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Archaea are widespread in the environment and play fundamental roles in diverse ecosystems; however, characterization of their unique biology requires advanced tools. This is particularly challenging when characterizing gene function. Here, we generate randomly barcoded transposon libraries in the model methanogenic archaeon Methanococcus maripaludis and use high-throughput growth methods to conduct fitness assays (RB-TnSeq) across over 100 unique growth conditions. Using our approach, we identified new genes involved in nutrient utilization and response to oxidative stress. We identified novel genes for the usage of diverse nitrogen sources in M. maripaludis including a putative regulator of alanine deamination and molybdate transporters important for nitrogen fixation. Furthermore, leveraging the fitness data, we inferred that M. maripaludis can utilize additional nitrogen sources including ʟ-glutamine, ᴅ-glucuronamide, and adenosine. Under autotrophic growth conditions, we identified a gene encoding a domain of unknown function (DUF166) that is important for fitness and hypothesize that it has an accessory role in carbon dioxide assimilation. Finally, comparing fitness costs of oxygen versus sulfite stress, we identified a previously uncharacterized class of dissimilatory sulfite reductase-like proteins (Dsr-LP; group IIId) that is important during growth in the presence of sulfite. When overexpressed, Dsr-LP conferred sulfite resistance and enabled use of sulfite as the sole sulfur source. The high-throughput approach employed here allowed for generation of a large-scale data set that can be used as a resource to further understand gene function and metabolism in the archaeal domain.IMPORTANCEArchaea are widespread in the environment, yet basic aspects of their biology remain underexplored. To address this, we apply randomly barcoded transposon libraries (RB-TnSeq) to the model archaeon Methanococcus maripaludis. RB-TnSeq coupled with high-throughput growth assays across over 100 unique conditions identified roles for previously uncharacterized genes, including several encoding proteins with domains of unknown function (DUFs). We also expand on our understanding of carbon and nitrogen metabolism and characterize a group IIId dissimilatory sulfite reductase-like protein as a functional sulfite reductase. This data set encompasses a wide range of additional conditions including stress, nitrogen fixation, amino acid supplementation, and autotrophy, thus providing an extensive data set for the archaeal community to mine for characterizing additional genes of unknown function.

A mechanistic understanding of host-microbe interactions in the gut microbiome is hindered by poorly annotated bacterial genomes. While functional genomics can generate large gene-to-phenotype datasets to accelerate functional discovery, their applications to study gut anaerobes have been limited. For instance, most gain-of-function screens of gut-derived genes have been performed in Escherichia coli and assayed in a small number of conditions. To address these challenges, we develop Barcoded Overexpression BActerial shotgun library sequencing (Boba-seq). We demonstrate the power of this approach by assaying genes from diverse gut Bacteroidales overexpressed in Bacteroides thetaiotaomicron. From hundreds of experiments, we identify new functions and phenotypes for 29 genes important for carbohydrate metabolism or tolerance to antibiotics or bile salts. Highlights include the discovery of a D-glucosamine kinase, a raffinose transporter, and several routes that increase tolerance to ceftriaxone and bile salts through lipid biosynthesis. This approach can be readily applied to develop screens in other strains and additional phenotypic assays.

Castellaniella species have been isolated from a variety of mixed-waste environments including the nitrate and multiple metal-contaminated subsurface at the Oak Ridge Reservation (ORR). Previous studies examining microbial community composition and nitrate removal at ORR during biostimulation efforts reported increased abundances of members of the Castellaniella genus concurrent with increased denitrification rates. Thus, we asked how genomic and abiotic factors control the Castellaniella biogeography at the site to understand how these factors may influence nitrate transformation in an anthropogenically impacted setting. We report the isolation and characterization of several Castellaniella strains from the ORR subsurface. Five of these isolates match at 100% identity (at the 16S rRNA gene V4 region) to two Castellaniella amplicon sequence variants (ASVs), ASV1 and ASV2, that have persisted in the ORR subsurface for at least 2 decades. However, ASV2 has consistently higher relative abundance in samples taken from the site and was also the dominant blooming denitrifier population during a prior biostimulation effort. We found that the ASV2 representative strain has greater resistance to mixed metal stress than the ASV1 representative strains. We attribute this resistance, in part, to the large number of unique heavy metal resistance genes identified on a genomic island in the ASV2 representative genome. Additionally, we suggest that the relatively lower fitness of ASV1 may be connected to the loss of the nitrous oxide reductase (nos) operon (and associated nitrous oxide reductase activity) due to the insertion at this genomic locus of a mobile genetic element carrying copper resistance genes. This study demonstrates the value of integrating genomic, environmental, and phenotypic data to characterize the biogeography of key microorganisms in contaminated sites.

The sources and sinks of nitrous oxide, as control emissions to the atmosphere, are generally poorly constrained for most environmental systems. Initial depth-resolved analysis of nitrous oxide flux from observation wells and the proximal surface within a nitrate contaminated aquifer system revealed high subsurface production but little escape from the surface. To better understand the environmental controls of production and emission at this site, we used a combination of isotopic, geochemical, and molecular analyses to show that chemodenitrification and bacterial denitrification are major sources of nitrous oxide in this subsurface, where low DO, low pH, and high nitrate are correlated with significant nitrous oxide production. Depth-resolved metagenomes showed that consumption of nitrous oxide near the surface was correlated with an enrichment of Clade II nitrous oxide reducers, consistent with a growing appreciation of their importance in controlling release of nitrous oxide to the atmosphere. Our work also provides evidence for the reduction of nitrous oxide at a pH of 4, well below the generally accepted limit of pH 5.

The integration of biology and spacefaring has led to the development of three interrelated fields: Astrobiology, Bioastronautics, and Space Bioprocess Engineering. Astrobiology is concerned with the study of the origin, evolution, distribution, and future of life in the universe, while Bioastronautics focuses on the effects of spaceflight on biological systems, including human physiology and psychology. Space Bioprocess Engineering, on the other hand, deals with the design, deployment, and management of biotechnology for human exploration. This paper highlights the unique contributions of each field and outlines opportunities for biologists to engage in these exciting avenues of research. By providing a clear overview of the major fields of biology and spacefaring, this paper serves as a valuable resource for scientists and researchers interested in exploring the integration of these disciplines.

