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]

Complement membrane attack and tumourigenesis: a systems biology approach.

J Biol Chem. 2016 May 19;

Authors: Towner LD, Wheat RA, Hughes TR, Morgan BP

Abstract
Tumour development driven by inflammation is now an established phenomenon but the role that complement plays remains uncertain. Recent evidence has suggested that various components of the complement (C) cascade may influence tumour development in disparate ways; however, little attention has been paid to that of the membrane attack complex (MAC). This is despite abundant evidence documenting the effects of this complex on cell behaviour, including cell activation, protection from/induction of apoptosis, release of inflammatory cytokines, growth factors and ECM components and regulators and the triggering of the NLRP3 inflammasome. Here we present a novel approach to this issue by using global gene expression studies in conjunction with a systems biology analysis. Using network analysis of MAC responsive expression changes we demonstrated a cluster of co-regulated genes known to have their impact in the extracellular space and on the supporting stroma and with well-characterized tumour promoting roles. Network analysis highlighted the central role for EGFR activation in mediating the observed responses to MAC exposure. Overall, the study sheds light on the mechanisms by which sublytic MAC causes tumour cell responses and exposes a gene expression signature that implicates MAC as a driver of tumour progression. These findings have implications for understanding of the roles of C and the MAC in tumour development and progression which in turn will inform future therapeutic strategies in cancer.

PMID: 27226542 [PubMed - as supplied by publisher]

Redox regulation of vascular remodeling.

Cell Mol Life Sci. 2016 Jan;73(2):349-63

Authors: Karimi Galougahi K, Ashley EA, Ali ZA

Abstract
Vascular remodeling is a dynamic process of structural and functional changes in response to biochemical and biomechanical signals in a complex in vivo milieu. While inherently adaptive, dysregulation leads to maladaptive remodeling. Reactive oxygen species participate in homeostatic cell signaling in tightly regulated- and compartmentalized cellular circuits. It is well established that perturbations in oxidation-reduction (redox) homeostasis can lead to a state of oxidative-, and more recently, reductive stress. We provide an overview of the redox signaling in the vasculature and review the role of oxidative- and reductive stress in maladaptive vascular remodeling. Particular emphasis has been placed on essential processes that determine phenotype modulation, migration and fate of the main cell types in the vessel wall. Recent advances in systems biology and the translational opportunities they may provide to specifically target the redox pathways driving pathological vascular remodeling are discussed.

PMID: 26483132 [PubMed - indexed for MEDLINE]

Systems Metabolic Engineering of Escherichia coli.

EcoSal Plus. 2016 May;7(1)

Authors: Choi KR, Shin JH, Cho JS, Yang D, Lee SY

Abstract
Systems metabolic engineering, which recently emerged as metabolic engineering integrated with systems biology, synthetic biology, and evolutionary engineering, allows engineering of microorganisms on a systemic level for the production of valuable chemicals far beyond its native capabilities. Here, we review the strategies for systems metabolic engineering and particularly its applications in Escherichia coli. First, we cover the various tools developed for genetic manipulation in E. coli to increase the production titers of desired chemicals. Next, we detail the strategies for systems metabolic engineering in E. coli, covering the engineering of the native metabolism, the expansion of metabolism with synthetic pathways, and the process engineering aspects undertaken to achieve higher production titers of desired chemicals. Finally, we examine a couple of notable products as case studies produced in E. coli strains developed by systems metabolic engineering. The large portfolio of chemical products successfully produced by engineered E. coli listed here demonstrates the sheer capacity of what can be envisioned and achieved with respect to microbial production of chemicals. Systems metabolic engineering is no longer in its infancy; it is now widely employed and is also positioned to further embrace next-generation interdisciplinary principles and innovation for its upgrade. Systems metabolic engineering will play increasingly important roles in developing industrial strains including E. coli that are capable of efficiently producing natural and nonnatural chemicals and materials from renewable nonfood biomass.

PMID: 27223822 [PubMed - as supplied by publisher]

Cox process representation and inference for stochastic reaction-diffusion processes.

