Recent Developments in Systems Biology and Metabolic Engineering of Plant-Microbe Interactions.

Front Plant Sci. 2016;7:1421

Authors: Kumar V, Baweja M, Singh PK, Shukla P

Abstract
Microorganisms play a crucial role in the sustainability of the various ecosystems. The characterization of various interactions between microorganisms and other biotic factors is a necessary footstep to understand the association and functions of microbial communities. Among the different microbial interactions in an ecosystem, plant-microbe interaction plays an important role to balance the ecosystem. The present review explores plant-microbe interactions using gene editing and system biology tools toward the comprehension in improvement of plant traits. Further, system biology tools like FBA (flux balance analysis), OptKnock, and constraint-based modeling helps in understanding such interactions as a whole. In addition, various gene editing tools have been summarized and a strategy has been hypothesized for the development of disease free plants. Furthermore, we have tried to summarize the predictions through data retrieved from various types of sources such as high throughput sequencing data (e.g., single nucleotide polymorphism detection, RNA-seq, proteomics) and metabolic models have been reconstructed from such sequences for species communities. It is well known fact that systems biology approaches and modeling of biological networks will enable us to learn the insight of such network and will also help further in understanding these interactions.

PMID: 27725824 [PubMed - in process]

The "omics" of human male infertility: integrating big data in a systems biology approach.

Cell Tissue Res. 2016 Jan;363(1):295-312

Authors: Carrell DT, Aston KI, Oliva R, Emery BR, De Jonge CJ

Abstract
Spermatogenesis is a complex process in which >2300 genes are temporally and spatially regulated to form a terminally differentiated sperm cell that must maintain the ability to contribute to a totipotent embryo which can successfully differentiate into a healthy individual. This process is dependent on fidelity of the genome, epigenome, transcriptome, and proteome of the spermatogonia, supporting cells, and the resulting sperm cell. Infertility and/or disease risk may increase in the offspring if abnormalities are present. This review highlights the recent advances in our understanding of these processes in light of the "omics revolution". We briefly review each of these areas, as well as highlight areas of future study and needs to advance further.

PMID: 26661835 [PubMed - indexed for MEDLINE]

Multiple abiotic stimuli are integrated in the regulation of rice gene expression under field conditions.

Elife. 2015 Nov 26;4:

Authors: Plessis A, Hafemeister C, Wilkins O, Gonzaga ZJ, Meyer RS, Pires I, Müller C, Septiningsih EM, Bonneau R, Purugganan M

Abstract
Plants rely on transcriptional dynamics to respond to multiple climatic fluctuations and contexts in nature. We analyzed the genome-wide gene expression patterns of rice (Oryza sativa) growing in rainfed and irrigated fields during two distinct tropical seasons and determined simple linear models that relate transcriptomic variation to climatic fluctuations. These models combine multiple environmental parameters to account for patterns of expression in the field of co-expressed gene clusters. We examined the similarities of our environmental models between tropical and temperate field conditions, using previously published data. We found that field type and macroclimate had broad impacts on transcriptional responses to environmental fluctuations, especially for genes involved in photosynthesis and development. Nevertheless, variation in solar radiation and temperature at the timescale of hours had reproducible effects across environmental contexts. These results provide a basis for broad-based predictive modeling of plant gene expression in the field.

PMID: 26609814 [PubMed - indexed for MEDLINE]

Dynamics and heterogeneity of a fate determinant during transition towards cell differentiation.

Elife. 2015 Nov 19;4:

Authors: Peláez N, Gavalda-Miralles A, Wang B, Navarro HT, Gudjonson H, Rebay I, Dinner AR, Katsaggelos AK, Amaral LA, Carthew RW

Abstract
Yan is an ETS-domain transcription factor responsible for maintaining Drosophila eye cells in a multipotent state. Yan is at the core of a regulatory network that determines the time and place in which cells transit from multipotency to one of several differentiated lineages. Using a fluorescent reporter for Yan expression, we observed a biphasic distribution of Yan in multipotent cells, with a rapid inductive phase and slow decay phase. Transitions to various differentiated states occurred over the course of this dynamic process, suggesting that Yan expression level does not strongly determine cell potential. Consistent with this conclusion, perturbing Yan expression by varying gene dosage had no effect on cell fate transitions. However, we observed that as cells transited to differentiation, Yan expression became highly heterogeneous and this heterogeneity was transient. Signals received via the EGF Receptor were necessary for the transience in Yan noise since genetic loss caused sustained noise. Since these signals are essential for eye cells to differentiate, we suggest that dynamic heterogeneity of Yan is a necessary element of the transition process, and cell states are stabilized through noise reduction.

