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]

DrugQuest - a text mining workflow for drug association discovery.

BMC Bioinformatics. 2016;17(Suppl 5):182

Authors: Papanikolaou N, Pavlopoulos GA, Theodosiou T, Vizirianakis IS, Iliopoulos I

Abstract
BACKGROUND: Text mining and data integration methods are gaining ground in the field of health sciences due to the exponential growth of bio-medical literature and information stored in biological databases. While such methods mostly try to extract bioentity associations from PubMed, very few of them are dedicated in mining other types of repositories such as chemical databases.
RESULTS: Herein, we apply a text mining approach on the DrugBank database in order to explore drug associations based on the DrugBank "Description", "Indication", "Pharmacodynamics" and "Mechanism of Action" text fields. We apply Name Entity Recognition (NER) techniques on these fields to identify chemicals, proteins, genes, pathways, diseases, and we utilize the TextQuest algorithm to find additional biologically significant words. Using a plethora of similarity and partitional clustering techniques, we group the DrugBank records based on their common terms and investigate possible scenarios why these records are clustered together. Different views such as clustered chemicals based on their textual information, tag clouds consisting of Significant Terms along with the terms that were used for clustering are delivered to the user through a user-friendly web interface.
CONCLUSIONS: DrugQuest is a text mining tool for knowledge discovery: it is designed to cluster DrugBank records based on text attributes in order to find new associations between drugs. The service is freely available at http://bioinformatics.med.uoc.gr/drugquest .

PMID: 27295093 [PubMed - as supplied by publisher]

TEES 2.2: Biomedical Event Extraction for Diverse Corpora.

BMC Bioinformatics. 2015;16 Suppl 16:S4

Authors: Björne J, Salakoski T

Abstract
BACKGROUND: The Turku Event Extraction System (TEES) is a text mining program developed for the extraction of events, complex biomedical relationships, from scientific literature. Based on a graph-generation approach, the system detects events with the use of a rich feature set built via dependency parsing. The TEES system has achieved record performance in several of the shared tasks of its domain, and continues to be used in a variety of biomedical text mining tasks.
RESULTS: The TEES system was quickly adapted to the BioNLP'13 Shared Task in order to provide a public baseline for derived systems. An automated approach was developed for learning the underlying annotation rules of event type, allowing immediate adaptation to the various subtasks, and leading to a first place in four out of eight tasks. The system for the automated learning of annotation rules is further enhanced in this paper to the point of requiring no manual adaptation to any of the BioNLP'13 tasks. Further, the scikit-learn machine learning library is integrated into the system, bringing a wide variety of machine learning methods usable with TEES in addition to the default SVM. A scikit-learn ensemble method is also used to analyze the importances of the features in the TEES feature sets.
CONCLUSIONS: The TEES system was introduced for the BioNLP'09 Shared Task and has since then demonstrated good performance in several other shared tasks. By applying the current TEES 2.2 system to multiple corpora from these past shared tasks an overarching analysis of the most promising methods and possible pitfalls in the evolving field of biomedical event extraction are presented.

PMID: 26551925 [PubMed - indexed for MEDLINE]

Application of the EVEX resource to event extraction and network construction: Shared Task entry and result analysis.

BMC Bioinformatics. 2015;16 Suppl 16:S3

Authors: Hakala K, Van Landeghem S, Salakoski T, Van de Peer Y, Ginter F

Abstract
BACKGROUND: Modern methods for mining biomolecular interactions from literature typically make predictions based solely on the immediate textual context, in effect a single sentence. No prior work has been published on extending this context to the information automatically gathered from the whole biomedical literature. Thus, our motivation for this study is to explore whether mutually supporting evidence, aggregated across several documents can be utilized to improve the performance of the state-of-the-art event extraction systems.
RESULTS: In the GE task, our re-ranking approach led to a modest performance increase and resulted in the first rank of the official Shared Task results with 50.97% F-score. Additionally, in this paper we explore and evaluate the usage of distributed vector representations for this challenge.
CONCLUSIONS: For the GRN task, we were able to produce a gene regulatory network from the EVEX data, warranting the use of such generic large-scale text mining data in network biology settings. A detailed performance and error analysis provides more insight into the relatively low recall rates.

PMID: 26551766 [PubMed - indexed for MEDLINE]

SynLethDB: synthetic lethality database toward discovery of selective and sensitive anticancer drug targets.

