Genomic cloud computing: legal and ethical points to consider.

Eur J Hum Genet. 2015 Oct;23(10):1271-8

Authors: Dove ES, Joly Y, Tassé AM, Public Population Project in Genomics and Society (P3G) International Steering Committee, International Cancer Genome Consortium (ICGC) Ethics and Policy Committee, Knoppers BM

Abstract
The biggest challenge in twenty-first century data-intensive genomic science, is developing vast computer infrastructure and advanced software tools to perform comprehensive analyses of genomic data sets for biomedical research and clinical practice. Researchers are increasingly turning to cloud computing both as a solution to integrate data from genomics, systems biology and biomedical data mining and as an approach to analyze data to solve biomedical problems. Although cloud computing provides several benefits such as lower costs and greater efficiency, it also raises legal and ethical issues. In this article, we discuss three key 'points to consider' (data control; data security, confidentiality and transfer; and accountability) based on a preliminary review of several publicly available cloud service providers' Terms of Service. These 'points to consider' should be borne in mind by genomic research organizations when negotiating legal arrangements to store genomic data on a large commercial cloud service provider's servers. Diligent genomic cloud computing means leveraging security standards and evaluation processes as a means to protect data and entails many of the same good practices that researchers should always consider in securing their local infrastructure.

PMID: 25248396 [PubMed - indexed for MEDLINE]

Genetic and metabolic engineering of microorganisms for the development of new flavor compounds from terpenic substrates.

Crit Rev Biotechnol. 2015;35(3):313-25

Authors: Bution ML, Molina G, Abrahão MR, Pastore GM

Abstract
Throughout human history, natural products have been the basis for the discovery and development of therapeutics, cosmetic and food compounds used in industry. Many compounds found in natural organisms are rather difficult to chemically synthesize and to extract in large amounts, and in this respect, genetic and metabolic engineering are playing an increasingly important role in the production of these compounds, such as new terpenes and terpenoids, which may potentially be used to create aromas in industry. Terpenes belong to the largest class of natural compounds, are produced by all living organisms and play a fundamental role in human nutrition, cosmetics and medicine. Recent advances in systems biology and synthetic biology are allowing us to perform metabolic engineering at the whole-cell level, thus enabling the optimal design of microorganisms for the efficient production of drugs, cosmetic and food additives. This review describes the recent advances made in the genetic and metabolic engineering of the terpenes pathway with a particular focus on systems biotechnology.

PMID: 24494701 [PubMed - indexed for MEDLINE]

Resolving the etiology of atopic disorders by using genetic analysis of racial ancestry.

J Allergy Clin Immunol. 2016 Jun 10;

Authors: Gupta J, Johansson E, Bernstein JA, Chakraborty R, Khurana Hershey GK, Rothenberg ME, Mersha TB

Abstract
Atopic dermatitis (AD), food allergy, allergic rhinitis, and asthma are common atopic disorders of complex etiology. The frequently observed atopic march from early AD to asthma, allergic rhinitis, or both later in life and the extensive comorbidity of atopic disorders suggest common causal mechanisms in addition to distinct ones. Indeed, both disease-specific and shared genomic regions exist for atopic disorders. Their prevalence also varies among races; for example, AD and asthma have a higher prevalence in African Americans when compared with European Americans. Whether this disparity stems from true genetic or race-specific environmental risk factors or both is unknown. Thus far, the majority of the genetic studies on atopic diseases have used populations of European ancestry, limiting their generalizability. Large-cohort initiatives and new analytic methods, such as admixture mapping, are currently being used to address this knowledge gap. Here we discuss the unique and shared genetic risk factors for atopic disorders in the context of ancestry variations and the promise of high-throughput "-omics"-based systems biology approach in providing greater insight to deconstruct their genetic and nongenetic etiologies. Future research will also focus on deep phenotyping and genotyping of diverse racial ancestry, gene-environment, and gene-gene interactions.

