Pan-cancer analyses reveal cancer-type-specific fungal ecologies and bacteriome interactions.

Cancer-microbe associations have been explored for centuries, but cancer-associated fungi have rarely been examined. Here, we comprehensively characterize the cancer mycobiome within 17,401 patient tissue, blood, and plasma samples across 35 cancer types in four independent cohorts. We report fungal DNA and cells at low abundances across many major human cancers, with differences in community compositions that differ among cancer types, even when accounting for technical background. Fungal histological staining of tissue microarrays supported intratumoral presence and frequent spatial association with cancer cells and macrophages. Comparing intratumoral fungal communities with matched bacteriomes and immunomes revealed co-occurring bi-domain ecologies, often with permissive, rather than competitive, microenvironments and distinct immune responses. Clinically focused assessments suggested prognostic and diagnostic capacities of the tissue and plasma mycobiomes, even in stage I cancers, and synergistic predictive performance with bacteriomes.

Floxed exon (Flexon): A flexibly positioned stop cassette for recombinase-mediated conditional gene expression.

Conditional gene expression is a powerful tool for genetic analysis of biological phenomena. In the widely used "lox-stop-lox" approach, insertion of a stop cassette consisting of a series of stop codons and polyadenylation signals flanked by lox sites into the 5' untranslated region (UTR) of a gene prevents expression until the cassette is excised by tissue-specific expression of Cre recombinase. Although lox-stop-lox and similar approaches using other site-specific recombinases have been successfully used in many experimental systems, this design has certain limitations. Here, we describe the Floxed exon (Flexon) approach, which uses a stop cassette composed of an artificial exon flanked by artificial introns, designed to cause premature termination of translation and nonsense-mediated decay of the mRNA and allowing for flexible placement into a gene. We demonstrate its efficacy in Caenorhabditis elegans by showing that, when promoters that cause weak and/or transient cell-specific expression are used to drive Cre in combination with a gfp(flexon) transgene, strong and sustained expression of green fluorescent protein (GFP) is obtained in specific lineages. We also demonstrate its efficacy in an endogenous gene context: we inserted a flexon into the Argonaute gene rde-1 to abrogate RNA interference (RNAi), and restored RNAi tissue specifically by expression of Cre. Finally, we describe several potential additional applications of the Flexon approach, including more precise control of gene expression using intersectional methods, tissue-specific protein degradation, and generation of genetic mosaics. The Flexon approach should be feasible in any system where a site-specific recombination-based method may be applied.

Ultralow-input single-tube linked-read library method enables short-read second-generation sequencing systems to routinely generate highly accurate and economical long-range sequencing information.

Long-range sequencing information is required for haplotype phasing, de novo assembly, and structural variation detection. Current long-read sequencing technologies can provide valuable long-range information but at a high cost with low accuracy and high DNA input requirements. We have developed a single-tube Transposase Enzyme Linked Long-read Sequencing (TELL-seq) technology, which enables a low-cost, high-accuracy, and high-throughput short-read second-generation sequencer to generate over 100 kb of long-range sequencing information with as little as 0.1 ng input material. In a PCR tube, millions of clonally barcoded beads are used to uniquely barcode long DNA molecules in an open bulk reaction without dilution and compartmentation. The barcoded linked-reads are used to successfully assemble genomes ranging from microbes to human. These linked-reads also generate megabase-long phased blocks and provide a cost-effective tool for detecting structural variants in a genome, which are important to identify compound heterozygosity in recessive Mendelian diseases and discover genetic drivers and diagnostic biomarkers in cancers.

Tuning of shortening speed in coleoid cephalopod muscle: no evidence for tissue-specific muscle myosin heavy chain isoforms.

