The spinal cord, a nexus for brain-body crosstalk, controls gut physiology and microbial homeostasis, but the underlying mechanisms remain unclear. Using genome-resolved longitudinal metagenomics in male and female C57BL/6 mice before and up to 6 months after disrupting the spinal cord-gut axis, we reconstructed over 6,500 microbial draft genomes. This "Mouse B6 Gut Catalog" improved or doubled species- and strain-level representation in other published catalogs. Impaired spinal cord-gut crosstalk induced persistent, sex-, time- and lesion-specific alterations in community composition, marked by a consistent loss of Lactobacillus johnsonii . Feeding this key bacterium to mice with a clinically relevant spinal cord injury improved host health. Genome-resolved, community-contextualized metabolic profiling revealed that shifts in carbohydrate- mediated microbe-microbe interactions explain the reduction of L. johnsonii . These findings identify carbohydrate metabolism as a keystone mechanism shaping gut microbiota and emphasize that mammalian health and gut ecosystem function depend on a functional spinal cord-gut axis. Additionally, these data improve murine microbiome catalogs and demonstrate that metagenome-informed microbial interventions can improve host health and likely mitigate long-term dysbiosis.

Arctic permafrosts are rapidly thawing in response to climate change, stimulating microbial activity and release of additional greenhouse gases, such as methane. Recently, catechin amendment of thawed permafrost soil microcosms demonstrated >80% decrease in methane production over 35 days compared to unamended controls, with metagenome, metatranscriptome and metabolome analyses revealing a shift in prokaryotic carbon metabolism from a syntrophic network feeding methanogens to one dominated by catechin fermentation. Here we leverage these same data to investigate potential virus impacts on this microbial community metabolism shift. In total, 900 DNA virus operational taxonomic units (vOTUs) were identified as actively lytic based on transcribed structural and lysis genes. Of these, 41% were predicted to infect at least one of 56 transcriptionally active prokaryote genera representing 13 phyla. The most active vOTUs were predicted to infect key catechin-degrading genera including Clostridium and undescribed Bacillota genus JAGFXR01. Temporally, viral communities responded later than prokaryotes to catechin amendment, reflecting a virus production lag to targeting key microbial responders. An induced prophage represented by a vOTU predicted to infect JAGFXR01 dominated the catechin-amended viral community response. It reached abundances 20-156 times higher than its host, suggesting intense viral lysis that could release degraded catechin intermediates. Indeed, catechin intermediate gene expression in non-catechin-degraders were elevated in catechin-amended samples, suggesting JAGFXR01 lysis products were taken up by non-catechin-degraders as part of community carbon metabolism rewiring. Together, these results potentially place viruses at the heart of carbon rewiring that modulates ecosystem outputs of climate-critical thawing permafrosts. ### Competing Interest Statement The authors have declared no competing interest. National Science Foundation, DGE-1343012, 2022070 Department of Energy, DE-AC02-05CH11231 Grantham Foundation for the Protection of the Environment

The oceans buffer against climate change via biogeochemical cycles underpinned by microbial metabolic networks. While planetary-scale surveys provide baseline microbiome data, inferring metabolic and biogeochemical impacts remains challenging. Here, we constructed a metabolic model for each TARA Ocean metagenome or metatranscriptome, quantified the importance of each metabolic reaction, and used this to assess planetary-scale heterotrophic prokaryotic metabolic phenotypes as a proxy for marine biogeochemistry. This revealed metabolism-inferred ecological zones that matched taxonomy- and function-inferred ones, connections between microbial metabolism and diversity, and predictions about long-sought virus ecological roles, including that virus-encoded metabolic genes target important reactions and identify viral shuntor shuttle-enriched ocean regions. Together, this framework is agile and resolves planetary-scale community metabolic features to better incorporate microbes and viruses into future predictive ecosystem and climate models. ### Competing Interest Statement SJH has a conflict of interest; he is a co-founder of Koonkie Inc., a bioinformatics consulting company that designs and provides scalable algorithmic and data analytics solutions in the cloud.

