Toward Characterizing Environmental Sources of Non-tuberculous Mycobacteria (NTM) at the Species Level: A Tutorial Review of NTM Phylogeny and Phylogenetic Classification.

Nontuberculous mycobacteria (NTM) are any mycobacteria that do not cause tuberculosis or leprosy. While the majority of NTM are harmless and some of them are considered probiotic, a growing number of people are being diagnosed with NTM infections. Therefore, their detection in the environment is of interest to clinicians, environmental microbiologists, and water quality researchers alike. This review provides a tutorial on the foundational approaches for taxonomic classifications, with a focus on the phylogenetic relationships among NTM revealed by the 16S rRNA gene, rpoB gene, and hsp65 gene, and by genome-based approaches. Recent updates on the Mycobacterium genus taxonomy are also provided. A synthesis on the habitats of 189 mycobacterial species in a genome-based taxonomy framework was performed, with attention paid to environmental sources (e.g., drinking water, aquatic environments, and soil). The 16S rRNA gene-based classification accuracy for various regions was evaluated (V3, V3-V4, V3-V5, V4, V4-V5, and V1-V9), revealing overall excellent genus-level classification (up to 100% accuracy) yet only modest performance (up to 63.5% accuracy) at the species level. Future research quantifying NTM species in water systems, determining the effects of water treatment and plumbing conditions on their variations, developing high throughput species-level characterization tools for use in the environment, and incorporating the characterization of functions in a phylogenetic framework will likely fill critical knowledge gaps. We believe this tutorial will be useful for researchers new to the field of molecular or genome-based taxonomic profiling of environmental microbiomes. Experts may also find this review useful in terms of the selected key findings of the past 30 years, recent updates on phylogenomic analyses, as well as a synthesis of the ecology of NTM in a phylogenetic framework.

Validation of 16S rRNA gene sequencing and metagenomics for evaluating microbial immigration in a methanogenic bioreactor.

To quantitatively evaluate the impact of microbial immigration from an upstream community on the microbial assembly of a downstream community, an ecological genomics (ecogenomics)-based mass balance (EGMB) model coupled with 16S rRNA gene sequencing was previously developed. In this study, a mock community was used to further validate the EGMB models and demonstrate the feasibility of using metagenome-based EGMB model to reveal both microbial activity and function. The mock community consisting of Aeromonas, Escherichia, and Pseudomonas was fed into a lab-scale methanogenic bioreactor together with dissolved organic substrate. Using qPCR, 16S rRNA gene, 16S rRNA gene copy number normalization (GCN), and metagenome, results showed highly comparable community profiles in the feed. In the bioreactor, Aeromonas and Pseudomonas exhibited negative growth rates throughout the experiment by all approaches. Escherichia's growth rate was negative by most biomarkers but was slightly positive by 16S rRNA gene. Still, all approaches showed a decreasing trend toward negative in the growth rate of Escherichia as reactor operation time increased. Uncultivated populations of phyla Desulfobacterota, Chloroflexi, Actinobacteriota, and Spirochaetota were observed to increase in abundance, suggesting their contribution in degrading the feed biomass. Based on metabolic reconstruction of metagenomes, these populations possessed functions of hydrolysis, fermentation, fatty acid degradation, or acetate oxidation. Overall results supported the application of both 16S rRNA gene- and metagenome-based EGMB models to measure the growth rate of microbes in the bioreactor, and the latter had advantage in providing insights into the microbial functions of uncultivated populations.

Impact of salinity origin on microbial communities in saline springs within the Illinois Basin, USA.

