A communal catalogue reveals Earth's multiscale microbial diversity.

Our growing awareness of the microbial world's importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project. Coordinated protocols and new analytical methods, particularly the use of exact sequences instead of clustered operational taxonomic units, enable bacterial and archaeal ribosomal RNA gene sequences to be followed across multiple studies and allow us to explore patterns of diversity at an unprecedented scale. The result is both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth's microbial diversity.

Dominance of Sulfurospirillum in Metagenomes Associated with the Methane Ice Worm (Sirsoe methanicola).

Sirsoe methanicola, commonly known as the methane ice worm, is the only macrofaunal species known to inhabit the Gulf of Mexico methane hydrates. Little is known about this elusive marine polychaete that can colonize rich carbon and energy reserves. Metagenomic analysis of gut contents and worm fragments predicted diverse metabolic capabilities with the ability to utilize a range of nitrogen, sulfur, and organic carbon compounds through microbial taxa affiliated with Campylobacterales, Desulfobacterales, Enterobacterales, SAR324, Alphaproteobacteria, and Mycoplasmatales. Entomoplasmatales and Chitinivibrionales were additionally identified from extracted full-length 16S rRNA sequences, and read analysis identified 196 bacterial families. Overall, the microbial community appeared dominated by uncultured Sulfurospirillum, a taxon previously considered free-living rather than host-associated. Metagenome-assembled genomes (MAGs) classified as uncultured Sulfurospirillum predicted thiosulfate disproportionation and the reduction of tetrathionate, sulfate, sulfide/polysulfide, and nitrate. Microbial amino acid and vitamin B12 biosynthesis genes were identified in multiple MAGs, suggesting nutritional value to the host. Reads assigned to aerobic or anaerobic methanotrophic taxa were rare. IMPORTANCE Methane hydrates represent vast reserves of natural gas with roles in global carbon cycling and climate change. This study provided the first analysis of metagenomes associated with Sirsoe methanicola, the only polychaete species known to colonize methane hydrates. Previously unrecognized participation of Sulfurospirillum in a gut microbiome is provided, and the role of sulfur compound redox reactions within this community is highlighted. The comparative biology of S. methanicola is of general interest given research into the adverse effects of sulfide production in human gut microbiomes. In addition, taxonomic assignments are provided for nearly 200 bacterial families, expanding our knowledge of microbiomes in the deep sea.

Species-level functional profiling of metagenomes and metatranscriptomes.

Functional profiles of microbial communities are typically generated using comprehensive metagenomic or metatranscriptomic sequence read searches, which are time-consuming, prone to spurious mapping, and often limited to community-level quantification. We developed HUMAnN2, a tiered search strategy that enables fast, accurate, and species-resolved functional profiling of host-associated and environmental communities. HUMAnN2 identifies a community's known species, aligns reads to their pangenomes, performs translated search on unclassified reads, and finally quantifies gene families and pathways. Relative to pure translated search, HUMAnN2 is faster and produces more accurate gene family profiles. We applied HUMAnN2 to study clinal variation in marine metabolism, ecological contribution patterns among human microbiome pathways, variation in species' genomic versus transcriptional contributions, and strain profiling. Further, we introduce 'contributional diversity' to explain patterns of ecological assembly across different microbial community types.

Red Sea SAR11 and Prochlorococcus Single-Cell Genomes Reflect Globally Distributed Pangenomes.