Chromate [Cr(VI)] is a toxic heavy metal frequently detected in wastewater, often alongside nitrate (NO3 -). Nitrate-dependent anaerobic methane oxidation (N-DAMO) is a promising process for the simultaneous removal of methane (CH4) and NO3 - in wastewater treatment plants. Because Cr(VI) can serve as an alternative electron acceptor, its presence may alter the N-DAMO performance. Here, we investigated the impact of Cr(VI) on an enrichment culture containing Candidatus Methanoperedens and Candidatus Methylomirabilis, using NO3 - as the electron acceptor and 13C-CH4 as the electron donor. Cultures were exposed to varying Cr(VI) concentrations, and microbial activity was assessed using GC-MS, 16S rRNA gene sequencing, and qPCR. Cr(VI) was reduced within the cultures, but this reduction was not linked to CH4 oxidation. Instead, CH4 oxidation was significantly inhibited, with declines in the relative abundances of both N-DAMO organisms. Cr(VI) reduction was likely mediated by denitrifiers through nitrate reductase activity or abiotically via the reaction with nitrite (NO2 -). These findings reveal functional resilience of microbial consortia in contaminated environments but highlight Cr(VI) toxicity as a constraint for N-DAMO-based wastewater treatment.

The gut microbiome has emerged as a clear player in health and disease, in part by mediating host response to environment and lifestyle. The urobiome (microbiota of the urinary tract) likely functions similarly. However, efforts to characterize the urobiome and assess its functional potential have been limited due to technical challenges including low microbial biomass and high host cell shedding in urine. Here, to begin addressing these challenges, we evaluate urine sample volume (100 ml–5 mL) and host DNA depletion methods and their effects on urobiome profiles in healthy dogs, which are a robust large animal model for the human urobiome. We collected urine from seven dogs and fractionated samples into aliquots. One set of samples was spiked with host (canine) cells to model a biologically relevant host cell burden in urine. Samples then underwent DNA extraction followed by 16S rRNA gene and shotgun metagenomic sequencing. We then assembled metagenome-assembled genomes (MAGs) and compared microbial composition and diversity across groups. We tested six methods of DNA extraction: QIAamp BiOstic Bacteremia (no host depletion), QIAamp DNA Microbiome, Molzym MolYsis, NEBNext Microbiome DNA Enrichment, Zymo HostZERO, and propidium monoazide. In relation to urine sample volume, ≥ 3.0 mL resulted in the most consistent urobiome profiling. In relation to host depletion, individual (dog) but not extraction method drove overall differences in microbial composition. DNA Microbiome yielded the greatest microbial diversity in 16S rRNA sequencing data and shotgun metagenomic sequencing data and maximized MAG recovery while effectively depleting host DNA in host-spiked urine samples. As proof-of-principle, we then mined MAGs for select metabolic functions including central metabolism pathways and environmental chemical degradation. Our findings provide guidelines for studying the urobiome in relation to sample volume and host depletion and lay the foundation for future evaluation of urobiome function in relation to health and disease.

Microorganisms often drive ecosystem function, yet precision disturbance response and ecosystem impact predictions remain challenging due to poorly captured ecological and metabolic interconnectedness and functional redundancy. For example, while mammalian gut dysbiosis is recognized to influence host metabolism, key microbiota and mechanisms governing their effects remain poorly understood. Here we developed a genome-resolved eco-systems biology workflow to predict how gut microbial metabolism affects mammalian health, and we applied it to a 'spinal cord-gut axis' dataset. By scaling and integrating temporally resolved network analytics and consensus statistical approaches, we identified largely previously uncharacterized microbial species that best predict host physiology following neurological impairment. In silico validation through "complete" pathway-centric and comparative genomic analyses revealed that among these species, the major encoded microbial metabolic changes were in pathways directly linked to host nitrogen balance, and they varied by host sex and microbial ecotype/species. Moreover, we identified the exact bacterial species (and their draft genome sequences) driving urease-dependent versus amino acid-dependent nitrogen gut metabolism - findings that explain previously mechanistically-ambiguous, but clinically relevant, ammonia-driven host nitrogen imbalance. More broadly, these ecology- and community-aware approaches provide a framework to study dynamic, interconnected microbiomes that advances from enrichment-based single-taxon and single-gene correlations towards building microbe(s)-driven mechanistic insights that integrate community context and whole pathways.

