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

Microbial ecology of northern Gulf of Mexico estuarine waters

Estuarine and coastal ecosystems are of high economic and ecological importance, owing to their diverse communities and the disproportionate role they play in carbon cycling, particularly in carbon sequestration. Organisms inhabiting these environments must overcome strong natural fluctuations in salinity, nutrients, and turbidity, as well as numerous climate change-induced disturbances such as land loss, sea level rise, and, in some locations, increasingly severe tropical cyclones that threaten to disrupt future ecosystem health. The northern Gulf of Mexico (nGoM) along the Louisiana coast contains dozens of estuaries, including the Mississippi-Atchafalaya River outflow, which dramatically influence the region due to their vast upstream watershed. Nevertheless, the microbiology of these estuaries and surrounding coastal environments has received little attention. To improve our understanding of microbial ecology in the understudied coastal nGoM, we conducted a 16S rRNA gene amplicon survey at eight sites and multiple time points along the Louisiana coast and one inland swamp spanning freshwater to high brackish salinities, totaling 47 duplicated Sterivex (0.2-2.7 µm) and prefilter (>2.7 µm) samples. We cataloged over 13,000 Amplicon Sequence ariants (ASVs) from common freshwater and marine clades such as SAR11 (Alphaproteobacteria), Synechococcus (Cyanobacteria), and acI and Candidatus Actinomarina (Actinobacteria). We observed correlations with freshwater or marine habitats in many organisms and characterized a group of taxa with specialized distributions across brackish water sites, supporting the hypothesis of an endogenous brackish-water community. Additionally, we observed brackish-water associations for several aquatic clades typically considered marine or freshwater taxa, such as SAR11 subclade II, SAR324, and the acI Actinobacteria. The data presented here expand the geographic coverage of microbial ecology in estuarine communities, help delineate the native and transitory members of these environments, and provide critical aquatic microbiological baseline data for coastal and estuarine sites in the nGoM.IMPORTANCEEstuarine and coastal waters are diverse ecosystems influenced by tidal fluxes, interconnected wetlands, and river outflows, which are of high economic and ecological importance. Microorganisms play a pivotal role in estuaries as "first responders" and ecosystem architects, yet despite their ecological importance, they remain underrepresented in microbial studies compared to open ocean environments. This leads to substantial knowledge gaps that are important for understanding global biogeochemical cycling and making decisions about conservation and management strategies in these environments. Our study makes key contributions to the microbial ecology of estuarine and coastal habitats in the northern Gulf of Mexico. Our microbial community data support the concept of a globally distributed, core brackish microbiome and emphasize previously underrecognized brackish-water taxa. Given the projected worsening of land loss, oil spills, and natural disasters in this region, our results will serve as important baseline data for researchers investigating the microbial communities found across estuaries.

Description of a 'plankton filtration bias' in sequencing-based bacterial community analysis and of an Arduino microcontroller-based flowmeter device that can help to resolve it

Diversity studies of aquatic picoplankton (bacterioplankton) communities using size-class filtration, DNA extraction, PCR and sequencing of phylogenetic markers, require a robust methodological pipeline, since biases have been demonstrated essentially at all levels, including DNA extraction, primer choice and PCR. Even different filtration volumes of the same plankton sample and, thus, different biomass loading of the filters, can distort the sequencing results. In this study, we designed an Arduino microcontroller-based flowmeter that records the decrease of initial (maximal) flowrate as proxy for increasing biomass loading and clogging of filters during plankton filtration. The device was tested using freshwater plankton of Lake Constance, and total DNA was extracted and an 16S rDNA amplicon was sequenced. We confirmed that different filtration volumes used for the same water sample affect the sequencing results. Differences were visible in alpha and beta diversities and across all taxonomic ranks. Taxa most affected were typical freshwater Actinobacteria and Bacteroidetes, increasing up to 38% and decreasing up to 29% in relative abundance, respectively. In another experiment, a lake water sample was filtered undiluted and three-fold diluted, and each filtration was stopped once the flowrate had reduced to 50% of initial flowrate, hence, at the same degree of filter clogging. The three-fold diluted sample required three-fold filtration volumes, while equivalent amounts of total DNA were extracted and differences across all taxonomic ranks were not statistically significant compared to the undiluted controls. In conclusion, this work confirms a volume/biomass-dependent bacterioplankton filtration bias for sequencing-based community analyses and provides an improved procedure for controlling biomass loading during filtrations and recovery of equivalent amounts of DNA from samples independent of the plankton density. The application of the device can also avoid the distorting of sequencing results as caused by the plankton filtration bias.

Evolving understanding of rumen methanogen ecophysiology

Production of methane by methanogenic archaea, or methanogens, in the rumen of ruminants is a thermodynamic necessity for microbial conversion of feed to volatile fatty acids, which are essential nutrients for the animals. On the other hand, methane is a greenhouse gas and its production causes energy loss for the animal. Accordingly, there are ongoing efforts toward developing effective strategies for mitigating methane emissions from ruminant livestock that require a detailed understanding of the diversity and ecophysiology of rumen methanogens. Rumen methanogens evolved from free-living autotrophic ancestors through genome streamlining involving gene loss and acquisition. The process yielded an oligotrophic lifestyle, and metabolically efficient and ecologically adapted descendants. This specialization poses serious challenges to the efforts of obtaining axenic cultures of rumen methanogens, and consequently, the information on their physiological properties remains in most part inferred from those of their non-rumen representatives. This review presents the current knowledge of rumen methanogens and their metabolic contributions to enteric methane production. It also identifies the respective critical gaps that need to be filled for aiding the efforts to mitigate methane emission from livestock operations and at the same time increasing the productivity in this critical agriculture sector.

Trophic interactions shape the spatial organization of medium-chain carboxylic acid producing granular biofilm communities

Granular biofilms producing medium-chain carboxylic acids (MCCA) from carbohydrate-rich industrial feedstocks harbor highly streamlined communities converting sugars to MCCA either directly or via lactic acid as intermediate. We investigated the spatial organization and growth activity patterns of MCCA producing granular biofilms grown on an industrial side stream to test (i) whether key functional guilds (lactic acid producing Olsenella and MCCA producing Oscillospiraceae) stratified in the biofilm based on substrate usage, and (ii) whether spatial patterns of growth activity shaped the unique, lenticular morphology of these biofilms. First, three novel isolates (one Olsenella and two Oscillospiraceae species) representing over half of the granular biofilm community were obtained and used to develop FISH probes, revealing that key functional guilds were not stratified. Instead, the outer 150-500 µm of the granular biofilm consisted of a well-mixed community of Olsenella and Oscillospiraceae, while deeper layers were made up of other bacteria with lower activities. Second, nanoSIMS analysis of 15N incorporation in biofilms grown in normal and lactic acid amended conditions suggested Oscillospiraceae switched from sugars to lactic acid as substrate. This suggests competitive-cooperative interactions may govern the spatial organization of these biofilms, and suggests that optimizing biofilm size may be a suitable process engineering strategy. Third, growth activities were similar in the polar and equatorial biofilm peripheries, leaving the mechanism behind the lenticular biofilm morphology unexplained. Physical processes (e.g., shear hydrodynamics, biofilm life cycles) may have contributed to lenticular biofilm development. Together, this study develops an ecological framework of MCCA-producing granular biofilms that informs bioprocess development.

Strong succession in prokaryotic association networks and community assembly mechanisms in an acid mine drainage-impacted riverine ecosystem

Acid mine drainage (AMD) serves as an ideal model system for investigating microbial ecology, interaction, and assembly mechanism in natural environments. While previous studies have explored the structure and function of microbial communities in AMD, the succession patterns of microbial association networks and underlying assembly mechanisms during natural attenuation processes remain elusive. Here, we investigated prokaryotic microbial diversity and community assembly along an AMD-impacted river, from the extremely acidic, heavily polluted headwaters to the nearly neutral downstream sites. Microbial diversity was increased along the river, and microbial community composition shifted from acidophile-dominated to freshwater taxa-dominated communities. The complexity and relative modularity of the microbial networks were also increased, indicating greater network stability during succession. Deterministic processes, including abiotic selection of pH and high contents of sulfur and iron, governed community assembly in the headwaters. Although the stochasticity ratio was increased downstream, manganese content, microbial negative cohesion, and relative modularity played important roles in shaping microbial community structure. Overall, this study provides valuable insights into the ecological processes that govern microbial community succession in AMD-impacted riverine ecosystems. These findings have important implications for in-situ remediation of AMD contamination.

In the right place, at the right time: the integration of bacteria into the Plankton Ecology Group model

BACKGROUND

Planktonic microbial communities have critical impacts on the pelagic food web and water quality status in freshwater ecosystems, yet no general model of bacterial community assembly linked to higher trophic levels and hydrodynamics has been assessed. In this study, we utilized a 2-year survey of planktonic communities from bacteria to zooplankton in three freshwater reservoirs to investigate their spatiotemporal dynamics.

