Animal models support a role for the gut microbiota in the development of hypertension. There has been a lack of epidemiological cohort studies to confirm these findings in human populations. We examined cross-sectional associations between measures of gut microbial diversity and taxonomic composition and blood pressure (BP) in 529 participants of the biracial (black and white) CARDIA study (Coronary Artery Risk Development in Young Adults). We sequenced V3-V4 regions of the 16S ribosomal RNA marker gene using DNA extracted from stool samples collected at CARDIA’s Year 30 follow-up examination (2015–2016; aged 48–60 years). We quantified associations between BP (hypertension [defined as systolic BP ≥140 mm Hg or diastolic BP ≥90 mm Hg or antihypertension medication use] and systolic BP) and within and between-person diversity measures. We conducted genera-specific multivariable-adjusted regression analysis, accounting for multiple comparisons using the false discovery rate. Hypertension and systolic BP were inversely associated with measures of α-diversity, including richness and the Shannon Diversity Index, and were distinguished with respect to principal coordinates based on a similarity matrix of genera abundance. Several specific genera were significantly associated with hypertension and systolic BP, though results were attenuated with adjustment for body mass index. Our findings support associations between within-person and between-person gut microbial community diversity and taxonomic composition and BP in a diverse population-based cohort of middle-aged adults. Future study is needed to define functional pathways that underlie observed associations and identify specific microbial targets for intervention.

Commercial trade in wildlife is the major cause of species endangerment and a main threat to animal welfare in China and its neighboring countries. Driven by consumptive use for food and traditional medicine, the large volume of both legal and illegal trade in wildlife has caused great destruction to ecosystems and pushed many species to the brink of extinction. Data gathered from trading hubs at ports, boundary markets, city markets and stores, indicates the large amount of wildlife traded in the region of Guangxi, Yunnan and Qinghai provinces, a direct result of the numerous wildlife markets available. In a survey distributed in various trading places, while about half of the respondents agreed that wildlife should be protected, 60% of them had consumed wildlife at some point in the last 2 years. The results also indicated that law and regulation on wildlife trade control is insufficient. Wildlife trade controls are very limited because of bias on the utilization of wildlife as a natural resource to be exploited by the government agencies. The survey also shows that the current situation of wildlife consumption in key cities in China is serious, especially the consumption for food. The main consumption groups in China are male and young people with high education levels and good incomes. The key in public awareness publicity and education is to give them more information on the negative impacts of wildlife consumption and knowledge of protection.

Background Despite recent decreases in the cost of sequencing, shotgun metagenome sequencing remains more expensive compared with 16S rRNA amplicon sequencing. Methods have been developed to predict the functional profiles of microbial communities based on their taxonomic composition. In this study, we evaluated the performance of three commonly used metagenome prediction tools (PICRUSt, PICRUSt2, and Tax4Fun) by comparing the significance of the differential abundance of predicted functional gene profiles to those from shotgun metagenome sequencing across different environments. Results We selected 7 datasets of human, non-human animal, and environmental (soil) samples that have publicly available 16S rRNA and shotgun metagenome sequences. As we would expect based on previous literature, strong Spearman correlations were observed between predicted gene compositions and gene relative abundance measured with shotgun metagenome sequencing. However, these strong correlations were preserved even when the abundance of genes were permuted across samples. This suggests that simple correlation coefficient is a highly unreliable measure for the performance of metagenome prediction tools. As an alternative, we compared the performance of genes predicted with PICRUSt, PICRUSt2, and Tax4Fun to sequenced metagenome genes in inference models associated with metadata within each dataset. With this approach, we found reasonable performance for human datasets, with the metagenome prediction tools performing better for inference on genes related to “housekeeping” functions. However, their performance degraded sharply outside of human datasets when used for inference. Conclusion We conclude that the utility of PICRUSt, PICRUSt2, and Tax4Fun for inference with the default database is likely limited outside of human samples and that development of tools for gene prediction specific to different non-human and environmental samples is warranted.

Bacteria and fungi are important mediators of biogeochemical processes and play essential roles in the establishment of plant communities, which makes knowledge about their recovery after extreme disturbances valuable for understanding ecosystem development. However, broad ecological differences between bacterial and fungal organisms, such as growth rates, stress tolerance, and substrate utilization, suggest they could follow distinct trajectories and show contrasting dynamics during recovery. In this study, we analyzed both the intra-annual variability and decade-scale recovery of bacterial and fungal communities in a chronosequence of reclaimed mined soils using next-generation sequencing to quantify their abundance, richness, ␤-diversity, taxonomic composition, and cooccurrence network properties. Bacterial communities shifted gradually, with overlapping ␤-diversity patterns across chronosequence ages, while shifts in fungal communities were more distinct among different ages. In addition, the magnitude of intra-annual variability in bacterial ␤-diversity was comparable to the changes across decades of chronosequence age, while fungal communities changed minimally across months. Finally, the complexity of bacterial cooccurrence networks increased with chronosequence age, while fungal networks did not show clear age-related trends. We hypothesize that these contrasting dynamics of bacteria and fungi in the chronosequence result from (i) higher growth rates for bacteria, leading to higher intra-annual variability; (ii) higher tolerance to environmental changes for fungi; and (iii) stronger influence of vegetation on fungal communities. IMPORTANCE Both bacteria and fungi play essential roles in ecosystem functions, and information about their recovery after extreme disturbances is important for understanding whole-ecosystem development. Given their many differences in phenotype, phylogeny, and life history, a comparison of different bacterial and fungal recovery patterns improves the understanding of how different components of the soil microbiota respond to ecosystem recovery. In this study, we highlight key differences between soil bacteria and fungi during the restoration of reclaimed mine soils in the form of long-term diversity patterns, intra-annual variability, and potential interaction networks. Cooccurrence networks revealed increasingly complex bacterial community interactions during recovery, in contrast to much simpler and more isolated fungal network patterns. This study compares bacterial and fungal cooccurrence networks and reveals cooccurrences persisting through successional ages.KEYWORDS bacteria, chronosequence, cooccurrence networks, disturbance, fungi, reclaimed mine soils, soil microbiota E cologists have been studying the succession dynamics of plant communities for more than a century (1, 2), and the patterns of changes in plant community composition are used as indicators for the restoration of ecosystems (3-5). However,

The purpose of this study is to evaluate similarities and differences in gut bacterial measurements and stability in the microbial communities of three different types of samples that could be used to assess different niches of the gut microbiome: rectal swab, stool, and normal rectal mucosa samples. In swab-stool comparisons, there were substantial taxa differences with some taxa varying largely by sample type (e.g. Thermaceae), inter-individual subject variation (e.g. Desulfovibrionaceae), or by both sample type and participant (e.g. Enterobacteriaceae). Comparing all three sample types with whole-genome metagenome shotgun sequencing, swab samples were much closer to stool samples than mucosa samples although all KEGG functional Level 1 and Level 2 pathways were significantly different across all sample types (e.g. transcription and environmental adaptation). However, the individual signature of participants was also observed and was largely stable between two time points. Thus, we found that while the distribution of some taxa was associated with these different sampling techniques, other taxa largely reflected individual differences in the microbial community that were insensitive to sampling technique. There is substantial variability in the assessment of the gut microbial community according to the type of sample.