Microbiomes shape ecosystems through functional profiles influenced by gene gains and losses. While culture-based experiments demonstrate that mobile genetic elements (MGEs) can mediate gene flux, quantitative field data remains scarce. Here we leverage large-scale soil meta-omic data to develop and apply analytics for studying MGEs. In our model permafrost-thaw ecosystem, Stordalen Mire, we identify ~2.1 million MGE recombinases across 89 microbial phyla to assess ecological distributions, functions impacted, and past mobility and current activity. This revealed MGEs shape natural genetic diversity via lineage-specific engagement, and functions including canonical defense elements alongside diverse regulatory and metabolic genes affecting carbon flux and nutrient cycling. These findings and this systematic meta-omic framework open new avenues to better investigate MGE diversity, activity, mobility, and impacts in nature. ### Competing Interest Statement The authors have declared no competing interest.

Coastal ecosystems are increasingly exposed to high nutrient loads and salinity intrusions due to rising seawater levels. Microbial communities, key drivers of elemental cycles in these ecosystems, consequently, experience fluctuations. This study investigates how the methane-rich coastal sediment microbiome from the Stockholm Archipelago copes with high and low nitrogen and sulfide loading by simulating coastal conditions in two methane-saturated anoxic brackish bioreactors. Over a year, the bioreactors were subjected to the same ratio of nitrate, ammonium and sulfide (2:1:1) under eutrophic or oligotrophic conditions and monitored using 16S rRNA gene amplicon and metagenomic sequencing. Sulfide was depleted in both conditions. Sulfide-dependent denitrification was the predominant process in eutrophic conditions, whereas dissimilatory nitrate reduction to ammonium dominated under oligotrophic conditions. Methane oxidation was driven by Methylobacter and Methylomonas in eutrophic conditions, whereas a more diverse methane-oxidising microbial community developed under oligotrophic conditions, which likely competed for nitrate with anaerobic methanotrophic archaea and the gammaproteobacterial MBAE14. Novel putative copper-dependent membrane-bound monooxygenases (Cu-MMOs) were identified in MBAE14 and co-enriched Rugosibacter genomes, suggesting the need for further physiological and genetic characterisation. This study highlights the importance of understanding coastal anoxic microbiomes under fluctuating conditions, revealing complex interactions and novel pathways crucial for ecosystem functioning.

Prokaryotic microbes have impacted marine biogeochemical cycles for billions of years. Viruses also impact these cycles, through lysis, horizontal gene transfer, and encoding and expressing genes that contribute to metabolic reprogramming of prokaryotic cells. While this impact is difficult to quantify in nature, we hypothesized that it can be examined by surveying virus-encoded auxiliary metabolic genes (AMGs) and assessing their ecological context. We systematically developed a global ocean AMG catalog by integrating previously described and newly identified AMGs and then placed this catalog into ecological and metabolic contexts relevant to ocean biogeochemistry. From 7.6 terabases of Tara Oceans paired prokaryote- and virus-enriched metagenomic sequence data, we increased known ocean virus populations to 579,904 (up 16

