaque societies. Utilizing this network approach has provided greater insight into how behavioral and social processes influence social stability in nonhuman primate groups.

On the road to bioartificial organs.

PubMed

Ren, X; Ott, H C

2014-10-01

Biological organs are highly orchestrated systems with well-coordinated positioning, grouping, and interaction of different cell types within their specialized extracellular environment. Bioartificial organs are intended to be functional replacements of native organs generated through bioengineering techniques and hold the potential to alleviate donor organ shortage for transplantation. The development, production, and evaluation of such bioartificial organs require synergistic efforts of biology, material science, engineering, and medicine. In this review, we highlight the emerging platforms enabling structured assembly of multiple cell types into functional grafts and discuss recent advances and challenges in the development of bioartificial organs, including cell sources, in vitro organ culture, in vivo evaluation, and clinical considerations.

Involvement of the nitric oxide in melatonin-mediated protection against injury.

PubMed

Fan, Wenguo; He, Yifan; Guan, Xiaoyan; Gu, Wenzhen; Wu, Zhi; Zhu, Xiao; Huang, Fang; He, Hongwen

2018-05-01

Melatonin is a hormone mainly synthesized by the pineal gland in vertebrates and known well as an endogenous regulator of circadian and seasonal rhythms. It has been demonstrated that melatonin is involved in many physiological and pathophysiological processes showing antioxidant, anti-apoptotic and anti-inflammatory properties. Nitric oxide (NO) is a free radical gas in the biological system, which is produced by nitric oxide synthase (NOS) family. NO acts as a biological mediator and plays important roles in different systems in humans. The NO/NOS system exerts a broad spectrum of signaling functions. Accumulating evidence has clearly revealed that melatonin regulates NO/NOS system through multiple mechanisms that may influence physiological and pathophysiological processes. This article reviews the latest evidence for the effects of melatonin on NO/NOS regulation in different organs and disease conditions, the potential cellular mechanisms by which melatonin is involved in organ protection are discussed. Copyright © 2018 Elsevier Inc. All rights reserved.

Statistical approach for selection of biologically informative genes.

PubMed

Das, Samarendra; Rai, Anil; Mishra, D C; Rai, Shesh N

2018-05-20

Selection of informative genes from high dimensional gene expression data has emerged as an important research area in genomics. Many gene selection techniques have been proposed so far are either based on relevancy or redundancy measure. Further, the performance of these techniques has been adjudged through post selection classification accuracy computed through a classifier using the selected genes. This performance metric may be statistically sound but may not be biologically relevant. A statistical approach, i.e. Boot-MRMR, was proposed based on a composite measure of maximum relevance and minimum redundancy, which is both statistically sound and biologically relevant for informative gene selection. For comparative evaluation of the proposed approach, we developed two biological sufficient criteria, i.e. Gene Set Enrichment with QTL (GSEQ) and biological similarity score based on Gene Ontology (GO). Further, a systematic and rigorous evaluation of the proposed technique with 12 existing gene selection techniques was carried out using five gene expression datasets. This evaluation was based on a broad spectrum of statistically sound (e.g. subject classification) and biological relevant (based on QTL and GO) criteria under a multiple criteria decision-making framework. The performance analysis showed that the proposed technique selects informative genes which are more biologically relevant. The proposed technique is also found to be quite competitive with the existing techniques with respect to subject classification and computational time. Our results also showed that under the multiple criteria decision-making setup, the proposed technique is best for informative gene selection over the available alternatives. Based on the proposed approach, an R Package, i.e. BootMRMR has been developed and available at https://cran.r-project.org/web/packages/BootMRMR. This study will provide a practical guide to select statistical techniques for selecting informative genes from high dimensional expression data for breeding and system biology studies. Published by Elsevier B.V.

“Gestaltomics”: Systems Biology Schemes for the Study of Neuropsychiatric Diseases

PubMed Central

Gutierrez Najera, Nora A.; Resendis-Antonio, Osbaldo; Nicolini, Humberto

2017-01-01

The integration of different sources of biological information about what defines a behavioral phenotype is difficult to unify in an entity that reflects the arithmetic sum of its individual parts. In this sense, the challenge of Systems Biology for understanding the “psychiatric phenotype” is to provide an improved vision of the shape of the phenotype as it is visualized by “Gestalt” psychology, whose fundamental axiom is that the observed phenotype (behavior or mental disorder) will be the result of the integrative composition of every part. Therefore, we propose the term “Gestaltomics” as a term from Systems Biology to integrate data coming from different sources of information (such as the genome, transcriptome, proteome, epigenome, metabolome, phenome, and microbiome). In addition to this biological complexity, the mind is integrated through multiple brain functions that receive and process complex information through channels and perception networks (i.e., sight, ear, smell, memory, and attention) that in turn are programmed by genes and influenced by environmental processes (epigenetic). Today, the approach of medical research in human diseases is to isolate one disease for study; however, the presence of an additional disease (co-morbidity) or more than one disease (multimorbidity) adds complexity to the study of these conditions. This review will present the challenge of integrating psychiatric disorders at different levels of information (Gestaltomics). The implications of increasing the level of complexity, for example, studying the co-morbidity with another disease such as cancer, will also be discussed. PMID:28536537

A Biologically-Based Alternative Water Processor for Long Duration Space Missions

NASA Technical Reports Server (NTRS)

Barta, Daniel J.; Pickering, Karen D.; Meyer, Caitlin; Pensinger, Stuart; Vega, Leticia; Flynn, Michael; Jackson, Andrew; Wheeler, Raymond

2015-01-01

A wastewater recovery system has been developed that combines novel biological and physicochemical components for recycling wastewater on long duration space missions. Functionally, this Alternative Water Processor (AWP) would replace the Urine Processing Assembly on the International Space Station and reduce or eliminate the need for the multifiltration beds of the Water Processing Assembly (WPA). At its center are two unique game changing technologies: 1) a biological water processor (BWP) to mineralize organic forms of carbon and nitrogen and 2) an advanced membrane processor (Forward Osmosis Secondary Treatment) for removal of solids and inorganic ions. The AWP is designed for recycling larger quantities of wastewater from multiple sources expected during future exploration missions, including urine, hygiene (hand wash, shower, oral and shave) and laundry. The BWP utilizes a single-stage membrane-aerated biological reactor for simultaneous nitrification and denitrification. The Forward Osmosis Secondary Treatment (FOST) system uses a combination of forward osmosis (FO) and reverse osmosis (RO), is resistant to biofouling and can easily tolerate wastewaters high in non-volatile organics and solids associated with shower and/or hand washing. The BWP was operated continuously for over 300 days. After startup, the mature biological system averaged 85% organic carbon removal and 44% nitrogen removal, close to maximum based on available carbon. The FOST has averaged 93% water recovery, with a maximum of 98%. If the wastewater is slighty acidified, ammonia rejection is optimal. This paper will provide a description of the technology and summarize results from ground-based testing using real wastewater.

Endocrine hormones and local signals during the development of the mouse mammary gland.

PubMed

Brisken, Cathrin; Ataca, Dalya

2015-01-01

Most of mammary gland development occurs postnatally under the control of female reproductive hormones, which in turn interact with other endocrine factors. While hormones impinge on many tissues and trigger very complex biological responses, tissue recombination experiments with hormone receptor-deficient mammary epithelia revealed eminent roles for estrogens, progesterone, and prolactin receptor (PrlR) signaling that are intrinsic to the mammary epithelium. A subset of the luminal mammary epithelial cells expresses the estrogen receptor α (ERα), the progesterone receptor (PR), and the PrlR and act as sensor cells. These cells convert the detected systemic signals into local signals that are developmental stage-dependent and may be direct, juxtacrine, or paracrine. This setup ensures that the original input is amplified and that the biological responses of multiple cell types can be coordinated. Some key mediators of hormone action have been identified such as Wnt, EGFR, IGFR, and RANK signaling. Multiple signaling pathways such as FGF, Hedgehog, and Notch signaling participate in driving different aspects of mammary gland development locally but how they link to the hormonal control remains to be elucidated. An increasing number of endocrine factors are appearing to have a role in mammary gland development, the adipose tissue is increasingly recognized to play a role in endocrine regulation, and a complex role of the immune system with multiple different cell types is being revealed. For further resources related to this article, please visit the WIREs website. © 2015 Wiley Periodicals, Inc.

Atypical case of Wolfram syndrome revealed through targeted exome sequencing in a patient with suspected mitochondrial disease

PubMed Central

2012-01-01

Background Mitochondrial diseases comprise a diverse set of clinical disorders that affect multiple organ systems with varying severity and age of onset. Due to their clinical and genetic heterogeneity, these diseases are difficult to diagnose. We have developed a targeted exome sequencing approach to improve our ability to properly diagnose mitochondrial diseases and apply it here to an individual patient. Our method targets mitochondrial DNA (mtDNA) and the exons of 1,600 nuclear genes involved in mitochondrial biology or Mendelian disorders with multi-system phenotypes, thereby allowing for simultaneous evaluation of multiple disease loci. Case Presentation Targeted exome sequencing was performed on a patient initially suspected to have a mitochondrial disorder. The patient presented with diabetes mellitus, diffuse brain atrophy, autonomic neuropathy, optic nerve atrophy, and a severe amnestic syndrome. Further work-up revealed multiple heteroplasmic mtDNA deletions as well as profound thiamine deficiency without a clear nutritional cause. Targeted exome sequencing revealed a homozygous c.1672C > T (p.R558C) missense mutation in exon 8 of WFS1 that has previously been reported in a patient with Wolfram syndrome. Conclusion This case demonstrates how clinical application of next-generation sequencing technology can enhance the diagnosis of patients suspected to have rare genetic disorders. Furthermore, the finding of unexplained thiamine deficiency in a patient with Wolfram syndrome suggests a potential link between WFS1 biology and thiamine metabolism that has implications for the clinical management of Wolfram syndrome patients. PMID:22226368

Quantification of Fatty Acid Oxidation Products Using On-line High Performance Liquid Chromatography Tandem Mass Spectrometry

PubMed Central

Levison, Bruce S.; Zhang, Renliang; Wang, Zeneng; Fu, Xiaoming; DiDonato, Joseph A.; Hazen, Stanley L.

2013-01-01

Oxidized fatty acids formed via lipid peroxidation are implicated in pathological processes such as inflammation and atherosclerosis. A number of methods may be used to detect specific oxidized fatty acids containing a single or multiple combinations of epoxide, hydroxyl, ketone and hydroperoxide moieties on varying carbon chain lengths from C8 up to C30. Some of these methods are nonspecific and their use in biological systems is fraught with difficulty. Measures of specific-oxidized fatty acid derivatives help in identifying oxidation pathways in pathological processes. We used liquid chromatography coupled with electrospray ionization tandem mass spectrometry (LC-MS/MS) as efficient, selective and sensitive methods for identifying and analyzing multiple specific fatty acid peroxidation products in human plasma and other biological matrices. We then distilled the essential components of a number of these analyses to provide an efficient protocol by which fatty acid oxidation products and their parent compounds can be determined. In this protocol, addition of synthetic internal standard to the sample, followed by base hydrolysis at elevated temperature, and liquid-liquid phase sample extraction with lighter than water solvents facilitates isolation of the oxidized fatty acid species. These species can be identified and accurately quantified using stable isotope dilution and multiple reaction monitoring. Use of a coupled multiplexed gradient HPLC system on the front end enables high-throughput chromatography and more efficient use of mass spectrometer time. PMID:23499838

An optics-based variable-temperature assay system for characterizing thermodynamics of biomolecular reactions on solid support

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

Fei, Yiyan; Landry, James P.; Zhu, X. D., E-mail: xdzhu@physics.ucdavis.edu

A biological state is equilibrium of multiple concurrent biomolecular reactions. The relative importance of these reactions depends on physiological temperature typically between 10 °C and 50 °C. Experimentally the temperature dependence of binding reaction constants reveals thermodynamics and thus details of these biomolecular processes. We developed a variable-temperature opto-fluidic system for real-time measurement of multiple (400–10 000) biomolecular binding reactions on solid supports from 10 °C to 60 °C within ±0.1 °C. We illustrate the performance of this system with investigation of binding reactions of plant lectins (carbohydrate-binding proteins) with 24 synthetic glycans (i.e., carbohydrates). We found that the lectin-glycan reactions in general can be enthalpy-driven,more » entropy-driven, or both, and water molecules play critical roles in the thermodynamics of these reactions.« less

Integrated photoacoustic, ultrasound and fluorescence platform for diagnostic medical imaging-proof of concept study with a tissue mimicking phantom.

PubMed

James, Joseph; Murukeshan, Vadakke Matham; Woh, Lye Sun

2014-07-01

The structural and molecular heterogeneities of biological tissues demand the interrogation of the samples with multiple energy sources and provide visualization capabilities at varying spatial resolution and depth scales for obtaining complementary diagnostic information. A novel multi-modal imaging approach that uses optical and acoustic energies to perform photoacoustic, ultrasound and fluorescence imaging at multiple resolution scales from the tissue surface and depth is proposed in this paper. The system comprises of two distinct forms of hardware level integration so as to have an integrated imaging system under a single instrumentation set-up. The experimental studies show that the system is capable of mapping high resolution fluorescence signatures from the surface, optical absorption and acoustic heterogeneities along the depth (>2cm) of the tissue at multi-scale resolution (<1µm to <0.5mm).

An optics-based variable-temperature assay system for characterizing thermodynamics of biomolecular reactions on solid support

NASA Astrophysics Data System (ADS)

Fei, Yiyan; Landry, James P.; Li, Yanhong; Yu, Hai; Lau, Kam; Huang, Shengshu; Chokhawala, Harshal A.; Chen, Xi; Zhu, X. D.

2013-11-01

A biological state is equilibrium of multiple concurrent biomolecular reactions. The relative importance of these reactions depends on physiological temperature typically between 10 °C and 50 °C. Experimentally the temperature dependence of binding reaction constants reveals thermodynamics and thus details of these biomolecular processes. We developed a variable-temperature opto-fluidic system for real-time measurement of multiple (400-10 000) biomolecular binding reactions on solid supports from 10 °C to 60 °C within ±0.1 °C. We illustrate the performance of this system with investigation of binding reactions of plant lectins (carbohydrate-binding proteins) with 24 synthetic glycans (i.e., carbohydrates). We found that the lectin-glycan reactions in general can be enthalpy-driven, entropy-driven, or both, and water molecules play critical roles in the thermodynamics of these reactions.

Interaction of Herbal Compounds with Biological Targets: A Case Study with Berberine

PubMed Central

Chen, Xiao-Wu; Di, Yuan Ming; Zhang, Jian; Zhou, Zhi-Wei; Li, Chun Guang; Zhou, Shu-Feng

2012-01-01

Berberine is one of the main alkaloids found in the Chinese herb Huang lian (Rhizoma Coptidis), which has been reported to have multiple pharmacological activities. This study aimed to analyze the molecular targets of berberine based on literature data followed by a pathway analysis using the PANTHER program. PANTHER analysis of berberine targets showed that the most classes of molecular functions include receptor binding, kinase activity, protein binding, transcription activity, DNA binding, and kinase regulator activity. Based on the biological process classification of in vitro berberine targets, those targets related to signal transduction, intracellular signalling cascade, cell surface receptor-linked signal transduction, cell motion, cell cycle control, immunity system process, and protein metabolic process are most frequently involved. In addition, berberine was found to interact with a mixture of biological pathways, such as Alzheimer's disease-presenilin and -secretase pathways, angiogenesis, apoptosis signalling pathway, FAS signalling pathway, Hungtington disease, inflammation mediated by chemokine and cytokine signalling pathways, interleukin signalling pathway, and p53 pathways. We also explored the possible mechanism of action for the anti-diabetic effect of berberine. Further studies are warranted to elucidate the mechanisms of action of berberine using systems biology approach. PMID:23213296

Semantic Web meets Integrative Biology: a survey.

PubMed

Chen, Huajun; Yu, Tong; Chen, Jake Y

2013-01-01

Integrative Biology (IB) uses experimental or computational quantitative technologies to characterize biological systems at the molecular, cellular, tissue and population levels. IB typically involves the integration of the data, knowledge and capabilities across disciplinary boundaries in order to solve complex problems. We identify a series of bioinformatics problems posed by interdisciplinary integration: (i) data integration that interconnects structured data across related biomedical domains; (ii) ontology integration that brings jargons, terminologies and taxonomies from various disciplines into a unified network of ontologies; (iii) knowledge integration that integrates disparate knowledge elements from multiple sources; (iv) service integration that build applications out of services provided by different vendors. We argue that IB can benefit significantly from the integration solutions enabled by Semantic Web (SW) technologies. The SW enables scientists to share content beyond the boundaries of applications and websites, resulting into a web of data that is meaningful and understandable to any computers. In this review, we provide insight into how SW technologies can be used to build open, standardized and interoperable solutions for interdisciplinary integration on a global basis. We present a rich set of case studies in system biology, integrative neuroscience, bio-pharmaceutics and translational medicine, to highlight the technical features and benefits of SW applications in IB.

Stochastic and superharmonic stochastic resonances of a confined overdamped harmonic oscillator

NASA Astrophysics Data System (ADS)

Zhang, Lu; Lai, Li; Peng, Hao; Tu, Zhe; Zhong, Suchuan

2018-01-01

The dynamics of many soft condensed matter and biological systems is affected by space limitations, which produce some peculiar effects on the systems' stochastic resonance (SR) behavior. In this study, we propose a model where SR can be observed: a confined overdamped harmonic oscillator that is subjected to a sinusoidal driving force and is under the influence of a multiplicative white noise. The output response of the system is a periodic signal with harmonic frequencies that are odd multiples of the driving frequency. We verify the amplitude resonances at the driving frequencies and superharmonic frequencies that are equal to three, five, and seven times the driving frequency, using a numerical method based on the stochastic Taylor expansion. The synergistic effect of the multiplicative white noise, constant boundaries, and periodic driving force that can induce a SR in the output amplitude at the driving and superharmonic frequencies is found. The SR phenomenon found in this paper is sensitive to the driving amplitude and frequency, inherent potential parameter, and boundary width, thus leading to various resonance conditions. Therefore, the mechanism found could be beneficial for the characterization of these confined systems and could constitute an important tool for controlling their basic properties.