PMID: 26583752 [PubMed - indexed for MEDLINE]

Reproductive systems biology tackles global issues of population growth, food safety and reproductive health.

Cell Tissue Res. 2016 Jan;363(1):1-5

Authors: Sutovsky P, Cupp AS, Thompson W, Baker M

PMID: 26578088 [PubMed - indexed for MEDLINE]

Attention stabilizes the shared gain of V4 populations.

Elife. 2015 Nov 02;4:e08998

Authors: Rabinowitz NC, Goris RL, Cohen M, Simoncelli EP

Abstract
Responses of sensory neurons represent stimulus information, but are also influenced by internal state. For example, when monkeys direct their attention to a visual stimulus, the response gain of specific subsets of neurons in visual cortex changes. Here, we develop a functional model of population activity to investigate the structure of this effect. We fit the model to the spiking activity of bilateral neural populations in area V4, recorded while the animal performed a stimulus discrimination task under spatial attention. The model reveals four separate time-varying shared modulatory signals, the dominant two of which each target task-relevant neurons in one hemisphere. In attention-directed conditions, the associated shared modulatory signal decreases in variance. This finding provides an interpretable and parsimonious explanation for previous observations that attention reduces variability and noise correlations of sensory neurons. Finally, the recovered modulatory signals reflect previous reward, and are predictive of subsequent choice behavior.

PMID: 26523390 [PubMed - indexed for MEDLINE]

A proteomics approach to identifying key protein targets involved in VEGF inhibitor mediated attenuation of bleomycin-induced pulmonary fibrosis.

Proteomics. 2016 Jan;16(1):33-46

Authors: Kulkarni YM, Dutta S, Iyer AK, Venkatadri R, Kaushik V, Ramesh V, Wright CA, Semmes OJ, Yakisich JS, Azad N

Abstract
Idiopathic pulmonary fibrosis (IPF) is a progressive lung disease with a life expectancy of less than 5 years post diagnosis for most patients. Poor molecular characterization of IPF has led to insufficient understanding of the pathogenesis of the disease, resulting in lack of effective therapies. In this study, we have integrated a label-free LC-MS based approach with systems biology to identify signaling pathways and regulatory nodes within protein interaction networks that govern phenotypic changes that may lead to IPF. Ingenuity Pathway Analysis of proteins modulated in response to bleomycin treatment identified PI3K/Akt and Wnt signaling as the most significant profibrotic pathways. Similar analysis of proteins modulated in response to vascular endothelial growth factor (VEGF) inhibitor (CBO-P11) treatment identified natural killer cell signaling and PTEN signaling as the most significant antifibrotic pathways. Mechanistic/mammalian target of rapamycin (mTOR) and extracellular signal-regulated kinase (ERK) were identified to be key mediators of pro- and antifibrotic response, where bleomycin (BLM) treatment resulted in increased expression and VEGF inhibitor treatment attenuated expression of mTOR and ERK. Using a BLM mouse model of pulmonary fibrosis and VEGF inhibitor CBO-P11 as a therapeutic measure, we identified a comprehensive set of signaling pathways and proteins that contribute to the pathogenesis of pulmonary fibrosis that can be targeted for therapy against this fatal disease.

PMID: 26425798 [PubMed - indexed for MEDLINE]

Some assembly required: evolutionary and systems perspectives on the mammalian reproductive system.

Cell Tissue Res. 2016 Jan;363(1):267-78

Authors: Mordhorst BR, Wilson ML, Conant GC

Abstract
In this review, we discuss the way that insights from evolutionary theory and systems biology shed light on form and function in mammalian reproductive systems. In the first part of the review, we contrast the rapid evolution seen in some reproductive genes with the generally conservative nature of development. We discuss directional selection and coevolution as potential drivers of rapid evolution in sperm and egg proteins. Such rapid change is very different from the highly conservative nature of later embryo development. However, it is not unique, as some regions of the sex chromosomes also show elevated rates of evolutionary change. To explain these contradictory trends, we argue that it is not reproductive functions per se that induce rapid evolution. Rather, it is the fact that biotic interactions, such as speciation events and sexual conflict, have no evolutionary endpoint and hence can drive continuous evolutionary changes. Returning to the question of sex chromosome evolution, we discuss the way that recent advances in evolutionary genomics and systems biology and, in particular, the development of a theory of gene balance provide a better understanding of the evolutionary patterns seen on these chromosomes. We end the review with a discussion of a surprising and incompletely understood phenomenon observed in early embryos: namely the Warburg effect, whereby glucose is fermented to lactate and alanine rather than respired to carbon dioxide. We argue that evolutionary insights, from both yeasts and tumor cells, help to explain the Warburg effect, and that new metabolic modeling approaches are useful in assessing the potential sources of the effect.