ABSTRACT Since the discovery of complete ammonia oxidizers (comammox) within the genus Nitrospira, their distribution and abundance across habitats have been intensively studied to better understand their ecological significance. Many primers targeting their ammonia monooxygenase subunit A gene (amoA) have been designed to detect and quantify comammox bacteria and to describe their community structure. We identified 38 published primers, but only few had high coverage and specificity for all known comammox Nitrospira or one of the two described subclades. For each target group, we comprehensively evaluated selected primer pairs using in silico analyses, endpoint PCRs, qPCRs, and amplicon sequencing on samples from various environments. Endpoint PCRs and qPCRs showed that the most commonly used primer pairs (comaA-244F/659R, comaB-244F/659R, and Ntsp-amoA162F/359R) produced several bands, which likely inflated quantifications via qPCR. In contrast, the recently published primer combinations CA377F/C576R, CB377F/C576R, and CA-CB377F/C576R resulted mostly in a single band. Furthermore, amplicon sequencing demonstrated that these primer combinations also captured the highest richness of comammox Nitrospira. Taken together, our results indicate that few existing comammox amoA primer combinations have both high specificity and coverage and that the choice of these high-specificity and high-coverage primer pairs substantially impacts the accurate detection, quantification, and community description of comammox bacteria. We, therefore, recommend using the CA377F/C576R, CB377F/C576R, and CA-CB377F/C576R primer pairs.IMPORTANCEBacteria that can fully convert ammonia via nitrite to nitrate, the complete ammonia oxidizers (comammox), were recently discovered and are found in many natural and engineered environments. PCR-based tools to study their abundance and diversity were rapidly developed, resulting in a plethora of primers available, many of which are widely used. The presence of comammox bacteria in an environment can, however, only be correctly determined if the used primers detect all members of this group while not detecting any other guilds. This study assesses the coverage and specificity of existing primers targeting comammox bacteria using both computational and standard molecular techniques, revealing large differences in their performance. The uniform usage of well-performing primers across studies could aid in generating comparable and generalizable data to better understand the importance of comammox bacteria in the environment.

Hybrid metagenomic assembly of microbial communities, leveraging both long- and short-read sequencing technologies, is becoming an increasingly accessible approach, yet its widespread application faces several challenges. High-quality references may not be available for assembly accuracy comparisons common for benchmarking, and certain aspects of hybrid assembly may benefit from dataset-dependent, empiric guidance rather than the application of a uniform approach. In this study, several simple, reference-free characteristics-particularly coding gene content and read recruitment profiles-were hypothesized to be reliable indicators of assembly quality improvement during iterative error-fixing processes. These characteristics were compared to reference-dependent genome- and gene-centric analyses common for microbial community metagenomic studies. Two laboratory-scale bioreactors were sequenced with short- and long-read platforms, and assembled with commonly used software packages. Following long read assembly, long read correction and short read polishing were iterated up to ten times to resolve errors. These iterative processes were shown to have a substantial effect on gene- and genome-centric community compositions. Simple, reference-free assembly characteristics, specifically changes in gene fragmentation and short read recruitment, were robustly correlated with advanced analyses common in published comparative studies, and therefore are suitable proxies for hybrid metagenome assembly quality to simplify the identification of the optimal number of correction and polishing iterations. As hybrid metagenomic sequencing approaches will likely remain relevant due to the low added cost of short-read sequencing for differential coverage binning or the ability to access lower abundance community members, it is imperative that users are equipped to estimate assembly quality prior to downstream analyses.

