Advancing our understanding of infant bronchiolitis through phenotyping and endotyping: Clinical and molecular approaches.

Expert Rev Respir Med. 2016 May 18;

Authors: Hasegawa K, Dumas O, Hartert TV, Camargo CA

Abstract
INTRODUCTION: Bronchiolitis is a major public health problem worldwide. However, no effective treatment strategies are available, other than supportive care. Areas Covered: Although bronchiolitis has been considered a single disease diagnosed based on clinical characteristics, emerging evidence supports both clinical and pathobiological heterogeneity. The characterization of this heterogeneity supports the concept that bronchiolitis consists of multiple phenotypes or consistent grouping of characteristics. Expert Commentary: Using unbiased statistical approaches, multidimentional clinical characteristics will derive bronchiolitis phenotypes. Furthermore, molecular and systems biology approaches will, by linking pathobiology to phenotype, identify endotypes. Large cohort studies of bronchiolitis with comprehensive clinical characterization and system-wide profiling of the "-omics" data (e.g., host genome, transcriptome, epigenome, viral genome, microbiome, metabolome) should enhance our ability to molecularly understand these phenotypes and lead to more targeted and personalized approaches to bronchiolitis treatment.

PMID: 27192374 [PubMed - as supplied by publisher]

Practical aspects of NGS-based pathways analysis for personalized cancer science and medicine.

Oncotarget. 2016 May 14;

Authors: Kotelnikova EA, Pyatnitskiy M, Paleeva A, Kremenetskaya O, Vinogradov D

Abstract
Nowadays, the personalized approach to health care and cancer care in particular is becoming more and more popular and is taking an important place in the translational medicine paradigm. In some cases, detection of the patient-specific individual mutations that point to a targeted therapy has already become a routine practice for clinical oncologists. Wider panels of genetic markers are also on the market which cover a greater number of possible oncogenes including those with lower reliability of resulting medical conclusions. In light of the large availability of high-throughput technologies, it is very tempting to use complete patient-specific New Generation Sequencing (NGS) or other "omics" data for cancer treatment guidance. However, there are still no gold standard methods and protocols to evaluate them. Here we will discuss the clinical utility of each of the data types and describe a systems biology approach adapted for single patient measurements. We will try to summarize the current state of the field focusing on the clinically relevant case-studies and practical aspects of data processing.

PMID: 27191992 [PubMed - as supplied by publisher]

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Computational Systems Biology Approach Predicts Regulators and Targets of microRNAs and Their Genomic Hotspots in Apoptosis Process.

Mol Biotechnol. 2016 May 13;

Authors: Alanazi IO, Ebrahimie E

Abstract
Novel computational systems biology tools such as common targets analysis, common regulators analysis, pathway discovery, and transcriptomic-based hotspot discovery provide new opportunities in understanding of apoptosis molecular mechanisms. In this study, after measuring the global contribution of microRNAs in the course of apoptosis by Affymetrix platform, systems biology tools were utilized to obtain a comprehensive view on the role of microRNAs in apoptosis process. Network analysis and pathway discovery highlighted the crosstalk between transcription factors and microRNAs in apoptosis. Within the transcription factors, PRDM1 showed the highest upregulation during the course of apoptosis, with more than 9-fold expression increase compared to non-apoptotic condition. Within the microRNAs, MIR1208 showed the highest expression in non-apoptotic condition and downregulated by more than 6 fold during apoptosis. Common regulators algorithm showed that TNF receptor is the key upstream regulator with a high number of regulatory interactions with the differentially expressed microRNAs. BCL2 and AKT1 were the key downstream targets of differentially expressed microRNAs. Enrichment analysis of the genomic locations of differentially expressed microRNAs led us to the discovery of chromosome bands which were highly enriched (p < 0.01) with the apoptosis-related microRNAs, such as 13q31.3, 19p13.13, and Xq27.3 This study opens a new avenue in understanding regulatory mechanisms and downstream functions in the course of apoptosis as well as distinguishing genomic-enriched hotspots for apoptosis process.

PMID: 27178576 [PubMed - as supplied by publisher]

A heuristic model for working memory deficit in schizophrenia.

