The impact of host metapopulation structure on the population genetics of colonizing bacteria

Many key bacterial pathogens are frequently carried asymptomatically, and the emergence and spread of these opportunistic pathogens can be driven, or mitigated, via demographic changes within the host population. These inter-host transmission dynamics combine with basic evolutionary parameters such as rates of mutation and recombination, population size and selection, to shape the genetic diversity within bacterial populations. Whilst many studies have focused on how molecular processes underpin bacterial population structure, the impact of host migration and the connectivity of the local populations has received far less attention. A stochastic neutral model incorporating heightened local transmission has been previously shown to fit closely with genetic data for several bacterial species. However, this model did not incorporate transmission limiting population stratification, nor the possibility of migration of strains between subpopulations, which we address here by presenting an extended model. We study the consequences of migration in terms of shared genetic variation and show by simulation that the previously used summary statistic, the allelic mismatch distribution, can be insensitive to even large changes in microepidemic and migration rates. Using likelihood-free inference with genotype network topological summaries we fit a simpler model to commensal and hospital samples from the common nosocomial pathogens Staphylococcus aureus, Staphylococcus epidermidis, Enterococcus faecalis and Enterococcus faecium. Only the hospital data for E. faecium display clearly marked deviations from the model predictions which may be attributable to its adaptation to the hospital environment

Crowdfunding Models, Strategies, and Choices Between Them

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Gut Microbiome Composition Is Predictive of Incident Type 2 Diabetes in a Population Cohort of 5,572 Finnish Adults

OBJECTIVETo examine the previously unknown long-term association between gut microbiome composition and incident type 2 diabetes in a representative population cohort.RESEARCH DESIGN AND METHODSWe collected fecal samples from 5,572 Finns (mean age 48.7 years; 54.1% women) in 2002 who were followed up for incident type 2 diabetes until 31 December 2017. The samples were sequenced using shotgun metagenomics. We examined associations between gut microbiome composition and incident diabetes using multivariable-adjusted Cox regression models. We first used the eastern Finland subpopulation to obtain initial findings and validated these in the western Finland subpopulation.RESULTSAltogether, 432 cases of incident diabetes occurred over the median follow-up of 15.8 years. We detected four species and two clusters consistently associated with incident diabetes in the validation models. These four species were Clostridium citroniae (hazard ratio [HR] 1.21; 95% CI 1.04–1.42), C. bolteae (HR 1.20; 95% CI 1.04–1.39), Tyzzerella nexilis (HR 1.17; 95% CI 1.01–1.36), and Ruminococcus gnavus (HR 1.17; 95% CI 1.01–1.36). The positively associated clusters, cluster 1 (HR 1.18; 95% CI 1.02–1.38) and cluster 5 (HR 1.18; 95% CI 1.02–1.36), mostly consisted of these same species.CONCLUSIONSWe observed robust species-level taxonomic features predictive of incident type 2 diabetes over long-term follow-up. These findings build on and extend previous mainly cross-sectional evidence and further support links between dietary habits, metabolic diseases, and type 2 diabetes that are modulated by the gut microbiome. The gut microbiome can potentially be used to improve disease prediction and uncover novel therapeutic targets for diabetes.</p

Genome-wide association of functional traits linked with<i> Campylobacter jejuni </i>survival from farm to fork

Campylobacter jejuni is a major cause of bacterial gastroenteritis worldwide, primarily associated with the consumption of contaminated poultry. C. jejuni lineages vary in host range and prevalence in human infection, suggesting differences in survival throughout the poultry processing chain. From 7,343 MLST-characterised isolates, we sequenced 600 C. jejuni and C. coli isolates from various stages of poultry processing and clinical cases. A genome-wide association study (GWAS) in C. jejuni ST-21 and ST-45 complexes identified genetic elements over-represented in clinical isolates that increased in frequency throughout the poultry processing chain. Disease-associated SNPs were distinct in these complexes, sometimes organised in haplotype blocks. The function of genes containing associated elements was investigated, demonstrating roles for cj1377c in formate metabolism, nuoK in aerobic survival and oxidative respiration, and cj1368-70 in nucleotide salvage. This work demonstrates the utility of GWAS for investigating transmission in natural zoonotic pathogen populations and provides evidence that major C. jejuni lineages have distinct genotypes associated with survival, within the host specific niche, from farm to fork. </p

Toxoplasma gondii seropositivity and risk factors in pregnant women followed up by the Family Health Strategy

INTRODUCTION : Toxoplasmosis is a zoonotic infection caused by Toxoplasma gondii. It is transmitted by the ingestion of contaminated water and foods, by soil contaminated with cat feces, especially while handling it, and congenitally via the placenta. The diagnosis of maternal infection is made by serological detection of either IgM or IgG antibodies. This study assessed the seropositivity in pregnant women followed up by the Family Health Strategy (FHS) in Lages, Santa Catarina, Brazil. METHODS: The study was performed in 19 FHS units and included 148 childbearing women. The outcomes evaluated were IgM and IgG seropositivity and behavioral variables. RESULTS: IgG yielded positive results in 16% of the pregnant women, whereas IgM was positive in only 1%. CONCLUSIONS: The 1% IgM positivity rate for T. gondii indicates congenital toxoplasmosis is not common in Lages

