Corrigendum: Predicting Essential Genes and Proteins Based on Machine Learning and Network Topological Features: A Comprehensive Review.

Front Physiol. 2016;7:617

Authors: Zhang X, Acencio ML, Lemke N

Abstract
[This corrects the article on p. 75 in vol. 7, PMID: 27014079.].

PMID: 27980533 [PubMed - in process]

Differentiation of Diabetes by Pathophysiology, Natural History, and Prognosis.

Diabetes. 2016 Dec 15;:

Authors: Skyler JS, Bakris GL, Bonifacio E, Darsow T, Eckel RH, Groop L, Groop PH, Handelsman Y, Insel RA, Mathieu C, McElvaine AT, Palmer JP, Pugliese A, Schatz DA, Sosenko JM, Wilding JP, Ratner RE

Abstract
The American Diabetes Association, JDRF, the European Association for the Study of Diabetes, and the American Association of Clinical Endocrinologists convened a research symposium, "The Differentiation of Diabetes by Pathophysiology, Natural History and Prognosis" on 10-12 October 2015. International experts in genetics, immunology, metabolism, endocrinology, and systems biology discussed genetic and environmental determinants of type 1 and type 2 diabetes risk and progression, as well as complications. The participants debated how to determine appropriate therapeutic approaches based on disease pathophysiology and stage and defined remaining research gaps hindering a personalized medical approach for diabetes to drive the field to address these gaps. The authors recommend a structure for data stratification to define the phenotypes and genotypes of subtypes of diabetes that will facilitate individualized treatment.

PMID: 27980006 [PubMed - as supplied by publisher]

Prediction of Chemical Multi-target Profiles and Adverse Outcomes with Systems Toxicology.

Curr Med Chem. 2016 Dec 14;

Authors: Wathieu H, Ojo A, Dakshanamurthy S

Abstract
The field of systems biology, termed systems toxicology when applied to the characterization of adverse outcomes following chemical exposure, seeks to develop biological networks to explain phenotypic responses. Ideally, these are qualitatively and quantitatively similar to the actual network of biological entities that have functional consequences in living organisms. In this review, we outline computational tools for predicting chemical-protein interactions of multi-target compounds. Then, we discuss how the methods of systems toxicology currently draw on those interactions to predict resulting adverse outcomes which include diseases, adverse drug reactions, and toxic endpoints. These methods are useful for predicting the safety of drugs in drug development and the toxicity of environmental chemicals (ECs) in environmental toxicology.

PMID: 27978797 [PubMed - as supplied by publisher]

Investigating a holobiont: Microbiota perturbations and transkingdom networks.

Gut Microbes. 2016;7(2):126-35

Authors: Greer R, Dong X, Morgun A, Shulzhenko N

Abstract
The scientific community has recently come to appreciate that, rather than existing as independent organisms, multicellular hosts and their microbiota comprise a complex evolving superorganism or metaorganism, termed a holobiont. This point of view leads to a re-evaluation of our understanding of different physiological processes and diseases. In this paper we focus on experimental and computational approaches which, when combined in one study, allowed us to dissect mechanisms (traditionally named host-microbiota interactions) regulating holobiont physiology. Specifically, we discuss several approaches for microbiota perturbation, such as use of antibiotics and germ-free animals, including advantages and potential caveats of their usage. We briefly review computational approaches to characterize the microbiota and, more importantly, methods to infer specific components of microbiota (such as microbes or their genes) affecting host functions. One such approach called transkingdom network analysis has been recently developed and applied in our study. (1) Finally, we also discuss common methods used to validate the computational predictions of host-microbiota interactions using in vitro and in vivo experimental systems.

PMID: 26979110 [PubMed - indexed for MEDLINE]

Temporal retinal transcriptome and systems biology analysis identifies key pathways and hub genes in Staphylococcus aureus endophthalmitis.