Saline springs within the Illinois Basin result from the discharge of deep-seated evaporated seawater (brine) and likely contain diverse and complex microbial communities that are poorly understood. In this study, seven saline/mineral springs with different geochemical characteristics and salinity origins were investigated using geochemical and molecular microbiological analyses to reveal the composition of microbial communities inhabiting springs and their key controlling factors. The 16S rRNA sequencing results demonstrated that each spring harbours a unique microbial community influenced by its geochemical properties and subsurface conditions. The microbial communities in springs that originated from Cambrian/Ordovician strata, which are deep confined units that have limited recharge from overlying formations, share a greater similarity in community composition and have a higher species richness and more overlapped taxa than those that originated from shallower Pennsylvanian strata, which are subject to extensive regional surface and groundwater recharge. The microbial distribution along the spring flow paths at the surface indicates that 59.8%-94.2% of total sequences in sedimentary samples originated from spring water, highlighting the role of springs in influencing microbiota in the immediate terrestrial environment. The results indicate that the springs introduce microbiota with a high biodiversity into surface terrestrial or aquatic ecosystems, potentially affecting microbial reservoirs in downstream ecosystems.

Meta-Omics-Supervised Characterization of Respiration Activities Associated with Microbial Immigrants in Anaerobic Sludge Digesters.

Immigration has been recently recognized as an important ecological process that affects the microbial community structure in diverse ecosystems. However, the fate of microbial immigrants in the new environment and their involvement in the local biochemical network remain unclear. In this study, we performed meta-omics-supervised characterization of immigrants' activities in anaerobic sludge digesters. Metagenomic analyses revealed that immigrants from the feed sludge accounted for the majority of populations capable of anaerobic respiration in a digester. Electron acceptors that were predicted to be respired, including nitrate, nitrite, sulfate, and elemental sulfur, were added to digester sludge in batch tests. Consumption of up to 91% of the added electron acceptors was observed within the experiment period. 16S rRNA sequencing detected populations that were stimulated by the electron acceptors, largely overlapping with respiration-capable immigrants identified by metagenomic analysis. Metatranscriptomic analysis of the batch tests provided additional evidence for upregulated expression of respiration genes and concomitant suppressed expression of methanogenesis. Anaerobic respiration activity was further evaluated in full-scale digesters in nine wastewater treatment plants. Although nitrate and sulfate respiration were ubiquitous, the expression level of respiration genes was generally 2-3 orders of magnitude lower than the expression of methanogenesis in most digesters, suggesting marginal ecological roles by immigrants in full-scale digester ecosystems.

Relative Importance of Stochastic Assembly Process of Membrane Biofilm Increased as Biofilm Aged.

The relative importance of different ecological processes controlling biofilm community assembly over time on membranes with different surface characteristics has never been investigated in membrane bioreactors (MBRs). In this study, five ultrafiltration hollow-fiber membranes - having identical nominal pore size (0.1µm) but different hydrophobic or hydrophilic surface characteristics - were operated simultaneously in the same MBR tank with a constant flux of 10 liters per square meter per hour (LMH). In parallel, membrane modules operated without permeate flux (0 LMH) were submerged in the same MBR tank, to investigate the passive microbial adsorption onto different hydrophobic or hydrophilic membranes. Samples from the membrane biofilm were collected after 1, 10, 20, and 30days of continuous filtration. The membrane biofilm microbiome were investigated using 16S rRNA gene amplicon sequencing from DNA and cDNA samples. Similar beta diversity trends were observed for both DNA- and cDNA-based analyses. Beta diversity analyses revealed that the nature of the membrane surface (i.e., hydrophobic vs. hydrophilic) did not seem to have an effect in shaping the bacterial community, and a similar biofilm microbiome evolved for all types of membranes. Similarly, membrane modules operated with and without permeate flux did not significantly influence alpha and beta diversity of the membrane biofilm. Nevertheless, different-aged membrane biofilm samples exhibited significant differences. Proteobacteria was the most dominant phylum in early-stage membrane biofilm after 1 and 10days of filtration. Subsequently, the relative reads abundance of the phyla Bacteroidetes and Firmicutes increased within the membrane biofilm communities after 20 and 30days of filtration, possibly due to successional steps that lead to the formation of a relatively aged biofilm. Our findings indicate distinct membrane biofilm assembly patterns with different-aged biofilm. Ecological null model analyses revealed that the assembly of early-stage biofilm community developed after 1 and 10days of filtration was mainly governed by homogenous selection. As the biofilm aged (days 20 and 30), stochastic processes (e.g., ecological drift) started to become important in shaping the assembly of biofilm community.

