Recon2Neo4j: Applying graph database technologies for managing comprehensive genome-scale networks.

Bioinformatics. 2016 Dec 19;:

Authors: Balaur I, Mazein A, Saqi M, Lysenko A, Rawlings CJ, Auffray C

Abstract
The goal of this work is to offer a computational framework for exploring data from the Recon2 human metabolic reconstruction model. Advanced user access features have been developed using the Neo4j graph database technology and this paper describes key features such as efficient management of the network data, examples of the network querying for addressing particular tasks, and how query results are converted back to the Systems Biology Markup Language (SBML) standard format. The Neo4j-based metabolic framework facilitates exploration of highly-connected and comprehensive human metabolic data and identification of metabolic subnetworks of interest. A Java-based parser component has been developed to convert query results (available in the JSON format) into SBML and SIF formats in order to facilitate further results exploration, enhancement or network sharing.
AVAILABILITY: The Neo4j-based metabolic framework is freely available from: https://diseaseknowledgebase.etriks.org/metabolic/browser/ The java code files developed for this work are available from the following url: https://github.com/ibalaur/MetabolicFramework CONTACT: ibalaur@eisbm.org SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID: 27993779 [PubMed - as supplied by publisher]

Current Experimental Methods for Characterizing Protein-Protein Interactions.

ChemMedChem. 2016 Apr 19;11(8):738-56

Authors: Zhou M, Li Q, Wang R

Abstract
Protein molecules often interact with other partner protein molecules in order to execute their vital functions in living organisms. Characterization of protein-protein interactions thus plays a central role in understanding the molecular mechanism of relevant protein molecules, elucidating the cellular processes and pathways relevant to health or disease for drug discovery, and charting large-scale interaction networks in systems biology research. A whole spectrum of methods, based on biophysical, biochemical, or genetic principles, have been developed to detect the time, space, and functional relevance of protein-protein interactions at various degrees of affinity and specificity. This article presents an overview of these experimental methods, outlining the principles, strengths and limitations, and recent developments of each type of method.

PMID: 26864455 [PubMed - indexed for MEDLINE]

Using Sub-Network Combinations to Scale Up an Enumeration Method for Determining the Network Structures of Biological Functions.

PLoS One. 2016;11(12):e0168214

Authors: Xi JY, Ouyang Q

Abstract
Deduction of biological regulatory networks from their functions is one of the focus areas of systems biology. Among the different techniques used in this reverse-engineering task, one powerful method is to enumerate all candidate network structures to find suitable ones. However, this method is severely limited by calculation capability: due to the brute-force approach, it is infeasible for networks with large number of nodes to be studied using traditional enumeration method because of the combinatorial explosion. In this study, we propose a new reverse-engineering technique based on the enumerating method: sub-network combinations. First, a complex biological function is divided into several sub-functions. Next, the three-node-network enumerating method is applied to search for sub-networks that are able to realize each of the sub-functions. Finally, complex whole networks are constructed by enumerating all possible combinations of sub-networks. The optimal ones are selected and analyzed. To demonstrate the effectiveness of this new method, we used it to deduct the network structures of a Pavlovian-like function. The whole Pavlovian-like network was successfully constructed by combining robust sub-networks, and the results were analyzed. With sub-network combination, the complexity has been largely reduced. Our method also provides a functional modular view of biological systems.

PMID: 27992476 [PubMed - in process]

Biological causal links on physiological and evolutionary time scales.

Elife. 2016 Apr 26;5:e14424

Authors: Karmon A, Pilpel Y

Abstract
Correlation does not imply causation. If two variables, say A and B, are correlated, it could be because A causes B, or that B causes A, or because a third factor affects them both. We suggest that in many cases in biology, the causal link might be bi-directional: A causes B through a fast-acting physiological process, while B causes A through a slowly accumulating evolutionary process. Furthermore, many trained biologists tend to consistently focus at first on the fast-acting direction, and overlook the slower process in the opposite direction. We analyse several examples from modern biology that demonstrate this bias (codon usage optimality and gene expression, gene duplication and genetic dispensability, stem cell division and cancer risk, and the microbiome and host metabolism) and also discuss an example from linguistics. These examples demonstrate mutual effects between the fast physiological processes and the slow evolutionary ones. We believe that building awareness of inference biases among biologists who tend to prefer one causal direction over another could improve scientific reasoning.

PMID: 27113916 [PubMed - indexed for MEDLINE]

Dissecting mechanisms of mouse embryonic stem cells heterogeneity through a model-based analysis of transcription factor dynamics.