The contractile protein myosin II is ubiquitous in muscle. It is widely accepted that animals express tissue-specific myosin isoforms that differ in amino acid sequence and ATPase activity in order to tune muscle contractile velocities. Recent studies, however, suggested that the squid Doryteuthis pealeii might be an exception; members of this species do not express muscle-specific myosin isoforms, but instead alter sarcomeric ultrastructure to adjust contractile velocities. We investigated whether this alternative mechanism of tuning muscle contractile velocity is found in other coleoid cephalopods. We analyzed myosin heavy chain transcript sequences and expression profiles from muscular tissues of a cuttlefish, Sepia officinalis, and an octopus, Octopus bimaculoides, in order to determine if these cephalopods express tissue-specific myosin heavy chain isoforms. We identified transcripts of four and six different myosin heavy chain isoforms in S. officinalis and O. bimaculoides muscular tissues, respectively. Transcripts of all isoforms were expressed in all muscular tissues studied, and thus S. officinalis and O. bimaculoides do not appear to express tissue-specific muscle myosin isoforms. We also examined the sarcomeric ultrastructure in the transverse muscle fibers of the arms of O. bimaculoides and the arms and tentacles of S. officinalis using transmission electron microscopy and found that the fast contracting fibers of the prey capture tentacles of S. officinalis have shorter thick filaments than those found in the slower transverse muscle fibers of the arms of both species. It thus appears that coleoid cephalopods, including the cuttlefish and octopus, may use ultrastructural modifications rather than tissue-specific myosin isoforms to adjust contractile velocities.

A gain-of-function mutation in the M-domain of cardiac myosin-binding protein-C increases binding to actin.

The M-domain is the major regulatory subunit of cardiac myosin-binding protein-C (cMyBP-C) that modulates actin and myosin interactions to influence muscle contraction. However, the precise mechanism(s) and the specific residues involved in mediating the functional effects of the M-domain are not fully understood. Positively charged residues adjacent to phosphorylation sites in the M-domain are thought to be critical for effects of cMyBP-C on cross-bridge interactions by mediating electrostatic binding with myosin S2 and/or actin. However, recent structural studies revealed that highly conserved sequences downstream of the phosphorylation sites form a compact tri-helix bundle. Here we used site-directed mutagenesis to probe the functional significance of charged residues adjacent to the phosphorylation sites and conserved residues within the tri-helix bundle. Results confirm that charged residues adjacent to phosphorylation sites and residues within the tri-helix bundle are important for mediating effects of the M-domain on contraction. In addition, four missense variants within the tri-helix bundle that are associated with human hypertrophic cardiomyopathy caused either loss-of-function or gain-of-function effects on force. Importantly, the effects of the gain-of-function variant, L348P, increased the affinity of the M-domain for actin. Together, results demonstrate that functional effects of the M-domain are not due solely to interactions with charged residues near phosphorylatable serines and provide the first demonstration that the tri-helix bundle contributes to the functional effects of the M-domain, most likely by binding to actin.

Altered interactions between cardiac myosin binding protein-C and α-cardiac actin variants associated with cardiomyopathies.

The two genes most commonly associated with mutations linked to hypertrophic or dilated cardiomyopathies are ß-myosin and cardiac myosin binding protein-C (cMyBP-C). Both of these proteins interact with cardiac actin (ACTC). Currently there are 16 ACTC variants that have been found in patients with HCM or DCM. While some of these ACTC variants exhibit protein instability or polymerization-deficiencies that might contribute to the development of disease, other changes could cause changes in protein-protein interactions between sarcomere proteins and ACTC. To test the hypothesis that changes in ACTC disrupt interactions with cMyBP-C, we examined the interactions between seven ACTC variants and the N-terminal C0C2 fragment of cMyBP-C. We found there was a significant decrease in binding affinity (increase in Kd values) for the A331P and Y166C variants of ACTC. These results suggest that a change in the ability of cMyBP-C to bind actin filaments containing these ACTC protein variants might contribute to the development of disease. These results also provide clues regarding the binding site of the C0C2 fragment of cMyBP-C on F-actin.

Peripheral neuronal activation shapes the microbiome and alters gut physiology.