PMID: 27297995 [PubMed - as supplied by publisher]

Can stable isotope mass spectrometry replace ‎radiolabelled approaches in metabolic studies?

Plant Sci. 2016 Aug;249:59-69

Authors: Batista Silva W, Daloso DM, Fernie AR, Nunes-Nesi A, Araújo WL

Abstract
Metabolic pathways and the key regulatory points thereof can be deduced using isotopically labelled substrates. One prerequisite is the accurate measurement of the labeling pattern of targeted metabolites. The subsequent estimation of metabolic fluxes following incubation in radiolabelled substrates has been extensively used. Radiolabelling is a sensitive approach and allows determination of total label uptake since the total radiolabel content is easy to detect. However, the incubation of cells, tissues or the whole plant in a stable isotope enriched environment and the use of either mass spectrometry or nuclear magnetic resonance techniques to determine label incorporation within specific metabolites offers the possibility to readily obtain metabolic information with higher resolution. It additionally also offers an important complement to other post-genomic strategies such as metabolite profiling providing insights into the regulation of the metabolic network and thus allowing a more thorough description of plant cellular function. Thus, although safety concerns mean that stable isotope feeding is generally preferred, the techniques are in truth highly complementary and application of both approaches in tandem currently probably provides the best route towards a comprehensive understanding of plant cellular metabolism.

PMID: 27297990 [PubMed - in process]

Next generation sequencing technology and genomewide data analysis: Perspectives for retinal research.

Prog Retin Eye Res. 2016 Jun 10;

Authors: Chaitankar V, Karakülah G, Ratnapriya R, Giuste FO, Brooks MJ, Swaroop A

Abstract
The advent of high throughput next generation sequencing (NGS) has accelerated the pace of discovery of disease-associated genetic variants and genomewide profiling of expressed sequences and epigenetic marks, thereby permitting systems-based analyses of ocular development and disease. Rapid evolution of NGS and associated methodologies presents significant challenges in acquisition, management, and analysis of large data sets and for extracting biologically or clinically relevant information. Here we illustrate the basic design of commonly used NGS-based methods, specifically whole exome sequencing, transcriptome, and epigenome profiling, and provide recommendations for data analyses. We briefly discuss systems biology approaches for integrating multiple data sets to elucidate gene regulatory or disease networks. While we provide examples from the retina, the NGS guidelines reviewed here are applicable to other tissues/cell types as well.

PMID: 27297499 [PubMed - as supplied by publisher]

Differential integrative omic analysis for mechanism insights and biomarker discovery of abnormal Savda syndrome and its unique Munziq prescription.

Sci Rep. 2016;6:27831

Authors: Guo X, Bakri I, Abudula A, Arken K, Mijit M, Mamtimin B, Upur H

Abstract
Research has shown that many cancers have acommon pathophysiological origin and often present with similar symptoms. In terms of Traditional Uighur Medicine (TUM) Hilit (body fluid) theory, abnormal Savda syndrome (ASS) formed by abnormal Hilit is the common phenotype of complex diseases and in particular tumours. Abnormal Savda Munziq (ASMq), one representative of TUM, has been effective in the treatment of cancer since ancient times. Despite the physiopathology of ASS, the relationship between causative factors and the molecular mechanism of ASMq are not fully understood. The current study expanded upon earlier work by integrating traditional diagnostic approaches with others utilizing systems biology technology for the analysis of proteomic (iTRAQ) and metabolomic ((1)H-NMR) profiles of Uighur Medicine target organ lesion (liver) tumours. The candidate proteins were analyzed by enrichment analysis of the biological process and biomarker filters. Subsequently, 3Omics web-based tools were used to determine the relationships between proteins and appropriate metabolites. ELISA assay and IHC methods were used to verify the proteomic result; the protein von Willebrand factor (vWF) may be the "therapeutic window" of ASMq and biomarkers of ASS. This study is likely to be of great significance for the standardization and modernization of TUM.

