Weak Coherence in Abundance Patterns Between Bacterial Classes and Their Constituent OTUs Along a Regulated River

Abundance-Occupancy Relationships Along Taxonomic Ranks Reveal a Consistency of Niche Differentiation in Marine Bacterioplankton With Distinct Lifestyles

Abundance-occupancy relationships (AORs) are an important determinant of biotic community dynamics and habitat suitability. However, little is known about their role in complex bacterial communities, either within a phylogenetic framework or as a function of niche breadth. Based on data obtained in a field study in the St. Lawrence Estuary, we used 16S rRNA gene sequencing to examine the vertical patterns, strength, and character of AORs for particle-attached and free-living bacterial assemblages. Free-living communities were phylogenetically more diverse than particle-attached communities. The dominant taxa were consistent in terms of their presence/absence but population abundances differed in surface water vs. the cold intermediate layer. Significant, positive AORs characterized all of the surveyed communities across all taxonomic ranks of bacteria, thus demonstrating an ecologically conserved trend for both free-living and particle-attached bacteria. The strength of the AORs was low at the species level but higher at and above the genus level. These results demonstrate that an assessment of the distributions and population densities of finely resolved taxa does not necessarily improve determinations of apparent niche differences in marine bacterioplankton communities at regional scales compared with the information inferred from a broad taxonomic classification.

Rapid shifts in methanotrophic bacterial communities mitigate methane emissions from a tropical hydropower reservoir and its downstream river

Methane-oxidizing bacteria (MOB) present in the water column mitigate methane (CH₄) emissions from hydropower complexes to the atmosphere. By creating a discontinuity in rivers, dams cause large environmental variations, including in CH₄ and oxygen concentrations, between upstream, reservoir, and downstream segments. Although highest freshwater methanotrophic activity is often detected at low oxygen concentrations, CH₄ oxidation in well-oxygenated downstream rivers below dams has also been reported. Here we combined DNA and RNA high-throughput sequencing with microscopic enumeration (by CARD-FISH) and biogeochemical data to investigate the abundance, composition, and potential activity of MOB taxa from upstream to downstream waters in the tropical hydropower complex Batang Ai (Malaysia). High relative abundance of MOB (up to 61% in 16S rRNA sequences and 19% in cell counts) and enrichment of stable isotopic signatures of CH₄ (up to 0‰) were detected in the hypoxic hypolimnion of the reservoir and in the outflowing downstream river. MOB community shifts along the river-reservoir system reflected environmental sorting of taxa and an interrupted hydrologic connectivity in which downstream MOB communities resembled reservoir's hypolimnetic communities but differed from upstream and surface reservoir communities. In downstream waters, CH₄ oxidation was accompanied by fast cell growth of particular MOB taxa. Our results suggest that rapid shifts in active MOB communities allow the mitigation of CH₄ emissions from different zones of hydropower complexes, including in quickly re-oxygenated rivers downstream of dams.

Lifestyle preferences drive the structure and diversity of bacterial and archaeal communities in a small riverine reservoir

Spatial heterogeneity along river networks is interrupted by dams, affecting the transport, processing, and storage of organic matter, as well as the distribution of biota. We here investigated the structure of planktonic (free-living, FL), particle-attached (PA) and sediment-associated (SD) bacterial and archaeal communities within a small reservoir. We combined targeted-amplicon sequencing of bacterial and archaeal 16S rRNA genes in the DNA and RNA community fractions from FL, PA and SD, followed by imputed functional metagenomics, in order to unveil differences in their potential metabolic capabilities within the reservoir (tail, mid, and dam sections) and lifestyles (FL, PA, SD). Both bacterial and archaeal communities were structured according to their life-style preferences rather than to their location in the reservoir. Bacterial communities were richer and more diverse when attached to particles or inhabiting the sediment, while Archaea showed an opposing trend. Differences between PA and FL bacterial communities were consistent at functional level, the PA community showing higher potential capacity to degrade complex carbohydrates, aromatic compounds, and proteinaceous materials. Our results stressed that particle-attached prokaryotes were phylogenetically and metabolically distinct from their free-living counterparts, and that performed as hotspots for organic matter processing within the small reservoir.

