A Metataxonomic Approach Could Be Considered for Cattle Clinical Mastitis Diagnostics

Mastitis is one of the most costly diseases affecting the dairy industry, and identification of the causative microorganism(s) is essential. Here, we report the use of next-generation sequencing of bacterial 16S rRNA genes for clinical mastitis diagnosis. We used 65 paired milk samples, collected from the mastitic and a contralateral healthy quarter of mastitic dairy cattle to evaluate the technique as a potential alternative to bacterial culture or targeted PCR. One large commercial dairy farm was used, with one trained veterinarian collecting the milk samples. The 16S rRNA genes were individually amplified and sequenced using the MiSeq platform. The MiSeq Reporter was used in order to analyze the obtained sequences. Cattle were categorized according to whether or not 1 of the 10 most abundant bacterial genera in the mastitic quarter exhibited an increase in relative abundance between the healthy and mastitic quarters equal to, or exceeding, twofold. We suggest that this increase in relative abundance is indicative of the genus being a causative mastitis pathogen. Well-known mastitis-causing pathogens such as Streptococcus uberis and Staphylococcus spp. were identified in most cattle. We were able to diagnose 53 out of the 65 studied cases and identify potential new mastitis pathogens such as Sneathia sanguinegens and Listeria innocua, which are difficult to identify by bacterial culture because of their fastidious nature

Quantifying and mapping species threat abatement opportunitiesto support national target setting

The successful implementation of the Convention on Biological Diversity’s post-2020Global Biodiversity Framework will rely on effective translation of targets from global tonational level and increased engagement across diverse sectors of society. Species conserva-tion targets require policy support measures that can be applied to a diversity of taxonomicgroups, that link action targets to outcome goals, and that can be applied to both global andnational data sets to account for national context, which the species threat abatement andrestoration (STAR) metric does. To test the flexibility of STAR, we applied the metric to vascular plants listed on national red lists of Brazil, Norway, and South Africa. The STARmetric uses data on species’ extinction risk, distributions, and threats, which we obtainedfrom national red lists to quantify the contribution that threat abatement and habitatrestoration activities could make to reducing species’ extinction risk. Across all 3 coun-tries, the greatest opportunity for reducing plant species’ extinction risk was from abatingthreats from agricultural activities, which could reduce species’ extinction risk by 54% inNorway, 36% in South Africa, and 29% in Brazil. Species extinction risk could be reducedby a further 21% in South Africa by abating threats from invasive species and by 21% inBrazil by abating threats from urban expansion. Even with different approaches to red-listing among countries, the STAR metric yielded informative results that identified wherethe greatest conservation gains could be made for species through threat-abatement andrestoration activities. Quantifiably linking local taxonomic coverage and data collection toglobal processes with STAR would allow national target setting to align with global targetsand enable state and nonstate actors to measure and report on their potential contributionsto species conservation. habitat restoration, national red lists, species’ extinction risk, threat reduction, threatened species, vascular plantspublishedVersio

The Human Serum Metabolome

Continuing improvements in analytical technology along with an increased interest in performing comprehensive, quantitative metabolic profiling, is leading to increased interest pressures within the metabolomics community to develop centralized metabolite reference resources for certain clinically important biofluids, such as cerebrospinal fluid, urine and blood. As part of an ongoing effort to systematically characterize the human metabolome through the Human Metabolome Project, we have undertaken the task of characterizing the human serum metabolome. In doing so, we have combined targeted and non-targeted NMR, GC-MS and LC-MS methods with computer-aided literature mining to identify and quantify a comprehensive, if not absolutely complete, set of metabolites commonly detected and quantified (with today's technology) in the human serum metabolome. Our use of multiple metabolomics platforms and technologies allowed us to substantially enhance the level of metabolome coverage while critically assessing the relative strengths and weaknesses of these platforms or technologies. Tables containing the complete set of 4229 confirmed and highly probable human serum compounds, their concentrations, related literature references and links to their known disease associations are freely available at http://www.serummetabolome.ca

TPH2 Gene Polymorphisms and Major Depression – A Meta-Analysis

BACKGROUND: Tryptophan hydroxylase-2 (TPH2) is the rate-limiting enzyme in the synthetic pathway for brain serotonin and is considered key factor for maintaining normal serotonin transmission in the central neuron system (CNS). Gene-disease association studies have reported a relationship between TPH2 and major depressive disorder (MDD) in different populations, however subsequent studies have produced contradictory results. OBJECTIVES: We performed a systematic overview and a meta-analysis with all available data up-to-date. METHODS: We scrutinized PubMed, Embase, HuGNet and China National Knowledge Infrastructure (CNKI ) and last update was held on October 2011. We also searched the manuscripts and the supplementary documents of the published genome-wide association studies in the field. Effect sizes of independent loci that have been studied in more than 3 articles were synthesized using fixed and random effects models. RESULTS: We found 27 eligible articles that studied a total of 74 single nucleotide polymorphisms (SNPs). Finally, 12 independent loci were included in the meta-analysis. The synthesis of the data shown that two SNPs (rs4570625 and rs17110747) were associated with MDD using fixed effects models. SNP rs4570625 had low heterogeneity and remained significant using the more conservative random effects calculations with a summary OR = 0.83 (95% CI: 0.73-0.96). CONCLUSION: The current study identified a SNP (rs4570625) with strong epidemiological credibility; however more studies are required to provide robust evidence for other weak associations