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Recombination of short DNA fragments via horizontal gene transfer (HGT) can introduce beneficial alleles, create genomic disharmony through negative epistasis, and create adaptive gene combinations through positive epistasis. For non-core (accessory) genes, the negative epistatic cost is likely to be minimal because the incoming genes have not co-evolved with the recipient genome and are frequently observed as tightly linked cassettes with major effects. By contrast, interspecific recombination in the core genome is expected to be rare because disruptive allelic replacement is likely to introduce negative epistasis. Why then is homologous recombination common in the core of bacterial genomes? To understand this enigma, we take advantage of an exceptional model system, the common enteric pathogens Campylobacter jejuni and C. coli that are known for very high magnitude interspecies gene flow in the core genome. As expected, HGT does indeed disrupt co-adapted allele pairings, indirect evidence of negative epistasis. However, multiple HGT events enable recovery of the genome’s co-adaption between introgressing alleles, even in core metabolism genes (e.g., formate dehydrogenase). These findings demonstrate that, even for complex traits, genetic coalitions can be decoupled, transferred, and independently reinstated in a new genetic background—facilitating transition between fitness peaks. In this example, the two-step recombinational process is associated with C. coli that are adapted to the agricultural niche.

Recombination of short DNA fragments via horizontal gene transfer (HGT) can introduce beneficial alleles, create genomic disharmony through negative epistasis, and create adaptive gene combinations through positive epistasis. For non-core (accessory) genes, the negative epistatic cost is likely to be minimal because the incoming genes have not co-evolved with the recipient genome and are frequently observed as tightly linked cassettes with major effects. By contrast, interspecific recombination in the core genome is expected to be rare because disruptive allelic replacement is likely to introduce negative epistasis. Why then is homologous recombination common in the core of bacterial genomes? To understand this enigma, we take advantage of an exceptional model system, the common enteric pathogens Campylobacter jejuni and C. coli that are known for very high magnitude interspecies gene flow in the core genome. As expected, HGT does indeed disrupt co-adapted allele pairings, indirect evidence of negative epistasis. However, multiple HGT events enable recovery of the genome’s co-adaption between introgressing alleles, even in core metabolism genes (e.g., formate dehydrogenase). These findings demonstrate that, even for complex traits, genetic coalitions can be decoupled, transferred, and independently reinstated in a new genetic background—facilitating transition between fitness peaks. In this example, the two-step recombinational process is associated with C. coli that are adapted to the agricultural niche.

Recombination of short DNA fragments via horizontal gene transfer (HGT) can introduce beneficial alleles, create genomic disharmony through negative epistasis, and create adaptive gene combinations through positive epistasis. For non-core (accessory) genes, the negative epistatic cost is likely to be minimal because the incoming genes have not co-evolved with the recipient genome and are frequently observed as tightly linked cassettes with major effects. By contrast, interspecific recombination in the core genome is expected to be rare because disruptive allelic replacement is likely to introduce negative epistasis. Why then is homologous recombination common in the core of bacterial genomes? To understand this enigma, we take advantage of an exceptional model system, the common enteric pathogens Campylobacter jejuni and C. coli that are known for very high magnitude interspecies gene flow in the core genome. As expected, HGT does indeed disrupt co-adapted allele pairings, indirect evidence of negative epistasis. However, multiple HGT events enable recovery of the genome’s co-adaption between introgressing alleles, even in core metabolism genes (e.g., formate dehydrogenase). These findings demonstrate that, even for complex traits, genetic coalitions can be decoupled, transferred, and independently reinstated in a new genetic background—facilitating transition between fitness peaks. In this example, the two-step recombinational process is associated with C. coli that are adapted to the agricultural niche.

Recombination of short DNA fragments via horizontal gene transfer (HGT) can introduce beneficial alleles, create genomic disharmony through negative epistasis, and create adaptive gene combinations through positive epistasis. For non-core (accessory) genes, the negative epistatic cost is likely to be minimal because the incoming genes have not co-evolved with the recipient genome and are frequently observed as tightly linked cassettes with major effects. By contrast, interspecific recombination in the core genome is expected to be rare because disruptive allelic replacement is likely to introduce negative epistasis. Why then is homologous recombination common in the core of bacterial genomes? To understand this enigma, we take advantage of an exceptional model system, the common enteric pathogens Campylobacter jejuni and C. coli that are known for very high magnitude interspecies gene flow in the core genome. As expected, HGT does indeed disrupt co-adapted allele pairings, indirect evidence of negative epistasis. However, multiple HGT events enable recovery of the genome’s co-adaption between introgressing alleles, even in core metabolism genes (e.g., formate dehydrogenase). These findings demonstrate that, even for complex traits, genetic coalitions can be decoupled, transferred, and independently reinstated in a new genetic background—facilitating transition between fitness peaks. In this example, the two-step recombinational process is associated with C. coli that are adapted to the agricultural niche.

Coccidioidomycosis is a common fungal disease that is endemic to arid and semi-arid regions of both American continents. Coccidioides immitis and Coccidioides posadasii are the etiological agents of the disease, also known as Valley Fever. For several decades, the C. posadasii strain Silveira has been used widely in vaccine studies, is the source strain for production of diagnostic antigens, and is a widely used experimental strain for functional studies. In 2009, the genome was sequenced using Sanger sequencing technology, and a draft assembly and annotation were made available. In this study, the genome of the Silveira strain was sequenced using single molecule real-time sequencing PacBio technology, assembled into chromosomal-level contigs, genotyped, and the genome was reannotated using sophisticated and curated in silico tools. This high-quality genome sequencing effort has improved our understanding of chromosomal structure, gene set annotation, and lays the groundwork for identification of structural variants (e.g. transversions, translocations, and copy number variants), assessment of gene gain and loss, and comparison of transposable elements in future phylogenetic and population genomics studies.

The COVID-19 pandemic has triggered the first widespread vaccination campaign against a coronavirus. Many vaccinated subjects are previously naive to SARS-CoV-2; however, almost all have previously encountered other coronaviruses (CoVs), and the role of this immunity in shaping the vaccine response remains uncharacterized. Here, we use longitudinal samples and highly multiplexed serology to identify mRNA-1273 vaccine-induced antibody responses against a range of CoV Spike epitopes, in both phylogenetically conserved and non-conserved regions. Whereas reactivity to SARS-CoV-2 epitopes shows a delayed but progressive increase following vaccination, we observe distinct kinetics for the endemic CoV homologs at conserved sites in Spike S2: these become detectable sooner and decay at later time points. Using homolog-specific antibody depletion and alanine-substitution experiments, we show that these distinct trajectories reflect an evolving cross-reactive response that can distinguish rare, polymorphic residues within these epitopes. Our results reveal mechanisms for the formation of antibodies with broad reactivity against CoVs.

