Dynamic Phaeodactylum tricornutum exometabolites shape surrounding bacterial communities.

Roles of different ecological classes of algal exometabolites in regulating microbial community composition are not well understood. Here, we identify exometabolites from the model diatom Phaeodactylum tricornutum and demonstrate their potential to influence bacterial abundances. We profiled exometabolites across a time course of axenic algal growth using liquid chromatography-tandem mass spectrometry. We then investigated growth of 12 bacterial isolates on individual-identified exometabolites. Lastly, we compared responses of a P. tricornutum-adapted enrichment community to additions of two contrasting metabolites: selective growth substrate 4-hydroxybenzoic acid and putative signaling/facilitator molecule lumichrome. We identified 50 P. tricornutum metabolites and found distinct temporal accumulation patterns. Two exometabolites (of 12 tested) supported growth of distinct subsets of bacterial isolates. While algal exudates and algal presence drove similar changes in community composition compared with controls, exogenous 4-hydroxybenzoic acid addition promoted increased abundances of taxa that utilized it in isolation, and also revealed the importance of factors relating to algal presence in regulating community composition. This work demonstrates that secretion of selective bacterial growth substrates represents one mechanism by which algal exometabolites can influence bacterial community composition and illustrates how the algal exometabolome has the potential to modulate bacterial communities as a function of algal growth.

The ModelSEED Biochemistry Database for the integration of metabolic annotations and the reconstruction, comparison and analysis of metabolic models for plants, fungi and microbes.

For over 10 years, ModelSEED has been a primary resource for the construction of draft genome-scale metabolic models based on annotated microbial or plant genomes. Now being released, the biochemistry database serves as the foundation of biochemical data underlying ModelSEED and KBase. The biochemistry database embodies several properties that, taken together, distinguish it from other published biochemistry resources by: (i) including compartmentalization, transport reactions, charged molecules and proton balancing on reactions; (ii) being extensible by the user community, with all data stored in GitHub; and (iii) design as a biochemical 'Rosetta Stone' to facilitate comparison and integration of annotations from many different tools and databases. The database was constructed by combining chemical data from many resources, applying standard transformations, identifying redundancies and computing thermodynamic properties. The ModelSEED biochemistry is continually tested using flux balance analysis to ensure the biochemical network is modeling-ready and capable of simulating diverse phenotypes. Ontologies can be designed to aid in comparing and reconciling metabolic reconstructions that differ in how they represent various metabolic pathways. ModelSEED now includes 33,978 compounds and 36,645 reactions, available as a set of extensible files on GitHub, and available to search at https://modelseed.org/biochem and KBase.

multiPhATE: bioinformatics pipeline for functional annotation of phage isolates.

SUMMARY: To address the need for improved phage annotation tools that scale, we created an automated throughput annotation pipeline: multiple-genome Phage Annotation Toolkit and Evaluator (multiPhATE). multiPhATE is a throughput pipeline driver that invokes an annotation pipeline (PhATE) across a user-specified set of phage genomes. This tool incorporates a de novo phage gene calling algorithm and assigns putative functions to gene calls using protein-, virus- and phage-centric databases. multiPhATE's modular construction allows the user to implement all or any portion of the analyses by acquiring local instances of the desired databases and specifying the desired analyses in a configuration file. We demonstrate multiPhATE by annotating two newly sequenced Yersinia pestis phage genomes. Within multiPhATE, the PhATE processing pipeline can be readily implemented across multiple processors, making it adaptable for throughput sequencing projects. Software documentation assists the user in configuring the system. AVAILABILITY AND IMPLEMENTATION: multiPhATE was implemented in Python 3.7, and runs as a command-line code under Linux or Unix. multiPhATE is freely available under an open-source BSD3 license from https://github.com/carolzhou/multiPhATE. Instructions for acquiring the databases and third-party codes used by multiPhATE are included in the distribution README file. Users may report bugs by submitting to the github issues page associated with the multiPhATE distribution. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Combining multiple functional annotation tools increases coverage of metabolic annotation.