Evidence suggests many marine bacteria are cosmopolitan, with widespread but sparse strains poised to seed abundant populations under conducive growth conditions. However, studies supporting this "microbial seed bank" hypothesis have analyzed taxonomic marker genes rather than whole genomes/metagenomes, leaving open the possibility that disparate ocean regions harbor endemic gene content. The Red Sea is isolated geographically from the rest of the ocean and has a combination of high irradiance, high temperature, and high salinity that is unique among the oceans; we therefore asked whether it harbors endemic gene content. We sequenced and assembled single-cell genomes of 21 SAR11 (subclades Ia, Ib, Id, and II) and 5 Prochlorococcus (ecotype HLII) samples from the Red Sea and combined them with globally sourced reference genomes to cluster genes into ortholog groups (OGs). Ordination of OG composition could distinguish clades, including phylogenetically cryptic Prochlorococcus ecotypes LLII and LLIII. Compared with reference genomes, 1% of Prochlorococcus and 17% of SAR11 OGs were unique to the Red Sea genomes (RS-OGs). Most (83%) RS-OGs had no annotated function, but 65% of RS-OGs were expressed in diel Red Sea metatranscriptomes, suggesting they are functional. Searching Tara Oceans metagenomes, RS-OGs were as likely to be found as non-RS-OGs; nevertheless, Red Sea and other warm samples could be distinguished from cooler samples using the relative abundances of OGs. The results suggest that the prevalence of OGs in these surface ocean bacteria is largely cosmopolitan, with differences in population metagenomes manifested by differences in relative abundance rather than complete presence/absence of OGs.IMPORTANCE Studies have shown that as we sequence seawater from a selected environment deeper and deeper, we approach finding every bacterial taxon known for the ocean as a whole. However, such studies have focused on taxonomic marker genes rather than on whole genomes, raising the possibility that the lack of endemism results from the method of investigation. We took a geographically isolated water body, the Red Sea, and sequenced single cells from it. We compared those single-cell genomes to available genomes from around the ocean and to ocean-spanning metagenomes. We showed that gene ortholog groups found in Red Sea genomes but not in other genomes are nevertheless common across global ocean metagenomes. These results suggest that Baas Becking's hypothesis "everything is everywhere, but the environment selects" also applies to gene ortholog groups. This widely dispersed functional diversity may give oceanic microbial communities the functional capacity to respond rapidly to changing conditions.

Transcriptional characterization of Vibrio fischeri during colonization of juvenile Euprymna scolopes.

The marine bacterium Vibrio fischeri is the monospecific symbiont of the Hawaiian bobtail squid, Euprymna scolopes, and the establishment of this association involves a number of signaling pathways and transcriptional responses between both partners. We report here the first full RNA-Seq dataset representing host-associated V. fischeri cells from colonized juvenile E. scolopes, as well as comparative transcriptomes under both laboratory and simulated marine planktonic conditions. These data elucidate the broad transcriptional changes that these bacteria undergo during the early stages of symbiotic colonization. We report several previously undescribed and unexpected transcriptional responses within the early stages of this symbiosis, including gene expression patterns consistent with biochemical stresses inside the host, and metabolic patterns distinct from those reported in associations with adult animals. Integration of these transcriptional data with a recently developed metabolic model of V. fischeri provides us with a clearer picture of the metabolic state of symbionts within the juvenile host, including their possible carbon sources. Taken together, these results expand our understanding of the early stages of the squid-vibrio symbiosis, and more generally inform the transcriptional responses underlying the activities of marine microbes during host colonization.

Selection Maintains Low Genomic GC Content in Marine SAR11 Lineages.

The genomic G+C content of ocean bacteria varies from below 30% to over 60%. This broad range of base composition is likely shaped by distinct mutational processes, recombination, effective population size, and selection driven by environmental factors. A number of studies have hypothesized that depletion of G/C in genomes of marine bacterioplankton cells is an adaptation to the nitrogen-poor pelagic oceans, but they failed to disentangle environmental factors from mutational biases and population history. Here, we reconstructed the evolutionary changes of bases at synonymous sites in genomes of two marine SAR11 populations and a freshwater counterpart with its evolutionary origin rooted in the marine lineage. Although they all have similar genome sizes, DNA repair gene repertoire, and base compositions, there is a stronger bias toward A/T changes, a reduced frequency of nitrogenous amino acids, and an exclusive occurrence of polyamine, opine, and taurine transport systems in the ocean populations, consistent with a greater nitrogen stress in surface oceans compared with freshwater lakes. Furthermore, the ratio of nonsynoymous to synonymous nucleotide diversity is not statistically distinguishable among these populations, suggesting that population history has a limited effect. Taken together, the ecological transition of SAR11 from ocean to freshwater habitats makes nitrogen more available to these organisms, and thus relaxation of purifying selection drove a genome-wide reduction in the frequency of G/C to A/T changes in the freshwater population.

Phage auxiliary metabolic genes and the redirection of cyanobacterial host carbon metabolism.

