Host-microbiome associations in saliva predict COVID-19 severity.

Established evidence indicates that oral microbiota plays a crucial role in modulating host immune responses to viral infection. Following severe acute respiratory syndrome coronavirus 2, there are coordinated microbiome and inflammatory responses within the mucosal and systemic compartments that are unknown. The specific roles the oral microbiota and inflammatory cytokines play in the pathogenesis of coronavirus disease 2019 (COVID-19) are yet to be explored. Here, we evaluated the relationships between the salivary microbiome and host parameters in different groups of COVID-19 severity based on their oxygen requirement. Saliva and blood samples (n = 80) were collected from COVID-19 and from noninfected individuals. We characterized the oral microbiomes using 16S ribosomal RNA gene sequencing and evaluated saliva and serum cytokines and chemokines using multiplex analysis. Alpha diversity of the salivary microbial community was negatively associated with COVID-19 severity, while diversity increased with health. Integrated cytokine evaluations of saliva and serum showed that the oral host response was distinct from the systemic response. The hierarchical classification of COVID-19 status and respiratory severity using multiple modalities separately (i.e. microbiome, salivary cytokines, and systemic cytokines) and simultaneously (i.e. multimodal perturbation analyses) revealed that the microbiome perturbation analysis was the most informative for predicting COVID-19 status and severity, followed by the multimodal. Our findings suggest that oral microbiome and salivary cytokines may be predictive of COVID-19 status and severity, whereas atypical local mucosal immune suppression and systemic hyperinflammation provide new cues to understand the pathogenesis in immunologically compromised populations.

Unveiling the Microbial Realm with VEBA 2.0: A modular bioinformatics suite for end-to-end genome-resolved prokaryotic, (micro)eukaryotic, and viral multi-omics from either short- or long-read sequencing.

The microbiome is a complex community of microorganisms, encompassing prokaryotic (bacterial and archaeal), eukaryotic, and viral entities. This microbial ensemble plays a pivotal role in influencing the health and productivity of diverse ecosystems while shaping the web of life. However, many software suites developed to study microbiomes analyze only the prokaryotic community and provide limited to no support for viruses and microeukaryotes. Previously, we introduced the Viral Eukaryotic Bacterial Archaeal (VEBA) open-source software suite to address this critical gap in microbiome research by extending genome-resolved analysis beyond prokaryotes to encompass the understudied realms of eukaryotes and viruses. Here we present VEBA 2.0 with key updates including a comprehensive clustered microeukaryotic protein database, rapid genome/protein-level clustering, bioprospecting, non-coding/organelle gene modeling, genome-resolved taxonomic/pathway profiling, long-read support, and containerization. We demonstrate VEBA's versatile application through the analysis of diverse case studies including marine water, Siberian permafrost, and white-tailed deer lung tissues with the latter showcasing how to identify integrated viruses. VEBA represents a crucial advancement in microbiome research, offering a powerful and accessible platform that bridges the gap between genomics and biotechnological solutions.

Efficient formation of single-copy human artificial chromosomes.

Large DNA assembly methodologies underlie milestone achievements in synthetic prokaryotic and budding yeast chromosomes. While budding yeast control chromosome inheritance through ~125-base pair DNA sequence-defined centromeres, mammals and many other eukaryotes use large, epigenetic centromeres. Harnessing centromere epigenetics permits human artificial chromosome (HAC) formation but is not sufficient to avoid rampant multimerization of the initial DNA molecule upon introduction to cells. We describe an approach that efficiently forms single-copy HACs. It employs a ~750-kilobase construct that is sufficiently large to house the distinct chromatin types present at the inner and outer centromere, obviating the need to multimerize. Delivery to mammalian cells is streamlined by employing yeast spheroplast fusion. These developments permit faithful chromosome engineering in the context of metazoan cells.

Validating a Promoter Library for Application in Plasmid-Based Diatom Genetic Engineering.