The drinking water quality of millions of people in South and Southeast Asia is at risk due to arsenic (As) contamination of groundwater and insufficient access to water treatment facilities. Intensive use of nitrogen (N) fertilizer increases the possibility of nitrate (NO3-) leaching into aquifers, yet very little is known about how the N cycle will interact with and affect the iron (Fe) and As mobility in aquifers. We hypothesized that input of NO3- into highly methanogenic aquifers can stimulate nitrate-dependent anaerobic methane oxidation (N-DAMO) and subsequently help to remove NO3- and decrease CH4 emission. We, therefore, investigated the effects of N input into aquifers and its effect on Fe and As mobility, by running a set of microcosm experiments using aquifer sediment from Van Phuc, Vietnam supplemented with 15NO3- and 13CH4. Additionally, we assessed the effect of N-DAMO by inoculating the sediment with two different N-DAMO enrichment cultures (N-DAMO(O) and N-DAMO(V)). We found that native microbial communities and both N-DAMO enrichments could efficiently consume nearly 5 mM NO3- in 5 days. In an uninoculated setup, NO3- was preferentially used over Fe(III) as electron acceptor and consequently inhibited Fe(III) reduction and As mobilization. The addition of N-DAMO(O) and N-DAMO(V) enrichment cultures led to substantial Fe(III) reduction followed by the release of Fe2+ (0.190±0.002 mM and 0.350±0.007 mM, respectively) and buildup of sedimentary Fe(II) (11.20±0.20 mM and 10.91±0.47 mM, respectively) at the end of the experiment (day 64). Only in the N-DAMO(O) inoculated setup, As was mobilized (27.1±10.8 μg/L), while in the setup inoculated with N-DAMO(V) a significant amount of Mn (24.15±0.41 mg/L) was released to the water. Methane oxidation and 13CO2 formation were observed only in the inoculated setups, suggesting that the native microbial community did not have sufficient potential for N-DAMO. An increase of NH4+ implied that dissimilatory nitrate reduction to ammonium (DNRA) took place in both inoculated setups. The archaeal community in all treatments was dominated by Ca. Methanoperedens while the bacterial community consisted largely of various denitrifiers. Overall, our results suggest that input of N fertilizers to the aquifer decreases As mobility and that CH4 cannot serve as an electron donor for the native NO3- reducing community. Graphical abstract

Abstract Agricultural drainage ditches are subjected to high anthropogenic nitrogen input, leading to eutrophication and greenhouse gas emissions. Nitrate-dependent anaerobic methane oxidation (N-DAMO) could be a promising remediation strategy to remove methane (CH4) and nitrate (NO3−) simultaneously. Therefore, we aimed to evaluate the potential of N-DAMO to remove excess NO3− and decrease CH4 release from agricultural drainage ditches. Microcosm experiments were conducted using sediment and surface water collected from three different sites: a sandy-clay ditch (SCD), a freshwater-fed peatland ditch (FPD), and a brackish peatland ditch (BPD). The microcosms were inoculated with an N-DAMO enrichment culture dominated by Candidatus Methanoperedens and Candidatus Methylomirabilis and supplemented with 13CH4 and 15NO3−. A significant decrease in CH4 and NO3− concentration was only observed in the BPD sediment. In freshwater sediments (FPD and SCD), the effect of N-DAMO inoculation on CH4 and NO3− removal was negligible, likely because N-DAMO microorganisms were outcompeted by heterotrophic denitrifiers consuming NO3− much faster. Overall, our results suggest that bioaugmentation with N-DAMO might be a potential strategy for decreasing NO3− concentrations and CH4 emission in brackish ecosystems with increasing agricultural activities where the native microbial community is incapable of efficient denitrification.

Hybrid metagenomic assembly, leveraging both long- and short-read sequencing technologies, of microbial communities is becoming an increasingly accessible approach, yet its widespread application faces several challenges. High-quality references may not be available for assembly accuracy comparisons common for benchmarking, and certain aspects of hybrid assembly may require dataset-dependent, empirically-guided optimization rather than application of a uniform approach. In this study, several simple, reference-free characteristics - gene lengths and read recruitment - were analyzed as reliable proxies of assembly quality to guide hybrid assembly optimization. These characteristics were further explored in relation to reference-dependent genome- and gene-centric analyses that are common for microbial community metagenomic studies. Here, two laboratory-scale bioreactors were sequenced with short and long read platforms, and assembled with commonly used software packages. Following long read assembly, long read correction and short read polishing were iterated to resolve errors. Each iteration in this process was shown so have a substantial effect on gene- and genome-centric community composition. Simple, reference-free assembly characteristics, specifically changes in gene fragmentation and short read recruitment, explored throughout this process replicated patterns of more advanced analyses seen in published comparative studies, and therefore are suitable proxies for hybrid metagenome assembly accuracy to save computational resources. Hybrid metagenomic sequencing approaches will likely remain relevant due to the low costs of short read sequencing, therefore it is imperative that users are equipped to estimate assembly accuracy prior to downstream gene- and genome-centric analyses.