Biochim Biophys Acta. 2016 May 10;

Authors: Qi Z, Yu GP, Tretter F, Pogarell O, Grace AA, Voit EO

Abstract
BACKGROUND: The life of schizophrenia patients is severely affected deficits in working memory. In various brain regions, the reciprocal interactions between excitatory glutamatergic neurons and inhibitory GABAergic neurons are crucial. Other neurotransmitters, in particular dopamine, serotonin, acetylcholine, and norepinephrine, modulate the local balance between glutamate and GABA and therefore regulate the function of brain regions. Persistent alterations in the balances between the neurotransmitters can result in working memory deficits.
METHODS: Here we present a heuristic computational model that accounts for interactions among neurotransmitters across various brain regions. The model is based on the concept of a neurochemical interaction matrix at the biochemical level and combines this matrix with a mobile model representing physiological dynamic balances among neurotransmitter systems associated with working memory.
RESULTS: The comparison of clinical and simulation results demonstrates that the model output is qualitatively very consistent with the available data. In addition, the model captured how perturbations migrated through different neurotransmitters and brain regions. Results showed that chronic administration of ketamine can cause a variety of imbalances, and application of an antagonist of the D2 receptor in PFC can also induce imbalances but in a very different manner.
CONCLUSIONS: The heuristic computational model permits a variety of assessments of genetic, biochemical, and pharmacological perturbations and serves as an intuitive tool for explaining clinical and biological observations.
GENERAL SIGNIFICANCE: The heuristic model is more intuitive than biophysically detailed models. It can serve as an important tool for interdisciplinary communication and even for psychiatric education of patients and relatives. This article is part of a Special Issue entitled "System Genetics" Guest Editor: Dr. Yudong Cai and Dr. Tao Huang.

PMID: 27177811 [PubMed - as supplied by publisher]

Systems Medicine approaches to improving understanding, treatment, and clinical management of Neuroendocrine Prostate Cancer.

Curr Pharm Des. 2016 May 13;

Authors: Yadav KK, Khader S, Readhead B, Yadav SS, Li L, Kasarksis A, Tewari AK, Dudley JT

Abstract
BACKGROUND: Prostate cancer is the most commonly diagnosed cancer in men. More than 200,000 new cases are added each year in the US, translating to a lifetime risk of 1 in 7 men. Neuroendocrine prostate cancer (NEPC) is an aggressive and treatment-resistant form of prostate cancer. A subset of patients treated with aggressive androgen deprivation therapy (ADT) present with NEPC. Patients with NEPC have a reduced 5-year overall survival rate of 12.6%. Knowledge integration from genetic, epigenetic, biochemical and therapeutic studies suggests NEPC as an indicative mechanism of resistance development to various forms of therapy.
METHODS: In this perspective, we discuss various experimental, computational and risk prediction methodologies that can be utilized to identify novel therapies against NEPC. We reviewed literature from PubMed using key terms, and computationally analyzed publicly available genomics data to present different possibilities for developing systems medicine based therapeutic and curative models to understand and target prostate cancer and specifically NEPC.
RESULTS: Our study includes gene-set analyses, network analyses, genomics and phenomics aided drug development, microRNA and peptide-based therapeutics, pathway modeling, drug repositioning and cancer immunotherapies. We also discuss the application of cancer risk estimations and mining of electronic medical records to develop personalized risk predictions models for NEPC. Preemptive stratification of patients who are at risk of evolving NEPC phenotypes using predictive models could also help to design and deliver better therapies.
CONCLUSIONS: Collectively, understanding the mechanism of NEPC evolution from prostate cancer using systems biology approaches would help in devising better treatment strategies and is critical and unmet clinical need.

PMID: 27174811 [PubMed - as supplied by publisher]

Editorial overview: Systems biology-the intersection of experiments and computation, underpinning biotechnology.

Curr Opin Biotechnol. 2016 May 9;

Authors: Styczynski MP, Theis FJ

PMID: 27173375 [PubMed - as supplied by publisher]

MicroRNAs in the Evaluation and Potential Treatment of Liver Diseases.