J R Soc Interface. 2016 Apr;13(117):

Authors: Herberg M, Glauche I, Zerjatke T, Winzi M, Buchholz F, Roeder I

Abstract
Pluripotent mouse embryonic stem cells (mESCs) show heterogeneous expression levels of transcription factors (TFs) involved in pluripotency regulation, among them Nanog and Rex1. The expression of both TFs can change dynamically between states of high and low activity, correlating with the cells' capacity for self-renewal. Stochastic fluctuations as well as sustained oscillations in gene expression are possible mechanisms to explain this behaviour, but the lack of suitable data hampered their clear distinction. Here, we present a systems biology approach in which novel experimental data on TF heterogeneity is complemented by an agent-based model of mESC self-renewal. Because the model accounts for intracellular interactions, cell divisions and heredity structures, it allows for evaluating the consistency of the proposed mechanisms with data on population growth and on TF dynamics after cell sorting. Our model-based analysis revealed that a bistable, noise-driven network model fulfils the minimal requirements to consistently explain Nanog and Rex1 expression dynamics in heterogeneous and sorted mESC populations. Moreover, we studied the impact of TF-related proliferation capacities on the frequency of state transitions and demonstrate that cellular genealogies can provide insights into the heredity structures of mESCs.

PMID: 27097654 [PubMed - indexed for MEDLINE]

Systems Vaccinology: Applications, Trends, and Perspectives.

Methods Mol Biol. 2016;1403:107-30

Authors: Sollner J

Abstract
The strategies employed in vaccinology have improved since the seminal work of Edward Jenner in the eighteenth century. Stimulated by failure to develop vaccines for cancers and chronic infectious diseases as well as an emergence of a multitude of new technologies not available earlier, vaccinology has moved from a largely experimental art to a new phase of innovation. Currently, immune reactions can be predicted and modeled before they occur and formulations can be optimized in advance for genetic background, age, sex, lifestyle, environmental factors, and microbiome. A multitude of scientific insights and technological advancements have led us to this current status, yet possibly none of the recent developments is individually more promising to achieve these goals than the interdisciplinary science of systems vaccinology. This review summarizes current trends and applications of systems vaccinology, including technically tangible areas of vaccine and immunology research which allow the transformative process into a truly broad understanding of vaccines, thereby effectively modeling interaction of vaccines with health and disease. It is becoming clear that a multitude of factors have to be considered to understand inter-patient variability of vaccine responses including those characterized from the interfaces between the immune system, microbiome, metabolome, and the nervous system.

PMID: 27076127 [PubMed - indexed for MEDLINE]

Synthetic biology and regulatory networks: where metabolic systems biology meets control engineering.

J R Soc Interface. 2016 Apr;13(117):

Authors: He F, Murabito E, Westerhoff HV

Abstract
Metabolic pathways can be engineered to maximize the synthesis of various products of interest. With the advent of computational systems biology, this endeavour is usually carried out through in silico theoretical studies with the aim to guide and complement further in vitro and in vivo experimental efforts. Clearly, what counts is the result in vivo, not only in terms of maximal productivity but also robustness against environmental perturbations. Engineering an organism towards an increased production flux, however, often compromises that robustness. In this contribution, we review and investigate how various analytical approaches used in metabolic engineering and synthetic biology are related to concepts developed by systems and control engineering. While trade-offs between production optimality and cellular robustness have already been studied diagnostically and statically, the dynamics also matter. Integration of the dynamic design aspects of control engineering with the more diagnostic aspects of metabolic, hierarchical control and regulation analysis is leading to the new, conceptual and operational framework required for the design of robust and productive dynamic pathways.

PMID: 27075000 [PubMed - indexed for MEDLINE]

Noise modulation in retinoic acid signaling sharpens segmental boundaries of gene expression in the embryonic zebrafish hindbrain.

Elife. 2016 Apr 12;5:e14034

Authors: Sosnik J, Zheng L, Rackauckas CV, Digman M, Gratton E, Nie Q, Schilling TF

Abstract
Morphogen gradients induce sharply defined domains of gene expression in a concentration-dependent manner, yet how cells interpret these signals in the face of spatial and temporal noise remains unclear. Using fluorescence lifetime imaging microscopy (FLIM) and phasor analysis to measure endogenous retinoic acid (RA) directly in vivo, we have investigated the amplitude of noise in RA signaling, and how modulation of this noise affects patterning of hindbrain segments (rhombomeres) in the zebrafish embryo. We demonstrate that RA forms a noisy gradient during critical stages of hindbrain patterning and that cells use distinct intracellular binding proteins to attenuate noise in RA levels. Increasing noise disrupts sharpening of rhombomere boundaries and proper patterning of the hindbrain. These findings reveal novel cellular mechanisms of noise regulation, which are likely to play important roles in other aspects of physiology and disease.

