Heme Mobilization in Animals: A Metallolipid's Journey.

Acc Chem Res. 2016 Jun 2;

Authors: Reddi AR, Hamza I

Abstract
Heme is universally recognized as an essential and ubiquitous prosthetic group that enables proteins to carry out a diverse array of functions. All heme-dependent processes, from protein hemylation to heme signaling, require the dynamic and rapid mobilization of heme to hemoproteins present in virtually every subcellular compartment. The cytotoxicity and hydrophobicity of heme necessitates that heme mobilization is carefully controlled at the cellular and systemic level. However, the molecules and mechanisms that mediate heme homeostasis are poorly understood. In this Account, we provide a heuristic paradigm with which to conceptualize heme trafficking and highlight the most recent developments in the mechanisms underlying heme trafficking. As an iron-containing tetrapyrrole, heme exhibits properties of both transition metals and lipids. Accordingly, we propose its transport and trafficking will reflect principles gleaned from the trafficking of both metals and lipids. Using this conceptual framework, we follow the flow of heme from the final step of heme synthesis in the mitochondria to hemoproteins present in various subcellular organelles. Further, given that many cells and animals that cannot make heme can assimilate it intact from nutritional sources, we propose that intercellular heme trafficking pathways must exist. This necessitates that heme be able to be imported and exported from cells, escorted between cells and organs, and regulated at the organismal level via a coordinated systemic process. In this Account, we highlight recently discovered heme transport and trafficking factors and provide the biochemical foundation for the cell and systems biology of heme. Altogether, we seek to reconceptualize heme from an exchange inert cofactor buried in hemoprotein active sites to an exchange labile and mobile metallonutrient.

PMID: 27254265 [PubMed - as supplied by publisher]

Metabolomic Analysis in Brain Research: Opportunities and Challenges.

Front Physiol. 2016;7:183

Authors: Vasilopoulou CG, Margarity M, Klapa MI

Abstract
Metabolism being a fundamental part of molecular physiology, elucidating the structure and regulation of metabolic pathways is crucial for obtaining a comprehensive perspective of cellular function and understanding the underlying mechanisms of its dysfunction(s). Therefore, quantifying an accurate metabolic network activity map under various physiological conditions is among the major objectives of systems biology in the context of many biological applications. Especially for CNS, metabolic network activity analysis can substantially enhance our knowledge about the complex structure of the mammalian brain and the mechanisms of neurological disorders, leading to the design of effective therapeutic treatments. Metabolomics has emerged as the high-throughput quantitative analysis of the concentration profile of small molecular weight metabolites, which act as reactants and products in metabolic reactions and as regulatory molecules of proteins participating in many biological processes. Thus, the metabolic profile provides a metabolic activity fingerprint, through the simultaneous analysis of tens to hundreds of molecules of pathophysiological and pharmacological interest. The application of metabolomics is at its standardization phase in general, and the challenges for paving a standardized procedure are even more pronounced in brain studies. In this review, we support the value of metabolomics in brain research. Moreover, we demonstrate the challenges of designing and setting up a reliable brain metabolomic study, which, among other parameters, has to take into consideration the sex differentiation and the complexity of brain physiology manifested in its regional variation. We finally propose ways to overcome these challenges and design a study that produces reproducible and consistent results.

PMID: 27252656 [PubMed]

Impact of Pathogen Population Heterogeneity and Stress-Resistant Variants on Food Safety.

Annu Rev Food Sci Technol. 2016;7:439-56

Authors: Abee T, Koomen J, Metselaar KI, Zwietering MH, den Besten HM

Abstract
This review elucidates the state-of-the-art knowledge about pathogen population heterogeneity and describes the genotypic and phenotypic analyses of persister subpopulations and stress-resistant variants. The molecular mechanisms underlying the generation of persister phenotypes and genetic variants are identified. Zooming in on Listeria monocytogenes, a comparative whole-genome sequence analysis of wild types and variants that enabled the identification of mutations in variants obtained after a single exposure to lethal food-relevant stresses is described. Genotypic and phenotypic features are compared to those for persistent strains isolated from food processing environments. Inactivation kinetics, models used for fitting, and the concept of kinetic modeling-based schemes for detection of variants are presented. Furthermore, robustness and fitness parameters of L. monocytogenes wild type and variants are used to model their performance in food chains. Finally, the impact of stress-resistant variants and persistence in food processing environments on food safety is discussed.

PMID: 26772414 [PubMed - indexed for MEDLINE]

Advancing metabolic engineering through systems biology of industrial microorganisms.