J Clin Med. 2016;5(5)

Authors: Mahgoub A, Steer CJ

Abstract
Acute and chronic liver disease continue to result in significant morbidity and mortality of patients, along with increasing burden on their families, society and the health care system. This in part is due to increased incidence of liver disease associated factors such as metabolic syndrome; improved survival of patients with chronic predisposing conditions such as HIV; as well as advances in the field of transplantation and associated care leading to improved survival. The fact that one disease can result in different manifestations and outcomes highlights the need for improved understanding of not just genetic phenomenon predisposing to a condition, but additionally the role of epigenetic and environmental factors leading to the phenotype of the disease. It is not surprising that providers continue to face daily challenges pertaining to diagnostic accuracy, prognostication of disease severity, progression, and response to therapies. A number of these challenges can be addressed by incorporating a personalized approach of management to the current paradigm of care. Recent advances in the fields of molecular biology and genetics have paved the way to more accurate, individualized and precise approach to caring for liver disease. The study of microRNAs and their role in both healthy and diseased livers is one example of such advances. As these small, non-coding RNAs work on fine-tuning of cellular activities and organ function in a dynamic and precise fashion, they provide us a golden opportunity to advance the field of hepatology. The study of microRNAs in liver disease promises tremendous improvement in hepatology and is likely to lay the foundation towards a personalized approach in liver disease.

PMID: 27171116 [PubMed]

Brain Radiation Information Data Exchange (BRIDE): integration of experimental data from low-dose ionising radiation research for pathway discovery.

BMC Bioinformatics. 2016;17(1):212

Authors: Karapiperis C, Kempf SJ, Quintens R, Azimzadeh O, Vidal VL, Pazzaglia S, Bazyka D, Mastroberardino PG, Scouras ZG, Tapio S, Benotmane MA, Ouzounis CA

Abstract
BACKGROUND: The underlying molecular processes representing stress responses to low-dose ionising radiation (LDIR) in mammals are just beginning to be understood. In particular, LDIR effects on the brain and their possible association with neurodegenerative disease are currently being explored using omics technologies.
RESULTS: We describe a light-weight approach for the storage, analysis and distribution of relevant LDIR omics datasets. The data integration platform, called BRIDE, contains information from the literature as well as experimental information from transcriptomics and proteomics studies. It deploys a hybrid, distributed solution using both local storage and cloud technology.
CONCLUSIONS: BRIDE can act as a knowledge broker for LDIR researchers, to facilitate molecular research on the systems biology of LDIR response in mammals. Its flexible design can capture a range of experimental information for genomics, epigenomics, transcriptomics, and proteomics. The data collection is available at: <bride.azurewebsites.net>.

PMID: 27170263 [PubMed - in process]

Molecular stripping in the NF-κB/IκB/DNA genetic regulatory network.

Proc Natl Acad Sci U S A. 2016 Jan 5;113(1):110-5

Authors: Potoyan DA, Zheng W, Komives EA, Wolynes PG

Abstract
Genetic switches based on the [Formula: see text] system are master regulators of an array of cellular responses. Recent kinetic experiments have shown that [Formula: see text] can actively remove NF-κB bound to its genetic sites via a process called "molecular stripping." This allows the [Formula: see text] switch to function under kinetic control rather than the thermodynamic control contemplated in the traditional models of gene switches. Using molecular dynamics simulations of coarse-grained predictive energy landscape models for the constituent proteins by themselves and interacting with the DNA we explore the functional motions of the transcription factor [Formula: see text] and its various binary and ternary complexes with DNA and the inhibitor IκB. These studies show that the function of the [Formula: see text] genetic switch is realized via an allosteric mechanism. Molecular stripping occurs through the activation of a domain twist mode by the binding of [Formula: see text] that occurs through conformational selection. Free energy calculations for DNA binding show that the binding of [Formula: see text] not only results in a significant decrease of the affinity of the transcription factor for the DNA but also kinetically speeds DNA release. Projections of the free energy onto various reaction coordinates reveal the structural details of the stripping pathways.

PMID: 26699500 [PubMed - indexed for MEDLINE]

Generating Systems Biology Markup Language Models from the Synthetic Biology Open Language.