PMID: 27296761 [PubMed - in process]

Individualized network-based drug repositioning infrastructure for precision oncology in the panomics era.

Brief Bioinform. 2016 Jun 12;

Authors: Cheng F, Hong H, Yang S, Wei Y

Abstract
Advances in next-generation sequencing technologies have generated the data supporting a large volume of somatic alterations in several national and international cancer genome projects, such as The Cancer Genome Atlas and the International Cancer Genome Consortium. These cancer genomics data have facilitated the revolution of a novel oncology drug discovery paradigm from candidate target or gene studies toward targeting clinically relevant driver mutations or molecular features for precision cancer therapy. This focuses on identifying the most appropriately targeted therapy to an individual patient harboring a particularly genetic profile or molecular feature. However, traditional experimental approaches that are used to develop new chemical entities for targeting the clinically relevant driver mutations are costly and high-risk. Drug repositioning, also known as drug repurposing, re-tasking or re-profiling, has been demonstrated as a promising strategy for drug discovery and development. Recently, computational techniques and methods have been proposed for oncology drug repositioning and identifying pharmacogenomics biomarkers, but overall progress remains to be seen. In this review, we focus on introducing new developments and advances of the individualized network-based drug repositioning approaches by targeting the clinically relevant driver events or molecular features derived from cancer panomics data for the development of precision oncology drug therapies (e.g. one-person trials) to fully realize the promise of precision medicine. We discuss several potential challenges (e.g. tumor heterogeneity and cancer subclones) for precision oncology. Finally, we highlight several new directions for the precision oncology drug discovery via biotherapies (e.g. gene therapy and immunotherapy) that target the 'undruggable' cancer genome in the functional genomics era.

PMID: 27296652 [PubMed - as supplied by publisher]

A Systems Biology Approach to Reveal Putative Host-Derived Biomarkers of Periodontitis by Network Topology Characterization of MMP-REDOX/NO and Apoptosis Integrated Pathways.

Front Cell Infect Microbiol. 2015;5:102

Authors: Zeidán-Chuliá F, Gürsoy M, Neves de Oliveira BH, Özdemir V, Könönen E, Gürsoy UK

Abstract
Periodontitis, a formidable global health burden, is a common chronic disease that destroys tooth-supporting tissues. Biomarkers of the early phase of this progressive disease are of utmost importance for global health. In this context, saliva represents a non-invasive biosample. By using systems biology tools, we aimed to (1) identify an integrated interactome between matrix metalloproteinase (MMP)-REDOX/nitric oxide (NO) and apoptosis upstream pathways of periodontal inflammation, and (2) characterize the attendant topological network properties to uncover putative biomarkers to be tested in saliva from patients with periodontitis. Hence, we first generated a protein-protein network model of interactions ("BIOMARK" interactome) by using the STRING 10 database, a search tool for the retrieval of interacting genes/proteins, with "Experiments" and "Databases" as input options and a confidence score of 0.400. Second, we determined the centrality values (closeness, stress, degree or connectivity, and betweenness) for the "BIOMARK" members by using the Cytoscape software. We found Ubiquitin C (UBC), Jun proto-oncogene (JUN), and matrix metalloproteinase-14 (MMP14) as the most central hub- and non-hub-bottlenecks among the 211 genes/proteins of the whole interactome. We conclude that UBC, JUN, and MMP14 are likely an optimal candidate group of host-derived biomarkers, in combination with oral pathogenic bacteria-derived proteins, for detecting periodontitis at its early phase by using salivary samples from patients. These findings therefore have broader relevance for systems medicine in global health as well.

PMID: 26793622 [PubMed - indexed for MEDLINE]

Changes in lipid metabolism and β-adrenergic response of adipose tissues of periparturient dairy cows affected by an energy-dense diet and nicotinic acid supplementation.