Coccidioidomycosis is a common fungal disease that is endemic to arid and semi-arid regions of both American continents. Coccidioides immitis and Coccidioides posadasii are the etiological agents of the disease, also known as Valley Fever. For several decades, the C. posadasii strain Silveira has been used widely in vaccine studies, is the source strain for production of diagnostic antigens, and is a widely used experimental strain for functional studies. In 2009, the genome was sequenced using Sanger sequencing technology, and a draft assembly and annotation were made available. In this study, the genome of the Silveira strain was sequenced using single molecule real-time sequencing PacBio technology, assembled into chromosomal-level contigs, genotyped, and the genome was reannotated using sophisticated and curated in silico tools. This high-quality genome sequencing effort has improved our understanding of chromosomal structure, gene set annotation, and lays the groundwork for identification of structural variants (e.g. transversions, translocations, and copy number variants), assessment of gene gain and loss, and comparison of transposable elements in future phylogenetic and population genomics studies.

The COVID-19 pandemic has triggered the first widespread vaccination campaign against a coronavirus. Many vaccinated subjects are previously naive to SARS-CoV-2; however, almost all have previously encountered other coronaviruses (CoVs), and the role of this immunity in shaping the vaccine response remains uncharacterized. Here, we use longitudinal samples and highly multiplexed serology to identify mRNA-1273 vaccine-induced antibody responses against a range of CoV Spike epitopes, in both phylogenetically conserved and non-conserved regions. Whereas reactivity to SARS-CoV-2 epitopes shows a delayed but progressive increase following vaccination, we observe distinct kinetics for the endemic CoV homologs at conserved sites in Spike S2: these become detectable sooner and decay at later time points. Using homolog-specific antibody depletion and alanine-substitution experiments, we show that these distinct trajectories reflect an evolving cross-reactive response that can distinguish rare, polymorphic residues within these epitopes. Our results reveal mechanisms for the formation of antibodies with broad reactivity against CoVs.

Francisella tularensis, the bacterium that causes the zoonosis tularemia, and its genetic near neighbor species, can be difficult or impossible to cultivate from complex samples. Thus, there is a lack of genomic information for these species that has, among other things, limited the development of robust detection assays for F. tularensis that are both specific and sensitive. The objective of this study was to develop and validate approaches to capture, enrich, sequence, and analyze Francisella DNA present in DNA extracts generated from complex samples. RNA capture probes were designed based upon the known pan genome of F. tularensis and other diverse species in the family Francisellaceae. Probes that targeted genomic regions also present in non-Francisellaceae species were excluded, and probes specific to particular Francisella species or phylogenetic clades were identified. The capture-enrichment system was then applied to diverse, complex DNA extracts containing low-level Francisella DNA, including human clinical tularemia samples, environmental samples (i.e., animal tissue and air filters), and whole ticks/tick cell lines, which was followed by sequencing of the enriched samples. Analysis of the resulting data facilitated rigorous and unambiguous confirmation of the detection of F. tularensis or other Francisella species in complex samples, identification of mixtures of different Francisella species in the same sample, analysis of gene content (e.g., known virulence and antimicrobial resistance loci), and high-resolution whole genome-based genotyping. The benefits of this capture-enrichment system include: even very low target DNA can be amplified; it is culture-independent, reducing exposure for research and/or clinical personnel and allowing genomic information to be obtained from samples that do not yield isolates; and the resulting comprehensive data not only provide robust means to confirm the presence of a target species in a sample, but also can provide d

Francisella tularensis, the bacterium that causes the zoonosis tularemia, and its genetic near neighbor species, can be difficult or impossible to cultivate from complex samples. Thus, there is a lack of genomic information for these species that has, among other things, limited the development of robust detection assays for F. tularensis that are both specific and sensitive. The objective of this study was to develop and validate approaches to capture, enrich, sequence, and analyze Francisella DNA present in DNA extracts generated from complex samples. RNA capture probes were designed based upon the known pan genome of F. tularensis and other diverse species in the family Francisellaceae. Probes that targeted genomic regions also present in non-Francisellaceae species were excluded, and probes specific to particular Francisella species or phylogenetic clades were identified. The capture-enrichment system was then applied to diverse, complex DNA extracts containing low-level Francisella DNA, including human clinical tularemia samples, environmental samples (i.e., animal tissue and air filters), and whole ticks/tick cell lines, which was followed by sequencing of the enriched samples. Analysis of the resulting data facilitated rigorous and unambiguous confirmation of the detection of F. tularensis or other Francisella species in complex samples, identification of mixtures of different Francisella species in the same sample, analysis of gene content (e.g., known virulence and antimicrobial resistance loci), and high-resolution whole genome-based genotyping. The benefits of this capture-enrichment system include: even very low target DNA can be amplified; it is culture-independent, reducing exposure for research and/or clinical personnel and allowing genomic information to be obtained from samples that do not yield isolates; and the resulting comprehensive data not only provide robust means to confirm the presence of a target species in a sample, but also can provide d

Francisella tularensis, the bacterium that causes the zoonosis tularemia, and its genetic near neighbor species, can be difficult or impossible to cultivate from complex samples. Thus, there is a lack of genomic information for these species that has, among other things, limited the development of robust detection assays for F. tularensis that are both specific and sensitive. The objective of this study was to develop and validate approaches to capture, enrich, sequence, and analyze Francisella DNA present in DNA extracts generated from complex samples. RNA capture probes were designed based upon the known pan genome of F. tularensis and other diverse species in the family Francisellaceae. Probes that targeted genomic regions also present in non-Francisellaceae species were excluded, and probes specific to particular Francisella species or phylogenetic clades were identified. The capture-enrichment system was then applied to diverse, complex DNA extracts containing low-level Francisella DNA, including human clinical tularemia samples, environmental samples (i.e., animal tissue and air filters), and whole ticks/tick cell lines, which was followed by sequencing of the enriched samples. Analysis of the resulting data facilitated rigorous and unambiguous confirmation of the detection of F. tularensis or other Francisella species in complex samples, identification of mixtures of different Francisella species in the same sample, analysis of gene content (e.g., known virulence and antimicrobial resistance loci), and high-resolution whole genome-based genotyping. The benefits of this capture-enrichment system include: even very low target DNA can be amplified; it is culture-independent, reducing exposure for research and/or clinical personnel and allowing genomic information to be obtained from samples that do not yield isolates; and the resulting comprehensive data not only provide robust means to confirm the presence of a target species in a sample, but also can provide d