Disentangling the syntrophic electron transfer mechanisms of Candidatus geobacter eutrophica through electrochemical stimulation and machine learning.

Interspecies hydrogen transfer (IHT) and direct interspecies electron transfer (DIET) are two syntrophy models for methanogenesis. Their relative importance in methanogenic environments is still unclear. Our recent discovery of a novel species Candidatus Geobacter eutrophica with the genetic potential of IHT and DIET may serve as a model species to address this knowledge gap. To experimentally demonstrate its DIET ability, we performed electrochemical enrichment of Ca. G. eutrophica-dominating communities under 0 and 0.4 V vs. Ag/AgCl based on the presumption that DIET and extracellular electron transfer (EET) share similar metabolic pathways. After three batches of enrichment, Geobacter OTU650, which was phylogenetically close to Ca. G. eutrophica, was outcompeted in the control but remained abundant and active under electrochemical stimulation, indicating Ca. G. eutrophica's EET ability. The high-quality draft genome further showed high phylogenomic similarity with Ca. G. eutrophica, and the genes encoding outer membrane cytochromes and enzymes for hydrogen metabolism were actively expressed. A Bayesian network was trained with the genes encoding enzymes for alcohol metabolism, hydrogen metabolism, EET, and methanogenesis from dominant fermentative bacteria, Geobacter, and Methanobacterium. Methane production could not be accurately predicted when the genes for IHT were in silico knocked out, inferring its more important role in methanogenesis. The genomics-enabled machine learning modeling approach can provide predictive insights into the importance of IHT and DIET.

Ecology and molecular targets of hypermutation in the global microbiome.

Changes in the sequence of an organism's genome, i.e., mutations, are the raw material of evolution. The frequency and location of mutations can be constrained by specific molecular mechanisms, such as diversity-generating retroelements (DGRs). DGRs have been characterized from cultivated bacteria and bacteriophages, and perform error-prone reverse transcription leading to mutations being introduced in specific target genes. DGR loci were also identified in several metagenomes, but the ecological roles and evolutionary drivers of these DGRs remain poorly understood. Here, we analyze a dataset of >30,000 DGRs from public metagenomes, establish six major lineages of DGRs including three primarily encoded by phages and seemingly used to diversify host attachment proteins, and demonstrate that DGRs are broadly active and responsible for >10% of all amino acid changes in some organisms. Overall, these results highlight the constraints under which DGRs evolve, and elucidate several distinct roles these elements play in natural communities.

Ecogenomics-Based Mass Balance Model Reveals the Effects of Fermentation Conditions on Microbial Activity.

Fermentation of waste activated sludge (WAS) is an alternative approach to reduce solid wastes while providing valuable soluble products, such as volatile fatty acids and alcohols. This study systematically identified optimal fermentation conditions and key microbial populations by conducting two sets of experiments under different combinations of biochemical and physical parameters. Based on fermentation product concentrations, methane production, and solid removal, fermentation performance was enhanced under the combined treatments of inoculum heat shock (>60°C), pH 5, 55°C, and short solid retention time (<10 days). An ecogenomics-based mass balance (EGMB) approach was used to determine the net growth rates of individual microbial populations, and classified them into four microbial groups: known syntrophs, known methanogens, fermenters, and WAS-associated populations. Their growth rates were observed to be affected by the treatment conditions. The growth rates of syntrophs and fermenters, such as Syntrophomonas and Parabacteroides increased with a decrease in SRT. In contrast, treatment conditions, such as inoculum heat shock and high incubation temperature inhibited the growth of WAS-associated populations, such as Terrimonas and Bryobacter. There were also populations insensitive to the treatment conditions, such as those related to Microbacter and Rikenellaceae. Overall, the EGMB approach clearly revealed the ecological roles of important microbial guilds in the WAS fermentation system, and guided the selection of optimal conditions for WAS fermentation in future pilot-scale operation.

Metagenomic and Metatranscriptomic Analyses Revealed Uncultured Bacteroidales Populations as the Dominant Proteolytic Amino Acid Degraders in Anaerobic Digesters.

