Pilgrim Erik M, Smucker Nathan J, Wu Huiyun, Martinson John, Nietch Christopher T, Molina Marirosa, Darling John A, Johnson Brent R
United States Environmental Protection Agency, Office of Research and Development, Cincinnati, OH 45268, USA.
School of Public Health & Tropical Medicine, Tulane University, New Orleans, LA 70112, USA.
Water (Basel). 2022 Jul 30;14(15):1-24. doi: 10.3390/w14152361.
Indicators based on nutrient-biota relationships in streams can inform water quality restoration and protection programs. Bacterial assemblages could be particularly useful indicators of nutrient effects because they are species-rich, important contributors to ecosystem processes in streams, and responsive to rapidly changing conditions. Here, we sampled 25 streams weekly (12-14 times each) and used 16S rRNA gene metabarcoding of periphyton-associated bacteria to quantify the effects of total phosphorus (TP) and total nitrogen (TN). Threshold indicator taxa analysis identified assemblage-level changes and amplicon sequence variants (ASVs) that increased or decreased with increasing TP and TN concentrations (i.e., low P, high P, low N, and high N ASVs). Boosted regression trees confirmed that relative abundances of gene sequence reads for these four indicator groups were associated with nutrient concentrations. Gradient forest analysis complemented these results by using multiple predictors and random forest models for each ASV to identify portions of TP and TN gradients at which the greatest changes in assemblage structure occurred. Synthesized statistical results showed bacterial assemblage structure began changing at 24 μg TP/L with the greatest changes occurring from 110 to 195 μg/L. Changes in the bacterial assemblages associated with TN gradually occurred from 275 to 855 μg/L. Taxonomic and phylogenetic analyses showed that low nutrient ASVs were commonly Firmicutes, Verrucomicrobiota, Flavobacteriales, and Caulobacterales, Pseudomonadales, and Rhodobacterales of Proteobacteria, whereas other groups, such as Chitinophagales of Bacteroidota, and Burkholderiales, Rhizobiales, Sphingomonadales, and Steroidobacterales of Proteobacteria comprised the high nutrient ASVs. Overall, the responses of bacterial ASV indicators in this study highlight the utility of metabarcoding periphyton-associated bacteria for quantifying biotic responses to nutrient inputs in streams.
基于溪流中营养物质与生物群落关系的指标可为水质恢复和保护计划提供参考。细菌群落可能是营养物质影响的特别有用的指标，因为它们物种丰富，是溪流生态系统过程的重要贡献者，并且对快速变化的条件有响应。在这里，我们每周对25条溪流进行采样（每条溪流采样12 - 14次），并使用与周丛生物相关细菌的16S rRNA基因宏条形码技术来量化总磷（TP）和总氮（TN）的影响。阈值指示分类群分析确定了随着TP和TN浓度增加而增加或减少的群落水平变化和扩增子序列变体（ASV）（即低磷、高磷、低氮和高氮ASV）。增强回归树证实，这四个指示组的基因序列读数相对丰度与营养物质浓度相关。梯度森林分析通过对每个ASV使用多个预测变量和随机森林模型来补充这些结果，以确定群落结构发生最大变化的TP和TN梯度部分。综合统计结果表明，细菌群落结构在TP浓度为24μg/L时开始变化，最大变化发生在110至195μg/L之间。与TN相关的细菌群落变化在275至855μg/L之间逐渐发生。分类学和系统发育分析表明，低营养ASV通常属于厚壁菌门、疣微菌门、黄杆菌目、柄杆菌目、假单胞菌目以及变形菌门的红杆菌目，而其他类群，如拟杆菌门的噬几丁质菌目以及变形菌门的伯克霍尔德菌目、根瘤菌目、鞘脂单胞菌目和类固醇杆菌目则构成了高营养ASV。总体而言，本研究中细菌ASV指标的响应突出了对与周丛生物相关细菌进行宏条形码分析在量化溪流中生物对营养物质输入响应方面的实用性。