ACS Synth Biol. 2015 Aug 21;4(8):873-9

Authors: Roehner N, Zhang Z, Nguyen T, Myers CJ

Abstract
In the context of synthetic biology, model generation is the automated process of constructing biochemical models based on genetic designs. This paper discusses the use cases for model generation in genetic design automation (GDA) software tools and introduces the foundational concepts of standards and model annotation that make this process useful. Finally, this paper presents an implementation of model generation in the GDA software tool iBioSim and provides an example of generating a Systems Biology Markup Language (SBML) model from a design of a 4-input AND sensor written in the Synthetic Biology Open Language (SBOL).

PMID: 25822671 [PubMed - indexed for MEDLINE]

Quo vadis? The challenges of recombinant protein folding and secretion in Pichia pastoris.

Appl Microbiol Biotechnol. 2015 Apr;99(7):2925-38

Authors: Puxbaum V, Mattanovich D, Gasser B

Abstract
The development of Pichia pastoris as a production platform for recombinant proteins has been a remarkable success story over the last three decades. Stable cheap production processes and the good protein secretion abilities were pacemakers of this development. However, limitations of protein folding, glycosylation or secretion have been identified quite early on. With the availability of genome sequences and the development of systems biology characterization in the last 5 years, remarkable success in strain improvement was achieved. Here, we focus on recent developments of characterization and improvement of P. pastoris production strains regarding protein folding, intracellular trafficking, glycosylation and proteolytic degradation.

PMID: 25722021 [PubMed - indexed for MEDLINE]

The proteomic response of cheliped myofibril tissue in the eurythermal porcelain crab Petrolisthes cinctipes to heat shock following acclimation to daily temperature fluctuations.

J Exp Biol. 2015 Feb 1;218(Pt 3):388-403

Authors: Garland MA, Stillman JH, Tomanek L

Abstract
The porcelain crab Petrolisthes cinctipes lives under rocks and in mussel beds in the mid-intertidal zone where it experiences immersion during high tide and saturating humid conditions in air during low tide, which can increase habitat temperature by up to 20°C. To identify the biochemical changes affected by increasing temperature fluctuations and subsequent heat shock, we acclimated P. cinctipes for 30 days to one of three temperature regimes: (1) constant 10°C, (2) daily temperature fluctuations between 10 and 20°C (5 h up-ramp to 20°C, 1 h down-ramp to 10°C) and (3) 10-30°C (up-ramp to 30°C). After acclimation, animals were exposed to either 10°C or a 30°C heat shock to analyze the proteomic changes in claw muscle tissue. Following acclimation to 10-30°C (measured at 10°C), enolase and ATP synthase increased in abundance. Following heat shock, isoforms of arginine kinase and glycolytic enzymes such as aldolase, triose phosphate isomerase and glyceraldehyde 3-phosphate dehydrogenase increased across all acclimation regimes. Full-length isoforms of hemocyanin increased abundance following acclimation to 10-30°C, but hemocyanin fragments increased after heat shock following constant 10°C and fluctuating 10-20°C, possibly playing a role as antimicrobial peptides. Following constant 10°C and fluctuating 10-20°C, paramyosin and myosin heavy chain type-B increased in abundance, respectively, whereas myosin light and heavy chain decreased with heat shock. Actin-binding proteins, which stabilize actin filaments (filamin and tropomyosin), increased during heat shock following 10-30°C; however, actin severing and depolymerization proteins (gelsolin and cofilin) increased during heat shock following 10-20°C, possibly promoting muscle fiber restructuring. RAF kinase inhibitor protein and prostaglandin reductase increased during heat shock following constant 10°C and fluctuating 10-20°C, possibly inhibiting an immune response during heat shock. The results suggest that ATP supply, muscle fiber restructuring and immune responses are all affected by temperature fluctuations and subsequent acute heat shock in muscle tissue. Furthermore, although heat shock after acclimation to constant 10°C and fluctuating 10-30°C showed the greatest effects on the proteome, moderately fluctuating temperatures (10-20°C) broadened the temperature range over which claw muscle was able to respond to an acute heat shock with limited changes in the muscle proteome.

PMID: 25653421 [PubMed - indexed for MEDLINE]

The microbiome-immune-host defense barrier complex (microimmunosome) and developmental programming of noncommunicable diseases.