Curr Opin Biotechnol. 2015 Dec;36:8-15

Authors: Dai Z, Nielsen J

Abstract
Development of sustainable processes to produce bio-based compounds is necessary due to the severe environmental problems caused by the use of fossil resources. Metabolic engineering can facilitate the development of highly efficient cell factories to produce these compounds from renewable resources. The objective of systems biology is to gain a comprehensive and quantitative understanding of living cells and can hereby enhance our ability to characterize and predict cellular behavior. Systems biology of industrial microorganisms is therefore valuable for metabolic engineering. Here we review the application of systems biology tools for the identification of metabolic engineering targets which may lead to reduced development time for efficient cell factories. Finally, we present some perspectives of systems biology for advancing metabolic engineering further.

PMID: 26318074 [PubMed - indexed for MEDLINE]

A Systems Biology Perspective on the Molecular Mechanisms Underlying the Therapeutic Effects of Buyang Huanwu Decoction on Ischemic Stroke.

Rejuvenation Res. 2015 Aug;18(4):313-25

Authors: Guo Q, Zhong M, Xu H, Mao X, Zhang Y, Lin N

Abstract
Ischemic stroke is the leading cause of adult disability worldwide. The outcome is worse in older patients, especially in terms of disability. Buyang Huanwu decoction (BHD), a famous traditional Chinese medicine formula, has been used extensively in the treatment of ischemic stroke for centuries. However, its pharmacological mechanisms have not been fully elucidated. In this study, 82 putative targets for 411 composite compounds contained in BHD were predicted on the basis of our previously developed target prediction system. On the basis of large-scale molecular docking, more than 80% compound-putative target pairs had medium to strong binding efficiency. The pharmacological networks of BHD were built according to relationships among herbs, putative targets, and known therapeutic targets for ischemic stroke, and 121 major nodes were identified by calculating three topological features-degree, node betweenness, and closeness. Importantly, the pathway enrichment analysis identified several signaling pathways involved with major putative targets of BHD, such as the calcium signaling pathway, vascular smooth muscle contraction, and nucleotide-binding oligomerization domain (NOD)-like receptor signaling pathway, which have not hitherto been reported. These data are expected to help find new therapeutic effects of BHD and optimize clinical use of this formula. Collectively, our study developed a comprehensive systems approach integrating drug target prediction and network and functional analyses to reveal the relationships of the herbs in BHD with their putative targets, and for the first time with ischemic stroke-related pathway systems. This is a pilot study based on bioinformatics analysis; thus, further experimental studies are required to validate our findings.

PMID: 25687091 [PubMed - indexed for MEDLINE]

Autism cornered: network analyses reveal mechanisms of autism spectrum disorders.

Mol Syst Biol. 2014;10:778

Authors: Auffray C

Abstract
Despite a wealth of behavioral, cognitive,biological, and genetic studies, the causes of autism have remained largely unknown.In their recent work, Snyder and colleagues(Li et al, 2014) use a systems biology approach and shed light on the molecular and cellular mechanisms underlying autism, thus opening novel avenues forunderstanding the disease and developing potential treatments.

PMID: 25549969 [PubMed - indexed for MEDLINE]

11 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"Systems Biology"[Title/Abstract] AND ("2005/01/01"[PDAT] : "3000"[PDAT])

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11 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"Systems Biology"[Title/Abstract] AND ("2005/01/01"[PDAT] : "3000"[PDAT])

These pubmed results were generated on 2016/06/01

PubMed comprises more than 24 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

Role of frameshift ubiquitin B protein in Alzheimer's disease.

Wiley Interdiscip Rev Syst Biol Med. 2016 May 30;

Authors: Chen X, Petranovic D

Abstract
Alzheimer's disease (AD) is the most common neurodegenerative disease and is characterized by accumulation of misfolded and aggregated proteins. Since the ubiquitin-proteasome system (UPS) is the major intracellular protein quality control (PQC) system in eukaryotic cells, it is likely involved in the etiology of AD. The frameshift form of ubiquitin (Ubb(+1) ) accumulates in the neuritic plaques and neurofibrillary tangles in patients with AD. Ubb(+1) accumulates in an age-dependent manner as a result of RNA-polymerase mediated molecular misreading during transcription, which allows the formation of mutant proteins in the absence of gene mutations. The accumulation of the Ubb(+1) protein may act as an endogenous reporter for proteasome dysfunction and a growing number of studies have shown that Ubb(+1) may play more important pathogenic roles in AD etiology than previously hypothesized. The yeast Saccharomyces cerevisiae shares many conserved biological processes with all eukaryotic cells, including human neurons. This organism has been regarded as a model system for investigating the fundamental intracellular mechanisms, including those underlying neurodegeneration. We propose here that yeast systems biology approaches, combined with cell and molecular biology approaches will increase the relevant knowledge needed for advancement and elucidation of mechanisms and complex traits, which could provide new targets for therapeutic intervention in AD. For further resources related to this article, please visit the WIREs website.