Microbial communities have evolved to colonize all ecosystems of the planet, from the deep sea to the human gut. Microbes survive by sensing, responding, and adapting to immediate environmental cues. This process is driven by signal transduction proteins such as histidine kinases, which use their sensing domains to bind or otherwise detect environmental cues and transduce signals to adjust internal processes. We hypothesized that an ecosystems unique stimuli leave a sensor fingerprint, able to identify and shed insight on ecosystem conditions. To test this, we collected 20,712 publicly available metagenomes from Host-associated, Environmental, and Engineered ecosystems across the globe. We extracted and clustered the collections nearly 18M unique sensory domains into 113,712 similar groupings with MMseqs2. We built gradient-boosted decision tree machine learning models and found we could classify the ecosystem type (accuracy: 87%) and predict the levels of different physical parameters (R2 score: 83%) using the sensor cluster abundance as features. Feature importance enables identification of the most predictive sensors to differentiate between ecosystems which can lead to mechanistic interpretations if the sensor domains are well annotated. To demonstrate this, a machine learning model was trained to predict patients disease state and used to identify domains related to oxygen sensing present in a healthy gut but missing in patients with abnormal conditions. Moreover, since 98.7% of identified sensor domains are uncharacterized, importance ranking can be used to prioritize sensors to determine what ecosystem function they may be sensing. Furthermore, these new predictive sensors can function as targets for novel sensor engineering with applications in biotechnology, ecosystem maintenance, and medicine.IMPORTANCEMicrobes infect, colonize, and proliferate due to their ability to sense and respond quickly to their surroundings. In this research, we extract the sensory proteins from a diverse range of environmental, engineered, and host-associated metagenomes. We trained machine learning classifiers using sensors as features such that it is possible to predict the ecosystem for a metagenome from its sensor profile. We use the optimized models feature importance to identify the most impactful and predictive sensors in different environments. We next use the sensor profile from human gut metagenomes to classify their disease states and explore which sensors can explain differences between diseases. The sensors most predictive of environmental labels here, most of which correspond to uncharacterized proteins, are a useful starting point for the discovery of important environment signals and the development of possible diagnostic interventions.

Mobile genetic elements (MGEs) like plasmids, viruses, and transposable elements can provide fitness benefits to their hosts for survival in the presence of environmental stressors. Heavy metal resistance genes (HMRGs) are frequently observed on MGEs, suggesting that MGEs may be an important driver of adaptive evolution in environments contaminated with heavy metals. Here, we report the meta-mobilome of the heavy metal-contaminated regions of the Oak Ridge Reservation subsurface. This meta-mobilome was compared with one derived from samples collected from unimpacted regions of the Oak Ridge Reservation subsurface. We assembled 1615 unique circularized DNA elements that we propose to be MGEs. The circular elements from the highly contaminated subsurface were enriched in HMRG clusters relative to those from the nearby unimpacted regions. Additionally, we found that these HMRGs were associated with Gamma and Betaproteobacteria hosts in the contaminated subsurface and potentially facilitate the persistence and dominance of these taxa in this region. Finally, the HMRGs were associated with conjugative elements, suggesting their potential for future lateral transfer. We demonstrate how our understanding of MGE ecology, evolution, and function can be enhanced through the genomic context provided by completed MGE assemblies.

Genome sequencing has revealed an incredible diversity of bacteria and archaea, but there are no fast and convenient tools for browsing across these genomes. It is cumbersome to view the prevalence of homologs for a protein of interest, or the gene neighborhoods of those homologs, across the diversity of the prokaryotes. We developed a web-based tool, fast.genomics, that uses two strategies to support fast browsing across the diversity of prokaryotes. First, the database of genomes is split up. The main database contains one representative from each of the 6,377 genera that have a high-quality genome, and additional databases for each taxonomic order contain up to 10 representatives of each species. Second, homologs of proteins of interest are identified quickly by using accelerated searches, usually in a few seconds. Once homologs are identified, fast.genomics can quickly show their prevalence across taxa, view their neighboring genes, or compare the prevalence of two different proteins. Fast.genomics is available at https://fast.genomics.lbl.gov.

The Escherichia coli genome-scale metabolic model (GEM) is an exemplar systems biology model for the simulation of cellular metabolism. Experimental validation of model predictions is essential to pinpoint uncertainty and ensure continued development of accurate models. Here, we quantified the accuracy of four subsequent E. coli GEMs using published mutant fitness data across thousands of genes and 25 different carbon sources. This evaluation demonstrated the utility of the area under a precision-recall curve relative to alternative accuracy metrics. An analysis of errors in the latest (iML1515) model identified several vitamins/cofactors that are likely available to mutants despite being absent from the experimental growth medium and highlighted isoenzyme gene-protein-reaction mapping as a key source of inaccurate predictions. A machine learning approach further identified metabolic fluxes through hydrogen ion exchange and specific central metabolism branch points as important determinants of model accuracy. This work outlines improved practices for the assessment of GEM accuracy with high-throughput mutant fitness data and highlights promising areas for future model refinement in E. coli and beyond.

Environmental contamination constrains microbial communities impacting diversity and total metabolic activity. The former S-3 Ponds contamination site at Oak Ridge Reservation (ORR), TN, has elevated concentrations of nitric acid and multiple metals from decades of processing nuclear material. To determine the nature of the metal contamination in the sediment, a three-step sequential chemical extraction (BCR) was performed on sediment segments from a core located upgradient (EB271, non-contaminated) and one downgradient (EB106, contaminated) of the S-3 Ponds. The resulting exchangeable, reducing, and oxidizing fractions were analyzed for 18 different elements. Comparison of the two cores revealed changes in operational speciation for several elements caused by the contamination. Those present from the S-3 Ponds, including Al, U, Co, Cu, Ni, and Cd, were not only elevated in concentration in the EB106 core but were also operationally more available with increased mobility in the acidic environment. Other elements, including Mg, Ca, P, V, As, and Mo, were less operationally available in EB106 having decreased concentrations in the exchangeable fraction. The bioavailability of essential macro nutrients Mg, Ca, and P from the two types of sediment was determined using three metal-tolerant bacteria previously isolated from ORR. Mg and Ca were available from both sediments for all three strains; however, P was not bioavailable from either sediment for any strain. The decreased operational speciation of P in contaminated ORR sediment may increase the dependence of the microbial community on other pools of P or select for microorganisms with increased P scavenging capabilities. Hence, the microbial community at the former S-3 Ponds contamination site may be constrained not only by increased toxic metal concentrations but also by the availability of essential elements, including P.