BACKGROUND: Genome-scale metabolic modeling is a cornerstone of systems biology analysis of microbial organisms and communities, yet these genome-scale modeling efforts are invariably based on incomplete functional annotations. Annotated genomes typically contain 30-50% of genes without functional annotation, severely limiting our knowledge of the "parts lists" that the organisms have at their disposal. These incomplete annotations may be sufficient to derive a model of a core set of well-studied metabolic pathways that support growth in pure culture. However, pathways important for growth on unusual metabolites exchanged in complex microbial communities are often less understood, resulting in missing functional annotations in newly sequenced genomes. RESULTS: Here, we present results on a comprehensive reannotation of 27 bacterial reference genomes, focusing on enzymes with EC numbers annotated by KEGG, RAST, EFICAz, and the BRENDA enzyme database, and on membrane transport annotations by TransportDB, KEGG and RAST. Our analysis shows that annotation using multiple tools can result in a drastically larger metabolic network reconstruction, adding on average 40% more EC numbers, 3-8 times more substrate-specific transporters, and 37% more metabolic genes. These results are even more pronounced for bacterial species that are phylogenetically distant from well-studied model organisms such as E. coli. CONCLUSIONS: Metabolic annotations are often incomplete and inconsistent. Combining multiple functional annotation tools can greatly improve genome coverage and metabolic network size, especially for non-model organisms and non-core pathways.

Attachment between heterotrophic bacteria and microalgae influences symbiotic microscale interactions.

The surface and surroundings of microalgal cells (phycosphere) are critical interaction zones but have been difficult to functionally interrogate due to methodological limitations. We examined effects of phycosphere-associated bacteria for two biofuel-relevant microalgal species (Phaeodactylum tricornutum and Nannochloropsis salina) using stable isotope tracing and high spatial resolution mass spectrometry imaging (NanoSIMS) to quantify elemental exchanges at the single-cell level. Each algal species responded differently to bacterial attachment. In P. tricornutum, a high percentage of cells had attached bacteria (92%-98%, up to eight bacteria per alga) and fixed 64% more carbon with attached bacteria compared to axenic cells. In contrast, N. salina cells were less commonly associated with bacteria (42%-63%), harboured fewer bacteria per alga, and fixed 10% more carbon without attached bacteria compared to axenic cells. An uncultivated bacterium related to Haliscomenobacter sp. was identified as an effective mutualist; it increased carbon fixation when attached to P. tricornutum and incorporated 71% more algal-fixed carbon relative to other bacteria. Our results illustrate how phylogenetic identity and physical location of bacteria and algae facilitate diverse metabolic responses. Phycosphere-mediated, mutualistic chemical exchanges between autotrophs and heterotrophs may be a fruitful means to increase microalgal productivity for applied engineering efforts.

Mutualistic co-evolution of type III effector genes in Sinorhizobium fredii and Bradyrhizobium japonicum.

Two diametric paradigms have been proposed to model the molecular co-evolution of microbial mutualists and their eukaryotic hosts. In one, mutualist and host exhibit an antagonistic arms race and each partner evolves rapidly to maximize their own fitness from the interaction at potential expense of the other. In the opposing model, conflicts between mutualist and host are largely resolved and the interaction is characterized by evolutionary stasis. We tested these opposing frameworks in two lineages of mutualistic rhizobia, Sinorhizobium fredii and Bradyrhizobium japonicum. To examine genes demonstrably important for host-interactions we coupled the mining of genome sequences to a comprehensive functional screen for type III effector genes, which are necessary for many Gram-negative pathogens to infect their hosts. We demonstrate that the rhizobial type III effector genes exhibit a surprisingly high degree of conservation in content and sequence that is in contrast to those of a well characterized plant pathogenic species. This type III effector gene conservation is particularly striking in the context of the relatively high genome-wide diversity of rhizobia. The evolution of rhizobial type III effectors is inconsistent with the molecular arms race paradigm. Instead, our results reveal that these loci are relatively static in rhizobial lineages and suggest that fitness conflicts between rhizobia mutualists and their host plants have been largely resolved.