Current understanding of amino acid (AA) degraders in anaerobic digesters is mainly based on cultured species, whereas microorganisms that play important roles in a complex microbial community remain poorly characterized. This study investigated short-term enrichments degrading single AAs using metagenomics and metatranscriptomics. Metagenomic analysis revealed that populations related to cultured AA degraders had an abundance <2.5% of the sequences. In contrast, metagenomic-assembled bins related to uncultured Bacteroidales collectively accounted for >35% of the sequences. Phylogenetic analyses suggested that these Bacteroidales populations represented a yet-to-be characterized family lineage, i.e., Bacteroidetes vadinHA17. The bins possessed the genetic capacity related to protein degradation, including surface adhesion (3-7 genes), secreted peptidase (52-77 genes), and polypeptide-specific transporters (2-5 genes). Furthermore, metatranscriptomics revealed that these Bacteroidales populations expressed the complete metabolic pathways for degrading 16 to 17 types of AAs in enrichments fed with respective substrates. These characteristics were distinct from cultured AA degraders including Acidaminobacter and Peptoclostridium, suggesting the uncultured Bacteroidales were the major protein-hydrolyzing and AA-degrading populations. These uncultured Bacteroidales were further found to be dominant and active in full-scale anaerobic digesters, indicating their important ecological roles in the native habitats. "Candidatus Aminobacteroidaceae" was proposed to represent the previously uncharted family Bacteroidetes vadinHA17.

Catabolism and interactions of uncultured organisms shaped by eco-thermodynamics in methanogenic bioprocesses.

BACKGROUND: Current understanding of the carbon cycle in methanogenic environments involves trophic interactions such as interspecies H2 transfer between organotrophs and methanogens. However, many metabolic processes are thermodynamically sensitive to H2 accumulation and can be inhibited by H2 produced from co-occurring metabolisms. Strategies for driving thermodynamically competing metabolisms in methanogenic environments remain unexplored. RESULTS: To uncover how anaerobes combat this H2 conflict in situ, we employ metagenomics and metatranscriptomics to revisit a model ecosystem that has inspired many foundational discoveries in anaerobic ecology-methanogenic bioreactors. Through analysis of 17 anaerobic digesters, we recovered 1343 high-quality metagenome-assembled genomes and corresponding gene expression profiles for uncultured lineages spanning 66 phyla and reconstructed their metabolic capacities. We discovered that diverse uncultured populations can drive H2-sensitive metabolisms through (i) metabolic coupling with concurrent H2-tolerant catabolism, (ii) forgoing H2 generation in favor of interspecies transfer of formate and electrons (cytochrome- and pili-mediated) to avoid thermodynamic conflict, and (iii) integration of low-concentration O2 metabolism as an ancillary thermodynamics-enhancing electron sink. Archaeal populations support these processes through unique methanogenic metabolisms-highly favorable H2 oxidation driven by methyl-reducing methanogenesis and tripartite uptake of formate, electrons, and acetate. CONCLUSION: Integration of omics and eco-thermodynamics revealed overlooked behavior and interactions of uncultured organisms, including coupling favorable and unfavorable metabolisms, shifting from H2 to formate transfer, respiring low-concentration O2, performing direct interspecies electron transfer, and interacting with high H2-affinity methanogenesis. These findings shed light on how microorganisms overcome a critical obstacle in methanogenic carbon cycles we had hitherto disregarded and provide foundational insight into anaerobic microbial ecology. Video Abstract.

Superior resolution characterisation of microbial diversity in anaerobic digesters using full-length 16S rRNA gene amplicon sequencing.