Systems Bioinformatics: increasing precision of computational diagnostics and therapeutics through network-based approaches.

PubMed

Oulas, Anastasis; Minadakis, George; Zachariou, Margarita; Sokratous, Kleitos; Bourdakou, Marilena M; Spyrou, George M

2017-11-27

Systems Bioinformatics is a relatively new approach, which lies in the intersection of systems biology and classical bioinformatics. It focuses on integrating information across different levels using a bottom-up approach as in systems biology with a data-driven top-down approach as in bioinformatics. The advent of omics technologies has provided the stepping-stone for the emergence of Systems Bioinformatics. These technologies provide a spectrum of information ranging from genomics, transcriptomics and proteomics to epigenomics, pharmacogenomics, metagenomics and metabolomics. Systems Bioinformatics is the framework in which systems approaches are applied to such data, setting the level of resolution as well as the boundary of the system of interest and studying the emerging properties of the system as a whole rather than the sum of the properties derived from the system's individual components. A key approach in Systems Bioinformatics is the construction of multiple networks representing each level of the omics spectrum and their integration in a layered network that exchanges information within and between layers. Here, we provide evidence on how Systems Bioinformatics enhances computational therapeutics and diagnostics, hence paving the way to precision medicine. The aim of this review is to familiarize the reader with the emerging field of Systems Bioinformatics and to provide a comprehensive overview of its current state-of-the-art methods and technologies. Moreover, we provide examples of success stories and case studies that utilize such methods and tools to significantly advance research in the fields of systems biology and systems medicine. © The Author 2017. Published by Oxford University Press.

Common pitfalls in preclinical cancer target validation.

PubMed

Kaelin, William G

2017-07-01

An alarming number of papers from laboratories nominating new cancer drug targets contain findings that cannot be reproduced by others or are simply not robust enough to justify drug discovery efforts. This problem probably has many causes, including an underappreciation of the danger of being misled by off-target effects when using pharmacological or genetic perturbants in complex biological assays. This danger is particularly acute when, as is often the case in cancer pharmacology, the biological phenotype being measured is a 'down' readout (such as decreased proliferation, decreased viability or decreased tumour growth) that could simply reflect a nonspecific loss of cellular fitness. These problems are compounded by multiple hypothesis testing, such as when candidate targets emerge from high-throughput screens that interrogate multiple targets in parallel, and by a publication and promotion system that preferentially rewards positive findings. In this Perspective, I outline some of the common pitfalls in preclinical cancer target identification and some potential approaches to mitigate them.

Adaptive inference for distinguishing credible from incredible patterns in nature

USGS Publications Warehouse

Holling, Crawford S.; Allen, Craig R.

2002-01-01

Strong inference is a powerful and rapid tool that can be used to identify and explain patterns in molecular biology, cell biology, and physiology. It is effective where causes are single and separable and where discrimination between pairwise alternative hypotheses can be determined experimentally by a simple yes or no answer. But causes in ecological systems are multiple and overlapping and are not entirely separable. Frequently, competing hypotheses cannot be distinguished by a single unambiguous test, but only by a suite of tests of different kinds, that produce a body of evidence to support one line of argument and not others. We call this process "adaptive inference". Instead of pitting each member of a pair of hypotheses against each other, adaptive inference relies on the exuberant invention of multiple, competing hypotheses, after which carefully structured comparative data are used to explore the logical consequences of each. Herein we present an example that demonstrates the attributes of adaptive inference that have developed out of a 30-year study of the resilience of ecosystems.

Biologically-controlled multiple equilibria of tidal landforms and the fate of the Venice lagoon

NASA Astrophysics Data System (ADS)

Marani, Marco; D'Alpaos, Andrea; Lanzoni, Stefano; Carniello, Luca; Rinaldo, Andrea

2007-06-01

Looking across a tidal landscape, can one foresee the signs of impending shifts among different geomorphological structures? This is a question of paramount importance considering the ecological, cultural and socio-economic relevance of tidal environments and their worldwide decline. In this Letter we argue affirmatively by introducing a model of the coupled tidal physical and biological processes. Multiple equilibria, and transitions among them, appear in the evolutionary dynamics of tidal landforms. Vegetation type, disturbances of the benthic biofilm, sediment availability and marine transgressions or regressions drive the bio-geomorphic evolution of the system. Our approach provides general quantitative routes to model the fate of tidal landforms, which we illustrate in the case of the Venice lagoon (Italy), for which a large body of empirical observations exists spanning at least five centuries. Such observations are reproduced by the model, which also predicts that salt marshes in the Venice lagoon may not survive climatic changes in the next century if IPCC's scenarios of high relative sea level rise occur.

A modular platform for one-step assembly of multi-component membrane systems by fusion of charged proteoliposomes

NASA Astrophysics Data System (ADS)

Ishmukhametov, Robert R.; Russell, Aidan N.; Berry, Richard M.

2016-10-01

An important goal in synthetic biology is the assembly of biomimetic cell-like structures, which combine multiple biological components in synthetic lipid vesicles. A key limiting assembly step is the incorporation of membrane proteins into the lipid bilayer of the vesicles. Here we present a simple method for delivery of membrane proteins into a lipid bilayer within 5 min. Fusogenic proteoliposomes, containing charged lipids and membrane proteins, fuse with oppositely charged bilayers, with no requirement for detergent or fusion-promoting proteins, and deliver large, fragile membrane protein complexes into the target bilayers. We demonstrate the feasibility of our method by assembling a minimal electron transport chain capable of adenosine triphosphate (ATP) synthesis, combining Escherichia coli F1Fo ATP-synthase and the primary proton pump bo3-oxidase, into synthetic lipid vesicles with sizes ranging from 100 nm to ~10 μm. This provides a platform for the combination of multiple sets of membrane protein complexes into cell-like artificial structures.

When things don't add up: quantifying impacts of multiple stressors from individual metabolism to ecosystem processing.

PubMed

Galic, Nika; Sullivan, Lauren L; Grimm, Volker; Forbes, Valery E

2018-04-01

Ecosystems are exposed to multiple stressors which can compromise functioning and service delivery. These stressors often co-occur and interact in different ways which are not yet fully understood. Here, we applied a population model representing a freshwater amphipod feeding on leaf litter in forested streams. We simulated impacts of hypothetical stressors, individually and in pairwise combinations that target the individuals' feeding, maintenance, growth and reproduction. Impacts were quantified by examining responses at three levels of biological organisation: individual-level body sizes and cumulative reproduction, population-level abundance and biomass and ecosystem-level leaf litter decomposition. Interactive effects of multiple stressors at the individual level were mostly antagonistic, that is, less negative than expected. Most population- and ecosystem-level responses to multiple stressors were stronger than expected from an additive model, that is, synergistic. Our results suggest that across levels of biological organisation responses to multiple stressors are rarely only additive. We suggest methods for efficiently quantifying impacts of multiple stressors at different levels of biological organisation. © 2018 John Wiley & Sons Ltd/CNRS.

A tunable algorithm for collective decision-making.

PubMed

Pratt, Stephen C; Sumpter, David J T

2006-10-24

Complex biological systems are increasingly understood in terms of the algorithms that guide the behavior of system components and the information pathways that link them. Much attention has been given to robust algorithms, or those that allow a system to maintain its functions in the face of internal or external perturbations. At the same time, environmental variation imposes a complementary need for algorithm versatility, or the ability to alter system function adaptively as external circumstances change. An important goal of systems biology is thus the identification of biological algorithms that can meet multiple challenges rather than being narrowly specified to particular problems. Here we show that emigrating colonies of the ant Temnothorax curvispinosus tune the parameters of a single decision algorithm to respond adaptively to two distinct problems: rapid abandonment of their old nest in a crisis and deliberative selection of the best available new home when their old nest is still intact. The algorithm uses a stepwise commitment scheme and a quorum rule to integrate information gathered by numerous individual ants visiting several candidate homes. By varying the rates at which they search for and accept these candidates, the ants yield a colony-level response that adaptively emphasizes either speed or accuracy. We propose such general but tunable algorithms as a design feature of complex systems, each algorithm providing elegant solutions to a wide range of problems.

Imaging System and Method for Biomedical Analysis

DTIC Science & Technology

2013-03-11

biological particles and items of interest. Broadly, Padmanabhan et al. utilize the diffraction of a laser light source in flow cytometry to count...spread of light from multiple LED devices over the entire sample surface. Preferably, light source 308 projects a full spectrum white light. Light...for example, red blood cells, white blood cells (which may include lymphocytes which are relatively large and easily detectable), T-helper cells

Apical polarity in three-dimensional culture systems: where to now?

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

Inman, J.L.; Bissell, Mina

2010-01-21

Delineation of the mechanisms that establish and maintain the polarity of epithelial tissues is essential to understanding morphogenesis, tissue specificity and cancer. Three-dimensional culture assays provide a useful platform for dissecting these processes but, as discussed in a recent study in BMC Biology on the culture of mammary gland epithelial cells, multiple parameters that influence the model must be taken into account.

The rhizosphere microbial community in a multiple parallel mineralization system suppresses the pathogenic fungus Fusarium oxysporum

PubMed Central

Fujiwara, Kazuki; Iida, Yuichiro; Iwai, Takashi; Aoyama, Chihiro; Inukai, Ryuya; Ando, Akinori; Ogawa, Jun; Ohnishi, Jun; Terami, Fumihiro; Takano, Masao; Shinohara, Makoto

2013-01-01

The rhizosphere microbial community in a hydroponics system with multiple parallel mineralization (MPM) can potentially suppress root-borne diseases. This study focused on revealing the biological nature of the suppression against Fusarium wilt disease, which is caused by the fungus Fusarium oxysporum, and describing the factors that may influence the fungal pathogen in the MPM system. We demonstrated that the rhizosphere microbiota that developed in the MPM system could suppress Fusarium wilt disease under in vitro and greenhouse conditions. The microbiological characteristics of the MPM system were able to control the population dynamics of F. oxysporum, but did not eradicate the fungal pathogen. The roles of the microbiological agents underlying the disease suppression and the magnitude of the disease suppression in the MPM system appear to depend on the microbial density. F. oxysporum that survived in the MPM system formed chlamydospores when exposed to the rhizosphere microbiota. These results suggest that the microbiota suppresses proliferation of F. oxysporum by controlling the pathogen's morphogenesis and by developing an ecosystem that permits coexistence with F. oxysporum. PMID:24311557

Neuromechanical tuning of nonlinear postural control dynamics

NASA Astrophysics Data System (ADS)

Ting, Lena H.; van Antwerp, Keith W.; Scrivens, Jevin E.; McKay, J. Lucas; Welch, Torrence D. J.; Bingham, Jeffrey T.; DeWeerth, Stephen P.

2009-06-01

Postural control may be an ideal physiological motor task for elucidating general questions about the organization, diversity, flexibility, and variability of biological motor behaviors using nonlinear dynamical analysis techniques. Rather than presenting "problems" to the nervous system, the redundancy of biological systems and variability in their behaviors may actually be exploited to allow for the flexible achievement of multiple and concurrent task-level goals associated with movement. Such variability may reflect the constant "tuning" of neuromechanical elements and their interactions for movement control. The problem faced by researchers is that there is no one-to-one mapping between the task goal and the coordination of the underlying elements. We review recent and ongoing research in postural control with the goal of identifying common mechanisms underlying variability in postural control, coordination of multiple postural strategies, and transitions between them. We present a delayed-feedback model used to characterize the variability observed in muscle coordination patterns during postural responses to perturbation. We emphasize the significance of delays in physiological postural systems, requiring the modulation and coordination of both the instantaneous, "passive" response to perturbations as well as the delayed, "active" responses to perturbations. The challenge for future research lies in understanding the mechanisms and principles underlying neuromechanical tuning of and transitions between the diversity of postural behaviors. Here we describe some of our recent and ongoing studies aimed at understanding variability in postural control using physical robotic systems, human experiments, dimensional analysis, and computational models that could be enhanced from a nonlinear dynamics approach.

Identification of Single- and Multiple-Class Specific Signature Genes from Gene Expression Profiles by Group Marker Index

PubMed Central

Tsai, Yu-Shuen; Aguan, Kripamoy; Pal, Nikhil R.; Chung, I-Fang

2011-01-01

Informative genes from microarray data can be used to construct prediction model and investigate biological mechanisms. Differentially expressed genes, the main targets of most gene selection methods, can be classified as single- and multiple-class specific signature genes. Here, we present a novel gene selection algorithm based on a Group Marker Index (GMI), which is intuitive, of low-computational complexity, and efficient in identification of both types of genes. Most gene selection methods identify only single-class specific signature genes and cannot identify multiple-class specific signature genes easily. Our algorithm can detect de novo certain conditions of multiple-class specificity of a gene and makes use of a novel non-parametric indicator to assess the discrimination ability between classes. Our method is effective even when the sample size is small as well as when the class sizes are significantly different. To compare the effectiveness and robustness we formulate an intuitive template-based method and use four well-known datasets. We demonstrate that our algorithm outperforms the template-based method in difficult cases with unbalanced distribution. Moreover, the multiple-class specific genes are good biomarkers and play important roles in biological pathways. Our literature survey supports that the proposed method identifies unique multiple-class specific marker genes (not reported earlier to be related to cancer) in the Central Nervous System data. It also discovers unique biomarkers indicating the intrinsic difference between subtypes of lung cancer. We also associate the pathway information with the multiple-class specific signature genes and cross-reference to published studies. We find that the identified genes participate in the pathways directly involved in cancer development in leukemia data. Our method gives a promising way to find genes that can involve in pathways of multiple diseases and hence opens up the possibility of using an existing drug on other diseases as well as designing a single drug for multiple diseases. PMID:21909426

Do Houseflies Think? Patterns of Induction and Biological Beliefs in Development.

ERIC Educational Resources Information Center

Gutheil, Grant; Vera, Alonzo; Keil, Frank C.

1998-01-01

Examined preschoolers' inductive inferences across biological and non-biological kinds. Found support for gradual-enrichment model of conceptual change. Four-year-olds had a limited, coherent, independent biological theory which may form the basis of mature understanding of biological kinds. Explored results in terms of multiple explanatory…

Unsupervised multiple kernel learning for heterogeneous data integration.

PubMed

Mariette, Jérôme; Villa-Vialaneix, Nathalie

2018-03-15

Recent high-throughput sequencing advances have expanded the breadth of available omics datasets and the integrated analysis of multiple datasets obtained on the same samples has allowed to gain important insights in a wide range of applications. However, the integration of various sources of information remains a challenge for systems biology since produced datasets are often of heterogeneous types, with the need of developing generic methods to take their different specificities into account. We propose a multiple kernel framework that allows to integrate multiple datasets of various types into a single exploratory analysis. Several solutions are provided to learn either a consensus meta-kernel or a meta-kernel that preserves the original topology of the datasets. We applied our framework to analyse two public multi-omics datasets. First, the multiple metagenomic datasets, collected during the TARA Oceans expedition, was explored to demonstrate that our method is able to retrieve previous findings in a single kernel PCA as well as to provide a new image of the sample structures when a larger number of datasets are included in the analysis. To perform this analysis, a generic procedure is also proposed to improve the interpretability of the kernel PCA in regards with the original data. Second, the multi-omics breast cancer datasets, provided by The Cancer Genome Atlas, is analysed using a kernel Self-Organizing Maps with both single and multi-omics strategies. The comparison of these two approaches demonstrates the benefit of our integration method to improve the representation of the studied biological system. Proposed methods are available in the R package mixKernel, released on CRAN. It is fully compatible with the mixOmics package and a tutorial describing the approach can be found on mixOmics web site http://mixomics.org/mixkernel/. jerome.mariette@inra.fr or nathalie.villa-vialaneix@inra.fr. Supplementary data are available at Bioinformatics online.

Context Specificity of Stress-activated Mitogen-activated Protein (MAP) Kinase Signaling: The Story as Told by Caenorhabditis elegans.

PubMed

Andrusiak, Matthew G; Jin, Yishi

2016-04-08

Stress-associated p38 and JNK mitogen-activated protein (MAP) kinase signaling cascades trigger specific cellular responses and are involved in multiple disease states. At the root of MAP kinase signaling complexity is the differential use of common components on a context-specific basis. The roundwormCaenorhabditis eleganswas developed as a system to study genes required for development and nervous system function. The powerful genetics ofC. elegansin combination with molecular and cellular dissections has led to a greater understanding of how p38 and JNK signaling affects many biological processes under normal and stress conditions. This review focuses on the studies revealing context specificity of different stress-activated MAPK components inC. elegans. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Next Generation Sequencing Technology and Genomewide Data Analysis: Perspectives for Retinal Research

PubMed Central

Chaitankar, Vijender; Karakülah, Gökhan; Ratnapriya, Rinki; Giuste, Felipe O.; Brooks, Matthew J.; Swaroop, Anand

2016-01-01

The advent of high throughput next generation sequencing (NGS) has accelerated the pace of discovery of disease-associated genetic variants and genomewide profiling of expressed sequences and epigenetic marks, thereby permitting systems-based analyses of ocular development and disease. Rapid evolution of NGS and associated methodologies presents significant challenges in acquisition, management, and analysis of large data sets and for extracting biologically or clinically relevant information. Here we illustrate the basic design of commonly used NGS-based methods, specifically whole exome sequencing, transcriptome, and epigenome profiling, and provide recommendations for data analyses. We briefly discuss systems biology approaches for integrating multiple data sets to elucidate gene regulatory or disease networks. While we provide examples from the retina, the NGS guidelines reviewed here are applicable to other tissues/cell types as well. PMID:27297499

From genomes to societies: a holistic view of determinants of human health.