Nucleic Acids Res. 2016 Jan 4;44(D1):D1011-7

Authors: Guo J, Liu H, Zheng J

Abstract
Synthetic lethality (SL) is a type of genetic interaction between two genes such that simultaneous perturbations of the two genes result in cell death or a dramatic decrease of cell viability, while a perturbation of either gene alone is not lethal. SL reflects the biologically endogenous difference between cancer cells and normal cells, and thus the inhibition of SL partners of genes with cancer-specific mutations could selectively kill cancer cells but spare normal cells. Therefore, SL is emerging as a promising anticancer strategy that could potentially overcome the drawbacks of traditional chemotherapies by reducing severe side effects. Researchers have developed experimental technologies and computational prediction methods to identify SL gene pairs on human and a few model species. However, there has not been a comprehensive database dedicated to collecting SL pairs and related knowledge. In this paper, we propose a comprehensive database, SynLethDB (http://histone.sce.ntu.edu.sg/SynLethDB/), which contains SL pairs collected from biochemical assays, other related databases, computational predictions and text mining results on human and four model species, i.e. mouse, fruit fly, worm and yeast. For each SL pair, a confidence score was calculated by integrating individual scores derived from different evidence sources. We also developed a statistical analysis module to estimate the druggability and sensitivity of cancer cells upon drug treatments targeting human SL partners, based on large-scale genomic data, gene expression profiles and drug sensitivity profiles on more than 1000 cancer cell lines. To help users access and mine the wealth of the data, we developed other practical functionalities, such as search and filtering, orthology search, gene set enrichment analysis. Furthermore, a user-friendly web interface has been implemented to facilitate data analysis and interpretation. With the integrated data sets and analytics functionalities, SynLethDB would be a useful resource for biomedical research community and pharmaceutical industry.

PMID: 26516187 [PubMed - indexed for MEDLINE]

Insulin secretion abnormalities in patients with cystic fibrosis.

J Cyst Fibros. 2016 Jun 8;

Authors: Schnyder MA, Benden C, Faulenbach M, Schmid C

PMID: 27289198 [PubMed - as supplied by publisher]

Bioelectrical impedance in young patients with cystic fibrosis: Validation of a specific equation and clinical relevance.

J Cyst Fibros. 2016 Jun 8;

Authors: Charatsi AM, Dusser P, Freund R, Maruani G, Rossin H, Boulier A, Le Bourgeois M, Chedevergne F, de Blic J, Letourneur A, Casimir G, Jais JP, Sermet-Gaudelus I

Abstract
BACKGROUND: Body composition (BC) analysis based on bioelectrical impedance analysis (BIA) provides conflicting results. The purpose of the study was to validate an equation specific for young patients with cystic fibrosis (CF), describe their BC and investigate its association with lung function.
METHODS: Fifty-four young CF patients were evaluated by BIA and dual X-ray absorptiometry (DXA). An empirically derived CF-specific equation for fat-free mass (FFM) estimation by BIA was elaborated after stepwise multivariate regression and the agreement between BIA and DXA was assessed by Bland-Altman plots. The association between BC and lung function was investigated by regression analysis.
RESULTS: The mean difference between the BIA and DXA assessment was close to zero. A total of 22.5% of patients (n=9) presented a FFM z-score≤-2. They had a worse pulmonary function and diaphragmatic impairment. Among these 9 patients, 7 had a normal BMI z-score>-1.
CONCLUSIONS: BIA, based on a CF-specific equation, is a reliable method for BC assessment and allows the identification of patients at risk of nutritional degradation and bad respiratory prognosis.

PMID: 27289197 [PubMed - as supplied by publisher]

Nutritional status of children with clinical conditions.