RESULTS

We observed site-specific occurrence and microdiversification of bacteria in lacustrine and riverine environments, as well as in deep hypolimnia. Moreover, we determined recurrent bacterial seasonal patterns driven by both biotic and abiotic conditions, which could be integrated into the well-known Plankton Ecology Group (PEG) model describing primarily the seasonalities of larger plankton groups. Importantly, bacteria with different ecological potentials showed finely coordinated successions affiliated with four seasonal phases, including the spring bloom dominated by fast-growing opportunists, the clear-water phase associated with oligotrophic ultramicrobacteria, the summer phase characterized by phytoplankton bloom-associated bacteria, and the fall/winter phase driven by decay-specialists.

CONCLUSIONS

Our findings elucidate the major principles driving the spatiotemporal microbial community distribution in freshwater ecosystems. We suggest an extension to the original PEG model by integrating new findings on recurrent bacterial seasonal trends. Video Abstract.

Shallow shotgun sequencing reduces technical variation in microbiome analysis

The microbiome is known to play a role in many human diseases, but identifying key microbes and their functions generally requires large studies due to the vast number of species and genes, and the high levels of intra-individual and inter-individual variation. 16S amplicon sequencing of the rRNA gene is commonly used for large studies due to its comparatively low sequencing cost, but it has poor taxonomic and functional resolution. Deep shotgun sequencing is a more accurate and comprehensive alternative for small studies, but can be cost-prohibitive for biomarker discovery in large populations. Shallow or moderate-depth shotgun metagenomics may serve as a viable alternative to 16S sequencing for large-scale and/or dense longitudinal studies, but only if resolution and reproducibility are comparable. Here we applied both 16S and shallow shotgun stool microbiome sequencing to a cohort of 5 subjects sampled twice daily and weekly, with technical replication at the DNA extraction and the library preparation/sequencing steps, for a total of 80 16S samples and 80 shallow shotgun sequencing samples. We found that shallow shotgun sequencing produced lower technical variation and higher taxonomic resolution than 16S sequencing, at a much lower cost than deep shotgun sequencing. These findings suggest that shallow shotgun sequencing provides a more specific and more reproducible alternative to 16S sequencing for large-scale microbiome studies where costs prohibit deep shotgun sequencing and where bacterial species are expected to have good coverage in whole-genome reference databases.

Complete Genome Sequences of Three Limnohabitans sp. (Lhab-A3) Strains, INBF002, TEGF004, and MORI2, Isolated from Two Lakes and a River in Japan

Freshwater bacterioplankton of the genus Limnohabitans represent a dominant group that has worldwide distribution. Here, we report the complete genome sequences of three Limnohabitans sp. (Lhab-A3 tribe) strains, i.e., INBF002, TEGF004, and MORI2, which were isolated from surface water samples from two shallow eutrophic lakes and a river in Japan.

Species invasions shift microbial phenology in a two-decade freshwater time series

Invasive species impart abrupt changes on ecosystems, but their impacts on microbial communities are often overlooked. We paired a 20 y freshwater microbial community time series with zooplankton and phytoplankton counts, rich environmental data, and a 6 y cyanotoxin time series. We observed strong microbial phenological patterns that were disrupted by the invasions of spiny water flea (Bythotrephes cederströmii) and zebra mussels (Dreissena polymorpha). First, we detected shifts in Cyanobacteria phenology. After the spiny water flea invasion, Cyanobacteria dominance crept earlier into clearwater; and after the zebra mussel invasion, Cyanobacteria abundance crept even earlier into the diatom-dominated spring. During summer, the spiny water flea invasion sparked a cascade of shifting diversity where zooplankton diversity decreased and Cyanobacteria diversity increased. Second, we detected shifts in cyanotoxin phenology. After the zebra mussel invasion, microcystin increased in early summer and the duration of toxin production increased by over a month. Third, we observed shifts in heterotrophic bacteria phenology. The Bacteroidota phylum and members of the acI Nanopelagicales lineage were differentially more abundant. The proportion of the bacterial community that changed differed by season; spring and clearwater communities changed most following the spiny water flea invasion that lessened clearwater intensity, while summer communities changed least following the zebra mussel invasion despite the shifts in Cyanobacteria diversity and toxicity. A modeling framework identified the invasions as primary drivers of the observed phenological changes. These long-term invasion-mediated shifts in microbial phenology demonstrate the interconnectedness of microbes with the broader food web and their susceptibility to long-term environmental change.

Geospatial analysis reveals a hotspot of fecal bacteria in Canadian prairie lakes linked to agricultural non-point sources

Lakes are sentinels of environmental changes within their watersheds including those induced by a changing climate and anthropogenic activities. In particular, contamination originating from point or non-point sources (NPS) within watersheds might be reflected in changes in the bacterial composition of lake water. We assessed the abundance of potentially pathogenic bacteria (PPB) sampled in 413 lakes within 8 southern Canadian ecozones that represent a wide diversity of lakes and watershed land use. The study objectives were (1) to explore the diversity of PPB; (2) to build a fecal multi-indicator from a cluster of co-occurring PPB; and (3) to predict the fecal multi-indicator over thousands of lakes. We identified bacterial taxa based on 16S rRNA amplicon sequencing and clustered 33 PPB matching taxa in the Canadian ePATHogen database using a Sørensen dissimilarity index on binary data across the sampled lakes. One cluster contained Erysipelothrix, Desulfovibrio, Bacteroides, Vibrio and Acholeplasma and was related to the NPS fraction of agriculture and pasture within the watershed as its main driver and thus it was determined as the fecal multi-indicator. We subsequently developed a fecal multi-indicator predictive model across 200 212 southern Canadian lakes which explained 55.1% of the deviance. Mapping the predictions showed higher fecal multi-indicator abundances in the Prairies and Boreal Plains compared to the other ecozones. These results represent the first attempt to map a potential fecal multi-indicator at the continental scale, which may be further improved in the future. Lastly, the study demonstrates the capacity of a multi-disciplinary approach leveraging both datasets derived from remote sensing and DNA sequencing to provide mapping information for public health governmental policies.

Environmental changes associated with drying climate are expected to affect functional groups of pro- and microeukaryotes differently in temporary saline waters

Temporary ponds are among the most sensitive aquatic habitats to climate change. Their microbial communities have crucial roles in food webs and biogeochemical cycling, yet how their communities are assembled along environmental gradients is still understudied. This study aimed to reveal the environmental drivers of diversity (OTU-based richness, evenness, and phylogenetic diversity) and community composition from a network of saline temporary ponds, soda pans, in two consecutive spring seasons characterized by contrasting weather conditions. We used DNA-based molecular methods to investigate microbial community composition. We tested the effect of environmental variables on the diversity of prokaryotic (Bacteria, Cyanobacteria) and microeukaryotic functional groups (ciliates, heterotrophic flagellates and nanoflagellates, fungi, phytoplankton) within and across the years. Conductivity and the concentration of total suspended solids and phosphorus were the most important environmental variables affecting diversity patterns in all functional groups. Environmental conditions were harsher and they also had a stronger impact on community composition in the dry spring. Our results imply that these conditions, which are becoming more frequent with climate change, have a negative effect on microbial diversity in temporary saline ponds. This eventually might translate into community-level shifts across trophic groups with changing local conditions with implications for ecosystem functioning.

Maximizing the reliability and the number of species assignments in metabarcoding studies using a curated regional library and a public repository

Biodiversity assessments relying on DNA have increased rapidly over the last decade. However, the reliability of taxonomic assignments in metabarcoding studies is variable and affected by the reference databases and the assignment methods used. Species level assignments are usually considered as reliable using regional libraries but unreliable using public repositories. In this study, we aimed to test this assumption for metazoan species detected in the Gulf of St. Lawrence in the Northwest Atlantic. We first created a regional library (GSL-rl) by data mining COI barcode sequences from BOLD, and included a reliability ranking system for species assignments. We then estimated 1) the accuracy and precision of the public repository NCBI-nt for species assignments using sequences from the regional library and 2) compared the detection and reliability of species assignments of a metabarcoding dataset using either NCBI-nt or the regional library and popular assignment methods. With NCBI-nt and sequences from the regional library, the BLAST-LCA (least common ancestor) method was the most precise method for species assignments, but the accuracy was higher with the BLAST-TopHit method (>80% over all taxa, between 70% and 90% amongst taxonomic groups). With the metabarcoding dataset, the reliability of species assignments was greater using GSL-rl compared to NCBI-nt. However, we also observed that the total number of reliable species assignments could be maximized using both GSL-rl and NCBI-nt with different optimized assignment methods. The use of a two-step approach for species assignments, i.e., using a regional library and a public repository, could improve the reliability and the number of detected species in metabarcoding studies.