Higher order asymptotics for negative binomial regression inferences from RNA-sequencing data.

RNA sequencing (RNA-Seq) is the current method of choice for characterizing transcriptomes and quantifying gene expression changes. This next generation sequencing-based method provides unprecedented depth and resolution. The negative binomial (NB) probability distribution has been shown to be a useful model for frequencies of mapped RNA-Seq reads and consequently provides a basis for statistical analysis of gene expression. Negative binomial exact tests are available for two-group comparisons but do not extend to negative binomial regression analysis, which is important for examining gene expression as a function of explanatory variables and for adjusted group comparisons accounting for other factors. We address the adequacy of available large-sample tests for the small sample sizes typically available from RNA-Seq studies and consider a higher-order asymptotic (HOA) adjustment to likelihood ratio tests. We demonstrate that 1) the HOA-adjusted likelihood ratio test is practically indistinguishable from the exact test in situations where the exact test is available, 2) the type I error of the HOA test matches the nominal specification in regression settings we examined via simulation, and 3) the power of the likelihood ratio test does not appear to be affected by the HOA adjustment. This work helps clarify the accuracy of the unadjusted likelihood ratio test and the degree of improvement available with the HOA adjustment. Furthermore, the HOA test may be preferable even when the exact test is available because it does not require ad hoc library size adjustments.

Differential laboratory passaging of SARS-CoV-2 viral stocks impacts the in vitro assessment of neutralizing antibodies.

Viral populations in natural infections can have a high degree of sequence diversity, which can directly impact immune escape. However, antibody potency is often tested in vitro with a relatively clonal viral populations, such as laboratory virus or pseudotyped virus stocks, which may not accurately represent the genetic diversity of circulating viral genotypes. This can affect the validity of viral phenotype assays, such as antibody neutralization assays. To address this issue, we tested whether recombinant virus carrying SARS-CoV-2 spike (VSV-SARS-CoV-2-S) stocks could be made more genetically diverse by passage, and if a stock passaged under selective pressure was more capable of escaping monoclonal antibody (mAb) neutralization than unpassaged stock or than viral stock passaged without selective pressures. We passaged VSV-SARS-CoV-2-S four times concurrently in three cell lines and then six times with or without polyclonal antiserum selection pressure. All three of the monoclonal antibodies tested neutralized the viral population present in the unpassaged stock. The viral inoculum derived from serial passage without antiserum selection pressure was neutralized by two of the three mAbs. However, the viral inoculum derived from serial passage under antiserum selection pressure escaped neutralization by all three mAbs. Deep sequencing revealed the rapid acquisition of multiple mutations associated with antibody escape in the VSV-SARS-CoV-2-S that had been passaged in the presence of antiserum, including key mutations present in currently circulating Omicron subvariants. These data indicate that viral stock that was generated under polyclonal antiserum selection pressure better reflects the natural environment of the circulating virus and may yield more biologically relevant outcomes in phenotypic assays. Thus, mAb assessment assays that utilize a more genetically diverse, biologically relevant, virus stock may yield data that are relevant for prediction of mAb efficacy and for enhancing biosurveillance.

Microbiome processing of organic nitrogen input supports growth and cyanotoxin production of Microcystis aeruginosa cultures.