Nat Commun. 2016;7:11729

Authors: Schnoerr D, Grima R, Sanguinetti G

Abstract
Complex behaviour in many systems arises from the stochastic interactions of spatially distributed particles or agents. Stochastic reaction-diffusion processes are widely used to model such behaviour in disciplines ranging from biology to the social sciences, yet they are notoriously difficult to simulate and calibrate to observational data. Here we use ideas from statistical physics and machine learning to provide a solution to the inverse problem of learning a stochastic reaction-diffusion process from data. Our solution relies on a non-trivial connection between stochastic reaction-diffusion processes and spatio-temporal Cox processes, a well-studied class of models from computational statistics. This connection leads to an efficient and flexible algorithm for parameter inference and model selection. Our approach shows excellent accuracy on numeric and real data examples from systems biology and epidemiology. Our work provides both insights into spatio-temporal stochastic systems, and a practical solution to a long-standing problem in computational modelling.

PMID: 27222432 [PubMed - in process]

Data Mining for Identification of Molecular Targets in Ovarian Cancer.

Asian Pac J Cancer Prev. 2016;17(4):1691-9

Authors: Villegas-Ruiz V, Juarez-Mendez S

Abstract
Ovarian cancer is possibly the sixth most common malignancy worldwide, in Mexico representing the fourth leading cause of gynecological cancer death more than 70% being diagnosed at an advanced stage and the survival being very poor. Ovarian tumors are classified according to histological characteristics, epithelial ovarian cancer as the most common (~80%). We here used high-density microarrays and a systems biology approach to identify tissue-associated deregulated genes. Non-malignant ovarian tumors showed a gene expression profile associated with immune mediated inflammatory responses (28 genes), whereas malignant tumors had a gene expression profile related to cell cycle regulation (1,329 genes) and ovarian cell lines to cell cycling and metabolism (1,664 genes).

PMID: 27221839 [PubMed - in process]

Genomic Landscape of Colorectal Mucosa and Adenomas.

Cancer Prev Res (Phila). 2016 May 24;

Authors: Borras E, San Lucas FA, Chang K, Zhou R, Masand G, Fowler J, Mork ME, You YN, Taggart MW, McAllister F, Jones DA, Davies GE, Edelmann W, Ehli EA, Lynch PM, Hawk ET, Capella G, Scheet P, Vilar E

Abstract
The molecular basis of the adenoma-to-carcinoma transition has been deduced using comparative analysis of genetic alterations observed through the sequential steps of intestinal carcinogenesis. However, comprehensive genomic analyses of adenomas and at-risk mucosa are still lacking. Therefore, our aim was to characterize the genomic landscape of colonic at-risk mucosa and adenomas. We analyzed the mutation profile and copy number changes of 25 adenomas and adjacent mucosa from 12 familial adenomatous polyposis patients using whole-exome sequencing and validated allelic imbalances (AI) in 37 adenomas using SNP arrays. We assessed for evidence of clonality and performed estimations on the proportions of driver and passenger mutations using a systems biology approach. Adenomas had lower mutational rates than did colorectal cancers and showed recurrent alterations in known cancer driver genes (APC, KRAS, FBXW7, TCF7L2) and AIs in chromosomes 5, 7, and 13. Moreover, 80% of adenomas had somatic alterations in WNT pathway genes. Adenomas displayed evidence of multiclonality similar to stage I carcinomas. Strong correlations between mutational rate and patient age were observed in at-risk mucosa and adenomas. Our data indicate that at least 23% of somatic mutations are present in at-risk mucosa prior to adenoma initiation. The genomic profiles of at-risk mucosa and adenomas illustrate the evolution from normal tissue to carcinoma via greater resolution of molecular changes at the inflection point of premalignant lesions. Furthermore, substantial genomic variation exists in at-risk mucosa before adenoma formation, and deregulation of the WNT pathway is required to foster carcinogenesis. Cancer Prev Res; 9(6); 1-11. ©2016 AACR.

PMID: 27221540 [PubMed - as supplied by publisher]

[Deepening the idea of systems biology and promoting the development of pan-vascular medical science].

Zhonghua Xin Xue Guan Bing Za Zhi. 2016 May 24;44(5):373-4

Authors: Ge JB

PMID: 27220570 [PubMed - in process]

The bovine milk microbiota: insights and perspectives from -omics studies.