Characterization of plant growth promoting activities of indigenous bacteria of phosphate mine wastes, a first step toward revegetation

Morocco holds the vast majority of the world's phosphate reserves, but due to the processes involved in extracting and commercializing these reserves, large quantities of de-structured, nutritionally deficient mine phosphate wastes are produced each year. In a semi-arid climate, these wastes severely hamper plant growth and development leading to huge unvegetated areas. Soil indigenous Plant Growth-Promoting Bacteria (PGPB) play a pivotal role in restauration of these phosphate mining wastes by revegetation, by increasing plants development, soil functioning, and nutrient cycling. The development of a vegetative cover above the degraded phosphate wastes, could stabilize and reintegrate these wastes in the surrounding environment. The current study's objectives were to isolate, characterize, and identify indigenous bacterial strains, and test their PGP activity in vitro and, for the best-performing strains in planta, in order to assess their potential for acting as biofertilizers. A quantitative test for the synthesis of auxin and the production of siderophores as well as a qualitative test for the solubilization of phosphate were performed on all isolated bacterial strains. The production of hydrogen cyanide (HCN), exopolysaccharides (EPS), and enzymes were also examined. Three bacteria, selected among the best PGPB of this study, were tested in planta to determine whether such indigenous bacteria could aid plant growth in this de-structured and nutrient-poor mining soil. Using 16S rRNA gene sequencing, 41 bacterial strains were isolated and 11 genera were identified: Acinetobacter, Agrococcus, Bacillus, Brevibacterium, Microbacterium, Neobacillus, Paenibacillus, Peribacillus, Pseudarthrobacter, Stenotrophomonas, and Raoultella. Among the three best performing bacteria (related to Bacillus paramycoides, Brevibacterium anseongense, and Stenotrophomonas rhizophila), only Stenotrophomonas rhizophila and Brevibacterium anseongense were able to significantly enhance Lupinus albus L. growth. The best inoculation results were obtained using the strain related to Stenotrophomonas rhizophila, improving the plant's root dry weight and chlorophyll content. This is also, to our knowledge, the first study to show a PGP activity of Brevibacterium anseongense.

Variability of Microbial Communities in Two Long-Term Ice-Covered Freshwater Lakes in the Subarctic Region of Yakutia, Russia

Although under-ice microbial communities are subject to a cold environment, low concentrations of nutrients, and a lack of light, they nevertheless take an active part in biogeochemical cycles. However, we still lack an understanding of how high their diversity is and how these communities are distributed during the long-term ice-cover period. Here, we assessed for the first time the composition and distribution of microbial communities during the ice-cover period in two subarctic lakes (Labynkyr and Vorota) located in the area of the lowest temperature in the Northern Hemisphere. The diversity distribution and abundance of main bacterial taxa as well as the composition of microalgae varied by time and habitat. The 16S rRNA gene sequencing method revealed, in general, a high diversity of bacterial communities where Proteobacteria (~ 45%) and Actinobacteria (~ 21%) prevailed. There were significant differences between the communities of the lakes: Chthoniobacteraceae, Moraxellaceae, and Pirellulaceae were abundant in Lake Labynkyr, while Cyanobiaceae, Oligoflexales, Ilumatobacteraceae, and Methylacidiphilaceae were more abundant in Lake Vorota. The most abundant families were evenly distributed in April, May, and June their contribution was different in different habitats. In April, Moraxellaceae and Ilumatobacteraceae were the most abundant in the water column, while Sphingomonadaceae was abundant both in water column and on the ice bottom. In May, the abundance of Comamonadaceae increased and reached the maximum in June, while Cyanobiaceae, Oxalobacteraceae, and Pirellulaceae followed. We found a correlation of the structure of bacterial communities with snow thickness, pH, N_min concentration, and conductivity. We isolated psychrophilic heterotrophic bacteria both from dominating and minor taxa of the communities studied. This allowed for specifying their ecological function in the under-ice communities. These findings will advance our knowledge of the under-ice microbial life.

Beyond Basic Diversity Estimates-Analytical Tools for Mechanistic Interpretations of Amplicon Sequencing Data

Understanding microbial ecology through amplifying short read regions, typically 16S rRNA for prokaryotic species or 18S rRNA for eukaryotic species, remains a popular, economical choice. These methods provide relative abundances of key microbial taxa, which, depending on the experimental design, can be used to infer mechanistic ecological underpinnings. In this review, we discuss recent advancements in in situ analytical tools that have the power to elucidate ecological phenomena, unveil the metabolic potential of microbial communities, identify complex multidimensional interactions between species, and compare stability and complexity under different conditions. Additionally, we highlight methods that incorporate various modalities and additional information, which in combination with abundance data, can help us understand how microbial communities respond to change in a typical ecosystem. Whilst the field of microbial informatics continues to progress substantially, our emphasis is on popular methods that are applicable to a broad range of study designs. The application of these methods can increase our mechanistic understanding of the ongoing dynamics of complex microbial communities.

Seasonal Succession and Coherence Among Bacteria and Microeukaryotes in Lake Baikal

Microorganisms exhibit seasonal succession governed by physicochemical factors and interspecies interactions, yet drivers of this process in different environments remain to be determined. We used high-throughput sequencing of 16S rRNA and 18S rRNA genes to study seasonal dynamics of bacterial and microeukaryotic communities at pelagic site of Lake Baikal from spring (under-ice, mixing) to autumn (direct stratification). The microbial community was subdivided into distinctive coherent clusters of operational taxonomic units (OTUs). Individual OTUs were consistently replaced during different seasonal events. The coherent clusters change their contribution to the microbial community depending on season. Changes of temperature, concentrations of silicon, and nitrates are the key factors affected the structure of microbial communities. Functional prediction revealed that some bacterial or eukaryotic taxa that switched with seasons had similar functional properties, which demonstrate their functional redundancy. We have also detected specific functional properties in different coherent clusters of bacteria or microeukaryotes, which can indicate their ability to adapt to seasonal changes of environment. Our results revealed a relationship between seasonal succession, coherency, and functional features of freshwater bacteria and microeukaryotes.

Bacterial, Phytoplankton, and Viral Distributions and Their Biogeochemical Contexts in Meromictic Lake Cadagno Offer Insights into the Proterozoic Ocean Microbial Loop

Lake Cadagno, a permanently stratified high-alpine lake with a persistent microbial bloom in its chemocline, has long been considered a model for the low-oxygen, high-sulfide Proterozoic ocean. Although the lake has been studied for over 25 years, the absence of concerted study of the bacteria, phytoplankton, and viruses, together with primary and secondary production, has hindered a comprehensive understanding of its microbial food web. Here, the identities, abundances, and productivity of microbes were evaluated in the context of Lake Cadagno biogeochemistry. Photosynthetic pigments together with 16S rRNA gene phylogenies suggest the prominence of eukaryotic phytoplankton chloroplasts, primarily chlorophytes. Chloroplasts closely related to those of high-alpine-adapted Ankyra judayi persisted with oxygen in the mixolimnion, where photosynthetic efficiency was high, while chloroplasts of Closteriopsis-related chlorophytes peaked in the chemocline and monimolimnion. The anoxygenic phototrophic sulfur bacterium Chromatium dominated the chemocline along with Lentimicrobium, a genus of known fermenters. Secondary production peaked in the chemocline, which suggested that anoxygenic primary producers depended on heterotrophic nutrient remineralization. The virus-to-microbe ratio peaked with phytoplankton abundances in the mixolimnion and were at a minimum where Chromatium abundance was highest, trends that suggest that viruses may play a role in the modulation of primary production. Through the combined analysis of bacterial, eukaryotic, viral, and biogeochemical spatial dynamics, we provide a comprehensive synthesis of the Lake Cadagno microbial loop. This study offers a new ecological perspective on how biological and geochemical connections may have occurred in the chemocline of the Proterozoic ocean, where eukaryotic microbial life is thought to have evolved.

Flavobacterium ammonificans sp. nov. and Flavobacterium ammoniigenes sp. nov., ammonifying bacteria isolated from surface river water

Three aerobic, Gram-stain-negative, non-motile, rod-shaped bacteria, designated as strains SHINM13^T, GENT5^T and GENT11 were isolated from surface river water (Saitama Prefecture, Japan). SHINM13^T and GENT11 were positive for catalase, whereas GENT5^T was negative. Phylogenetic analyses based on the 16S rRNA gene (1341 bp) or 40 marker gene (34,513 bp) sequences revealed that the strains formed distinct phylogenetic lineages within the genus Flavobacterium. The three strains shared 99.3-99.6 % 16S rRNA gene sequence similarity among each other. The average nucleotide identity by orthology (OrthoANI) and digital DNA-DNA hybridization (dDDH) values between strains SHINM13^T and GENT11 were 96.56 and 82.1 %, respectively, and those between SHINM13^T and GENT5^T were 83.46 % and 52.9 %, respectively. The major cellular fatty acids were C_15 : 1ω6c, iso-C_15 : 0, iso-C_15 : 1G, anteiso-C_15 : 0 and iso-C_15 : 0 3-OH. The major polar lipid was phosphatidylethanolamine. SHINM13^T and GENT5^T contained menaquinone-6 (MK-6) as the predominant respiratory quinone, and their DNA G+C contents were 34.4 and 35.1 mol%, respectively. Genome sequencing of the three isolates revealed a genome size of 2.26-2.40 Mbp. Furthermore, all three isolates converted dissolved organic nitrogen to ammonium during cell growth. On the basis of the results of phenotypic and phylogenetic analyses, strains SHINM13^T and GENT11 and GENT5^T represent two distinct novel species in the genus Flavobacterium, for which the names Flavobacterium ammonificans sp. nov. (type strain SHINM13^T =JCM 34684^T =NCIMB 15379^T) and Flavobacterium ammoniigenes sp. nov. (type strain GENT5^T =JCM 32249^T=NCIMB 15380^T) are proposed.