Francisella tularensis, the bacterium that causes the zoonosis tularemia, and its genetic near neighbor species, can be difficult or impossible to cultivate from complex samples. Thus, there is a lack of genomic information for these species that has, among other things, limited the development of robust detection assays for F. tularensis that are both specific and sensitive. The objective of this study was to develop and validate approaches to capture, enrich, sequence, and analyze Francisella DNA present in DNA extracts generated from complex samples. RNA capture probes were designed based upon the known pan genome of F. tularensis and other diverse species in the family Francisellaceae. Probes that targeted genomic regions also present in non-Francisellaceae species were excluded, and probes specific to particular Francisella species or phylogenetic clades were identified. The capture-enrichment system was then applied to diverse, complex DNA extracts containing low-level Francisella DNA, including human clinical tularemia samples, environmental samples (i.e., animal tissue and air filters), and whole ticks/tick cell lines, which was followed by sequencing of the enriched samples. Analysis of the resulting data facilitated rigorous and unambiguous confirmation of the detection of F. tularensis or other Francisella species in complex samples, identification of mixtures of different Francisella species in the same sample, analysis of gene content (e.g., known virulence and antimicrobial resistance loci), and high-resolution whole genome-based genotyping. The benefits of this capture-enrichment system include: even very low target DNA can be amplified; it is culture-independent, reducing exposure for research and/or clinical personnel and allowing genomic information to be obtained from samples that do not yield isolates; and the resulting comprehensive data not only provide robust means to confirm the presence of a target species in a sample, but also can provide d

Francisella tularensis, the bacterium that causes the zoonosis tularemia, and its genetic near neighbor species, can be difficult or impossible to cultivate from complex samples. Thus, there is a lack of genomic information for these species that has, among other things, limited the development of robust detection assays for F. tularensis that are both specific and sensitive. The objective of this study was to develop and validate approaches to capture, enrich, sequence, and analyze Francisella DNA present in DNA extracts generated from complex samples. RNA capture probes were designed based upon the known pan genome of F. tularensis and other diverse species in the family Francisellaceae. Probes that targeted genomic regions also present in non-Francisellaceae species were excluded, and probes specific to particular Francisella species or phylogenetic clades were identified. The capture-enrichment system was then applied to diverse, complex DNA extracts containing low-level Francisella DNA, including human clinical tularemia samples, environmental samples (i.e., animal tissue and air filters), and whole ticks/tick cell lines, which was followed by sequencing of the enriched samples. Analysis of the resulting data facilitated rigorous and unambiguous confirmation of the detection of F. tularensis or other Francisella species in complex samples, identification of mixtures of different Francisella species in the same sample, analysis of gene content (e.g., known virulence and antimicrobial resistance loci), and high-resolution whole genome-based genotyping. The benefits of this capture-enrichment system include: even very low target DNA can be amplified; it is culture-independent, reducing exposure for research and/or clinical personnel and allowing genomic information to be obtained from samples that do not yield isolates; and the resulting comprehensive data not only provide robust means to confirm the presence of a target species in a sample, but also can provide d

Coccidioidomycosis is a common fungal disease that is endemic to arid and semi-arid regions of both American continents. Coccidioides immitis and C. posadasii are the etiological agents of the disease, also known as Valley Fever. For several decades, the C. posadasii strain Silveira has been used widely in vaccine studies, is the source strain for production of diagnostic antigens, and is a widely used experimental strain for functional studies. In 2009, the genome was sequenced using Sanger sequencing technology, and a draft assembly and annotation was made available. In the current study, the genome of the Silveira strain was sequenced using Single Molecule Real Time Sequencing (SMRT) PacBio technology, assembled into chromosomal-level contigs, genotyped, and the genome was reannotated using sophisticated and curated in silico tools. This high-quality genome sequencing effort has improved our understanding of chromosomal structure, gene set annotation, and lays the groundwork for identification of structural variants (e.g. transversions, translocations, and copy number variants), assessment of gene gain and loss, and comparison of transposable elements in future phylogenetic and population genomics studies.

Coccidioidomycosis is a common fungal disease that is endemic to arid and semi-arid regions of both American continents. Coccidioides immitis and C. posadasii are the etiological agents of the disease, also known as Valley Fever. For several decades, the C. posadasii strain Silveira has been used widely in vaccine studies, is the source strain for production of diagnostic antigens, and is a widely used experimental strain for functional studies. In 2009, the genome was sequenced using Sanger sequencing technology, and a draft assembly and annotation was made available. In the current study, the genome of the Silveira strain was sequenced using Single Molecule Real Time Sequencing (SMRT) PacBio technology, assembled into chromosomal-level contigs, genotyped, and the genome was reannotated using sophisticated and curated in silico tools. This high-quality genome sequencing effort has improved our understanding of chromosomal structure, gene set annotation, and lays the groundwork for identification of structural variants (e.g. transversions, translocations, and copy number variants), assessment of gene gain and loss, and comparison of transposable elements in future phylogenetic and population genomics studies.

Viruses and plasmids (invasive mobile genetic elements (iMGEs)) have important roles in shaping microbial communities, but their dynamic interactions with CRISPR-based immunity remain unresolved. We analysed generation-resolved iMGE–host dynamics spanning one and a half years in a microbial consortium from a biological wastewater treatment plant using integrated meta-omics. We identified 31 bacterial metagenome-assembled genomes encoding complete CRISPR–Cas systems and their corresponding iMGEs. CRISPR-targeted plasmids outnumbered their bacteriophage counterparts by at least fivefold, highlighting the importance of CRISPR-mediated defence against plasmids. Linear modelling of our time-series data revealed that the variation in plasmid abundance over time explained more of the observed community dynamics than phages. Community-scale CRISPR-based plasmid–host and phage–host interaction networks revealed an increase in CRISPR-mediated interactions coinciding with a decrease in the dominant ‘Candidatus Microthrix parvicella’ population. Protospacers were enriched in sequences targeting genes involved in the transmission of iMGEs. Understanding the factors shaping the fitness of specific populations is necessary to devise control strategies for undesirable species and to predict or explain community-wide phenotypes.