PubMed

Shi, Yuyan; Zhong, Sheng

2014-08-01

Both biological and social sciences have identified contributing factors to human health. However, health outcomes are unlikely to equal a simple sum of these identified factors. This article makes an attempt to put together the information, methods, and technologies that relate to health outcomes from biological, behavioral, and social disciplines. Much of this information was obtained by controlling for the variations of the factors in 'other' disciplines. For example, genetic factors were controlled for in identifying the behavioral determinants of health. Looking forward, better understandings of health outcomes may require exploiting the interactions of health determinants that were identified from different disciplines. We propose the concept of 'systems health' studies, which take health outcomes as the outputs of a system, where the inputs and their interactions from multiple disciplines are considered. Copyright © 2014 Elsevier Ltd. All rights reserved.

Chronic Inflammation: Accelerator of Biological Aging.

PubMed

Fougère, Bertrand; Boulanger, Eric; Nourhashémi, Fati; Guyonnet, Sophie; Cesari, Matteo

2017-09-01

Biological aging is characterized by a chronic low-grade inflammation level. This chronic phenomenon has been named "inflamm-aging" and is a highly significant risk factor for morbidity and mortality in the older persons. The most common theories of inflamm-aging include redox stress, mitochondrial dysfunction, glycation, deregulation of the immune system, hormonal changes, epigenetic modifications, and dysfunction telomere attrition. Inflamm-aging plays a role in the initiation and progression of age-related diseases such as type II diabetes, Alzheimer's disease, cardiovascular disease, frailty, sarcopenia, osteoporosis, and cancer. This review will cover the identification of pathways that control age-related inflammation across multiple systems and its potential causal role in contributing to adverse health outcomes. © The Author 2016. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

BioFVM: an efficient, parallelized diffusive transport solver for 3-D biological simulations

PubMed Central

Ghaffarizadeh, Ahmadreza; Friedman, Samuel H.; Macklin, Paul

2016-01-01

Motivation: Computational models of multicellular systems require solving systems of PDEs for release, uptake, decay and diffusion of multiple substrates in 3D, particularly when incorporating the impact of drugs, growth substrates and signaling factors on cell receptors and subcellular systems biology. Results: We introduce BioFVM, a diffusive transport solver tailored to biological problems. BioFVM can simulate release and uptake of many substrates by cell and bulk sources, diffusion and decay in large 3D domains. It has been parallelized with OpenMP, allowing efficient simulations on desktop workstations or single supercomputer nodes. The code is stable even for large time steps, with linear computational cost scalings. Solutions are first-order accurate in time and second-order accurate in space. The code can be run by itself or as part of a larger simulator. Availability and implementation: BioFVM is written in C ++ with parallelization in OpenMP. It is maintained and available for download at http://BioFVM.MathCancer.org and http://BioFVM.sf.net under the Apache License (v2.0). Contact: paul.macklin@usc.edu. Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26656933

Direct and Indirect Visualization of Bacterial Effector Delivery into Diverse Plant Cell Types during Infection[OPEN

PubMed Central

Henry, Elizabeth; Jauneau, Alain; Deslandes, Laurent

2017-01-01

To cause disease, diverse pathogens deliver effector proteins into host cells. Pathogen effectors can inhibit defense responses, alter host physiology, and represent important cellular probes to investigate plant biology. However, effector function and localization have primarily been investigated after overexpression in planta. Visualizing effector delivery during infection is challenging due to the plant cell wall, autofluorescence, and low effector abundance. Here, we used a GFP strand system to directly visualize bacterial effectors delivered into plant cells through the type III secretion system. GFP is a beta barrel that can be divided into 11 strands. We generated transgenic Arabidopsis thaliana plants expressing GFP1-10 (strands 1 to 10). Multiple bacterial effectors tagged with the complementary strand 11 epitope retained their biological function in Arabidopsis and tomato (Solanum lycopersicum). Infection of plants expressing GFP1-10 with bacteria delivering GFP11-tagged effectors enabled direct effector detection in planta. We investigated the temporal and spatial delivery of GFP11-tagged effectors during infection with the foliar pathogen Pseudomonas syringae and the vascular pathogen Ralstonia solanacearum. Thus, the GFP strand system can be broadly used to investigate effector biology in planta. PMID:28600390

Biological and nonbiological complex drugs for multiple sclerosis in Latin America: regulations and risk management.

PubMed

Carrá, Adriana; Macías Islas, Miguel Angel; Tarulla, Adriana; Bichuetti, Denis Bernardi; Finkelsztejn, Alessandro; Fragoso, Yara Dadalti; Árcega-Revilla, Raul; Cárcamo Rodríguez, Claudia; Durán, Juan Carlos; Bonitto, Juan García; León, Rosalba; Oehninger Gatti, Carlos; Orozco, Geraldine; Vizcarra Escobar, Darwin

2015-06-01

Biological drugs and nonbiological complex drugs with expired patents are followed by biosimilars and follow-on drugs that are supposedly similar and comparable with the reference product in terms of quality, safety and efficacy. Unlike simple molecules that can be copied and reproduced, biosimilars and follow-on complex drugs are heterogeneous and need specific regulations from health and pharmacovigilance agencies. A panel of 14 Latin American experts on multiple sclerosis from nine different countries met to discuss the recommendations regarding biosimilars and follow-on complex drugs for treating multiple sclerosis. Specific measures relating to manufacturing, therapeutic equivalence assessment and pharmacovigilance reports need to be implemented before commercialization. Physical, chemical, biological and immunogenic characterizations of the new product need to be available before clinical trials start. The new product must maintain the same immunogenicity as the original. Automatic substitution of biological and complex drugs poses unacceptable risks to the patient.

The implications of non-linear biological oscillations on human electrophysiology for electrohypersensitivity (EHS) and multiple chemical sensitivity (MCS).

PubMed

Sage, Cindy

2015-01-01

The 'informational content' of Earth's electromagnetic signaling is like a set of operating instructions for human life. These environmental cues are dynamic and involve exquisitely low inputs (intensities) of critical frequencies with which all life on Earth evolved. Circadian and other temporal biological rhythms depend on these fluctuating electromagnetic inputs to direct gene expression, cell communication and metabolism, neural development, brainwave activity, neural synchrony, a diversity of immune functions, sleep and wake cycles, behavior and cognition. Oscillation is also a universal phenomenon, and biological systems of the heart, brain and gut are dependent on the cooperative actions of cells that function according to principles of non-linear, coupled biological oscillations for their synchrony. They are dependent on exquisitely timed cues from the environment at vanishingly small levels. Altered 'informational content' of environmental cues can swamp natural electromagnetic cues and result in dysregulation of normal biological rhythms that direct growth, development, metabolism and repair mechanisms. Pulsed electromagnetic fields (PEMF) and radiofrequency radiation (RFR) can have the devastating biological effects of disrupting homeostasis and desynchronizing normal biological rhythms that maintain health. Non-linear, weak field biological oscillations govern body electrophysiology, organize cell and tissue functions and maintain organ systems. Artificial bioelectrical interference can give false information (disruptive signaling) sufficient to affect critical pacemaker cells (of the heart, gut and brain) and desynchronize functions of these important cells that orchestrate function and maintain health. Chronic physiological stress undermines homeostasis whether it is chemically induced or electromagnetically induced (or both exposures are simultaneous contributors). This can eventually break down adaptive biological responses critical to health maintenance; and resilience can be compromised. Electrohypersensitivity can be caused by successive assaults on human bioelectrochemical dynamics from exogenous electromagnetic fields (EMF) and RFR or a single acute exposure. Once sensitized, further exposures are widely reported to cause reactivity to lower and lower intensities of EMF/RFR, at which point thousand-fold lower levels can cause adverse health impacts to the electrosensitive person. Electrohypersensitivity (EHS) can be a precursor to, or linked with, multiple chemical sensitivity (MCS) based on reports of individuals who first develop one condition, then rapidly develop the other. Similarity of chemical biomarkers is seen in both conditions [histamines, markers of oxidative stress, auto-antibodies, heat shock protein (HSP), melatonin markers and leakage of the blood-brain barrier]. Low intensity pulsed microwave activation of voltage-gated calcium channels (VGCCs) is postulated as a mechanism of action for non-thermal health effects.

Molecular biomimetics: utilizing nature's molecular ways in practical engineering.

PubMed

Tamerler, Candan; Sarikaya, Mehmet

2007-05-01

In nature, proteins are the machinery that accomplish many functions through their specific recognition and interactions in biological systems from single-celled to multicellular organisms. Biomolecule-material interaction is accomplished via molecular specificity, leading to the formation of controlled structures and functions at all scales of dimensional hierarchy. Through evolution, molecular recognition and, consequently, functions developed through successive cycles of mutation and selection. Using biology as a guide, we can now understand, engineer and control peptide-material interactions and exploit these to tailor novel materials and systems for practical applications. We adapted combinatorial biology protocols to display peptide libraries, either on the cell surface or on phages, to select short peptides specific to a variety of practical materials systems. Following the selection step, we determined the kinetics and stability of peptide binding experimentally to understand the bound peptide structure via modeling and its assembly via atomic force microscopy. The peptides were further engineered to have multiple repeats or their amino acid sequences varied to tailor their function. Both nanoparticles and flat inorganic substrates containing multimaterials patterned at the nano- and microscales were used for self-directed immobilization of molecular constructs. The molecular biomimetic approach opens up new avenues for the design and utilization of multifunctional molecular systems with wide ranging applications, from tissue engineering, drug delivery and biosensors, to nanotechnology and bioremediation. Here we give examples of protein-mediated functional materials in biology, peptide selection and engineering with affinity to inorganics, demonstrate potential utilizations in materials science, engineering and medicine, and describe future prospects.

A biologically plausible computational model for auditory object recognition.

PubMed

Larson, Eric; Billimoria, Cyrus P; Sen, Kamal

2009-01-01

Object recognition is a task of fundamental importance for sensory systems. Although this problem has been intensively investigated in the visual system, relatively little is known about the recognition of complex auditory objects. Recent work has shown that spike trains from individual sensory neurons can be used to discriminate between and recognize stimuli. Multiple groups have developed spike similarity or dissimilarity metrics to quantify the differences between spike trains. Using a nearest-neighbor approach the spike similarity metrics can be used to classify the stimuli into groups used to evoke the spike trains. The nearest prototype spike train to the tested spike train can then be used to identify the stimulus. However, how biological circuits might perform such computations remains unclear. Elucidating this question would facilitate the experimental search for such circuits in biological systems, as well as the design of artificial circuits that can perform such computations. Here we present a biologically plausible model for discrimination inspired by a spike distance metric using a network of integrate-and-fire model neurons coupled to a decision network. We then apply this model to the birdsong system in the context of song discrimination and recognition. We show that the model circuit is effective at recognizing individual songs, based on experimental input data from field L, the avian primary auditory cortex analog. We also compare the performance and robustness of this model to two alternative models of song discrimination: a model based on coincidence detection and a model based on firing rate.

Integrated Optoelectronics for Parallel Microbioanalysis

NASA Technical Reports Server (NTRS)

Stirbl, Robert; Moynihan, Philip; Bearman, Gregory; Lane, Arthur

2003-01-01

Miniature, relatively inexpensive microbioanalytical systems ("laboratory-on-achip" devices) have been proposed for the detection of hazardous microbes and toxic chemicals. Each system of this type would include optoelectronic sensors and sensor-output-processing circuitry that would simultaneously look for the optical change, fluorescence, delayed fluorescence, or phosphorescence signatures from multiple redundant sites that have interacted with the test biomolecules in order to detect which one(s) was present in a given situation. These systems could be used in a variety of settings that could include doctors offices, hospitals, hazardous-material laboratories, biological-research laboratories, military operations, and chemical-processing plants.

BioSentinel: Developing a Space Radiation Biosensor

NASA Technical Reports Server (NTRS)

Santa Maria, Sergio R.

2015-01-01

BioSentinel is an autonomous fully self-contained science mission that will conduct the first study of the biological response to space radiation outside low Earth orbit (LEO) in over 40 years. The 4-unit (4U) BioSentinel biosensor system, is housed within a 6-Unit (6U) spacecraft, and uses yeast cells in multiple independent microfluidic cards to detect and measure DNA damage that occurs in response to ambient space radiation. Cell growth and metabolic activity will be measured using a 3-color LED detection system and a metabolic indicator dye with a dedicated thermal control system per fluidic card.

Emergence of multiple ocean ecosystem drivers in a large ensemble suite with an Earth system model

NASA Astrophysics Data System (ADS)

Rodgers, K. B.; Lin, J.; Frölicher, T. L.

2015-06-01

Marine ecosystems are increasingly stressed by human-induced changes. Marine ecosystem drivers that contribute to stressing ecosystems - including warming, acidification, deoxygenation and perturbations to biological productivity - can co-occur in space and time, but detecting their trends is complicated by the presence of noise associated with natural variability in the climate system. Here we use large initial-condition ensemble simulations with an Earth system model under a historical/RCP8.5 (representative concentration pathway 8.5) scenario over 1950-2100 to consider emergence characteristics for the four individual and combined drivers. Using a 1-standard-deviation (67% confidence) threshold of signal to noise to define emergence with a 30-year trend window, we show that ocean acidification emerges much earlier than other drivers, namely during the 20th century over most of the global ocean. For biological productivity, the anthropogenic signal does not emerge from the noise over most of the global ocean before the end of the 21st century. The early emergence pattern for sea surface temperature in low latitudes is reversed from that of subsurface oxygen inventories, where emergence occurs earlier in the Southern Ocean. For the combined multiple-driver field, 41% of the global ocean exhibits emergence for the 2005-2014 period, and 63% for the 2075-2084 period. The combined multiple-driver field reveals emergence patterns by the end of this century that are relatively high over much of the Southern Ocean, North Pacific, and Atlantic, but relatively low over the tropics and the South Pacific. For the case of two drivers, the tropics including habitats of coral reefs emerges earliest, with this driven by the joint effects of acidification and warming. It is precisely in the regions with pronounced emergence characteristics where marine ecosystems may be expected to be pushed outside of their comfort zone determined by the degree of natural background variability to which they are adapted. The results underscore the importance of sustained multi-decadal observing systems for monitoring multiple ecosystems drivers.

Modeling autism: a systems biology approach

PubMed Central

2012-01-01

Autism is the fastest growing developmental disorder in the world today. The prevalence of autism in the US has risen from 1 in 2500 in 1970 to 1 in 88 children today. People with autism present with repetitive movements and with social and communication impairments. These impairments can range from mild to profound. The estimated total lifetime societal cost of caring for one individual with autism is $3.2 million US dollars. With the rapid growth in this disorder and the great expense of caring for those with autism, it is imperative for both individuals and society that techniques be developed to model and understand autism. There is increasing evidence that those individuals diagnosed with autism present with highly diverse set of abnormalities affecting multiple systems of the body. To this date, little to no work has been done using a whole body systems biology approach to model the characteristics of this disorder. Identification and modelling of these systems might lead to new and improved treatment protocols, better diagnosis and treatment of the affected systems, which might lead to improved quality of life by themselves, and, in addition, might also help the core symptoms of autism due to the potential interconnections between the brain and nervous system with all these other systems being modeled. This paper first reviews research which shows that autism impacts many systems in the body, including the metabolic, mitochondrial, immunological, gastrointestinal and the neurological. These systems interact in complex and highly interdependent ways. Many of these disturbances have effects in most of the systems of the body. In particular, clinical evidence exists for increased oxidative stress, inflammation, and immune and mitochondrial dysfunction which can affect almost every cell in the body. Three promising research areas are discussed, hierarchical, subgroup analysis and modeling over time. This paper reviews some of the systems disturbed in autism and suggests several systems biology research areas. Autism poses a rich test bed for systems biology modeling techniques. PMID:23043674

A method of solving tilt illumination for multiple distance phase retrieval

NASA Astrophysics Data System (ADS)

Guo, Cheng; Li, Qiang; Tan, Jiubin; Liu, Shutian; Liu, Zhengjun

2018-07-01

Multiple distance phase retrieval is a technique of using a series of intensity patterns to reconstruct a complex-valued image of object. However, tilt illumination originating from the off-axis displacement of incident light significantly impairs its imaging quality. To eliminate this affection, we use cross-correlation calibration to estimate oblique angle of incident light and a Fourier-based strategy to correct tilted illumination effect. Compared to other methods, binary and biological object are both stably reconstructed in simulation and experiment. This work provides a simple but beneficial method to solve the problem of tilt illumination for lens-free multi-distance system.

Extramedullary plasmacytomas in the context of multiple myeloma.

PubMed

Aguado, Beatriz; Iñigo, Belen; Sastre, Jose L; Oriol, Albert

2011-11-01

Plasmacytoma is a frequent complication of multiple myeloma, either at diagnosis or within disease progression. The extramedullary disease confers a poorer prognosis and is biologically distinct with high-risk molecular and histological features, being resistant to conventional treatments. Radiation therapy remains the most effective treatment for extramedullary lesions to achieve local control. There are very limited data from randomized trials regarding the most appropriate systemic treatment. Case reports such as those presented here, as well as retrospective analysis of series, suggest that lenalidomide is an effective agent, in combination with dexamethasone, in this setting. Additional studies are needed to define the proper management of this condition.

A CRISPR view of development

PubMed Central

Harrison, Melissa M.; Jenkins, Brian V.; O’Connor-Giles, Kate M.

2014-01-01

The CRISPR (clustered regularly interspaced short palindromic repeat)–Cas9 (CRISPR-associated nuclease 9) system is poised to transform developmental biology by providing a simple, efficient method to precisely manipulate the genome of virtually any developing organism. This RNA-guided nuclease (RGN)-based approach already has been effectively used to induce targeted mutations in multiple genes simultaneously, create conditional alleles, and generate endogenously tagged proteins. Illustrating the adaptability of RGNs, the genomes of >20 different plant and animal species as well as multiple cell lines and primary cells have been successfully modified. Here we review the current and potential uses of RGNs to investigate genome function during development. PMID:25184674

Training Systems Modelers through the Development of a Multi-scale Chagas Disease Risk Model

NASA Astrophysics Data System (ADS)

Hanley, J.; Stevens-Goodnight, S.; Kulkarni, S.; Bustamante, D.; Fytilis, N.; Goff, P.; Monroy, C.; Morrissey, L. A.; Orantes, L.; Stevens, L.; Dorn, P.; Lucero, D.; Rios, J.; Rizzo, D. M.