RESCRIPt: Reproducible sequence taxonomy reference database management

Nucleotide sequence and taxonomy reference databases are critical resources for widespread applications including marker-gene and metagenome sequencing for microbiome analysis, diet metabarcoding, and environmental DNA (eDNA) surveys. Reproducibly generating, managing, using, and evaluating nucleotide sequence and taxonomy reference databases creates a significant bottleneck for researchers aiming to generate custom sequence databases. Furthermore, database composition drastically influences results, and lack of standardization limits cross-study comparisons. To address these challenges, we developed RESCRIPt, a Python 3 software package and QIIME 2 plugin for reproducible generation and management of reference sequence taxonomy databases, including dedicated functions that streamline creating databases from popular sources, and functions for evaluating, comparing, and interactively exploring qualitative and quantitative characteristics across reference databases. To highlight the breadth and capabilities of RESCRIPt, we provide several examples for working with popular databases for microbiome profiling (SILVA, Greengenes, NCBI-RefSeq, GTDB), eDNA and diet metabarcoding surveys (BOLD, GenBank), as well as for genome comparison. We show that bigger is not always better, and reference databases with standardized taxonomies and those that focus on type strains have quantitative advantages, though may not be appropriate for all use cases. Most databases appear to benefit from some curation (quality filtering), though sequence clustering appears detrimental to database quality. Finally, we demonstrate the breadth and extensibility of RESCRIPt for reproducible workflows with a comparison of global hepatitis genomes. RESCRIPt provides tools to democratize the process of reference database acquisition and management, enabling researchers to reproducibly and transparently create reference materials for diverse research applications. RESCRIPt is released under a permissive BSD-3 license at https://github.com/bokulich-lab/RESCRIPt.

Generating and managing sequence and taxonomy reference data presents a bottleneck to many researchers, whether they are generating custom databases or attempting to format existing, curated reference databases for use with standard sequence analysis tools. Evaluating database quality and choosing the “best” database can be an equally formidable challenge. We developed RESCRIPt to alleviate this bottleneck, supporting reproducible, streamlined generation, curation, and evaluation of reference sequence databases. RESCRIPt uses QIIME 2 artifact file formats, which store all processing steps as data provenance within each file, allowing researchers to retrace the computational steps used to generate any given file. We used RESCRIPt to benchmark several commonly used marker-gene sequence databases for 16S rRNA genes, ITS, and COI sequences, demonstrating both the utility of RESCRIPt to streamline use of these databases, but also to evaluate several qualitative and quantitative characteristics of each database. We show that larger databases are not always best, and curation steps to reduce redundancy and filter out noisy sequences may be beneficial for some applications. We anticipate that RESCRIPt will streamline the use, management, and evaluation/selection of reference database materials for microbiomics, diet metabarcoding, eDNA, and other diverse applications.

Human Fecal Contamination Corresponds to Changes in the Freshwater Bacterial Communities of a Large River Basin

Microbial water quality is generally monitored by culturable fecal indicator bacteria (FIB), which are intended to signal human health risk due to fecal pollution. However, FIB have limited utility in most urbanized watersheds as they do not discriminate among fecal pollution sources, tend to make up a small fraction of the total microbial community, and do not inform on pollution impacts on the native ecosystem. To move beyond these limitations, we assessed entire bacterial communities and investigated how bacterial diversity relates to traditional ecological and human health-relevant water quality indicators throughout the Milwaukee River Basin. Samples were collected from 16 sites on 5 days during the summer, including both wet and dry weather events, and were processed by 16S rRNA gene amplicon sequencing. Historical water quality at each sampling location, as opposed to upstream land use, was associated significantly with bacterial community alpha diversity. Source partitioning the sequence data was important for determining water quality relationships. Sewage-associated bacterial sequences were detected in all samples, and the relative abundance of sewage sequences was strongly associated with the human Bacteroides fecal marker. From this relationship, we developed a preliminary threshold for human sewage pollution when using bacterial community sequence data. Certain abundant freshwater bacterial sequences were also associated with human fecal pollution, suggesting their possible utility in water quality monitoring. This study sheds light on how bacterial community analysis can be used to supplement current water quality monitoring techniques to better understand interactions between ecological water quality and human health indicators. IMPORTANCE Surface waters in highly developed mixed-use watersheds are frequently impacted by a wide variety of pollutants, leading to a range of impairments that must be monitored and remediated. With advancing technologies, microbial community sequencing may soon become a feasible method for routine evaluation of the ecological quality and human health risk of a water body. In this study, we partnered with a local citizen science organization to evaluate the utility of microbial community sequencing for identifying pollution sources and ecological impairments in a large mixed-use watershed. We show that changes in microbial community diversity and composition are indicative of both long-term ecological impairments and short-term fecal pollution impacts. By source partitioning the sequence data, we also estimate a threshold target for human sewage pollution, which may be useful as a starting point for future development of sequencing-based water quality monitoring techniques.

Bioavailable Nutrients (N and P) and Precipitation Patterns Drive Cyanobacterial Blooms in Missisquoi Bay, Lake Champlain

Anthropogenic activities release large amounts of nitrogen (N) and phosphorus (P) nutrients into the environment. Sources of nutrients include surface and sub-surface runoffs from agricultural practices with the application of chemical fertilizers and manure as well as combined sewer overflows (CSOs). Nutrient runoffs contribute to the eutrophication of aquatic ecosystems and enhance the growth of cyanobacteria. Precipitation is an important driving force behind the runoff of nutrients from agricultural fields into surrounding water bodies. To understand the dynamics between nutrient input, precipitation and cyanobacterial growth in Missisquoi Bay, Lake Champlain (Quebec), one location in Pike River (a major tributary into the bay) and four locations in Missisquoi Bay were monitored from April to November in 2017 and 2018. Biweekly water samples were analyzed using chemical methods and high-throughput sequencing of 16S rRNA gene amplicons. High concentrations of N and P were typically measured in April and May. Three major spikes in nutrient concentrations were observed in early and mid-summer as well as early fall, all of which were associated with intense cumulative precipitation events of 40 to 100 mm within 7 days prior to sampling. Despite the high concentrations of nutrients in the spring and early summer, the cyanobacterial blooms appeared in mid to late summer as the water temperature increased. Dolichospermum sp. was the major bloom-forming cyanobacterium during both summers. A second intense bloom event of Microcystis was also observed in the fall (October and November) for both years. Variation in the cyanobacteria population was strongly associated with inorganic and readily available fractions of N and P such as nitrites and nitrates (NOx), ammonia (NH₃) and dissolved organic phosphorus (DOP). During blooms, total Kjeldahl nitrogen (TKN) and total particulate phosphorus (TPP) fractions had a substantial influence on total nitrogen (TN) and total phosphorus (TP) concentrations, respectively. The abundance of bacteria involved in the metabolism of nitrogen compared to that of phosphorus revealed the importance of nitrogen on overall microbial dynamics as well as CB formation in the bay. Our findings emphasize the combined influence of precipitation events, temperature and several bioavailable fractions of nitrogen and phosphorus on cyanobacterial bloom episodes.

Aquatic microbial community is partially functionally redundant: Insights from an in situ reciprocal transplant experiment

Microbial communities are considered to be functionally redundant, but few studies have tested this hypothesis empirically. In this study, we performed an in situ reciprocal transplant experiment on the surface and bottom waters of two lakes (Tsuei-Feng (T) and Yuan-Yang (Y)) with disparate trophic states and tracked changes in their microbial community composition and functions for 6 weeks using high-throughput sequencing and functional approaches. T lake's surface (Ts) and bottom (Tb) water active bacterial community (16S rRNA gene-transcript) was dominated by Actinobacteria, Bacteroidia, and Cyanobacteria, whereas Y lake's surface (Ys) and bottom (Yb) water had Gammaproteobacteria, Alphaproteobacteria, and Bacteroidia as the dominant classes. The community composition was resistant to changes in environmental conditions following the reciprocal transplant, but their functions tended to become similar to the incubating lakes' functional profiles. A significant linear positive relationship was observed between the microbial community and functional attributes (surface: R² = 0.5065, p < 0.0001; bottom: R² = 0.4592, p < 0.0001), though with varying scales of similarity (1-Bray Curtis distance), suggesting partial functional redundancy. Also, the entropy-based L-divergence measure identified high divergence in community composition (surface: 1.21 ± 0.54; bottom: 1.17 ± 0.51), and relatively low divergence in functional attributes (surface: 0.04 ± 0.01; bottom: 0.04 ± 0.01) in the two lakes' surface and bottom waters, providing further support for the presence of partial functional redundancy. This study enriches our understanding of community functional relationships and establishes the presence of partial functional redundancy in freshwater ecosystems.

