Introduction: USA300 has remained the dominant community and healthcare associated methicillin-resistant Staphylococcus aureus (MRSA) clone in the United States and in northern South America for at least the past 20 years. In this time, it has experienced epidemic spread in both of these locations. However, its pre-epidemic evolutionary history and origins are incompletely understood. Large sequencing databases, such as NCBI, PATRIC, and Staphopia, contain clues to the early evolution of USA300 in the form of sequenced genomes of USA300 isolates that are representative of lineages that diverged prior to the establishment of the South American epidemic (SAE) clade and North American epidemic (NAE) clade. In addition, historical isolates collected prior to the emergence of epidemics can help reconstruct early events in the history of this lineage. Methods: Here, we take advantage of the accrued, publicly available data, as well as two newly sequenced pre-epidemic historical isolates from 1996, and a very early diverging ACME-negative NAE genome, to understand the pre-epidemic evolution of USA300. We use database mining techniques to emphasize genomes similar to pre-epidemic isolates, with the goal of reconstructing the early molecular evolution of the USA300 lineage. Results: Phylogenetic analysis with these genomes confirms that the NAE and SAE USA300 lineages diverged from a most recent common ancestor around 1970 with high confidence, and it also pinpoints the independent acquisition events of the of the ACME and COMER loci with greater precision than in previous studies. We provide evidence for a North American origin of the USA300 lineage and identify multiple introductions of USA300 into South and North America. Notably, we describe a third major USA300 clade (the pre-epidemic branching clade; PEB1) consisting of both MSSA and MRSA isolates circulating around the world that diverged from the USA300 lineage prior to the establishment of the South and North American epidemics. We present a detailed analysis of specific sequence characteristics of each of the major clades, and present diagnostic positions that can be used to classify new genomes.

Vancomycin-intermediate Staphylococcus aureus (VISA) is currently defined as having minimal inhibitory concentration (MIC) of 4–8 µg/ml. VISA evolves through changes in multiple genetic loci with at least 16 candidate genes identified in clinical and in vitro-selected VISA strains. We report a whole-genome comparative analysis of 49 vancomycin-sensitive S. aureus and 26 VISA strains. Resistance to vancomycin was determined by broth microdilution, Etest, and population analysis profile-area under the curve (PAP-AUC). Genome-wide association studies (GWAS) of 55,977 single-nucleotide polymorphisms identified in one or more strains found one highly significant association (P = 8.78E-08) between a nonsynonymous mutation at codon 481 (H481) of the rpoB gene and increased vancomycin MIC. Additionally, we used a database of public S. aureus genome sequences to identify rare mutations in candidate genes associated with VISA. On the basis of these data, we proposed a preliminary model called ECM+RMCG for the VISA phenotype as a benchmark for future efforts. The model predicted VISA based on the presence of a rare mutation in a set of candidate genes (walKR, vraSR, graSR, and agrA) and/or three previously experimentally verified mutations (including the rpoB H481 locus) with an accuracy of 81% and a sensitivity of 73%. Further, the level of resistance measured by both Etest and PAP-AUC regressed positively with the number of mutations present in a strain. This study demonstrated 1) the power of GWAS for identifying common genetic variants associated with antibiotic resistance in bacteria and 2) that rare mutations in candidate gene, identified using large genomic data sets, can also be associated with resistance phenotypes.