2012-12-01

The goal of our NSF-sponsored Division of Behavioral and Cognitive Sciences grant is to create a multidisciplinary approach to develop spatially explicit models of vector-borne disease risk using Chagas disease as our model. Chagas disease is a parasitic disease endemic to Latin America that afflicts an estimated 10 million people. The causative agent (Trypanosoma cruzi) is most commonly transmitted to humans by blood feeding triatomine insect vectors. Our objectives are: (1) advance knowledge on the multiple interacting factors affecting the transmission of Chagas disease, and (2) provide next generation genomic and spatial analysis tools applicable to the study of other vector-borne diseases worldwide. This funding is a collaborative effort between the RSENR (UVM), the School of Engineering (UVM), the Department of Biology (UVM), the Department of Biological Sciences (Loyola (New Orleans)) and the Laboratory of Applied Entomology and Parasitology (Universidad de San Carlos). Throughout this five-year study, multi-educational groups (i.e., high school, undergraduate, graduate, and postdoctoral) will be trained in systems modeling. This systems approach challenges students to incorporate environmental, social, and economic as well as technical aspects and enables modelers to simulate and visualize topics that would either be too expensive, complex or difficult to study directly (Yasar and Landau 2003). We launch this research by developing a set of multi-scale, epidemiological models of Chagas disease risk using STELLA® software v.9.1.3 (isee systems, inc., Lebanon, NH). We use this particular system dynamics software as a starting point because of its simple graphical user interface (e.g., behavior-over-time graphs, stock/flow diagrams, and causal loops). To date, high school and undergraduate students have created a set of multi-scale (i.e., homestead, village, and regional) disease models. Modeling the system at multiple spatial scales forces recognition that the system's structure generates its behavior; and STELLA®'s graphical interface allows researchers at multiple educational levels to observe patterns and trends as the system changes over time. Graduate students and postdoctoral researchers will utilize these initial models to more efficiently communicate and transfer knowledge across disciplines prior to generating more novel and complex disease risk models. The hope is that these models will improve causal viewpoints, understanding of the system patterns, and how to best mitigate disease risk across multiple spatial scales. Yasar O, Landau RH (2003) Elements of computational science and engineering education. Siam Review 45(4): 787-805.

Organization of excitable dynamics in hierarchical biological networks.

PubMed

Müller-Linow, Mark; Hilgetag, Claus C; Hütt, Marc-Thorsten

2008-09-26

This study investigates the contributions of network topology features to the dynamic behavior of hierarchically organized excitable networks. Representatives of different types of hierarchical networks as well as two biological neural networks are explored with a three-state model of node activation for systematically varying levels of random background network stimulation. The results demonstrate that two principal topological aspects of hierarchical networks, node centrality and network modularity, correlate with the network activity patterns at different levels of spontaneous network activation. The approach also shows that the dynamic behavior of the cerebral cortical systems network in the cat is dominated by the network's modular organization, while the activation behavior of the cellular neuronal network of Caenorhabditis elegans is strongly influenced by hub nodes. These findings indicate the interaction of multiple topological features and dynamic states in the function of complex biological networks.

BIOSPIDA: A Relational Database Translator for NCBI

PubMed Central

Hagen, Matthew S.; Lee, Eva K.

2010-01-01

As the volume and availability of biological databases continue widespread growth, it has become increasingly difficult for research scientists to identify all relevant information for biological entities of interest. Details of nucleotide sequences, gene expression, molecular interactions, and three-dimensional structures are maintained across many different databases. To retrieve all necessary information requires an integrated system that can query multiple databases with minimized overhead. This paper introduces a universal parser and relational schema translator that can be utilized for all NCBI databases in Abstract Syntax Notation (ASN.1). The data models for OMIM, Entrez-Gene, Pubmed, MMDB and GenBank have been successfully converted into relational databases and all are easily linkable helping to answer complex biological questions. These tools facilitate research scientists to locally integrate databases from NCBI without significant workload or development time. PMID:21347013

Why an extended evolutionary synthesis is necessary

PubMed Central

2017-01-01

Since the last major theoretical integration in evolutionary biology—the modern synthesis (MS) of the 1940s—the biosciences have made significant advances. The rise of molecular biology and evolutionary developmental biology, the recognition of ecological development, niche construction and multiple inheritance systems, the ‘-omics’ revolution and the science of systems biology, among other developments, have provided a wealth of new knowledge about the factors responsible for evolutionary change. Some of these results are in agreement with the standard theory and others reveal different properties of the evolutionary process. A renewed and extended theoretical synthesis, advocated by several authors in this issue, aims to unite pertinent concepts that emerge from the novel fields with elements of the standard theory. The resulting theoretical framework differs from the latter in its core logic and predictive capacities. Whereas the MS theory and its various amendments concentrate on genetic and adaptive variation in populations, the extended framework emphasizes the role of constructive processes, ecological interactions and systems dynamics in the evolution of organismal complexity as well as its social and cultural conditions. Single-level and unilinear causation is replaced by multilevel and reciprocal causation. Among other consequences, the extended framework overcomes many of the limitations of traditional gene-centric explanation and entails a revised understanding of the role of natural selection in the evolutionary process. All these features stimulate research into new areas of evolutionary biology. PMID:28839929

Discovery of a new method for potent drug development using power function of stoichiometry ofhomomeric biocomplexes or biological nanomotors

PubMed Central

Pi, Fengmei; Vieweger, Mario; Zhao, Zhengyi; Wang, Shaoying; Guo, Peixuan

2015-01-01

Introduction Multidrug resistance and the appearance of incurable diseases inspire the quest for potent therapeutics. Areas Covered We review a new methodology in designing potent drugs by targeting multi-subunit homomeric biological motors, machines, or complexes with Z>1 and K=1, where Z is the stoichiometry of the target, and K is the number of drugged subunits required to block the function of the complex. The condition is similar to a series, electrical circuit of Christmas decorations; failure of one light bulb causes the entire lighting system to lose power. In most multisubunit, homomeric biological systems, a sequential coordination or cooperative action mechanism is utilized, thus K equals 1. Drug inhibition depends on the ratio of drugged to nondrugged complexes. When K=1, and Z>1, the inhibition effect follows a power law with respect to Z, leading to enhanced drug potency. The hypothesis that the potency of drug inhibition depends on the stoichiometry of the targeted biological complexes was recently quantified by Yang-Hui's Triangle (or binomial distribution), and proved using a highly sensitive in vitro phi29 viral DNA packaging system. Examples of targeting homomeric bio-complexes with high stoichiometry for potent drug discovery are discussed. Expert Opinion Biomotors with multiple subunits are widespread in viruses, bacteria, and cells, making this approach generally applicable in the development of inhibition drugs with high efficiency. PMID:26307193

Promoting Inquiry-Based Teaching in Laboratory Courses: Are We Meeting the Grade?

PubMed Central

Butler, Amy; Burke da Silva, Karen

2014-01-01

Over the past decade, repeated calls have been made to incorporate more active teaching and learning in undergraduate biology courses. The emphasis on inquiry-based teaching is especially important in laboratory courses, as these are the courses in which students are applying the process of science. To determine the current state of research on inquiry-based teaching in undergraduate biology laboratory courses, we reviewed the recent published literature on inquiry-based exercises. The majority of studies in our data set were in the subdisciplines of biochemistry, cell biology, developmental biology, genetics, and molecular biology. In addition, most exercises were guided inquiry, rather than open ended or research based. Almost 75% of the studies included assessment data, with two-thirds of these studies including multiple types of assessment data. However, few exercises were assessed in multiple courses or at multiple institutions. Furthermore, assessments were rarely based on published instruments. Although the results of the studies in our data set show a positive effect of inquiry-based teaching in biology laboratory courses on student learning gains, research that uses the same instrument across a range of courses and institutions is needed to determine whether these results can be generalized. PMID:25185228

Development of a GCR Event-based Risk Model

NASA Technical Reports Server (NTRS)

Cucinotta, Francis A.; Ponomarev, Artem L.; Plante, Ianik; Carra, Claudio; Kim, Myung-Hee

2009-01-01

A goal at NASA is to develop event-based systems biology models of space radiation risks that will replace the current dose-based empirical models. Complex and varied biochemical signaling processes transmit the initial DNA and oxidative damage from space radiation into cellular and tissue responses. Mis-repaired damage or aberrant signals can lead to genomic instability, persistent oxidative stress or inflammation, which are causative of cancer and CNS risks. Protective signaling through adaptive responses or cell repopulation is also possible. We are developing a computational simulation approach to galactic cosmic ray (GCR) effects that is based on biological events rather than average quantities such as dose, fluence, or dose equivalent. The goal of the GCR Event-based Risk Model (GERMcode) is to provide a simulation tool to describe and integrate physical and biological events into stochastic models of space radiation risks. We used the quantum multiple scattering model of heavy ion fragmentation (QMSFRG) and well known energy loss processes to develop a stochastic Monte-Carlo based model of GCR transport in spacecraft shielding and tissue. We validated the accuracy of the model by comparing to physical data from the NASA Space Radiation Laboratory (NSRL). Our simulation approach allows us to time-tag each GCR proton or heavy ion interaction in tissue including correlated secondary ions often of high multiplicity. Conventional space radiation risk assessment employs average quantities, and assumes linearity and additivity of responses over the complete range of GCR charge and energies. To investigate possible deviations from these assumptions, we studied several biological response pathway models of varying induction and relaxation times including the ATM, TGF -Smad, and WNT signaling pathways. We then considered small volumes of interacting cells and the time-dependent biophysical events that the GCR would produce within these tissue volumes to estimate how GCR event rates mapped to biological signaling induction and relaxation times. We considered several hypotheses related to signaling and cancer risk, and then performed simulations for conditions where aberrant or adaptive signaling would occur on long-duration space mission. Our results do not support the conventional assumptions of dose, linearity and additivity. A discussion on how event-based systems biology models, which focus on biological signaling as the mechanism to propagate damage or adaptation, can be further developed for cancer and CNS space radiation risk projections is given.

State of the science: chronic periodontitis and systemic health.

PubMed

Otomo-Corgel, Joan; Pucher, Jeffery J; Rethman, Michael P; Reynolds, Mark A

2012-09-01

Inflammatory periodontal diseases exhibit an association with multiple systemic conditions. Currently, there is a lack of consensus among experts on the nature of these associations and confusion among health care providers and the public on how to interpret this rapidly growing body of science. This article overviews the current evidence linking periodontal diseases to diabetes, cardiovascular disease, osteoporosis, preterm low birth weight babies, respiratory diseases, and rheumatoid arthritis. Evidence was taken from systematic reviews, clinical trials, and mechanistic studies retrieved in searches of the PubMed electronic database. The available data provide the basis for applied practical clinical recommendations. Evidence is summarized and critically reviewed from systematic reviews, primary clinical trials, and mechanistic studies Surrogate markers for chronic periodontitis, such as tooth loss, show relatively consistent but weak associations with multiple systemic conditions. Despite biological plausibility, shorter-term interventional trials have generally not supported unambiguous cause-and-effect relationships. Nevertheless, the effective treatment of periodontal infections is important to achieve oral health goals, as well as to reduce the systemic risks of chronic local inflammation and bacteremias. Inflammatory periodontal diseases exhibit an association with multiple systemic conditions. With pregnancy as a possible exception, the local and systemic effects of periodontal infections and inflammation are usually exerted for many years, typically among those who are middle-aged or older. It follows that numerous epidemiological associations linking chronic periodontitis to age-associated and biologically complex conditions such as diabetes, cardiovascular disease, osteoporosis, respiratory diseases, rheumatoid arthritis, certain cancers, erectile dysfunction, kidney disease and dementia, have been reported. In the coming years, it seems likely that additional associations will be reported, despite adjustments for known genetic, behavioral and environmental confounders. Determining cause-and-effect mechanisms is more complicated, especially in circumstances where systemic effects may be subtle. Currently, however, there is a lack of consensus among experts on the nature of these associations and confusion among health care providers and the public on how to interpret this rapidly growing body of science. This article overviews the current evidence linking periodontal diseases to diabetes, cardiovascular disease, osteoporosis, preterm/low birth weight babies, respiratory diseases, and rheumatoid arthritis. Copyright © 2012 Elsevier Inc. All rights reserved.

Purification and biological characterization of soluble, recombinant mouse IFNβ expressed in insect cells.

PubMed

Stifter, Sebastian A; Gould, Jodee A; Mangan, Niamh E; Reid, Hugh H; Rossjohn, Jamie; Hertzog, Paul J; de Weerd, Nicole A

2014-02-01

Interferon β (IFNβ) is a member of the type I interferon family of cytokines widely recognised for their anti-viral, anti-proliferative and immunomodulatory properties. Recombinant, biologically active forms of this cytokine are used clinically for the treatment of multiple sclerosis and in laboratories to study the role of this cytokine in health and disease. Established methods for expression of IFNβ utilise either bacterial systems from which the insoluble recombinant proteins must be refolded, or mammalian expression systems in which large volumes of cell culture are required for recovery of acceptable yields. Utilising the baculovirus expression system and Trichoplusia ni (Cabbage Looper) BTI-TN-5B1-4 cell line, we report a reproducible method for production and purification of milligram/litre quantities of biologically active murine IFNβ. Due to the design of our construct and the eukaryotic nature of insect cells, the resulting soluble protein is secreted allowing purification of the Histidine-tagged natively-folded protein from the culture supernatant. The IFNβ purification method described is a two-step process employing immobilised metal-ion affinity chromatography (IMAC) and reverse-phase high performance liquid chromatography (RP-HPLC) that results in production of significantly more purified IFNβ than any other reported eukaryotic-based expression system. Recombinant murine IFNβ produced by this method was natively folded and demonstrated hallmark type I interferon biological effects including antiviral and anti-proliferative activities, and induced genes characteristic of IFNβ activity in vivo. Recombinant IFNβ also had specific activity levels exceeding that of the commercially available equivalent. Together, our findings provide a method for production of highly pure, biologically active murine IFNβ. Copyright © 2013 Elsevier Inc. All rights reserved.

Practice Makes Pretty Good: Assessment of Primary Literature Reading Abilities across Multiple Large-Enrollment Biology Laboratory Courses

ERIC Educational Resources Information Center

Sato, Brian K.; Kadandale, Pavan; He, Wenliang; Murata, Paige M. N.; Latif, Yama; Warschauer, Mark

2014-01-01

Primary literature is essential for scientific communication and is commonly utilized in undergraduate biology education. Despite this, there is often little time spent "training" our students how to critically analyze a paper. To address this, we introduced a primary literature module in multiple upper-division laboratory courses. In…

MIMO: an efficient tool for molecular interaction maps overlap

PubMed Central

2013-01-01

Background Molecular pathways represent an ensemble of interactions occurring among molecules within the cell and between cells. The identification of similarities between molecular pathways across organisms and functions has a critical role in understanding complex biological processes. For the inference of such novel information, the comparison of molecular pathways requires to account for imperfect matches (flexibility) and to efficiently handle complex network topologies. To date, these characteristics are only partially available in tools designed to compare molecular interaction maps. Results Our approach MIMO (Molecular Interaction Maps Overlap) addresses the first problem by allowing the introduction of gaps and mismatches between query and template pathways and permits -when necessary- supervised queries incorporating a priori biological information. It then addresses the second issue by relying directly on the rich graph topology described in the Systems Biology Markup Language (SBML) standard, and uses multidigraphs to efficiently handle multiple queries on biological graph databases. The algorithm has been here successfully used to highlight the contact point between various human pathways in the Reactome database. Conclusions MIMO offers a flexible and efficient graph-matching tool for comparing complex biological pathways. PMID:23672344

Understanding Randomness and its Impact on Student Learning: Lessons Learned from Building the Biology Concept Inventory (BCI)

PubMed Central

Garvin-Doxas, Kathy

2008-01-01

While researching student assumptions for the development of the Biology Concept Inventory (BCI; http://bioliteracy.net), we found that a wide class of student difficulties in molecular and evolutionary biology appears to be based on deep-seated, and often unaddressed, misconceptions about random processes. Data were based on more than 500 open-ended (primarily) college student responses, submitted online and analyzed through our Ed's Tools system, together with 28 thematic and think-aloud interviews with students, and the responses of students in introductory and advanced courses to questions on the BCI. Students believe that random processes are inefficient, whereas biological systems are very efficient. They are therefore quick to propose their own rational explanations for various processes, from diffusion to evolution. These rational explanations almost always make recourse to a driver, e.g., natural selection in evolution or concentration gradients in molecular biology, with the process taking place only when the driver is present, and ceasing when the driver is absent. For example, most students believe that diffusion only takes place when there is a concentration gradient, and that the mutational processes that change organisms occur only in response to natural selection pressures. An understanding that random processes take place all the time and can give rise to complex and often counterintuitive behaviors is almost totally absent. Even students who have had advanced or college physics, and can discuss diffusion correctly in that context, cannot make the transfer to biological processes, and passing through multiple conventional biology courses appears to have little effect on their underlying beliefs. PMID:18519614

Synergistic Synthetic Biology: Units in Concert

PubMed Central

Trosset, Jean-Yves; Carbonell, Pablo

2013-01-01

Synthetic biology aims at translating the methods and strategies from engineering into biology in order to streamline the design and construction of biological devices through standardized parts. Modular synthetic biology devices are designed by means of an adequate elimination of cross-talk that makes circuits orthogonal and specific. To that end, synthetic constructs need to be adequately optimized through in silico modeling by choosing the right complement of genetic parts and by experimental tuning through directed evolution and craftsmanship. In this review, we consider an additional and complementary tool available to the synthetic biologist for innovative design and successful construction of desired circuit functionalities: biological synergies. Synergy is a prevalent emergent property in biological systems that arises from the concerted action of multiple factors producing an amplification or cancelation effect compared with individual actions alone. Synergies appear in domains as diverse as those involved in chemical and protein activity, polypharmacology, and metabolic pathway complementarity. In conventional synthetic biology designs, synergistic cross-talk between parts and modules is generally attenuated in order to verify their orthogonality. Synergistic interactions, however, can induce emergent behavior that might prove useful for synthetic biology applications, like in functional circuit design, multi-drug treatment, or in sensing and delivery devices. Synergistic design principles are therefore complementary to those coming from orthogonal design and may provide added value to synthetic biology applications. The appropriate modeling, characterization, and design of synergies between biological parts and units will allow the discovery of yet unforeseeable, novel synthetic biology applications. PMID:25022769

Synergistic Synthetic Biology: Units in Concert.

