Plasmid Acquisition Alters Vancomycin Susceptibility in Clostridioides difficile.

The increasing incidence of primary and recurring Clostridioides difficile infections (CDI), which evade current treatment strategies, reflects the changing biology of C difficile. Here, we describe a putative plasmid-mediated mechanism potentially driving decreased sensitivity of C difficile to vancomycin treatment. We identified a broad host range transferable plasmid in a C difficile strain associated with lack of adequate response to vancomycin treatment. The transfer of this plasmid to a vancomycin-susceptible C difficile isolate decreased its susceptibility to vancomycin in vitro and resulted in more severe disease in a humanized mouse model. Our findings suggest plasmid acquisition in the gastrointestinal tract to be a possible mechanism underlying vancomycin treatment failure in patients with CDI, but further work is needed to characterize the mechanism by which plasmid genes determine vancomycin susceptibility in C difficile.

Acinetobacter baumannii Genomic Sequence-Based Core Genome Multilocus Sequence Typing Using Ridom SeqSphere+ and Antimicrobial Susceptibility Prediction in ARESdb.

Whole-genome sequencing (WGS) is rapidly replacing traditional typing methods for the investigation of infectious disease outbreaks. Additionally, WGS data are being used to predict phenotypic antimicrobial susceptibility. Acinetobacter baumannii, which is often multidrug-resistant, is a significant culprit in outbreaks in health care settings. A well-characterized collection of A. baumannii was studied using core genome multilocus sequence typing (cgMLST). Seventy-two isolates previously typed by PCR-electrospray ionization mass spectrometry (PCR/ESI-MS) provided by the Antimicrobial Resistance Leadership Group (ARLG) were analyzed using a clinical microbiology laboratory developed workflow for cgMLST with genomic susceptibility prediction performed using the ARESdb platform. Previously performed PCR/ESI-MS correlated with cgMLST using relatedness thresholds of allelic differences of ≤9 and ≤200 allelic differences in 78 and 94% of isolates, respectively. Categorical agreement between genotypic and phenotypic antimicrobial susceptibility across a panel of 11 commonly used drugs was 89%, with minor, major, and very major error rates of 8%, 11%, and 1%, respectively.

Clostridioides difficile Whole-genome Sequencing Differentiates Relapse With the Same Strain From Reinfection With a New Strain.

BACKGROUND: Current approaches in tracking Clostridioides difficile infection (CDI) and individualizing patient management are incompletely defined. METHODS: We recruited 468 subjects with CDI at Mayo Clinic Rochester between May and December 2016 and performed whole-genome sequencing (WGS) on C. difficile isolates from 397. WGS was also performed on isolates from a subset of the subjects at the time of a recurrence of infection. The sequence data were analyzed by determining core genome multilocus sequence type (cgMLST), with isolates grouped by allelic differences and the predicted ribotype. RESULTS: There were no correlations between C. difficile isolates based either on cgMLST or ribotype groupings and CDI outcome. An epidemiologic assessment of hospitalized subjects harboring C. difficile isolates with ≤2 allelic differences, based on standard infection prevention and control assessment, revealed no evidence of person-to-person transmission. Interestingly, community-acquired CDI subjects in 40% of groups with ≤2 allelic differences resided within the same zip code. Among 18 subjects clinically classified as having recurrent CDI, WGS revealed 14 with initial and subsequent isolates differing by ≤2 allelic differences, suggesting a relapse of infection with the same initial strain, and 4 with isolates differing by >50 allelic differences, suggesting reinfection. Among the 5 subjects classified as having a reinfection based on the timing of recurrence, 3 had isolates with ≤2 allelic differences between them, suggesting a relapse, and 2 had isolates differing by >50 allelic differences, suggesting reinfection. CONCLUSIONS: Our findings point to potential transmission of C. difficile in the community. WGS better differentiates relapse from reinfection than do definitions based on the timing of recurrence.

Yersinia occitanica is a later heterotypic synonym of Yersinia kristensenii subsp. rochesterensis and elevation of Yersinia kristensenii subsp. rochesterensis to species status.

The taxonomic position of Yersinia kristensenii subsp. rochesterensis and Yersinia occitanica was re-evaluated by genomic analysis. Average nucleotide identity (ANI), digital DNA-DNA hybridization values, and phylogenetic analyses of the type strains indicate that Y. kristensenii subsp. rochesterensis and Y. occitanica are the same genospecies. Additionally, the overall genomic relatedness index (OGRI) values reveal that Y. kristensenii subsp. rochesterensis should be elevated to species status as Yersinia rochesterensis sp. nov.