Phylogeny-Aware Analysis of Metagenome Community Ecology Based on Matched Reference Genomes while Bypassing Taxonomy

We introduce the operational genomic unit (OGU) method, a metagenome analysis strategy that directly exploits sequence alignment hits to individual reference genomes as the minimum unit for assessing the diversity of microbial communities and their relevance to environmental factors. This approach is independent of taxonomic classification, granting the possibility of maximal resolution of community composition, and organizes features into an accurate hierarchy using a phylogenomic tree. The outputs are suitable for contemporary analytical protocols for community ecology, differential abundance, and supervised learning while supporting phylogenetic methods, such as UniFrac and phylofactorization, that are seldom applied to shotgun metagenomics despite being prevalent in 16S rRNA gene amplicon studies. As demonstrated in two real-world case studies, the OGU method produces biologically meaningful patterns from microbiome data sets. Such patterns further remain detectable at very low metagenomic sequencing depths. Compared with taxonomic unit-based analyses implemented in currently adopted metagenomics tools, and the analysis of 16S rRNA gene amplicon sequence variants, this method shows superiority in informing biologically relevant insights, including stronger correlation with body environment and host sex on the Human Microbiome Project data set and more accurate prediction of human age by the gut microbiomes of Finnish individuals included in the FINRISK 2002 cohort. We provide Woltka, a bioinformatics tool to implement this method, with full integration with the QIIME 2 package and the Qiita web platform, to facilitate adoption of the OGU method in future metagenomics studies.IMPORTANCE Shotgun metagenomics is a powerful, yet computationally challenging, technique compared to 16S rRNA gene amplicon sequencing for decoding the composition and structure of microbial communities. Current analyses of metagenomic data are primarily based on taxonomic classification, which is limited in feature resolution. To solve these challenges, we introduce operational genomic units (OGUs), which are the individual reference genomes derived from sequence alignment results, without further assigning them taxonomy. The OGU method advances current read-based metagenomics in two dimensions: (i) providing maximal resolution of community composition and (ii) permitting use of phylogeny-aware tools. Our analysis of real-world data sets shows that it is advantageous over currently adopted metagenomic analysis methods and the finest-grained 16S rRNA analysis methods in predicting biological traits. We thus propose the adoption of OGUs as an effective practice in metagenomic studies.</p

Whole-genome sequencing association analysis of quantitative red blood cell phenotypes: The NHLBI TOPMed program

Whole-genome sequencing (WGS), a powerful tool for detecting novel coding and non-coding disease-causing variants, has largely been applied to clinical diagnosis of inherited disorders. Here we leveraged WGS data in up to 62,653 ethnically diverse participants from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program and assessed statistical association of variants with seven red blood cell (RBC) quantitative traits. We discovered 14 single variant-RBC trait associations at 12 genomic loci, which have not been reported previously. Several of the RBC trait-variant associations (RPN1, ELL2, MIDN, HBB, HBA1, PIEZO1, and G6PD) were replicated in independent GWAS datasets imputed to the TOPMed reference panel. Most of these discovered variants are rare/low frequency, and several are observed disproportionately among non-European Ancestry (African, Hispanic/Latino, or East Asian) populations. We identified a 3 bp indel p.Lys2169del (g.88717175_88717177TCT[4]) (common only in the Ashkenazi Jewish population) of PIEZO1, a gene responsible for the Mendelian red cell disorder hereditary xerocytosis (MIM: 194380), associated with higher mean corpuscular hemoglobin concentration (MCHC). In stepwise conditional analysis and in gene-based rare variant aggregated association analysis, we identified several of the variants in HBB, HBA1, TMPRSS6, and G6PD that represent the carrier state for known coding, promoter, or splice site loss-of-function variants that cause inherited RBC disorders. Finally, we applied base and nuclease editing to demonstrate that the sentinel variant rs112097551 (nearest gene RPN1) acts through a cis-regulatory element that exerts long-range control of the gene RUVBL1 which is essential for hematopoiesis. Together, these results demonstrate the utility of WGS in ethnically diverse population-based samples and gene editing for expanding knowledge of the genetic architecture of quantitative hematologic traits and suggest a continuum between complex trait and Mendelian red cell disorders

Rous sarcoma virus nucleic acid-binding protein p12 is necessary for viral 70S RNA dimer formation and packaging.

To study the function(s) of the Rous sarcoma virus nucleic acid-binding protein p12, we constructed mutants by using two restriction sites in the p12 proviral coding sequence of the Prague C strain to insert KpnI synthetic linkers. The two restriction sites are in the same reading frame, which allowed us to construct a deletion mutant lacking the two conserved Cys-His regions and a duplication mutant containing three intact Cys-His boxes. These mutant DNAs were transfected into chicken embryo fibroblasts, and the viral particles produced in a transient assay were characterized biochemically and for infectivity. Our results indicate that the Rous sarcoma virus nucleic acid-binding protein p12 is necessary for genomic RNA packaging but not for particle assembly and is implicated in the formation of a stable 70S dimeric RNA. Moreover, the fact that one mutant was apparently able to package normal 70S RNA but was not infectious suggests a role for p12 during the infection process