Hybrid metagenomic assembly, leveraging both long- and short-read sequencing technologies, of microbial communities is becoming an increasingly accessible approach, yet its widespread application faces several challenges. High-quality references may not be available for assembly accuracy comparisons common for benchmarking, and certain aspects of hybrid assembly may require dataset-dependent, empirically-guided optimization rather than application of a uniform approach. In this study, several simple, reference-free characteristics – gene lengths and read recruitment – were analyzed as reliable proxies of assembly quality to guide hybrid assembly optimization. These characteristics were further explored in relation to reference-dependent genome- and gene-centric analyses that are common for microbial community metagenomic studies. Here, two laboratory-scale bioreactors were sequenced with short and long read platforms, and assembled with commonly used software packages. Following long read assembly, long read correction and short read polishing were iterated to resolve errors. Each iteration in this process was shown so have a substantial effect on gene- and genome-centric community composition. Simple, reference-free assembly characteristics, specifically changes in gene fragmentation and short read recruitment, explored throughout this process replicated patterns of more advanced analyses seen in published comparative studies, and therefore are suitable proxies for hybrid metagenome assembly accuracy to save computational resources. Hybrid metagenomic sequencing approaches will likely remain relevant due to the low costs of short read sequencing, therefore it is imperative that users are equipped to estimate assembly accuracy prior to downstream gene- and genome-centric analyses.### Competing Interest StatementThe authors have declared no competing interest.

Pharmaceuticals are relatively new to nature and often not completely removed in wastewater treatment plants (WWTPs). Consequently, these micropollutants end up in water bodies all around the world posing a great environmental risk. One exception to this recalcitrant conversion is paracetamol, whose full degradation has been linked to several microorganisms. However, the genes and corresponding proteins involved in microbial paracetamol degradation are still elusive. In order to improve our knowledge of the microbial paracetamol degradation pathway, we inoculated a bioreactor with sludge of a hospital WWTP (Pharmafilter, Delft, NL) and fed it with paracetamol as the sole carbon source. Paracetamol was fully degraded without any lag phase and the enriched microbial community was investigated by metagenomic and metatranscriptomic analyses, which demonstrated that the microbial community was very diverse. Dilution and plating on paracetamol-amended agar plates yielded two Pseudomonas sp. isolates: a fast-growing Pseudomonas sp. that degraded 200 mg/L of paracetamol in approximately 10 h while excreting 4-aminophenol, and a slow-growing Pseudomonas sp. that degraded paracetamol without obvious intermediates in more than 90 days. Each Pseudomonas sp. contained a different highly-expressed amidase (31% identity to each other). These amidase genes were not detected in the bioreactor metagenome suggesting that other as-yet uncharacterized amidases may be responsible for the first biodegradation step of paracetamol. Uncharacterized deaminase genes and genes encoding dioxygenase enzymes involved in the catabolism of aromatic compounds and amino acids were the most likely candidates responsible for the degradation of paracetamol intermediates based on their high expression levels in the bioreactor meta-genome and the Pseudomonas spp. genomes. Furthermore, cross-feeding between different community members might have occurred to efficiently degrade paracetamol and its intermediates in the bioreactor. This study in-creases our knowledge about the ongoing microbial evolution towards biodegradation of pharmaceuticals and points to a large diversity of (amidase) enzymes that are likely involved in paracetamol metabolism in WWTPs.