Phages are one of the key ecological drivers of microbial community dynamics, function, and evolution. Despite their importance in bacterial ecology and evolutionary processes, phage genes are poorly characterized, hampering their usage in a variety of biotechnological applications. Methods to characterize such genes, even those critical to the phage life cycle, are labor intensive and are generally phage specific. Here, we develop a systematic gene essentiality mapping method scalable to new phage-host combinations that facilitate the identification of nonessential genes. As a proof of concept, we use an arrayed genome-wide CRISPR interference (CRISPRi) assay to map gene essentiality landscape in the canonical coliphages λ and P1. Results from a single panel of CRISPRi probes largely recapitulate the essential gene roster determined from decades of genetic analysis for lambda and provide new insights into essential and nonessential loci in P1. We present evidence of how CRISPRi polarity can lead to false positive gene essentiality assignments and recommend caution towards interpreting CRISPRi data on gene essentiality when applied to less studied phages. Finally, we show that we can engineer phages by inserting DNA barcodes into newly identified inessential regions, which will empower processes of identification, quantification, and tracking of phages in diverse applications.

Lytic phages can be potent and selective inhibitors of microbial growth and can have profound impacts on microbiome composition and function. However, there is uncertainty about the biogeochemical conditions under which phage predation modulates microbial ecosystem function, particularly in terrestrial systems. Ionic strength is critical for infection of bacteria by many phages, but quantitative data is limited on the ion thresholds for phage infection that can be compared with environmental ion concentrations. Similarly, while carbon composition varies in the environment, we do not know how this variability influences the impact of phage predation on microbiome function. Here, we measured the half-maximal effective concentrations (EC50) of 80 different inorganic ions for the infection of E. coli with two canonical dsDNA and ssRNA phages, T4 and MS2, respectively. Many alkaline earth metals and alkali metals enabled lytic infection but the ionic strength thresholds varied for different ions between phages. Additionally, using a freshwater nitrate-reducing microbiome, we found that the ability of lytic phages to influence nitrate reduction end-products depended upon the carbon source as well as ionic strength. For all phage:host pairs, the ion EC50s for phage infection exceeded the ion concentrations found in many terrestrial freshwater systems. Thus, our findings support a model where phages most influence terrestrial microbial functional ecology in hot spots and hot moments such as metazoan guts, drought influenced soils, or biofilms where ion concentration is locally or transiently elevated and nutrients are available to support the growth of specific phage hosts.

Microbial assembly and metabolic potential in the subsurface critical zone (SCZ) are substantially impacted by subsurface geochemistry and hydrogeology, selecting for microbes distinct from those in surficial soils. In this study, we integrated metagenomics and geochemistry to elucidate how microbial composition and metabolic potential are shaped and impacted by vertical variations in geochemistry and hydrogeology in terrestrial subsurface sediment. A sediment core from an uncontaminated, pristine well at Oak Ridge Field Research Center in Oak Ridge, Tennessee, including the shallow subsurface, vadose zone, capillary fringe, and saturated zone, was used in this study. Our results showed that subsurface microbes were highly localized and that communities were rarely interconnected. Microbial community composition as well as metabolic potential in carbon and nitrogen cycling varied even over short vertical distances. Further analyses indicated a strong depth-related covariation of community composition with a subset of 12 environmental variables. An analysis of dissolved organic carbon (DOC) quality via ultrahigh resolution mass spectrometry suggested that the SCZ was generally a low-carbon environment, with the relative portion of labile DOC decreasing and that of recalcitrant DOC increasing along the depth, selecting microbes from copiotrophs to oligotrophs and also impacting the microbial metabolic potential in the carbon cycle. Our study demonstrates that sediment geochemistry and hydrogeology are vital in the selection of distinct microbial populations and metabolism in the SCZ. IMPORTANCE In this study, we explored the links between geochemical parameters, microbial community structure and metabolic potential across the depth of sediment, including the shallow subsurface, vadose zone, capillary fringe, and saturated zone. Our results revealed that microbes in the terrestrial subsurface can be highly localized, with communities rarely being interconnected along the depth. Overall, our research demonstrates that sediment geochemistry and hydrogeology are vital in the selection of distinct microbial populations and metabolic potential in different depths of subsurface terrestrial sediment. Such studies correlating microbial community analyses and geochemistry analyses, including high resolution mass spectrometry analyses of natural organic carbon, will further the fundamental understanding of microbial ecology and biogeochemistry in subsurface terrestrial ecosystems and will benefit the future development of predictive models on nutrient turnover in these environments.

Single-strand RNA (ssRNA) Fiersviridae phages cause host lysis with a product of single gene (sgl for single-gene lysis; product Sgl) that induces autolysis. Many different Sgls have been discovered, but the molecular targets of only a few have been identified. In this study, we used a high-throughput genetic screen to uncover genome-wide host suppressors of diverse Sgls. In addition to validating known molecular mechanisms, we discovered that the Sgl of PP7, an ssRNA phage of Pseudomonas aeruginosa, targets MurJ, the flippase responsible for lipid II export, previously shown to be the target of the Sgl of coliphage M. These two Sgls, which are unrelated and predicted to have opposite membrane topology, thus represent a case of convergent evolution. We extended the genetic screens to other uncharacterized Sgls and uncovered a common set of multicopy suppressors, suggesting that these Sgls act by the same or similar mechanism.

As renewed interest in human space-exploration intensifies, a coherent and modernized strategy for mission design and planning has become increasingly crucial. Biotechnology has emerged as a promising approach to increase resilience, flexibility, and efficiency of missions, by virtue of its ability to effectively utilize in situ resources and reclaim resources from waste streams. Here we outline four primary mission-classes on Moon and Mars that drive a staged and accretive biomanufacturing strategy. Each class requires a unique approach to integrate biomanufacturing into the existing mission-architecture and so faces unique challenges in technology development. These challenges stem directly from the resources available in a given mission-class-the degree to which feedstocks are derived from cargo and in situ resources-and the degree to which loop-closure is necessary. As mission duration and distance from Earth increase, the benefits of specialized, sustainable biomanufacturing processes also increase. Consequentially, we define specific design-scenarios and quantify the usefulness of in-space biomanufacturing, to guide techno-economics of space-missions. Especially materials emerged as a potentially pivotal target for biomanufacturing with large impact on up-mass cost. Subsequently, we outline the processes needed for development, testing, and deployment of requisite technologies. As space-related technology development often does, these advancements are likely to have profound implications for the creation of a resilient circular bioeconomy on Earth.

Computational models are increasingly used to investigate and predict the complex dynamics of biological and biochemical systems. Nevertheless, governing equations of a biochemical system may not be (fully) known, which would necessitate learning the system dynamics directly from, often limited and noisy, observed data. On the other hand, when expensive models are available, systematic and efficient quantification of the effects of model uncertainties on quantities of interest can be an arduous task. This paper leverages the notion of flow-map (de)compositions to present a framework that can address both of these challenges via learning data-driven models useful for capturing the dynamical behavior of biochemical systems. Data-driven flow-map models seek to directly learn the integration operators of the governing differential equations in a black-box manner, irrespective of structure of the underlying equations. As such, they can serve as a flexible approach for deriving fast-to-evaluate surrogates for expensive computational models of system dynamics, or, alternatively, for reconstructing the long-term system dynamics via experimental observations. We present a data-efficient approach to data-driven flow-map modeling based on polynomial chaos Kriging. The approach is demonstrated for discovery of the dynamics of various benchmark systems and a coculture bioreactor subject to external forcing, as well as for uncertainty quantification of a microbial electrosynthesis reactor. Such data-driven models and analyses of dynamical systems can be paramount in the design and optimization of bioprocesses and integrated biomanufacturing systems.