While diatoms are promising synthetic biology platforms, there currently exists a limited number of validated genetic regulatory parts available for genetic engineering. The standard method for diatom transformation, nonspecific introduction of DNA into chromosomes via biolistic particle bombardment, is low throughput and suffers from clonal variability and epigenetic effects. Recent developments in diatom engineering have demonstrated that autonomously replicating episomal plasmids serve as stable expression platforms for diverse gene expression technologies. These plasmids are delivered via bacterial conjugation and, when combined with modular DNA assembly technologies, provide a flexibility and speed not possible with biolistic-mediated strain generation. In order to expand the current toolbox for plasmid-based engineering in the diatom Phaeodactylum tricornutum, a conjugation-based forward genetics screen for promoter discovery was developed, and application to a diatom genomic DNA library defined 252 P. tricornutum promoter elements. From this library, 40 promoter/terminator pairs were delivered via conjugation on episomal plasmids, characterized in vivo, and ranked across 4 orders of magnitude difference in reporter gene expression levels.

Genus-Wide Transcriptional Landscapes Reveal Correlated Gene Networks Underlying Microevolutionary Divergence in Diatoms.

Marine microbes like diatoms make up the base of marine food webs and drive global nutrient cycles. Despite their key roles in ecology, biogeochemistry, and biotechnology, we have limited empirical data on how forces other than adaptation may drive diatom diversification, especially in the absence of environmental change. One key feature of diatom populations is frequent extreme reductions in population size, which can occur both in situ and ex situ as part of bloom-and-bust growth dynamics. This can drive divergence between closely related lineages, even in the absence of environmental differences. Here, we combine experimental evolution and transcriptome landscapes (t-scapes) to reveal repeated evolutionary divergence within several species of diatoms in a constant environment. We show that most of the transcriptional divergence can be captured on a reduced set of axes, and that repeatable evolution can occur along a single major axis of variation defined by core ortholog expression comprising common metabolic pathways. Previous work has associated specific transcriptional changes in gene networks with environmental factors. Here, we find that these same gene networks diverge in the absence of environmental change, suggesting these pathways may be central in generating phenotypic diversity as a result of both selective and random evolutionary forces. If this is the case, these genes and the functions they encode may represent universal axes of variation. Such axes that capture suites of interacting transcriptional changes during diversification improve our understanding of both global patterns in local adaptation and microdiversity, as well as evolutionary forces shaping algal cultivation.

Genotypic diversity and unrecognized antifungal resistance among populations of Candida glabrata from positive blood cultures.

The longstanding model is that most bloodstream infections (BSIs) are caused by a single organism. We perform whole genome sequencing of five-to-ten strains from blood culture (BC) bottles in each of ten patients with Candida glabrata BSI. We demonstrate that BCs contain mixed populations of clonal but genetically diverse strains. Genetically distinct strains from two patients exhibit phenotypes that are potentially important during BSIs, including differences in susceptibility to antifungal agents and phagocytosis. In both patients, the clinical microbiology lab recovered a fluconazole-susceptible index strain, but we identify mixed fluconazole-susceptible and -resistant populations. Diversity in drug susceptibility is likely clinically relevant, as fluconazole-resistant strains were subsequently recovered by the clinical laboratory during persistent or relapsing infections. In one patient, unrecognized respiration-deficient small colony variants are fluconazole-resistant and significantly attenuated for virulence during murine candidiasis. Our data suggest a population-based model of C. glabrata genotypic and phenotypic diversity during BSIs.

Competition between skin antimicrobial peptides and commensal bacteria in type 2 inflammation enables survival of S. aureus.

During inflammation, the skin deploys antimicrobial peptides (AMPs) yet during allergic inflammation it becomes more susceptible to Staphylococcus aureus. To understand this contradiction, single-cell sequencing of Il4ra-/- mice combined with skin microbiome analysis reveals that lower production of AMPs from interleukin-4 receptor α (IL-4Rα) activation selectively inhibits survival of antibiotic-producing strains of coagulase-negative Staphylococcus (CoNS). Diminished AMPs under conditions of T helper type 2 (Th2) inflammation enable expansion of CoNS strains without antibiotic activity and increase Staphylococcus aureus (S. aureus), recapitulating the microbiome on humans with atopic dermatitis. This response is rescued in Camp-/- mice or after topical steroids, since further inhibition of AMPs enables survival of antibiotic-producing CoNS strains. In conditions of Th17 inflammation, a higher expression of host AMPs is sufficient to directly inhibit S. aureus survival. These results show that antimicrobials produced by the host and commensal bacteria each act to control S. aureus on the skin.