Resistance, resilience, and functional redundancy of freshwater bacterioplankton communities facing a gradient of agricultural stressors in a mesocosm experiment

Agricultural pollution with fertilizers and pesticides is a common disturbance to freshwater biodiversity. Bacterioplankton communities are at the base of aquatic food webs, but their responses to these potentially interacting stressors are rarely explored. To test the extent of resistance and resilience in bacterioplankton communities faced with agricultural stressors, we exposed freshwater mesocosms to single and combined gradients of two commonly used pesticides: the herbicide glyphosate (0-15 mg/L) and the neonicotinoid insecticide imidacloprid (0-60 μg/L), in high or low nutrient backgrounds. Over the 43-day experiment, we tracked variation in bacterial density with flow cytometry, carbon substrate use with Biolog EcoPlates, and taxonomic diversity and composition with environmental 16S rRNA gene amplicon sequencing. We show that only glyphosate (at the highest dose, 15 mg/L), but not imidacloprid, nutrients, or their interactions measurably changed community structure, favouring members of the Proteobacteria including the genus Agrobacterium. However, no change in carbon substrate use was detected throughout, suggesting functional redundancy despite taxonomic changes. We further show that communities are resilient at broad, but not fine taxonomic levels: 24 days after glyphosate application the precise amplicon sequence variants do not return, and tend to be replaced by phylogenetically close taxa. We conclude that high doses of glyphosate - but still within commonly acceptable regulatory guidelines - alter freshwater bacterioplankton by favouring a subset of higher taxonomic units (i.e., genus to phylum) that transiently thrive in the presence of glyphosate. Longer-term impacts of glyphosate at finer taxonomic resolution merit further investigation.

Cultivation of Dominant Freshwater Bacterioplankton Lineages Using a High-Throughput Dilution-to-Extinction Culturing Approach Over a 1-Year Period

Although many culture-independent molecular analyses have elucidated a great diversity of freshwater bacterioplankton, the ecophysiological characteristics of several abundant freshwater bacterial groups are largely unknown due to the scarcity of cultured representatives. Therefore, a high-throughput dilution-to-extinction culturing (HTC) approach was implemented herein to enable the culture of these bacterioplankton lineages using water samples collected at various seasons and depths from Lake Soyang, an oligotrophic reservoir located in South Korea. Some predominant freshwater bacteria have been isolated from Lake Soyang via HTC (e.g., the acI lineage); however, large-scale HTC studies encompassing different seasons and water depths have not been documented yet. In this HTC approach, bacterial growth was detected in 14% of 5,376 inoculated wells. Further, phylogenetic analyses of 16S rRNA genes from a total of 605 putatively axenic bacterial cultures indicated that the HTC isolates were largely composed of Actinobacteria, Bacteroidetes, Alphaproteobacteria, Betaproteobacteria, Gammaproteobacteria, and Verrucomicrobia. Importantly, the isolates were distributed across diverse taxa including phylogenetic lineages that are widely known cosmopolitan and representative freshwater bacterial groups such as the acI, acIV, LD28, FukuN57, MNG9, and TRA3-20 lineages. However, some abundant bacterial groups including the LD12 lineage, Chloroflexi, and Acidobacteria could not be domesticated. Among the 71 taxonomic groups in the HTC isolates, representative strains of 47 groups could either form colonies on agar plates or be revived from frozen glycerol stocks. Additionally, season and water depth significantly affected bacterial community structure, as demonstrated by 16S rRNA gene amplicon sequencing analyses. Therefore, our study successfully implemented a dilution-to-extinction cultivation strategy to cultivate previously uncultured or underrepresented freshwater bacterial groups, thus expanding the basis for future multi-omic studies.

Depth-discrete metagenomics reveals the roles of microbes in biogeochemical cycling in the tropical freshwater Lake Tanganyika

Lake Tanganyika (LT) is the largest tropical freshwater lake, and the largest body of anoxic freshwater on Earth's surface. LT's mixed oxygenated surface waters float atop a permanently anoxic layer and host rich animal biodiversity. However, little is known about microorganisms inhabiting LT's 1470 meter deep water column and their contributions to nutrient cycling, which affect ecosystem-level function and productivity. Here, we applied genome-resolved metagenomics and environmental analyses to link specific taxa to key biogeochemical processes across a vertical depth gradient in LT. We reconstructed 523 unique metagenome-assembled genomes (MAGs) from 34 bacterial and archaeal phyla, including many rarely observed in freshwater lakes. We identified sharp contrasts in community composition and metabolic potential with an abundance of typical freshwater taxa in oxygenated mixed upper layers, and Archaea and uncultured Candidate Phyla in deep anoxic waters. Genomic capacity for nitrogen and sulfur cycling was abundant in MAGs recovered from anoxic waters, highlighting microbial contributions to the productive surface layers via recycling of upwelled nutrients, and greenhouse gases such as nitrous oxide. Overall, our study provides a blueprint for incorporation of aquatic microbial genomics in the representation of tropical freshwater lakes, especially in the context of ongoing climate change, which is predicted to bring increased stratification and anoxia to freshwater lakes.

BEExact: a Metataxonomic Database Tool for High-Resolution Inference of Bee-Associated Microbial Communities

High-throughput 16S rRNA gene sequencing technologies have robust potential to improve our understanding of bee (Hymenoptera: Apoidea)-associated microbial communities and their impact on hive health and disease. Despite recent computation algorithms now permitting exact inferencing of high-resolution exact amplicon sequence variants (ASVs), the taxonomic classification of these ASVs remains a challenge due to inadequate reference databases. To address this, we assemble a comprehensive data set of all publicly available bee-associated 16S rRNA gene sequences, systematically annotate poorly resolved identities via inclusion of 618 placeholder labels for uncultivated microbial dark matter, and correct for phylogenetic inconsistencies using a complementary set of distance-based and maximum likelihood correction strategies. To benchmark the resultant database (BEExact), we compare performance against all existing reference databases in silico using a variety of classifier algorithms to produce probabilistic confidence scores. We also validate realistic classification rates on an independent set of ∼234 million short-read sequences derived from 32 studies encompassing 50 different bee types (36 eusocial and 14 solitary). Species-level classification rates on short-read ASVs range from 80 to 90% using BEExact (with ∼20% due to "bxid" placeholder names), whereas only ∼30% at best can be resolved with current universal databases. A series of data-driven recommendations are developed for future studies. We conclude that BEExact (https://github.com/bdaisley/BEExact) enables accurate and standardized microbiota profiling across a broad range of bee species-two factors of key importance to reproducibility and meaningful knowledge exchange within the scientific community that together, can enhance the overall utility and ecological relevance of routine 16S rRNA gene-based sequencing endeavors.IMPORTANCE The failure of current universal taxonomic databases to support the rapidly expanding field of bee microbiota research has led to many investigators relying on "in-house" reference sets or manual classification of sequence reads (usually based on BLAST searches), often with vague identity thresholds and subjective taxonomy choices. This time-consuming, error- and bias-prone process lacks standardization, cripples the potential for comparative cross-study analysis, and in many cases is likely to incorrectly sway study conclusions. BEExact is structured on and leverages several complementary bioinformatic techniques to enable refined inference of bee host-associated microbial communities without any other methodological modifications necessary. It also bridges the gap between current practical outcomes (i.e., phylotype-to-genus level constraints with 97% operational taxonomic units [OTUs]) and the theoretical resolution (i.e., species-to-strain level classification with 100% ASVs) attainable in future microbiota investigations. Other niche habitats could also likely benefit from customized database curation via implementation of the novel approaches introduced in this study.

Impacts of Extreme Weather Events on Bacterial Community Composition of a Temperate Humic Lake

Extreme weather events are projected to increase in frequency and intensity as climate change continues. Heterotrophic bacteria play a critical role in lake ecosystems, yet little research has been done to determine how they are affected by such extremes. The purpose of this study was to use high-throughput sequencing to explore the bacterial community composition of a humic oligotrophic lake on the North Atlantic Irish coast and to assess the impacts on composition dynamics related to extreme weather events. Samples for sequencing were collected from Lough Feeagh on a fortnightly basis from April to November 2018. Filtration was used to separate free-living and particle-associated bacterial communities and amplicon sequencing was performed for the 16S rRNA V4 region. Two named storms, six high discharge events, and one drought period occurred during the sampling period. These events had variable, context-dependent effects on bacterial communities in Lough Feeagh. The particle-associated community was found to be more likely to respond to physical changes, such as mixing, while the free-living population responded to changes in nutrient and carbon concentrations. Generally, however, the high stability of the bacterial community observed in Lough Feeagh suggests that the bacterial community is relatively resilient to extreme weather events.