Cyanophages infecting the marine cyanobacteria Prochlorococcus and Synechococcus encode and express genes for the photosynthetic light reactions. Sequenced cyanophage genomes lack Calvin cycle genes, however, suggesting that photosynthetic energy harvested via phage proteins is not used for carbon fixation. We report here that cyanophages carry and express a Calvin cycle inhibitor, CP12, whose host homologue directs carbon flux from the Calvin cycle to the pentose phosphate pathway (PPP). Phage CP12 was coexpressed with phage genes involved in the light reactions, deoxynucleotide biosynthesis, and the PPP, including a transaldolase gene that is the most prevalent PPP gene in cyanophages. Phage transaldolase was purified to homogeneity from several strains and shown to be functional in vitro, suggesting that it might facilitate increased flux through this key reaction in the host PPP, augmenting production of NADPH and ribose 5-phosphate. Kinetic measurements of phage and host transaldolases revealed that the phage enzymes have k(cat)/K(m) values only approximately one third of the corresponding host enzymes. The lower efficiency of phage transaldolase may be a tradeoff for other selective advantages such as reduced gene size: we show that more than half of host-like cyanophage genes are significantly shorter than their host homologues. Consistent with decreased Calvin cycle activity and increased PPP and light reaction activity under infection, the host NADPH/NADP ratio increased two-fold in infected cells. We propose that phage-augmented NADPH production fuels deoxynucleotide biosynthesis for phage replication, and that the selection pressures molding phage genomes involve fitness advantages conferred through mobilization of host energy stores.

Decoding dissolved information: environmental DNA sequencing at global scale to monitor a changing ocean.

The use of environmental DNA (eDNA) technology for environmental monitoring is rapidly expanding, with applications for fisheries, coral reefs, harmful algal blooms, invasive and endangered species, and biodiversity monitoring. By enabling detection of species over space and time, eDNA fulfills a fundamental need of environmental surveys. Traditional surveys are expensive, require significant capital expenditure, and can be destructive; eDNA offers promise for cheaper, less invasive, and higher-resolution (i.e. genetic) assessments of environments and stocks. However, challenges in quantification, detection limits, biobanking capacity, reference databases, and data management and integration remain significant hurdles to efficient eDNA monitoring at global and decadal scale. Here, we consider the current state of eDNA technology and its suitability for the problems for which it is being used. We explore the current best practices, the logistical and social challenges that prevent eDNA from widespread adoption and benefit, and the emerging technologies that may address those challenges.

Investigation of machine learning algorithms for taxonomic classification of marine metagenomes.

Microbial communities play key roles in ocean ecosystems through regulation of biogeochemical processes such as carbon and nutrient cycling, food web dynamics, and gut microbiomes of invertebrates, fish, reptiles, and mammals. Assessments of marine microbial diversity are therefore critical to understanding spatiotemporal variations in microbial community structure and function in ocean ecosystems. With recent advances in DNA shotgun sequencing for metagenome samples and computational analysis, it is now possible to access the taxonomic and genomic content of ocean microbial communities to study their structural patterns, diversity, and functional potential. However, existing taxonomic classification tools depend upon manually curated phylogenetic trees, which can create inaccuracies in metagenomes from less well-characterized communities, such as from ocean water. Herein, we explore the utility of deep learning tools-DeepMicrobes and a novel Residual Network architecture-that leverage natural language processing and convolutional neural network architectures to map input sequence data (k-mers) to output labels (taxonomic groups) without reliance on a curated taxonomic tree. We trained both models using metagenomic reads simulated from marine microbial genomes in the MarRef database. The performance of both models (accuracy, precision, and percent microbe predicted) was compared with the standard taxonomic classification tool Kraken2 using 10 complex metagenomic data sets simulated from MarRef. Our results demonstrate that time, compute power, and microbial genomic diversity still pose challenges for machine learning (ML). Moreover, our results suggest that high genome coverage and rectification of class imbalance are prerequisites for a well-trained model, and therefore should be a major consideration in future ML work. IMPORTANCE Taxonomic profiling of microbial communities is essential to model microbial interactions and inform habitat conservation. This work develops approaches in constructing training/testing data sets from publicly available marine metagenomes and evaluates the performance of machine learning (ML) approaches in read-based taxonomic classification of marine metagenomes. Predictions from two models are used to test accuracy in metagenomic classification and to guide improvements in ML approaches. Our study provides insights on the methods, results, and challenges of deep learning on marine microbial metagenomic data sets. Future machine learning approaches can be improved by rectifying genome coverage and class imbalance in the training data sets, developing alternative models, and increasing the accessibility of computational resources for model training and refinement.

Tourmaline: A containerized workflow for rapid and iterable amplicon sequence analysis using QIIME 2 and Snakemake.

