Amplicon-based marker gene surveys form the basis of most microbiome and other microbial community studies. Such PCR-based methods have multiple steps, each of which is susceptible to error and bias. Variance in results has also arisen through the use of multiple methods of next-generation sequencing (NGS) amplicon library preparation. Here we formally characterized errors and biases by comparing different methods of amplicon-based NGS library preparation. Using mock community standards, we analyzed the amplification process to reveal insights into sources of experimental error and bias in amplicon-based microbial community and microbiome experiments. We present a method that improves on the current best practices and enables the detection of taxonomic groups that often go undetected with existing methods.
Relatives have more similar gut microbiomes than nonrelatives, but the degree to which this similarity results from shared genotypes versus shared environments has been controversial. Here, we leveraged 16,234 gut microbiome profiles, collected over 14 years from 585 wild baboons, to reveal that host genetic effects on the gut microbiome are nearly universal. Controlling for diet, age, and socioecological variation, 97% of microbiome phenotypes were significantly heritable, including several reported as heritable in humans. Heritability was typically low (mean = 0.068) but was systematically greater in the dry season, with low diet diversity, and in older hosts. We show that longitudinal profiles and large sample sizes are crucial to quantifying microbiome heritability, and indicate scope for selection on microbiome characteristics as a host phenotype.
Aims: A next-generation, Illumina-based sequencing approach was used to characterize the bacterial community at ten sites along the Upper Mississippi River to evaluate shifts in the community potentially resulting from upstream inputs and land use changes. Furthermore, methodological parameters including filter size, sample volume and sample reproducibility were evaluated to determine the best sampling practices for community characterization. Methods and Results: Community structure and diversity in the river was determined using Illumina next-generation sequencing technology and the V6 hypervariable region of 16S rDNA. A total of 16 400 operational taxonomic units (OTUs) were observed (4594 AE 824 OTUs per sample). Proteobacteria, Actinobacteria, Bacteroidetes, Cyanobacteria and Verrucomicrobia accounted for 93Á6 AE 1Á3% of all sequence reads, and 90Á5 AE 2Á5% belonged to OTUs shared among all sites (n = 552). Among nonshared sequence reads at each site, 33-49% were associated with potentially anthropogenic impacts upstream of the second sampling site. Alpha diversity decreased with distance from the pristine headwaters, while rainfall and pH were positively correlated with diversity. Replication and smaller filter pore sizes minimally influenced the characterization of community structure. Conclusions: Shifts in community structure are related to changes in the relative abundance, rather than presence/absence of OTUs, suggesting a 'core bacterial community' is present throughout the Upper Mississippi River. Significance and Impact of the Study: This study is among the first to characterize a large riverine bacterial community using a next-generationsequencing approach and demonstrates that upstream influences and potentially anthropogenic impacts can influence the presence and relative abundance of OTUs downstream resulting in significant variation in community structure.
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