The gastrointestinal (GI) tract is innervated by intrinsic neurons of the enteric nervous system (ENS) and extrinsic neurons of the central nervous system and peripheral ganglia. The GI tract also harbors a diverse microbiome, but interactions between the ENS and the microbiome remain poorly understood. Here, we activate choline acetyltransferase (ChAT)-expressing or tyrosine hydroxylase (TH)-expressing gut-associated neurons in mice to determine effects on intestinal microbial communities and their metabolites as well as on host physiology. The resulting multi-omics datasets support broad roles for discrete peripheral neuronal subtypes in shaping microbiome structure, including modulating bile acid profiles and fungal colonization. Physiologically, activation of either ChAT+ or TH+ neurons increases fecal output, while only ChAT+ activation results in increased colonic contractility and diarrhea-like fluid secretion. These findings suggest that specific subsets of peripherally activated neurons differentially regulate the gut microbiome and GI physiology in mice without involvement of signals from the brain.

Developing Science Literacy in Students and Society: Theory, Research, and Practice.

The subject of scientific literacy has never been more critical to the scientific community as well as society in general. As opportunities to spread misinformation increase with the rise of new technologies, it is critical for society to have at its disposal the means for ensuring that its citizens possess the basic scientific literacy necessary to make critical decisions on topics like climate change, biotechnology, and other science-based issues. As the Guest Editors of this themed issue of the Journal of Microbiology and Biology Education, we present a wide array of techniques that the scientific community is using to promote scientific literacy in both academic and nonacademic settings. The diversity of the techniques presented here give us confidence that the scientific community will rise to the challenge of ensuring that our society will be prepared to make fact-based and wise decisions that will preserve and improve our quality of life.

Comprehensive evaluation of shotgun metagenomics, amplicon sequencing, and harmonization of these platforms for epidemiological studies.

In a large cohort of 1,772 participants from the Hispanic Community Health Study/Study of Latinos with overlapping 16SV4 rRNA gene (bacterial amplicon), ITS1 (fungal amplicon), and shotgun sequencing data, we demonstrate that 16SV4 amplicon sequencing and shotgun metagenomics offer the same level of taxonomic accuracy for bacteria at the genus level even at shallow sequencing depths. In contrast, for fungal taxa, we did not observe meaningful agreements between shotgun and ITS1 amplicon results. Finally, we show that amplicon and shotgun data can be harmonized and pooled to yield larger microbiome datasets with excellent agreement (<1% effect size variance across three independent outcomes) using pooled amplicon/shotgun data compared to pure shotgun metagenomic analysis. Thus, there are multiple approaches to study the microbiome in epidemiological studies, and we provide a demonstration of a powerful pooling approach that will allow researchers to leverage the massive amount of amplicon sequencing data generated over the last two decades.

Muscular tissues of the squid Doryteuthis pealeii express identical myosin heavy chain isoforms: an alternative mechanism for tuning contractile speed.

The speed of muscle contraction is largely controlled at the sarcomere level by the ATPase activity of the motor protein myosin. Differences in amino acid sequence in catalytically important regions of myosin yield different myosin isoforms with varying ATPase activities and resulting differences in cross-bridge cycling rates and interfilamentary sliding velocities. Modulation of whole-muscle performance by changes in myosin isoform ATPase activity is regarded as a universal mechanism to tune contractile properties, especially in vertebrate muscles. Invertebrates such as squid, however, may exhibit an alternative mechanism to tune contractile properties that is based on differences in muscle ultrastructure, including variable myofilament and sarcomere lengths. To determine definitively whether contractile properties of squid muscles are regulated via different myosin isoforms (i.e. different ATPase activities), the nucleotide and amino acid sequences of the myosin heavy chain from the squid Doryteuthis pealeii were determined from the mantle, arm, tentacle, fin and funnel retractor musculature. We identified three myosin heavy chain isoforms in squid muscular tissues, with differences arising at surface loop 1 and the carboxy terminus. All three isoforms were detected in all five tissues studied. These results suggest that the muscular tissues of D. pealeii express identical myosin isoforms, and it is likely that differences in muscle ultrastructure, not myosin ATPase activity, represent the most important mechanism for tuning contractile speeds.

SALSA, a genetically encoded biosensor for spatiotemporal quantification of Notch signal transduction in vivo.