BACKGROUND: Amplicon sequencing (metabarcoding) is a common method to survey diversity of environmental communities whereby a single genetic locus is amplified and sequenced from the DNA of whole or partial organisms, organismal traces (e.g., skin, mucus, feces), or microbes in an environmental sample. Several software packages exist for analyzing amplicon data, among which QIIME 2 has emerged as a popular option because of its broad functionality, plugin architecture, provenance tracking, and interactive visualizations. However, each new analysis requires the user to keep track of input and output file names, parameters, and commands; this lack of automation and standardization is inefficient and creates barriers to meta-analysis and sharing of results. FINDINGS: We developed Tourmaline, a Python-based workflow that implements QIIME 2 and is built using the Snakemake workflow management system. Starting from a configuration file that defines parameters and input files-a reference database, a sample metadata file, and a manifest or archive of FASTQ sequences-it uses QIIME 2 to run either the DADA2 or Deblur denoising algorithm; assigns taxonomy to the resulting representative sequences; performs analyses of taxonomic, alpha, and beta diversity; and generates an HTML report summarizing and linking to the output files. Features include support for multiple cores, automatic determination of trimming parameters using quality scores, representative sequence filtering (taxonomy, length, abundance, prevalence, or ID), support for multiple taxonomic classification and sequence alignment methods, outlier detection, and automated initialization of a new analysis using previous settings. The workflow runs natively on Linux and macOS or via a Docker container. We ran Tourmaline on a 16S ribosomal RNA amplicon data set from Lake Erie surface water, showing its utility for parameter optimization and the ability to easily view interactive visualizations through the HTML report, QIIME 2 viewer, and R- and Python-based Jupyter notebooks. CONCLUSION: Automated workflows like Tourmaline enable rapid analysis of environmental amplicon data, decreasing the time from data generation to actionable results. Tourmaline is available for download at github.com/aomlomics/tourmaline.

MIxS-SA: a MIxS extension defining the minimum information standard for sequence data from symbiont-associated micro-organisms.

The symbiont-associated (SA) environmental package is a new extension to the minimum information about any (x) sequence (MIxS) standards, established by the Parasite Microbiome Project (PMP) consortium, in collaboration with the Genomics Standard Consortium. The SA was built upon the host-associated MIxS standard, but reflects the nestedness of symbiont-associated microbiota within and across host-symbiont-microbe interactions. This package is designed to facilitate the collection and reporting of a broad range of metadata information that apply to symbionts such as life history traits, association with one or multiple host organisms, or the nature of host-symbiont interactions along the mutualism-parasitism continuum. To better reflect the inherent nestedness of all biological systems, we present a novel feature that allows users to co-localize samples, to nest a package within another package, and to identify replicates. Adoption of the MIxS-SA and of the new terms will facilitate reports of complex sampling design from a myriad of environments.

Standardized multi-omics of Earth's microbiomes reveals microbial and metabolite diversity.

Despite advances in sequencing, lack of standardization makes comparisons across studies challenging and hampers insights into the structure and function of microbial communities across multiple habitats on a planetary scale. Here we present a multi-omics analysis of a diverse set of 880 microbial community samples collected for the Earth Microbiome Project. We include amplicon (16S, 18S, ITS) and shotgun metagenomic sequence data, and untargeted metabolomics data (liquid chromatography-tandem mass spectrometry and gas chromatography mass spectrometry). We used standardized protocols and analytical methods to characterize microbial communities, focusing on relationships and co-occurrences of microbially related metabolites and microbial taxa across environments, thus allowing us to explore diversity at extraordinary scale. In addition to a reference database for metagenomic and metabolomic data, we provide a framework for incorporating additional studies, enabling the expansion of existing knowledge in the form of an evolving community resource. We demonstrate the utility of this database by testing the hypothesis that every microbe and metabolite is everywhere but the environment selects. Our results show that metabolite diversity exhibits turnover and nestedness related to both microbial communities and the environment, whereas the relative abundances of microbially related metabolites vary and co-occur with specific microbial consortia in a habitat-specific manner. We additionally show the power of certain chemistry, in particular terpenoids, in distinguishing Earth's environments (for example, terrestrial plant surfaces and soils, freshwater and marine animal stool), as well as that of certain microbes including Conexibacter woesei (terrestrial soils), Haloquadratum walsbyi (marine deposits) and Pantoea dispersa (terrestrial plant detritus). This Resource provides insight into the taxa and metabolites within microbial communities from diverse habitats across Earth, informing both microbial and chemical ecology, and provides a foundation and methods for multi-omics microbiome studies of hosts and the environment.

Subsurface automated samplers for eDNA (SASe) for biological monitoring and research.