Host-Microbiome Associations in Saliva Predict COVID-19 Severity.

Established evidence indicates that oral microbiota plays a crucial role in modulating host immune responses to viral infection. Following Severe Acute Respiratory Syndrome Coronavirus 2 - SARS-CoV-2 - there are coordinated microbiome and inflammatory responses within the mucosal and systemic compartments that are unknown. The specific roles that the oral microbiota and inflammatory cytokines play in the pathogenesis of COVID-19 are yet to be explored. We evaluated the relationships between the salivary microbiome and host parameters in different groups of COVID-19 severity based on their Oxygen requirement. Saliva and blood samples (n = 80) were collected from COVID-19 and from non-infected individuals. We characterized the oral microbiomes using 16S ribosomal RNA gene sequencing and evaluated saliva and serum cytokines using Luminex multiplex analysis. Alpha diversity of the salivary microbial community was negatively associated with COVID-19 severity. Integrated cytokine evaluations of saliva and serum showed that the oral host response was distinct from the systemic response. The hierarchical classification of COVID-19 status and respiratory severity using multiple modalities separately (i.e., microbiome, salivary cytokines, and systemic cytokines) and simultaneously (i.e., multi-modal perturbation analyses) revealed that the microbiome perturbation analysis was the most informative for predicting COVID-19 status and severity, followed by the multi-modal. Our findings suggest that oral microbiome and salivary cytokines may be predictive of COVID-19 status and severity, whereas atypical local mucosal immune suppression and systemic hyperinflammation provide new cues to understand the pathogenesis in immunologically naïve populations.

Genotypic diversity and unrecognized antifungal resistance among populations of Candida glabrata from positive blood cultures.

The longstanding paradigm is that most bloodstream infections (BSIs) are caused by a single organism. We performed whole genome sequencing of five-to-ten strains from blood culture (BC) bottles in each of ten patients with Candida glabrata BSI. We demonstrated that BCs contained mixed populations of clonal but genetically diverse strains. Genetically distinct strains from two patients exhibited phenotypes that were potentially important during BSIs, including differences in susceptibility to antifungal agents and phagocytosis. In both patients, the clinical microbiology lab recovered a fluconazole-susceptible index strain, but we identified mixed fluconazole-susceptible and â€"resistant populations. Diversity in drug susceptibility was likely clinically relevant, as fluconazole-resistant strains were subsequently recovered by the clinical laboratory during persistent or relapsing infections. In one patient, unrecognized respiration-deficient small colony variants were fluconazole-resistant and significantly attenuated for virulence during murine candidiasis. Our data suggest a new population-based paradigm of C. glabrata genotypic and phenotypic diversity during BSIs.

VEBA: a modular end-to-end suite for in silico recovery, clustering, and analysis of prokaryotic, microeukaryotic, and viral genomes from metagenomes.