PMID: 27067377 [PubMed - indexed for MEDLINE]

An Immunological Perspective on Neonatal Sepsis.

Trends Mol Med. 2016 Apr;22(4):290-302

Authors: Kan B, Razzaghian HR, Lavoie PM

Abstract
Despite concerted international efforts, mortality from neonatal infections remains unacceptably high in some areas of the world, particularly for premature infants. Recent developments in flow cytometry and next-generation sequencing technologies have led to major discoveries over the past few years, providing a more integrated understanding of the developing human immune system in the context of its microbial environment. We review these recent findings, focusing on how in human newborns incomplete maturation of the immune system before a full term of gestation impacts on their vulnerability to infection. We also discuss some of the clinical implications of this research in guiding the design of more-accurate age-adapted diagnostic and preventive strategies for neonatal sepsis.

PMID: 26993220 [PubMed - indexed for MEDLINE]

Mixed-mode oscillations and population bursting in the pre-Bötzinger complex.

Elife. 2016 Mar 14;5:e13403

Authors: Bacak BJ, Kim T, Smith JC, Rubin JE, Rybak IA

Abstract
This study focuses on computational and theoretical investigations of neuronal activity arising in the pre-Bötzinger complex (pre-BötC), a medullary region generating the inspiratory phase of breathing in mammals. A progressive increase of neuronal excitability in medullary slices containing the pre-BötC produces mixed-mode oscillations (MMOs) characterized by large amplitude population bursts alternating with a series of small amplitude bursts. Using two different computational models, we demonstrate that MMOs emerge within a heterogeneous excitatory neural network because of progressive neuronal recruitment and synchronization. The MMO pattern depends on the distributed neuronal excitability, the density and weights of network interconnections, and the cellular properties underlying endogenous bursting. Critically, the latter should provide a reduction of spiking frequency within neuronal bursts with increasing burst frequency and a dependence of the after-burst recovery period on burst amplitude. Our study highlights a novel mechanism by which heterogeneity naturally leads to complex dynamics in rhythmic neuronal populations.

PMID: 26974345 [PubMed - indexed for MEDLINE]

Learning (from) the errors of a systems biology model.

Sci Rep. 2016 Feb 11;6:20772

Authors: Engelhardt B, Frőhlich H, Kschischo M

Abstract
Mathematical modelling is a labour intensive process involving several iterations of testing on real data and manual model modifications. In biology, the domain knowledge guiding model development is in many cases itself incomplete and uncertain. A major problem in this context is that biological systems are open. Missed or unknown external influences as well as erroneous interactions in the model could thus lead to severely misleading results. Here we introduce the dynamic elastic-net, a data driven mathematical method which automatically detects such model errors in ordinary differential equation (ODE) models. We demonstrate for real and simulated data, how the dynamic elastic-net approach can be used to automatically (i) reconstruct the error signal, (ii) identify the target variables of model error, and (iii) reconstruct the true system state even for incomplete or preliminary models. Our work provides a systematic computational method facilitating modelling of open biological systems under uncertain knowledge.

PMID: 26865316 [PubMed - indexed for MEDLINE]

Atlas Toolkit: Fast registration of 3D morphological datasets in the absence of landmarks.

Sci Rep. 2016 Feb 11;6:20732

Authors: Grocott T, Thomas P, Münsterberg AE

Abstract
Image registration is a gateway technology for Developmental Systems Biology, enabling computational analysis of related datasets within a shared coordinate system. Many registration tools rely on landmarks to ensure that datasets are correctly aligned; yet suitable landmarks are not present in many datasets. Atlas Toolkit is a Fiji/ImageJ plugin collection offering elastic group-wise registration of 3D morphological datasets, guided by segmentation of the interesting morphology. We demonstrate the method by combinatorial mapping of cell signalling events in the developing eyes of chick embryos, and use the integrated datasets to predictively enumerate Gene Regulatory Network states.

PMID: 26864723 [PubMed - indexed for MEDLINE]

Functional and Genomic Features of Human Genes Mutated in Neuropsychiatric Disorders.