Sampling of environmental DNA (eDNA) in seawater is an increasingly common approach to non-invasively assess marine biodiversity, detect cryptic or invasive species, and monitor specific groups of organisms. Despite this remarkable utility, collection and filtration of eDNA samples in the field still requires considerable time and effort. Recent advancements in automated water samplers have standardized the eDNA collection process, allowing researchers to collect eDNA day or night, sample in locations that are difficult to access, and remove the need for highly trained personnel to perform sampling. However, the high cost of purchasing or building these samplers represents a financial hurdle to widespread application. To overcome this difficulty, we have designed and built a low-cost subsurface automated sampler for eDNA (SASe). Each sampler is submersible to 55 m, can filter a pre-programmable volume of water, and preserves eDNA at the site of collection. SASe samplers have replaceable filters and a low build cost (∼280 USD vs. >100,000 USD for other eDNA samplers), which facilitates repeated field sampling at fine spatial and temporal scales. Lab testing has shown the SASe to be as effective as a standard desktop peristaltic pump for sampling, preserving, and recovering marine eDNA. SASe design files and operating code are open-source, promoting the use of this tool to meet a range of future eDNA research applications, including project-specific customizations to the current design.

Microbiome Metadata Standards: Report of the National Microbiome Data Collaborative's Workshop and Follow-On Activities.

Microbiome samples are inherently defined by the environment in which they are found. Therefore, data that provide context and enable interpretation of measurements produced from biological samples, often referred to as metadata, are critical. Important contributions have been made in the development of community-driven metadata standards; however, these standards have not been uniformly embraced by the microbiome research community. To understand how these standards are being adopted, or the barriers to adoption, across research domains, institutions, and funding agencies, the National Microbiome Data Collaborative (NMDC) hosted a workshop in October 2019. This report provides a summary of discussions that took place throughout the workshop, as well as outcomes of the working groups initiated at the workshop.

Genomic analysis of oceanic cyanobacterial myoviruses compared with T4-like myoviruses from diverse hosts and environments.

T4-like myoviruses are ubiquitous, and their genes are among the most abundant documented in ocean systems. Here we compare 26 T4-like genomes, including 10 from non-cyanobacterial myoviruses, and 16 from marine cyanobacterial myoviruses (cyanophages) isolated on diverse Prochlorococcus or Synechococcus hosts. A core genome of 38 virion construction and DNA replication genes was observed in all 26 genomes, with 32 and 25 additional genes shared among the non-cyanophage and cyanophage subsets, respectively. These hierarchical cores are highly syntenic across the genomes, and sampled to saturation. The 25 cyanophage core genes include six previously described genes with putative functions (psbA, mazG, phoH, hsp20, hli03, cobS), a hypothetical protein with a potential phytanoyl-CoA dioxygenase domain, two virion structural genes, and 16 hypothetical genes. Beyond previously described cyanophage-encoded photosynthesis and phosphate stress genes, we observed core genes that may play a role in nitrogen metabolism during infection through modulation of 2-oxoglutarate. Patterns among non-core genes that may drive niche diversification revealed that phosphorus-related gene content reflects source waters rather than host strain used for isolation, and that carbon metabolism genes appear associated with putative mobile elements. As well, phages isolated on Synechococcus had higher genome-wide %G+C and often contained different gene subsets (e.g. petE, zwf, gnd, prnA, cpeT) than those isolated on Prochlorococcus. However, no clear diagnostic genes emerged to distinguish these phage groups, suggesting blurred boundaries possibly due to cross-infection. Finally, genome-wide comparisons of both diverse and closely related, co-isolated genomes provide a locus-to-locus variability metric that will prove valuable for interpreting metagenomic data sets.

Two hundred and fifty-four metagenome-assembled bacterial genomes from the bank vole gut microbiota.

Vertebrate gut microbiota provide many essential services to their host. To better understand the diversity of such services provided by gut microbiota in wild rodents, we assembled metagenome shotgun sequence data from a small mammal, the bank vole Myodes glareolus (Rodentia, Cricetidae). We were able to identify 254 metagenome assembled genomes (MAGs) that were at least 50% (n = 133 MAGs), 80% (n = 77 MAGs) or 95% (n = 44 MAGs) complete. As typical for a rodent gut microbiota, these MAGs are dominated by taxa assigned to the phyla Bacteroidetes (n = 132 MAGs) and Firmicutes (n = 80), with some Spirochaetes (n = 15) and Proteobacteria (n = 11). Based on coverage over contigs, Bacteroidetes were estimated to be most abundant group, followed by Firmicutes, Spirochaetes and Proteobacteria. These draft bacterial genomes can be used freely to determine the likely functions of gut microbiota community composition in wild rodents.