PubMed

Trosset, Jean-Yves; Carbonell, Pablo

2013-01-01

Synthetic biology aims at translating the methods and strategies from engineering into biology in order to streamline the design and construction of biological devices through standardized parts. Modular synthetic biology devices are designed by means of an adequate elimination of cross-talk that makes circuits orthogonal and specific. To that end, synthetic constructs need to be adequately optimized through in silico modeling by choosing the right complement of genetic parts and by experimental tuning through directed evolution and craftsmanship. In this review, we consider an additional and complementary tool available to the synthetic biologist for innovative design and successful construction of desired circuit functionalities: biological synergies. Synergy is a prevalent emergent property in biological systems that arises from the concerted action of multiple factors producing an amplification or cancelation effect compared with individual actions alone. Synergies appear in domains as diverse as those involved in chemical and protein activity, polypharmacology, and metabolic pathway complementarity. In conventional synthetic biology designs, synergistic cross-talk between parts and modules is generally attenuated in order to verify their orthogonality. Synergistic interactions, however, can induce emergent behavior that might prove useful for synthetic biology applications, like in functional circuit design, multi-drug treatment, or in sensing and delivery devices. Synergistic design principles are therefore complementary to those coming from orthogonal design and may provide added value to synthetic biology applications. The appropriate modeling, characterization, and design of synergies between biological parts and units will allow the discovery of yet unforeseeable, novel synthetic biology applications.

Computational immunology--from bench to virtual reality.

PubMed

Chan, Cliburn; Kepler, Thomas B

2007-02-01

Drinking from a fire-hose is an old cliché for the experience of learning basic and clinical sciences in medical school, and the pipe has been growing fatter at an alarming rate. Of course, it does not stop when one graduates; if anything, both the researcher and clinician are flooded with even more information. Slightly embarrassingly, while modern science is very good at generating new information, our ability to weave multiple strands of data into a useful and coherent story lags quite far behind. Bioinformatics, systems biology and computational medicine have arisen in recent years to address just this challenge. This essay is an introduction to the problem of data synthesis and integration in biology and medicine, and how the relatively new art of biological simulation can provide a new kind of map for understanding physiology and pathology. The nascent field of computational immunology will be used for illustration, but similar trends are occurring broadly across all of biology and medicine.

The Biological Connection Markup Language: a SBGN-compliant format for visualization, filtering and analysis of biological pathways.

PubMed

Beltrame, Luca; Calura, Enrica; Popovici, Razvan R; Rizzetto, Lisa; Guedez, Damariz Rivero; Donato, Michele; Romualdi, Chiara; Draghici, Sorin; Cavalieri, Duccio

2011-08-01

Many models and analysis of signaling pathways have been proposed. However, neither of them takes into account that a biological pathway is not a fixed system, but instead it depends on the organism, tissue and cell type as well as on physiological, pathological and experimental conditions. The Biological Connection Markup Language (BCML) is a format to describe, annotate and visualize pathways. BCML is able to store multiple information, permitting a selective view of the pathway as it exists and/or behave in specific organisms, tissues and cells. Furthermore, BCML can be automatically converted into data formats suitable for analysis and into a fully SBGN-compliant graphical representation, making it an important tool that can be used by both computational biologists and 'wet lab' scientists. The XML schema and the BCML software suite are freely available under the LGPL for download at http://bcml.dc-atlas.net. They are implemented in Java and supported on MS Windows, Linux and OS X.

Multichannel microformulators for massively parallel machine learning and automated design of biological experiments

NASA Astrophysics Data System (ADS)

Wikswo, John; Kolli, Aditya; Shankaran, Harish; Wagoner, Matthew; Mettetal, Jerome; Reiserer, Ronald; Gerken, Gregory; Britt, Clayton; Schaffer, David

Genetic, proteomic, and metabolic networks describing biological signaling can have 102 to 103 nodes. Transcriptomics and mass spectrometry can quantify 104 different dynamical experimental variables recorded from in vitro experiments with a time resolution approaching 1 s. It is difficult to infer metabolic and signaling models from such massive data sets, and it is unlikely that causality can be determined simply from observed temporal correlations. There is a need to design and apply specific system perturbations, which will be difficult to perform manually with 10 to 102 externally controlled variables. Machine learning and optimal experimental design can select an experiment that best discriminates between multiple conflicting models, but a remaining problem is to control in real time multiple variables in the form of concentrations of growth factors, toxins, nutrients and other signaling molecules. With time-division multiplexing, a microfluidic MicroFormulator (μF) can create in real time complex mixtures of reagents in volumes suitable for biological experiments. Initial 96-channel μF implementations control the exposure profile of cells in a 96-well plate to different temporal profiles of drugs; future experiments will include challenge compounds. Funded in part by AstraZeneca, NIH/NCATS HHSN271201600009C and UH3TR000491, and VIIBRE.

Development of hydrogels for regenerative engineering.

PubMed

Guan, Xiaofei; Avci-Adali, Meltem; Alarçin, Emine; Cheng, Hao; Kashaf, Sara Saheb; Li, Yuxiao; Chawla, Aditya; Jang, Hae Lin; Khademhosseini, Ali

2017-05-01

The aim of regenerative engineering is to restore complex tissues and biological systems through convergence in the fields of advanced biomaterials, stem cell science, and developmental biology. Hydrogels are one of the most attractive biomaterials for regenerative engineering, since they can be engineered into tissue mimetic 3D scaffolds to support cell growth due to their similarity to native extracellular matrix. Advanced nano- and micro-technologies have dramatically increased the ability to control properties and functionalities of hydrogel materials by facilitating biomimetic fabrication of more sophisticated compositions and architectures, thus extending our understanding of cell-matrix interactions at the nanoscale. With this perspective, this review discusses the most commonly used hydrogel materials and their fabrication strategies for regenerative engineering. We highlight the physical, chemical, and functional modulation of hydrogels to design and engineer biomimetic tissues based on recent achievements in nano- and micro-technologies. In addition, current hydrogel-based regenerative engineering strategies for treating multiple tissues, such as musculoskeletal, nervous and cardiac tissue, are also covered in this review. The interaction of multiple disciplines including materials science, cell biology, and chemistry, will further play an important role in the design of functional hydrogels for the regeneration of complex tissues. Copyright © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Nothing in Evolution Makes Sense Except in the Light of Genomics: Read-Write Genome Evolution as an Active Biological Process.

PubMed

Shapiro, James A

2016-06-08

The 21st century genomics-based analysis of evolutionary variation reveals a number of novel features impossible to predict when Dobzhansky and other evolutionary biologists formulated the neo-Darwinian Modern Synthesis in the middle of the last century. These include three distinct realms of cell evolution; symbiogenetic fusions forming eukaryotic cells with multiple genome compartments; horizontal organelle, virus and DNA transfers; functional organization of proteins as systems of interacting domains subject to rapid evolution by exon shuffling and exonization; distributed genome networks integrated by mobile repetitive regulatory signals; and regulation of multicellular development by non-coding lncRNAs containing repetitive sequence components. Rather than single gene traits, all phenotypes involve coordinated activity by multiple interacting cell molecules. Genomes contain abundant and functional repetitive components in addition to the unique coding sequences envisaged in the early days of molecular biology. Combinatorial coding, plus the biochemical abilities cells possess to rearrange DNA molecules, constitute a powerful toolbox for adaptive genome rewriting. That is, cells possess "Read-Write Genomes" they alter by numerous biochemical processes capable of rapidly restructuring cellular DNA molecules. Rather than viewing genome evolution as a series of accidental modifications, we can now study it as a complex biological process of active self-modification.

Nothing in Evolution Makes Sense Except in the Light of Genomics: Read–Write Genome Evolution as an Active Biological Process

PubMed Central

Shapiro, James A.

2016-01-01

The 21st century genomics-based analysis of evolutionary variation reveals a number of novel features impossible to predict when Dobzhansky and other evolutionary biologists formulated the neo-Darwinian Modern Synthesis in the middle of the last century. These include three distinct realms of cell evolution; symbiogenetic fusions forming eukaryotic cells with multiple genome compartments; horizontal organelle, virus and DNA transfers; functional organization of proteins as systems of interacting domains subject to rapid evolution by exon shuffling and exonization; distributed genome networks integrated by mobile repetitive regulatory signals; and regulation of multicellular development by non-coding lncRNAs containing repetitive sequence components. Rather than single gene traits, all phenotypes involve coordinated activity by multiple interacting cell molecules. Genomes contain abundant and functional repetitive components in addition to the unique coding sequences envisaged in the early days of molecular biology. Combinatorial coding, plus the biochemical abilities cells possess to rearrange DNA molecules, constitute a powerful toolbox for adaptive genome rewriting. That is, cells possess “Read–Write Genomes” they alter by numerous biochemical processes capable of rapidly restructuring cellular DNA molecules. Rather than viewing genome evolution as a series of accidental modifications, we can now study it as a complex biological process of active self-modification. PMID:27338490

ePlant: Visualizing and Exploring Multiple Levels of Data for Hypothesis Generation in Plant Biology[OPEN

PubMed Central

Waese, Jamie; Fan, Jim; Yu, Hans; Fucile, Geoffrey; Shi, Ruian; Cumming, Matthew; Town, Chris; Stuerzlinger, Wolfgang

2017-01-01

A big challenge in current systems biology research arises when different types of data must be accessed from separate sources and visualized using separate tools. The high cognitive load required to navigate such a workflow is detrimental to hypothesis generation. Accordingly, there is a need for a robust research platform that incorporates all data and provides integrated search, analysis, and visualization features through a single portal. Here, we present ePlant (http://bar.utoronto.ca/eplant), a visual analytic tool for exploring multiple levels of Arabidopsis thaliana data through a zoomable user interface. ePlant connects to several publicly available web services to download genome, proteome, interactome, transcriptome, and 3D molecular structure data for one or more genes or gene products of interest. Data are displayed with a set of visualization tools that are presented using a conceptual hierarchy from big to small, and many of the tools combine information from more than one data type. We describe the development of ePlant in this article and present several examples illustrating its integrative features for hypothesis generation. We also describe the process of deploying ePlant as an “app” on Araport. Building on readily available web services, the code for ePlant is freely available for any other biological species research. PMID:28808136

Regulation of gene expression by manipulating transcriptional repressor activity using a novel CoSRI technology.

PubMed

Xu, Yue; Li, Song Feng; Parish, Roger W

2017-07-01

Targeted gene manipulation is a central strategy for studying gene function and identifying related biological processes. However, a methodology for manipulating the regulatory motifs of transcription factors is lacking as these factors commonly possess multiple motifs (e.g. repression and activation motifs) which collaborate with each other to regulate multiple biological processes. We describe a novel approach designated conserved sequence-guided repressor inhibition (CoSRI) that can specifically reduce or abolish the repressive activities of transcription factors in vivo. The technology was evaluated using the chimeric MYB80-EAR transcription factor and subsequently the endogenous WUS transcription factor. The technology was employed to develop a reversible male sterility system applicable to hybrid seed production. In order to determine the capacity of the technology to regulate the activity of endogenous transcription factors, the WUS repressor was chosen. The WUS repression motif could be inhibited in vivo and the transformed plants exhibited the wus-1 phenotype. Consequently, the technology can be used to manipulate the activities of transcriptional repressor motifs regulating beneficial traits in crop plants and other eukaryotic organisms. © 2016 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

A pharma perspective on the systems medicine and pharmacology of inflammation.

PubMed

Lahoz-Beneytez, Julio; Schnizler, Katrin; Eissing, Thomas

2015-02-01

Biological systems are complex and comprehend multiple scales of organisation. Hence, holistic approaches are necessary to capture the behaviour of these entities from the molecular and cellular to the whole organism level. This also applies to the understanding and treatment of different diseases. Traditional systems biology has been successful in describing different biological phenomena at the cellular level, but it still lacks of a holistic description of the multi-scale interactions within the body. The importance of the physiological context is of particular interest in inflammation. Regulatory agencies have urged the scientific community to increase the translational power of bio-medical research and it has been recognised that modelling and simulation could be a path to follow. Interestingly, in pharma R&D, modelling and simulation has been employed since a long time ago. Systems pharmacology, and particularly physiologically based pharmacokinetic/pharmacodynamic models, serve as a suitable framework to integrate the available and emerging knowledge at different levels of the drug development process. Systems medicine and pharmacology of inflammation will potentially benefit from this framework in order to better understand inflammatory diseases and to help to transfer the vast knowledge on the molecular and cellular level into a more physiological context. Ultimately, this may lead to reliable predictions of clinical outcomes such as disease progression or treatment efficacy, contributing thereby to a better care of patients. Copyright © 2014 Elsevier Inc. All rights reserved.

Model reduction in mathematical pharmacology : Integration, reduction and linking of PBPK and systems biology models.

PubMed

Snowden, Thomas J; van der Graaf, Piet H; Tindall, Marcus J

2018-03-26

In this paper we present a framework for the reduction and linking of physiologically based pharmacokinetic (PBPK) models with models of systems biology to describe the effects of drug administration across multiple scales. To address the issue of model complexity, we propose the reduction of each type of model separately prior to being linked. We highlight the use of balanced truncation in reducing the linear components of PBPK models, whilst proper lumping is shown to be efficient in reducing typically nonlinear systems biology type models. The overall methodology is demonstrated via two example systems; a model of bacterial chemotactic signalling in Escherichia coli and a model of extracellular regulatory kinase activation mediated via the extracellular growth factor and nerve growth factor receptor pathways. Each system is tested under the simulated administration of three hypothetical compounds; a strong base, a weak base, and an acid, mirroring the parameterisation of pindolol, midazolam, and thiopental, respectively. Our method can produce up to an 80% decrease in simulation time, allowing substantial speed-up for computationally intensive applications including parameter fitting or agent based modelling. The approach provides a straightforward means to construct simplified Quantitative Systems Pharmacology models that still provide significant insight into the mechanisms of drug action. Such a framework can potentially bridge pre-clinical and clinical modelling - providing an intermediate level of model granularity between classical, empirical approaches and mechanistic systems describing the molecular scale.

Systems biology approaches and tools for analysis of interactomes and multi-target drugs.

PubMed

Schrattenholz, André; Groebe, Karlfried; Soskic, Vukic

2010-01-01

Systems biology is essentially a proteomic and epigenetic exercise because the relatively condensed information of genomes unfolds on the level of proteins. The flexibility of cellular architectures is not only mediated by a dazzling number of proteinaceous species but moreover by the kinetics of their molecular changes: The time scales of posttranslational modifications range from milliseconds to years. The genetic framework of an organism only provides the blue print of protein embodiments which are constantly shaped by external input. Indeed, posttranslational modifications of proteins represent the scope and velocity of these inputs and fulfil the requirements of integration of external spatiotemporal signal transduction inside an organism. The optimization of biochemical networks for this type of information processing and storage results in chemically extremely fine tuned molecular entities. The huge dynamic range of concentrations, the chemical diversity and the necessity of synchronisation of complex protein expression patterns pose the major challenge of systemic analysis of biological models. One further message is that many of the key reactions in living systems are essentially based on interactions of moderate affinities and moderate selectivities. This principle is responsible for the enormous flexibility and redundancy of cellular circuitries. In complex disorders such as cancer or neurodegenerative diseases, which initially appear to be rooted in relatively subtle dysfunctions of multimodal physiologic pathways, drug discovery programs based on the concept of high affinity/high specificity compounds ("one-target, one-disease"), which has been dominating the pharmaceutical industry for a long time, increasingly turn out to be unsuccessful. Despite improvements in rational drug design and high throughput screening methods, the number of novel, single-target drugs fell much behind expectations during the past decade, and the treatment of "complex diseases" remains a most pressing medical need. Currently, a change of paradigm can be observed with regard to a new interest in agents that modulate multiple targets simultaneously, essentially "dirty drugs." Targeting cellular function as a system rather than on the level of the single target, significantly increases the size of the drugable proteome and is expected to introduce novel classes of multi-target drugs with fewer adverse effects and toxicity. Multiple target approaches have recently been used to design medications against atherosclerosis, cancer, depression, psychosis and neurodegenerative diseases. A focussed approach towards "systemic" drugs will certainly require the development of novel computational and mathematical concepts for appropriate modelling of complex data. But the key is the extraction of relevant molecular information from biological systems by implementing rigid statistical procedures to differential proteomic analytics.

A nano grating tunable MEMS optical filter for high-speed on-chip multispectral fluorescent detection.

PubMed

Truxal, Steven C; Huang, Nien-Tsu; Kurabayashi, Katsuo

2009-01-01

We report a microelectromechanical (MEMS) tunable optical filter and its integration in a fluorescence microscope for high speed on-chip spectral measurements. This integration allows for measurements of any fluorescence sample placed onto the microscope stage. We demonstrate the system capabilities by taking spectral measurements of multicolor fluorescent beads and fluorescently labeled cells passing through a microfluidic cytometer. The system has applications in biological studies where the measurement of multiple fluorescent peaks is restricted by the detection method's speed and sensitivity.

HPC AND GRID COMPUTING FOR INTEGRATIVE BIOMEDICAL RESEARCH

PubMed Central

Kurc, Tahsin; Hastings, Shannon; Kumar, Vijay; Langella, Stephen; Sharma, Ashish; Pan, Tony; Oster, Scott; Ervin, David; Permar, Justin; Narayanan, Sivaramakrishnan; Gil, Yolanda; Deelman, Ewa; Hall, Mary; Saltz, Joel

2010-01-01

Integrative biomedical research projects query, analyze, and integrate many different data types and make use of datasets obtained from measurements or simulations of structure and function at multiple biological scales. With the increasing availability of high-throughput and high-resolution instruments, the integrative biomedical research imposes many challenging requirements on software middleware systems. In this paper, we look at some of these requirements using example research pattern templates. We then discuss how middleware systems, which incorporate Grid and high-performance computing, could be employed to address the requirements. PMID:20107625

Protein location prediction using atomic composition and global features of the amino acid sequence

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

Cherian, Betsy Sheena, E-mail: betsy.skb@gmail.com; Nair, Achuthsankar S.