BACKGROUND: With the advent of metagenomics, the importance of microorganisms and how their interactions are relevant to ecosystem resilience, sustainability, and human health has become evident. Cataloging and preserving biodiversity is paramount not only for the Earth's natural systems but also for discovering solutions to challenges that we face as a growing civilization. Metagenomics pertains to the in silico study of all microorganisms within an ecological community in situ, however, many software suites recover only prokaryotes and have limited to no support for viruses and eukaryotes. RESULTS: In this study, we introduce the Viral Eukaryotic Bacterial Archaeal (VEBA) open-source software suite developed to recover genomes from all domains. To our knowledge, VEBA is the first end-to-end metagenomics suite that can directly recover, quality assess, and classify prokaryotic, eukaryotic, and viral genomes from metagenomes. VEBA implements a novel iterative binning procedure and hybrid sample-specific/multi-sample framework that yields more genomes than any existing methodology alone. VEBA includes a consensus microeukaryotic database containing proteins from existing databases to optimize microeukaryotic gene modeling and taxonomic classification. VEBA also provides a unique clustering-based dereplication strategy allowing for sample-specific genomes and genes to be directly compared across non-overlapping biological samples. Finally, VEBA is the only pipeline that automates the detection of candidate phyla radiation bacteria and implements the appropriate genome quality assessments. VEBA's capabilities are demonstrated by reanalyzing 3 existing public datasets which recovered a total of 948 MAGs (458 prokaryotic, 8 eukaryotic, and 482 viral) including several uncharacterized organisms and organisms with no public genome representatives. CONCLUSIONS: The VEBA software suite allows for the in silico recovery of microorganisms from all domains of life by integrating cutting edge algorithms in novel ways. VEBA fully integrates both end-to-end and task-specific metagenomic analysis in a modular architecture that minimizes dependencies and maximizes productivity. The contributions of VEBA to the metagenomics community includes seamless end-to-end metagenomics analysis but also provides users with the flexibility to perform specific analytical tasks. VEBA allows for the automation of several metagenomics steps and shows that new information can be recovered from existing datasets.

A Silent Operon of Photorhabdus luminescens Encodes a Prodrug Mimic of GTP.

With the overmining of actinomycetes for compounds acting against Gram-negative pathogens, recent efforts to discover novel antibiotics have been focused on other groups of bacteria. Teixobactin, the first antibiotic without detectable resistance that binds lipid II, comes from an uncultured Eleftheria terra, a betaproteobacterium; odilorhabdins, from Xenorhabdus, are broad-spectrum inhibitors of protein synthesis, and darobactins from Photorhabdus target BamA, the essential chaperone of the outer membrane of Gram-negative bacteria. Xenorhabdus and Photorhabdus are symbionts of the nematode gut microbiome and attractive producers of secondary metabolites. Only small portions of their biosynthetic gene clusters (BGC) are expressed in vitro. To access their silent operons, we first separated extracts from a small library of isolates into fractions, resulting in 200-fold concentrated material, and then screened them for antimicrobial activity. This resulted in a hit with selective activity against Escherichia coli, which we identified as a novel natural product antibiotic, 3'-amino 3'-deoxyguanosine (ADG). Mutants resistant to ADG mapped to gsk and gmk, kinases of guanosine. Biochemical analysis shows that ADG is a prodrug that is converted into an active ADG triphosphate (ADG-TP), a mimic of GTP. ADG incorporates into a growing RNA chain, interrupting transcription, and inhibits cell division, apparently by interfering with the GTPase activity of FtsZ. Gsk of the purine salvage pathway, which is the first kinase in the sequential phosphorylation of ADG, is restricted to E. coli and closely related species, explaining the selectivity of the compound. There are probably numerous targets of ADG-TP among GTP-dependent proteins. The discovery of ADG expands our knowledge of prodrugs, which are rare among natural compounds. IMPORTANCE Drug-resistant Gram-negative bacteria have become the major problem driving the antimicrobial resistance crisis. Searching outside the overmined actinomycetes, we focused on Photorhabdus, gut symbionts of enthomopathogenic nematodes that carry up to 40 biosynthetic gene clusters coding for secondary metabolites. Most of these are silent and do not express in vitro. To gain access to silent operons, we first fractionated supernatant from Photorhabdus and then tested 200-fold concentrated material for activity. This resulted in the isolation of a novel antimicrobial, 3'-amino 3'-deoxyguanosine (ADG), active against E. coli. ADG is an analog of guanosine and is converted into an active ADG-TP in the cell. ADG-TP inhibits transcription and probably numerous other GTP-dependent targets, such as FtsZ. Natural product prodrugs have been uncommon; discovery of ADG broadens our knowledge of this type of antibiotic.

Differential network analysis of oral microbiome metatranscriptomes identifies community scale metabolic restructuring in dental caries.