Generation of Comprehensive Ecosystem-Specific Reference Databases with Species-Level Resolution by High-Throughput Full-Length 16S rRNA Gene Sequencing and Automated Taxonomy Assignment (AutoTax)

High-throughput 16S rRNA gene amplicon sequencing is an essential method for studying the diversity and dynamics of microbial communities. However, this method is presently hampered by the lack of high-identity reference sequences for many environmental microbes in the public 16S rRNA gene reference databases and by the absence of a systematic and comprehensive taxonomy for the uncultured majority. Here, we demonstrate how high-throughput synthetic long-read sequencing can be applied to create ecosystem-specific full-length 16S rRNA gene amplicon sequence variant (FL-ASV) resolved reference databases that include high-identity references (>98.7% identity) for nearly all abundant bacteria (>0.01% relative abundance) using Danish wastewater treatment systems and anaerobic digesters as an example. In addition, we introduce a novel sequence identity-based approach for automated taxonomy assignment (AutoTax) that provides a complete seven-rank taxonomy for all reference sequences, using the SILVA taxonomy as a backbone, with stable placeholder names for unclassified taxa. The FL-ASVs are perfectly suited for the evaluation of taxonomic resolution and bias associated with primers commonly used for amplicon sequencing, allowing researchers to choose those that are ideal for their ecosystem. Reference databases processed with AutoTax greatly improves the classification of short-read 16S rRNA ASVs at the genus- and species-level, compared with the commonly used universal reference databases. Importantly, the placeholder names provide a way to explore the unclassified environmental taxa at different taxonomic ranks, which in combination with in situ analyses can be used to uncover their ecological roles.

Microbial enrichment, functional characterization and isolation from a cold seep yield piezotolerant obligate hydrocarbon degraders

Deep-sea environments can become contaminated with petroleum hydrocarbons. The effects of hydrostatic pressure (HP) in the deep sea on microbial oil degradation are poorly understood. Here, we performed long-term enrichments (100 days) from a natural cold seep while providing optimal conditions to sustain high hydrocarbon degradation rates. Through enrichments performed at increased HP and ambient pressure (AP) and by using control enrichments with marine broth, we demonstrated that both pressure and carbon source can have a big impact on the community structure. In contrast to previous studies, hydrocarbonoclastic operational taxonomic units (OTUs) remained dominant at both AP and increased HP, suggesting piezotolerance of these OTUs over the tested pressure range. Twenty-three isolates were obtained after isolation and dereplication. After recultivation at increased HP, an Alcanivorax sp. showed promising piezotolerance in axenic culture. Furthermore, preliminary co-cultivation tests indicated synergistic growth between some isolates, which shows promise for future synthetic community construction. Overall, more insights into the effect of increased HP on oil-degrading communities were obtained as well as several interesting isolates, e.g. a piezotolerant hydrocarbonoclastic bacterium for future deep-sea bioaugmentation investigation.

A large-scale assessment of lakes reveals a pervasive signal of land use on bacterial communities

Lakes play a pivotal role in ecological and biogeochemical processes and have been described as "sentinels" of environmental change. Assessing "lake health" across large geographic scales is critical to predict the stability of their ecosystem services and their vulnerability to anthropogenic disturbances. The LakePulse research network is tasked with the assessment of lake health across gradients of land use on a continental scale. Bacterial communities are an integral and rapidly responding component of lake ecosystems, yet large-scale responses to anthropogenic activity remain elusive. Here, we assess the ecological impact of land use on bacterial communities from over 200 lakes covering more than 660,000 km² across Eastern Canada. In addition to community variation between ecozones, land use across Eastern Canada also appeared to alter diversity, community composition, and network structure. Specifically, increasing anthropogenic impact within the watershed lowered diversity. Likewise, community composition was significantly correlated with agriculture and urban development within a watershed. Interaction networks showed decreasing complexity and fewer keystone taxa in impacted lakes. Moreover, we identified potential indicator taxa of high or low lake water quality. Together, these findings point to detectable bacterial community changes of largely unknown consequences induced by human activity within lake watersheds.

Environmental Controls on Microbial Diversity in Arctic Lakes of West Greenland

We assessed the microbial community structure of six arctic lakes in West Greenland and investigated relationships to lake physical and chemical characteristics. Lakes from the ice sheet region exhibited the highest species richness, while inland and plateau lakes had lower observed taxonomical diversity. Lake habitat differentiation during summer stratification appeared to alter within lake microbial community composition in only a subset of lakes, while lake variability across regions was a consistent driver of microbial community composition in these arctic lakes. Principal coordinate analysis revealed differentiation of communities along two axes: each reflecting differences in morphometric (lake surface area), geographic (latitude and distance from the ice sheet), physical lake variables (water clarity), and lakewater chemistry (dissolved organic carbon [DOC], dissolved oxygen [DO], total nitrogen [TN], and conductivity). Understanding these relationships between environmental variables and microbial communities is especially important as heterotrophic microorganisms are key to organic matter decomposition, nutrient cycling, and carbon flow through nutrient poor aquatic environments in the Arctic.

Construction of habitat-specific training sets to achieve species-level assignment in 16S rRNA gene datasets

BACKGROUND

The low cost of 16S rRNA gene sequencing facilitates population-scale molecular epidemiological studies. Existing computational algorithms can resolve 16S rRNA gene sequences into high-resolution amplicon sequence variants (ASVs), which represent consistent labels comparable across studies. Assigning these ASVs to species-level taxonomy strengthens the ecological and/or clinical relevance of 16S rRNA gene-based microbiota studies and further facilitates data comparison across studies.

RESULTS

To achieve this, we developed a broadly applicable method for constructing high-resolution training sets based on the phylogenic relationships among microbes found in a habitat of interest. When used with the naïve Bayesian Ribosomal Database Project (RDP) Classifier, this training set achieved species/supraspecies-level taxonomic assignment of 16S rRNA gene-derived ASVs. The key steps for generating such a training set are (1) constructing an accurate and comprehensive phylogenetic-based, habitat-specific database; (2) compiling multiple 16S rRNA gene sequences to represent the natural sequence variability of each taxon in the database; (3) trimming the training set to match the sequenced regions, if necessary; and (4) placing species sharing closely related sequences into a training-set-specific supraspecies taxonomic level to preserve subgenus-level resolution. As proof of principle, we developed a V1-V3 region training set for the bacterial microbiota of the human aerodigestive tract using the full-length 16S rRNA gene reference sequences compiled in our expanded Human Oral Microbiome Database (eHOMD). We also overcame technical limitations to successfully use Illumina sequences for the 16S rRNA gene V1-V3 region, the most informative segment for classifying bacteria native to the human aerodigestive tract. Finally, we generated a full-length eHOMD 16S rRNA gene training set, which we used in conjunction with an independent PacBio single molecule, real-time (SMRT)-sequenced sinonasal dataset to validate the representation of species in our training set. This also established the effectiveness of a full-length training set for assigning taxonomy of long-read 16S rRNA gene datasets.

CONCLUSION

Here, we present a systematic approach for constructing a phylogeny-based, high-resolution, habitat-specific training set that permits species/supraspecies-level taxonomic assignment to short- and long-read 16S rRNA gene-derived ASVs. This advancement enhances the ecological and/or clinical relevance of 16S rRNA gene-based microbiota studies. Video Abstract.

Temperature and Nutrient Levels Correspond with Lineage-Specific Microdiversification in the Ubiquitous and Abundant Freshwater Genus Limnohabitans

Most freshwater bacterial communities are characterized by a few dominant taxa that are often ubiquitous across freshwater biomes worldwide. Our understanding of the genomic diversity within these taxonomic groups is limited to a subset of taxa. Here, we investigated the genomic diversity that enables Limnohabitans, a freshwater genus key in funneling carbon from primary producers to higher trophic levels, to achieve abundance and ubiquity. We reconstructed eight putative Limnohabitans metagenome-assembled genomes (MAGs) from stations located along broad environmental gradients existing in Lake Michigan, part of Earth's largest surface freshwater system. De novo strain inference analysis resolved a total of 23 strains from these MAGs, which strongly partitioned into two habitat-specific clusters with cooccurring strains from different lineages. The largest number of strains belonged to the abundant LimB lineage, for which robust in situ strain delineation had not previously been achieved. Our data show that temperature and nutrient levels may be important environmental parameters associated with microdiversification within the Limnohabitans genus. In addition, strains predominant in low- and high-phosphorus conditions had larger genomic divergence than strains abundant under different temperatures. Comparative genomics and gene expression analysis yielded evidence for the ability of LimB populations to exhibit cellular motility and chemotaxis, a phenotype not yet associated with available Limnohabitans isolates. Our findings broaden historical marker gene-based surveys of Limnohabitans microdiversification and provide in situ evidence of genome diversity and its functional implications across freshwater gradients.IMPORTANCE Limnohabitans is an important bacterial taxonomic group for cycling carbon in freshwater ecosystems worldwide. Here, we examined the genomic diversity of different Limnohabitans lineages. We focused on the LimB lineage of this genus, which is globally distributed and often abundant, and its abundance has shown to be largely invariant to environmental change. Our data show that the LimB lineage is actually comprised of multiple cooccurring populations for which the composition and genomic characteristics are associated with variations in temperature and nutrient levels. The gene expression profiles of this lineage suggest the importance of chemotaxis and motility, traits that had not yet been associated with the Limnohabitans genus, in adapting to environmental conditions.