2010-01-22

Subcellular location of protein is constructive information in determining its function, screening for drug candidates, vaccine design, annotation of gene products and in selecting relevant proteins for further studies. Computational prediction of subcellular localization deals with predicting the location of a protein from its amino acid sequence. For a computational localization prediction method to be more accurate, it should exploit all possible relevant biological features that contribute to the subcellular localization. In this work, we extracted the biological features from the full length protein sequence to incorporate more biological information. A new biological feature, distribution of atomic composition is effectivelymore » used with, multiple physiochemical properties, amino acid composition, three part amino acid composition, and sequence similarity for predicting the subcellular location of the protein. Support Vector Machines are designed for four modules and prediction is made by a weighted voting system. Our system makes prediction with an accuracy of 100, 82.47, 88.81 for self-consistency test, jackknife test and independent data test respectively. Our results provide evidence that the prediction based on the biological features derived from the full length amino acid sequence gives better accuracy than those derived from N-terminal alone. Considering the features as a distribution within the entire sequence will bring out underlying property distribution to a greater detail to enhance the prediction accuracy.« less

Are viruses alive? The replicator paradigm sheds decisive light on an old but misguided question

PubMed Central

Koonin, Eugene V.; Starokadomskyy, Petro

2016-01-01

The question whether or not “viruses are alive” has caused considerable debate over many years. Yet, the question is effectively without substance because the answer depends entirely on the definition of life or the state of “being alive” that is bound to be arbitrary. In contrast, the status of viruses among biological entities is readily defined within the replicator paradigm. All biological replicators form a continuum along the selfishness-cooperativity axis, from the completely selfish to fully cooperative forms. Within this range, typical, lytic viruses represent the selfish extreme whereas temperate viruses and various mobile elements occupy positions closer to the middle of the range. Selfish replicators not only belong to the biological realm but are intrinsic to any evolving system of replicators. No such system can evolve without the emergence of parasites, and moreover, parasites drive the evolution of biological complexity at multiple levels. The history of life is a story of parasite-host coevolution that includes both the incessant arms race and various forms of cooperation. All organisms are communities of interacting, coevolving replicators of different classes. A complete theory of replicator coevolution remains to be developed, but it appears likely that not only the differentiation between selfish and cooperative replicators but the emergence of the entire range of replication strategies, from selfish to cooperative, is intrinsic to biological evolution. PMID:26965225

Radiobiological concepts for treatment planning of schemes that combines external beam radiotherapy and systemic targeted radiotherapy

NASA Astrophysics Data System (ADS)

Fabián Calderón Marín, Carlos; González González, Joaquín Jorge; Laguardia, Rodolfo Alfonso

2017-09-01

The combination of radiotherapy modalities with external bundles and systemic radiotherapy (CIERT) could be a reliable alternative for patients with multiple lesions or those where treatment planning maybe difficult because organ(s)-at-risk (OARs) constraints. Radiobiological models should have the capacity for predicting the biological irradiation response considering the differences in the temporal pattern of dose delivering in both modalities. Two CIERT scenarios were studied: sequential combination in which one modality is executed following the other one and concurrent combination when both modalities are running simultaneously. Expressions are provided for calculation of the dose-response magnitudes Tumor Control Probability (TCP) and Normal Tissue Complication Probability (NTCP). General results on radiobiological modeling using the linear-quadratic (LQ) model are also discussed. Inter-subject variation of radiosensitivity and volume irradiation effect in CIERT are studied. OARs should be under control during the planning in concurrent CIERT treatment as the administered activity is increased. The formulation presented here may be used for biological evaluation of prescriptions and biological treatment planning of CIERT schemes in clinical situation.

Biological and psychological markers of stress in humans: focus on the Trier Social Stress Test.

PubMed

Allen, Andrew P; Kennedy, Paul J; Cryan, John F; Dinan, Timothy G; Clarke, Gerard

2014-01-01

Validated biological and psychological markers of acute stress in humans are an important tool in translational research. The Trier Social Stress Test (TSST), involving public interview and mental arithmetic performance, is among the most popular methods of inducing acute stress in experimental settings, and reliably increases hypothalamic-pituitary-adrenal axis activation. However, although much research has focused on HPA axis activity, the TSST also affects the sympathetic-adrenal-medullary system, the immune system, cardiovascular outputs, gastric function and cognition. We critically assess the utility of different biological and psychological markers, with guidance for future research, and discuss factors which can moderate TSST effects. We outline the effects of the TSST in stress-related disorders, and if these responses can be abrogated by pharmacological and psychological treatments. Modified TSST protocols are discussed, and the TSST is compared to alternative methods of inducing acute stress. Our analysis suggests that multiple readouts are necessary to derive maximum information; this strategy will enhance our understanding of the psychobiology of stress and provide the means to assess novel therapeutic agents. Copyright © 2013 Elsevier Ltd. All rights reserved.

Convergence Science in a Nano World

PubMed Central

Cady, Nathaniel

2013-01-01

Convergence is a new paradigm that brings together critical advances in the life sciences, physical sciences and engineering. Going beyond traditional “interdisciplinary” studies, “convergence” describes the culmination of truly integrated research and development, yielding revolutionary advances in both scientific research and new technologies. At its core, nanotechnology embodies these elements of convergence science by bringing together multiple disciplines with the goal of creating innovative and groundbreaking technologies. In the biological and biomedical sciences, nanotechnology research has resulted in dramatic improvements in sensors, diagnostics, imaging, and even therapeutics. In particular, there is a current push to examine the interface between the biological world and micro/nano-scale systems. For example, my laboratory is developing novel strategies for spatial patterning of biomolecules, electrical and optical biosensing, nanomaterial delivery systems, cellular patterning techniques, and the study of cellular interactions with nano-structured surfaces. In this seminar, I will give examples of how convergent research is being applied to three major areas of biological research &endash; cancer diagnostics, microbiology, and DNA-based biosensing. These topics will be presented as case studies, showing the benefits (and challenges) of multi-disciplinary, convergent research and development.

The Rise of Mitochondria in Medicine

PubMed Central

Picard, Martin; Wallace, Douglas C; Burelle, Yan

2016-01-01

Once considered exclusively the cell's powerhouse, mitochondria are now recognized to perform multiple essential cellular functions beyond energy production, impacting most areas of cell biology and medicine. Since the emergence of molecular biology and the discovery of pathogenic mitochondrial DNA defects in the 1980's, research advances have revealed a number of common human diseases which share an underlying pathogenesis involving mitochondrial dysfunction. Mitochondria undergo function-defining dynamic shape changes, communicate with each other, regulate gene expression within the nucleus, modulate synaptic transmission within the brain, release molecules that contribute to oncogenic transformation and trigger inflammatory responses systemically, and influence the regulation of complex physiological systems. Novel “mitopathogenic” mechanisms are thus being uncovered across a number of medical disciplines including genetics, oncology, neurology, immunology, and critical care medicine. Increasing knowledge of the bioenergetic aspects of human disease has provided new opportunities for diagnosis, therapy, prevention, and in connecting various domains of medicine. In this article, we overview specific aspects of mitochondrial biology that have contributed to – and likely will continue to enhance the progress of modern medicine. PMID:27423788

Automatic Visual Tracking and Social Behaviour Analysis with Multiple Mice

PubMed Central

Giancardo, Luca; Sona, Diego; Huang, Huiping; Sannino, Sara; Managò, Francesca; Scheggia, Diego; Papaleo, Francesco; Murino, Vittorio

2013-01-01

Social interactions are made of complex behavioural actions that might be found in all mammalians, including humans and rodents. Recently, mouse models are increasingly being used in preclinical research to understand the biological basis of social-related pathologies or abnormalities. However, reliable and flexible automatic systems able to precisely quantify social behavioural interactions of multiple mice are still missing. Here, we present a system built on two components. A module able to accurately track the position of multiple interacting mice from videos, regardless of their fur colour or light settings, and a module that automatically characterise social and non-social behaviours. The behavioural analysis is obtained by deriving a new set of specialised spatio-temporal features from the tracker output. These features are further employed by a learning-by-example classifier, which predicts for each frame and for each mouse in the cage one of the behaviours learnt from the examples given by the experimenters. The system is validated on an extensive set of experimental trials involving multiple mice in an open arena. In a first evaluation we compare the classifier output with the independent evaluation of two human graders, obtaining comparable results. Then, we show the applicability of our technique to multiple mice settings, using up to four interacting mice. The system is also compared with a solution recently proposed in the literature that, similarly to us, addresses the problem with a learning-by-examples approach. Finally, we further validated our automatic system to differentiate between C57B/6J (a commonly used reference inbred strain) and BTBR T+tf/J (a mouse model for autism spectrum disorders). Overall, these data demonstrate the validity and effectiveness of this new machine learning system in the detection of social and non-social behaviours in multiple (>2) interacting mice, and its versatility to deal with different experimental settings and scenarios. PMID:24066146

Genotet: An Interactive Web-based Visual Exploration Framework to Support Validation of Gene Regulatory Networks.

PubMed

Yu, Bowen; Doraiswamy, Harish; Chen, Xi; Miraldi, Emily; Arrieta-Ortiz, Mario Luis; Hafemeister, Christoph; Madar, Aviv; Bonneau, Richard; Silva, Cláudio T

2014-12-01

Elucidation of transcriptional regulatory networks (TRNs) is a fundamental goal in biology, and one of the most important components of TRNs are transcription factors (TFs), proteins that specifically bind to gene promoter and enhancer regions to alter target gene expression patterns. Advances in genomic technologies as well as advances in computational biology have led to multiple large regulatory network models (directed networks) each with a large corpus of supporting data and gene-annotation. There are multiple possible biological motivations for exploring large regulatory network models, including: validating TF-target gene relationships, figuring out co-regulation patterns, and exploring the coordination of cell processes in response to changes in cell state or environment. Here we focus on queries aimed at validating regulatory network models, and on coordinating visualization of primary data and directed weighted gene regulatory networks. The large size of both the network models and the primary data can make such coordinated queries cumbersome with existing tools and, in particular, inhibits the sharing of results between collaborators. In this work, we develop and demonstrate a web-based framework for coordinating visualization and exploration of expression data (RNA-seq, microarray), network models and gene-binding data (ChIP-seq). Using specialized data structures and multiple coordinated views, we design an efficient querying model to support interactive analysis of the data. Finally, we show the effectiveness of our framework through case studies for the mouse immune system (a dataset focused on a subset of key cellular functions) and a model bacteria (a small genome with high data-completeness).

On-chip wavelength multiplexed detection of cancer DNA biomarkers in blood

PubMed Central

Cai, H.; Stott, M. A.; Ozcelik, D.; Parks, J. W.; Hawkins, A. R.; Schmidt, H.

2016-01-01

We have developed an optofluidic analysis system that processes biomolecular samples starting from whole blood and then analyzes and identifies multiple targets on a silicon-based molecular detection platform. We demonstrate blood filtration, sample extraction, target enrichment, and fluorescent labeling using programmable microfluidic circuits. We detect and identify multiple targets using a spectral multiplexing technique based on wavelength-dependent multi-spot excitation on an antiresonant reflecting optical waveguide chip. Specifically, we extract two types of melanoma biomarkers, mutated cell-free nucleic acids —BRAFV600E and NRAS, from whole blood. We detect and identify these two targets simultaneously using the spectral multiplexing approach with up to a 96% success rate. These results point the way toward a full front-to-back chip-based optofluidic compact system for high-performance analysis of complex biological samples. PMID:28058082

Ion distributions in electrolyte confined by multiple dielectric interfaces

NASA Astrophysics Data System (ADS)

Jing, Yufei; Zwanikken, Jos W.; Jadhao, Vikram; de La Cruz, Monica

2014-03-01

The distribution of ions at dielectric interfaces between liquids characterized by different dielectric permittivities is crucial to nanoscale assembly processes in many biological and synthetic materials such as cell membranes, colloids and oil-water emulsions. The knowledge of ionic structure of these systems is also exploited in energy storage devices such as double-layer super-capacitors. The presence of multiple dielectric interfaces often complicates computing the desired ionic distributions via simulations or theory. Here, we use coarse-grained models to compute the ionic distributions in a system of electrolyte confined by two planar dielectric interfaces using Car-Parrinello molecular dynamics simulations and liquid state theory. We compute the density profiles for various electrolyte concentrations, stoichiometric ratios and dielectric contrasts. The explanations for the trends in these profiles and discuss their effects on the behavior of the confined charged fluid are also presented.

Evolution of complex adaptations in molecular systems

PubMed Central

Pál, Csaba; Papp, Balázs

2017-01-01

A central challenge in evolutionary biology concerns the mechanisms by which complex adaptations arise. Such adaptations depend on the fixation of multiple, highly specific mutations, where intermediate stages of evolution seemingly provide little or no benefit. It is generally assumed that the establishment of complex adaptations is very slow in nature, as evolution of such traits demands special population genetic or environmental circumstances. However, blueprints of complex adaptations in molecular systems are pervasive, indicating that they can readily evolve. We discuss the prospects and limitations of non-adaptive scenarios, which assume multiple neutral or deleterious steps in the evolution of complex adaptations. Next, we examine how complex adaptations can evolve by natural selection in changing environment. Finally, we argue that molecular ’springboards’, such as phenotypic heterogeneity and promiscuous interactions facilitate this process by providing access to new adaptive paths. PMID:28782044

A dynamic bead-based microarray for parallel DNA detection

NASA Astrophysics Data System (ADS)

Sochol, R. D.; Casavant, B. P.; Dueck, M. E.; Lee, L. P.; Lin, L.

2011-05-01

A microfluidic system has been designed and constructed by means of micromachining processes to integrate both microfluidic mixing of mobile microbeads and hydrodynamic microbead arraying capabilities on a single chip to simultaneously detect multiple bio-molecules. The prototype system has four parallel reaction chambers, which include microchannels of 18 × 50 µm2 cross-sectional area and a microfluidic mixing section of 22 cm length. Parallel detection of multiple DNA oligonucleotide sequences was achieved via molecular beacon probes immobilized on polystyrene microbeads of 16 µm diameter. Experimental results show quantitative detection of three distinct DNA oligonucleotide sequences from the Hepatitis C viral (HCV) genome with single base-pair mismatch specificity. Our dynamic bead-based microarray offers an effective microfluidic platform to increase parallelization of reactions and improve microbead handling for various biological applications, including bio-molecule detection, medical diagnostics and drug screening.

Multistability with a Metastable Mixed State

NASA Astrophysics Data System (ADS)

Sneppen, Kim; Mitarai, Namiko

2012-09-01

Complex dynamical systems often show multiple metastable states. In macroevolution, such behavior is suggested by punctuated equilibrium and discrete geological epochs. In molecular biology, bistability is found in epigenetics and in the many mutually exclusive states that a human cell can take. Sociopolitical systems can be single-party regimes or a pluralism of balancing political fractions. To introduce multistability, we suggest a model system of D mutually exclusive microstates that battle for dominance in a large system. Assuming one common intermediate state, we obtain D+1 metastable macrostates for the system, one of which is a self-reinforced mixture of all D+1 microstates. Robustness of this metastable mixed state increases with diversity D.

CEBS object model for systems biology data, SysBio-OM.

PubMed

Xirasagar, Sandhya; Gustafson, Scott; Merrick, B Alex; Tomer, Kenneth B; Stasiewicz, Stanley; Chan, Denny D; Yost, Kenneth J; Yates, John R; Sumner, Susan; Xiao, Nianqing; Waters, Michael D

2004-09-01

To promote a systems biology approach to understanding the biological effects of environmental stressors, the Chemical Effects in Biological Systems (CEBS) knowledge base is being developed to house data from multiple complex data streams in a systems friendly manner that will accommodate extensive querying from users. Unified data representation via a single object model will greatly aid in integrating data storage and management, and facilitate reuse of software to analyze and display data resulting from diverse differential expression or differential profile technologies. Data streams include, but are not limited to, gene expression analysis (transcriptomics), protein expression and protein-protein interaction analysis (proteomics) and changes in low molecular weight metabolite levels (metabolomics). To enable the integration of microarray gene expression, proteomics and metabolomics data in the CEBS system, we designed an object model, Systems Biology Object Model (SysBio-OM). The model is comprehensive and leverages other open source efforts, namely the MicroArray Gene Expression Object Model (MAGE-OM) and the Proteomics Experiment Data Repository (PEDRo) object model. SysBio-OM is designed by extending MAGE-OM to represent protein expression data elements (including those from PEDRo), protein-protein interaction and metabolomics data. SysBio-OM promotes the standardization of data representation and data quality by facilitating the capture of the minimum annotation required for an experiment. Such standardization refines the accuracy of data mining and interpretation. The open source SysBio-OM model, which can be implemented on varied computing platforms is presented here. A universal modeling language depiction of the entire SysBio-OM is available at http://cebs.niehs.nih.gov/SysBioOM/. The Rational Rose object model package is distributed under an open source license that permits unrestricted academic and commercial use and is available at http://cebs.niehs.nih.gov/cebsdownloads. The database and interface are being built to implement the model and will be available for public use at http://cebs.niehs.nih.gov.

A perturbation analysis of a mechanical model for stable spatial patterning in embryology

NASA Astrophysics Data System (ADS)

Bentil, D. E.; Murray, J. D.

1992-12-01

We investigate a mechanical cell-traction mechanism that generates stationary spatial patterns. A linear analysis highlights the model's potential for these heterogeneous solutions. We use multiple-scale perturbation techniques to study the evolution of these solutions and compare our solutions with numerical simulations of the model system. We discuss some potential biological applications among which are the formation of ridge patterns, dermatoglyphs, and wound healing.