PMID: 26254045 [PubMed - indexed for MEDLINE]

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The bm12 Inducible Model of Systemic Lupus Erythematosus (SLE) in C57BL/6 Mice.

J Vis Exp. 2015 Nov 01;(105):e53319

Authors: Klarquist J, Janssen EM

Abstract
Systemic lupus erythematosus (SLE) is an autoimmune disease with diverse clinical and immunological manifestations. Several spontaneous and inducible animal models mirror common components of human disease, including the bm12 transfer model. Upon transfer of bm12 splenocytes or purified CD4 T cells, C57BL/6 mice rapidly develop large frequencies of T follicular helper cells (Tfh), germinal center (GC) B cells, and plasma cells followed by high levels of circulating anti-nuclear antibodies. Since this model utilizes mice on a pure C57BL/6 background, researchers can quickly and easily study disease progression in transgenic or knockout mouse strains in a relatively short period of time. Here we describe protocols for the induction of the model and the quantitation Tfh, GC B cells, and plasma cells by multi-color flow cytometry. Importantly, these protocols can also be used to characterize disease in most mouse models of SLE and identify Tfh, GC B cells, and plasma cells in other disease models.

PMID: 26554458 [PubMed - indexed for MEDLINE]

Inferring unknown biological functions by integration of GO annotations and gene expression data.

IEEE/ACM Trans Comput Biol Bioinform. 2016 Oct 07;:

Authors: Leale G, Baya A, Milone D, Granitto P, Stegmayer G

Abstract
Characterizing genes with semantic information is an important process regarding the description of gene products. In spite that complete genomes of many organisms have been already sequenced, the biological functions of all of their genes are still unknown. Since experimentally studying the functions of those genes, one by one, would be unfeasible, new computational methods for gene functions inference are needed. We present here a novel computational approach for inferring biological function for a set of genes with previously unknown function, given a set of genes with well-known information. This approach is based on the premise that genes with similar behaviour should be grouped together. This is known as the guilt-by-association principle. Thus, it is possible to take advantage of clustering techniques to obtain groups of unknown genes that are co-clustered with genes that have well-known semantic information (GO annotations). Meaningful knowledge to infer unknown semantic information can therefore be provided by these well-known genes. We provide a method to explore the potential function of new genes according to those currently annotated. The results obtained indicate that the proposed approach could be a useful and effective tool when used by biologists to guide the inference of biological functions for recently discovered genes. Our work sets an important landmark in the field of identifying unknown gene functions through clustering, using an external source of biological input. A simple web interface to this proposal can be found at http://fich.unl.edu.ar/sinc/webdemo/gamma-am/.

PMID: 27723603 [PubMed - as supplied by publisher]

Facile and Phase-Defined Determination of HLA Alleles with Morpholino-Functionalized Nanoparticle Probes.

Nanomedicine. 2016 Oct 5;:

Authors: Zu Y, Tan MH, Ee CR, Ying JY

Abstract
A number of human leukocyte antigen (HLA) gene alleles have been found to be genetic risk markers for immunologically mediated drug hypersensitivity. Clinical adoption of HLA pharmacogenomics requires facile and accurate allele screening assays. As HLA genes are highly polymorphic, currently available methods are usually labor-intensive and liable to generate false positives. Herein we report a general strategy for screening HLA alleles with nanoparticle probes. Specific HLA alleles can be identified by gauging three to five sequence variants. Single-polymerase chain reaction (PCR) and dual-PCR methods have been proposed to achieve phase-defined determination of the sequence variants. Morpholino-functionalized gold nanoparticle probes allow for colorimetric and highly specific detection. Assays for HLA-B*58:01 and HLA-B*15:02 have been developed and validated with 49 selected human genomic DNA samples. The facile nanoparticle probe-based assays can be implemented easily in molecular diagnostic laboratories for accurate and cost-effective screening of HLA alleles.

PMID: 27720927 [PubMed - as supplied by publisher]

Personalized Learning: From Neurogenetics of Behaviors to Designing Optimal Language Training.