Notch-mediated lateral specification is a fundamental mechanism to resolve stochastic cell fate choices by amplifying initial differences between equivalent cells. To study how stochastic events impact Notch activity, we developed a biosensor, SALSA (sensor able to detect lateral signaling activity), consisting of an amplifying "switch"-Notch tagged with TEV protease-and a "reporter"-GFP fused to a nuclearly localized red fluorescent protein, separated by a TEVp cut site. When ligand activates Notch, TEVp enters the nucleus and releases GFP from its nuclear tether, allowing Notch activation to be quantified based on the changes in GFP subcellular localization. We show that SALSA accurately reports Notch activity in different signaling paradigms in Caenorhabditis elegans and use time-lapse imaging to test hypotheses about how stochastic elements ensure a reproducible and robust outcome in a canonical lin-12/Notch-mediated lateral signaling paradigm. SALSA should be generalizable to other experimental systems and be adaptable to increase options for bespoke "SynNotch" applications.

Transcriptional Profiles of a Foliar Fungal Endophyte (Pestalotiopsis, Ascomycota) and Its Bacterial Symbiont (Luteibacter, Gammaproteobacteria) Reveal Sulfur Exchange and Growth Regulation during Early Phases of Symbiotic Interaction.

Symbiosis with bacteria is widespread among eukaryotes, including fungi. Bacteria that live within fungal mycelia (endohyphal bacteria) occur in many plant-associated fungi, including diverse Mucoromycota and Dikarya. Pestalotiopsis sp. strain 9143 is a filamentous ascomycete isolated originally as a foliar endophyte of Platycladus orientalis (Cupressaceae). It is infected naturally with the endohyphal bacterium Luteibacter sp. strain 9143, which influences auxin and enzyme production by its fungal host. Previous studies have used transcriptomics to examine similar symbioses between endohyphal bacteria and root-associated fungi such as arbuscular mycorrhizal fungi and plant pathogens. However, currently there are no gene expression studies of endohyphal bacteria of Ascomycota, the most species-rich fungal phylum. To begin to understand such symbioses, we developed methods for assessing gene expression by Pestalotiopsis sp. and Luteibacter sp. when grown in coculture and when each was grown axenically. Our assays showed that the density of Luteibacter sp. in coculture was greater than in axenic culture, but the opposite was true for Pestalotiopsis sp. Dual-transcriptome sequencing (RNA-seq) data demonstrate that growing in coculture modulates developmental and metabolic processes in both the fungus and bacterium, potentially through changes in the balance of organic sulfur via methionine acquisition. Our analyses also suggest an unexpected, potential role of the bacterial type VI secretion system in symbiosis establishment, expanding current understanding of the scope and dynamics of fungal-bacterial symbioses. IMPORTANCE Interactions between microbes and their hosts have important outcomes for host and environmental health. Foliar fungal endophytes that infect healthy plants can harbor facultative endosymbionts called endohyphal bacteria, which can influence the outcome of plant-fungus interactions. These bacterial-fungal interactions can be influential but are poorly understood, particularly from a transcriptome perspective. Here, we report on a comparative, dual-RNA-seq study examining the gene expression patterns of a foliar fungal endophyte and a facultative endohyphal bacterium when cultured together versus separately. Our findings support a role for the fungus in providing organic sulfur to the bacterium, potentially through methionine acquisition, and the potential involvement of a bacterial type VI secretion system in symbiosis establishment. This work adds to the growing body of literature characterizing endohyphal bacterial-fungal interactions, with a focus on a model facultative bacterial-fungal symbiosis in two species-rich lineages, the Ascomycota and Proteobacteria.

A comparison of six DNA extraction protocols for 16S, ITS and shotgun metagenomic sequencing of microbial communities.

Microbial communities contain a broad phylogenetic diversity of organisms; however, the majority of methods center on describing bacteria and archaea. Fungi are important symbionts in many ecosystems and are potentially important members of the human microbiome, beyond those that can cause disease. To expand our analysis of microbial communities to include data from the fungal internal transcribed spacer (ITS) region, five candidate DNA extraction kits were compared against our standardized protocol for describing bacteria and archaea using 16S rRNA gene amplicon- and shotgun metagenomics sequencing. The results are presented considering a diverse panel of host-associated and environmental sample types and comparing the cost, processing time, well-to-well contamination, DNA yield, limit of detection and microbial community composition among protocols. Across all criteria, the MagMAX Microbiome kit was found to perform best. The PowerSoil Pro kit performed comparably but with increased cost per sample and overall processing time. The Zymo MagBead, NucleoMag Food and Norgen Stool kits were included.