The Multiple Futures of Racism--Beyond Color and Culture, toward a New Paradigm for Resolution in the Third Millennium.

ERIC Educational Resources Information Center

Rosado, Caleb

The paper asserts that racism is still one of the most pervasive social evils in the world. Part of the problem is that attempts to eliminate racism have focused on surface differences of race, color, and biological supremacy. Such attempts do not get to the root of the problem, the deep-level value and belief systems that undergird racism. This…

PRISMATIC: Unified Hierarchical Probabilistic Verification Tool

DTIC Science & Technology

2011-09-01

security protocols such as for anonymity and quantum cryptography ; and biological reaction pathways. PRISM is currently the leading probabilistic...a whole will only deadlock and fail with a probability ≤ p/2. The assumption allows us to partition the overall system verification problem into two ...run on any port using the standard HTTP protocol. In this way multiple instances of the PRISMATIC web service can respond to different requests when

Structure-function relations in physiology education: Where's the mechanism?

PubMed

Lira, Matthew E; Gardner, Stephanie M

2017-06-01

Physiology demands systems thinking: reasoning within and between levels of biological organization and across different organ systems. Many physiological mechanisms explain how structures and their properties interact at one level of organization to produce emergent functions at a higher level of organization. Current physiology principles, such as structure-function relations, selectively neglect mechanisms by not mentioning this term explicitly. We explored how students characterized mechanisms and functions to shed light on how students make sense of these terms. Students characterized mechanisms as 1 ) processes that occur at levels of organization lower than that of functions; and 2 ) as detailed events with many steps involved. We also found that students produced more variability in how they characterized functions compared with mechanisms: students characterized functions in relation to multiple levels of organization and multiple definitions. We interpret these results as evidence that students see mechanisms as holding a more narrow definition than used in the biological sciences, and that students struggle to coordinate and distinguish mechanisms from functions due to cognitive processes germane to learning in many domains. We offer the instructional suggestion that we scaffold student learning by affording students opportunities to relate and also distinguish between these terms so central to understanding physiology. Copyright © 2017 the American Physiological Society.

Recent Achievements in Characterizing the Histone Code and Approaches to Integrating Epigenomics and Systems Biology.

PubMed

Janssen, K A; Sidoli, S; Garcia, B A

2017-01-01

Functional epigenetic regulation occurs by dynamic modification of chromatin, including genetic material (i.e., DNA methylation), histone proteins, and other nuclear proteins. Due to the highly complex nature of the histone code, mass spectrometry (MS) has become the leading technique in identification of single and combinatorial histone modifications. MS has now overcome antibody-based strategies due to its automation, high resolution, and accurate quantitation. Moreover, multiple approaches to analysis have been developed for global quantitation of posttranslational modifications (PTMs), including large-scale characterization of modification coexistence (middle-down and top-down proteomics), which is not currently possible with any other biochemical strategy. Recently, our group and others have simplified and increased the effectiveness of analyzing histone PTMs by improving multiple MS methods and data analysis tools. This review provides an overview of the major achievements in the analysis of histone PTMs using MS with a focus on the most recent improvements. We speculate that the workflow for histone analysis at its state of the art is highly reliable in terms of identification and quantitation accuracy, and it has the potential to become a routine method for systems biology thanks to the possibility of integrating histone MS results with genomics and proteomics datasets. © 2017 Elsevier Inc. All rights reserved.

Network Analysis of Epidermal Growth Factor Signaling Using Integrated Genomic, Proteomic and Phosphorylation Data

PubMed Central

Waters, Katrina M.; Liu, Tao; Quesenberry, Ryan D.; Willse, Alan R.; Bandyopadhyay, Somnath; Kathmann, Loel E.; Weber, Thomas J.; Smith, Richard D.; Wiley, H. Steven; Thrall, Brian D.

2012-01-01

To understand how integration of multiple data types can help decipher cellular responses at the systems level, we analyzed the mitogenic response of human mammary epithelial cells to epidermal growth factor (EGF) using whole genome microarrays, mass spectrometry-based proteomics and large-scale western blots with over 1000 antibodies. A time course analysis revealed significant differences in the expression of 3172 genes and 596 proteins, including protein phosphorylation changes measured by western blot. Integration of these disparate data types showed that each contributed qualitatively different components to the observed cell response to EGF and that varying degrees of concordance in gene expression and protein abundance measurements could be linked to specific biological processes. Networks inferred from individual data types were relatively limited, whereas networks derived from the integrated data recapitulated the known major cellular responses to EGF and exhibited more highly connected signaling nodes than networks derived from any individual dataset. While cell cycle regulatory pathways were altered as anticipated, we found the most robust response to mitogenic concentrations of EGF was induction of matrix metalloprotease cascades, highlighting the importance of the EGFR system as a regulator of the extracellular environment. These results demonstrate the value of integrating multiple levels of biological information to more accurately reconstruct networks of cellular response. PMID:22479638

Exploring the MACH Model’s Potential as a Metacognitive Tool to Help Undergraduate Students Monitor Their Explanations of Biological Mechanisms

PubMed Central

Trujillo, Caleb M.; Anderson, Trevor R.; Pelaez, Nancy J.

2016-01-01

When undergraduate biology students learn to explain biological mechanisms, they face many challenges and may overestimate their understanding of living systems. Previously, we developed the MACH model of four components used by expert biologists to explain mechanisms: Methods, Analogies, Context, and How. This study explores the implementation of the model in an undergraduate biology classroom as an educational tool to address some of the known challenges. To find out how well students’ written explanations represent components of the MACH model before and after they were taught about it and why students think the MACH model was useful, we conducted an exploratory multiple case study with four interview participants. We characterize how two students explained biological mechanisms before and after a teaching intervention that used the MACH components. Inductive analysis of written explanations and interviews showed that MACH acted as an effective metacognitive tool for all four students by helping them to monitor their understanding, communicate explanations, and identify explanatory gaps. Further research, though, is needed to more fully substantiate the general usefulness of MACH for promoting students’ metacognition about their understanding of biological mechanisms. PMID:27252295

Do Sophisticated Epistemic Beliefs Predict Meaningful Learning? Findings from a Structural Equation Model of Undergraduate Biology Learning

ERIC Educational Resources Information Center

Lee, Silvia Wen-Yu; Liang, Jyh-Chong; Tsai, Chin-Chung

2016-01-01

This study investigated the relationships among college students' epistemic beliefs in biology (EBB), conceptions of learning biology (COLB), and strategies of learning biology (SLB). EBB includes four dimensions, namely "multiple-source," "uncertainty," "development," and "justification." COLB is further…

μOrgano: A Lego®-Like Plug & Play System for Modular Multi-Organ-Chips.

PubMed

Loskill, Peter; Marcus, Sivan G; Mathur, Anurag; Reese, Willie Mae; Healy, Kevin E

2015-01-01

Human organ-on-a-chip systems for drug screening have evolved as feasible alternatives to animal models, which are unreliable, expensive, and at times erroneous. While chips featuring single organs can be of great use for both pharmaceutical testing and basic organ-level studies, the huge potential of the organ-on-a-chip technology is revealed by connecting multiple organs on one chip to create a single integrated system for sophisticated fundamental biological studies and devising therapies for disease. Furthermore, since most organ-on-a-chip systems require special protocols with organ-specific media for the differentiation and maturation of the tissues, multi-organ systems will need to be temporally customizable and flexible in terms of the time point of connection of the individual organ units. We present a customizable Lego®-like plug & play system, μOrgano, which enables initial individual culture of single organ-on-a-chip systems and subsequent connection to create integrated multi-organ microphysiological systems. As a proof of concept, the μOrgano system was used to connect multiple heart chips in series with excellent cell viability and spontaneously physiological beat rates.

μOrgano: A Lego®-Like Plug & Play System for Modular Multi-Organ-Chips

PubMed Central

Loskill, Peter; Marcus, Sivan G.; Mathur, Anurag; Reese, Willie Mae; Healy, Kevin E.

2015-01-01

Human organ-on-a-chip systems for drug screening have evolved as feasible alternatives to animal models, which are unreliable, expensive, and at times erroneous. While chips featuring single organs can be of great use for both pharmaceutical testing and basic organ-level studies, the huge potential of the organ-on-a-chip technology is revealed by connecting multiple organs on one chip to create a single integrated system for sophisticated fundamental biological studies and devising therapies for disease. Furthermore, since most organ-on-a-chip systems require special protocols with organ-specific media for the differentiation and maturation of the tissues, multi-organ systems will need to be temporally customizable and flexible in terms of the time point of connection of the individual organ units. We present a customizable Lego®-like plug & play system, μOrgano, which enables initial individual culture of single organ-on-a-chip systems and subsequent connection to create integrated multi-organ microphysiological systems. As a proof of concept, the μOrgano system was used to connect multiple heart chips in series with excellent cell viability and spontaneously physiological beat rates. PMID:26440672

Clinical features and pathophysiology of Complex Regional Pain Syndrome – current state of the art

PubMed Central

Marinus, Johan; Moseley, G. Lorimer; Birklein, Frank; Baron, Ralf; Maihöfner, Christian; Kingery, Wade S.; van Hilten, Jacobus J.

2017-01-01

That a minor injury can trigger a complex regional pain syndrome (CRPS) - multiple system dysfunction, severe and often chronic pain and disability - has fascinated scientists and perplexed clinicians for decades. However, substantial advances across several medical disciplines have recently increased our understanding of CRPS. Compelling evidence implicates biological pathways that underlie aberrant inflammation, vasomotor dysfunction, and maladaptive neuroplasticity in the clinical features of CRPS. Collectively, the evidence points to CRPS being a multifactorial disorder that is associated with an aberrant host response to tissue injury. Varying susceptibility to perturbed regulation of any of the underlying biological pathways probably accounts for the clinical heterogeneity of CRPS. PMID:21683929

Demystified … Nitric oxide

PubMed Central

Stuart-Smith, K

2002-01-01

The discovery of nitric oxide (NO) demonstrated that cells could communicate via the manufacture and local diffusion of an unstable lipid soluble molecule. Since the original demonstration of the vascular relaxant properties of endothelium derived NO, this fascinating molecule has been shown to have multiple, complex roles within many biological systems. This review cannot hope to cover all of the recent advances in NO biology, but seeks to place the discovery of NO in its historical context, and show how far our understanding has come in the past 20 years. The role of NO in mitochondrial respiration, and consequently in oxidative stress, is described in detail because these processes probably underline the importance of NO in the development of disease. PMID:12456772

Collective cell migration: a physics perspective

NASA Astrophysics Data System (ADS)

Hakim, Vincent; Silberzan, Pascal

2017-07-01

Cells have traditionally been viewed either as independently moving entities or as somewhat static parts of tissues. However, it is now clear that in many cases, multiple cells coordinate their motions and move as collective entities. Well-studied examples comprise development events, as well as physiological and pathological situations. Different ex vivo model systems have also been investigated. Several recent advances have taken place at the interface between biology and physics, and have benefitted from progress in imaging and microscopy, from the use of microfabrication techniques, as well as from the introduction of quantitative tools and models. We review these interesting developments in quantitative cell biology that also provide rich examples of collective out-of-equilibrium motion.

Enabling a systems biology knowledgebase with gaggle and firegoose

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

Baliga, Nitin S.

The overall goal of this project was to extend the existing Gaggle and Firegoose systems to develop an open-source technology that runs over the web and links desktop applications with many databases and software applications. This technology would enable researchers to incorporate workflows for data analysis that can be executed from this interface to other online applications. The four specific aims were to (1) provide one-click mapping of genes, proteins, and complexes across databases and species; (2) enable multiple simultaneous workflows; (3) expand sophisticated data analysis for online resources; and enhance open-source development of the Gaggle-Firegoose infrastructure. Gaggle is anmore » open-source Java software system that integrates existing bioinformatics programs and data sources into a user-friendly, extensible environment to allow interactive exploration, visualization, and analysis of systems biology data. Firegoose is an extension to the Mozilla Firefox web browser that enables data transfer between websites and desktop tools including Gaggle. In the last phase of this funding period, we have made substantial progress on development and application of the Gaggle integration framework. We implemented the workspace to the Network Portal. Users can capture data from Firegoose and save them to the workspace. Users can create workflows to start multiple software components programmatically and pass data between them. Results of analysis can be saved to the cloud so that they can be easily restored on any machine. We also developed the Gaggle Chrome Goose, a plugin for the Google Chrome browser in tandem with an opencpu server in the Amazon EC2 cloud. This allows users to interactively perform data analysis on a single web page using the R packages deployed on the opencpu server. The cloud-based framework facilitates collaboration between researchers from multiple organizations. We have made a number of enhancements to the cmonkey2 application to enable and improve the integration within different environments, and we have created a new tools pipeline for generating EGRIN2 models in a largely automated way.« less

Cutaneous sarcoidosis successfully treated with alefacept.

PubMed

Garcia-Zuazaga, Jorge; Korman, Neil J

2006-01-01

Sarcoidosis is a systemic granulomatous disease of unknown etiology that affects multiple organ systems, including the pulmonary, lymphatic, skeletal, and integumentary systems. Improved understanding of the intrinsic immunology and molecular biology in sarcoidosis can be applied to the treatment of this disease. Alefacept is a human fusion protein consisting of the extracellular domain of leukocyte function-associated antigen 3 fused with the Fc portion of human immunoglobulin G1. It works by blocking the interaction between antigen-presenting cells and T cells to inhibit activation and by inducing apoptosis of CD4+ T cells. In this case report, we describe a 46-year-old patient with recalcitrant lupus pernio who was successfully treated with alefacept. To determine whether T-cell inhibition, specifically the use of alefacept, may be used to treat a patient with recalcitrant cutaneous sarcoidosis. Case report. There was a modest clinical improvement after 8 weeks of intramuscular injections of alefacept. This case report provides further evidence of successful treatment of sarcoidosis with biologic agents directed against T-lymphocyte activation.

Induced mutation and epigenetics modification in plants for crop improvement by targeting CRISPR/Cas9 technology.

PubMed

Khan, Muhammad Hafeez Ullah; Khan, Shahid U; Muhammad, Ali; Hu, Limin; Yang, Yang; Fan, Chuchuan

2018-06-01

Clustered regularly interspaced palindromic repeats associated protein Cas9 (CRISPR-Cas9), originally an adaptive immunity system of prokaryotes, is revolutionizing genome editing technologies with minimal off-targets in the present era. The CRISPR/Cas9 is now highly emergent, advanced, and highly specific tool for genome engineering. The technology is widely used to animal and plant genomes to achieve desirable results. The present review will encompass how CRISPR-Cas9 is revealing its beneficial role in characterizing plant genetic functions, genomic rearrangement, how it advances the site-specific mutagenesis, and epigenetics modification in plants to improve the yield of field crops with minimal side-effects. The possible pitfalls of using and designing CRISPR-Cas9 for plant genome editing are also discussed for its more appropriate applications in plant biology. Therefore, CRISPR/Cas9 system has multiple benefits that mostly scientists select for genome editing in several biological systems. © 2017 Wiley Periodicals, Inc.

Nitric oxide cycle in mammals and the cyclicity principle.

PubMed

Reutov, V P

2002-03-01

This paper continues a series of reports considering nitric oxide (NO) and its cyclic conversions in mammals. Numerous facts are summarized with the goal of developing a general concept that would allow the statement of the multiple effects of NO on various systems of living organisms in the form of a short and comprehensive law. The current state of biological aspects of NO research is analyzed in term of elucidation of possible role of these studies in the system of biological sciences. The general concept is based on a notion on cyclic conversions of NO and its metabolites. NO cycles in living organisms and nitrogen turnover in the biosphere and also the Bethe nitrogen-carbon cycle in star matter are considered. A hypothesis that the cyclic organization of processes in living organisms and the biosphere reflects the evolution of life is proposed: the development of physiological functions and metabolism are suggested to be closely related to space and evolution of the Earth as a planet of the Solar System.

Photo-Modulated Therapeutic Protein Release from a Hydrogel Depot Using Visible Light.

PubMed

Basuki, Johan S; Qie, Fengxiang; Mulet, Xavier; Suryadinata, Randy; Vashi, Aditya V; Peng, Yong Y; Li, Lingli; Hao, Xiaojuan; Tan, Tianwei; Hughes, Timothy C

2017-01-19

The use of biomacromolecular therapeutics has revolutionized disease treatment, but frequent injections are required owing to their short half-life in vivo. Thus there is a need for a drug delivery system that acts as a reservoir and releases the drug remotely "on demand". Here we demonstrate a simple light-triggered local drug delivery system through photo-thermal interactions of polymer-coated gold nanoparticles (AuNPs) inside an agarose hydrogel as therapeutic depot. Localized temperature increase induced by the visible light exposure caused reversible softening of the hydrogel matrix to release the pre-loaded therapeutics. The release profile can be adjusted by AuNPs and agarose concentrations, light intensity and exposure time. Importantly, the biological activity of the released bevacizumab was highly retained. In this study we demonstrate the potential application of this facile AuNPs/hydrogel system for ocular therapeutics delivery through its versatility to release multiple biologics, compatibility to ocular cells and spatiotemporal control using visible light. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Structural and molecular interrogation of intact biological systems

PubMed Central

Chung, Kwanghun; Wallace, Jenelle; Kim, Sung-Yon; Kalyanasundaram, Sandhiya; Andalman, Aaron S.; Davidson, Thomas J.; Mirzabekov, Julie J.; Zalocusky, Kelly A.; Mattis, Joanna; Denisin, Aleksandra K.; Pak, Sally; Bernstein, Hannah; Ramakrishnan, Charu; Grosenick, Logan; Gradinaru, Viviana; Deisseroth, Karl

2014-01-01

Obtaining high-resolution information from a complex system, while maintaining the global perspective needed to understand system function, represents a key challenge in biology. Here we address this challenge with a method (termed CLARITY) for the transformation of intact tissue into a nanoporous hydrogel-hybridized form (crosslinked to a three-dimensional network of hydrophilic polymers) that is fully assembled but optically transparent and macromolecule-permeable. Using mouse brains, we show intact-tissue imaging of long-range projections, local circuit wiring, cellular relationships, subcellular structures, protein complexes, nucleic acids and neurotransmitters. CLARITY also enables intact-tissue in situ hybridization, immunohistochemistry with multiple rounds of staining and de-staining in non-sectioned tissue, and antibody labelling throughout the intact adult mouse brain. Finally, we show that CLARITY enables fine structural analysis of clinical samples, including non-sectioned human tissue from a neuropsychiatric-disease setting, establishing a path for the transmutation of human tissue into a stable, intact and accessible form suitable for probing structural and molecular underpinnings of physiological function and disease. PMID:23575631

The European approach to in-transit melanoma lesions.