Viruses and plasmids (invasive mobile genetic elements (iMGEs)) have important roles in shaping microbial communities, but their dynamic interactions with CRISPR-based immunity remain unresolved. We analysed generation-resolved iMGE–host dynamics spanning one and a half years in a microbial consortium from a biological wastewater treatment plant using integrated meta-omics. We identified 31 bacterial metagenome-assembled genomes encoding complete CRISPR–Cas systems and their corresponding iMGEs. CRISPR-targeted plasmids outnumbered their bacteriophage counterparts by at least fivefold, highlighting the importance of CRISPR-mediated defence against plasmids. Linear modelling of our time-series data revealed that the variation in plasmid abundance over time explained more of the observed community dynamics than phages. Community-scale CRISPR-based plasmid–host and phage–host interaction networks revealed an increase in CRISPR-mediated interactions coinciding with a decrease in the dominant ‘Candidatus Microthrix parvicella’ population. Protospacers were enriched in sequences targeting genes involved in the transmission of iMGEs. Understanding the factors shaping the fitness of specific populations is necessary to devise control strategies for undesirable species and to predict or explain community-wide phenotypes.

The development of reliable, mixed-culture biotechnological processes hinges on understanding how microbial ecosystems respond to disturbances. Here we reveal extensive phenotypic plasticity and niche complementarity in oleaginous microbial populations from a biological wastewater treatment plant. We perform meta-omics analyses (metagenomics, metatranscriptomics, metaproteomics and metabolomics) on in situ samples over 14 months at weekly intervals. Based on 1,364 de novo metagenome-assembled genomes, we uncover four distinct fundamental niche types. Throughout the time-series, we observe a major, transient shift in community structure, coinciding with substrate availability changes. Functional omics data reveals extensive variation in gene expression and substrate usage amongst community members. Ex situ bioreactor experiments confirm that responses occur within five hours of a pulse disturbance, demonstrating rapid adaptation by specific populations. Our results show that community resistance and resilience are a function of phenotypic plasticity and niche complementarity, and set the foundation for future ecological engineering efforts.

Viruses and plasmids (invasive mobile genetic elements (iMGEs)) have important roles in shaping microbial communities, but their dynamic interactions with CRISPR-based immunity remain unresolved. We analysed generation-resolved iMGE–host dynamics spanning one and a half years in a microbial consortium from a biological wastewater treatment plant using integrated meta-omics. We identified 31 bacterial metagenome-assembled genomes encoding complete CRISPR–Cas systems and their corresponding iMGEs. CRISPR-targeted plasmids outnumbered their bacteriophage counterparts by at least fivefold, highlighting the importance of CRISPR-mediated defence against plasmids. Linear modelling of our time-series data revealed that the variation in plasmid abundance over time explained more of the observed community dynamics than phages. Community-scale CRISPR-based plasmid–host and phage–host interaction networks revealed an increase in CRISPR-mediated interactions coinciding with a decrease in the dominant ‘Candidatus Microthrix parvicella’ population. Protospacers were enriched in sequences targeting genes involved in the transmission of iMGEs. Understanding the factors shaping the fitness of specific populations is necessary to devise control strategies for undesirable species and to predict or explain community-wide phenotypes.

Viruses and plasmids (invasive mobile genetic elements (iMGEs)) have important roles in shaping microbial communities, but their dynamic interactions with CRISPR-based immunity remain unresolved. We analysed generation-resolved iMGE–host dynamics spanning one and a half years in a microbial consortium from a biological wastewater treatment plant using integrated meta-omics. We identified 31 bacterial metagenome-assembled genomes encoding complete CRISPR–Cas systems and their corresponding iMGEs. CRISPR-targeted plasmids outnumbered their bacteriophage counterparts by at least fivefold, highlighting the importance of CRISPR-mediated defence against plasmids. Linear modelling of our time-series data revealed that the variation in plasmid abundance over time explained more of the observed community dynamics than phages. Community-scale CRISPR-based plasmid–host and phage–host interaction networks revealed an increase in CRISPR-mediated interactions coinciding with a decrease in the dominant ‘Candidatus Microthrix parvicella’ population. Protospacers were enriched in sequences targeting genes involved in the transmission of iMGEs. Understanding the factors shaping the fitness of specific populations is necessary to devise control strategies for undesirable species and to predict or explain community-wide phenotypes.

The development of reliable, mixed-culture biotechnological processes hinges on understanding how microbial ecosystems respond to disturbances. Here we reveal extensive phenotypic plasticity and niche complementarity in oleaginous microbial populations from a biological wastewater treatment plant. We perform meta-omics analyses (metagenomics, metatranscriptomics, metaproteomics and metabolomics) on in situ samples over 14 months at weekly intervals. Based on 1,364 de novo metagenome-assembled genomes, we uncover four distinct fundamental niche types. Throughout the time-series, we observe a major, transient shift in community structure, coinciding with substrate availability changes. Functional omics data reveals extensive variation in gene expression and substrate usage amongst community members. Ex situ bioreactor experiments confirm that responses occur within five hours of a pulse disturbance, demonstrating rapid adaptation by specific populations. Our results show that community resistance and resilience are a function of phenotypic plasticity and niche complementarity, and set the foundation for future ecological engineering efforts.

Viruses and plasmids (invasive mobile genetic elements (iMGEs)) have important roles in shaping microbial communities, but their dynamic interactions with CRISPR-based immunity remain unresolved. We analysed generation-resolved iMGE–host dynamics spanning one and a half years in a microbial consortium from a biological wastewater treatment plant using integrated meta-omics. We identified 31 bacterial metagenome-assembled genomes encoding complete CRISPR–Cas systems and their corresponding iMGEs. CRISPR-targeted plasmids outnumbered their bacteriophage counterparts by at least fivefold, highlighting the importance of CRISPR-mediated defence against plasmids. Linear modelling of our time-series data revealed that the variation in plasmid abundance over time explained more of the observed community dynamics than phages. Community-scale CRISPR-based plasmid–host and phage–host interaction networks revealed an increase in CRISPR-mediated interactions coinciding with a decrease in the dominant ‘Candidatus Microthrix parvicella’ population. Protospacers were enriched in sequences targeting genes involved in the transmission of iMGEs. Understanding the factors shaping the fitness of specific populations is necessary to devise control strategies for undesirable species and to predict or explain community-wide phenotypes.