Rivers have a significant role in global carbon and nitrogen cycles, serving as a nexus for nutrient transport between terrestrial and marine ecosystems. Although rivers have a small global surface area, they contribute substantially to worldwide greenhouse gas emissions through microbially mediated processes within the river hyporheic zone. Despite this importance, research linking microbial and viral communities to specific biogeochemical reactions is still nascent in these sediment environments. To survey the metabolic potential and gene expression underpinning carbon and nitrogen biogeochemical cycling in river sediments, we collected an integrated data set of 33 metagenomes, metaproteomes, and paired metabolomes. We reconstructed over 500 microbial metagenome-assembled genomes (MAGs), which we dereplicated into 55 unique, nearly complete medium- and high-quality MAGs spanning 12 bacterial and archaeal phyla. We also reconstructed 2,482 viral genomic contigs, which were dereplicated into 111 viral MAGs (vMAGs) of >10 kb in size. As a result of integrating gene expression data with geochemical and metabolite data, we created a conceptual model that uncovered new roles for microorganisms in organic matter decomposition, carbon sequestration, nitrogen mineralization, nitrification, and denitrification. We show how these metabolic pathways, integrated through shared resource pools of ammonium, carbon dioxide, and inorganic nitrogen, could ultimately contribute to carbon dioxide and nitrous oxide fluxes from hyporheic sediments. Further, by linking viral MAGs to these active microbial hosts, we provide some of the first insights into viral modulation of river sediment carbon and nitrogen cycling. IMPORTANCE Here we created HUM-V (hyporheic uncultured microbial and viral), an annotated microbial and viral MAG catalog that captures strain and functional diversity encoded in these Columbia River sediment samples. Demonstrating its utility, this genomic inventory encompasses multiple representatives of dominant microbial and archaeal phyla reported in other river sediments and provides novel viral MAGs that can putatively infect these. Furthermore, we used HUM-V to recruit gene expression data to decipher the functional activities of these MAGs and reconstruct their active roles in Columbia River sediment biogeochemical cycling. Ultimately, we show the power of MAG-resolved multi-omics to uncover interactions and chemical handoffs in river sediments that shape an intertwined carbon and nitrogen metabolic network. The accessible microbial and viral MAGs in HUM-V will serve as a community resource to further advance more untargeted, activity-based measurements in these, and related, freshwater terrestrial-aquatic ecosystems.

Microbial ammonia oxidation is the initial nitrification step used in biological nitrogen-removal during water treatment processes, and the discovery of complete ammonia-oxidizing (comammox) bacteria added a novel member to this functional group. It is important to identify and understand the predominant microorganisms responsible for ammonium removal in biotechnological process design and optimization. In this study, we used a full-scale bioreactor to treat ammonium in groundwater (9.3 +/- 0.5 mg NH4+-N/L) and investigated the key ammonia-oxidizing prokaryotes present. The groundwater ammonium was stably and efficiently oxidized throughout similar to 700 days of bioreactor operation. 16S rRNA gene amplicon sequencing of the bioreactor community showed a high abundance of Nitrospira (12.5-45.9%), with the dominant sequence variant (3.5-37.8%) most closely related to Candidatus Nitrospira nitrosa. Furthermore, analyses of amoA, the marker gene for ammonia oxidation, indicated the presence of two distinct comammox Nitrospira populations, however, the relative abundance of only one of these populations was strongly correlated to ammonia oxidation rates and was robustly expressed. After 380 days of operation copper wires were immersed into the reactor at 0.04-0.06 m(2)/m(3) tank, which caused a gradual abundance increase of one discrete comammox Nitrospira population. However, further increase of the copper dosing (0.08 m(2)/m(3) tank) inverted the most abundant ammonia-oxidizing population to Nitrosomonas sp. These results indicate that comammox Nitrospira were capable of efficient ammonium removal in groundwater without exogenous nutrients, but copper addition can stimulate comammox Nitrospira or lead to dominance of Nitrosomonas depending on dosage.