In the version of this article initially published, the affiliation for Qizhi Zhang and Chris S. Henry was incorrectly shown as the University of Tennessee instead of Argonne National Laboratory. The affiliations have been corrected in the HTML and PDF versions of the article.

BackgroundIntracellular biomacromolecules, such as industrial enzymes and biopolymers, represent an important class of bio-derived products obtained from bacterial hosts. A common key step in the downstream separation of these biomolecules is lysis of the bacterial cell wall to effect release of cytoplasmic contents. Cell lysis is typically achieved either through mechanical disruption or reagent-based methods, which introduce issues of energy demand, material needs, high costs, and scaling problems. Osmolysis, a cell lysis method that relies on hypoosmotic downshock upon resuspension of cells in distilled water, has been applied for bioseparation of intracellular products from extreme halophiles and mammalian cells. However, most industrial bacterial strains are non-halotolerant and relatively resistant to hypoosmotic cell lysis.ResultsTo overcome this limitation, we developed two strategies to increase the susceptibility of non-halotolerant hosts to osmolysis using Cupriavidus necator, a strain often used in electromicrobial production, as a prototypical strain. In one strategy, C. necator was evolved to increase its halotolerance from 1.5% to 3.25% (w/v) NaCl through adaptive laboratory evolution, and genes potentially responsible for this phenotypic change were identified by whole genome sequencing. The evolved halotolerant strain experienced an osmolytic efficiency of 47% in distilled water following growth in 3% (w/v) NaCl. In a second strategy, the cells were made susceptible to osmolysis by knocking out the large-conductance mechanosensitive channel (mscL) gene in C. necator. When these strategies were combined by knocking out the mscL gene from the evolved halotolerant strain, greater than 90% osmolytic efficiency was observed upon osmotic downshock. A modified version of this strategy was applied to E. coli BL21 by deleting the mscL and mscS (small-conductance mechanosensitive channel) genes. When grown in medium with 4% NaCl and subsequently resuspended in distilled water, this engineered strain experienced 75% cell lysis, although decreases in cell growth rate due to higher salt concentrations were observed.ConclusionsOur strategy is shown to be a simple and effective way to lyse cells for the purification of intracellular biomacromolecules and may be applicable in many bacteria used for bioproduction.

The fitness effects of all possible mutations available to an organism largely shape the dynamics of evolutionary adaptation. Yet, whether and how this adaptive landscape changes over evolutionary times, especially upon ecological diversification and changes in community composition, remains poorly understood. We sought to fill this gap by analyzing a stable community of two closely related ecotypes ("L" and "S") shortly after they emerged within the E. coli Long-Term Evolution Experiment (LTEE). We engineered genome-wide barcoded transposon libraries to measure the invasion fitness effects of all possible gene knockouts in the coexisting strains as well as their ancestor, for many different, ecologically relevant conditions. We find consistent statistical patterns of fitness effect variation across both genetic background and community composition, despite the idiosyncratic behavior of individual knockouts. Additionally, fitness effects are correlated with evolutionary outcomes for a number of conditions, possibly revealing shifting patterns of adaptation. Together, our results reveal how ecological and epistatic effects combine to shape the adaptive landscape in a nascent ecological community.

Sulfate-reducing bacteria (SRB) are obligate anaerobes that can couple their growth to the reduction of sulfate. Despite the importance of SRB to global nutrient cycles and their damage to the petroleum industry, our molecular understanding of their physiology remains limited. To systematically provide new insights into SRB biology, we generated a randomly barcoded transposon mutant library in the model SRB Desulfovibrio vulgaris Hildenborough (DvH) and used this genome-wide resource to assay the importance of its genes under a range of metabolic and stress conditions. In addition to defining the essential gene set of DvH, we identified a conditional phenotype for 1,137 non-essential genes. Through examination of these conditional phenotypes, we were able to make a number of novel insights into our molecular understanding of DvH, including how this bacterium synthesizes vitamins. For example, we identified DVU0867 as an atypical L-aspartate decarboxylase required for the synthesis of pantothenic acid, provided the first experimental evidence that biotin synthesis in DvH occurs via a specialized acyl carrier protein and without methyl esters, and demonstrated that the uncharacterized dehydrogenase DVU0826:DVU0827 is necessary for the synthesis of pyridoxal phosphate. In addition, we used the mutant fitness data to identify genes involved in the assimilation of diverse nitrogen sources and gained insights into the mechanism of inhibition of chlorate and molybdate. Our large-scale fitness dataset and RB-TnSeq mutant library are community-wide resources that can be used to generate further testable hypotheses into the gene functions of this environmentally and industrially important group of bacteria.

A protein's function depends on functional residues that determine its binding specificity or its catalytic activity, but these residues are typically not considered when annotating a protein's function. To help biologists investigate the functional residues of proteins, we developed two interactive web-based tools, SitesBLAST and Sites on a Tree. Given a protein sequence, SitesBLAST finds homologs that have known functional residues and shows whether the functional residues are conserved. Sites on a Tree shows how functional residues vary across a protein family by showing them on a phylogenetic tree. These tools are available at http://papers.genomics.lbl.gov/sites. IMPORTANCE For most microbes of interest, a genome sequence is available, but the function of its proteins is not known. Instead, proteins' functions are predicted from their similarity to other protein sequences. Within a protein's sequence, a few key residues are most important for function, such as catalyzing a chemical reaction or determining what it binds. But most function prediction tools do not take these key residues into account. We developed interactive tools for identifying functional residues in a protein sequence by comparing it to proteins with known functional residues. Our tools also make it easy to compare key residues across many similar proteins. This should help biologists check if a protein's function is predicted correctly, or to predict if groups of similar proteins have conserved functions.

Niche environmental conditions influence both the structure and function of microbial communities and the cellular function of individual strains. The terrestrial subsurface is a dynamic and diverse environment that exhibits specific biogeochemical conditions associated with depth, resulting in distinct environmental niches. Here, we present the characterization of seven distinct strains belonging to the genus Arthrobacter isolated from varying depths of a single sediment core and associated groundwater from an adjacent well. We characterized genotype and phenotype of each isolate to connect specific cellular functions and metabolisms to ecotype. Arthrobacter isolates from each ecotype demonstrated functional and genomic capacities specific to their biogeochemical conditions of origin, including laboratory-demonstrated characterization of salinity tolerance and optimal pH, and genes for utilization of carbohydrates and other carbon substrates. Analysis of the Arthrobacter pangenome revealed that it is notably open with a volatile accessory genome compared to previous pangenome studies on other genera, suggesting a high potential for adaptability to environmental niches.