J Anim Sci. 2015 Aug;93(8):4012-22

Authors: Kenéz Á, Tienken R, Locher L, Meyer U, Rizk A, Rehage J, Dänicke S, Huber K

Abstract
Dairy cattle will mobilize large amounts of body fat during early lactation as an effect of decreased lipogenesis and increased lipolysis. Regulation of lipid metabolism involves fatty acid synthesis from acetate and β-adrenergic-stimulated phosphorylation of hormone-sensitive lipase (HSL) and perilipin in adipocytes. Although basic mechanisms of mobilizing fat storage in transition cows are understood, we lack a sufficiently detailed understanding to declare the exact regulatory network of these in a broad range of dairy cattle. The objective of the present study was to quantify 1) protein abundance of fatty acid synthase (FAS), 2) extent of phosphorylation of HSL and perilipin in vivo, and 3) β-adrenergic stimulated lipolytic response of adipose tissues in vitro at different stages of the periparturient period. We fed 20 German Holstein cows an energy-dense or an energetically adequate diet prepartum and 0 or 24 g/d nicotinic acid (NA) supplementation. Biopsy samples of subcutaneous and retroperitoneal adipose tissue were obtained at d 42 prepartum (d -42) and at d 1, 21, and 100 postpartum (d +1, d +21, d +100, respectively). To assess β-adrenergic response, tissue samples were incubated with 1 μ isoproterenol for 90 min at 37°C. The NEFA and glycerol release, as well as HSL and perilipin phosphorylation, was measured as indicators of in vitro stimulated lipolysis. In addition, protein expression of FAS and extent of HSL and perilipin phosphorylation were measured in fresh, nonincubated samples. There was no effect of dietary energy density or NA on the observed variables. The extent of HSL and perilipin phosphorylation under isoproterenol stimulation was strongly correlated with the release of NEFA and glycerol, consistent with the functional link between β-adrenergic-stimulated protein phosphorylation and lipolysis. In the nonincubated samples, FAS protein expression was decreased at d +1 and d +21, whereas HSL and perilipin phosphorylation increased from d -42 to d +1 and remained at an increased level throughout the first 100 d of lactation. In vitro lipolytic response was significant in prepartum samples at times when in vivo lipolysis was only minimally activated by phosphorylation. These data extend our understanding of the complex nature of control of lipolysis and lipogenesis in dairy cows and could be useful to the ongoing development of systems biology models of metabolism to help improve our quantitative knowledge of the cow.

PMID: 26440181 [PubMed - indexed for MEDLINE]

Systematic Mapping of Kinase Addiction Combinations in Breast Cancer Cells by Integrating Drug Sensitivity and Selectivity Profiles.

Chem Biol. 2015 Aug 20;22(8):1144-55

Authors: Szwajda A, Gautam P, Karhinen L, Jha SK, Saarela J, Shakyawar S, Turunen L, Yadav B, Tang J, Wennerberg K, Aittokallio T

Abstract
Chemical perturbation screens offer the possibility to identify actionable sets of cancer-specific vulnerabilities. However, most inhibitors of kinases or other cancer targets result in polypharmacological effects, which complicate the identification of target dependencies directly from the drug-response phenotypes. In this study, we developed a chemical systems biology approach that integrates comprehensive drug sensitivity and selectivity profiling to provide functional insights into both single and multi-target oncogenic signal addictions. When applied to 21 breast cancer cell lines, perturbed with 40 kinase inhibitors, the subtype-specific addiction patterns clustered in agreement with patient-derived subtypes, while showing considerable variability between the heterogeneous breast cancers. Experimental validation of the top predictions revealed a number of co-dependencies between kinase targets that led to unexpected synergistic combinations between their inhibitors, such as dasatinib and axitinib in the triple-negative basal-like HCC1937 cell line.

PMID: 26211361 [PubMed - indexed for MEDLINE]

Design of Probabilistic Boolean Networks Based on Network Structure and Steady-State Probabilities.