Open Neurol J. 2016;10:143-148

Authors: Forero DA, Prada CF, Perry G

Abstract
BACKGROUND: In recent years, a large number of studies around the world have led to the identification of causal genes for hereditary types of common and rare neurological and psychiatric disorders.
OBJECTIVE: To explore the functional and genomic features of known human genes mutated in neuropsychiatric disorders.
METHODS: A systematic search was used to develop a comprehensive catalog of genes mutated in neuropsychiatric disorders (NPD). Functional enrichment and protein-protein interaction analyses were carried out. A false discovery rate approach was used for correction for multiple testing.
RESULTS: We found several functional categories that are enriched among NPD genes, such as gene ontologies, protein domains, tissue expression, signaling pathways and regulation by brain-expressed miRNAs and transcription factors. Sixty six of those NPD genes are known to be druggable. Several topographic parameters of protein-protein interaction networks and the degree of conservation between orthologous genes were identified as significant among NPD genes.
CONCLUSION: These results represent one of the first analyses of enrichment of functional categories of genes known to harbor mutations for NPD. These findings could be useful for a future creation of computational tools for prioritization of novel candidate genes for NPD.

PMID: 27990183 [PubMed - in process]

AVP1: One Protein, Many Roles.

Trends Plant Sci. 2016 Dec 15;:

Authors: Schilling RK, Tester M, Marschner P, Plett DC, Roy SJ

Abstract
Constitutive expression of the Arabidopsis vacuolar proton-pumping pyrophosphatase (H(+)-PPase) gene (AVP1) increases plant growth under various abiotic stress conditions and, importantly, under nonstressed conditions. Many interpretations have been proposed to explain these phenotypes, including greater vacuolar ion sequestration, increased auxin transport, enhanced heterotrophic growth, and increased transport of sucrose from source to sink tissues. In this review, we evaluate all the roles proposed for AVP1, using findings published to date from mutant plants lacking functional AVP1 and transgenic plants expressing AVP1. It is clear that AVP1 is one protein with many roles, and that one or more of these roles act to enhance plant growth. The complexity suggests that a systems biology approach to evaluate biological networks is required to investigate these intertwined roles.

PMID: 27989652 [PubMed - as supplied by publisher]

Cellular and humoral biomarkers of Bronchopulmonary Dysplasia.

Early Hum Dev. 2016 Dec 15;:

Authors: Lal CV, Ambalavanan N

Abstract
The pathogenesis of Bronchopulmonary Dysplasia (BPD) is multifactorial and the clinical phenotype of BPD is extremely variable. Predicting BPD is difficult, as it is a disease with a clinical operational definition but many clinical phenotypes and endotypes. Most biomarkers studied over the years have low predictive accuracy, and none are currently used in routine clinical care or shown to be useful for predicting longer-term respiratory outcome. Targeted cellular and humoral biomarkers and novel systems biology 'omic' based approaches including genomic and microbiomic analyses are described in this review.

PMID: 27989587 [PubMed - as supplied by publisher]

Gene Architectures that Minimize Cost of Gene Expression.

Mol Cell. 2016 Nov 25;:

Authors: Frumkin I, Schirman D, Rotman A, Li F, Zahavi L, Mordret E, Asraf O, Wu S, Levy SF, Pilpel Y

Abstract
Gene expression burdens cells by consuming resources and energy. While numerous studies have investigated regulation of expression level, little is known about gene design elements that govern expression costs. Here, we ask how cells minimize production costs while maintaining a given protein expression level and whether there are gene architectures that optimize this process. We measured fitness of ∼14,000 E. coli strains, each expressing a reporter gene with a unique 5' architecture. By comparing cost-effective and ineffective architectures, we found that cost per protein molecule could be minimized by lowering transcription levels, regulating translation speeds, and utilizing amino acids that are cheap to synthesize and that are less hydrophobic. We then examined natural E. coli genes and found that highly expressed genes have evolved more forcefully to minimize costs associated with their expression. Our study thus elucidates gene design elements that improve the economy of protein expression in natural and heterologous systems.

PMID: 27989436 [PubMed - as supplied by publisher]

PGSB/MIPS PlantsDB Database Framework for the Integration and Analysis of Plant Genome Data.

Methods Mol Biol. 2017;1533:33-44

Authors: Spannagl M, Nussbaumer T, Bader K, Gundlach H, Mayer KF

Abstract
Plant Genome and Systems Biology (PGSB), formerly Munich Institute for Protein Sequences (MIPS) PlantsDB, is a database framework for the integration and analysis of plant genome data, developed and maintained for more than a decade now. Major components of that framework are genome databases and analysis resources focusing on individual (reference) genomes providing flexible and intuitive access to data. Another main focus is the integration of genomes from both model and crop plants to form a scaffold for comparative genomics, assisted by specialized tools such as the CrowsNest viewer to explore conserved gene order (synteny). Data exchange and integrated search functionality with/over many plant genome databases is provided within the transPLANT project.