Reprod Toxicol. 2016 May 7;

Authors: R Dietert R

Abstract
Through its role as gatekeeper and filter to the external world, the microbiome affects developmental programming of physiological systems including the immune system. In turn, the immune system must tolerate, personalize, and prune the microbiome. Immune and host barrier status in early life significantly effects everything from embryo viability and pregnancy duration to the likelihood of misregulated inflammation, and risk of noncommunicable diseases (NCDs). Since the programming of and interactions among the microbiome, the host defense barrier, and the immune system can affect inflammation-driven health risks across the lifespan, a systems biology-type understanding of these three biological components may be useful. Here, I consider the potential utility of focusing on programming of a newly-defined systems biology unit termed the "microimmunosome."

PMID: 27167696 [PubMed - as supplied by publisher]

Sparse factor model for co-expression networks with an application using prior biological knowledge.

Stat Appl Genet Mol Biol. 2016 May 11;

Authors: Blum Y, Houée-Bigot M, Causeur D

Abstract
Inference on gene regulatory networks from high-throughput expression data turns out to be one of the main current challenges in systems biology. Such networks can be very insightful for the deep understanding of interactions between genes. Because genes-gene interactions is often viewed as joint contributions to known biological mechanisms, inference on the dependence among gene expressions is expected to be consistent to some extent with the functional characterization of genes which can be derived from ontologies (GO, KEGG, …). The present paper introduces a sparse factor model as a general framework either to account for a prior knowledge on joint contributions of modules of genes to latent biological processes or to infer on the corresponding co-expression network. We propose an ℓ1 - regularized EM algorithm to fit a sparse factor model for correlation. We demonstrate how it helps extracting modules of genes and more generally improves the gene clustering performance. The method is compared to alternative estimation procedures for sparse factor models of relevance networks in a simulation study. The integration of a biological knowledge based on the gene ontology (GO) is also illustrated on a liver expression data generated to understand adiposity variability in chicken.

PMID: 27166726 [PubMed - as supplied by publisher]

Many-molecule encapsulation by an icosahedral shell.

Elife. 2016 May 11;5

Authors: Perlmutter JD, Mohajerani F, Hagan MF

Abstract
We computationally study how an icosahedral shell assembles around hundreds of molecules. Such a process occurs during the formation of the carboxysome, a bacterial microcompartment that assembles around many copies of the enzymes ribulose 1,5-bisphosphate carboxylase/oxygenase and carbonic anhydrase to facilitate carbon fixation in cyanobacteria. Our simulations identify two classes of assembly pathways leading to encapsulation of many-molecule cargoes. In one, shell assembly proceeds concomitantly with cargo condensation. In the other, the cargo first forms a dense globule; then, shell proteins assemble around and bud from the condensed cargo complex. Although the model is simplified, the simulations predict intermediates and closure mechanisms not accessible in experiments, and show how assembly can be tuned between these two pathways by modulating protein interactions. In addition to elucidating assembly pathways and critical control parameters for microcompartment assembly, our results may guide the reengineering of viruses as nanoreactors that self-assemble around their reactants.

PMID: 27166515 [PubMed - as supplied by publisher]

Computational modeling approaches in gonadotropin signaling.

Theriogenology. 2016 Apr 20;

Authors: Ayoub MA, Yvinec R, Crépieux P, Poupon A

Abstract
Follicle-stimulating hormone and LH play essential roles in animal reproduction. They exert their function through binding to their cognate receptors, which belong to the large family of G protein-coupled receptors. This recognition at the plasma membrane triggers a plethora of cellular events, whose processing and integration ultimately lead to an adapted biological response. Understanding the nature and the kinetics of these events is essential for innovative approaches in drug discovery. The study and manipulation of such complex systems requires the use of computational modeling approaches combined with robust in vitro functional assays for calibration and validation. Modeling brings a detailed understanding of the system and can also be used to understand why existing drugs do not work as well as expected, and how to design more efficient ones.

PMID: 27165991 [PubMed - as supplied by publisher]

Punctuated evolution and transitional hybrid network in an ancestral cell cycle of fungi.