Bacillus cereus strain CPT56D-587-MTF (CPTF) was isolated from the highly contaminated Oak Ridge Reservation (ORR) subsurface. This site is contaminated with high levels of nitric acid and multiple heavy metals. Amplicon sequencing of the 16S rRNA genes (V4 region) in sediment from this area revealed an amplicon sequence variant (ASV) with 100% identity to the CPTF 16S rRNA sequence. Notably, this CPTF-matching ASV had the highest relative abundance in this community survey, with a median relative abundance of 3.77% and comprised 20%-40% of reads in some samples. Pangenomic analysis revealed that strain CPTF has expanded genomic content compared to other B. cereus species-largely due to plasmid acquisition and expansion of transposable elements. This suggests that these features are important for rapid adaptation to native environmental stressors. We connected genotype to phenotype in the context of the unique geochemistry of the site. These analyses revealed that certain genes (e.g. nitrate reductase, heavy metal efflux pumps) that allow this strain to successfully occupy the geochemically heterogenous microniches of its native site are characteristic of the B. cereus species while others such as acid tolerance are mobile genetic element associated and are generally unique to strain CPTF.

BackgroundMany organizations face challenges in managing and analyzing data, especially when relevant datasets arise from multiple sources and methods. Analyzing heterogeneous datasets and additional derived data requires rigorous tracking of their interrelationships and provenance. This task has long been a Grand Challenge of data science and has more recently been formalized in the FAIR principles: that all data objects be Findable, Accessible, Interoperable, and Reusable, both for machines and for people. Adherence to these principles is necessary for proper stewardship of information, for testing regulatory compliance, for measuring the efficiency of processes, and for facilitating reuse of data-analytical frameworks.FindingsWe present the Contextual Ontology-based Repository Analysis Library (CORAL), a platform that greatly facilitates adherence to all 4 of the FAIR principles, including the especially difficult challenge of making heterogeneous datasets Interoperable and Reusable across all parts of a large, long-lasting organization. To achieve this, CORAL's data model requires that data generators extensively document the context for all data, and our tools maintain that context throughout the entire analysis pipeline. CORAL also features a web interface for data generators to upload and explore data, as well as a Jupyter notebook interface for data analysts, both backed by a common API.ConclusionsCORAL enables organizations to build FAIR data types on the fly as they are needed, avoiding the expense of bespoke data modeling. CORAL provides a uniquely powerful platform to enable integrative cross-dataset analyses, generating deeper insights than are possible using traditional analysis tools.

Rhodanobacter has been found as the dominant genus in aquifers contaminated with high concentrations of nitrate and uranium in Oak Ridge, TN, USA. The in situ stimulation of denitrification has been proposed as a potential method to remediate nitrate and uranium contamination. Among the Rhodanobacter species, Rhodanobacter denitrificans strains have been reported to be capable of denitrification and contain abundant metal resistance genes. However, due to the lack of a mutagenesis system in these strains, our understanding of the mechanisms underlying low-pH resistance and the ability to dominate in the contaminated environment remains limited. Here, we developed an in-frame markerless deletion system in two R. denitrificans strains. First, we optimized the growth conditions, tested antibiotic resistance, and determined appropriate transformation parameters in 10 Rhodanobacter strains. We then deleted the upp gene, which encodes uracil phosphoribosyltransferase, in R. denitrificans strains FW104-R3 and FW104-R5. The resulting strains were designated R3_Δupp and R5_Δupp and used as host strains for mutagenesis with 5-fluorouracil (5-FU) resistance as the counterselection marker to generate markerless deletion mutants. To test the developed protocol, the narG gene encoding nitrate reductase was knocked out in the R3_Δupp and R5_Δupp host strains. As expected, the narG mutants could not grow in anoxic medium with nitrate as the electron acceptor. Overall, these results show that the in-frame markerless deletion system is effective in two R. denitrificans strains, which will allow for future functional genomic studies in these strains furthering our understanding of the metabolic and resistance mechanisms present in Rhodanobacter species. IMPORTANCE Rhodanobacter denitrificans is capable of denitrification and is also resistant to toxic heavy metals and low pH. Accordingly, the presence of Rhodanobacter species at a particular environmental site is considered an indicator of nitrate and uranium contamination. These characteristics suggest its future potential application in bioremediation of nitrate or concurrent nitrate and uranium contamination in groundwater ecosystems. Due to the lack of genetic tools in this organism, the mechanisms of low-pH and heavy metal resistance in R. denitrificans strains remain elusive, which impedes its use in bioremediation strategies. Here, we developed a genome editing method in two R. denitrificans strains. This work marks a crucial step in developing Rhodanobacter as a model for studying the diverse mechanisms of low-pH and heavy metal resistance associated with denitrification.

Abstract: Space bioprocess engineering (SBE) is an emerging multi-disciplinary field to design, realize, and manage biologically-driven technologies specifically with the goal of supporting life on long term space missions. SBE considers synthetic biology and bioprocess engineering under the extreme constraints of the conditions of space. A coherent strategy for the long term development of this field is lacking. In this Perspective, we describe the need for an expanded mandate to explore biotechnological needs of the future missions. We then identify several key parameters—metrics, deployment, and training—which together form a pathway towards the successful development and implementation of SBE technologies of the future.

Bacillus cereus strain CPT56D-587-MTF was isolated from nitrate- and toxic metal-contaminated subsurface sediment at the Oak Ridge Reservation (ORR) (Oak Ridge, TN, USA). Here, we report the complete genome sequence of this strain to provide genomic insight into its strategies for survival at this mixed-waste site.

A central question surrounding possible human exploration of Mars is whether crewed missions can be supported by available technologies using in situ resources. Here, we show that photovoltaics-based power systems would be adequate and practical to sustain a crewed outpost for an extended period over a large fraction of the planet’s surface. Climate data were integrated into a radiative transfer model to predict spectrally-resolved solar flux across the Martian surface. This informed detailed balance calculations for solar cell devices that identified optimal bandgap combinations for maximizing production capacity over a Martian year. We then quantified power systems, manufacturing, and agricultural demands for a six-person mission, which revealed that photovoltaics-based power generation would require (Formula presented.) 10 t of carry-along mass, outperforming alternatives over ∼50% of Mars’ surface.

