Biology subjects

Arkin, A. P.

Publications and source records attributed to Arkin, A. P..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

Emergence and disruption of cooperativity in a denitrifying microbial community

Anthropogenic perturbations to the nitrogen cycle, primarily through use of synthetic fertilizers, is driving an unprecedented increase in the emission of nitrous oxide (N2O), a potent greenhouse gas and an ozone depleting substance, causing urgency in identifying the sources and sinks of N2O. Microbial denitrification is a primary contributor to biotic production of N2O in anoxic regions of soil, marine systems, and wastewater treatment facilities. Here, through comprehensive genome analysis, we show that pathway partitioning is a ubiquitous mechanism of complete denitrification within microbial communities. We have investigated mechanisms and consequences of process partitioning of denitrification through detailed physiological characterization and kinetic modeling of a synthetic community of Rhodanobacter R12 and Acidovorax 3H11. We have discovered that these two bacterial isolates, from a heavily nitrate (NO3-) contaminated superfund site, complete denitrification through the exchange of nitrite (NO2-) and nitric oxide (NO). The process partitioning of denitrification and other processes, including amino acid metabolism, contribute to increased cooperativity within this denitrifying community. We demonstrate that certain contexts, such as high NO3-, cause unbalanced growth of community members, due to differences in their substrate utilization kinetics. The altered growth characteristics of community members drives accumulation of toxic NO2-, which disrupts denitrification causing N2O off gassing.

microbiology↗

bioRxiv2024

Improving the annotation of amino acid biosynthesis pathways: GapMind 2024

We previously described GapMind, an automated web-based tool for annotating amino acid biosynthesis pathways in bacterial and archaeal genomes. We used GapMind to identify gaps in biosynthetic pathways and systematically used comparative genomics and high-throughput genetics to identify candidate genes to fill these gaps. We confirmed the activity of ten of the proposed enzymes by using cross-species complementation assays. Highlights include a novel route to glycine, two families that can replace phosphoserine phosphatase, an alternative N-succinyl-L,L-diaminopimelate desuccinylase, an alternative N-acetylornithine deacetylase, and a bifunctional MetB/MetC. We updated GapMind to include these additional enzymes. Across 208 prokaryotes that have high-quality genomes and can grow in minimal media, the average number of unexplained missing steps or gaps in amino acid biosynthesis dropped from 1.4 per genome to 0.7 per genome. The majority of remaining gaps involve the gain or loss of phosphate groups.

microbiology↗

bioRxiv2024

Dual transposon sequencing (Dual Tn-seq) to probe genome-wide genetic interactions

Understanding gene function on a genome-wide scale is a fundamental goal in biology. With the advent of next-generation sequencing, high-throughput methods such as transposon sequencing (Tn- seq) were developed to measure fitness of single deletion mutants en masse. Nevertheless, gene redundancy complicates these approaches, as inactivating genes individually may not produce discernable phenotypes. Here, we report Dual Tn-seq, a technique for simultaneously assaying fitness of a comprehensive pool of double mutants. Dual Tn-seq couples random barcode transposon-site sequencing (RB Tn-seq) with the Cre-lox system, allowing us to determine the fitness of {approx}68% of all possible double mutant combinations in the human pathogen Streptococcus pneumoniae. Genetic interactions identified from {approx}1.4 billion double mutants uncovered new avenues in widely conserved biochemical pathways, exemplified by the discovery of a new CTP synthase and a regulator of peptidoglycan biosynthesis. Since Dual Tn-seq has very few requirements, it can be readily adapted to diverse organisms.

microbiology↗

bioRxiv2024

High-throughput protein characterization by complementation using DNA barcoded fragment libraries

Our ability to predict, control, or design biological function is fundamentally limited by poorly annotated gene function. This can be particularly challenging in non-model systems. Accordingly, there is motivation for new high-throughput methods for accurate functional annotation. Here, we use complementation of auxotrophs and DNA barcode sequencing (Coaux-Seq) to enable high-throughput characterization of protein function. Fragment libraries from eleven genetically diverse bacteria were tested in twenty different auxotrophic strains of Escherichia coli to identify genes that complement missing biochemical activity. Although assay effectiveness ranged with respect to source genome, with 41% of expected enzymes recovered, even distant E. coli relatives like Bacillus subtilis and Bacteroides thetaiotaomicron showed success. Coaux-Seq provided the first experimental validation for 53 proteins, of which 11 are less than 40% identical to an experimentally characterized protein on an amino acid basis. Among unexpected function identified was a sulfate uptake transporter, an O-succinylhomoserine sulfhydrylase for methionine synthesis, and an aminotransferase. We also identified instances of cross-feeding wherein protein overexpression and nearby non-auxotrophic strains enabled growth. Altogether, Coaux-Seqs utility is demonstrated, with future applications in ecology, health, and engineering.