Neuropsychologia. 2016 Oct 5;:

Authors: Wong PC, Vuong L, Liu K

Abstract
Variability in drug responsivity has prompted the development of Personalized Medicine, which has shown great promise in utilizing genotypic information to develop safer and more effective drug regimens for patients. Similarly, individual variability in learning outcomes has puzzled researchers who seek to create optimal learning environments for students. "Personalized Learning" seeks to identify genetic, neural and behavioral predictors of individual differences in learning and aims to use predictors to help create optimal teaching paradigms. Evidence for Personalized Learning can be observed by connecting research in pharmacogenomics, cognitive genetics and behavioral experiments across domains of learning, which provides a framework for conducting empirical studies from the laboratory to the classroom and holds promise for addressing learning effectiveness in the individual learners. Evidence can also be seen in the subdomain of speech learning, thus providing initial support for the applicability of Personalized Learning to language.

PMID: 27720749 [PubMed - as supplied by publisher]

Pharmacogenomics and adverse drug reactions: Primetime and not ready for primetime tests.

J Allergy Clin Immunol. 2016 Oct;138(4):943-955

Authors: Khan DA

Abstract
Adverse drug reactions (ADRs) are a relatively common cause of morbidity and mortality. Many factors can contribute to ADRs, including genetics. The degree to which genetics contributes to ADRs is not entirely clear and varies by drug, as well as the type of ADR. Pharmacogenetics and, more recently, pharmacogenomics have been applied to the field of ADRs for both predictable ADRs and hypersensitivity drug reactions. Evaluations for glucose-6-phosphate dehydrogenase and thiopurine S-methyltransferase are commonplace clinical tests to reduce hematologic problems associated with drugs, such as dapsone and azathioprine, respectively. Numerous pharmacogenetic associations have been discovered for immediate hypersensitivity reactions to β-lactams, aspirin, and nonsteroidal anti-inflammatory drugs; however, the clinical utility of testing for these genetic associations has not been established. In contrast, pharmacogenetic testing for HLA-B*1502 before carbamazepine in patients of certain Asian ethnicities and testing for HLA-B*5701 before abacavir treatment are recommended. This review will focus on pharmacogenetics and pharmacogenomics and their role in reducing ADRs, especially those caused by drug hypersensitivity reactions.

PMID: 27720019 [PubMed - in process]

A model to assess the cost-effectiveness of pharmacogenomics tests in chronic heart failure: the case of ivabradine.

Pharmacogenomics. 2016 Oct 10;:

Authors: Iliza AC, Matteau A, Guertin JR, Mitchell D, Fanton-Aita F, Dubois A, Dubé MP, Tardif JC, LeLorier J

Abstract
Pharmacogenomics (PGx) tests have the potential of improving the effectiveness of expensive new drugs by predicting the likelihood, for a particular patient, to respond to a treatment. The objective of this study was to develop a pharmacoeconomic model to determine the characteristics and the cost-effectiveness of a hypothetical PGx test, which would identify patients who are most likely to respond to an expensive treatment for chronic heart failure. For this purpose, we chose the example of ivabradine. Our results suggest that the use of a PGx test that could select a subgroup of patients to be treated with an expensive drug has the potential to provide more efficient drug utilization.

PMID: 27719379 [PubMed - as supplied by publisher]

Pharmacogenetics driving personalized medicine: analysis of genetic polymorphisms related to breast cancer medications in Italian isolated populations.

J Transl Med. 2016 Jan 22;14:22

Authors: Cocca M, Bedognetti D, La Bianca M, Gasparini P, Girotto G

Abstract
BACKGROUND: Breast cancer is the most common cancer in women characterized by a high variable clinical outcome among individuals treated with equivalent regimens and novel targeted therapies. In this study, we performed a population based approach intersecting high-throughput genotype data from Friuli Venezia Giulia (FVG) isolated populations with publically available pharmacogenomics information to estimate the frequency of genotypes correlated with responsiveness to breast cancer treatment thus improving the clinical management of this disease in an efficient and cost effective way.
METHODS: A list of 80 variants reported to be related to the efficacy or toxicity of breast cancer drugs was obtained from PharmGKB database. Fourty-one were present in FVG, 1000G European (EUR) and ExAC (Non Finnish European) databases. Their frequency was extracted using PLINK software and the differences tested by Fisher's exact test.
RESULTS: Statistical analyses revealed that 13 out of the 41 (32 %) variants were significantly different in frequency in our sample as compared to the EUR/ExAC cohorts. For nine variants the available level of evidence (LOE) included polymorphisms related to cyclophosphamide, tamoxifen, doxorubicin, fluorpyrimidine and paclitaxel. In particular, for trastuzumab two variants were detected: (1) rs1801274-G within FCGR2A and associated with decreased efficacy (LOE 2B); (2) rs1136201-G located within ERBB2 and associated with increased toxicity (LOE 3). Both these two variants were underrepresented in the FVG population compared to EUR/ExAC population thus suggesting a high therapeutic index of this drug in our population. Moreover, as regards fluoropyrimidines, the frequency of two polymorphisms within the DPYD gene associated with drug toxicity (e.g., rs2297595-C allele and rs3918290-T allele, LOE 2A and 1, respectively) was extremely low in FVG population thus suggesting that a larger number of FVG patients could benefit from full dosage of fluoropyrimidine therapy.
CONCLUSIONS: All these findings increase the overall knowledge on the prevalence of specific variants related with breast cancer treatment responsiveness in FVG population and highlight the importance of assessing gene polymorphisms related with cancer medications in isolated communities.