Prevalence and evolution of core photosystem II genes in marine cyanobacterial viruses and their hosts.

Cyanophages (cyanobacterial viruses) are important agents of horizontal gene transfer among marine cyanobacteria, the numerically dominant photosynthetic organisms in the oceans. Some cyanophage genomes carry and express host-like photosynthesis genes, presumably to augment the host photosynthetic machinery during infection. To study the prevalence and evolutionary dynamics of this phenomenon, 33 cultured cyanophages of known family and host range and viral DNA from field samples were screened for the presence of two core photosystem reaction center genes, psbA and psbD. Combining this expanded dataset with published data for nine other cyanophages, we found that 88% of the phage genomes contain psbA, and 50% contain both psbA and psbD. The psbA gene was found in all myoviruses and Prochlorococcus podoviruses, but could not be amplified from Prochlorococcus siphoviruses or Synechococcus podoviruses. Nearly all of the phages that encoded both psbA and psbD had broad host ranges. We speculate that the presence or absence of psbA in a phage genome may be determined by the length of the latent period of infection. Whether it also carries psbD may reflect constraints on coupling of viral- and host-encoded PsbA-PsbD in the photosynthetic reaction center across divergent hosts. Phylogenetic clustering patterns of these genes from cultured phages suggest that whole genes have been transferred from host to phage in a discrete number of events over the course of evolution (four for psbA, and two for psbD), followed by horizontal and vertical transfer between cyanophages. Clustering patterns of psbA and psbD from Synechococcus cells were inconsistent with other molecular phylogenetic markers, suggesting genetic exchanges involving Synechococcus lineages. Signatures of intragenic recombination, detected within the cyanophage gene pool as well as between hosts and phages in both directions, support this hypothesis. The analysis of cyanophage psbA and psbD genes from field populations revealed significant sequence diversity, much of which is represented in our cultured isolates. Collectively, these findings show that photosynthesis genes are common in cyanophages and that significant genetic exchanges occur from host to phage, phage to host, and within the phage gene pool. This generates genetic diversity among the phage, which serves as a reservoir for their hosts, and in turn influences photosystem evolution.

A Novel Sparse Compositional Technique Reveals Microbial Perturbations.

The central aims of many host or environmental microbiome studies are to elucidate factors associated with microbial community compositions and to relate microbial features to outcomes. However, these aims are often complicated by difficulties stemming from high-dimensionality, non-normality, sparsity, and the compositional nature of microbiome data sets. A key tool in microbiome analysis is beta diversity, defined by the distances between microbial samples. Many different distance metrics have been proposed, all with varying discriminatory power on data with differing characteristics. Here, we propose a compositional beta diversity metric rooted in a centered log-ratio transformation and matrix completion called robust Aitchison PCA. We demonstrate the benefits of compositional transformations upstream of beta diversity calculations through simulations. Additionally, we demonstrate improved effect size, classification accuracy, and robustness to sequencing depth over the current methods on several decreased sample subsets of real microbiome data sets. Finally, we highlight the ability of this new beta diversity metric to retain the feature loadings linked to sample ordinations revealing salient intercommunity niche feature importance. IMPORTANCE By accounting for the sparse compositional nature of microbiome data sets, robust Aitchison PCA can yield high discriminatory power and salient feature ranking between microbial niches. The software to perform this analysis is available under an open-source license and can be obtained at https://github.com/biocore/DEICODE; additionally, a QIIME 2 plugin is provided to perform this analysis at https://library.qiime2.org/plugins/deicode/.

MetaMiner: A Scalable Peptidogenomics Approach for Discovery of Ribosomal Peptide Natural Products with Blind Modifications from Microbial Communities.

Ribosomally synthesized and post-translationally modified peptides (RiPPs) are an important class of natural products that contain antibiotics and a variety of other bioactive compounds. The existing methods for discovery of RiPPs by combining genome mining and computational mass spectrometry are limited to discovering specific classes of RiPPs from small datasets, and these methods fail to handle unknown post-translational modifications. Here, we present MetaMiner, a software tool for addressing these challenges that is compatible with large-scale screening platforms for natural product discovery. After searching millions of spectra in the Global Natural Products Social (GNPS) molecular networking infrastructure against just eight genomic and metagenomic datasets, MetaMiner discovered 31 known and seven unknown RiPPs from diverse microbial communities, including human microbiome and lichen microbiome, and microorganisms isolated from the International Space Station.