UNLABELLED: Staphylococcus aureus and Pseudomonas aeruginosa are the most common bacterial pathogens isolated from cystic fibrosis (CF) related lung infections. When both of these opportunistic pathogens are found in a coinfection, CF patients tend to have higher rates of pulmonary exacerbations and experience a more rapid decrease in lung function. When cultured together under standard laboratory conditions, it is often observed that P. aeruginosa effectively inhibits S. aureus growth. Previous work from our group revealed that S. aureus from CF infections have isolate-specific survival capabilities when cocultured with P. aeruginosa . In this study, we designed a serial transfer evolution experiment to identify mutations that allow S. aureus to adapt to the presence of P. aeruginosa . Using S. aureus USA300 JE2 as our ancestral strain, populations of S. aureus were repeatedly cocultured with fresh P. aeruginosa strain, PAO1. After 8 coculture periods, S. aureus populations that survived better in the presence of PAO1 were observed. We found two independent mutations in the highly conserved S. aureus aspartate transporter, gltT , that were unique to evolved P. aeruginosa -tolerant isolates. Subsequent phenotypic testing demonstrated that gltT mutants have reduced uptake of glutamate and outcompete wild-type S. aureus when glutamate is absent from chemically-defined media. These findings together demonstrate that the presence of P. aeruginosa exerts selective pressure on S. aureus to alter its uptake and metabolism of key amino acids when the two bacteria are cultured together. IMPORTANCE: Staphylococcus aureus and Pseudomonas aeruginosa are the two most common bacterial pathogens that infect people with the genetic disease, cystic fibrosis (CF). They are often found together in CF-associated polymicrobial infections that are associated with worse patient prognosis. Understanding how these very different opportunistic pathogens influence each other in a shared environment is pertinent to improving the treatment of polymicrobial infections. While much attention has been brought to the interspecific interactions between S. aureus and P. aeruginosa, few studies have used experimental evolution methods to identify determinants of their competition and coexistence. Here, we use a serial transfer experimental evolution approach and identified a single genetic change associated with improved survival of S. aureus in the presence of P. aeruginosa. Our findings implicate metabolism of shared resources as an important factor in S. aureus's ability to survive in the presence of P. aeruginosa .

Introduction: Chlamydia trachomatis, a gram-negative obligate intracellular bacterium, commonly causes sexually transmitted infections (STIs). Little is known about C. trachomatis transmission within the host, which is important for understanding disease epidemiology and progression. Methods: We used RNA-bait enrichment and whole-genome sequencing to compare rectal, vaginal and endocervical samples collected at the same time from 26 study participants who attended Fijian Ministry of Health and Medical Services clinics and tested positive for C. trachomatis at each anatomic site. Results: The 78 C. trachomatis genomes from participants resolved into two major clades of the C. trachomatis phylogeny (the “prevalent urogenital and anorectal” clade and “non-prevalent urogenital and anorectal” clade). For 21 participants, genome sequences were almost identical in each anatomic site. For the other five participants, two distinct C. trachomatis strains were present in different sites; in two cases, the vaginal sample was a mixture of strains. Discussion: The absence of large numbers of fixed SNPs between C. trachomatis genomes within many of the participants could indicate recent acquisition of infection prior to the clinic visit without sufficient time to accumulate significant genetic variation in different body sites. This model suggests that many C. trachomatis infections may be resolved relatively quickly in the Fijian population, possibly reflecting common prescription or over-the-counter antibiotics usage.

Staphylococcus aureus is a major human pathogen causing serious implant-associated infections. Combination treatment with rifampin (10 to 15 mg/kg per day), which has dose-dependent activity, is recommended to treat S. aureus orthopedic implant-associated infections. Rifampin, however, has limited bone penetration. Here, dynamic 11C-rifampin positron emission tomography (PET) performed in prospectively enrolled patients with confirmed S. aureus bone infection (n = 3) or without orthopedic infection (n = 12) demonstrated bone/plasma area under the concentration-time curve ratio of 0.14 (interquartile range, 0.09 to 0.19), exposures lower than previously thought. PET-based pharmacokinetic modeling predicted rifampin concentration-time profiles in bone and facilitated studies in a mouse model of S. aureus orthopedic implant infection. Administration of highdose rifampin (human equipotent to 35 mg/kg per day) substantially increased bone concentrations (2 mg/liter versus <0.2 mg/liter with standard dosing) in mice and achieved higher bacterial killing and biofilm disruption. Treatment for 4 weeks with high-dose rifampin and vancomycin was noninferior to the recommended 6-week treatment of standard-dose rifampin with vancomycin in mice (risk difference, -6.7% favoring high-dose rifampin regimen). High-dose rifampin treatment ameliorated antimicrobial resistance (0% versus 38%; P = 0.04) and mitigated adverse bone remodeling (P < 0.01). Last, whole-genome sequencing demonstrated that administration of high-dose rifampin in mice reduced selection of bacterial mutations conferring rifampin resistance (rpoB) and mutations in genes potentially linked to persistence. These data suggest that administration of high-dose rifampin is necessary to achieve optimal bone concentrations, which could shorten and improve treatments for S. aureus orthopedic implant infections.