genomics↗

bioRxiv2024

Interactive Tools for Functional Annotation of Bacterial Genomes

Automated annotations of protein function are error-prone because of our lack of knowledge of protein functions. For example, it is often impossible to predict the correct substrate for an enzyme or a transporter. Furthermore, much of the knowledge that we do have about the functions of proteins is missing from the underlying databases. We discuss how to use interactive tools to quickly find different kinds of information relevant to a proteins function. Combining these tools often allows us to infer a proteins function. Ideally, accurate annotations would allow us to predict a bacteriums capabilities from its genome sequence, but in practice, this remains challenging. We describe interactive tools that infer potential capabilities from a genome sequence or that search a genome to find proteins that might perform a specific function of interest.

bioinformatics↗

bioRxiv2024

High-throughput genetics enables identification of nutrient utilization and accessory energy metabolism genes in a model methanogen

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 provide the first evidence that M. maripaludis can utilize the nitrogen sources L-glutamine, D-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 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 dataset that can be used as a resource to further understand gene function and metabolism in the archaeal domain. Significance StatementArchaea 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 dataset encompasses a wide range of additional conditions including stress, nitrogen fixation, amino acid supplementation, and autotrophy; thus, providing an extensive dataset for the archaeal community to mine for characterizing additional genes of unknown function.

microbiology↗

bioRxiv2024

Genomic and environmental controls on Castellaniella biogeography in an anthropogenically disturbed subsurface

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 to 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. ORR Castellaniella strains showed a higher degree of genetic diversification than those originating from non-ORR sites, which we attribute to the multitude of extreme stressors faced in the ORR subsurface. 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 two 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.

microbiology↗

bioRxiv2024

Niche exclusion of a lung pathogen in mice with designed probiotic communities

For years, the airway microbiota have been theorized to be gatekeepers of respiratory health, as pathogens entering the airway make contact with resident microbes prior to or coincident with their interaction with host cells. Thus, modification of the native airway community may serve as a means of altering the local environment in favor of health. In this work, we hypothesize that synthetic bacterial communities introduced into the airway can serve as prophylactic countermeasures against infection by Burkholderia thailandensis in mice. We demonstrate that understanding of antagonistic interactions between a pathogen and airway microbiota in vitro can guide identification of probiotics with protective capabilities in vivo. Specifically, we show that niche overlap between the probiotic and pathogen is indicative of probiotic performance in vivo. This work serves as a foundation for the rational design of probiotic communities for protection against and treatment of respiratory infections.

microbiology↗

bioRxiv2023

Mixed Waste Contamination Selects for a Mobile Genetic Element Population Enriched in Multiple Heavy Metal Resistance Genes

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 (ORR) subsurface. This meta-mobilome was compared to one derived from samples collected from unimpacted regions of the ORR subsurface. We assembled 1,615 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.

microbiology↗

bioRxiv2023

ModelSEED v2: High-throughput genome-scale metabolic model reconstruction with enhanced energy biosynthesis pathway prediction

Since the release of ModelSEED in 2010, the systems biology research community has used the ModelSEED genome-scale metabolic model reconstruction pipeline to build over 200,000 draft metabolic reconstructions that support hundreds of publications. Here we describe the first comprehensive update to this reconstruction tool, with new features such as (i) a dramatically improved representation of energy metabolism, which ensures that models produce accurate amounts of ATP per mol of nutrient consumed; (ii) a new template for Archaea model reconstruction; and (iii) a significantly improved curation of all metabolic pathways with mappings to RAST subsystems annotations. We applied the improved pipeline to build and analyze core and genome-scale models for Archaea and Bacteria genomes in KEGG. The new ModelSEED pipeline generates larger models that possess more reactions and genes and require fewer gap-filled reactions. In addition, we see conserved patterns in the ATP biosynthesis mechanism across phylogeny, and identify clades where our understanding of energy biosynthesis is still poor. ModelSEED v2 is available through KBase and the ModelSEED website (https://modelseed.org/), which supports reconstruction, gap-filling, flux balance analysis and model export through a modern web interface.