Sci Rep. 2016 Feb 11;6:21502

Authors: Rajamani D, Singh PK, Rottmann BG, Singh N, Bhasin MK, Kumar A

Abstract
Bacterial endophthalmitis remains a devastating inflammatory condition associated with permanent vision loss. Hence, assessing the host response in this disease may provide new targets for intervention. Using a mouse model of Staphylococcus aureus (SA) endophthalmitis and performing retinal transcriptome analysis, we discovered progressive changes in the expression of 1,234 genes. Gene ontology (GO) and pathway analyses revealed the major pathways impacted in endophthalmitis includes: metabolism, inflammatory/immune, antimicrobial, cell trafficking, and lipid biosynthesis. Among the immune/inflammation pathways, JAK/Stat and IL-17A signaling were the most significantly affected. Interactive network-based analyses identified 13 focus hub genes (IL-6, IL-1β, CXCL2, STAT3, NUPR1, Jun, CSF1, CYR61, CEBPB, IGF-1, EGFR1, SPP1, and TGM2) within these important pathways. The expression of hub genes confirmed by qRT-PCR, ELISA (IL-6, IL-1β, and CXCL2), and Western blot or immunostaining (CEBP, STAT3, NUPR1, and IGF1) showed strong correlation with transcriptome data. Since TLR2 plays an important role in SA endophthalmitis, counter regulation analysis of TLR2 ligand pretreated retina or the use of retinas from TLR2 knockout mice showed the down-regulation of inflammatory regulatory genes. Collectively, our study provides, for the first time, a comprehensive analysis of the transcriptomic response and identifies key pathways regulating retinal innate responses in staphylococcal endophthalmitis.

PMID: 26865111 [PubMed - indexed for MEDLINE]

Gene regulatory network inference using fused LASSO on multiple data sets.

Sci Rep. 2016 Feb 11;6:20533

Authors: Omranian N, Eloundou-Mbebi JM, Mueller-Roeber B, Nikoloski Z

Abstract
Devising computational methods to accurately reconstruct gene regulatory networks given gene expression data is key to systems biology applications. Here we propose a method for reconstructing gene regulatory networks by simultaneous consideration of data sets from different perturbation experiments and corresponding controls. The method imposes three biologically meaningful constraints: (1) expression levels of each gene should be explained by the expression levels of a small number of transcription factor coding genes, (2) networks inferred from different data sets should be similar with respect to the type and number of regulatory interactions, and (3) relationships between genes which exhibit similar differential behavior over the considered perturbations should be favored. We demonstrate that these constraints can be transformed in a fused LASSO formulation for the proposed method. The comparative analysis on transcriptomics time-series data from prokaryotic species, Escherichia coli and Mycobacterium tuberculosis, as well as a eukaryotic species, mouse, demonstrated that the proposed method has the advantages of the most recent approaches for regulatory network inference, while obtaining better performance and assigning higher scores to the true regulatory links. The study indicates that the combination of sparse regression techniques with other biologically meaningful constraints is a promising framework for gene regulatory network reconstructions.

PMID: 26864687 [PubMed - indexed for MEDLINE]

An ongoing role for Wnt signaling in differentiating melanocytes in vivo.

Pigment Cell Melanoma Res. 2016 Dec 15;:

Authors: Vibert L, Aquino G, Gehring I, Subkhankulova T, Schilling TF, Rocco A, Kelsh RN

Abstract
A role for Wnt signaling in melanocyte specification from neural crest is conserved across vertebrates, but possible ongoing roles in melanocyte differentiation have received little attention. Using a systems biology approach to investigate the gene regulatory network underlying stable melanocyte differentiation in zebrafish highlighted a requirement for a positive feedback loop involving the melanocyte master regulator Mitfa. Here we test the hypothesis that Wnt signaling contributes to that positive feedback. We show firstly that Wnt signaling remains active in differentiating melanocytes and secondly that enhanced Wnt signaling drives elevated transcription of mitfa. We show that chemical activation of the Wnt signaling pathway at early stages of melanocyte development enhances melanocyte specification as expected, but importantly that at later (differentiation) stages it results in altered melanocyte morphology, although melanisation is not obviously affected. Downregulation of Wnt signaling also results in altered melanocyte morphology and organisation. We conclude that Wnt signaling plays a role in regulating ongoing aspects of melanocyte differentiation in zebrafish. This article is protected by copyright. All rights reserved.

PMID: 27977907 [PubMed - as supplied by publisher]

Determining the Significance of Protein Network Features and Attributes Using Permutation Testing.

Methods Mol Biol. 2017;1549:199-208

Authors: Cursons J, Davis MJ

Abstract
Network analysis methods are increasing in popularity. An approach commonly applied to analyze proteomics data involves the use of protein-protein interaction (PPI) networks to explore the systems-level cooperation between proteins identified in a study. In this context, protein interaction networks can be used alongside the statistical analysis of proteomics data and traditional functional enrichment or pathway enrichment analyses. In network analysis it is possible to adjust for some of the complexities that arise due to the known, explicit interdependence between the measured quantities, in particular, differences in the number of interactions between proteins. Here we describe a method for calculating robust empirical p-values for protein interaction networks. We also provide a worked example with python code demonstrating the implementation of this methodology.