IEEE Trans Neural Netw Learn Syst. 2016 Jun 6;

Authors: Kobayashi K, Hiraishi K

Abstract
In this brief, we consider the problem of finding a probabilistic Boolean network (PBN) based on a network structure and desired steady-state properties. In systems biology and synthetic biology, such problems are important as an inverse problem. Using a matrix-based representation of PBNs, a solution method for this problem is proposed. The problem of finding a BN has been studied so far. In the problem of finding a PBN, we must calculate not only the Boolean functions, but also the probabilities of selecting a Boolean function and the number of candidates of the Boolean functions. Hence, the problem of finding a PBN is more difficult than that of finding a BN. The effectiveness of the proposed method is presented by numerical examples.

PMID: 27295690 [PubMed - as supplied by publisher]

How modeling standards, software, and initiatives support reproducibility in systems biology and systems medicine.

IEEE Trans Biomed Eng. 2016 Jun 2;

Authors: Waltemath D, Wolkenhauer O

Abstract
Only reproducible results are of significance to science. A lack of suitable standards and appropriate support of standards in software tools has led to numerous publications with irreproducible results. Our objectives are to identify the key challenges of reproducible research and to highlight existing solutions.
RESULTS: In this paper, we summarise problems concerning reproducibility in systems biology and systems medicine. We focus on initiatives, standards and software tools that aim to improve the reproducibility of simulation studies.
CONCLUSIONS: The long-term success of systems biology and systems medicine depends on trustworthy models and simulations. This requires openness to ensure reusability and transparency to enable reproducibility of results in these fields.

PMID: 27295645 [PubMed - as supplied by publisher]

Metabolomics as a Challenging Approach for Medicinal Chemistry and Personalized Medicine.

J Med Chem. 2016 Jun 13;

Authors: Frederich M, Pirotte B, Fillet M, De Tullio P

Abstract
"Omics" sciences have been developed to provide a holistic point of view of biology and to better understand the complexity of an organism as a whole. These systems biology approaches can be examined at different levels, starting from the most fundamental, i.e., the genome, and finishing with the most functional, i.e., the metabolome. Similar to how genomics is applied to the exploration of DNA, metabolomics is the qualitative and quantitative study of metabolites. This emerging field is clearly linked to genomics, transcriptomics and proteomics. In addition, metabolomics provides a unique and direct vision of the functional outcome of an organism's activities that are required for it to survive, grow and respond to internal and external stimuli or stress, e.g., pathologies and drugs. The links between metabolic changes, patient phenotype, physiological and/or pathological status and treatment are now well established and have opened a new area for the application of metabolomics in the drug discovery process and in personalized medicine.

PMID: 27295417 [PubMed - as supplied by publisher]

Unbiased Rare Event Sampling in Spatial Stochastic Systems Biology Models Using a Weighted Ensemble of Trajectories.

PLoS Comput Biol. 2016 Feb;12(2):e1004611

Authors: Donovan RM, Tapia JJ, Sullivan DP, Faeder JR, Murphy RF, Dittrich M, Zuckerman DM

Abstract
The long-term goal of connecting scales in biological simulation can be facilitated by scale-agnostic methods. We demonstrate that the weighted ensemble (WE) strategy, initially developed for molecular simulations, applies effectively to spatially resolved cell-scale simulations. The WE approach runs an ensemble of parallel trajectories with assigned weights and uses a statistical resampling strategy of replicating and pruning trajectories to focus computational effort on difficult-to-sample regions. The method can also generate unbiased estimates of non-equilibrium and equilibrium observables, sometimes with significantly less aggregate computing time than would be possible using standard parallelization. Here, we use WE to orchestrate particle-based kinetic Monte Carlo simulations, which include spatial geometry (e.g., of organelles, plasma membrane) and biochemical interactions among mobile molecular species. We study a series of models exhibiting spatial, temporal and biochemical complexity and show that although WE has important limitations, it can achieve performance significantly exceeding standard parallel simulation--by orders of magnitude for some observables.