At its current rate, the rise of antimicrobial-resistant (AMR) infections is predicted to paralyze our industries and healthcare facilities while becoming the leading global cause of loss of human life. With limited new antibiotics on the horizon, we need to invest in alternative solutions. Bacteriophages (phages)-viruses targeting bacteria-offer a powerful alternative approach to tackle bacterial infections. Despite recent advances in using phages to treat recalcitrant AMR infections, the field lacks systematic development of phage therapies scalable to different applications. We propose a Phage Foundry framework to establish metrics for phage characterization and to fill the knowledge and technological gaps in phage therapeutics. Coordinated investment in AMR surveillance, sampling, characterization, and data sharing procedures will enable rational exploitation of phages for treatments. A fully realized Phage Foundry will enhance the sharing of knowledge, technology, and viral reagents in an equitable manner and will accelerate the biobased economy.

Rhodanobacter species dominate in the Oak Ridge Reservation (ORR) subsurface environments contaminated with acids, nitrate, metal radionuclides, and other heavy metals. To uncover the genomic features underlying adaptations to these mixed-waste environments and to guide genetic tool development, we sequenced the whole genomes of eight Rhodanobacter strains isolated from the ORR site. The genome sizes ranged from 3.9 to 4.2 Mb harboring 3,695 to 4,035 protein-coding genes and GC contents approximately 67%. Seven strains were classified as R. denitrificans and one strain, FW510-R12, as R. thiooxydans based on full length 16S rRNA sequences. According to gene annotation, the top two Cluster of Orthologous Groups (COGs) with high pan-genome expansion rates (Pan/Core gene ratio) were "replication, recombination and repair" and "defense mechanisms." The denitrifying genes had high DNA homologies except the predicted protein structure variances in NosZ. In contrast, heavy metal resistance genes were diverse with between 7 to 34% of them were located in genomic islands, and these results suggested origins from horizontal gene transfer. Analysis of the methylation patterns in four strains revealed the unique 5mC methylation motifs. Most orthologs (78%) had ratios of nonsynonymous to synonymous substitutions (dN/dS) less than one when compared to the type strain 2APBS1, suggesting the prevalence of negative selection. Overall, the results provide evidence for the important roles of horizontal gene transfer and negative selection in genomic adaptation at the contaminated field site. The complex restriction-modification system genes and the unique methylation motifs in Rhodanobacter strains suggest the potential recalcitrance to genetic manipulation. IMPORTANCE Despite the dominance of Rhodanobacter species in the subsurface of the contaminated Oak Ridge Reservation (ORR) site, very little is known about the mechanisms underlying their adaptions to the various stressors present at ORR. Recently, multiple Rhodanobacter strains have been isolated from the ORR groundwater samples from several wells with varying geochemical properties. Using Illumina, PacBio, and Oxford Nanopore sequencing platforms, we obtained the whole genome sequences of eight Rhodanobacter strains. Comparison of the whole genomes demonstrated the genetic diversity, and analysis of the long nanopore reads revealed the heterogeneity of methylation patterns in strains isolated from the same well. Although all strains contained a complete set of denitrifying genes, the predicted tertiary structures of NosZ differed. The sequence comparison results demonstrate the important roles of horizontal gene transfer and negative selection in adaptation. In addition, these strains may be recalcitrant to genetic manipulation due to the complex restriction-modification systems and methylations.

Magnetotactic bacteria (MTB) are a phylogenetically diverse group of bacteria remarkable for their ability to biomineralize magnetite (Fe3O4) or greigite (Fe3S4) in organelles called magnetosomes. The majority of genes required for magnetosome formation are encoded by a magnetosome gene island (MAI). Most previous genetic studies of MTB have focused on the MAI, using screens to identify key MAI genes or targeted genetics to isolate specific genes and their function in one specific growth condition. This is the first study that has taken an unbiased approach to look at many different growth conditions to reveal key genes both inside and outside the MAI. Here, we conducted random barcoded transposon mutagenesis (RB-TnSeq) in Magnetospirillum magneticum AMB-1. We generated a library of 184,710 unique strains in a wild-type background, generating ∼34 mutant strains for each gene. RB-TnSeq also allowed us to determine the essential gene set of AMB-1 under standard laboratory growth conditions. To pinpoint novel genes that are important for magnetosome formation, we subjected the library to magnetic selection screens under varied growth conditions. We compared biomineralization under standard growth conditions to biomineralization under high-iron and anaerobic conditions, respectively. Strains with transposon insertions in the MAI gene mamT had an exacerbated biomineralization defect under both high-iron and anaerobic conditions compared to standard conditions, adding to our knowledge of the role of MamT in magnetosome formation. Mutants in an ex-MAI gene, amb4151, are more magnetic than wild-type cells under anaerobic conditions. All three of these phenotypes were validated by creating a markerless deletion strain of the gene and evaluating with TEM imaging. Overall, our results indicate that growth conditions affect which genes are required for biomineralization and that some MAI genes may have more nuanced functions than was previously understood. IMPORTANCE Magnetotactic bacteria (MTB) are a group of bacteria that can form nano-sized crystals of magnetic minerals. MTB are likely an important part of their ecosystems, because they can account for up to a third of the microbial biomass in an aquatic habitat and consume large amounts of iron, potentially impacting the iron cycle. The ecology of MTB is relatively understudied; however, the cell biology and genetics of MTB have been studied for decades. Here, we leverage genetic studies of MTB to inform environmental studies. We expand the genetic toolset for studying MTB in the lab and identify novel genes, or functions of genes, that have an impact on biomineralization.

Microbial-mediated nitrate removal from groundwater is widely recognized as the predominant mechanism for nitrate attenuation in contaminated aquifers and is largely dependent on the presence of a carbon-bearing electron donor. The repeated exposure of a natural microbial community to an electron donor can result in the sustained ability of the community to remove nitrate; this phenomenon has been clearly demonstrated at the laboratory scale. However, in situ demonstrations of this ability are lacking. For this study, ethanol (electron donor) was repeatedly injected into a groundwater well (treatment) for six consecutive weeks to establish the sustained ability of a microbial community to remove nitrate. A second well (control) located upgradient was not injected with ethanol during this time. The treatment well demonstrated strong evidence of sustained ability as evident by ethanol, nitrate, and subsequent sulfate removal up to 21, 64, and 68%, respectively, as compared to the conservative tracer (bromide) upon consecutive exposures. Both wells were then monitored for six additional weeks under natural (no injection) conditions. During the final week, ethanol was injected into both treatment and control wells. The treatment well demonstrated sustained ability as evident by ethanol and nitrate removal up to 20 and 21%, respectively, as compared to bromide, whereas the control did not show strong evidence of nitrate removal (5% removal). Surprisingly, the treatment well did not indicate a sustained and selective enrichment of a microbial community. These results suggested that the predominant mechanism(s) of sustained ability likely exist at the enzymatic- and/or genetic-levels. The results of this study demonstrated the in situ ability of a microbial community to remove nitrate can be sustained in the prolonged absence of an electron donor.