Clin Nutr. 2016 May 26;

Authors: Murphy AJ, Hill RJ, Buntain H, White M, Brookes D, Davies PS

Abstract
BACKGROUND & AIMS: Nutritional status is an important consideration in many pediatric clinical conditions. This paper aimed to examine and compare the nutritional status, represented by body cell mass (BCM), of children with cancer, Crohn's disease (CD), cystic fibrosis (CF) and anorexia nervosa (AN).
METHODS: Anthropometry was measured and BCM was calculated from whole body potassium-40 counting in 259 children being treated for clinical conditions (n = 66 cancer; n = 59 AN; n = 75 CF; n = 59 CD) and 108 healthy children. BCM was adjusted for height (BCMI) and expressed as a Z-score relative to laboratory reference data.
RESULTS: The CD (-0.80 ± 1.61; p = 0.0001) and AN (-1.13 ± 0.99; p = 0.0001) groups had significantly lower BMI Z-score than the healthy control (0.13 ± 0.75), cancer (0.50 ± 1.40) and CF groups (-0.09 ± 0.95). The cancer (-1.16 ± 1.60; p = 0.0001), CD (-1.13 ± 1.36; p = 0.0001) and AN (-0.97 ± 1.18; p = 0.0001) groups had significantly reduced BCM compared to the healthy control (0.07 ± 0.93) and CF group (0.31 ± 1.08). According to BCMI Z-score, 42.4% of patients with cancer, 41.7% of the patients with CD, 27.1% of patients with AN, and 4.0% of patients with CF were considered malnourished.
CONCLUSIONS: This study demonstrates that children undergoing treatment for clinical conditions may have alterations in BCM, independent of BMI. Children with cancer, CD and AN all had a high prevalence of malnutrition. Assessment of body composition, not just body size, is vital to understand nutritional status in children with clinical conditions.

PMID: 27289162 [PubMed - as supplied by publisher]

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Connectivity mapping (ssCMap) to predict A20-inducing drugs and their antiinflammatory action in cystic fibrosis.

Proc Natl Acad Sci U S A. 2016 Jun 10;

Authors: Malcomson B, Wilson H, Veglia E, Thillaiyampalam G, Barsden R, Donegan S, El Banna A, Elborn JS, Ennis M, Kelly C, Zhang SD, Schock BC

Abstract
Cystic fibrosis (CF) lung disease is characterized by chronic and exaggerated inflammation in the airways. Despite recent developments to therapeutically overcome the underlying functional defect in the cystic fibrosis transmembrane conductance regulator, there is still an unmet need to also normalize the inflammatory response. The prolonged and heightened inflammatory response in CF is, in part, mediated by a lack of intrinsic down-regulation of the proinflammatory NF-κB pathway. We have previously identified reduced expression of the NF-κB down-regulator A20 in CF as a key target to normalize the inflammatory response. Here, we have used publicly available gene array expression data together with a statistically significant connections' map (sscMap) to successfully predict drugs already licensed for the use in humans to induce A20 mRNA and protein expression and thereby reduce inflammation. The effect of the predicted drugs on A20 and NF-κB(p65) expression (mRNA) as well as proinflammatory cytokine release (IL-8) in the presence and absence of bacterial LPS was shown in bronchial epithelial cells lines (16HBE14o-, CFBE41o-) and in primary nasal epithelial cells from patients with CF (Phe508del homozygous) and non-CF controls. Additionally, the specificity of the drug action on A20 was confirmed using cell lines with tnfαip3 (A20) knockdown (siRNA). We also show that the A20-inducing effect of ikarugamycin and quercetin is lower in CF-derived airway epithelial cells than in non-CF cells.

PMID: 27286825 [PubMed - as supplied by publisher]

RareVariantVis: new tool for visualization of causative variants in rare monogenic disorders using whole genome sequencing data.

Bioinformatics. 2016 Jun 10;

Authors: Stokowy T, Garbulowski M, Fiskerstrand T, Holdhus R, Labun K, Sztromwasser P, Gilissen C, Hoischen A, Houge G, Petersen K, Jonassen I, Steen VM

Abstract
MOTIVATION: The search for causative genetic variants in rare diseases of presumed monogenic inheritance has been boosted by the implementation of whole exome (WES) and whole genome (WGS) sequencing. In many cases, WGS seems to be superior to WES, but the analysis and visualization of the vast amounts of data is demanding.
RESULTS: To aid this challenge, we have developed a new tool - RareVariantVis - for analysis of genome sequence data (including non-coding regions) for both germ line and somatic variants. It visualizes variants along their respective chromosomes, providing information about exact chromosomal position, zygosity and frequency, with point-and-click information regarding dbSNP IDs, gene association and variant inheritance. Rare variants as well as de novo variants can be flagged in different colors. We show the performance of the RareVariantVis tool in the Genome in a Bottle WGS data set.
AVAILABILITY: https://www.bioconductor.org/packages/3.3/bioc/html/RareVariantVis.html CONTACT: tomasz.stokowy@k2.uib.no SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID: 27288501 [PubMed - as supplied by publisher]

A giant adrenal myelolipoma in a beta-thalassemia major patient: Does ineffective erythropoiesis play a role?

