Meter-scale variation within a single transect demands attention to taxon accumulation curves in riverine microbiome studies

doi:10.1007/s11783-022-1543-6

Front. Environ. Sci. Eng.

2022, Vol. 16

Issue (5) : 64 https://doi.org/10.1007/s11783-022-1543-6

RESEARCH ARTICLE

Meter-scale variation within a single transect demands attention to taxon accumulation curves in riverine microbiome studies

Bingdi Liu¹, Lin Zhang¹, Jason H. Knouft^2,³, Fangqiong Ling^1,^4,^5,⁶(

)

¹. Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, MO 63130, USA
². Department of Biology, Saint Louis University, St. Louis, MO 63103, USA
³. National Great Rivers Research and Education Center, East Alton, MO 62035, USA
⁴. Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, MO 63130, USA
⁵. Division of Biological and Biomedical Sciences, Washington University in St. Louis, St. Louis, MO 63110, USA
⁶. Division of Computational and Data Science, Washington University in St. Louis, St. Louis, MO 63130, USA

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Abstract

● Riverine microbiomes exhibited hyperlocal variation within a single transect.

● Certain family-level taxa directionally associated with river center and bank.

● Taxon accumulation curves within a transect urges more nuanced sampling design.

Microbial communities inhabiting river ecosystems play crucial roles in global biogeochemical cycling and pollution attenuation. Spatial variations in local microbial assemblages are important for detailed understanding of community assembly and developing robust biodiversity sampling strategies. Here, we intensely analyzed twenty water samples collected from a one-meter spaced transect from the near-shore to the near-center in the Meramec River in eastern Missouri, USA and examined the microbial community composition with 16S rRNA gene amplicon sequencing. Riverine microbiomes across the transect exhibited extremely high similarity, with Pearson’s correlation coefficients above 0.9 for all pairwise community composition comparisons. However, despite the high similarity, PERMANOVA revealed significant spatial differences between near-shore and near-center communities (p = 0.001). Sloan’s neutral model simulations revealed that within-transect community composition variation was largely explained by demographic stochasticity (R² = 0.89). Despite being primarily explained by neutral processes, LefSe analyses also revealed taxa from ten families of which relative abundances differed directionally from the bank to the river center, indicating an additional role of environmental filtering. Notably, the local variations within a river transect can have profound impacts on the documentation of alpha diversity. Taxon-accumulation curves indicated that even twenty samples did not fully saturate the sampling effort at the genus level, yet four, six and seven samples were able to capture 80% of the phylum-level, family-level, and genus-level diversity, respectively. This study for the first time reveals hyperlocal variations in riverine microbiomes and their assembly mechanisms, demanding attention to more robust sampling strategies for documenting microbial diversity in riverine systems.

Keywords Microbiome Freshwater Taxon accumulation curve Community assembly

Corresponding Author(s): Fangqiong Ling

Issue Date: 16 May 2022

Cite this article:

Bingdi Liu,Lin Zhang,Jason H. Knouft, et al. Meter-scale variation within a single transect demands attention to taxon accumulation curves in riverine microbiome studies[J]. Front. Environ. Sci. Eng., 2022, 16(5): 64.

URL:

https://academic.hep.com.cn/fese/EN/10.1007/s11783-022-1543-6
https://academic.hep.com.cn/fese/EN/Y2022/V16/I5/64

Fig.1 Sampling location and sampling scheme. (A) Location of the sampling transect in the Meramec River watershed. (38.502075°N, 90.591522°W). (B) Schematics of intensive transect sampling. Twenty water microbiome samples were taken in 1-meter intervals from near-shore to near-center in the transect.

Fig.2 High reproducibility and microbiome profiles of sites within a transect. (A) The average relative abundance of abundant phyla (> 3% in relative abundance) and classes (> 0.05% in relative abundance) in all river water microbiome samples. The taxa that were assigned as “NA” at phylum level were grouped into “unclassified Phyla” and the phyla with mean relative abundance less than 3% were grouped into “other phyla”. The classes from “other phyla” were not labeled and classes assigned with “NA” or with mean relative abundance less than 0.05% were grouped into “other Class” under their own phyla. (B) The distribution of Pearson correlation coefficients of 190 pairs from twenty sites.

Fig.3 Near-shore and near-center groups emerged in PCoA analysis of Bray-Curtis dissimilarities. (A) The principal coordinate analysis resulting from Bray-Curtis dissimilarities revealed a dramatic difference in composition between near-shore and near-center samples. Circles indicate samples; numbers indicate the distance between the sampling site and the shore. Orange and blue polygons indicate near-shore and near-center groups. (B) Histogram of 1-Bray-Curtis dissimilarity values from 90 pairs of within-group comparisons in near-shore or near-center groups. (C) Histogram of 1-Bray-Curtis dissimilarity values from 100 pairs between-group comparisons across near-shore or near-center groups.

Fig.4 The informative ASVs explained the community composition difference in near-shore and near-center groups. (A) Linear discriminant analysis (LDA) effect size measurement at the ASV level and accumulated with the family names. (B) Area plots of relative abundance of informative ASVs accumulating at the family level.

Fig.5 Taxon accumulative curves within a transect exhibiting the detection efficiency for the richness of phylum (A), family (B), and genus (C). The vertical bars indicate the confidence intervals, and the lines indicate the mean number of taxa accumulated.

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