PMID: 27987163 [PubMed - in process]

Disease Model of GATA4 Mutation Reveals Transcription Factor Cooperativity in Human Cardiogenesis.

Cell. 2016 Dec 15;167(7):1734-1749.e22

Authors: Ang YS, Rivas RN, Ribeiro AJ, Srivas R, Rivera J, Stone NR, Pratt K, Mohamed TM, Fu JD, Spencer CI, Tippens ND, Li M, Narasimha A, Radzinsky E, Moon-Grady AJ, Yu H, Pruitt BL, Snyder MP, Srivastava D

Abstract
Mutation of highly conserved residues in transcription factors may affect protein-protein or protein-DNA interactions, leading to gene network dysregulation and human disease. Human mutations in GATA4, a cardiogenic transcription factor, cause cardiac septal defects and cardiomyopathy. Here, iPS-derived cardiomyocytes from subjects with a heterozygous GATA4-G296S missense mutation showed impaired contractility, calcium handling, and metabolic activity. In human cardiomyocytes, GATA4 broadly co-occupied cardiac enhancers with TBX5, another transcription factor that causes septal defects when mutated. The GATA4-G296S mutation disrupted TBX5 recruitment, particularly to cardiac super-enhancers, concomitant with dysregulation of genes related to the phenotypic abnormalities, including cardiac septation. Conversely, the GATA4-G296S mutation led to failure of GATA4 and TBX5-mediated repression at non-cardiac genes and enhanced open chromatin states at endothelial/endocardial promoters. These results reveal how disease-causing missense mutations can disrupt transcriptional cooperativity, leading to aberrant chromatin states and cellular dysfunction, including those related to morphogenetic defects.

PMID: 27984724 [PubMed - in process]

Ribosome profiling reveals an adaptation strategy of reduced bacterium to acute stress.

Biochimie. 2016 Oct 27;:

Authors: Fisunov GY, Evsyutina DV, Garanina IA, Arzamasov AA, Butenko IO, Altukhov IA, Nikitina AS, Govorun VM

Abstract
Bacteria of class Mollicutes (mycoplasmas) feature significant genome reduction which makes them good model organisms for systems biology studies. Previously we demonstrated, that drastic transcriptional response of mycoplasmas to stress results in a very limited response on the level of protein. In this study we used heat stress model of M. gallisepticum and ribosome profiling to elucidate the process of genetic information transfer under stress. We found that under heat stress ribosomes demonstrate selectivity towards mRNA binding. We identified that heat stress response may be divided into two groups on the basis of absolute transcript abundance and fold-change in the translatome. One represents a noise-like response and another is likely an adaptive one. The latter include ClpB chaperone, cell division cluster, homologs of immunoblocking proteins and short ORFs with unknown function. We found that previously identified read-through of terminators contributes to the upregulation of transcripts in the translatome as well. In addition we identified that ribosomes of M. gallisepticum undergo reorganization under the heat stress. The most notable event is decrease of the amount of associated HU protein. In conclusion, only changes of few adaptive transcripts significantly impact translatome, while widespread noise-like transcription plays insignificant role in translation during stress.

PMID: 27984202 [PubMed - as supplied by publisher]

Algal Cell Factories: Approaches, Applications, and Potentials.

Mar Drugs. 2016 Dec 13;14(12):

Authors: Fu W, Chaiboonchoe A, Khraiwesh B, Nelson DR, Al-Khairy D, Mystikou A, Alzahmi A, Salehi-Ashtiani K

Abstract
With the advent of modern biotechnology, microorganisms from diverse lineages have been used to produce bio-based feedstocks and bioactive compounds. Many of these compounds are currently commodities of interest, in a variety of markets and their utility warrants investigation into improving their production through strain development. In this review, we address the issue of strain improvement in a group of organisms with strong potential to be productive "cell factories": the photosynthetic microalgae. Microalgae are a diverse group of phytoplankton, involving polyphyletic lineage such as green algae and diatoms that are commonly used in the industry. The photosynthetic microalgae have been under intense investigation recently for their ability to produce commercial compounds using only light, CO₂, and basic nutrients. However, their strain improvement is still a relatively recent area of work that is under development. Importantly, it is only through appropriate engineering methods that we may see the full biotechnological potential of microalgae come to fruition. Thus, in this review, we address past and present endeavors towards the aim of creating productive algal cell factories and describe possible advantageous future directions for the field.

PMID: 27983586 [PubMed - in process]