Dental caries is a microbial disease and the most common chronic health condition, affecting nearly 3.5 billion people worldwide. In this study, we used a multiomics approach to characterize the supragingival plaque microbiome of 91 Australian children, generating 658 bacterial and 189 viral metagenome-assembled genomes with transcriptional profiling and gene-expression network analysis. We developed a reproducible pipeline for clustering sample-specific genomes to integrate metagenomics and metatranscriptomics analyses regardless of biosample overlap. We introduce novel feature engineering and compositionally-aware ensemble network frameworks while demonstrating their utility for investigating regime shifts associated with caries dysbiosis. These methods can be applied when differential abundance modeling does not capture statistical enrichments or the results from such analysis are not adequate for providing deeper insight into disease. We identified which organisms and metabolic pathways were central in a coexpression network as well as how these networks were rewired between caries and caries-free phenotypes. Our findings provide evidence of a core bacterial microbiome that was transcriptionally active in the supragingival plaque of all participants regardless of phenotype, but also show highly diagnostic changes in the ways that organisms interact. Specifically, many organisms exhibit high connectedness with central carbon metabolism to Cardiobacterium and this shift serves a bridge between phenotypes. Our evidence supports the hypothesis that caries is a multifactorial ecological disease.

Interactions between fecal gut microbiome, enteric pathogens, and energy regulating hormones among acutely malnourished rural Gambian children.

BACKGROUND: The specific roles that gut microbiota, known pathogens, and host energy-regulating hormones play in the pathogenesis of non-edematous severe acute malnutrition (marasmus SAM) and moderate acute malnutrition (MAM) during outpatient nutritional rehabilitation are yet to be explored. METHODS: We applied an ensemble of sample-specific (intra- and inter-modality) association networks to gain deeper insights into the pathogenesis of acute malnutrition and its severity among children under 5 years of age in rural Gambia, where marasmus SAM is most prevalent. FINDINGS: Children with marasmus SAM have distinct microbiome characteristics and biologically-relevant multimodal biomarkers not observed among children with moderate acute malnutrition. Marasmus SAM was characterized by lower microbial richness and biomass, significant enrichments in Enterobacteriaceae, altered interactions between specific Enterobacteriaceae and key energy regulating hormones and their receptors. INTERPRETATION: Our findings suggest that marasmus SAM is characterized by the collapse of a complex system with nested interactions and key associations between the gut microbiome, enteric pathogens, and energy regulating hormones.  Further exploration of these systems will help inform innovative preventive and therapeutic interventions. FUNDING: The work was supported by the UK Medical Research Council (MRC; MC-A760-5QX00) and the UK Department for International Development (DFID) under the MRC/DFID Concordat agreement; Bill and Melinda Gates Foundation (OPP 1066932) and the National Institute of Medical Research (NIMR), UK. This network analysis was supported by NIH U54GH009824 [CLD] and NSF OCE-1558453 [CLD].

Coral microbiome manipulation elicits metabolic and genetic restructuring to mitigate heat stress and evade mortality.

Beneficial microorganisms for corals (BMCs) ameliorate environmental stress, but whether they can prevent mortality and the underlying host response mechanisms remains elusive. Here, we conducted omics analyses on the coral Mussismilia hispida exposed to bleaching conditions in a long-term mesocosm experiment and inoculated with a selected BMC consortium or a saline solution placebo. All corals were affected by heat stress, but the observed "post-heat stress disorder" was mitigated by BMCs, signified by patterns of dimethylsulfoniopropionate degradation, lipid maintenance, and coral host transcriptional reprogramming of cellular restructuration, repair, stress protection, and immune genes, concomitant with a 40% survival rate increase and stable photosynthetic performance by the endosymbiotic algae. This study provides insights into the responses that underlie probiotic host manipulation. We demonstrate that BMCs trigger a dynamic microbiome restructuring process that instigates genetic and metabolic alterations in the coral host that eventually mitigate coral bleaching and mortality.

Predicting antimicrobial mechanism-of-action from transcriptomes: A generalizable explainable artificial intelligence approach.