The development of reliable, mixed-culture biotechnological processes hinges on understanding how microbial ecosystems respond to disturbances. Here we reveal extensive phenotypic plasticity and niche complementarity in oleaginous microbial populations from a biological wastewater treatment plant. We perform meta-omics analyses (metagenomics, metatranscriptomics, metaproteomics and metabolomics) on in situ samples over 14 months at weekly intervals. Based on 1,364 de novo metagenome-assembled genomes, we uncover four distinct fundamental niche types. Throughout the time-series, we observe a major, transient shift in community structure, coinciding with substrate availability changes. Functional omics data reveals extensive variation in gene expression and substrate usage amongst community members. Ex situ bioreactor experiments confirm that responses occur within five hours of a pulse disturbance, demonstrating rapid adaptation by specific populations. Our results show that community resistance and resilience are a function of phenotypic plasticity and niche complementarity, and set the foundation for future ecological engineering efforts.

Coccidioidomycosis, or Valley fever, is caused by two species of dimorphic fungi. Based on molecular phylogenetic evidence, the genus Coccidioides contains two reciprocally monophyletic species: C. immitis and C. posadasii. However, phenotypic variation between species has not been deeply investigated. We therefore explored differences in growth rate under various conditions. A collection of 39 C. posadasii and 46 C. immitis isolates, representing the full geographical range of the two species, was screened for mycelial growth rate at 37 °C and 28 °C on solid media. The radial growth rate was measured for 16 days on yeast extract agar. A linear mixed effect model was used to compare the growth rate of C. posadasii and C. immitis at 37 °C and 28 °C, respectively. C. posadasii grew significantly faster at 37 °C, when compared to C. immitis; whereas both species had similar growth rates at 28 °C. These results indicate thermotolerance differs between these two species. As the ecological niche has not been well-described for Coccidioides spp., and disease variability between species has not been shown, the evolutionary pressure underlying the adaptation is unclear. However, this research reveals the first significant phenotypic difference between the two species that directly applies to ecological research.

Coccidioides posadasii is a pathogenic fungus that causes coccidioidomycosis in many arid regions of the Americas. One of these regions is bordered by the Caribbean Sea, and the surrounding landscape may play an important role in the dispersion of C. posadasii across South America through southeastern Mexico, Honduras, Guatemala, and Venezuela. Comparative phylogenomic analyses of C. posadasii reveal that clinical strains from Venezuela are genetically distinct from the North American populations found in (i) Arizona and (ii) Texas, Mexico, and the rest of South America (TX/MX/SA). We find evidence for admixture between the Venezuela and the North American populations of C. posadasii in Central America. Additionally, the proportion of Venezuelan alleles in the admixed population decreases as latitude (and distance from Venezuela) increases. Our results indicate that the population in Venezuela may have been subjected to a recent bottleneck and shows a strong population structure. This analysis provides insight into potential for Coccidioides spp. to invade new regions.IMPORTANCE Valley Fever is a fungal disease caused by two species of fungi: Coccidioides immitis and C. posadasii These fungi are found throughout the arid regions of North and South America; however, our understanding of genetic diversity and disease in South America is limited. In this report, we analyze 10 new genomes of Coccidioides posadasii from regions bordering the Caribbean Sea. We show that these populations are distinct and that isolates from Venezuela are likely a result of a recent bottleneck. These data point to patterns that might be observed when investigating recently established populations.

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

Microbial communities are strongly shaped by the niche breadths of their constituent populations. However, a detailed understanding of microbial niche ecology is typically lacking. Integrated multi-omic analyses of host- or environment-derived samples offer the prospect of resolving fundamental and realised niches in situ. In turn, this is considered a prerequisite for niche engineering in order to drive an individual population or a community towards a specific phenotype, e.g., improvement of a biotechnological process. Here, we sampled floating islets on the surface of an activated sludge tank in a time-series spanning 51 time-points over 14 months. Multi-omics datasets (metagenomics, metatranscriptomics, metaproteomics, and (meta-)metabolomics) were generated for all time-points. Leveraging nucleotide sequencing data, we analyzed the community structure and reconstructed genomes for specific populations of interest. Moreover, based on their metabolic potential, three major groups emerged, serving as proxies for their respective fundamental niches . Time-resolved linkage of the proteomic and transcriptomic data to the reconstructed genomes revealed a fine-grained picture of niche realization. In particular, environmental factors (temperature, metabolites, oxygen) were significantly associated with gene expression of individual populations. Furthermore, we subjected the community to controlled oxygen conditions (stable or dynamic) in a bioreactor experiment and measured the transcriptomic response. Our results suggest short-term adaptations of populations of interest with respect to lipid metabolism, among other pathways. In conclusion, our work demonstrates how longitudinal multi-omic datasets can be integrated in order to further our understanding of microbial niche ecology within a biotechnological process with potential applications beyond waste water treatment.

Microbial communities are strongly shaped by the niche breadths of their constituent populations. However, a detailed understanding of microbial niche ecology is typically lacking. Integrated multi-omic analyses of host- or environment-derived samples offer the prospect of resolving fundamental and realised niches in situ. In turn, this is considered a prerequisite for niche engineering in order to drive an individual population or a community towards a specific phenotype, e.g., improvement of a biotechnological process. Here, we sampled floating islets on the surface of an activated sludge tank in a time-series spanning 51 time-points over 14 months. Multi-omics datasets (metagenomics, metatranscriptomics, metaproteomics, and (meta-)metabolomics) were generated for all time-points. Leveraging nucleotide sequencing data, we analyzed the community structure and reconstructed genomes for specific populations of interest. Moreover, based on their metabolic potential, three major groups emerged, serving as proxies for their respective fundamental niches . Time-resolved linkage of the proteomic and transcriptomic data to the reconstructed genomes revealed a fine-grained picture of niche realization. In particular, environmental factors (temperature, metabolites, oxygen) were significantly associated with gene expression of individual populations. Furthermore, we subjected the community to controlled oxygen conditions (stable or dynamic) in a bioreactor experiment and measured the transcriptomic response. Our results suggest short-term adaptations of populations of interest with respect to lipid metabolism, among other pathways. In conclusion, our work demonstrates how longitudinal multi-omic datasets can be integrated in order to further our understanding of microbial niche ecology within a biotechnological process with potential applications beyond waste water treatment.