PMID: 26801900 [PubMed - indexed for MEDLINE]

Past Roadblocks and New Opportunities in Transcription Factor Network Mapping.

Trends Genet. 2016 Oct 6;:

Authors: Brent MR

Abstract
One of the principal mechanisms by which cells differentiate and respond to changes in external signals or conditions is by changing the activity levels of transcription factors (TFs). This changes the transcription rates of target genes via the cell's TF network, which ultimately contributes to reconfiguring cellular state. Since microarrays provided our first window into global cellular state, computational biologists have eagerly attacked the problem of mapping TF networks, a key part of the cell's control circuitry. In retrospect, however, steady-state mRNA abundance levels were a poor substitute for TF activity levels and gene transcription rates. Likewise, mapping TF binding through chromatin immunoprecipitation proved less predictive of functional regulation and less amenable to systematic elucidation of complete networks than originally hoped. This review explains these roadblocks and the current, unprecedented blossoming of new experimental techniques built on second-generation sequencing, which hold out the promise of rapid progress in TF network mapping.

PMID: 27720190 [PubMed - as supplied by publisher]

Predictive biomarkers for linking disease pathology and drug effect.

Curr Pharm Des. 2016 Oct 06;:

Authors: Mayer B, Heinzel A, Lukas A, Perco P

Abstract
BACKGROUND: Productivity in drug R&D continues seeing significant attrition in clinical stage testing. Approval of new molecular entities proceeds with slow pace specifically when it comes to chronic, age-related diseases, calling for new conceptual approaches, methodological implementation and organizational adoption in drug development.
METHODS: Detailed phenotyping of disease presentation together with comprehensive representation of drug mechanism of action is considered as a path forward, and a big data spectrum has become available covering behavioral, clinical and molecular characteristics, the latter combining reductionist and explorative strategies. On this basis integrative analytics in the realm of Systems Biology has emerged, essentially aiming at traversing associations into causal relationships for bridging molecular disease specifics and clinical phenotype surrogates and finally explaining drug response and outcome.
RESULTS: From a conceptual perspective bottom-up modeling approaches are available, with dynamical hierarchies as formalism capable of describing clinical findings as emergent properties of an underlying molecular process network comprehensively resembling disease pathology. In such representation biomarker candidates serve as proxy of a molecular process set, at the interface of a corresponding representation of drug mechanism of action allowing patient stratification and prediction of drug response. In practical implementation network analytics on a protein coding gene level has provided a number of example cases for matching disease presentation and drug molecular effect, and workflows combining computational hypothesis generation and experimental evaluation have become available for systematically optimizing biomarker candidate selection.
CONCLUSION: With biomarker-based enrichment strategies in adaptive clinical trials, implementation routes for tackling development attrition are provided. Predictive biomarkers add precision in drug development and as companion diagnostics in clinical practice.

PMID: 27719641 [PubMed - as supplied by publisher]

In search for symmetries in the metabolism of cancer.

Wiley Interdiscip Rev Syst Biol Med. 2016 Jan-Feb;8(1):23-35

Authors: Gatto F, Nielsen J

Abstract
Even though aerobic glycolysis, or the Warburg effect, is arguably the most common trait of metabolic reprogramming in cancer, it is unobserved in certain tumor types. Systems biology advocates a global view on metabolism to dissect which traits are consistently reprogrammed in cancer, and hence likely to constitute an obligate step for the evolution of cancer cells. We refer to such traits as symmetric. Here, we review early systems biology studies that attempted to reveal symmetric traits in the metabolic reprogramming of cancer, discuss the symmetry of reprogramming of nucleotide metabolism, and outline the current limitations that, if unlocked, could elucidate whether symmetries in cancer metabolism may be claimed.

PMID: 26538017 [PubMed - indexed for MEDLINE]