To better combat the expansion of antibiotic resistance in pathogens, new compounds, particularly those with novel mechanisms-of-action [MOA], represent a major research priority in biomedical science. However, rediscovery of known antibiotics demonstrates a need for approaches that accurately identify potential novelty with higher throughput and reduced labor. Here we describe an explainable artificial intelligence classification methodology that emphasizes prediction performance and human interpretability by using a Hierarchical Ensemble of Classifiers model optimized with a novel feature selection algorithm called Clairvoyance; collectively referred to as a CoHEC model. We evaluated our methods using whole transcriptome responses from Escherichia coli challenged with 41 known antibiotics and 9 crude extracts while depositing 122 transcriptomes unique to this study. Our CoHEC model can properly predict the primary MOA of previously unobserved compounds in both purified forms and crude extracts at an accuracy above 99%, while also correctly identifying darobactin, a newly discovered antibiotic, as having a novel MOA. In addition, we deploy our methods on a recent E. coli transcriptomics dataset from a different strain and a Mycobacterium smegmatis metabolomics timeseries dataset showcasing exceptionally high performance; improving upon the performance metrics of the original publications. We not only provide insight into the biological interpretation of our model but also that the concept of MOA is a non-discrete heuristic with diverse effects for different compounds within the same MOA, suggesting substantial antibiotic diversity awaiting discovery within existing MOA.

A synonymous UPF3B variant causing a speech disorder implicates NMD as a regulator of neurodevelopmental disorder gene networks.

Loss-of-function mutations of the X-chromosome gene UPF3B cause male neurodevelopmental disorders (NDDs) via largely unknown mechanisms. We investigated initially by interrogating a novel synonymous UPF3B variant in a male with absent speech. In silico and functional studies using cell lines derived from this individual show altered UPF3B RNA splicing. The resulting mRNA species encodes a frame-shifted protein with a premature termination codon (PTC) predicted to elicit degradation via nonsense-mediated mRNA decay (NMD). UPF3B mRNA was reduced in the cell line, and no UPF3B protein was produced, confirming a loss-of-function allele. UPF3B is itself involved in the NMD mechanism which degrades both PTC-bearing mutant transcripts and also many physiological transcripts. RNAseq analysis showed that ~1.6% of mRNAs exhibited altered expression. These mRNA changes overlapped and correlated with those we identified in additional cell lines obtained from individuals harbouring other UPF3B mutations, permitting us to interrogate pathogenic mechanisms of UPF3B-associated NDDs. We identified 102 genes consistently deregulated across all UPF3B mutant cell lines. Of the 51 upregulated genes, 75% contained an NMD-targeting feature, thus identifying high-confidence direct NMD targets. Intriguingly, 22 of the dysregulated genes encoded known NDD genes, suggesting UPF3B-dependent NMD regulates gene networks critical for cognition and behaviour. Indeed, we show that 78.5% of all NDD genes encode a transcript predicted to be targeted by NMD. These data describe the first synonymous UPF3B mutation in a patient with prominent speech and language disabilities and identify plausible mechanisms of pathology downstream of UPF3B mutations involving the deregulation of NDD-gene networks.

Applications of weighted association networks applied to compositional data in biology.

Next-generation sequencing technologies have generated, and continue to produce, an increasingly large corpus of biological data. The data generated are inherently compositional as they convey only relative information dependent upon the capacity of the instrument, experimental design and technical bias. There is considerable information to be gained through network analysis by studying the interactions between components within a system. Network theory methods using compositional data are powerful approaches for quantifying relationships between biological components and their relevance to phenotype, environmental conditions or other external variables. However, many of the statistical assumptions used for network analysis are not designed for compositional data and can bias downstream results. In this mini-review, we illustrate the utility of network theory in biological systems and investigate modern techniques while introducing researchers to frameworks for implementation. We overview (1) compositional data analysis, (2) data transformations and (3) network theory along with insight on a battery of network types including static-, temporal-, sample-specific- and differential-networks. The intention of this mini-review is not to provide a comprehensive overview of network methods, rather to introduce microbiology researchers to (semi)-unsupervised data-driven approaches for inferring latent structures that may give insight into biological phenomena or abstract mechanics of complex systems.

Transcriptomic Study of Substrate-Specific Transport Mechanisms for Iron and Carbon in the Marine Copiotroph Alteromonas macleodii.