To discover novel catabolic enzymes and transporters, we combined high-throughput genetic data from 29 bacteria with an automated tool to find gaps in their catabolic pathways. GapMind for carbon sources automatically annotates the uptake and catabolism of 62 compounds in bacterial and archaeal genomes. For the compounds that are utilized by the 29 bacteria, we systematically examined the gaps in GapMind's predicted pathways, and we used the mutant fitness data to find additional genes that were involved in their utilization. We identified novel pathways or enzymes for the utilization of glucosamine, citrulline, myo-inositol, lactose, and phenylacetate, and we annotated 299 diverged enzymes and transporters. We also curated 125 proteins from published reports. For the 29 bacteria with genetic data, GapMind finds high-confidence paths for 85% of utilized carbon sources. In diverse bacteria and archaea, 38% of utilized carbon sources have high-confidence paths, which was improved from 27% by incorporating the fitness-based annotations and our curation. GapMind for carbon sources is available as a web server (http://papers.genomics.lbl.gov/carbon) and takes just 30 seconds for the typical genome.

Exometabolomics is an approach to assess how microorganisms alter, or react to their environments through the depletion and production of metabolites. It allows the examination of how soil microbes transform the small molecule metabolites within their environment, which can be used to study resource competition and cross-feeding. This approach is most powerful when used with defined media that enable tracking of all metabolites. However, microbial growth media have traditionally been developed for the isolation and growth of microorganisms but not metabolite utilization profiling through Liquid Chromatography Tandem Mass Spectrometry (LC-MS/MS). Here, we describe the construction of a defined medium, the Northen Lab Defined Medium (NLDM), that not only supports the growth of diverse soil bacteria but also is defined and therefore suited for exometabolomic experiments. Metabolites included in NLDM were selected based on their presence in R2A medium and soil, elemental stoichiometry requirements, as well as knowledge of metabolite usage by different bacteria. We found that NLDM supported the growth of 108 of the 110 phylogenetically diverse (spanning 36 different families) soil bacterial isolates tested and all of its metabolites were trackable through LC-MS/MS analysis. These results demonstrate the viability and utility of the constructed NLDM medium for growing and characterizing diverse microbial isolates and communities.

Though bacteriophages (phages) are known to play a crucial role in bacterial fitness and virulence, our knowledge about the genetic basis of their interaction, cross-resistance and host-range is sparse. Here, we employed genome-wide screens in Salmonella enterica serovar Typhimurium to discover host determinants involved in resistance to eleven diverse lytic phages including four new phages isolated from a therapeutic phage cocktail. We uncovered 301 diverse host factors essential in phage infection, many of which are shared between multiple phages demonstrating potential cross-resistance mechanisms. We validate many of these novel findings and uncover the intricate interplay between RpoS, the virulence-associated general stress response sigma factor and RpoN, the nitrogen starvation sigma factor in phage cross-resistance. Finally, the infectivity pattern of eleven phages across a panel of 23 genome sequenced Salmonella strains indicates that additional constraints and interactions beyond the host factors uncovered here define the phage host range.

Microbes drive myriad ecosystem processes, but under strong influence from viruses. Because studying viruses in complex systems requires different tools than those for microbes, they remain underexplored. To combat this, we previously aggregated double-stranded DNA (dsDNA) virus analysis capabilities and resources into 'iVirus' on the CyVerse collaborative cyberinfrastructure. Here we substantially expand iVirus's functionality and accessibility, to iVirus 2.0, as follows. First, core iVirus apps were integrated into the Department of Energy's Systems Biology KnowledgeBase (KBase) to provide an additional analytical platform. Second, at CyVerse, 20 software tools (apps) were upgraded or added as new tools and capabilities. Third, nearly 20-fold more sequence reads were aggregated to capture new data and environments. Finally, documentation, as "live" protocols, was updated to maximize user interaction with and contribution to infrastructure development. Together, iVirus 2.0 serves as a uniquely central and accessible analytical platform for studying how viruses, particularly dsDNA viruses, impact diverse microbial ecosystems.

Bacterial communities in water, soil, and humans play an essential role in environmental ecology and human health. PCR-based amplicon analysis, such as 16S rRNA sequencing, is a fundamental tool for quantifying and studying microbial composition, dynamics, and interactions. However, given the complexity of microbial communities, a substantial number of samples becomes necessary for analyses that parse the factors that determine microbial composition. A common bottleneck in performing these kinds of experiments is genomic DNA (gDNA) extraction, which is time-consuming, expensive, and often biased based on the types of species present. Direct PCR method is a potentially simpler and more accurate alternative to gDNA extraction methods that do not require the intervening purification step. In this study, we evaluated three variations of direct PCR methods using diverse heterogeneous bacterial cultures, including both Gram-positive and Gram-negative species, ZymoBIOMICS microbial community standards, and groundwater. By comparing direct PCR methods with DNeasy Blood and Tissue Kits for microbial isolates and DNeasy PowerSoil Kits for microbial communities, we found that a specific variant of the direct PCR method exhibits an overall efficiency comparable to that of the conventional DNeasy PowerSoil protocol in the circumstances we tested. We also found that the method showed higher efficiency for extracting gDNA from the Gram-negative strains compared to DNeasy Blood and Tissue protocol. This direct PCR method is 1,600 times less expensive ($0.34 for 96 samples) and 10 times simpler (15 min hands-on time for 96 samples) than the DNeasy PowerSoil protocol. The direct PCR method can also be fully automated and is compatible with small-volume samples, thereby permitting scaling of samples and replicates needed to support high-throughput large-scale bacterial community analysis. IMPORTANCE Understanding bacterial interactions and assembly in complex microbial communities using 16S rRNA sequencing normally requires a large experimental load. However, the current DNA extraction methods, including cell disruption and genomic DNA purification, are normally biased, costly, time-consuming, labor-intensive, and not amenable to miniaturization by droplets or 1,536-well plates due to the significant DNA loss during the purification step for tiny-volume and low-cell-density samples. A direct PCR method could potentially solve these problems. In this study, we developed a direct PCR method which exhibits similar efficiency as the widely used method, the DNeasy PowerSoil protocol, while being 1,600 times less expensive and 10 times faster to execute. This simple, cost-effective, and automation-friendly direct-PCR-based 16S rRNA sequencing method allows us to study the dynamics, microbial interaction, and assembly of various microbial communities in a high-throughput fashion.