Microbial communities are strongly shaped by the niche breadths of their constituent populations. However, a detailed understanding of microbial niche ecology is typically lacking. Integrated multi-omic analyses of host- or environment-derived samples offer the prospect of resolving fundamental and realised niches in situ. In turn, this is considered a prerequisite for niche engineering in order to drive an individual population or a community towards a specific phenotype, e.g., improvement of a biotechnological process. Here, we sampled floating islets on the surface of an activated sludge tank in a time-series spanning 51 time-points over 14 months. Multi-omics datasets (metagenomics, metatranscriptomics, metaproteomics, and (meta-)metabolomics) were generated for all time-points. Leveraging nucleotide sequencing data, we analyzed the community structure and reconstructed genomes for specific populations of interest. Moreover, based on their metabolic potential, three major groups emerged, serving as proxies for their respective fundamental niches . Time-resolved linkage of the proteomic and transcriptomic data to the reconstructed genomes revealed a fine-grained picture of niche realization. In particular, environmental factors (temperature, metabolites, oxygen) were significantly associated with gene expression of individual populations. Furthermore, we subjected the community to controlled oxygen conditions (stable or dynamic) in a bioreactor experiment and measured the transcriptomic response. Our results suggest short-term adaptations of populations of interest with respect to lipid metabolism, among other pathways. In conclusion, our work demonstrates how longitudinal multi-omic datasets can be integrated in order to further our understanding of microbial niche ecology within a biotechnological process with potential applications beyond waste water treatment.

Microbial communities are strongly shaped by the niche breadths of their constituent populations. However, a detailed understanding of microbial niche ecology is typically lacking. Integrated multi-omic analyses of host- or environment-derived samples offer the prospect of resolving fundamental and realised niches in situ. In turn, this is considered a prerequisite for niche engineering in order to drive an individual population or a community towards a specific phenotype, e.g., improvement of a biotechnological process. Here, we sampled floating islets on the surface of an activated sludge tank in a time-series spanning 51 time-points over 14 months. Multi-omics datasets (metagenomics, metatranscriptomics, metaproteomics, and (meta-)metabolomics) were generated for all time-points. Leveraging nucleotide sequencing data, we analyzed the community structure and reconstructed genomes for specific populations of interest. Moreover, based on their metabolic potential, three major groups emerged, serving as proxies for their respective fundamental niches . Time-resolved linkage of the proteomic and transcriptomic data to the reconstructed genomes revealed a fine-grained picture of niche realization. In particular, environmental factors (temperature, metabolites, oxygen) were significantly associated with gene expression of individual populations. Furthermore, we subjected the community to controlled oxygen conditions (stable or dynamic) in a bioreactor experiment and measured the transcriptomic response. Our results suggest short-term adaptations of populations of interest with respect to lipid metabolism, among other pathways. In conclusion, our work demonstrates how longitudinal multi-omic datasets can be integrated in order to further our understanding of microbial niche ecology within a biotechnological process with potential applications beyond waste water treatment.

Microbial communities are strongly shaped by the niche breadths of their constituent populations. However, a detailed understanding of microbial niche ecology is typically lacking. Integrated multi-omic analyses of host- or environment-derived samples offer the prospect of resolving fundamental and realised niches in situ. In turn, this is considered a prerequisite for niche engineering in order to drive an individual population or a community towards a specific phenotype, e.g., improvement of a biotechnological process. Here, we sampled floating islets on the surface of an activated sludge tank in a time-series spanning 51 time-points over 14 months. Multi-omics datasets (metagenomics, metatranscriptomics, metaproteomics, and (meta-)metabolomics) were generated for all time-points. Leveraging nucleotide sequencing data, we analyzed the community structure and reconstructed genomes for specific populations of interest. Moreover, based on their metabolic potential, three major groups emerged, serving as proxies for their respective fundamental niches . Time-resolved linkage of the proteomic and transcriptomic data to the reconstructed genomes revealed a fine-grained picture of niche realization. In particular, environmental factors (temperature, metabolites, oxygen) were significantly associated with gene expression of individual populations. Furthermore, we subjected the community to controlled oxygen conditions (stable or dynamic) in a bioreactor experiment and measured the transcriptomic response. Our results suggest short-term adaptations of populations of interest with respect to lipid metabolism, among other pathways. In conclusion, our work demonstrates how longitudinal multi-omic datasets can be integrated in order to further our understanding of microbial niche ecology within a biotechnological process with potential applications beyond waste water treatment.

For many infections transmitting to humans from reservoirs in nature, disease dispersal patterns over space and time are largely unknown. Here, a reversed genomics approach helped us understand disease dispersal and yielded insight into evolution and biological properties of Francisella tularensis, the bacterium causing tularemia. We whole-genome sequenced 67 strains and characterized by single-nucleotide polymorphism assays 138 strains, collected from individuals infected 1947-2012 across Western Europe. We used the data for phylogenetic, population genetic and geographical network analyses. All strains (n= 205) belonged to a monophyletic population of recent ancestry not found outside Western Europe. Most strains (n= 195) throughout the study area were assigned to a star-like phylogenetic pattern indicating that colonization of Western Europe occurred via clonal expansion. In the East of the study area, strains were more diverse, consistent with a founder population spreading from east to west. The relationship of genetic and geographic distance within the F. tularensis population was complex and indicated multiple long-distance dispersal events. Mutation rate estimates based on year of isolation indicated null rates; in outbreak hotspots only, there was a rate of 0.4 mutations/genome/year. Patterns of nucleotide substitution showed marked AT mutational bias suggestive of genetic drift. These results demonstrate that tularemia has moved from east to west in Europe and that F. tularensis has a biology characterized by long-range geographical dispersal events and mostly slow, but variable, replication rates. The results indicate that mutation-driven evolution, a resting survival phase, genetic drift and long-distance geographical dispersal events have interacted to generate genetic diversity within this species.

For many infections transmitting to humans from reservoirs in nature, disease dispersal patterns over space and time are largely unknown. Here, a reversed genomics approach helped us understand disease dispersal and yielded insight into evolution and biological properties of Francisella tularensis, the bacterium causing tularemia. We whole-genome sequenced 67 strains and characterized by single-nucleotide polymorphism assays 138 strains, collected from individuals infected 1947-2012 across Western Europe. We used the data for phylogenetic, population genetic and geographical network analyses. All strains (n= 205) belonged to a monophyletic population of recent ancestry not found outside Western Europe. Most strains (n= 195) throughout the study area were assigned to a star-like phylogenetic pattern indicating that colonization of Western Europe occurred via clonal expansion. In the East of the study area, strains were more diverse, consistent with a founder population spreading from east to west. The relationship of genetic and geographic distance within the F. tularensis population was complex and indicated multiple long-distance dispersal events. Mutation rate estimates based on year of isolation indicated null rates; in outbreak hotspots only, there was a rate of 0.4 mutations/genome/year. Patterns of nucleotide substitution showed marked AT mutational bias suggestive of genetic drift. These results demonstrate that tularemia has moved from east to west in Europe and that F. tularensis has a biology characterized by long-range geographical dispersal events and mostly slow, but variable, replication rates. The results indicate that mutation-driven evolution, a resting survival phase, genetic drift and long-distance geographical dispersal events have interacted to generate genetic diversity within this species.