PMID: 26845334 [PubMed - indexed for MEDLINE]

Quantitative Selection Analysis of Bacteriophage φCbK Susceptibility in Caulobacter crescentus.

J Mol Biol. 2016 Jan 29;428(2 Pt B):419-30

Authors: Christen M, Beusch C, Bösch Y, Cerletti D, Flores-Tinoco CE, Del Medico L, Tschan F, Christen B

Abstract
Classical molecular genetics uses stringent selective conditions to identify mutants with distinct phenotypic responses. Mutations giving rise to less pronounced phenotypes are often missed. However, to gain systems-level insights into complex genetic interaction networks requires genome-wide assignment of quantitative phenotypic traits. In this paper, we present a quantitative selection approach coupled with transposon sequencing (QS-TnSeq) to globally identify the cellular components that orchestrate susceptibility of the cell cycle model bacterium Caulobacter crescentus toward bacteriophage φCbK infection. We found that 135 genes representing 3.30% of the Caulobacter genome exhibit significant accumulation of transposon insertions upon φCbK selection. More than 85% thereof consist of new factors not previously associated with phage φCbK susceptibility. Using hierarchical clustering of dose-dependent TnSeq datasets, we grouped these genes into functional modules that correlate with different stages of the φCbK infection process. We assign φCbK susceptibility to eight new genes that represent novel components of the pilus secretion machinery. Further, we demonstrate that, from 86 motility genes, only seven genes encoding structural and regulatory components of the flagellar hook increase phage resistance when disrupted by transposons, suggesting a link between flagellar hook assembly and pili biogenesis. In addition, we observe high recovery of Tn5 insertions within regulatory sequences of the genes encoding the essential NADH:ubiquinone oxidoreductase complex indicating that intact proton motive force is crucial for effective phage propagation. In sum, QS-TnSeq is broadly applicable to perform quantitative and genome-wide systems-genetics analysis of complex phenotypic traits.

PMID: 26593064 [PubMed - indexed for MEDLINE]

PGSB PlantsDB: updates to the database framework for comparative plant genome research.

Nucleic Acids Res. 2016 Jan 4;44(D1):D1141-7

Authors: Spannagl M, Nussbaumer T, Bader KC, Martis MM, Seidel M, Kugler KG, Gundlach H, Mayer KF

Abstract
PGSB (Plant Genome and Systems Biology: formerly MIPS) PlantsDB (http://pgsb.helmholtz-muenchen.de/plant/index.jsp) is a database framework for the comparative analysis and visualization of plant genome data. The resource has been updated with new data sets and types as well as specialized tools and interfaces to address user demands for intuitive access to complex plant genome data. In its latest incarnation, we have re-worked both the layout and navigation structure and implemented new keyword search options and a new BLAST sequence search functionality. Actively involved in corresponding sequencing consortia, PlantsDB has dedicated special efforts to the integration and visualization of complex triticeae genome data, especially for barley, wheat and rye. We enhanced CrowsNest, a tool to visualize syntenic relationships between genomes, with data from the wheat sub-genome progenitor Aegilops tauschii and added functionality to the PGSB RNASeqExpressionBrowser. GenomeZipper results were integrated for the genomes of barley, rye, wheat and perennial ryegrass and interactive access is granted through PlantsDB interfaces. Data exchange and cross-linking between PlantsDB and other plant genome databases is stimulated by the transPLANT project (http://transplantdb.eu/).

PMID: 26527721 [PubMed - indexed for MEDLINE]

High-throughput, big data and complexity in clinical proteomics: an interview with Jasminka Godovac-Zimmermann.