To uncover metal toxicity targets and defense mechanisms of the facultative anaerobe Pantoea sp. strain MT58 (MT58), we used a multiomic strategy combining two global techniques, random bar code transposon site sequencing (RB-TnSeq) and activity-based metabolomics. MT58 is a metal-tolerant Oak Ridge Reservation (ORR) environmental isolate that was enriched in the presence of metals at concentrations measured in contaminated groundwater at an ORR nuclear waste site. The effects of three chemically different metals found at elevated concentrations in the ORR contaminated environment were investigated: the cation Al3+, the oxyanion CrO42-, and the oxycation UO22+. Both global techniques were applied using all three metals under both aerobic and anaerobic conditions to elucidate metal interactions mediated through the activity of metabolites and key genes/proteins. These revealed that Al3+ binds intracellular arginine, CrO42- enters the cell through sulfate transporters and oxidizes intracellular reduced thiols, and membrane-bound lipopolysaccharides protect the cell from UO22+ toxicity. In addition, the Tol outer membrane system contributed to the protection of cellular integrity from the toxic effects of all three metals. Likewise, we found evidence of regulation of lipid content in membranes under metal stress. Individually, RB-TnSeq and metabolomics are powerful tools to explore the impact various stresses have on biological systems. Here, we show that together they can be used synergistically to identify the molecular actors and mechanisms of these pertubations to an organism, furthering our understanding of how living systems interact with their environment. IMPORTANCE Studying microbial interactions with their environment can lead to a deeper understanding of biological molecular mechanisms. In this study, two global techniques, RB-TnSeq and activity metabolomics, were successfully used to probe the interactions between a metal-resistant microorganism, Pantoea sp. strain MT58, and metals contaminating a site where the organism can be located. A number of novel metal-microbe interactions were uncovered, including Al3+ toxicity targeting arginine synthesis, which could lead to a deeper understanding of the impact Al3+ contamination has on microbial communities as well as its impact on higher-level organisms, including plants for whom Al3+ contamination is an issue. Using multiomic approaches like the one described here is a way to further our understanding of microbial interactions and their impacts on the environment overall.

Microbial-mediated nitrate removal from groundwater is widely recognized as the predominant mechanism for nitrate attenuation in contaminated aquifers and is largely dependent on the presence of a carbon-bearing electron donor. The repeated exposure of a natural microbial community to an electron donor can result in the sustained ability of the community to remove nitrate; this phenomenon has been clearly demonstrated at the laboratory scale. However, in situ demonstrations of this ability are lacking. For this study, ethanol (electron donor) was repeatedly injected into a groundwater well (treatment) for six consecutive weeks to establish the sustained ability of a microbial community to remove nitrate. A second well (control) located upgradient was not injected with ethanol during this time. The treatment well demonstrated strong evidence of sustained ability as evident by ethanol, nitrate, and subsequent sulfate removal up to 21, 64, and 68%, respectively, as compared to the conservative tracer (bromide) upon consecutive exposures. Both wells were then monitored for six additional weeks under natural (no injection) conditions. During the final week, ethanol was injected into both treatment and control wells. The treatment well demonstrated sustained ability as evident by ethanol and nitrate removal up to 20 and 21%, respectively, as compared to bromide, whereas the control did not show strong evidence of nitrate removal (5% removal). Surprisingly, the treatment well did not indicate a sustained and selective enrichment of a microbial community. These results suggested that the predominant mechanism(s) of sustained ability likely exist at the enzymatic- and/or genetic-levels. The results of this study demonstrated the in situ ability of a microbial community to remove nitrate can be sustained in the prolonged absence of an electron donor.

Space missions have always assumed that the risk of spacecraft malfunction far outweighs the risk of human system failure. This assumption breaks down for longer duration exploration missions and exposes vulnerabilities in space medical systems. Space agencies can no longer reduce the majority of the human health and performance risks through crew members selection process and emergency re-supply or evacuation. No mature medical solutions exist to address this risk. With recent advances in biotechnology, there is promise for lessening this risk by augmenting a space pharmacy with a biologically-based space foundry for the on-demand manufacturing of high-value medical products. Here we review the challenges and opportunities of molecular pharming, the production of pharmaceuticals in plants, as the basis of a space medical foundry to close the risk gap in current space medical systems. Plants have long been considered to be an important life support object in space and can now also be viewed as programmable factories in space. Advances in molecular pharming-based space foundries will have widespread applications in promoting simple and accessible pharmaceutical manufacturing on Earth.

Aspergillus flavus is an opportunistic pathogen of crops, including peanuts and maize, and is the second leading cause of aspergillosis in immunocompromised patients. A. flavus is also a major producer of the mycotoxin, aflatoxin, a potent carcinogen, which results in significant crop losses annually. The A. flavus isolate NRRL 3357 was originally isolated from peanut and has been used as a model organism for understanding the regulation and production of secondary metabolites, such as aflatoxin. A draft genome of NRRL 3357 was previously constructed, enabling the development of molecular tools and for understanding population biology of this particular species. Here, we describe an updated, near complete, telomere-to-telomere assembly and re-annotation of the eight chromosomes of A. flavus NRRL 3357 genome, accomplished via long-read PacBio and Oxford Nanopore technologies combined with Illumina short-read sequencing. A total of 13,715 protein-coding genes were predicted. Using RNA-seq data, a significant improvement was achieved in predicted 5' and 3' untranslated regions, which were incorporated into the new gene models.

Tailocins are bactericidal protein complexes produced by a wide variety of bacteria that kill closely related strains and may play a role in microbial community structure. Thanks to their high specificity, tailocins have been proposed as precision antibacterial agents for therapeutic applications. Compared to tailed phages, with whom they share an evolutionary and morphological relationship, bacterially produced tailocins kill their host upon production but producing strains display resistance to self-intoxication. Though lipopolysaccharide (LPS) has been shown to act as a receptor for tailocins, the breadth of factors involved in tailocin sensitivity, and the mechanisms behind resistance to self-intoxication, remain unclear. Here, we employed genome-wide screens in four non-model pseudomonads to identify mutants with altered fitness in the presence of tailocins produced by closely related pseudomonads. Our mutant screens identified O-antigen composition and display as most important in defining sensitivity to our tailocins. In addition, the screens suggest LPS thinning as a mechanism by which resistant strains can become more sensitive to tailocins. We validate many of these novel findings, and extend these observations of tailocin sensitivity to 130 genome-sequenced pseudomonads. This work offers insights into tailocin-bacteria interactions, informing the potential use of tailocins in microbiome manipulation and antibacterial therapy.