Compositionally Aware Phylogenetic Beta-Diversity Measures Better Resolve Microbiomes Associated with Phenotype.

Microbiome data have several specific characteristics (sparsity and compositionality) that introduce challenges in data analysis. The integration of prior information regarding the data structure, such as phylogenetic structure and repeated-measure study designs, into analysis, is an effective approach for revealing robust patterns in microbiome data. Past methods have addressed some but not all of these challenges and features: for example, robust principal-component analysis (RPCA) addresses sparsity and compositionality; compositional tensor factorization (CTF) addresses sparsity, compositionality, and repeated measure study designs; and UniFrac incorporates phylogenetic information. Here we introduce a strategy of incorporating phylogenetic information into RPCA and CTF. The resulting methods, phylo-RPCA, and phylo-CTF, provide substantial improvements over state-of-the-art methods in terms of discriminatory power of underlying clustering ranging from the mode of delivery to adult human lifestyle. We demonstrate quantitatively that the addition of phylogenetic information improves effect size and classification accuracy in both data-driven simulated data and real microbiome data. IMPORTANCE Microbiome data analysis can be difficult because of particular data features, some unavoidable and some due to technical limitations of DNA sequencing instruments. The first step in many analyses that ultimately reveals patterns of similarities and differences among sets of samples (e.g., separating samples from sick and healthy people or samples from seawater versus soil) is calculating the difference between each pair of samples. We introduce two new methods to calculate these differences that combine features of past methods, specifically being able to take into account the principles that most types of microbes are not in most samples (sparsity), that abundances are relative rather than absolute (compositionality), and that all microbes have a shared evolutionary history (phylogeny). We show using simulated and real data that our new methods provide improved classification accuracy of ordinal sample clusters and increased effect size between sample groups on beta-diversity distances.

Swapping Metagenomics Preprocessing Pipeline Components Offers Speed and Sensitivity Increases.

Increasing data volumes on high-throughput sequencing instruments such as the NovaSeq 6000 leads to long computational bottlenecks for common metagenomics data preprocessing tasks such as adaptor and primer trimming and host removal. Here, we test whether faster recently developed computational tools (Fastp and Minimap2) can replace widely used choices (Atropos and Bowtie2), obtaining dramatic accelerations with additional sensitivity and minimal loss of specificity for these tasks. Furthermore, the taxonomic tables resulting from downstream processing provide biologically comparable results. However, we demonstrate that for taxonomic assignment, Bowtie2's specificity is still required. We suggest that periodic reevaluation of pipeline components, together with improvements to standardized APIs to chain them together, will greatly enhance the efficiency of common bioinformatics tasks while also facilitating incorporation of further optimized steps running on GPUs, FPGAs, or other architectures. We also note that a detailed exploration of available algorithms and pipeline components is an important step that should be taken before optimization of less efficient algorithms on advanced or nonstandard hardware. IMPORTANCE In shotgun metagenomics studies that seek to relate changes in microbial DNA across samples, processing the data on a computer often takes longer than obtaining the data from the sequencing instrument. Recently developed software packages that perform individual steps in the pipeline of data processing in principle offer speed advantages, but in practice they may contain pitfalls that prevent their use, for example, they may make approximations that introduce unacceptable errors in the data. Here, we show that differences in choices of these components can speed up overall data processing by 5-fold or more on the same hardware while maintaining a high degree of correctness, greatly reducing the time taken to interpret results. This is an important step for using the data in clinical settings, where the time taken to obtain the results may be critical for guiding treatment.

Postnatal exposure to ambient air pollutants is associated with the composition of the infant gut microbiota at 6-months of age.