PubMed

Hoekstra, H J

2008-05-01

The biological behavior of melanoma is unpredictable. Three to five per cent of melanoma patients will develop in-transit lesions and the median time to recurrence ranges between 13-16 months. At the time of recurrence the risk of occult nodal metastasis, with clinically negative regional lymph nodes, is as high as 50%. The risk of in-transit lesions depends on the tumor biology and not on the surgical approach to the regional lymph nodes. The high incidence of in-transit lesions at the lower limb may be caused by the gravity and delayed lymphatic drainage. The treatment of limited disease is local excision, laser ablation, cryosurgery, while multiple in-transit lesions or bulky disease located in a limb can be successfully treated with regional chemotherapy, a therapeutic isolated limb perfusion or infusion with melphalan or a combination of melphalan and tumor necrosis factor (TNF) alpha. If local regional treatment or systemic dacarbazine based systemic treatment fails, novel systemic treatment strategies with vaccines, antibodies and gene therapy are currently investigated.

Biomimicry Promotes the Efficiency of a 10-Step Sequential Enzymatic Reaction on Nanoparticles, Converting Glucose to Lactate.

PubMed

Mukai, Chinatsu; Gao, Lizeng; Nelson, Jacquelyn L; Lata, James P; Cohen, Roy; Wu, Lauren; Hinchman, Meleana M; Bergkvist, Magnus; Sherwood, Robert W; Zhang, Sheng; Travis, Alexander J

2017-01-02

For nanobiotechnology to achieve its potential, complex organic-inorganic systems must grow to utilize the sequential functions of multiple biological components. Critical challenges exist: immobilizing enzymes can block substrate-binding sites or prohibit conformational changes, substrate composition can interfere with activity, and multistep reactions risk diffusion of intermediates. As a result, the most complex tethered reaction reported involves only 3 enzymes. Inspired by the oriented immobilization of glycolytic enzymes on the fibrous sheath of mammalian sperm, here we show a complex reaction of 10 enzymes tethered to nanoparticles. Although individual enzyme efficiency was higher in solution, the efficacy of the 10-step pathway measured by conversion of glucose to lactate was significantly higher when tethered. To our knowledge, this is the most complex organic-inorganic system described, and it shows that tethered, multi-step biological pathways can be reconstituted in hybrid systems to carry out functions such as energy production or delivery of molecular cargo. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Biomimicry promotes the efficiency of a 10-step sequential enzymatic reaction on nanoparticles, converting glucose to lactate

PubMed Central

Mukai, Chinatsu; Gao, Lizeng; Nelson, Jacquelyn L.; Lata, James P.; Cohen, Roy; Wu, Lauren; Hinchman, Meleana M.; Bergkvist, Magnus; Sherwood, Robert W.; Zhang, Sheng; Travis, Alexander J.

2016-01-01

For nanobiotechnology to achieve its potential, complex organic-inorganic systems must grow to utilize the sequential functions of multiple biological components. Critical challenges exist: immobilizing enzymes can block substrate-binding sites or prohibit conformational changes, substrate composition can interfere with activity, and multistep reactions risk diffusion of intermediates. As a result, the most complex tethered reaction reported involves only 3 enzymes. Inspired by the oriented immobilization of glycolytic enzymes on the fibrous sheath of mammalian sperm, here we show a complex reaction of 10 enzymes tethered to nanoparticles. Although individual enzyme efficiency was higher in solution, the efficacy of the 10-step pathway measured by conversion of glucose to lactate was significantly higher when tethered. To our knowledge, this is the most complex organic-inorganic system described, and it shows that tethered, multi-step biological pathways can be reconstituted in hybrid systems to carry out functions such as energy production or delivery of molecular cargo. PMID:27901298

Adipose tissue-organotypic culture system as a promising model for studying adipose tissue biology and regeneration

PubMed Central

Uchihashi, Kazuyoshi; Aoki, Shigehisa; Sonoda, Emiko; Yamasaki, Fumio; Piao, Meihua; Ootani, Akifumi; Yonemitsu, Nobuhisa; Sugihara, Hajime

2009-01-01

Adipose tissue consists of mature adipocytes, preadipocytes and mesenchymal stem cells (MSCs), but a culture system for analyzing their cell types within the tissue has not been established. We have recently developed “adipose tissue-organotypic culture system” that maintains unilocular structure, proliferative ability and functions of mature adipocytes for a long term, using three-dimensional collagen gel culture of the tissue fragments. In this system, both preadipocytes and MSCs regenerate actively at the peripheral zone of the fragments. Our method will open up a new way for studying both multiple cell types within adipose tissue and the cell-based mechanisms of obesity and metabolic syndrome. Thus, it seems to be a promising model for investigating adipose tissue biology and regeneration. In this article, we introduce adipose tissue-organotypic culture, and propose two theories regarding the mechanism of tissue regeneration that occurs specifically at peripheral zone of tissue fragments in vitro. PMID:19794899

Effect of posttranslational modifications on enzyme function and assembly.

PubMed

Ryšlavá, Helena; Doubnerová, Veronika; Kavan, Daniel; Vaněk, Ondřej

2013-10-30

The detailed examination of enzyme molecules by mass spectrometry and other techniques continues to identify hundreds of distinct PTMs. Recently, global analyses of enzymes using methods of contemporary proteomics revealed widespread distribution of PTMs on many key enzymes distributed in all cellular compartments. Critically, patterns of multiple enzymatic and nonenzymatic PTMs within a single enzyme are now functionally evaluated providing a holistic picture of a macromolecule interacting with low molecular mass compounds, some of them being substrates, enzyme regulators, or activated precursors for enzymatic and nonenzymatic PTMs. Multiple PTMs within a single enzyme molecule and their mutual interplays are critical for the regulation of catalytic activity. Full understanding of this regulation will require detailed structural investigation of enzymes, their structural analogs, and their complexes. Further, proteomics is now integrated with molecular genetics, transcriptomics, and other areas leading to systems biology strategies. These allow the functional interrogation of complex enzymatic networks in their natural environment. In the future, one might envisage the use of robust high throughput analytical techniques that will be able to detect multiple PTMs on a global scale of individual proteomes from a number of carefully selected cells and cellular compartments. This article is part of a Special Issue entitled: Posttranslational Protein modifications in biology and Medicine. Copyright © 2013 Elsevier B.V. All rights reserved.

Rising tides, cumulative impacts and cascading changes to estuarine ecosystem functions.

PubMed

O'Meara, Theresa A; Hillman, Jenny R; Thrush, Simon F

2017-08-31

In coastal ecosystems, climate change affects multiple environmental factors, yet most predictive models are based on simple cause-and-effect relationships. Multiple stressor scenarios are difficult to predict because they can create a ripple effect through networked ecosystem functions. Estuarine ecosystem function relies on an interconnected network of physical and biological processes. Estuarine habitats play critical roles in service provision and represent global hotspots for organic matter processing, nutrient cycling and primary production. Within these systems, we predicted functional changes in the impacts of land-based stressors, mediated by changing light climate and sediment permeability. Our in-situ field experiment manipulated sea level, nutrient supply, and mud content. We used these stressors to determine how interacting environmental stressors influence ecosystem function and compared results with data collected along elevation gradients to substitute space for time. We show non-linear, multi-stressor effects deconstruct networks governing ecosystem function. Sea level rise altered nutrient processing and impacted broader estuarine services ameliorating nutrient and sediment pollution. Our experiment demonstrates how the relationships between nutrient processing and biological/physical controls degrade with environmental stress. Our results emphasise the importance of moving beyond simple physically-forced relationships to assess consequences of climate change in the context of ecosystem interactions and multiple stressors.

Optimal design of compact and connected nature reserves for multiple species.

PubMed

Wang, Yicheng; Önal, Hayri

2016-04-01

When designing a conservation reserve system for multiple species, spatial attributes of the reserves must be taken into account at species level. The existing optimal reserve design literature considers either one spatial attribute or when multiple attributes are considered the analysis is restricted only to one species. We built a linear integer programing model that incorporates compactness and connectivity of the landscape reserved for multiple species. The model identifies multiple reserves that each serve a subset of target species with a specified coverage probability threshold to ensure the species' long-term survival in the reserve, and each target species is covered (protected) with another probability threshold at the reserve system level. We modeled compactness by minimizing the total distance between selected sites and central sites, and we modeled connectivity of a selected site to its designated central site by selecting at least one of its adjacent sites that has a nearer distance to the central site. We considered structural distance and functional distances that incorporated site quality between sites. We tested the model using randomly generated data on 2 species, one ground species that required structural connectivity and the other an avian species that required functional connectivity. We applied the model to 10 bird species listed as endangered by the state of Illinois (U.S.A.). Spatial coherence and selection cost of the reserves differed substantially depending on the weights assigned to these 2 criteria. The model can be used to design a reserve system for multiple species, especially species whose habitats are far apart in which case multiple disjunct but compact and connected reserves are advantageous. The model can be modified to increase or decrease the distance between reserves to reduce or promote population connectivity. © 2015 Society for Conservation Biology.

Incorporation of multiple cloud layers for ultraviolet radiation modeling studies

NASA Technical Reports Server (NTRS)

Charache, Darryl H.; Abreu, Vincent J.; Kuhn, William R.; Skinner, Wilbert R.

1994-01-01

Cloud data sets compiled from surface observations were used to develop an algorithm for incorporating multiple cloud layers into a multiple-scattering radiative transfer model. Aerosol extinction and ozone data sets were also incorporated to estimate the seasonally averaged ultraviolet (UV) flux reaching the surface of the Earth in the Detroit, Michigan, region for the years 1979-1991, corresponding to Total Ozone Mapping Spectrometer (TOMS) version 6 ozone observations. The calculated UV spectrum was convolved with an erythema action spectrum to estimate the effective biological exposure for erythema. Calculations show that decreasing the total column density of ozone by 1% leads to an increase in erythemal exposure by approximately 1.1-1.3%, in good agreement with previous studies. A comparison of the UV radiation budget at the surface between a single cloud layer method and a multiple cloud layer method presented here is discussed, along with limitations of each technique. With improved parameterization of cloud properties, and as knowledge of biological effects of UV exposure increase, inclusion of multiple cloud layers may be important in accurately determining the biologically effective UV budget at the surface of the Earth.

Upper Secondary Students' Understanding of the Use of Multiple Models in Biology Textbooks--The Importance of Conceptual Variation and Incommensurability

ERIC Educational Resources Information Center

Gericke, Niklas; Hagberg, Mariana; Jorde, Doris

2013-01-01

In this study we investigate students' ability to discern conceptual variation and the use of multiple models in genetics when reading content-specific excerpts from biology textbooks. Using the history and philosophy of science as our reference, we were able to develop a research instrument allowing students themselves to investigate the…

A System-Level Pathway-Phenotype Association Analysis Using Synthetic Feature Random Forest

PubMed Central

Pan, Qinxin; Hu, Ting; Malley, James D.; Andrew, Angeline S.; Karagas, Margaret R.; Moore, Jason H.

2015-01-01

As the cost of genome-wide genotyping decreases, the number of genome-wide association studies (GWAS) has increased considerably. However, the transition from GWAS findings to the underlying biology of various phenotypes remains challenging. As a result, due to its system-level interpretability, pathway analysis has become a popular tool for gaining insights on the underlying biology from high-throughput genetic association data. In pathway analyses, gene sets representing particular biological processes are tested for significant associations with a given phenotype. Most existing pathway analysis approaches rely on single-marker statistics and assume that pathways are independent of each other. As biological systems are driven by complex biomolecular interactions, embracing the complex relationships between single-nucleotide polymorphisms (SNPs) and pathways needs to be addressed. To incorporate the complexity of gene-gene interactions and pathway-pathway relationships, we propose a system-level pathway analysis approach, synthetic feature random forest (SF-RF), which is designed to detect pathway-phenotype associations without making assumptions about the relationships among SNPs or pathways. In our approach, the genotypes of SNPs in a particular pathway are aggregated into a synthetic feature representing that pathway via Random Forest (RF). Multiple synthetic features are analyzed using RF simultaneously and the significance of a synthetic feature indicates the significance of the corresponding pathway. We further complement SF-RF with pathway-based Statistical Epistasis Network (SEN) analysis that evaluates interactions among pathways. By investigating the pathway SEN, we hope to gain additional insights into the genetic mechanisms contributing to the pathway-phenotype association. We apply SF-RF to a population-based genetic study of bladder cancer and further investigate the mechanisms that help explain the pathway-phenotype associations using SEN. The bladder cancer associated pathways we found are both consistent with existing biological knowledge and reveal novel and plausible hypotheses for future biological validations. PMID:24535726

3D-printing and mechanics of bio-inspired articulated and multi-material structures.

PubMed

Porter, Michael M; Ravikumar, Nakul; Barthelat, Francois; Martini, Roberto

2017-09-01

3D-printing technologies allow researchers to build simplified physical models of complex biological systems to more easily investigate their mechanics. In recent years, a number of 3D-printed structures inspired by the dermal armors of various fishes have been developed to study their multiple mechanical functionalities, including flexible protection, improved hydrodynamics, body support, or tail prehensility. Natural fish armors are generally classified according to their shape, material and structural properties as elasmoid scales, ganoid scales, placoid scales, carapace scutes, or bony plates. Each type of dermal armor forms distinct articulation patterns that facilitate different functional advantages. In this paper, we highlight recent studies that developed 3D-printed structures not only to inform the design and application of some articulated and multi-material structures, but also to explain the mechanics of the natural biological systems they mimic. Copyright © 2017 Elsevier Ltd. All rights reserved.

Syntheses and Functionalizations of Porphyrin Macrocycles

PubMed Central

Vicente, Maria da G.H.; Smith, Kevin M.

2014-01-01

Porphyrin macrocycles have been the subject of intense study in the last century because they are widely distributed in nature, usually as metal complexes of either iron or magnesium. As such, they serve as the prosthetic groups in a wide variety of primary metabolites, such as hemoglobins, myoglobins, cytochromes, catalases, peroxidases, chlorophylls, and bacteriochlorophylls; these compounds have multiple applications in materials science, biology and medicine. This article describes current methodology for preparation of simple, symmetrical model porphyrins, as well as more complex protocols for preparation of unsymmetrically substituted porphyrin macrocycles similar to those found in nature. The basic chemical reactivity of porphyrins and metalloporphyrin is also described, including electrophilic and nucleophilic reactions, oxidations, reductions, and metal-mediated cross-coupling reactions. Using the synthetic approaches and reactivity profiles presented, eventually almost any substituted porphyrin system can be prepared for applications in a variety of areas, including in catalysis, electron transport, model biological systems and therapeutics. PMID:25484638

A stratified myeloid system, the challenge of understanding macrophage diversity.

PubMed

Geissmann, F; Mass, E

2015-12-01

The present issue of 'Seminars in Immunology' addresses the topic of macrophage biology, 100 years after the death of Elie Metchnikoff (May 1845-July 1916). As foreseen by Metchnikoff, the roles of macrophages in the maintenance of homeostasis and immunity against pathogens have become a broad and active area of investigation. We now start to realize that the myeloid system includes a multiplicity of cell types with diverse developmental origins and functions. Therefore, the textbook picture of a plastic and multifunctional macrophage does not meet the requirements of our current knowledge anymore. Further development toward a quantitative and molecular understanding of myeloid cell biology in vivo and their roles in tissue homeostasis and remodeling will benefit from taking this complexity into account. A tentative model to help in this pursuit and account for myeloid cell and macrophage diversity is discussed below. Copyright © 2016. Published by Elsevier Ltd.

Viral Disease Networks?

NASA Astrophysics Data System (ADS)

Gulbahce, Natali; Yan, Han; Vidal, Marc; Barabasi, Albert-Laszlo

2010-03-01

Viral infections induce multiple perturbations that spread along the links of the biological networks of the host cells. Understanding the impact of these cascading perturbations requires an exhaustive knowledge of the cellular machinery as well as a systems biology approach that reveals how individual components of the cellular system function together. Here we describe an integrative method that provides a new approach to studying virus-human interactions and its correlations with diseases. Our method involves the combined utilization of protein - protein interactions, protein -- DNA interactions, metabolomics and gene - disease associations to build a ``viraldiseasome''. By solely using high-throughput data, we map well-known viral associated diseases and predict new candidate viral diseases. We use microarray data of virus-infected tissues and patient medical history data to further test the implications of the viral diseasome. We apply this method to Epstein-Barr virus and Human Papillomavirus and shed light into molecular development of viral diseases and disease pathways.

Mayo Clinic Zebrafish Facility Overview.

PubMed

Leveque, Ryan E; Clark, Karl J; Ekker, Stephen C

2016-07-01

The zebrafish (Danio rerio) is a premier nonmammalian vertebrate model organism. This small aquatic fish is utilized in multiple disciplines in the Mayo Clinic community and by many laboratories around the world because of its biological similarity to humans, its advanced molecular genetics, the elucidation of its genome sequence, and the ever-expanding and outstanding new biological tools now available to the zebrafish researcher. The Mayo Clinic Zebrafish Facility (MCZF) houses ∼2,000 tanks annotated using an in-house, Internet cloud-based bar-coding system tied to our established zfishbook.org web infrastructure. Paramecia are the primary food source for larval fish rearing, using a simplified culture protocol described herein. The MCZF supports the specific ongoing research in a variety of laboratories, while also serving as a local hub for new scientists as they learn to tap into the potential of this model system for understanding normal development, disease, and as models of health.