ResearchPad - group-d-streptococci https://www.researchpad.co Default RSS Feed en-us © 2020 Newgen KnowledgeWorks <![CDATA[Traditional milk transformation schemes in Côte d’Ivoire and their impact on the prevalence of <i>Streptococcus bovis</i> complex bacteria in dairy products]]> https://www.researchpad.co/article/elastic_article_14743 The Streptococcus bovis/Streptococcus equinus complex (SBSEC) and possibly Streptococcus infantarius subsp. infantarius (Sii) are associated with human and animal diseases. Sii predominate in spontaneously fermented milk products with unknown public health effects. Sii/SBSEC prevalence data from West Africa in correlation with milk transformation practices are limited. Northern Côte d’Ivoire served as study area due to its importance in milk production and consumption and to link a wider Sudano-Sahelian pastoral zone of cross-border trade. We aimed to describe the cow milk value chain and determine Sii/SBSEC prevalence with a cross-sectional study. Dairy production practices were described as non-compliant with basic hygiene standards. The system is influenced by secular sociocultural practices and environmental conditions affecting product properties. Phenotypic and molecular analyses identified SBSEC in 27/43 (62.8%) fermented and 26/67 (38.8%) unfermented milk samples. Stratified by collection stage, fermented milk at producer and vendor levels featured highest SBSEC prevalence of 71.4% and 63.6%, respectively. Sii with 62.8% and 38.8% as well as Streptococcus gallolyticus subsp. macedonicus with 7.0% and 7.5% were the predominant SBSEC species identified among fermented and unfermented milk samples, respectively. The population structure of Sii/SBSEC isolates seems to reflect evolving novel dairy-adapted, non-adapted and potentially pathogenic lineages. Northern Côte d’Ivoire was confirmed as area with high Sii presence in dairy products. The observed production practices and the high diversity of Sii/SBSEC supports in-depth investigations on Sii ecology niche, product safety and related technology in the dairy value chain potentially affecting large population groups across sub-Saharan Africa.

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<![CDATA[Case-control study: Determination of potential risk factors for the colonization of healthy volunteers with Streptococcus gallolyticus subsp. gallolyticus]]> https://www.researchpad.co/article/5989db59ab0ee8fa60bdf1c8

Streptococcus gallolyticus subsp. gallolyticus was identified in humans and animals as commensal of the gut and can act as a causative agent of endocarditis and septicemia. A case-control study was performed to identify yet unknown risk factors for the transmission of this facultative pathogen. The prevalence in the gut of 99 healthy volunteers was determined using real-time polymerase chain reaction resulting in 62.5% S. gallolyticus subsp. gallolyticus positive excrements. Subsequent cultivation offered three isolates and epidemiological analysis based on MLST revealed sequence type (ST) 3 and ST 7, previously detected from bovine and endocarditis patients. These results support the hypotheses of the zoonotic potential of this bacterium. Participant questionnaires were evaluated concerning personal characteristics, nutritional habits and animal contact. Specifically, closer contact between participants and animals influenced the colonization of the human gut significantly and was further affected if volunteers used excrement for the fertilization of plants.

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<![CDATA[Managing uncertainty in metabolic network structure and improving predictions using EnsembleFBA]]> https://www.researchpad.co/article/5989db54ab0ee8fa60bdd00b

Genome-scale metabolic network reconstructions (GENREs) are repositories of knowledge about the metabolic processes that occur in an organism. GENREs have been used to discover and interpret metabolic functions, and to engineer novel network structures. A major barrier preventing more widespread use of GENREs, particularly to study non-model organisms, is the extensive time required to produce a high-quality GENRE. Many automated approaches have been developed which reduce this time requirement, but automatically-reconstructed draft GENREs still require curation before useful predictions can be made. We present a novel approach to the analysis of GENREs which improves the predictive capabilities of draft GENREs by representing many alternative network structures, all equally consistent with available data, and generating predictions from this ensemble. This ensemble approach is compatible with many reconstruction methods. We refer to this new approach as Ensemble Flux Balance Analysis (EnsembleFBA). We validate EnsembleFBA by predicting growth and gene essentiality in the model organism Pseudomonas aeruginosa UCBPP-PA14. We demonstrate how EnsembleFBA can be included in a systems biology workflow by predicting essential genes in six Streptococcus species and mapping the essential genes to small molecule ligands from DrugBank. We found that some metabolic subsystems contributed disproportionately to the set of predicted essential reactions in a way that was unique to each Streptococcus species, leading to species-specific outcomes from small molecule interactions. Through our analyses of P. aeruginosa and six Streptococci, we show that ensembles increase the quality of predictions without drastically increasing reconstruction time, thus making GENRE approaches more practical for applications which require predictions for many non-model organisms. All of our functions and accompanying example code are available in an open online repository.

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