PMID: 27975293 [PubMed - in process]

Protocol for Standardizing High-to-Moderate Abundance Protein Biomarker Assessments Through an MRM-with-Standard-Peptides Quantitative Approach.

Adv Exp Med Biol. 2016;919:515-530

Authors: Percy AJ, Yang J, Chambers AG, Mohammed Y, Miliotis T, Borchers CH

Abstract
Quantitative mass spectrometry (MS)-based approaches are emerging as a core technology for addressing health-related queries in systems biology and in the biomedical and clinical fields. In several 'omics disciplines (proteomics included), an approach centered on selected or multiple reaction monitoring (SRM or MRM)-MS with stable isotope-labeled standards (SIS), at the protein or peptide level, has emerged as the most precise technique for quantifying and screening putative analytes in biological samples. To enable the widespread use of MRM-based protein quantitation for disease biomarker assessment studies and its ultimate acceptance for clinical analysis, the technique must be standardized to facilitate precise and accurate protein quantitation. To that end, we have developed a number of kits for assessing method/platform performance, as well as for screening proposed candidate protein biomarkers in various human biofluids. Collectively, these kits utilize a bottom-up LC-MS methodology with SIS peptides as internal standards and quantify proteins using regression analysis of standard curves. This chapter details the methodology used to quantify 192 plasma proteins of high-to-moderate abundance (covers a 6 order of magnitude range from 31 mg/mL for albumin to 18 ng/mL for peroxidredoxin-2), and a 21-protein subset thereof. We also describe the application of this method to patient samples for biomarker discovery and verification studies. Additionally, we introduce our recently developed Qualis-SIS software, which is used to expedite the analysis and assessment of protein quantitation data in control and patient samples.

PMID: 27975233 [PubMed - in process]

Systems biology: Molecular memoirs of a cellular family.

Nature. 2016 Dec 14;:

Authors: Beck LE, Raj A

PMID: 27974796 [PubMed - as supplied by publisher]

From 20th Century Metabolic Wall Charts to 21st Century Systems Biology: Database of Mammalian Metabolic Enzymes.

Am J Physiol Renal Physiol. 2016 Dec 14;:ajprenal.00601.2016

Authors: Corcoran CC, Grady CR, Pisitkun T, Parulekar J, Knepper MA

Abstract
The organization of the mammalian genome into gene subsets corresponding to specific functional classes has provided key tools for systems biology research. Here, we have created a web-accessible resource called the Mammalian Metabolic Enzyme Database (https://hpcwebapps.cit.nih.gov/ESBL/Database/MetabolicEnzymes/MetabolicEnzymeDatabase.html) keyed to the biochemical reactions represented on iconic metabolic pathway wall charts created in the previous century. Overall, we have mapped 1647 genes to these pathways, representing approximately 7 percent of the protein-coding genome. To illustrate the use of the database, we apply it to the area of kidney physiology. In so doing, we have created an additional database (Database of Metabolic Enzymes in Kidney Tubule Segments: https://hpcwebapps.cit.nih.gov/ESBL/Database/MetabolicEnzymes/), mapping mRNA abundance measurements (mined from RNA-Seq studies) for all metabolic enzymes to each of 14 renal tubule segments. We carry out bioinformatics analysis of the enzyme expression pattern among renal tubule segments and mine various data sources to identify vasopressin-regulated metabolic enzymes in the renal collecting duct.

PMID: 27974320 [PubMed - as supplied by publisher]

The hnRNP-Htt axis regulates necrotic cell death induced by transcriptional repression through impaired RNA splicing.

Cell Death Dis. 2016 Apr 28;7:e2207

Authors: Mao Y, Tamura T, Yuki Y, Abe D, Tamada Y, Imoto S, Tanaka H, Homma H, Tagawa K, Miyano S, Okazawa H

Abstract
In this study, we identify signaling network of necrotic cell death induced by transcriptional repression (TRIAD) by α-amanitin (AMA), the selective RNA polymerase II inhibitor, as a model of neurodegenerative cell death. We performed genetic screen of a knockdown (KD) fly library by measuring the ratio of transformation from pupa to larva (PL ratio) under TRIAD, and selected the cell death-promoting genes. Systems biology analysis of the positive genes mapped on protein-protein interaction databases predicted the signaling network of TRIAD and the core pathway including heterogeneous nuclear ribonucleoproteins (hnRNPs) and huntingtin (Htt). RNA sequencing revealed that AMA impaired transcription and RNA splicing of Htt, which is known as an endoplasmic reticulum (ER)-stabilizing molecule. The impairment in RNA splicing and PL ratio was rescued by overexpresion of hnRNP that had been also affected by transcriptional repression. Fly genetics with suppressor or expresser of Htt and hnRNP worsened or ameliorated the decreased PL ratio by AMA, respectively. Collectively, these results suggested involvement of RNA splicing and a regulatory role of the hnRNP-Htt axis in the process of the transcriptional repression-induced necrosis.