Expert Rev Mol Diagn. 2015;15(10):1241-4

Authors: Godovac-Zimmermann J, Raison C

Abstract
Interview with Professor Jasminka Godovac-Zimmermann, PhD by Claire Raison (Commissioning Editor) Professor Jasminka Godovac-Zimmermann is Head of the Proteomics and Molecular Cell Dynamics Group at University College London, UK. Professor Godovac-Zimmermann trained at the Max Planck Institute of Biochemistry, Germany, and specialized in protein chemistry. Her research focuses on proteomics in cancer and systems biology. Here she talks about the clinical impact of her work and her hopes and predictions for how proteomics and diagnostics could work together in future.

PMID: 26367346 [PubMed - indexed for MEDLINE]

Plant sulfur nutrition: From Sachs to Big Data.

Plant Signal Behav. 2015;10(9):e1055436

Authors: Kopriva S

Abstract
Together with water and carbon dioxide plants require 14 essential mineral nutrients to finish their life cycle. The research in plant nutrition can be traced back to Julius Sachs, who was the first to experimentally prove the essentiality of mineral nutrients for plants. Among those elements Sachs showed to be essential is sulfur. Plant sulfur nutrition has been not as extensively studied as the nutrition of nitrogen and phosphate, probably because sulfur was not limiting for agriculture. However, with the reduction of atmospheric sulfur dioxide emissions sulfur deficiency has become common. The research in sulfur nutrition has changed over the years from using yeast and algae as experimental material to adopting Arabidopsis as the plant model as well as from simple biochemical measurements of individual parameters to system biology. Here the evolution of sulfur research from the times of Sachs to the current Big Data is outlined.

PMID: 26305261 [PubMed - indexed for MEDLINE]

Recent strategies and progress in identifying host factors involved in virus replication.

Curr Opin Microbiol. 2015 Aug;26:79-88

Authors: König R, Stertz S

Abstract
Viruses are completely dependent on their host cells for the successful production of progeny viruses. At each stage of the viral life cycle an intricate interplay between virus and host takes place with the virus aiming to usurp the host cell for its purposes and the host cell trying to block the intruder from propagation. In recent years these interactions have been studied on a global level by systems biology approaches, such as RNA interference screens, transcriptomic or proteomic methodologies, and exciting new insights into the pathogen-host relationship have been revealed. In this review, we summarize the available data, give examples for important findings from such studies and point out current limitations and potential future directions.

PMID: 26112615 [PubMed - indexed for MEDLINE]

Synechocystis sp. PCC6803 metabolic models for the enhanced production of hydrogen.

Crit Rev Biotechnol. 2015 Jun;35(2):184-98

Authors: Montagud A, Gamermann D, Fernández de Córdoba P, Urchueguía JF

Abstract
In the present economy, difficulties to access energy sources are real drawbacks to maintain our current lifestyle. In fact, increasing interests have been gathered around efficient strategies to use energy sources that do not generate high CO2 titers. Thus, science-funding agencies have invested more resources into research on hydrogen among other biofuels as interesting energy vectors. This article reviews present energy challenges and frames it into the present fuel usage landscape. Different strategies for hydrogen production are explained and evaluated. Focus is on biological hydrogen production; fermentation and photon-fuelled hydrogen production are compared. Mathematical models in biology can be used to assess, explore and design production strategies for industrially relevant metabolites, such as biofuels. We assess the diverse construction and uses of genome-scale metabolic models of cyanobacterium Synechocystis sp. PCC6803 to efficiently obtain biofuels. This organism has been studied as a potential photon-fuelled production platform for its ability to grow from carbon dioxide, water and photons, on simple culture media. Finally, we review studies that propose production strategies to weigh this organism's viability as a biofuel production platform. Overall, the work presented in this review unveils the industrial capabilities of cyanobacterium Synechocystis sp. PCC6803 to evolve interesting metabolites as a clean biofuel production platform.

PMID: 24090244 [PubMed - indexed for MEDLINE]