Iron is an essential micronutrient for all microbial growth in the marine environment, and in heterotrophic bacteria, iron is tightly linked to carbon metabolism due to its central role as a cofactor in enzymes of the respiratory chain. Here, we present the iron- and carbon-regulated transcriptomes of a representative marine copiotroph, Alteromonas macleodii ATCC 27126, and characterize its cellular transport mechanisms. ATCC 27126 has distinct metabolic responses to iron and carbon limitation and, accordingly, uses distinct sets of TonB-dependent transporters for the acquisition of iron and carbon. These distinct sets of TonB-dependent transporters were of a similar number, indicating that the diversity of carbon and iron substrates available to ATCC 27126 is of a similar scale. For the first time in a marine bacterium, we have also identified six characteristic inner membrane permeases for the transport of siderophores via an ATPase-independent mechanism. An examination of the distribution of specific TonB-dependent transporters in 31 genomes across the genus Alteromonas points to niche specialization in transport capacity, particularly for iron. We conclude that the substrate-specific bioavailability of both iron and carbon in the marine environment will likely be a key control on the processing of organic matter through the microbial loop.IMPORTANCE As the major facilitators of the turnover of organic matter in the marine environment, the ability of heterotrophic bacteria to acquire specific compounds within the diverse range of dissolved organic matter will affect the regeneration of essential nutrients such as iron and carbon. TonB-dependent transporters are a prevalent cellular tool in Gram-negative bacteria that allow a relatively high-molecular-weight fraction of organic matter to be directly accessed. However, these transporters are not well characterized in marine bacteria, limiting our understanding of the flow of specific substrates through the marine microbial loop. Here, we characterize the TonB-dependent transporters responsible for iron and carbon acquisition in a representative marine copiotroph and examine their distribution across the genus Alteromonas We provide evidence that substrate-specific bioavailability is niche specific, particularly for iron complexes, indicating that transport capacity may serve as a significant control on microbial community dynamics and the resultant cycling of organic matter.

Author Correction: A new antibiotic selectively kills Gram-negative pathogens.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Influence of Substrate Concentration on the Culturability of Heterotrophic Soil Microbes Isolated by High-Throughput Dilution-to-Extinction Cultivation.

The vast majority of microbes inhabiting oligotrophic shallow subsurface soil environments have not been isolated or studied under controlled laboratory conditions. In part, the challenges associated with isolating shallow subsurface microbes may persist because microbes in deeper soils are adapted to low nutrient availability or quality. Here, we use high-throughput dilution-to-extinction culturing to isolate shallow subsurface microbes from a conifer forest in Arizona, USA. We hypothesized that the concentration of heterotrophic substrates in microbiological growth medium would affect which microbial taxa were culturable from these soils. To test this, we diluted cells extracted from soil into one of two custom-designed defined growth media that differed by 100-fold in the concentration of amino acids and organic carbon. Across the two media, we isolated a total of 133 pure cultures, all of which were classified as Actinobacteria or Alphaproteobacteria The substrate availability dictated which actinobacterial phylotypes were culturable but had no significant effect on the culturability of Alphaproteobacteria We isolated cultures that were representative of the most abundant phylotype in the soil microbial community (Bradyrhizobium spp.) and representatives of five of the top 10 most abundant Actinobacteria phylotypes, including Nocardioides spp., Mycobacterium spp., and several other phylogenetically divergent lineages. Flow cytometry of nucleic acid-stained cells showed that cultures isolated on low-substrate medium had significantly lower nucleic acid fluorescence than those isolated on high-substrate medium. These results show that dilution-to-extinction is an effective method to isolate abundant soil microbes and that the concentration of substrates in culture medium influences the culturability of specific microbial lineages.IMPORTANCE Isolating environmental microbes and studying their physiology under controlled conditions are essential aspects of understanding their ecology. Subsurface ecosystems are typically nutrient-poor environments that harbor diverse microbial communities-the majority of which are thus far uncultured. In this study, we use modified high-throughput cultivation methods to isolate subsurface soil microbes. We show that a component of whether a microbe is culturable from subsurface soils is the concentration of growth substrates in the culture medium. Our results offer new insight into technical approaches and growth medium design that can be used to access the uncultured diversity of soil microbes.