Nutrient-induced blooms of the globally abundant freshwater toxic cyanobacterium Microcystis cause worldwide public and ecosystem health concerns. The response of Microcystis growth and toxin production to new and recycled nitrogen (N) inputs and the impact of heterotrophic bacteria in the Microcystis phycosphere on these processes are not well understood. Here, using microbiome transplant experiments, cyanotoxin analysis, and nanometer-scale stable isotope probing to measure N incorporation and exchange at single cell resolution, we monitored the growth, cyanotoxin production, and microbiome community structure of several Microcystis strains grown on amino acids or proteins as the sole N source. We demonstrate that the type of organic N available shaped the microbial community associated with Microcystis, and external organic N input led to decreased bacterial colonization of Microcystis colonies. Our data also suggest that certain Microcystis strains could directly uptake amino acids, but with lower rates than heterotrophic bacteria. Toxin analysis showed that biomass-specific microcystin production was not impacted by N source (i.e. nitrate, amino acids, or protein) but rather by total N availability. Single-cell isotope incorporation revealed that some bacterial communities competed with Microcystis for organic N, but other communities promoted increased N uptake by Microcystis, likely through ammonification or organic N modification. Our laboratory culture data suggest that organic N input could support Microcystis blooms and toxin production in nature, and Microcystis-associated microbial communities likely play critical roles in this process by influencing cyanobacterial succession through either decreasing (via competition) or increasing (via biotransformation) N availability, especially under inorganic N scarcity.

Melanization slows the rapid movement of fungal necromass carbon and nitrogen into both bacterial and fungal decomposer communities and soils.

Microbial necromass contributes significantly to both soil carbon (C) persistence and ecosystem nitrogen (N) availability, but quantitative estimates of C and N movement from necromass into soils and decomposer communities are lacking. Additionally, while melanin is known to slow fungal necromass decomposition, how it influences microbial C and N acquisition as well as elemental release into soils remains unclear. Here, we tracked decomposition of isotopically labeled low and high melanin fungal necromass and measured 13C and 15N accumulation in surrounding soils and microbial communities over 77 d in a temperate forest in Minnesota, USA. Mass loss was significantly higher from low melanin necromass, corresponding with greater 13C and 15N soil inputs. A taxonomically and functionally diverse array of bacteria and fungi was enriched in 13C and/or 15N at all sampling points, with enrichment being consistently higher on low melanin necromass and earlier in decomposition. Similar patterns of preferential C and N enrichment of many bacterial and fungal genera early in decomposition suggest that both microbial groups co-contribute to the rapid assimilation of resource-rich soil organic matter inputs. While overall richness of taxa enriched in C was higher than in N for both bacteria and fungi, there was a significant positive relationship between C and N in co-enriched taxa. Collectively, our results demonstrate that melanization acts as a key ecological trait mediating not only fungal necromass decomposition rate but also necromass C and N release and that both elements are rapidly co-utilized by diverse bacterial and fungal decomposers in natural settings. IMPORTANCE Recent studies indicate that microbial dead cells, particularly those of fungi, play an important role in long-term carbon persistence in soils. Despite this growing recognition, how the resources within dead fungal cells (also known as fungal necromass) move into decomposer communities and soils are poorly quantified, particularly in studies based in natural environments. In this study, we found that the contribution of fungal necromass to soil carbon and nitrogen availability was slowed by the amount of melanin present in fungal cell walls. Further, despite the overall rapid acquisition of carbon and nitrogen from necromass by a diverse range of both bacteria and fungi, melanization also slowed microbial uptake of both elements. Collectively, our results indicate that melanization acts as a key ecological trait mediating not only fungal necromass decomposition rate, but also necromass carbon and nitrogen release into soil as well as microbial resource acquisition.

Terabase-Scale Coassembly of a Tropical Soil Microbiome.