Am J Hematol. 2016 Jun 10;

Authors: Motta I, Boiocchi L, Delbini P, Migone De Amicis M, Cassinerio E, Dondossola D, Rossi G, Cappellini MD

PMID: 27288248 [PubMed - as supplied by publisher]

Identification of genetic variants in pharmacokinetic genes associated with Ewing Sarcoma treatment outcome.

Ann Oncol. 2016 Jun 10;

Authors: Ruiz-Pinto S, Pita G, Patiño-García A, García-Miguel P, Alonso J, Pérez-Martínez A, Sastre A, Gómez-Mariano G, Lissat A, Scotlandi K, Serra M, Ladenstein R, Lapouble E, Pierron G, Kontny U, Picci P, Kovar H, Delattre O, González-Neira A

Abstract
BACKGROUND: Despite the effectiveness of current treatment protocols for Ewing sarcoma (ES), many patients still experience relapse, and survival following recurrence is less than 15%. We aimed to identify genetic variants that predict treatment outcome in children diagnosed with ES.
PATIENTS AND METHODS: We carried out a pharmacogenetic study of 384 single nucleotide polymorphisms (SNPs) in 24 key transport or metabolism genes relevant to drugs used to treat in pediatric patients (<30 years) with histologically confirmed ES. We studied the association of genotypes with tumor response and overall survival (OS) in a discovery cohort of 106 Spanish children, with replication in a second cohort of 389 pediatric patients from across Europe.
RESULTS: We identified associations with OS (P<0.05) for three SNPs in the Spanish cohort that were replicated in the European cohort. The strongest association observed was with rs7190447, located in the ATP-binding cassette sub-family C member 6 (ABCC6) gene (discovery: HR=14.30, 95%CI=1.53-134, P=0.020; replication: HR=9.28, 95%CI=2.20-39.2, P=0.0024) and its correlated SNP rs7192303, which was predicted to have a plausible regulatory function. We also replicated associations with rs4148737 in the ATP-binding cassette sub-family B member 1 (ABCB1) gene (discovery: HR=2.96, 95%CI=1.08-8.10, P=0.034; replication: HR=1.60, 95%CI=1.05-2.44, P=0.029), which we have previously found to be associated with poorer OS in pediatric osteosarcoma patients, and rs11188147 in cytochrome P450 family 2 subfamily C member 8 gene (CYP2C8) (discovery : HR=2.49, 95%CI=1.06-5.87, P=0.037; replication: HR=1.77, 95%CI=1.06-2.96, P=0.030), an enzyme involved in the oxidative metabolism of the ES chemotherapeutic agents cyclophosphamide and ifosfamide. None of the associations with tumor response were replicated.
CONCLUSION: Using an integrated pathway-based approach we identified polymorphisms in ABCC6, ABCB1 and CYP2C8 associated with OS. These associations were replicated in a large independent cohort, highlighting the importance of pharmacokinetic genes as prognostic markers in ES.

PMID: 27287205 [PubMed - as supplied by publisher]

The Story of Angioedema: from Quincke to Bradykinin.

Clin Rev Allergy Immunol. 2016 Jun 10;

Authors: Reshef A, Kidon M, Leibovich I

Abstract
The term "swelling" has been used in the old scriptures to illustrate a change of normal figure and, as such, an expression of illness. It should be noted that in ancient times, human diseases were very often regarded a punishment from God. Hence, it is not surprising that one of the oldest tests for infidelity involved swelling as an inflicted punishment. The great Greek physician Hippocrates (377-460 BC), considered one of the most outstanding figures in the history of medicine and "Father of the Western Medicine," already used the term oídēma to describe swelling of organs. It took many centuries later until the first description of angioedema as a distinct medical entity was minted by Quinke in 1882. The historical progression in angioedema research has been characterized by intermittent "leaps" in interest and scientific achievements. As an example, it took 75 years from the accurate description of hereditary angioedema (HAE) by Osler (1888), until a group of researchers headed by Donaldson (1963) disclosed the central role of C1 inhibitor in angioedema pathophysiology. What followed was a result of a collective effort by many researchers and scientific groups who were able to elucidate the intricate connections between the implicated biochemical pathways. Still, scientific progress was hardly translated into effective therapy, and another 45 years had to elapse until the renewed interest in HAE was boosted by studies on the efficacy and safety of novel therapies about 10 years ago. In the twenty-first century, HAE ceased to be an "orphan disease" and its future is far more optimistic. It is better managed now by specialized angioedema centers, harmonized clinical guidelines, educational programs, laboratory services, and continued basic and clinical research. Patient associations worldwide are offering support and guidance, and governments and healthcare systems are gradually addressing patient and family needs.