UNLABELLED: Chlamydia trachomatis , a gram-negative obligate intracellular bacterium, commonly causes sexually transmitted infections (STIs). Little is known about C. trachomatis transmission within the host, which is important for understanding disease epidemiology and progression. We used RNA-bait enrichment and whole-genome sequencing to compare rectal, vaginal and endocervical samples collected at the same time from 26 study participants who attended Fijian Ministry of Health and Medical Services clinics and tested positive for C. trachomatis at each anatomic site. The 78 C. trachomatis genomes from participants were from two major clades of the C. trachomatis phylogeny (the "prevalent urogenital and anorecta"l clade and "non-prevalent urogenital and anorectal" clade). For 21 participants, genome sequences were almost identical in each anatomic site. For the other five participants, two distinct C. trachomatis strains were present in different sites; in two cases, the vaginal sample was a mixture of strains. The absence of large numbers of fixed SNPs between C. trachomatis strains within many of the participants could indicate recent acquisition of infection prior to the clinic visit without sufficient time to accumulate significant variation in the different body sites. This model suggests that many C. trachomatis infections may be resolved relatively quickly in the Fijian population, possibly reflecting common prescription or over-the-counter antibiotics usage. IMPORTANCE: Chlamydia trachomatis is a bacterial pathogen that causes millions of sexually transmitted infections (STIs) annually across the globe. Because C. trachomatis lives inside human cells, it has historically been hard to study. We know little about how the bacterium spreads between body sites. Here, samples from 26 study participants who had simultaneous infections in their vagina, rectum and endocervix were genetically analyzed using an improved method to extract C. trachomatis DNA directly from clinical samples for genome sequencing. By analyzing patterns of mutations in the genomes, we found that 21 participants shared very similar C. trachomatis strains in all three anatomic sites, suggesting recent infection and spread. For five participants two C. trachomatis strains were evident, indicating multiple infections. This study is significant in that improved enrichment methods for genome sequencing provides robust data to genetically trace patterns of C. trachomatis infection and transmission within an individual for epidemiologic and pathogenesis interrogations.

Pseudomonas aeruginosa is an opportunistic pathogen responsible for chronic, drug-resistant lung infections in individuals with cystic fibrosis (CF). Although extensive heterogeneity in antimicrobial resistance (AMR) phenotypes of P. aeruginosa CF lung populations has been previously described, there has yet to be a thorough investigation on how genomic diversification drives the evolution of AMR diversity within a population. In this study, we harnessed sequencing from a collection of 300 clinical isolates of P. aeruginosa to unravel the evolution of resistance diversity in four individuals with CF. We found that genomic diversity was not always a reliable predictor of phenotypic AMR diversity within a population, and notably, the least genetically diverse population in this cohort displayed AMR diversity comparable to that of populations with up to two orders of magnitude more SNPs. Hypermutator strains often displayed increased sensitivity to antimicrobials, even when there was a history of use of antimicrobial in the treatment of the patient. Lastly, we sought to determine whether diversity in AMR could be explained by evolutionary trade-offs with other traits. Our results showed no strong evidence of collateral sensitivity between aminoglycoside, beta-lactam, or fluoroquinolone antibiotics within these populations. Additionally, there was no evidence of trade-offs between AMR and growth in a sputum-mimicking environment. Overall, our findings highlight that (i) genomic diversity within a population is not a necessary precursor to phenotypic diversity in AMR; (ii) hypermutator populations can evolve increased sensitivity to antimicrobials even under apparent antibiotic selection; and that (iii) resistance to a single antibiotic may not impose enough of a fitness cost to elicit trade-offs with fitness.