Comparison of Three Commercial Tools for Metagenomic Shotgun Sequencing Analysis.

Metagenomic shotgun sequencing for the identification of pathogens is being increasingly utilized as a diagnostic method. Interpretation of large and complicated data sets is a significant challenge, for which multiple commercial tools have been developed. Three commercial metagenomic shotgun sequencing tools, CosmosID, One Codex, and IDbyDNA, were compared to determine whether they result in similar interpretations of the same sequencing data. We selected 24 diverse samples from a previously characterized data set derived from DNA extracted from biofilms dislodged from the surfaces of resected arthroplasties (sonicate fluid). Sequencing data sets were analyzed using the three commercial tools and compared to culture results and prior metagenomic analysis interpretation. Identical interpretations from all three tools occurred for 6 samples. The total number of species identified included 28 by CosmosID, 59 by One Codex, and 41 by IDbyDNA. All of the tools performed similarly in detecting those microorganisms identified by culture, including polymicrobial mixes. These data show that while all of the tools performed well overall, there were some differences, particularly in their predilection for identifying low-abundance or contaminant organisms as present.

Bacterial Single Cell Whole Transcriptome Amplification in Microfluidic Platform Shows Putative Gene Expression Heterogeneity.

Single cell RNA sequencing is a technology that provides the capability of analyzing the transcriptome of a single cell from a population. So far, single cell RNA sequencing has been focused mostly on human cells due to the larger starting amount of RNA template for subsequent amplification. One of the major challenges of applying single cell RNA sequencing to microbial cells is to amplify the femtograms of the RNA template to obtain sufficient material for downstream sequencing with minimal contamination. To achieve this goal, efforts have been focused on multiround RNA amplification, but would introduce additional contamination and bias. In this work, we for the first time coupled a microfluidic platform with multiple displacement amplification technology to perform single cell whole transcriptome amplification and sequencing of Porphyromonas somerae, a microbe of interest in endometrial cancer, as a proof-of-concept demonstration of using single cell RNA sequencing tool to unveil gene expression heterogeneity in single microbial cells. Our results show that the bacterial single-cell gene expression regulation is distinct across different cells, supporting widespread heterogeneity.

Evaluation of the CosmosID Bioinformatics Platform for Prosthetic Joint-Associated Sonicate Fluid Shotgun Metagenomic Data Analysis.

We previously demonstrated that shotgun metagenomic sequencing can detect bacteria in sonicate fluid, providing a diagnosis of prosthetic joint infection (PJI). A limitation of the approach that we used is that data analysis was time-consuming and specialized bioinformatics expertise was required, both of which are barriers to routine clinical use. Fortunately, automated commercial analytic platforms that can interpret shotgun metagenomic data are emerging. In this study, we evaluated the CosmosID bioinformatics platform using shotgun metagenomic sequencing data derived from 408 sonicate fluid samples from our prior study with the goal of evaluating the platform vis-à-vis bacterial detection and antibiotic resistance gene detection for predicting staphylococcal antibacterial susceptibility. Samples were divided into a derivation set and a validation set, each consisting of 204 samples; results from the derivation set were used to establish cutoffs, which were then tested in the validation set for identifying pathogens and predicting staphylococcal antibacterial resistance. Metagenomic analysis detected bacteria in 94.8% (109/115) of sonicate fluid culture-positive PJIs and 37.8% (37/98) of sonicate fluid culture-negative PJIs. Metagenomic analysis showed sensitivities ranging from 65.7 to 85.0% for predicting staphylococcal antibacterial resistance. In conclusion, the CosmosID platform has the potential to provide fast, reliable bacterial detection and identification from metagenomic shotgun sequencing data derived from sonicate fluid for the diagnosis of PJI. Strategies for metagenomic detection of antibiotic resistance genes for predicting staphylococcal antibacterial resistance need further development.

Lack of correlation of virulence gene profiles of Staphylococcus aureus bacteremia isolates with mortality.