systems biology↗

bioRxiv2023

A fast comparative genome browser for diverse bacteria and archaea

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. ImportanceNow that we have genome sequences for tens of thousands of species of bacteria and archaea, we would like to predict the functions of their proteins. One common strategy is comparative genomics: by considering which genomes contain similar proteins, and which proteins are often encoded near each other, we can often guess the proteins functions. But there was no good way to do these analyses quickly. We built a website that performs them in a few seconds. We used two strategies to speed up the key step, which is finding similar proteins. First, we split up the database of genomes into a main database with one representative for each genus, and sub-databases for each taxonomic order. Either way, searches against fewer genomes are much faster. Second, we use accelerated searches to find similar proteins, with only a slight loss of sensitivity.

bioinformatics↗

bioRxiv2023

Genome-wide CRISPRi knockdown to map gene essentiality landscape in coliphages {lambda} and P1

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 non-essential genes. As proof of concept, we use a catalytically inactive Cas12a mediated genome-wide CRISPRi assay to determine the essential genes in the canonical coliphages {lambda} 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.

microbiology↗

bioRxiv2023

Geochemical constraints on bacteriophage infectivity in terrestrial environments

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 can proceed and modulate microbial ecosystem function, particularly in terrestrial systems. Ionic strength is known to be critical for infection of bacteria by many phages, but there is limited quantitative data on ion thresholds for phage infection that can be compared with environmental ion concentrations. Similarly, while carbon composition varies in terrestrial environments, we know little of which carbon sources favor or disfavor phage infection and how these higher order interactions impact 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. We found that many alkaline earth metals and alkali metals enabled successful lytic infection but that the ionic strength thresholds varied for different ions between phages. Additionally, using a freshwater nitrate reducing microbiome, we found that the ability of lytic phage to influence nitrate reduction end-products was dependent on the carbon source as well as the ion concentration. For all phage:host pairs we tested, the ion EC50s for phage infection we measured exceed the ion concentrations found in many terrestrial freshwater systems. Thus, our findings support a model where the influence of phages on terrestrial microbial functional ecology is greatest in hot spots and hot moments such as metazoan guts, drought influenced soils, or biofilms where ion concentration is locally or transiently elevated and carbon source composition is of a sufficiently low complexity to enrich for a dominant phage susceptible population. SignificanceViral-prokaryote dynamics greatly influence microbial ecology and the earths biogeochemical cycles. Thus, identifying the key environmental controls on phage predation is critical for predictive microbial ecology. Here we conduct laboratory experiments that implicate ionic strength and carbon composition as major controls on phage interactions with bacterial hosts in terrestrial microbiomes. We propose a model in which terrestrial phage predation is most favored in drought impacted soils and in higher ionic strength environments such as metazoan guts or between adjacent cells in biofilms.

microbiology↗

bioRxiv2023

Many Families of Lids for TonB-dependent Transporters in Bacteroides

Most TonB-dependent transporters in Bacteroides belong to the SusC family and work with an outer-membrane lipoprotein from the SusD family that functions like a lid. But the best-studied strain, B. thetaiotaomicron VPI-5482, also contains 18 TonB-dependent transporters that are not from the SusC family. We identified six families of putative lids for these transporters. The putative lids are lipoproteins that are encoded next to TonB-dependent transporters, but they are not homologous to SusD. AlphaFold-Multimer predicts that the putative lids bind the outer faces of the corresponding TonB-dependent receptors. Genetic data suggests that members of four of these families are required for the activity of the corresponding TonB-dependent receptors. Overall, of the 18 TonB-dependent receptors that do not belong to the SusC family, we identified alternate lids for nine.

microbiology↗

bioRxiv2023

Critical assessment of E. coli genome-scale metabolic model with high-throughput mutant fitness data