PMID: 27240056 [PubMed - as supplied by publisher]

Clearing and Labeling Techniques for Large-Scale Biological Tissues.

Mol Cells. 2016 May 30;

Authors: Seo J, Choe M, Kim SY

Abstract
Clearing and labeling techniques for large-scale biological tissues enable simultaneous extraction of molecular and structural information with minimal disassembly of the sample, facilitating the integration of molecular, cellular and systems biology across different scales. Recent years have witnessed an explosive increase in the number of such methods and their applications, reflecting heightened interest in organ-wide clearing and labeling across many fields of biology and medicine. In this review, we provide an overview and comparison of existing clearing and labeling techniques and discuss challenges and opportunities in the investigations of large-scale biological systems.

PMID: 27239813 [PubMed - as supplied by publisher]

From big data to smart data in Alzheimer's disease. The brain health modeling initiative to foster actionable knowledge.

Alzheimers Dement. 2016 May 26;

Authors: Geerts H, Dacks PA, Devanarayan V, Haas M, Khatchaturian Z, Gordon MF, Maudsley S, Romero K, Stephenson D, Brain Health Modeling Initiative (BHMI)

Abstract
Massive investment and technological advances in the collection of extensive and longitudinal information on thousands of Alzheimer patients results in large amounts of data. These "big-data" databases can potentially advance CNS research and drug development. However, although necessary, they are not sufficient, and we posit that they must be matched with analytical methods that go beyond retrospective data-driven associations with various clinical phenotypes. Although these empirically derived associations can generate novel and useful hypotheses, they need to be organically integrated in a quantitative understanding of the pathology that can be actionable for drug discovery and development. We argue that mechanism-based modeling and simulation approaches, where existing domain knowledge is formally integrated using complexity science and quantitative systems pharmacology can be combined with data-driven analytics to generate predictive actionable knowledge for drug discovery programs, target validation, and optimization of clinical development.

PMID: 27238630 [PubMed - as supplied by publisher]

Comparison and Optimization of Methods for the Simultaneous Extraction of DNA, RNA, Proteins, and Metabolites.

Anal Biochem. 2016 May 26;

Authors: Vorreiter F, Richter S, Peter M, Baumann S, von Bergen M, Tomm JM

Abstract
The challenge of performing a time-resolved comprehensive analysis of molecular systems has led to the quest to optimize extraction methods. When the size of a biological sample is limited, there is demand for the simultaneous extraction of molecules representing the four areas of 'omics,' genomics, transcriptomics, proteomics, and metabolomics. Here,we optimized a protocol for the simultaneous extraction of RNA, proteins, and metabolites and a compared it to tow existing protocols.second for the concurrent recovery of DNA, RNA, and proteins and compared it to two existing protconducted a previouslty described method. Our optimisation comprised the addition of a methanol/chloroform metabolite purification before the separation of DNA/RNA and proteins. Extracted DNA, RNA, proteins, and metabolites were quantitatively and/or qualitatively analyzed. Of the three methods, only the newly developed protocol yielded all biomolecule classes of adequate quantity and quality.

PMID: 27237373 [PubMed - as supplied by publisher]

FGFR2 risk SNPs confer breast cancer risk by augmenting estrogen responsiveness.

Carcinogenesis. 2016 May 28;

Authors: Campbell TM, Castro MA, de Santiago I, Fletcher MN, Halim S, Prathalingam R, Ponder BA, Meyer KB

Abstract
The fibroblast growth factor receptor 2 (FGFR2) locus is consistently the top hit in genome-wide association studies (GWAS) for estrogen receptor-positive (ER(+)) breast cancer. Yet, its mode of action continues to be controversial. Here we employ a systems biology approach to demonstrate that signalling via FGFR2 counteracts cell activation by estrogen. In the presence of estrogen, the estrogen receptor (ESR1) regulon (set of ESR1 target genes) is in an active state. However, signalling by FGFR2 is able to reverse the activity of the ESR1 regulon. This effect is seen in multiple distinct FGFR2 signalling model systems, across multiple cells lines and is dependent on the presence of FGFR2. Increased estrogen exposure has long been associated with an increased risk of breast cancer. We therefore hypothesised that risk variants should reduce FGFR2 expression and subsequent signalling. Indeed, transient transfection experiments assaying the three independent variants of the FGFR2 risk locus (rs2981578, rs35054928 and rs45631563) in their normal chromosomal context show that these single nucleotide polymorphisms (SNPs) map to transcriptional silencer elements and that, compared to wild type, the risk alleles augment silencer activity. The presence of risk variants results in lower FGFR2 expression and increased estrogen responsiveness. We thus propose a molecular mechanism by which FGFR2 can confer increased breast cancer risk that is consistent with estrogen exposure as a major driver of breast cancer risk. Our findings may have implications for the clinical use of FGFR2 inhibitors.