In the past decade, the characterisation of the microbial community in anaerobic digestion was primarily done by using high-throughput short-read amplicon sequencing. However, the short-read approach has inherent primer bias and low phylogenetic resolution. Our previous study using Illumina MiSeq suggested that the heterogeneity of AD microbiome was operation-driven. To advance our knowledge towards the complexity of the AD microbiome, we performed full-length 16S rRNA gene amplicon sequencing using PacBio Sequel for a more accurate phylogenetic identification. To this end, purified DNA samples from 19 global anaerobic digesters were sequenced. Sixteen methanogenic archaea were identified at the species level. Among them, Methanosarcina horonobensis and Methanosarcina flavescens had significant presence under specific operating conditions. Methanothrix concilii presented in all digesters sequenced. Unexpectedly, over 90% of the Smithella detected were closely related to alkane-degrading Smithella strains D17 and M82, not Smithella propionica. Using LEfSe and network analysis, the interspecies relationship between the fermentative and syntrophic bacteria was addressed. Comparison of the short- and long-read sequencing results were performed and discussed. From sample preparation to data analysis, this work characterised the digester microbiomes in a superior resolution.

360-Degree Distribution of Biofilm Quantity and Community in an Operational Unchlorinated Drinking Water Distribution Pipe.

In the present study, triplicate rings of 360° pipe surfaces of an operational drinking water distribution pipe were swabbed. Each ring was equally divided into 16 parts for swabbing. The collected swabs were grouped into 3 sections and compared with the biofilm samples sampled by sonication of specimens from the same pipe. The results showed that the biofilm is unevenly distributed over the 16 parts and the 3 sections of the pipe surface. Both the active biomass and the number of observed OTUs increased as the measurements proceeded from the top to the bottom of the pipe. The bacterial community was dominated in all sections by Proteobacteria. At the genus level, Nitrospira spp., Terrimonas spp., and Hyphomicrobium spp. were dominant in all sections. Gaiella spp. and Vicinamibacter spp. dominated in S-I, Blastopirellula spp. and Pirellula spp. dominated in S-II, while Holophaga spp. and Phaeodactylibacter spp. dominated in S-III. When swabbing and pipe specimen sonication were compared, the results showed that the sampling strategy significantly influences the obtained biofilm bacterial community. A consistent multisectional swabbing strategy is proposed for future biofilm sampling; it involves collecting swabs from all sections and comparing the swabs from the same position/section across locations.

Machine learning-aided analyses of thousands of draft genomes reveal specific features of activated sludge processes.

BACKGROUND: Microorganisms in activated sludge (AS) play key roles in the wastewater treatment processes. However, their ecological behaviors and differences from microorganisms in other environments have mainly been studied using the 16S rRNA gene that may not truly represent in situ functions. RESULTS: Here, we present 2045 archaeal and bacterial metagenome-assembled genomes (MAGs) recovered from 1.35 Tb of metagenomic data generated from 114 AS samples of 23 full-scale wastewater treatment plants (WWTPs). We found that the AS MAGs have obvious plant-specific features and that few proteins are shared by different WWTPs, especially for WWTPs located in geographically distant areas. Further, we developed a novel machine learning approach that can distinguish between AS MAGs and MAGs from other environments based on the clusters of orthologous groups of proteins with an accuracy of 96%. With the aid of machine learning, we also identified some functional features (e.g., functions related to aerobic metabolism, nutrient sensing/acquisition, and biofilm formation) that are likely vital for AS bacteria to adapt themselves in wastewater treatment bioreactors. CONCLUSIONS: Our work reveals that, although the bacterial species in different municipal WWTPs could be different, they may have similar deterministic functional features that allow them to adapt to the AS systems. Also, we provide valuable genome resources and a novel approach for future investigation and better understanding of the microbiome of AS and other ecosystems. Video Abtract.

Identifying anaerobic amino acids degraders through the comparison of short-term and long-term enrichments.

Degradation of amino acids is an important process in methanogenic environments. Early studies in the 1980s focused on isolated clostridia species to study the degradation behaviours. However, it is now well-recognized that isolated species may not represent those with important roles in situ. This study conducted a continuous enrichment experiment with focus on the comparison of the microbial communities after short-term enrichment (SE) and long-term enrichment (LE). Individual amino acids were used as the substrate, and two different anaerobic digester sludge were used as the inoculum. Based on 16S rRNA and 16S rRNA gene, a clear community shift was observed during a time course of 18 months. The SE communities were dominated by microbial populations such as an uncultured Bacteroidales that was different from known fermenters. In the LE communities, known amino acids fermenters were consistently observed with high abundance, including Peptoclostridium acidaminophilum, Acidaminobacter hydrogenoformans and Propionivibrio pelophilus. The community structures could be classified into four types depending on the diversity of fermenters and syntrophs. A culturability index was developed to compare the SE and LE community and revealed that long-term enrichment tended to select microbial populations closely related to species that has been cultivated whereas larger fractions of the inoculum and SE communities remained uncultured.