PMID: 27124581 [PubMed - indexed for MEDLINE]

Flux Control in Glycolysis Varies Across the Tree of Life.

J Mol Evol. 2016 Mar;82(2-3):146-61

Authors: Orlenko A, Hermansen RA, Liberles DA

Abstract
Biochemical thought posits that rate-limiting steps (defined here as points of flux control) are strongly selected as points of pathway regulation and control and are thus expected to be evolutionarily conserved. Conversely, population genetic thought based upon the concepts of mutation-selection-drift balance at the pathway level might suggest variation in flux controlling steps over evolutionary time. Glycolysis, as one of the most conserved and best characterized pathways, was studied to evaluate its evolutionary conservation. The flux controlling step in glycolysis was found to vary over the tree of life. Further, phylogenetic analysis suggested at least 60 events of gene duplication and additional events of putative positive selection that might alter pathway kinetic properties. Together, these results suggest that even with presumed largely negative selection on pathway output on glycolysis, the co-evolutionary process under the hood is dynamic.

PMID: 26920685 [PubMed - indexed for MEDLINE]

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Direction-dependent arm kinematics reveal optimal integration of gravity cues.

Elife. 2016 Nov 02;5:

Authors: Gaveau J, Berret B, Angelaki DE, Papaxanthis C

Abstract
The brain has evolved an internal model of gravity to cope with life in the Earth's gravitational environment. How this internal model benefits the implementation of skilled movement has remained unsolved. One prevailing theory has assumed that this internal model is used to compensate for gravity's mechanical effects on the body, such as to maintain invariant motor trajectories. Alternatively, gravity force could be used purposely and efficiently for the planning and execution of voluntary movements, thereby resulting in direction-depending kinematics. Here we experimentally interrogate these two hypotheses by measuring arm kinematics while varying movement direction in normal and zero-G gravity conditions. By comparing experimental results with model predictions, we show that the brain uses the internal model to implement control policies that take advantage of gravity to minimize movement effort.

PMID: 27805566 [PubMed - as supplied by publisher]

Computationally designed high specificity inhibitors delineate the roles of BCL2 family proteins in cancer.

Elife. 2016 Nov 02;5:

Authors: Berger S, Procko E, Margineantu D, Lee EF, Shen BW, Zelter A, Silva DA, Chawla K, Herold MJ, Garnier JM, Johnson R, MacCoss MJ, Lessene G, Davis TN, Stayton PS, Stoddard BL, Fairlie WD, Hockenbery DM, Baker D

Abstract
Many cancers overexpress one or more of the six human pro-survival BCL2 family proteins to evade apoptosis. To determine which BCL2 protein or proteins block apoptosis in different cancers, we computationally designed three-helix bundle protein inhibitors specific for each BCL2 pro-survival protein. Following in vitro optimization, each inhibitor binds its target with high picomolar to low nanomolar affinity and at least 300-fold specificity. Expression of the designed inhibitors in human cancer cell lines revealed unique dependencies on BCL2 proteins for survival which could not be inferred from other BCL2 profiling methods. Our results show that designed inhibitors can be generated for each member of a closely-knit protein family to probe the importance of specific protein-protein interactions in complex biological processes.

PMID: 27805565 [PubMed - as supplied by publisher]

Investigating cholesterol metabolism and ageing using a systems biology approach.

Proc Nutr Soc. 2016 Nov 2;:1-14

Authors: Morgan AE, Mooney KM, Wilkinson SJ, Pickles NA, Mc Auley MT

Abstract
CVD accounted for 27 % of all deaths in the UK in 2014, and was responsible for 1·7 million hospital admissions in 2013/2014. This condition becomes increasingly prevalent with age, affecting 34·1 and 29·8 % of males and females over 75 years of age respectively in 2011. The dysregulation of cholesterol metabolism with age, often observed as a rise in LDL-cholesterol, has been associated with the pathogenesis of CVD. To compound this problem, it is estimated by 2050, 22 % of the world's population will be over 60 years of age, in culmination with a growing resistance and intolerance to pre-existing cholesterol regulating drugs such as statins. Therefore, it is apparent research into additional therapies for hypercholesterolaemia and CVD prevention is a growing necessity. However, it is also imperative to recognise this complex biological system cannot be studied using a reductionist approach; rather its biological uniqueness necessitates a more integrated methodology, such as that offered by systems biology. In this review, we firstly discuss cholesterol metabolism and how it is affected by diet and the ageing process. Next, we describe therapeutic strategies for hypercholesterolaemia, and finally how the systems biology paradigm can be utilised to investigate how ageing interacts with complex systems such as cholesterol metabolism. We conclude by emphasising the need for nutritionists to work in parallel with the systems biology community, to develop novel approaches to studying cholesterol metabolism and its interaction with ageing.