For many infections transmitting to humans from reservoirs in nature, disease dispersal patterns over space and time are largely unknown. Here, a reversed genomics approach helped us understand disease dispersal and yielded insight into evolution and biological properties of Francisella tularensis, the bacterium causing tularemia. We whole-genome sequenced 67 strains and characterized by single-nucleotide polymorphism assays 138 strains, collected from individuals infected 1947-2012 across Western Europe. We used the data for phylogenetic, population genetic and geographical network analyses. All strains (n= 205) belonged to a monophyletic population of recent ancestry not found outside Western Europe. Most strains (n= 195) throughout the study area were assigned to a star-like phylogenetic pattern indicating that colonization of Western Europe occurred via clonal expansion. In the East of the study area, strains were more diverse, consistent with a founder population spreading from east to west. The relationship of genetic and geographic distance within the F. tularensis population was complex and indicated multiple long-distance dispersal events. Mutation rate estimates based on year of isolation indicated null rates; in outbreak hotspots only, there was a rate of 0.4 mutations/genome/year. Patterns of nucleotide substitution showed marked AT mutational bias suggestive of genetic drift. These results demonstrate that tularemia has moved from east to west in Europe and that F. tularensis has a biology characterized by long-range geographical dispersal events and mostly slow, but variable, replication rates. The results indicate that mutation-driven evolution, a resting survival phase, genetic drift and long-distance geographical dispersal events have interacted to generate genetic diversity within this species.

UnlabelledCoccidioidomycosis (or valley fever) is a fungal disease with high morbidity and mortality that affects tens of thousands of people each year. This infection is caused by two sibling species, Coccidioides immitis and C. posadasii, which are endemic to specific arid locales throughout the Western Hemisphere, particularly the desert southwest of the United States. Recent epidemiological and population genetic data suggest that the geographic range of coccidioidomycosis is expanding, as new endemic clusters have been identified in the state of Washington, well outside the established endemic range. The genetic mechanisms and epidemiological consequences of this expansion are unknown and require better understanding of the population structure and evolutionary history of these pathogens. Here we performed multiple phylogenetic inference and population genomics analyses of 68 new and 18 previously published genomes. The results provide evidence of substantial population structure in C. posadasii and demonstrate the presence of distinct geographic clades in central and southern Arizona as well as dispersed populations in Texas, Mexico, South America, and Central America. Although a smaller number of C. immitis strains were included in the analyses, some evidence of phylogeographic structure was also detected in this species, which has been historically limited to California and Baja, Mexico. Bayesian analyses indicated that C. posadasii is the more ancient of the two species and that Arizona contains the most diverse subpopulations. We propose a southern Arizona-northern Mexico origin for C. posadasii and describe a pathway for dispersal and distribution out of this region.ImportanceCoccidioidomycosis, or valley fever, is caused by the pathogenic fungi Coccidioides posadasii and C. immitis The fungal species and disease are primarily found in the American desert southwest, with spotted distribution throughout the Western Hemisphere. Initial molecular studies sug

Background: Clostridium botulinum is a diverse group of bacteria characterized by the production of botulinum neurotoxin. Botulinum neurotoxins are classified into serotypes (BoNT/A-G), which are produced by six species/Groups of Clostridia, but the genetic background of the bacteria remains poorly understood. The purpose of this study was to use comparative genomics to provide insights into the genetic diversity and evolutionary history of bacteria that produce the potent botulinum neurotoxin. Results: Comparative genomic analyses of over 170 Clostridia genomes, including our draft genome assemblies for 59 newly sequenced Clostridia strains from six continents and publicly available genomic data, provided in-depth insights into the diversity and distribution of BoNT-producing bacteria. These newly sequenced strains included Group I and II strains that express BoNT/A,/B,/E, or/F as well as bivalent strains. BoNT-producing Clostridia and closely related Clostridia species were delineated with a variety of methods including 16S rRNA gene, concatenated marker genes, core genome and concatenated multi-locus sequencing typing (MLST) gene phylogenies that related whole genome sequenced strains to publicly available strains and sequence types. These analyses illustrated the phylogenetic diversity in each Group and the diversity of genomic backgrounds that express the same toxin type or subtype. Comparisons of the botulinum neurotoxin genes did not identify novel toxin types or variants. Conclusions: This study represents one of the most comprehensive analyses of whole genome sequence data for Group I and II BoNT-producing strains. Read data and draft genome assemblies generated for 59 isolates will be a resource to the research community. Core genome phylogenies proved to be a powerful tool for differentiating BoNT-producing strains and can provide a framework for the study of these bacteria. Comparative genomic analyses of Clostridia species illustrate the diversity of bo

UnlabelledCoccidioidomycosis (or valley fever) is a fungal disease with high morbidity and mortality that affects tens of thousands of people each year. This infection is caused by two sibling species, Coccidioides immitis and C. posadasii, which are endemic to specific arid locales throughout the Western Hemisphere, particularly the desert southwest of the United States. Recent epidemiological and population genetic data suggest that the geographic range of coccidioidomycosis is expanding, as new endemic clusters have been identified in the state of Washington, well outside the established endemic range. The genetic mechanisms and epidemiological consequences of this expansion are unknown and require better understanding of the population structure and evolutionary history of these pathogens. Here we performed multiple phylogenetic inference and population genomics analyses of 68 new and 18 previously published genomes. The results provide evidence of substantial population structure in C. posadasii and demonstrate the presence of distinct geographic clades in central and southern Arizona as well as dispersed populations in Texas, Mexico, South America, and Central America. Although a smaller number of C. immitis strains were included in the analyses, some evidence of phylogeographic structure was also detected in this species, which has been historically limited to California and Baja, Mexico. Bayesian analyses indicated that C. posadasii is the more ancient of the two species and that Arizona contains the most diverse subpopulations. We propose a southern Arizona-northern Mexico origin for C. posadasii and describe a pathway for dispersal and distribution out of this region.ImportanceCoccidioidomycosis, or valley fever, is caused by the pathogenic fungi Coccidioides posadasii and C. immitis The fungal species and disease are primarily found in the American desert southwest, with spotted distribution throughout the Western Hemisphere.