Petabases of environmental metagenomic data are publicly available, presenting an opportunity to characterize complex environments and discover novel lineages of life. Metagenome coassembly, in which many metagenomic samples from an environment are simultaneously analyzed to infer the underlying genomes' sequences, is an essential tool for achieving this goal. We applied MetaHipMer2, a distributed metagenome assembler that runs on supercomputing clusters, to coassemble 3.4 terabases (Tbp) of metagenome data from a tropical soil in the Luquillo Experimental Forest (LEF), Puerto Rico. The resulting coassembly yielded 39 high-quality (>90% complete, <5% contaminated, with predicted 23S, 16S, and 5S rRNA genes and ≥18 tRNAs) metagenome-assembled genomes (MAGs), including two from the candidate phylum Eremiobacterota. Another 268 medium-quality (≥50% complete, <10% contaminated) MAGs were extracted, including the candidate phyla Dependentiae, Dormibacterota, and Methylomirabilota. In total, 307 medium- or higher-quality MAGs were assigned to 23 phyla, compared to 294 MAGs assigned to nine phyla in the same samples individually assembled. The low-quality (<50% complete, <10% contaminated) MAGs from the coassembly revealed a 49% complete rare biosphere microbe from the candidate phylum FCPU426 among other low-abundance microbes, an 81% complete fungal genome from the phylum Ascomycota, and 30 partial eukaryotic MAGs with ≥10% completeness, possibly representing protist lineages. A total of 22,254 viruses, many of them low abundance, were identified. Estimation of metagenome coverage and diversity indicates that we may have characterized ≥87.5% of the sequence diversity in this humid tropical soil and indicates the value of future terabase-scale sequencing and coassembly of complex environments. IMPORTANCE Petabases of reads are being produced by environmental metagenome sequencing. An essential step in analyzing these data is metagenome assembly, the computational reconstruction of genome sequences from microbial communities. "Coassembly" of metagenomic sequence data, in which multiple samples are assembled together, enables more complete detection of microbial genomes in an environment than "multiassembly," in which samples are assembled individually. To demonstrate the potential for coassembling terabases of metagenome data to drive biological discovery, we applied MetaHipMer2, a distributed metagenome assembler that runs on supercomputing clusters, to coassemble 3.4 Tbp of reads from a humid tropical soil environment. The resulting coassembly, its functional annotation, and analysis are presented here. The coassembly yielded more, and phylogenetically more diverse, microbial, eukaryotic, and viral genomes than the multiassembly of the same data. Our resource may facilitate the discovery of novel microbial biology in tropical soils and demonstrates the value of terabase-scale metagenome sequencing.

The Western Lake Erie culture collection: A promising resource for evaluating the physiological and genetic diversity of Microcystis and its associated microbiome.

Cyanobacterial harmful algal blooms (cyanoHABs) dominated by Microcystis spp. have significant public health and economic implications in freshwater bodies around the world. These blooms are capable of producing a variety of cyanotoxins, including microcystins, that affect fishing and tourism industries, human and environmental health, and access to drinking water. In this study, we isolated and sequenced the genomes of 21 primarily unialgal Microcystis cultures collected from western Lake Erie between 2017 and 2019. While some cultures isolated in different years have a high degree of genetic similarity (genomic Average Nucleotide Identity >99%), genomic data show that these cultures also represent much of the breadth of known Microcystis diversity in natural populations. Only five isolates contained all the genes required for microcystin biosynthesis while two isolates contained a previously described partial mcy operon. Microcystin production within cultures was also assessed using Enzyme-Linked Immunosorbent Assay (ELISA) and supported genomic results with high concentrations (up to 900 µg L⁻¹) in cultures with complete mcy operons and no or low toxin detected otherwise. These xenic cultures also contained a substantial diversity of bacteria associated with Microcystis, which has become increasingly recognized as an essential component of cyanoHAB community dynamics. These results highlight the genomic diversity among Microcystis strains and associated bacteria in Lake Erie, and their potential impacts on bloom development, toxin production, and toxin degradation. This culture collection significantly increases the availability of environmentally relevant Microcystis strains from temperate North America.

Prokaryotic Genome Annotation.

In the last decade, the high-throughput and relatively low cost of short-read sequencing technologies have revolutionized prokaryotic genomics. This has led to an exponential increase in the number of bacterial and archaeal genome sequences available, as well as corresponding increase of genome assembly and annotation tools developed. Together, these hardware and software technologies have given scientists unprecedented options to study their chosen microbial systems without the need for large teams of bioinformaticists or supercomputing facilities. While these analysis tools largely fall into only a few categories, each may have different requirements, caveats and file formats, and some may be rarely updated or even abandoned. And so, despite the apparent ease in sequencing and analyzing a prokaryotic genome, it is no wonder that the budding genomicist may quickly find oneself overwhelmed. Here, we aim to provide the reader with an overview of genome annotation and its most important considerations, as well as an easy-to-follow protocol to get started with annotating a prokaryotic genome.