Microhabitats are associated with diversity-productivity relationships in freshwater bacterial communities

Eukaryotic communities commonly display a positive relationship between biodiversity and ecosystem function (BEF) but the results have been mixed when assessed in bacterial communities. Habitat heterogeneity, a factor in eukaryotic BEFs, may explain these variable observations but it has not been thoroughly evaluated in bacterial communities. Here, we examined the impact of habitat on the relationship between diversity assessed based on the (phylogenetic) Hill diversity metrics and heterotrophic productivity. We sampled co-occurring free-living (more homogenous) and particle-associated (more heterogeneous) bacterial habitats in a freshwater, estuarine lake over three seasons: spring, summer and fall. There was a strong, positive, linear relationship between particle-associated bacterial richness and heterotrophic productivity that strengthened when considering dominant taxa. There were no observable BEF trends in free-living bacterial communities for any diversity metric. Biodiversity, richness and Inverse Simpson's index, were the best predictors of particle-associated production whereas pH was the best predictor of free-living production. Our findings show that heterotrophic productivity is positively correlated with the effective number of taxa and that BEF relationships are associated with microhabitats. These results add to the understanding of the highly distinct contributions to diversity and functioning contributed by bacteria in free-living and particle-associated habitats.

Network analysis reveals succession of Microcystis genotypes accompanying distinctive microbial modules with recurrent patterns

Every member of the ecological community is connected via a network of vital and complex relationships, called the web of life. To elucidate the ecological network and interactions among producers, consumers, and decomposers in the Daechung Reservoir, Korea, during cyanobacterial harmful algal blooms (cyanoHAB), especially those involving Microcystis, we investigated the diversity and compositions of the cyanobacterial (16S rRNA gene), including the genotypes of Microcystis (cpcBA-IGS gene), non-cyanobacterial (16S), and eukaryotic (18S) communities through high-throughput sequencing. Microcystis blooms were divided into the Summer Major Bloom and Autumn Minor Bloom with different dominant genotypes of Microcystis. Network analysis demonstrated that the modules involved in the different phases of the Microcystis blooms were categorized into the Pre-Bloom, Bloom, Post-Bloom, and Non-Bloom Groups at all sampling stations. In addition, the non-cyanobacterial components of each Group were classified, while the same Group showed similarity across all stations, suggesting that Microcystis and other microbes were highly interdependent and organized into cyanoHAB-related module units. Importantly, the Microcystis genotype-based sub-network uncovered that Pirellula, Pseudanabaena, and Vampirovibrionales preferred to interact with specific Microcystis genotypes in the Summer Major Bloom than with other genotypes in the Autumn Minor Bloom, while the copepod Skistodiaptomus exhibited the opposite pattern. In conclusion, the transition patterns of cyanoHAB-related modules and their key components could be crucial in the succession of Microcystis genotypes and to enhance the understanding of microbial ecology in an aquatic environment.

Microbial communities of the Laurentian Great Lakes reflect connectivity and local biogeochemistry

The Laurentian Great Lakes are a vast, interconnected freshwater system spanning strong physicochemical gradients, thus constituting a powerful natural laboratory for addressing fundamental questions about microbial ecology and evolution. We present a comparative analysis of pelagic microbial communities across all five Laurentian Great Lakes, focusing on Bacterial and Archaeal picoplankton characterized via 16S rRNA amplicon sequencing. We collected samples throughout the water column from the major basins of each lake in spring and summer over 2 years. Two oligotypes, classified as LD12 (Alphaproteobacteria) and acI‐B1 (Actinobacteria), were among the most abundant in every sample. At the same time, microbial communities showed distinct patterns with depth during summer stratification. Deep hypolimnion samples were frequently dominated by a Chloroflexi oligotype that reached up to 19% relative abundance. Stratified surface communities differed between the colder, less productive upper lakes (Superior, Michigan, Huron) and warmer, more productive lower lakes (Erie, Ontario), in part due to an Actinobacteria oligotype (acI‐C2) that averaged 7.7% of sequences in the lower lakes but <0.2% in the upper lakes. Together, our findings suggest that both hydrologic connectivity and local selective pressures shape microbial communities in the Great Lakes and establish a framework for future investigations.

Species abundance information improves sequence taxonomy classification accuracy

Popular naive Bayes taxonomic classifiers for amplicon sequences assume that all species in the reference database are equally likely to be observed. We demonstrate that classification accuracy degrades linearly with the degree to which that assumption is violated, and in practice it is always violated. By incorporating environment-specific taxonomic abundance information, we demonstrate a significant increase in the species-level classification accuracy across common sample types. At the species level, overall average error rates decline from 25% to 14%, which is favourably comparable to the error rates that existing classifiers achieve at the genus level (16%). Our findings indicate that for most practical purposes, the assumption that reference species are equally likely to be observed is untenable. q2-clawback provides a straightforward alternative for samples from common environments.

Taxonomy classification of amplicon sequences is an important step in investigating microbial communities in microbiome analysis. Here, the authors show incorporating environment-specific taxonomic abundance information can lead to improved species-level classification accuracy across common sample types.

Species abundance information improves sequence taxonomy classification accuracy

Popular naive Bayes taxonomic classifiers for amplicon sequences assume that all species in the reference database are equally likely to be observed. We demonstrate that classification accuracy degrades linearly with the degree to which that assumption is violated, and in practice it is always violated. By incorporating environment-specific taxonomic abundance information, we demonstrate a significant increase in the species-level classification accuracy across common sample types. At the species level, overall average error rates decline from 25% to 14%, which is favourably comparable to the error rates that existing classifiers achieve at the genus level (16%). Our findings indicate that for most practical purposes, the assumption that reference species are equally likely to be observed is untenable. q2-clawback provides a straightforward alternative for samples from common environments.

Randomized Lasso Links Microbial Taxa with Aquatic Functional Groups Inferred from Flow Cytometry

A major goal in microbial ecology is to understand how microbial community structure influences ecosystem functioning. Various methods to directly associate bacterial taxa to functional groups in the environment are being developed. In this study, we applied machine learning methods to relate taxonomic data obtained from marker gene surveys to functional groups identified by flow cytometry. This allowed us to identify the taxa that are associated with heterotrophic productivity in freshwater lakes and indicated that the key contributors were highly system specific, regularly rare members of the community, and that some could possibly switch between being low and high contributors. Our approach provides a promising framework to identify taxa that contribute to ecosystem functioning and can be further developed to explore microbial contributions beyond heterotrophic production.

High-nucleic-acid (HNA) and low-nucleic-acid (LNA) bacteria are two operational groups identified by flow cytometry (FCM) in aquatic systems. A number of reports have shown that HNA cell density correlates strongly with heterotrophic production, while LNA cell density does not. However, which taxa are specifically associated with these groups, and by extension, productivity has remained elusive. Here, we addressed this knowledge gap by using a machine learning-based variable selection approach that integrated FCM and 16S rRNA gene sequencing data collected from 14 freshwater lakes spanning a broad range in physicochemical conditions. There was a strong association between bacterial heterotrophic production and HNA absolute cell abundances (R² = 0.65), but not with the more abundant LNA cells. This solidifies findings, mainly from marine systems, that HNA and LNA bacteria could be considered separate functional groups, the former contributing a disproportionately large share of carbon cycling. Taxa selected by the models could predict HNA and LNA absolute cell abundances at all taxonomic levels. Selected operational taxonomic units (OTUs) ranged from low to high relative abundance and were mostly lake system specific (89.5% to 99.2%). A subset of selected OTUs was associated with both LNA and HNA groups (12.5% to 33.3%), suggesting either phenotypic plasticity or within-OTU genetic and physiological heterogeneity. These findings may lead to the identification of system-specific putative ecological indicators for heterotrophic productivity. Generally, our approach allows for the association of OTUs with specific functional groups in diverse ecosystems in order to improve our understanding of (microbial) biodiversity-ecosystem functioning relationships.

IMPORTANCE A major goal in microbial ecology is to understand how microbial community structure influences ecosystem functioning. Various methods to directly associate bacterial taxa to functional groups in the environment are being developed. In this study, we applied machine learning methods to relate taxonomic data obtained from marker gene surveys to functional groups identified by flow cytometry. This allowed us to identify the taxa that are associated with heterotrophic productivity in freshwater lakes and indicated that the key contributors were highly system specific, regularly rare members of the community, and that some could possibly switch between being low and high contributors. Our approach provides a promising framework to identify taxa that contribute to ecosystem functioning and can be further developed to explore microbial contributions beyond heterotrophic production.