Epidemiological studies in adults have shown that exposure to ambient air pollution (AAP) is associated with the composition of the adult gut microbiome, but these relationships have not been examined in infancy. We aimed to determine if 6-month postnatal AAP exposure was associated with the infant gut microbiota at 6 months of age in a cohort of Latino mother-infant dyads from the Southern California Mother's Milk Study (n = 103). We estimated particulate matter (PM2.5 and PM10) and nitrogen dioxide (NO2) exposure from birth to 6-months based on residential address histories. We characterized the infant gut microbiota using 16S rRNA amplicon sequencing at 6-months of age. At 6-months, the gut microbiota was dominated by the phyla Bacteroidetes, Firmicutes, Proteobacteria, and Actinobacteria. Our results show that, after adjusting for important confounders, postnatal AAP exposure was associated with the composition of the gut microbiota. As an example, PM10 exposure was positively associated with Dialister, Dorea, Acinetobacter, and Campylobacter while PM2.5 was positively associated with Actinomyces. Further, exposure to PM10 and PM2.5 was inversely associated with Alistipes and NO2 exposure was positively associated with Actinomyces, Enterococcus, Clostridium, and Eubacterium. Several of these taxa have previously been linked with systemic inflammation, including the genera Dialister and Dorea. This study provides the first evidence of significant associations between exposure to AAP and the composition of the infant gut microbiota, which may have important implications for future infant health and development.

Phylogeny-Aware Analysis of Metagenome Community Ecology Based on Matched Reference Genomes while Bypassing Taxonomy.

We introduce the operational genomic unit (OGU) method, a metagenome analysis strategy that directly exploits sequence alignment hits to individual reference genomes as the minimum unit for assessing the diversity of microbial communities and their relevance to environmental factors. This approach is independent of taxonomic classification, granting the possibility of maximal resolution of community composition, and organizes features into an accurate hierarchy using a phylogenomic tree. The outputs are suitable for contemporary analytical protocols for community ecology, differential abundance, and supervised learning while supporting phylogenetic methods, such as UniFrac and phylofactorization, that are seldom applied to shotgun metagenomics despite being prevalent in 16S rRNA gene amplicon studies. As demonstrated in two real-world case studies, the OGU method produces biologically meaningful patterns from microbiome data sets. Such patterns further remain detectable at very low metagenomic sequencing depths. Compared with taxonomic unit-based analyses implemented in currently adopted metagenomics tools, and the analysis of 16S rRNA gene amplicon sequence variants, this method shows superiority in informing biologically relevant insights, including stronger correlation with body environment and host sex on the Human Microbiome Project data set and more accurate prediction of human age by the gut microbiomes of Finnish individuals included in the FINRISK 2002 cohort. We provide Woltka, a bioinformatics tool to implement this method, with full integration with the QIIME 2 package and the Qiita web platform, to facilitate adoption of the OGU method in future metagenomics studies. IMPORTANCE Shotgun metagenomics is a powerful, yet computationally challenging, technique compared to 16S rRNA gene amplicon sequencing for decoding the composition and structure of microbial communities. Current analyses of metagenomic data are primarily based on taxonomic classification, which is limited in feature resolution. To solve these challenges, we introduce operational genomic units (OGUs), which are the individual reference genomes derived from sequence alignment results, without further assigning them taxonomy. The OGU method advances current read-based metagenomics in two dimensions: (i) providing maximal resolution of community composition and (ii) permitting use of phylogeny-aware tools. Our analysis of real-world data sets shows that it is advantageous over currently adopted metagenomic analysis methods and the finest-grained 16S rRNA analysis methods in predicting biological traits. We thus propose the adoption of OGUs as an effective practice in metagenomic studies.

Enhancing untargeted metabolomics using metadata-based source annotation.

Human untargeted metabolomics studies annotate only ~10% of molecular features. We introduce reference-data-driven analysis to match metabolomics tandem mass spectrometry (MS/MS) data against metadata-annotated source data as a pseudo-MS/MS reference library. Applying this approach to food source data, we show that it increases MS/MS spectral usage 5.1-fold over conventional structural MS/MS library matches and allows empirical assessment of dietary patterns from untargeted data.

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.