Mol Biosyst. 2016 May 24;

Authors: Addis MF, Tanca A, Uzzau S, Oikonomou G, Bicalho RC, Moroni P

Abstract
Recent significant progress in culture-independent techniques, together with the parallel development of -omics technologies and data analysis capabilities, have led to a new perception of the milk microbiota as a complex microbial community with great diversity and multifaceted biological roles, living in an environment that was until recently believed to be sterile. In this review, we summarize and discuss the latest findings on the milk microbiota in dairy cows, with a focus on the role it plays in bovine physiology and health. Following an introduction on microbial communities and the importance of their study, we present an overview of the -omics methods currently available for their characterization, and outline the potential offered by a systems biology approach encompassing metatranscriptomics, metaproteomics, and metametabolomics. Then, we review the recent discoveries on the dairy cow milk microbiome enabled by the application of -omics approaches. Learning from studies in humans and in the mouse model, and after a description of the endogenous route hypothesis, we discuss the role of the milk microbiota in the physiology and health of both the mother and the offspring, and report how it can be changed by farming practices and during infection. In conclusion, we shortly outline the impact of the milk microbiota on the quality of milk and of dairy products.

PMID: 27216801 [PubMed - as supplied by publisher]

Drug Design based on Protein Structure Network.

Mini Rev Med Chem. 2016 May 24;

Authors: Liang Z, Hu G

Abstract
Although structure-based drug design (SBDD) has become an indispensable tool in drug discovery for a long time, it continues to pose major challenges to date. With the advancement of "omics" techniques, systems biology has enriched SBDD into a new era, called polypharmacology, in which multi-targets drug or drug combination is designed to fight complex diseases. As a preliminary tool in systems biology, protein structure networks (PSNs) treat a protein as a set of residues linked by edges corresponding to the intramolecular interactions existing in folded structures between the residues. The PSN offers a computationally efficient tool to study the structure and function of proteins, and thus may facilitate structure-based drug design. Herein, we provide an overview of recent advances in PSNs, from predicting functionally important residues, to charactering protein-protein interactions and allosteric communication paths. Furthermore, we discuss potential pharmacological applications of PSN concepts and tools, and highlight the application to two families of drug targets, GPCRs and Hsp90. Although the application of PSNs as a framework for computer-aided drug discovery has been limited to date, we put forward the potential utility value in the near future and propose the PSNs could also serve as a new tool for polypharmacology research.

PMID: 27215941 [PubMed - as supplied by publisher]

[Big Biology : Supersizing Wissenschaft zu Beginn des 21. Jahrhunderts].

NTM. 2016 May 23;

Authors: Vermeulen N

PMID: 27215209 [PubMed - as supplied by publisher]

Systems biology in kidney transplantation: The application of multi-omics to a complex model.

Am J Transplant. 2016 May 23;

Authors: Bontha SV, Maluf DG, Mueller TF, Mas VR

Abstract
In spite of reduction of rejection rates and improvement in short term survival post kidney transplantation, modest progress has occurred in long-term graft attrition over the years. Timely identification of molecular events that precede clinical and histopathological changes might help in early intervention and thereby increase the graft half-life. Evolution of -omics tools has enabled systemic investigation of the influence of whole genome, epigenome, transcriptome, proteome, microbiome on transplant function and survival. In this 'omics' era, systemic approaches, in-depth clinical phenotyping and use of strict validation methods is the key for further understanding of the complex mechanisms associated with graft function. Systems biology is an inter-disciplinary holistic approach that focuses on complex and dynamic interactions within biological systems. The complexity of human kidney transplant is unlikely to be captured by a reductionist approach. It appears essential to integrate multi - omics data that can elucidate the multidimensional and multilayered regulation of the underlying heterogeneous and complex kidney transplant model. Here, we discuss studies which focus on genetic biomarkers, emerging technologies and systems biology approaches, which should increase the ability to discover biomarkers, understand mechanisms and stratify patients and responses post kidney transplantation. This article is protected by copyright. All rights reserved.

PMID: 27214826 [PubMed - as supplied by publisher]