PMID: 27287037 [PubMed - as supplied by publisher]

Advances in the integration of transcriptional regulatory information into genome-scale metabolic models.

Biosystems. 2016 Jun 7;

Authors: Vivek-Ananth RP, Samal A

Abstract
A major goal of systems biology is to build predictive computational models of cellular metabolism. Availability of complete genome sequences and wealth of legacy biochemical information has led to the reconstruction of genome-scale metabolic networks in the last 15 years for several organisms across the three domains of life. Due to paucity of information on kinetic parameters associated with metabolic reactions, the constraint-based modelling approach, flux balance analysis (FBA), has proved to be a vital alternative to investigate the capabilities of reconstructed metabolic networks. In parallel, advent of high-throughput technologies has led to the generation of massive amounts of omics data on transcriptional regulation comprising mRNA transcript levels and genome-wide binding profile of transcriptional regulators. A frontier area in metabolic systems biology has been the development of methods to integrate the available transcriptional regulatory information into constraint-based models of reconstructed metabolic networks in order to increase the predictive capabilities of computational models and understand the regulation of cellular metabolism. Here, we review the existing methods to integrate transcriptional regulatory information into constraint-based models of metabolic networks.

PMID: 27287878 [PubMed - as supplied by publisher]

Metabolic characterization of the natural progression of chronic hepatitis B.

Genome Med. 2016;8(1):64

Authors: Schoeman JC, Hou J, Harms AC, Vreeken RJ, Berger R, Hankemeier T, Boonstra A

Abstract
BACKGROUND: Worldwide, over 350 million people are chronically infected with the hepatitis B virus (HBV) and are at increased risk of developing progressive liver diseases. The confinement of HBV replication to the liver, which also acts as the central hub for metabolic and nutritional regulation, emphasizes the interlinked nature of host metabolism and the disease. Still, the metabolic processes operational during the distinct clinical phases of a chronic HBV infection-immune tolerant, immune active, inactive carrier, and HBeAg-negative hepatitis phases-remains unexplored.
METHODS: To investigate this, we conducted a targeted metabolomics approach on serum to determine the metabolic progression over the clinical phases of chronic HBV infection, using patient samples grouped based on their HBV DNA, alanine aminotransferase, and HBeAg serum levels.
RESULTS: Our data illustrate the strength of metabolomics to provide insight into the metabolic dysregulation experienced during chronic HBV. The immune tolerant phase is characterized by the speculated viral hijacking of the glycerol-3-phosphate-NADH shuttle, explaining the reduced glycerophospholipid and increased plasmalogen species, indicating a strong link to HBV replication. The persisting impairment of the choline glycerophospholipids, even during the inactive carrier phase with minimal HBV activity, alludes to possible metabolic imprinting effects. The progression of chronic HBV is associated with increased concentrations of very long chain triglycerides together with citrulline and ornithine, reflective of a dysregulated urea cycle peaking in the HBV envelope antigen-negative phase.
CONCLUSIONS: The work presented here will aid in future studies to (i) validate and understand the implication of these metabolic changes using a thorough systems biology approach, (ii) monitor and predict disease severity, as well as (iii) determine the therapeutic value of the glycerol-3-phosphate-NADH shuttle.

PMID: 27286979 [PubMed - as supplied by publisher]

Metabolic processes of Methanococcus maripaludis and potential applications.