Background: Rivers serve as a nexus for nutrient transfer between terrestrial and marine ecosystems and as such, have a significant impact on global carbon and nitrogen cycles. In river ecosystems, the sediments found within the hyporheic zone are microbial hotspots that can account for a significant portion of ecosystem respiration and have profound impacts on system biogeochemistry. Despite this, studies using genome-resolved analyses linking microbial and viral communities to nitrogen and carbon biogeochemistry are limited. Results: Here, we characterized the microbial and viral communities of Columbia River hyporheic zone sediments to reveal the metabolisms that actively cycle carbon and nitrogen. Using genome-resolved metagenomics, we created the Hyporheic Uncultured Microbial and Viral (HUM-V) database, containing a dereplicated database of 55 microbial Metagenome-Assembled Genomes (MAGs), representing 12 distinct phyla. We also sampled 111 viral Metagenome Assembled Genomes (vMAGs) from 26 distinct and novel genera. The HUM-V recruited metaproteomes from these same samples, providing the first inventory of microbial gene expression in hyporheic zone sediments. Combining this data with metabolite data, we generated a conceptual model where heterotrophic and autotrophic metabolisms co-occur to drive an integrated carbon and nitrogen cycle, revealing microbial sources and sinks for carbon dioxide and ammonium in these sediments. We uncovered the metabolic handoffs underpinning these processes including mutualistic nitrification by Thermoproteota (formerly Thaumarchaeota) and Nitrospirota, as well as identified possible cooperative and cheating behavior impacting nitrogen mineralization. Finally, by linking vMAGs to microbial genome hosts, we reveal possible viral controls on microbial nitrification and organic carbon degradation. Conclusions: Our multi-omics analyses provide new mechanistic insight into coupled carbon-nitrogen cycling in the hyporheic zone. This is a key step in developing predictive hydrobiogeochemical models that account for microbial cross-feeding and viral influences over potential and expressed microbial metabolisms. Furthermore, the publicly available HUM-V genome resource can be queried and expanded by researchers working in other ecosystems to assess the transferability of our results to other parts of the globe.

The advance of metagenomics in combination with intricate cultivation approaches has facilitated the discovery of novel ammonia-, methane-, and other short-chain alkane-oxidizing microorganisms, indicating that our understanding of the microbial biodiversity within the biogeochemical nitrogen and carbon cycles still is incomplete. The in situ detection and phylogenetic identification of novel ammonia- and alkane-oxidizing bacteria remain challenging due to their naturally low abundances and difficulties in obtaining new isolates from complex samples. Here, we describe an activity-based protein profiling protocol allowing cultivation-independent unveiling of ammonia- and alkane-oxidizing bacteria. In this protocol, 1,7-octadiyne is used as a bifunctional enzyme probe that, in combination with a highly specific alkyne-azide cycloaddition reaction, enables the fluorescent or biotin labeling of cells harboring active ammonia and alkane monooxygenases. Biotinylation of these enzymes in combination with immunogold labeling revealed the subcellular localization of the tagged proteins, which corroborated expected enzyme targets in model strains. In addition, fluorescent labeling of cells harboring active ammonia or alkane monooxygenases provided a direct link of these functional lifestyles to phylogenetic identification when combined with fluorescence in situ hybridization. Furthermore, we show that this activity-based labeling protocol can be successfully coupled with fluorescence-activated cell sorting for the enrichment of nitrifiers and alkane-oxidizing bacteria from complex environmental samples, enabling the recovery of high-quality metagenome-assembled genomes. In conclusion, this study demonstrates a novel, functional tagging technique for the reliable detection, identification, and enrichment of ammonia- and alkane-oxidizing bacteria present in complex microbial communities.