Core functional traits of bacterial communities in the Upper Mississippi River show limited variation in response to land cover

Abstract

Taxonomic characterization of environmental microbial communities via high-throughput DNA sequencing has revealed that patterns in microbial biogeography affect community structure. However, shifts in functional diversity related to variation in taxonomic composition are poorly understood. To overcome limitations due to the prohibitive cost of high-depth metagenomic sequencing, tools to infer functional diversity based on phylogenetic distributions of functional traits have been developed. In this study we characterized functional microbial diversity at 11 sites along the Mississippi River in Minnesota using both metagenomic sequencing and functional-inference-based (PICRUSt) approaches. This allowed us to determine how distance and variation in land cover throughout the river influenced the distribution of functional traits, as well as to validate PICRUSt inferences. The distribution and abundance of functional traits, by metagenomic analysis, were similar among sites, with a median standard deviation of 0.0002% among tier 3 functions in KEGG. Overall inferred functional variation was significantly different (P ≤ 0.035) between two water basins surrounded by agricultural vs. developed land cover, and abundances of bacterial orders that correlated with functional traits by metagenomic analysis were greater where abundances of the trait were inferred to be higher. PICRUSt inferences were significantly correlated (r = 0.147, P = 1.80 × 10−30) with metagenomic annotations. Discrepancies between metagenomic and PICRUSt taxonomic-functional relationships, however, suggested potential functional redundancy among abundant and rare taxa that impeded the ability to accurately assess unique functional traits among rare taxa at this sequencing depth. Results of this study suggest that a suite of “core functional traits” is conserved throughout the river and distributions of functional traits, rather than specific taxa, may shift in response to environmental heterogeneity.

Comparison of two bioinformatics tools used to characterize the microbial diversity and predictive functional attributes of microbial mats from Lake Obersee, Antarctica

“…In addition, accuracy of the PI-CRUSt predictions was estimated using the Nearest Sequenced Taxon Index (NSTI) values of the two mat samples used in this study. The NSTI value validates the taxonomy-based PICRUSt-predicted KEGG functional categories of the microbial communities (Langille et al, 2013; Staley et al, 2014; Lopes et al, 2016; Kim et al, 2017). Since the output of the functional profiles generated by PICRUSt was not compatible with Tax4Fun, we have written an R script for the comparative analyses of the taxonomy-based metabolic functional predictions of the microbial communities in the two mat samples (Supplementary Materials, S1.1, S1.2, and S2).…”

“…), and surface soil samples from the Austre Lovénbreen glacier in High Arctic (mean NSTI = 0.18 ± 0.03 s.d.) (Langille et al, 2013; Staley et al, 2014; Lopes et al, 2016; Kim et al, 2017). Thus, the mean NSTI values in our study suggest that the predicted metabolic functions of the microbial communities in Lake Obersee mat samples are close to the known microbial reference genome databases, implying higher accuracy of the predictions.…”

Spatial distribution of planktonic bacterial and archaeal communities in the upper section of the tidal reach in Yangtze River

“…Our findings showed that the predominant bacterial communities in this river section were Proteobacteria, Firmicutes, and Actinobacteria, which were all once abundant in many of the freshwater lakes and reservoirs in China32 and exhibited high abundances in some other freshwater environments30333435. From these findings, we found that the bacterial communities in this section of Yangtze River exhibited a typical feature of freshwater populations.…”

Microbial rRNA:rDNA gene ratios may be unexpectedly low due to extracellular DNA preservation in soils

“…Correction for 16S gene copy number is a built-in function of the PICRUSt functional gene prediction package (Langille et al, 2013), which has been used to investigate the functional diversity of bacterial communities in humans (David et al, 2013), salamanders (Loudon et al, 2013), and river water (Staley et al, 2014). Kembel et al (2012) showed that 16S gene copy correction of individual OTUs can affect measures of abundance for several taxa (Cyanobacteria Group II, Alteromonadales) within marine bacterial communities, as well as the structure of hierarchical clustering of communities sampled from the human microbiome.…”