Elife. 2016;5

Authors: Medina EM, Turner JJ, Gordân R, Skotheim JM, Buchler NE

Abstract
Although cell cycle control is an ancient, conserved, and essential process, some core animal and fungal cell cycle regulators share no more sequence identity than non-homologous proteins. Here, we show that evolution along the fungal lineage was punctuated by the early acquisition and entrainment of the SBF transcription factor through horizontal gene transfer. Cell cycle evolution in the fungal ancestor then proceeded through a hybrid network containing both SBF and its ancestral animal counterpart E2F, which is still maintained in many basal fungi. We hypothesize that a virally-derived SBF may have initially hijacked cell cycle control by activating transcription via the cis-regulatory elements targeted by the ancestral cell cycle regulator E2F, much like extant viral oncogenes. Consistent with this hypothesis, we show that SBF can regulate promoters with E2F binding sites in budding yeast.

PMID: 27162172 [PubMed - in process]

Global de novo protein-protein interactome elucidates interactions of drought responsive proteins in horsegram (Macrotyloma uniflorum).

J Proteome Res. 2016 May 10;

Authors: Bhardwaj J, Gangwar I, Panzade GP, Shankar R, Yadav SK

Abstract
Inspired by the availability of de novo transcriptome of horsegram (Macrotyloma uniflorum) and recent developments in systems biology studies, first ever global protein-protein interactome (PPI) map was constructed for this highly drought tolerant legume. Large-scale studies of PPIs and the constructed database would provide rationale behind the interplay at cascading translational levels for drought stress adaptive mechanisms in horsegram. Using a bidirectional approach (interolog and domain-based), a high confidence interactome map and database for horsegram was constructed. Available transcriptomic information for shoot and root tissues of a sensitive genotype (M-191; genotype 1) and a drought tolerant (M-249; genotype 2) of horsegram was utilized to draw comparative PPI sub-networks under drought stress. High confidence 6804 interactions were predicted among 1812 proteins covering about one-fourth of the horsegram proteome. Highest number of interactions (33.86%) in horsegram interactome matched with Arabidopsis PPI data. Top five hub nodes mostly included ubiquitin and heat shock related proteins. Higher numbers of PPIs were found to be responsive in shoot tissue (416) and root tissue (2228) of genotype 2 compared to shoot tissue (136) and root tissue (579) of genotype 1. Characterization of PPIs using gene ontology analysis revealed that kinase and transferase activities involved in signal transduction, cellular processes, nucleocytoplasmic transport, protein ubiquitination and localization of molecules were most responsive to drought stress. Hence, these could be framed in stress adaptive mechanisms of horsegram. Being the first legume global PPI map, it would provide new insights in gene and protein regulatory networks for drought stress tolerance mechanisms in horsegram. Information compiled in form of database (MauPIR) will provide the much needed high confidence systems biology information for horsegram genes, proteins and involved processes. This information would ease the effort and increase the efficacy for similar studies on other legumes. Public access is available at http://14.139.59.221/MauPIR/.

PMID: 27161830 [PubMed - as supplied by publisher]

Proteome-wide alterations on adipose tissue from obese patients as age-, diabetes- and gender-specific hallmarks.

Sci Rep. 2016;6:25756

Authors: Gómez-Serrano M, Camafeita E, García-Santos E, López JA, Rubio MA, Sánchez-Pernaute A, Torres A, Vázquez J, Peral B

Abstract
Obesity is a main global health issue and an outstanding cause of morbidity and mortality predisposing to type 2 diabetes (T2DM) and cardiovascular diseases. Huge research efforts focused on gene expression, cellular signalling and metabolism in obesity have improved our understanding of these disorders; nevertheless, to bridge the gap between the regulation of gene expression and changes in signalling/metabolism, protein levels must be assessed. We have extensively analysed visceral adipose tissue from age-, T2DM- and gender-matched obese patients using high-throughput proteomics and systems biology methods to identify new biomarkers for the onset of T2DM in obesity, as well as to gain insight into the influence of aging and gender in these disorders. About 250 proteins showed significant abundance differences in the age, T2DM and gender comparisons. In diabetic patients, remarkable gender-specific hallmarks were discovered regarding redox status, immune response and adipose tissue accumulation. Both aging and T2DM processes were associated with mitochondrial remodelling, albeit through well-differentiated proteome changes. Systems biology analysis highlighted mitochondrial proteins that could play a key role in the age-dependent pathophysiology of T2DM. Our findings could serve as a framework for future research in Translational Medicine directed at improving the quality of life of obese patients.

PMID: 27160966 [PubMed - in process]