Rapid and Stable Microbial Community Assembly in the Headwaters of a Third-Order Stream

Small streams and their headwaters are key sources of microbial diversity in fluvial systems and serve as an entry point for bacteria from surrounding environments. Community assembly processes occurring in these streams shape downstream population structure and nutrient cycles. To elucidate the development and stability of microbial communities along the length of a first- through third-order stream, fine-scale temporal and spatial sampling regimes were employed along McNutt Creek in Athens, GA, USA. 16S rRNA amplicon libraries were constructed from samples collected on a single day from 19 sites spanning the first 16.76 km of the stream. To provide context for this spatial study and evaluate temporal variability, selected sites at the stream's upper, mid, and lower reaches were sampled daily for 5 days preceding and following the spatial study. In a second study, three sites at and near the creek's headwaters were sampled daily for 11 days to understand initial bacterioplankton community assembly. Both studies revealed decreasing alpha and beta diversity with increasing downstream distance. These trends were accompanied by the enrichment of a small fraction of taxa found at low abundance in headwater-proximal sites. Similar sets of taxa consistently increased in relative abundance in downstream samples over time scales ranging from 1 day to 1 year, many of which belong to clades known to be abundant in freshwater environments. These results underpin the importance of headwaters as the site of rapid in-stream selection that results in the reproducible establishment of a highly stable community of freshwater riverine bacteria.IMPORTANCE Headwater streams are critical introduction points of microbial diversity for larger connecting rivers and play key roles in the establishment of taxa that partake in in-stream nutrient cycling. We examined the microbial community composition of a first- through third-order stream using fine-scale temporal and spatial regimes. Our results show that the bacterioplankton community develops rapidly and predictably from the headwater population with increasing total stream length. Along the length of the stream, the microbial community exhibits substantial diversity loss and enriches repeatedly for select taxa across days and years, although the relative abundances of individual taxa vary over time and space. This repeated enrichment of a stable stream community likely contributes to the stability and flexibility of downstream communities.

Improved taxonomic assignment of rumen bacterial 16S rRNA sequences using a revised SILVA taxonomic framework

The taxonomy and associated nomenclature of many taxa of rumen bacteria are poorly defined within databases of 16S rRNA genes. This lack of resolution results in inadequate definition of microbial community structures, with large parts of the community designated as incertae sedis, unclassified, or uncultured within families, orders, or even classes. We have begun resolving these poorly-defined groups of rumen bacteria, based on our desire to name these for use in microbial community profiling. We used the previously-reported global rumen census (GRC) dataset consisting of >4.5 million partial bacterial 16S rRNA gene sequences amplified from 684 rumen samples and representing a wide range of animal hosts and diets. Representative sequences from the 8,985 largest operational units (groups of sequence sharing >97% sequence similarity, and covering 97.8% of all sequences in the GRC dataset) were used to identify 241 pre-defined clusters (mainly at genus or family level) of abundant rumen bacteria in the ARB SILVA 119 framework. A total of 99 of these clusters (containing 63.8% of all GRC sequences) had no unique or had inadequate taxonomic identifiers, and each was given a unique nomenclature. We assessed this improved framework by comparing taxonomic assignments of bacterial 16S rRNA gene sequence data in the GRC dataset with those made using the original SILVA 119 framework, and three other frameworks. The two SILVA frameworks performed best at assigning sequences to genus-level taxa. The SILVA 119 framework allowed 55.4% of the sequence data to be assigned to 751 uniquely identifiable genus-level groups. The improved framework increased this to 87.1% of all sequences being assigned to one of 871 uniquely identifiable genus-level groups. The new designations were included in the SILVA 123 release (https://www.arb-silva.de/documentation/release-123/) and will be perpetuated in future releases.

Gene Expansion and Positive Selection as Bacterial Adaptations to Oligotrophic Conditions

By combining a genome-centric metagenomic approach with a culture-based approach, we investigated the genomic adaptations of prevalent populations in an engineered oligotrophic freshwater system. We found evidence for widespread positive selection on genes involved in phosphorus and carbon scavenging pathways and for gene expansions in motility and environmental sensing to be important genomic adaptations of the abundant taxon in this system. In addition, microscopic and flow cytometric analysis of the first freshwater representative of this population (Ramlibacter aquaticus LMG 30558^T) demonstrated phenotypic plasticity, possibly due to the metabolic versatility granted by its larger genome, to be a strategy to cope with nutrient limitation. Our study clearly demonstrates the need for the use of a broad set of genomic tools combined with culture-based physiological characterization assays to investigate and validate genomic adaptations.

We examined the genomic adaptations of prevalent bacterial taxa in a highly nutrient- and ion-depleted freshwater environment located in the secondary cooling water system of a nuclear research reactor. Using genome-centric metagenomics, we found that none of the prevalent bacterial taxa were related to typical freshwater bacterial lineages. We also did not identify strong signatures of genome streamlining, which has been shown to be one of the ecoevolutionary forces shaping the genome characteristics of bacterial taxa in nutrient-depleted environments. Instead, focusing on the dominant taxon, a novel Ramlibacter sp. which we propose to name Ramlibacter aquaticus, we detected extensive positive selection on genes involved in phosphorus and carbon scavenging pathways. These genes were involved in the high-affinity phosphate uptake and storage into polyphosphate granules, metabolism of nitrogen-rich organic matter, and carbon/energy storage into polyhydroxyalkanoate. In parallel, comparative genomics revealed a high number of paralogs and an accessory genome significantly enriched in environmental sensing pathways (i.e., chemotaxis and motility), suggesting extensive gene expansions in R. aquaticus. The type strain of R. aquaticus (LMG 30558^T) displayed optimal growth kinetics and productivity at low nutrient concentrations, as well as substantial cell size plasticity. Our findings with R. aquaticus LMG 30558^T demonstrate that positive selection and gene expansions may represent successful adaptive strategies to oligotrophic environments that preserve high growth rates and cellular productivity.

IMPORTANCE By combining a genome-centric metagenomic approach with a culture-based approach, we investigated the genomic adaptations of prevalent populations in an engineered oligotrophic freshwater system. We found evidence for widespread positive selection on genes involved in phosphorus and carbon scavenging pathways and for gene expansions in motility and environmental sensing to be important genomic adaptations of the abundant taxon in this system. In addition, microscopic and flow cytometric analysis of the first freshwater representative of this population (Ramlibacter aquaticus LMG 30558^T) demonstrated phenotypic plasticity, possibly due to the metabolic versatility granted by its larger genome, to be a strategy to cope with nutrient limitation. Our study clearly demonstrates the need for the use of a broad set of genomic tools combined with culture-based physiological characterization assays to investigate and validate genomic adaptations.

Freshwater carbon and nutrient cycles revealed through reconstructed population genomes

Although microbes mediate much of the biogeochemical cycling in freshwater, the categories of carbon and nutrients currently used in models of freshwater biogeochemical cycling are too broad to be relevant on a microbial scale. One way to improve these models is to incorporate microbial data. Here, we analyze both genes and genomes from three metagenomic time series and propose specific roles for microbial taxa in freshwater biogeochemical cycles. Our metagenomic time series span multiple years and originate from a eutrophic lake (Lake Mendota) and a humic lake (Trout Bog Lake) with contrasting water chemistry. Our analysis highlights the role of polyamines in the nitrogen cycle, the diversity of diazotrophs between lake types, the balance of assimilatory vs. dissimilatory sulfate reduction in freshwater, the various associations between types of phototrophy and carbon fixation, and the density and diversity of glycoside hydrolases in freshwater microbes. We also investigated aspects of central metabolism such as hydrogen metabolism, oxidative phosphorylation, methylotrophy, and sugar degradation. Finally, by analyzing the dynamics over time in nitrogen fixation genes and Cyanobacteria genomes, we show that the potential for nitrogen fixation is linked to specific populations in Lake Mendota. This work represents an important step towards incorporating microbial data into ecosystem models and provides a better understanding of how microbes may participate in freshwater biogeochemical cycling.

IDTAXA: a novel approach for accurate taxonomic classification of microbiome sequences

BACKGROUND

Microbiome studies often involve sequencing a marker gene to identify the microorganisms in samples of interest. Sequence classification is a critical component of this process, whereby sequences are assigned to a reference taxonomy containing known sequence representatives of many microbial groups. Previous studies have shown that existing classification programs often assign sequences to reference groups even if they belong to novel taxonomic groups that are absent from the reference taxonomy. This high rate of "over classification" is particularly detrimental in microbiome studies because reference taxonomies are far from comprehensive.

RESULTS

Here, we introduce IDTAXA, a novel approach to taxonomic classification that employs principles from machine learning to reduce over classification errors. Using multiple reference taxonomies, we demonstrate that IDTAXA has higher accuracy than popular classifiers such as BLAST, MAPSeq, QIIME, SINTAX, SPINGO, and the RDP Classifier. Similarly, IDTAXA yields far fewer over classifications on Illumina mock microbial community data when the expected taxa are absent from the training set. Furthermore, IDTAXA offers many practical advantages over other classifiers, such as maintaining low error rates across varying input sequence lengths and withholding classifications from input sequences composed of random nucleotides or repeats.

CONCLUSIONS

IDTAXA's classifications may lead to different conclusions in microbiome studies because of the substantially reduced number of taxa that are incorrectly identified through over classification. Although misclassification error is relatively minor, we believe that many remaining misclassifications are likely caused by errors in the reference taxonomy. We describe how IDTAXA is able to identify many putative mislabeling errors in reference taxonomies, enabling training sets to be automatically corrected by eliminating spurious sequences. IDTAXA is part of the DECIPHER package for the R programming language, available through the Bioconductor repository or accessible online ( http://DECIPHER.codes ).