PMID: 27804896 [PubMed - as supplied by publisher]

Cancer associated fibroblasts regulate keratinocyte cell-cell adhesion via TGF-ß-dependent pathways in genotype-specific oral cancer.

Carcinogenesis. 2016 Nov 1;:

Authors: Cirillo N, Hassona Y, Celentano A, Lim KP, Manchella S, Parkinson EK, Prime SS

Abstract
The inter-relationship between malignant epithelium and the underlying stroma is recognised as being of fundamental importance in tumour development and progression. In the present study, we used cancer associated fibroblasts (CAFs) derived from genetically unstable oral squamous cell carcinomas (GU-OSCC), tumours that are characterised by the loss of genes such as TP53 and p16(INK4A) and with extensive LOH, together with CAFs from their more genetically stable counterparts that have wild type TP53 and p16(INK4A) and minimal LOH (GS-OSCC). Using a systems biology approach to interpret the genome-wide transcriptional profile of the CAFs, we show that transforming growth factor-β (TGF-β) family members not only had biological relevance in silico but also, distinguished GU-OSCC-derived CAFs from GS-OSCC CAFs and fibroblasts from normal oral mucosa. In view of the close association between TGF-β family members, we examined the expression of TGF-β1 and TGF-β2 in the different fibroblast sub-types and show increased levels of active TGF-β1 and TGF-β2 in CAFs from GU-OSCC. CAFs from GU-OSCC, but not GS-OSCC or normal fibroblasts, induced EMT and down-regulated a broad spectrum of cell adhesion molecules resulting in epithelial dis-cohesion and invasion of target keratinocytes in vitro in a TGF-β-dependent manner. The results demonstrate that the TGF-β family of cytokines secreted by CAFs derived from genotype-specific oral cancer (GU-OSCC) promote, at least in part, the malignant phenotype by weakening intercellular epithelial adhesion.

PMID: 27803052 [PubMed - as supplied by publisher]

Whole-body and Whole-Organ Clearing and Imaging Techniques with Single-Cell Resolution: Toward Organism-Level Systems Biology in Mammals.

Cell Chem Biol. 2016 Jan 21;23(1):137-57

Authors: Susaki EA, Ueda HR

Abstract
Organism-level systems biology aims to identify, analyze, control and design cellular circuits in organisms. Many experimental and computational approaches have been developed over the years to allow us to conduct these studies. Some of the most powerful methods are based on using optical imaging in combination with fluorescent labeling, and for those one of the long-standing stumbling blocks has been tissue opacity. Recently, the solutions to this problem have started to emerge based on whole-body and whole-organ clearing techniques that employ innovative tissue-clearing chemistry. Here, we review these advancements and discuss how combining new clearing techniques with high-performing fluorescent proteins or small molecule tags, rapid volume imaging and efficient image informatics is resulting in comprehensive and quantitative organ-wide, single-cell resolution experimental data. These technologies are starting to yield information on connectivity and dynamics in cellular circuits at unprecedented resolution, and bring us closer to system-level understanding of physiology and diseases of complex mammalian systems.

PMID: 26933741 [PubMed - indexed for MEDLINE]

Proteomic contributions to our understanding of vaccine and immune responses.

Proteomics Clin Appl. 2015 Dec;9(11-12):972-89

Authors: Galassie AC, Link AJ

Abstract
Vaccines are one of the greatest public health successes; yet, due to the empirical nature of vaccine design, we have an incomplete understanding of how the genes and proteins induced by vaccines contribute to the development of both protective innate and adaptive immune responses. While the advent of genomics has enabled new vaccine development and facilitated understanding of the immune response, proteomics identifies potentially new vaccine antigens with increasing speed and sensitivity. In addition, as proteomics is complementary to transcriptomic approaches, a combination of both approaches provides a more comprehensive view of the immune response after vaccination via systems vaccinology. This review details the advances that proteomic strategies have made in vaccine development and reviews how proteomics contributes to the development of a more complete understanding of human vaccines and immune responses.

PMID: 26172619 [PubMed - indexed for MEDLINE]