PURPOSE: Whole genome sequencing (WGS) analysis of Staphylococcus aureus is increasingly used in clinical practice. Although bioinformatics tools used in WGS analysis readily define the S. aureus virulome, the clinical value of this type of analysis is unclear. Here, virulence genes in S. aureus bacteremia (SAB) isolates were evaluated by WGS, with superantigens (SAgs) further evaluated by conventional PCR and functional assays, and results correlated with mortality. METHODS: 152 SAB isolates collected throughout 2015 at a large Minnesota medical center were studied and associated clinical data analyzed. Virulence genes were identified from previously-reported WGS data (https://doi.org/10.1371/journal.pone.0179003). SAg genes sea, seb, sec, sed, see, seg, seh, sei, sej, and tst were also assessed by individual PCR assays. Mitogenicity of SAgs was assessed using an in vitro proliferation assay with splenocytes from HLA-DR3 transgenic mice. RESULTS: Of the 152 SAB isolates studied, 106 (69%) were methicillin-susceptible S. aureus (MSSA). The number of deaths attributed and not attributed to SAB, and 30-day survivors were 24 (16%), 2 (1%), and 128 (83%), respectively. From WGS data, both MSSA and MRSA had high proportions of adhesion (>80%) and immune-evasion (>70%) genes. There was no difference in virulomes between survivor- and non-survivor-associated isolates. Although over 60% of SAB isolates produced functional SAgs, there were no differences in the distribution or prevalence of SAg genes between survivor- and non-survivor-associated isolates. CONCLUSION: In this study of one year of SAB isolates from a large medical center, the S. aureus virulome, as assessed by WGS, and also for SAgs using individual PCRs and phenotypic characterization, did not impact mortality.

Yersinia kristensenii subsp. rochesterensis subsp. nov., isolated from human feces.

A single bacterial isolate, EPLC-04T, was isolated from human feces and identified as representing a member of the genus Yersinia on the basis of phenotypic characteristics, matrix assisted laser desorption ionization time-of-flight mass spectrometry and partial 16S rRNA gene sequencing. The isolate's phenotypic profile differed from that described for the most closely related species, Yersinia kristensenii, by exhibiting lipase production and lacking pyrazinamidase activity. Multiple genetic targets, including the complete (1465 bp) 16S rRNA gene sequence and partial sequences of groEL (539 bp), gyrB (935 bp), glnA (525 bp) and recA (535 bp) indicated that the isolate exhibited 98.91, 92.16, 90.81, 92.78 and 89.01 % identity with Yersinia aldovae, 98.98, 91.99, 90.17, 89.77 and 89.55 % identity with Yersinia intermedia, and 99.66, 98.11, 98.50, 98.49 and 98.51 % identity with Y. kristensenii, respectively. Phylogenetic reconstructions based on the combination of the four housekeeping genes indicated that the isolate formed a unique branch, supported by a bootstrap value of 100 %. Digital DNA-DNA homology and 16S rRNA gene sequencing identified EPLC-04T as representing Y. kristensenii. However, the unique phenotypic traits and results of phylogenetic analysis indicate that it represents a novel subspecies of Y. kristensenii. The name Yersinia kristenseniisubsp. rochesterensis subsp. nov. is proposed for this novel taxon (type strain EPLC-04T=ATCC BAA-2637T, DSMZ 28595T).

Synthesis of multi-omic data and community metabolic models reveals insights into the role of hydrogen sulfide in colon cancer.

Multi-omic data and genome-scale microbial metabolic models have allowed us to examine microbial communities, community function, and interactions in ways that were not available to us historically. Now, one of our biggest challenges is determining how to integrate data and maximize data potential. Our study demonstrates one way in which to test a hypothesis by combining multi-omic data and community metabolic models. Specifically, we assess hydrogen sulfide production in colorectal cancer based on stool, mucosa, and tissue samples collected on and off the tumor site within the same individuals. 16S rRNA microbial community and abundance data were used to select and inform the metabolic models. We then used MICOM, an open source platform, to track the metabolic flux of hydrogen sulfide through a defined microbial community that either represented on-tumor or off-tumor sample communities. We also performed targeted and untargeted metabolomics, and used the former to quantitatively evaluate our model predictions. A deeper look at the models identified several unexpected but feasible reactions, microbes, and microbial interactions involved in hydrogen sulfide production for which our 16S and metabolomic data could not account. These results will guide future in vitro, in vivo, and in silico tests to establish why hydrogen sulfide production is increased in tumor tissue.

Identification of Prosthetic Joint Infection Pathogens Using a Shotgun Metagenomics Approach.