Bacterial enrichment in highly-selective acetate-fed bioreactors and its application in rapid biofilm formation.

In this study, we systematically investigated the bacterial community dynamics in highly-selective (strong hydraulic selection pressure and high organic loading rate) bioreactors with acetate as the sole carbon source. 16S rRNA gene high-throughput sequencing and metagenomic sequencing results showed that phenolics-degrading bacteria (PDB), which were mainly Acinetobacter species, in the newly-formed aerobic granules could account for >70% of the total bacteria. Near full-length 16S rRNA gene sequences obtained by cloning suggest that the PDB are potentially novel species because they are distantly related to known Acinetobacter species. However, these PDB only temporarily appeared in the early stage of the granule formation and their abundance quickly decreased along the reactor operation. To retain these PDB, we demonstrated that the newly-formed aerobic granules could accelerate biofilm formation in moving bed biofilm reactors (MBBRs), and the biofilm carriers showed gradually-increased phenol degradation performance in the MBBRs. While, the bacterial community in biofilm significantly changed during the operation process of the MBBRs and the community structure became more complicated than that in the aerobic granules. Collectively, this study provides new insights into the microbial ecology of sludge granulation and biofilm formation process in the wastewater treatment systems for remediating phenolic matters.

Assessing the transition effects in a drinking water distribution system caused by changing supply water quality: an indirect approach by characterizing suspended solids.

Worldwide, it is common that the drinking water distribution systems (DWDSs) may be subjected to changes of supply water quality due to the needs of upgrading the treatment processes or switching the source water. However, the potential impacts of quality changed supply water on the stabilized ecological niches within DWDSs and the associated water quality deterioration risks were poorly documented. In the present study, such transition effects caused by changing the supply water quality that resulted from destabilization of biofilm and loose deposits in DWDS were investigated by analyzing the physiochemical and microbiological characteristics of suspended particles before (T0), during (T3-weeks) and after upgrading the treatments (T6-months) in an unchlorinated DWDS in the Netherlands. Our results demonstrated that after 6 months' time the upgraded treatments significantly improved the water quality. Remarkably, water quality deterioration was observed at the initial stage when the quality-improved treated water distributed into the network at T3-weeks, observed as a spike of total suspended solids (TSS, 50-260%), active biomass (ATP, 95-230%) and inorganic elements (e.g. Mn, 130-250%). Furthermore, pyrosequencing results revealed sharp differences in microbial community composition and structure for the bacteria associated with suspended particles between T0 and T3-weeks, which re-stabilized after 6 months at T6-months. The successful capture of transition effects was especially confirmed by the domination of Nitrospira spp. and Polaromonas spp. in the distribution system at T3-weeks, which were detected at rather low relative abundance at treatment plant. Though the transitional effects were captured, this study shows that the introduction of softening and additional filtration did not have an effect on the water quality for the consumer which improved considerably after 6-months' period. The methodology of monitoring suspended particles with MuPFiSs and additional analysis is capable of detecting transitional effects by monitoring the dynamics of suspended particles and its physiochemical and microbiological composition.

Quantifying the contribution of microbial immigration in engineered water systems.