Bacterial response to spatial gradients of algal-derived nutrients in a porous microplate.

Photosynthetic microalgae are responsible for 50% of the global atmospheric CO2 fixation into organic matter and hold potential as a renewable bioenergy source. Their metabolic interactions with the surrounding microbial community (the algal microbiome) play critical roles in carbon cycling, but due to methodological limitations, it has been challenging to examine how community development is influenced by spatial proximity to their algal host. Here we introduce a copolymer-based porous microplate to co-culture algae and bacteria, where metabolites are constantly exchanged between the microorganisms while maintaining physical separation. In the microplate, we found that the diatom Phaeodactylum tricornutum accumulated to cell abundances ~20 fold higher than under normal batch conditions due to constant replenishment of nutrients through the porous structure. We also demonstrate that algal-associated bacteria, both single isolates and complex communities, responded to inorganic nutrients away from their host as well as organic nutrients originating from the algae in a spatially predictable manner. These experimental findings coupled with a mathematical model suggest that host proximity and algal culture growth phase impact bacterial community development in a taxon-specific manner through organic and inorganic nutrient availability. Our novel system presents a useful tool to investigate universal metabolic interactions between microbes in aquatic ecosystems.

Bacterial Community Assembly, Succession, and Metabolic Function during Outdoor Cultivation of Microchloropsis salina.

Outdoor cultivation of microalgae has promising potential for renewable bioenergy, but there is a knowledge gap on the structure and function of the algal microbiome that coinhabits these ecosystems. Here, we describe the assembly mechanisms, taxonomic structure, and metabolic potential of bacteria associated with Microchloropsis salina cultivated outdoors. Open mesocosms were inoculated with algal cultures that were either free of bacteria or coincubated with one of two different strains of alga-associated bacteria and were sampled across five time points taken over multiple harvesting rounds of a 40-day experiment. Using quantitative analyses of metagenome-assembled genomes (MAGs), we tracked bacterial community compositional abundance and taxon-specific functional capacity involved in algal-bacterial interactions. One of the inoculated bacteria (Alteromonas sp.) persisted and dispersed across mesocosms, whereas the other inoculated strain (Phaeobacter gallaeciensis) disappeared by day 17 while a taxonomically similar but functionally distinct Phaeobacter strain became established. The inoculated strains were less abundant than 6 numerically dominant newly recruited taxa with functional capacities for mutualistic or saprophytic lifestyles, suggesting a generalist approach to persistence. This includes a highly abundant unclassified Rhodobacteraceae species that fluctuated between 25% and 77% of the total community. Overall, we did not find evidence for priority effects exerted by the distinct inoculum conditions; all mesocosms converged with similar microbial community compositions by the end of the experiment. Instead, we infer that the 15 total populations were retained due to host selection, as they showed high metabolic potential for algal-bacterial interactions such as recycling alga-produced carbon and nitrogen and production of vitamins and secondary metabolites associated with algal growth and senescence, including B vitamins, tropodithietic acid, and roseobacticides. IMPORTANCE Bacteria proliferate in nutrient-rich aquatic environments, including engineered algal biofuel systems, where they remineralize photosynthates, exchange secondary metabolites with algae, and can influence system output of biomass or oil. Despite this, knowledge on the microbial ecology of algal cultivation systems is lacking, and the subject is worthy of investigation. Here, we used metagenomics to characterize the metabolic capacities of the predominant bacteria associated with the biofuel-relevant microalga Microchloropsis salina and to predict testable metabolic interactions between algae and manipulated communities of bacteria. We identified a previously undescribed and uncultivated organism that dominated the community. Collectively, the microbial community may interact with the alga in cultivation via exchange of secondary metabolites which could affect algal success, which we demonstrate as a possible outcome from controlled experiments with metabolically analogous isolates. These findings address the scalability of lab-based algal-bacterial interactions through to cultivation systems and more broadly provide a framework for empirical testing of genome-based metabolic predictions.