PMID: 27236187 [PubMed - as supplied by publisher]

Thousands of novel translated open reading frames in humans inferred by ribosome footprint profiling.

Elife. 2016 May 27;5

Authors: Raj A, Wang SH, Shim H, Harpak A, Li YI, Engelmann B, Stephens M, Gilad Y, Pritchard JK

Abstract
Accurate annotation of protein coding regions is essential for understanding how genetic information is translated into function. We describe riboHMM, a new method that uses ribosome footprint data to accurately infer translated sequences. Applying riboHMM to human lymphoblastoid cell lines, we identified 7,273 novel coding sequences, including 2,442 translated upstream open reading frames. We observed an enrichment of footprints at inferred initiation sites after drug-induced arrest of translation initiation, validating many of the novel coding sequences. The novel proteins exhibit significant selective constraint in the inferred reading frames, suggesting that many are functional. Moreover, ~40% of bicistronic transcripts showed negative correlation in the translation levels of their two coding sequences, suggesting a potential regulatory role for these novel regions. Despite known limitations of mass spectrometry to detect protein expressed at low level, we estimated a 14% validation rate. Our work significantly expands the set of known coding regions in humans.

PMID: 27232982 [PubMed - as supplied by publisher]

Crowdsourcing the nodulation gene network discovery environment.

BMC Bioinformatics. 2016;17(1):223

Authors: Li Y, Jackson SA

Abstract
BACKGROUND: The Legumes (Fabaceae) are an economically and ecologically important group of plant species with the conspicuous capacity for symbiotic nitrogen fixation in root nodules, specialized plant organs containing symbiotic microbes. With the aim of understanding the underlying molecular mechanisms leading to nodulation, many efforts are underway to identify nodulation-related genes and determine how these genes interact with each other. In order to accurately and efficiently reconstruct nodulation gene network, a crowdsourcing platform, CrowdNodNet, was created.
RESULTS: The platform implements the jQuery and vis.js JavaScript libraries, so that users are able to interactively visualize and edit the gene network, and easily access the information about the network, e.g. gene lists, gene interactions and gene functional annotations. In addition, all the gene information is written on MediaWiki pages, enabling users to edit and contribute to the network curation.
CONCLUSIONS: Utilizing the continuously updated, collaboratively written, and community-reviewed Wikipedia model, the platform could, in a short time, become a comprehensive knowledge base of nodulation-related pathways. The platform could also be used for other biological processes, and thus has great potential for integrating and advancing our understanding of the functional genomics and systems biology of any process for any species. The platform is available at http://crowd.bioops.info/ , and the source code can be openly accessed at https://github.com/bioops/crowdnodnet under MIT License.

PMID: 27230384 [PubMed - in process]

Unraveling the environmental and genetic interactions in atherosclerosis: Central role of the gut microbiota.

Atherosclerosis. 2015 Aug;241(2):387-99

Authors: Org E, Mehrabian M, Lusis AJ

Abstract
Recent studies have convincingly linked gut microbiota to traits relevant to atherosclerosis, such as insulin resistance, dyslipidemia and inflammation, and have revealed novel disease pathways involving microbe-derived metabolites. These results have important implications for understanding how environmental and genetic factors act together to influence cardiovascular disease (CVD) risk. Thus, dietary constituents are not only absorbed and metabolized by the host but they also perturb the gut microbiota, which in turn influence host metabolism and inflammation. It also appears that host genetics helps to shape the gut microbiota community. Here, we discuss challenges in understanding these interactions and the role they play in CVD.

PMID: 26071662 [PubMed - indexed for MEDLINE]

Deciphering principles of morphogenesis from temporal and spatial patterns on the integument.