The E. coli genome-scale metabolic model (GEM) is a gold standard for the simulation of cellular metabolism. Experimental validation of model predictions is essential to pinpoint model uncertainty and ensure continued development of accurate models. Here we assessed the accuracy of the E. coli GEM using published mutant fitness data for the growth of gene knockout mutants across thousands of genes and 25 different carbon sources. We explored the progress of the E. coli GEM versions over time and further investigated errors in the latest version of the model (iML1515). We observed that model size is increasing while prediction accuracy is decreasing. We identified several adjustments that improve model accuracy - the addition of vitamins/cofactors and re-assignment of reaction reversibility and isoenzyme gene to reaction mapping. Furthermore, we applied a machine learning approach which identified hydrogen ion exchange and central metabolism branch points as important determinants of model accuracy. Continued integration of experimental data to validate GEMs will improve predictive modeling of the mapping from genotype to metabolic phenotype in E. coli and beyond. Synopsis O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY E. coli genome-scale metabolic model flux balance analysis (FBA) prediction accuracy was quantified with published experimental data assaying gene knockout mutant growth across different carbon sources. Insights into model development trends and sources of inaccuracy were revealed. O_LIModel representational power (size) has been increasing over time, while accuracy has been decreasing. C_LIO_LIAdding vitamins/cofactors to the model environment and re-assigning reaction reversibility and isoenzyme gene-to-reaction mapping improves correspondence between model predictions and experimental data. C_LIO_LIMachine learning reveals hydrogen ion exchange and central metabolism branch points as important features in the determination of model accuracy. C_LI

systems biology↗

bioRxiv2022

Towards Environmental Control of Microbiomes

Microbial communities have consequential effects on health and the environment yet remain uncontrollable due to their complex dynamics. Ecological modeling offers a platform to overcome their nonlinear and interconnected nature but traditionally does not account for context-dependence. Here, we extend the generalized Lotka-Volterra (gLV) model to accommodate a varying environment by identifying how environmental changes alter species growth rates and interactions in a manner that predicts full community trajectories across environmental gradients. We identify key environment-varying interactions within a synthetic community derived from the Oryzae sativa rhizosphere, and demonstrate how variations in the environment change fixed point compositions and rates of convergence. With our model, we simulate how precise perturbations of the environment can offer improvements in an optimal control problem of driving a community to a target composition. We show that environmental perturbation can minimize the total species input (direct species perturbation) and greatly expand the set of initial states from which a desired target can be reached despite stochasticity. This work demonstrates that a formal perspective on environmental influence of community dynamics is valuable for not only understanding seasonal changes or anthropogenic manipulations, but is critical for improving control of the microbiome.

systems biology↗

bioRxiv2022

Functional screens of barcoded expression libraries uncover new gene functions in carbon utilization among gut Bactereroidales

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 developed 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 identified new functions and novel phenotypes for 29 genes involved in 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 bile salts through lipid biosynthesis. This approach can be readily applied to develop screens in other strains and additional phenotypic assay types.

microbiology↗

bioRxiv2022

Eliminating Genes for a Two Component System Increases PHB Productivity in Cupriavidus basilensis 4G11 Under PHB Suppressing, Non-Stress Conditions

Species of bacteria from the genus Cupriavidus are known, in part, for their ability to produce high amounts of poly-hydroxybutyrate (PHB) making them attractive candidate bioplastic producers. The native production of PHB occurs during periods of metabolic stress, and the process regulating the initiation of PHB accumulation in these organisms is not fully understood. Screening an RB-TnSeq transposon library of Cupriavidus basilensis 4G11 allowed us to identify two genes of an apparent, uncharacterized two component system which, when omitted from the genome, are capable of increased PHB productivity in balanced, non-stress growth conditions. We observe average increases in PHB productivity of 56% and 41% relative to the wildtype parent strain, upon deleting each of two genes individually from the genome. The increased PHB phenotype disappears, however, in nitrogen-free unbalanced growth conditions suggesting the phenotype is specific to fast-growing, replete, non-stress growth. Bioproduction modeling suggests this phenotype could be due to a decreased reliance on metabolic stress induced by nitrogen limitation to initiate PHB production in the mutant strains. Such strains may allow for the use of single stage, continuous bioreactor systems, which are far simpler than PHB bioproduction schemes used previously. Bioproductivity modeling suggests that omitting this regulation in the cells may increase PHB productivity up to 24% relative to the wildtype organism when using single stage continuous systems. This work furthermore expands our understanding of the regulation of PHB accumulation in Cupriavidus, in particular the initiation of this process upon transition into unbalanced growth regimes.

genomics↗