Background: Metagenomic shotgun sequencing has the potential to change how many infections, particularly those caused by difficult-to-culture organisms, are diagnosed. Metagenomics was used to investigate prosthetic joint infections (PJIs), where pathogen detection can be challenging. Methods: Four hundred eight sonicate fluid samples generated from resected hip and knee arthroplasties were tested, including 213 from subjects with infections and 195 from subjects without infection. Samples were enriched for microbial DNA using the MolYsis basic kit, whole-genome amplified, and sequenced using Illumina HiSeq 2500 instruments. A pipeline was designed to screen out human reads and analyze remaining sequences for microbial content using the Livermore Metagenomics Analysis Toolkit and MetaPhlAn2 tools. Results: When compared to sonicate fluid culture, metagenomics was able to identify known pathogens in 94.8% (109/115) of culture-positive PJIs, with additional potential pathogens detected in 9.6% (11/115). New potential pathogens were detected in 43.9% (43/98) of culture-negative PJIs, 21 of which had no other positive culture sources from which these microorganisms had been detected. Detection of microorganisms in samples from uninfected aseptic failure cases was conversely rare (7/195 [3.6%] cases). The presence of human and contaminant microbial DNA from reagents was a challenge, as previously reported. Conclusions: Metagenomic shotgun sequencing is a powerful tool to identify a wide range of PJI pathogens, including difficult-to-detect pathogens in culture-negative infections.

Direct Detection and Identification of Prosthetic Joint Infection Pathogens in Synovial Fluid by Metagenomic Shotgun Sequencing.

Metagenomic shotgun sequencing has the potential to transform how serious infections are diagnosed by offering universal, culture-free pathogen detection. This may be especially advantageous for microbial diagnosis of prosthetic joint infection (PJI) by synovial fluid analysis since synovial fluid cultures are not universally positive and since synovial fluid is easily obtained preoperatively. We applied a metagenomics-based approach to synovial fluid in an attempt to detect microorganisms in 168 failed total knee arthroplasties. Genus- and species-level analyses of metagenomic sequencing yielded the known pathogen in 74 (90%) and 68 (83%) of the 82 culture-positive PJIs analyzed, respectively, with testing of two (2%) and three (4%) samples, respectively, yielding additional pathogens not detected by culture. For the 25 culture-negative PJIs tested, genus- and species-level analyses yielded 19 (76%) and 21 (84%) samples with insignificant findings, respectively, and 6 (24%) and 4 (16%) with potential pathogens detected, respectively. Genus- and species-level analyses of the 60 culture-negative aseptic failure cases yielded 53 (88%) and 56 (93%) cases with insignificant findings and 7 (12%) and 4 (7%) with potential clinically significant organisms detected, respectively. There was one case of aseptic failure with synovial fluid culture growth; metagenomic analysis showed insignificant findings, suggesting possible synovial fluid culture contamination. Metagenomic shotgun sequencing can detect pathogens involved in PJI when applied to synovial fluid and may be particularly useful for culture-negative cases.

A Novel Prosthetic Joint Infection Pathogen, Mycoplasma salivarium, Identified by Metagenomic Shotgun Sequencing.

Defining the microbial etiology of culture-negative prosthetic joint infection (PJI) can be challenging. Metagenomic shotgun sequencing is a new tool to identify organisms undetected by conventional methods. We present a case where metagenomics was used to identify Mycoplasma salivarium as a novel PJI pathogen in a patient with hypogammaglobulinemia.

Impact of Contaminating DNA in Whole-Genome Amplification Kits Used for Metagenomic Shotgun Sequencing for Infection Diagnosis.

Whole-genome amplification (WGA) is a useful tool for amplification of very small quantities of DNA for many uses, including metagenomic shotgun sequencing for infection diagnosis. Depending on the application, background DNA from WGA kits can be problematic. Three WGA kits were tested for their utility in a metagenomics approach to identify the pathogens in sonicate fluid comprised of biofilms and other materials dislodged from the surfaces of explanted prosthetic joints using sonication. The Illustra V2 Genomiphi, Illustra single cell Genomiphi, and Qiagen REPLI-g single cell kits were used to test identical sonicate fluid samples. Variations in the number of background reads, the genera identified in the background, and the number of reads from known pathogens known to be present in the samples were observed between kits. These results were then compared to those obtained with a library preparation without prior WGA using an NEBNext Ultra II paired-end kit, which requires a very small amount of input DNA. This approach also resulted in the presence of contaminant bacterial DNA and yielded fewer reads from the known pathogens. These findings highlight the impact that WGA kit selection can have on metagenomic analysis of low-biomass samples and the importance of the careful selection and consideration of the implications of using these tools.