Dev Dyn. 2015 Aug;244(8):905-20

Authors: Li A, Lai YC, Figueroa S, Yang T, Widelitz RB, Kobielak K, Nie Q, Chuong CM

Abstract
BACKGROUND: How tissue patterns form in development and regeneration is a fundamental issue remaining to be fully understood. The integument often forms repetitive units in space (periodic patterning) and time (cyclic renewal), such as feathers and hairs. Integument patterns are visible and experimentally manipulatable, helping us reveal pattern formative processes. Variability is seen in regional phenotypic specificities and temporal cycling at different physiological stages.
RESULTS: Here we show some cellular/molecular bases revealed by analyzing integument patterns. (1) Localized cellular activity (proliferation, rearrangement, apoptosis, differentiation) transforms prototypic organ primordia into specific shapes. Combinatorial positioning of different localized activity zones generates diverse and complex organ forms. (2) Competitive equilibrium between activators and inhibitors regulates stem cells through cyclic quiescence and activation.
CONCLUSIONS: Dynamic interactions between stem cells and their adjacent niche regulate regenerative behavior, modulated by multi-layers of macro-environmental factors (dermis, body hormone status, and external environment). Genomics studies may reveal how positional information of localized cellular activity is stored. In vivo skin imaging and lineage tracing unveils new insights into stem cell plasticity. Principles of self-assembly obtained from the integumentary organ model can be applied to help restore damaged patterns during regenerative wound healing and for tissue engineering to rebuild tissues. Developmental Dynamics 244:905-920, 2015. © 2015 Wiley Periodicals, Inc.

PMID: 25858668 [PubMed - indexed for MEDLINE]

Principles of Systems Biology-No. 5.

Cell Syst. 2016 May 25;2(5):290-292

Authors:

Abstract
If systems biology is about understanding how links between components yield emergent phenomena, this month's Cell Systems Call (Cell Systems 1, 307) contains a veritable bounty of examples, showcasing the breadth of the field from systems oceanography to molecular evolution to the influence of cellular niche microenvironments on stem cell development.

PMID: 27228344 [PubMed - as supplied by publisher]

TissueMiner: a multiscale analysis toolkit to quantify how cellular processes create tissue dynamics.

Elife. 2016 May 26;5

Authors: Etournay R, Merkel M, Popovi M, Brandl H, Dye NA, Aigouy B, Salbreux G, Eaton S, Jülicher F

Abstract
Segmentation and tracking of cells in long-term time-lapse experiments has emerged as a powerful method to understand how tissue shape changes emerge from the complex choreography of constituent cells. However, methods to store and interrogate the large datasets produced by these experiments are not widely available. Furthermore, recently developed methods for relating tissue shape changes to cell dynamics have not yet been widely applied by biologists because of their technical complexity. We therefore developed a database format that stores cellular connectivity and geometry information of deforming epithelial tissues, and computational tools to interrogate it and perform multi-scale analysis of morphogenesis. We provide tutorials for this computational framework, called TissueMiner, and demonstrate its capabilities by comparing cell and tissue dynamics in vein and inter-vein subregions of the Drosophila pupal wing. These analyses reveal an unexpected role for convergent extension in shaping wing veins.

PMID: 27228153 [PubMed - as supplied by publisher]

Recent Progress on Systems and Synthetic Biology Approaches to Engineer Fungi As Microbial Cell Factories.

Curr Genomics. 2016 Apr;17(2):85-98

Authors: Amores GR, Guazzaroni ME, Arruda LM, Silva-Rocha R

Abstract
Filamentous fungi are remarkable organisms naturally specialized in deconstructing plant biomass and this feature has a tremendous potential for biofuel production from renewable sources. The past decades have been marked by a remarkable progress in the genetic engineering of fungi to generate industry-compatible strains needed for some biotech applications. In this sense, progress in this field has been marked by the utilization of high-throughput techniques to gain deep understanding of the molecular machinery controlling the physiology of these organisms, starting thus the Systems Biology era of fungi. Additionally, genetic engineering has been extensively applied to modify wellcharacterized promoters in order to construct new expression systems with enhanced performance under the conditions of interest. In this review, we discuss some aspects related to significant progress in the understating and engineering of fungi for biotechnological applications, with special focus on the construction of synthetic promoters and circuits in organisms relevant for industry. Different engineering approaches are shown, and their potential and limitations for the construction of complex synthetic circuits in these organisms are examined. Finally, we discuss the impact of engineered promoter architecture in the single-cell behavior of the system, an often-neglected relationship with a tremendous impact in the final performance of the process of interest. We expect to provide here some new directions to drive future research directed to the construction of high-performance, engineered fungal strains working as microbial cell factories.

PMID: 27226765 [PubMed]