The most common approach to sampling the bacterial populations within an infected or colonised host is to sequence genomes from a single colony obtained from a culture plate. However, it is recognized that this method does not capture the genetic diversity in the population. An alternative is to sequence a mixture containing multiple colonies ("pool-seq"), but this has the disadvantage that it is a non-homogeneous sample, making it difficult to perform specific experiments. We compared differences in measures of genetic diversity between eight single-colony isolates (singles) and pool-seq on a set of 2286 S. aureus culture samples. The samples were obtained by swabbing three body sites on 85 human participants quarterly for a year, who initially presented with a methicillin-resistant S. aureus skin and soft-tissue infection (SSTI). We compared parameters such as sequence quality, contamination, allele frequency, nucleotide diversity and pangenome diversity in each pool to the corresponding singles. Comparing singles from the same culture plate, we found that 18% of sample collections contained mixtures of multiple Multilocus sequence types (MLSTs or STs). We showed that pool-seq data alone could predict the presence of multi-ST populations with 95% accuracy. We also showed that pool-seq could be used to estimate the number of polymorphic sites in the population. Additionally, we found that the pool may contain clinically relevant genes such as antimicrobial resistance markers that may be missed when only examining singles. These results highlight the potential advantage of analysing genome sequences of total populations obtained from clinical cultures rather than single colonies.

Genome-wide association studies (GWASs) have become an increasingly important approach for eukaryotic geneticists, facilitating the identification of hundreds of genetic polymorphisms that are responsible for inherited diseases. Despite the relative simplicity of bacterial genomes, the application of GWASs to identify polymorphisms responsible for important bacterial phenotypes has only recently been made possible through advances in genome sequencing technologies. Bacterial GWASs are now about to come of age thanks to the availability of massive datasets, and because of the potential to bridge genomics and traditional genetic approaches that is provided by improving validation strategies. A small number of pioneering GWASs in bacteria have been published in the past 2 years, examining from 75 to more than 3,000 strains. The experimental designs have been diverse, taking advantage of different processes in bacteria for generating variation. Analysis of data from bacterial GWASs can, to some extent, be performed using software developed for eukaryotic systems, but there are important differences in genome evolution that must be considered. The greatest experimental advantage of bacterial GWASs is the potential to perform downstream validation of causality and dissection of mechanism. We review the recent advances and remaining challenges in this field and propose strategies to improve the validation of bacterial GWASs.

Bacterial genomes exhibit widespread horizontal gene transfer, resulting in highly variable genome content that complicates the inference of genetic interactions. In this study, we develop a method for detecting coevolving genes from large datasets of bacterial genomes based on pairwise comparisons of closely related individuals, analogous to a pedigree study in eukaryotic populations. We apply our method to pairs of genes from the Staphylococcus aureus accessory genome of over 75,000 annotated gene families using a database of over 40,000 whole genomes. We find many pairs of genes that appear to be gained or lost in a coordinated manner, as well as pairs where the gain of one gene is associated with the loss of the other. These pairs form networks of rapidly coevolving genes, primarily consisting of genes involved in virulence, mechanisms of horizontal gene transfer, and antibiotic resistance, particularly the SCCmec complex. While we focus on gene gain and loss, our method can also detect genes that tend to acquire substitutions in tandem, or genotype-phenotype or phenotype-phenotype coevolution. Finally, we present the R package DeCoTUR that allows for the computation of our method.