HT-SIP: a semi-automated stable isotope probing pipeline identifies cross-kingdom interactions in the hyphosphere of arbuscular mycorrhizal fungi.

BACKGROUND: Linking the identity of wild microbes with their ecophysiological traits and environmental functions is a key ambition for microbial ecologists. Of many techniques that strive for this goal, Stable-isotope probing-SIP-remains among the most comprehensive for studying whole microbial communities in situ. In DNA-SIP, actively growing microorganisms that take up an isotopically heavy substrate build heavier DNA, which can be partitioned by density into multiple fractions and sequenced. However, SIP is relatively low throughput and requires significant hands-on labor. We designed and tested a semi-automated, high-throughput SIP (HT-SIP) pipeline to support well-replicated, temporally resolved amplicon and metagenomics experiments. We applied this pipeline to a soil microhabitat with significant ecological importance-the hyphosphere zone surrounding arbuscular mycorrhizal fungal (AMF) hyphae. AMF form symbiotic relationships with most plant species and play key roles in terrestrial nutrient and carbon cycling. RESULTS: Our HT-SIP pipeline for fractionation, cleanup, and nucleic acid quantification of density gradients requires one-sixth of the hands-on labor compared to manual SIP and allows 16 samples to be processed simultaneously. Automated density fractionation increased the reproducibility of SIP gradients compared to manual fractionation, and we show adding a non-ionic detergent to the gradient buffer improved SIP DNA recovery. We applied HT-SIP to 13C-AMF hyphosphere DNA from a 13CO2 plant labeling study and created metagenome-assembled genomes (MAGs) using high-resolution SIP metagenomics (14 metagenomes per gradient). SIP confirmed the AMF Rhizophagus intraradices and associated MAGs were highly enriched (10-33 atom% 13C), even though the soils' overall enrichment was low (1.8 atom% 13C). We assembled 212 13C-hyphosphere MAGs; the hyphosphere taxa that assimilated the most AMF-derived 13C were from the phyla Myxococcota, Fibrobacterota, Verrucomicrobiota, and the ammonia-oxidizing archaeon genus Nitrososphaera. CONCLUSIONS: Our semi-automated HT-SIP approach decreases operator time and improves reproducibility by targeting the most labor-intensive steps of SIP-fraction collection and cleanup. We illustrate this approach in a unique and understudied soil microhabitat-generating MAGs of actively growing microbes living in the AMF hyphosphere (without plant roots). The MAGs' phylogenetic composition and gene content suggest predation, decomposition, and ammonia oxidation may be key processes in hyphosphere nutrient cycling. Video Abstract.

Plant-associated fungi support bacterial resilience following water limitation.

Drought disrupts soil microbial activity and many biogeochemical processes. Although plant-associated fungi can support plant performance and nutrient cycling during drought, their effects on nearby drought-exposed soil microbial communities are not well resolved. We used H218O quantitative stable isotope probing (qSIP) and 16S rRNA gene profiling to investigate bacterial community dynamics following water limitation in the hyphospheres of two distinct fungal lineages (Rhizophagus irregularis and Serendipita bescii) grown with the bioenergy model grass Panicum hallii. In uninoculated soil, a history of water limitation resulted in significantly lower bacterial growth potential and growth efficiency, as well as lower diversity in the actively growing bacterial community. In contrast, both fungal lineages had a protective effect on hyphosphere bacterial communities exposed to water limitation: bacterial growth potential, growth efficiency, and the diversity of the actively growing bacterial community were not suppressed by a history of water limitation in soils inoculated with either fungus. Despite their similar effects at the community level, the two fungal lineages did elicit different taxon-specific responses, and bacterial growth potential was greater in R. irregularis compared to S. bescii-inoculated soils. Several of the bacterial taxa that responded positively to fungal inocula belong to lineages that are considered drought susceptible. Overall, H218O qSIP highlighted treatment effects on bacterial community structure that were less pronounced using traditional 16S rRNA gene profiling. Together, these results indicate that fungal-bacterial synergies may support bacterial resilience to moisture limitation.