Microb Cell Fact. 2016;15(1):107

Authors: Goyal N, Zhou Z, Karimi IA

Abstract
Methanococcus maripaludis is a rapidly growing, fully sequenced, genetically tractable model organism among hydrogenotrophic methanogens. It has the ability to convert CO2 and H2 into a useful cleaner energy fuel (CH4). In fact, this conversion enhances in the presence of free nitrogen as the sole nitrogen source due to prolonged cell growth. Given the global importance of GHG emissions and climate change, diazotrophy can be attractive for carbon capture and utilization applications from appropriately treated flue gases, where surplus hydrogen is available from renewable electricity sources. In addition, M. maripaludis can be engineered to produce other useful products such as terpenoids, hydrogen, methanol, etc. M. maripaludis with its unique abilities has the potential to be a workhorse like Escherichia coli and S. cerevisiae for fundamental and experimental biotechnology studies. More than 100 experimental studies have explored different specific aspects of the biochemistry and genetics of CO2 and N2 fixation by M. maripaludis. Its genome-scale metabolic model (iMM518) also exists to study genetic perturbations and complex biological interactions. However, a comprehensive review describing its cell structure, metabolic processes, and methanogenesis is still lacking in the literature. This review fills this crucial gap. Specifically, it integrates distributed information from the literature to provide a complete and detailed view for metabolic processes such as acetyl-CoA synthesis, pyruvate synthesis, glycolysis/gluconeogenesis, reductive tricarboxylic acid (RTCA) cycle, non-oxidative pentose phosphate pathway (NOPPP), nitrogen metabolism, amino acid metabolism, and nucleotide biosynthesis. It discusses energy production via methanogenesis and its relation to metabolism. Furthermore, it reviews taxonomy, cell structure, culture/storage conditions, molecular biology tools, genome-scale models, and potential industrial and environmental applications. Through the discussion, it develops new insights and hypotheses from experimental and modeling observations, and identifies opportunities for further research and applications.

PMID: 27286964 [PubMed - as supplied by publisher]

Comparative genome-scale modelling of Staphylococcus aureus strains identifies strain-specific metabolic capabilities linked to pathogenicity.

Proc Natl Acad Sci U S A. 2016 Jun 10;

Authors: Bosi E, Monk JM, Aziz RK, Fondi M, Nizet V, Palsson BØ

Abstract
Staphylococcus aureus is a preeminent bacterial pathogen capable of colonizing diverse ecological niches within its human host. We describe here the pangenome of S. aureus based on analysis of genome sequences from 64 strains of S. aureus spanning a range of ecological niches, host types, and antibiotic resistance profiles. Based on this set, S. aureus is expected to have an open pangenome composed of 7,411 genes and a core genome composed of 1,441 genes. Metabolism was highly conserved in this core genome; however, differences were identified in amino acid and nucleotide biosynthesis pathways between the strains. Genome-scale models (GEMs) of metabolism were constructed for the 64 strains of S. aureus These GEMs enabled a systems approach to characterizing the core metabolic and panmetabolic capabilities of the S. aureus species. All models were predicted to be auxotrophic for the vitamins niacin (vitamin B3) and thiamin (vitamin B1), whereas strain-specific auxotrophies were predicted for riboflavin (vitamin B2), guanosine, leucine, methionine, and cysteine, among others. GEMs were used to systematically analyze growth capabilities in more than 300 different growth-supporting environments. The results identified metabolic capabilities linked to pathogenic traits and virulence acquisitions. Such traits can be used to differentiate strains responsible for mild vs. severe infections and preference for hosts (e.g., animals vs. humans). Genome-scale analysis of multiple strains of a species can thus be used to identify metabolic determinants of virulence and increase our understanding of why certain strains of this deadly pathogen have spread rapidly throughout the world.

PMID: 27286824 [PubMed - as supplied by publisher]

The microbiome during pregnancy and early postnatal life.

Semin Fetal Neonatal Med. 2016 Jun 7;

Authors: Neu J

Abstract
We are changing our concept that the newborn infant emerges from a sterile environment. In-utero colonization may have major impacts on the developing mammal in terms of development of immunity and metabolism that, with epigenetic modifications, will lead to diseases in later life. In addition, the microbial profile that develops during and after birth depends on mode of delivery, type of feeding (human milk versus formula) and various other environmental factors to which the newborn is exposed. The goal of this review is to clarify that the microbiome in the maternal fetal unit as well as the immediate changes that occur as new microbes are acquired postnatally play major roles in subsequent health and disease. Rapidly developing technologies for multi-omic analyses and systems biology are shifting paradigms in both scientific knowledge and clinical care.

PMID: 27286643 [PubMed - as supplied by publisher]