TaxAss: Leveraging a Custom Freshwater Database Achieves Fine-Scale Taxonomic Resolution

Taxonomy assignment of freshwater microbial communities is limited by the minimally curated phylogenies used for large taxonomy databases. Here we introduce TaxAss, a taxonomy assignment workflow that classifies 16S rRNA gene amplicon data using two taxonomy reference databases: a large comprehensive database and a small ecosystem-specific database rigorously curated by scientists within a field. We applied TaxAss to five different freshwater data sets using the comprehensive SILVA database and the freshwater-specific FreshTrain database. TaxAss increased the percentage of the data set classified compared to using only SILVA, especially at fine-resolution family to species taxon levels, while across the freshwater test data sets classifications increased by as much as 11 to 40% of total reads. A similar increase in classifications was not observed in a control mouse gut data set, which was not expected to contain freshwater bacteria. TaxAss also maintained taxonomic richness compared to using only the FreshTrain across all taxon levels from phylum to species. Without TaxAss, most organisms not represented in the FreshTrain were unclassified, but at fine taxon levels, incorrect classifications became significant. We validated TaxAss using simulated amplicon data derived from full-length clone libraries and found that 96 to 99% of test sequences were correctly classified at fine resolution. TaxAss splits a data set's sequences into two groups based on their percent identity to reference sequences in the ecosystem-specific database. Sequences with high similarity to sequences in the ecosystem-specific database are classified using that database, and the others are classified using the comprehensive database. TaxAss is free and open source and is available at https://www.github.com/McMahonLab/TaxAssIMPORTANCE Microbial communities drive ecosystem processes, but microbial community composition analyses using 16S rRNA gene amplicon data sets are limited by the lack of fine-resolution taxonomy classifications. Coarse taxonomic groupings at the phylum, class, and order levels lump ecologically distinct organisms together. To avoid this, many researchers define operational taxonomic units (OTUs) based on clustered sequences, sequence variants, or unique sequences. These fine-resolution groupings are more ecologically relevant, but OTU definitions are data set dependent and cannot be compared between data sets. Microbial ecologists studying freshwater have curated a small, ecosystem-specific taxonomy database to provide consistent and up-to-date terminology. We created TaxAss, a workflow that leverages this database to assign taxonomy. We found that TaxAss improves fine-resolution taxonomic classifications (family, genus, and species). Fine taxonomic groupings are more ecologically relevant, so they provide an alternative to OTU-based analyses that is consistent and comparable between data sets.

High-throughput amplicon sequencing and stream benthic bacteria: identifying the best taxonomic level for multiple-stressor research

Disentangling the individual and interactive effects of multiple stressors on microbial communities is a key challenge to our understanding and management of ecosystems. Advances in molecular techniques allow studying microbial communities in situ and with high taxonomic resolution. However, the taxonomic level which provides the best trade-off between our ability to detect multiple-stressor effects versus the goal of studying entire communities remains unknown. We used outdoor mesocosms simulating small streams to investigate the effects of four agricultural stressors (nutrient enrichment, the nitrification inhibitor dicyandiamide (DCD), fine sediment and flow velocity reduction) on stream bacteria (phyla, orders, genera, and species represented by Operational Taxonomic Units with 97% sequence similarity). Community composition was assessed using amplicon sequencing (16S rRNA gene, V3-V4 region). DCD was the most pervasive stressor, affecting evenness and most abundant taxa, followed by sediment and flow velocity. Stressor pervasiveness was similar across taxonomic levels and lower levels did not perform better in detecting stressor effects. Community coverage decreased from 96% of all sequences for abundant phyla to 28% for species. Order-level responses were generally representative of responses of corresponding genera and species, suggesting that this level may represent the best compromise between stressor sensitivity and coverage of bacterial communities.

Coupling Bacterioplankton Populations and Environment to Community Function in Coastal Temperate Waters

Bacterioplankton play a key role in marine waters facilitating processes important for carbon cycling. However, the influence of specific bacterial populations and environmental conditions on bacterioplankton community performance remains unclear. The aim of the present study was to identify drivers of bacterioplankton community functions, taking into account the variability in community composition and environmental conditions over seasons, in two contrasting coastal systems. A Least Absolute Shrinkage and Selection Operator (LASSO) analysis of the biological and chemical data obtained from surface waters over a full year indicated that specific bacterial populations were linked to measured functions. Namely, Synechococcus (Cyanobacteria) was strongly correlated with protease activity. Both function and community composition showed seasonal variation. However, the pattern of substrate utilization capacity could not be directly linked to the community dynamics. The overall importance of dissolved organic matter (DOM) parameters in the LASSO models indicate that bacterioplankton respond to the present substrate landscape, with a particular importance of nitrogenous DOM. The identification of common drivers of bacterioplankton community functions in two different systems indicates that the drivers may be of broader relevance in coastal temperate waters.