For many infections transmitting to humans from reservoirs in nature, disease dispersal patterns over space and time are largely unknown. Here, a reversed genomics approach helped us understand disease dispersal and yielded insight into evolution and biological properties of Francisella tularensis, the bacterium causing tularemia. We whole-genome sequenced 67 strains and characterized by single-nucleotide polymorphism assays 138 strains, collected from individuals infected 1947-2012 across Western Europe. We used the data for phylogenetic, population genetic and geographical network analyses. All strains (n= 205) belonged to a monophyletic population of recent ancestry not found outside Western Europe. Most strains (n= 195) throughout the study area were assigned to a star-like phylogenetic pattern indicating that colonization of Western Europe occurred via clonal expansion. In the East of the study area, strains were more diverse, consistent with a founder population spreading from east to west. The relationship of genetic and geographic distance within the F. tularensis population was complex and indicated multiple long-distance dispersal events. Mutation rate estimates based on year of isolation indicated null rates; in outbreak hotspots only, there was a rate of 0.4 mutations/genome/year. Patterns of nucleotide substitution showed marked AT mutational bias suggestive of genetic drift. These results demonstrate that tularemia has moved from east to west in Europe and that F. tularensis has a biology characterized by long-range geographical dispersal events and mostly slow, but variable, replication rates. The results indicate that mutation-driven evolution, a resting survival phase, genetic drift and long-distance geographical dispersal events have interacted to generate genetic diversity within this species.

For many infections transmitting to humans from reservoirs in nature, disease dispersal patterns over space and time are largely unknown. Here, a reversed genomics approach helped us understand disease dispersal and yielded insight into evolution and biological properties of Francisella tularensis, the bacterium causing tularemia. We whole-genome sequenced 67 strains and characterized by single-nucleotide polymorphism assays 138 strains, collected from individuals infected 1947-2012 across Western Europe. We used the data for phylogenetic, population genetic and geographical network analyses. All strains (n= 205) belonged to a monophyletic population of recent ancestry not found outside Western Europe. Most strains (n= 195) throughout the study area were assigned to a star-like phylogenetic pattern indicating that colonization of Western Europe occurred via clonal expansion. In the East of the study area, strains were more diverse, consistent with a founder population spreading from east to west. The relationship of genetic and geographic distance within the F. tularensis population was complex and indicated multiple long-distance dispersal events. Mutation rate estimates based on year of isolation indicated null rates; in outbreak hotspots only, there was a rate of 0.4 mutations/genome/year. Patterns of nucleotide substitution showed marked AT mutational bias suggestive of genetic drift. These results demonstrate that tularemia has moved from east to west in Europe and that F. tularensis has a biology characterized by long-range geographical dispersal events and mostly slow, but variable, replication rates. The results indicate that mutation-driven evolution, a resting survival phase, genetic drift and long-distance geographical dispersal events have interacted to generate genetic diversity within this species.

Twelve Burkholderia pseudomallei isolates collected over a 32-month period from a patient with chronic melioidosis demonstrated identical multilocus sequence types (STs). However, whole-genome sequencing suggests a polyclonal infection. This study is the first to report a mixed infection with the same ST.

The global distribution of the soil-dwelling bacterium Burkholderia pseudomallei, causative agent of melioidosis, is poorly understood. We used established culturing methods developed for B. pseudomallei to isolate Burkholderia species from soil collected at 18 sampling sites in three states in the southern United States (Arizona (n = 4), Florida (n = 7), and Louisiana (n = 7)). Using multi-locus sequence typing (MLST) of seven genes, we identified 35 Burkholderia isolates from these soil samples. All species belonged to the B. cepacia complex (Bcc), including B. cenocepacia, B. cepacia, B. contaminans, B. diffusa, B. metallica, B. seminalis, B. vietnamiensis and two unnamed members of the Bcc. The MLST analysis provided a high level of resolution among and within these species. Despite previous clinical cases within the U.S. involving B. pseudomallei and its close phylogenetic relatives, we did not isolate any of these taxa. The Bcc contains a number of opportunistic pathogens that cause infections in cystic fibrosis patients. Interestingly, we found that B. vietnamiensis was present in soil from all three states, suggesting it may be a common component in southern U.S. soils. Most of the Burkholderia isolates collected in this study were from Florida (30/35; 86%), which may be due to the combination of relatively moist, sandy, and acidic soils found there compared to the other two states. We also investigated one MLST gene, recA, for its ability to identify species within Burkholderia. A 365bp fragment of recA recovered nearly the same species-level identification as MLST, thus demonstrating its cost effective utility when conducting environmental surveys for Burkholderia. Although we did not find B. pseudomallei, our findings document that other diverse Burkholderia species are present in soils in the southern United States.

Melioidosis, a disease of public health importance in Southeast Asia and northern Australia, is caused by the Gram-negative soil bacillus Burkholderia pseudomallei. Melioidosis is typically acquired through environmental exposure, and case clusters are rare, even in regions where the disease is endemic. B. pseudomallei is classed as a tier 1 select agent by the Centers for Disease Control and Prevention; from a biodefense perspective, source attribution is vital in an outbreak scenario to rule out a deliberate release. Two cases of melioidosis within a 3-month period at a residence in rural northern Australia prompted an investigation to determine the source of exposure. B. pseudomallei isolates from the property's groundwater supply matched the multilocus sequence type of the clinical isolates. Whole-genome sequencing confirmed the water supply as the probable source of infection in both cases, with the clinical isolates differing from the likely infecting environmental strain by just one single nucleotide polymorphism (SNP) each. For the first time, we report a phylogenetic analysis of genomewide insertion/deletion (indel) data, an approach conventionally viewed as problematic due to high mutation rates and homoplasy. Our whole-genome indel analysis was concordant with the SNP phylogeny, and these two combined data sets provided greater resolution and a better fit with our epidemiological chronology of events. Collectively, this investigation represents a highly accurate account of source attribution in a melioidosis outbreak and gives further insight into a frequently overlooked reservoir of B. pseudomallei. Our methods and findings have important implications for outbreak source tracing of this bacterium and other highly recombinogenic pathogens.