Multiple Mutations Associated with Emergent Variants Can Be Detected as Low-Frequency Mutations in Early SARS-CoV-2 Pandemic Clinical Samples.

Genetic analysis of intra-host viral populations provides unique insight into pre-emergent mutations that may contribute to the genotype of future variants. Clinical samples positive for SARS-CoV-2 collected in California during the first months of the pandemic were sequenced to define the dynamics of mutation emergence as the virus became established in the state. Deep sequencing of 90 nasopharyngeal samples showed that many mutations associated with the establishment of SARS-CoV-2 globally were present at varying frequencies in a majority of the samples, even those collected as the virus was first detected in the US. A subset of mutations that emerged months later in consensus sequences were detected as subconsensus members of intra-host populations. Spike mutations P681H, H655Y, and V1104L were detected prior to emergence in variant genotypes, mutations were detected at multiple positions within the furin cleavage site, and pre-emergent mutations were identified in the nucleocapsid and the envelope genes. Because many of the samples had a very high depth of coverage, a bioinformatics pipeline, "Mappgene", was established that uses both iVar and LoFreq variant calling to enable identification of very low-frequency variants. This enabled detection of a spike protein deletion present in many samples at low frequency and associated with a variant of concern.

Quantitative Stable-Isotope Probing (qSIP) with Metagenomics Links Microbial Physiology and Activity to Soil Moisture in Mediterranean-Climate Grassland Ecosystems.

The growth and physiology of soil microorganisms, which play vital roles in biogeochemical cycling, are shaped by both current and historical soil environmental conditions. Here, we developed and applied a genome-resolved metagenomic implementation of quantitative stable isotope probing (qSIP) with an H218O labeling experiment to identify actively growing soil microorganisms and their genomic capacities. qSIP enabled measurement of taxon-specific growth because isotopic incorporation into microbial DNA requires production of new genome copies. We studied three Mediterranean grassland soils across a rainfall gradient to evaluate the hypothesis that historic precipitation levels are an important factor controlling trait selection. We used qSIP-informed genome-resolved metagenomics to resolve the active subset of soil community members and identify their characteristic ecophysiological traits. Higher year-round precipitation levels correlated with higher activity and growth rates of flagellar motile microorganisms. In addition to heavily isotopically labeled bacteria, we identified abundant isotope-labeled phages, suggesting phage-induced cell lysis likely contributed to necromass production at all three sites. Further, there was a positive correlation between phage activity and the activity of putative phage hosts. Contrary to our expectations, the capacity to decompose the diverse complex carbohydrates common in soil organic matter or oxidize methanol and carbon monoxide were broadly distributed across active and inactive bacteria in all three soils, implying that these traits are not highly selected for by historical precipitation. IMPORTANCE Soil moisture is a critical factor that strongly shapes the lifestyle of soil organisms by changing access to nutrients, controlling oxygen diffusion, and regulating the potential for mobility. We identified active microorganisms in three grassland soils with similar mineral contexts, yet different historic rainfall inputs, by adding water labeled with a stable isotope and tracking that isotope in DNA of growing microbes. By examining the genomes of active and inactive microorganisms, we identified functions that are enriched in growing organisms, and showed that different functions were selected for in different soils. Wetter soil had higher activity of motile organisms, but activity of pathways for degradation of soil organic carbon compounds, including simple carbon substrates, were comparable for all three soils. We identified many labeled, and thus active bacteriophages (viruses that infect bacteria), implying that the cells they killed contributed to soil organic matter. The activity of these bacteriophages was significantly correlated with activity of their hosts.