Immigration is a process that can influence the assembly of microbial communities in natural and engineered environments. However, it remains challenging to quantitatively evaluate the contribution of this process to the microbial diversity and function in the receiving ecosystems. Currently used methods, i.e., counting shared microbial species, microbial source tracking, and neutral community model, rely on abundance profile to reveal the extent of overlapping between the upstream and downstream communities. Thus, they cannot suggest the quantitative contribution of immigrants to the downstream community function because activities of individual immigrants are not considered after entering the receiving environment. This limitation can be overcome by using an approach that couples a mass balance model with high-throughput DNA sequencing, i.e., ecogenomics-based mass balance. It calculates the net growth rate of individual microbial immigrants and partitions the entire community into active populations that contribute to the community function and inactive ones that carry minimal function. Linking activities of immigrants to their abundance further provides quantification of the contribution from an upstream environment to the downstream community. Considering only active populations can improve the accuracy of identifying key environmental parameters dictating process performance using methods such as machine learning.

Diversity and geochemical community assembly processes of the living rare biosphere in a sand-and-gravel aquifer ecosystem in the Midwestern United States.

Natural microbial communities consist of a limited number of abundant species and an extraordinarily diverse population of rare species referred to as the rare biosphere. Recent studies have revealed that the rare biosphere is not merely an inactive dormant population but may play substantial functional roles in the ecosystem. However, structure, activity and community assembly processes of the rare biosphere are poorly understood. In this study, we evaluated the present and living microbial community structures including rare populations in an aquifer ecosystem, the Mahomet Aquifer, USA, by both 16S rDNA and rRNA amplicon deep sequencing. The 13 groundwater samples formed three distinct groups based on the "entire" community structure, and the same grouping was obtained when focusing on the "rare" subcommunities (<0.1% of total abundance), while the "abundant" subcommunities (>1.0%) gave a different grouping. In the correlation analyses, the observed grouping pattern is associated with several geochemical factors, and structures of not only the entire community but also the rare subcommunity are correlated with geochemical profiles in the aquifer ecosystem. Our findings first indicate that the living rare biosphere in the aquifer system has the metabolic potential to adapt to local geochemical factors which dictate the community assembly processes.

Nexus of Stochastic and Deterministic Processes on Microbial Community Assembly in Biological Systems.

Microbial community assembly in engineered biological systems is often simultaneously influenced by stochastic and deterministic processes, and the nexus of these two mechanisms remains to be further investigated. Here, three lab-scale activated sludge reactors were seeded with identical inoculum and operated in parallel under eight different sludge retention time (SRT) by sequentially reducing the SRT from 15 days to 1 day. Using 16S rRNA gene amplicon sequencing data, the microbial populations at the start-up (15-day SRT) and SRT-driven (≤10-day SRT) phases were observed to be noticeably different. Clustering results demonstrated ecological succession at the start-up phase with no consistent successional steps among the three reactors, suggesting that stochastic processes played an important role in the community assembly during primary succession. At the SRT-driven phase, the three reactors shared 31 core operational taxonomic units (OTUs). Putative primary acetate utilizers and secondary metabolizers were proposed based on K-means clustering, network and synchrony analysis. The shared core populations accounted for 65% of the total abundance, indicating that the microbial communities at the SRT-driven phase were shaped predominantly by deterministic processes. Sloan's Neutral model and a null model analysis were performed to disentangle and quantify the relative influence of stochastic and deterministic processes on community assembly. The increased estimated migration rate in the neutral community model and the higher percentage of stochasticity in the null model implied that stochastic community assembly was intensified by strong deterministic factors. This was confirmed by the significantly different α- and ß-diversity indices at SRTs shorter than 2 days and the observation that over half of the core OTUs were unshared or unsynchronized. Overall, this study provided quantitative insights into the nexus of stochastic and deterministic processes on microbial community assembly in a biological process.

Drinking Water Microbiome Project: Is it Time?

Now is an opportune time to foster collaborations across sectors and geographical boundaries to enable development of best practices for drinking water (DW) microbiome research, focusing on accuracy and reproducibility of meta-omic techniques (while learning from past microbiome projects). A large-scale coordinated effort that builds on this foundation will enable the urgently needed comprehensive spatiotemporal understanding and control of DW microbiomes by engineering interventions to protect public health. This opinion paper highlights the need to initiate and conduct a large-scale coordinated DW microbiome project by addressing key knowledge gaps and recommends a roadmap for this effort.