Comparison of Whole-Genome Sequencing Methods for Analysis of Three Methicillin-Resistant Staphylococcus aureus Outbreaks.

Whole-genome sequencing (WGS) can provide excellent resolution in global and local epidemiological investigations of Staphylococcus aureus outbreaks. A variety of sequencing approaches and analytical tools have been used; it is not clear which is ideal. We compared two WGS strategies and two analytical approaches to the standard method of SmaI restriction digestion pulsed-field gel electrophoresis (PFGE) for typing S. aureus Forty-two S. aureus isolates from three outbreaks and 12 reference isolates were studied. Near-complete genomes, assembled de novo with paired-end and long-mate-pair (8 kb) libraries were first assembled and analyzed utilizing an in-house assembly and analytical informatics pipeline. In addition, paired-end data were assembled and analyzed using a commercial software package. Single nucleotide variant (SNP) analysis was performed using the in-house pipeline. Two assembly strategies were used to generate core genome multilocus sequence typing (cgMLST) data. First, the near-complete genome data generated with the in-house pipeline were imported into the commercial software and used to perform cgMLST analysis. Second, the commercial software was used to assemble paired-end data, and resolved assemblies were used to perform cgMLST. Similar isolate clustering was observed using SNP calling and cgMLST, regardless of data assembly strategy. All methods provided more discrimination between outbreaks than did PFGE. Overall, all of the evaluated WGS strategies yielded statistically similar results for S. aureus typing.

Carbapenem- and Colistin-Resistant Enterobacter cloacae from Delta, Colorado, in 2015.

Resistance to carbapenems in Enterobacteriaceae is a clinical problem of growing significance. Difficulty in treating multidrug-resistant Gram-negative organisms with conventional antibiotics has led to a renewed and increasing use of polymyxin compounds, such as colistin. Here, we report the isolation of carbapenem- and colistin-resistant Enterobacter cloacae from a polymicrobial lower extremity wound in an ambulatory patient. Whole-genome sequencing demonstrated the presence of chromosomal blaIMI-1 and blaAmpC, as well as numerous efflux pump genes.

An Immunocompromised Child with Bloodstream Infection Caused by Two Escherichia coli Strains, One Harboring NDM-5 and the Other Harboring OXA-48-Like Carbapenemase.

We describe a 16-year-old neutropenic patient from the Middle East with bloodstream infection caused by two carbapenemase-producing Escherichia coli isolates that we characterized by whole-genome sequencing. While one displayed meropenem resistance and was blaNDM positive, the other demonstrated meropenem susceptibility yet harbored blaOXA181 (which encodes a blaOXA48-like enzyme). This report highlights the challenge of laboratory detection of blaOXA48-like enzymes and the clinical implications of genotypic resistance detection in carbapenemase-producing Enterobacteriaceae.

Metronidazole- and carbapenem-resistant bacteroides thetaiotaomicron isolated in Rochester, Minnesota, in 2014.

Emerging antimicrobial resistance in members of the Bacteroides fragilis group is a concern in clinical medicine. Although metronidazole and carbapenem resistance have been reported in Bacteroides thetaiotaomicron, a member of the B. fragilis group, they have not, to the best of our knowledge, been reported together in the same B. thetaiotaomicron isolate. Herein, we report isolation of piperacillin-tazobactam-, metronidazole-, clindamycin-, ertapenem-, and meropenem-resistant B. thetaiotaomicron from a patient with postoperative intra-abdominal abscess and empyema. Whole-genome sequencing demonstrated the presence of nimD with at least a portion of IS1169 upstream, a second putative nim gene, two ß-lactamase genes (one of which has not been previously reported), two tetX genes, tetQ, ermF, two cat genes, and a number of efflux pumps. This report highlights emerging antimicrobial resistance in B. thetaiotaomicron and the importance of identification and antimicrobial susceptibility testing of selected anaerobic bacteria.

Quantification of the relative roles of niche and neutral processes in structuring gastrointestinal microbiomes.

The theoretical description of the forces that shape ecological communities focuses around two classes of models. In niche theory, deterministic interactions between species, individuals, and the environment are considered the dominant factor, whereas in neutral theory, stochastic forces, such as demographic noise, speciation, and immigration, are dominant. Species abundance distributions predicted by the two classes of theory are difficult to distinguish empirically, making it problematic to deduce ecological dynamics from typical measures of diversity and community structure. Here, we show that the fusion of species abundance data with genome-derived measures of evolutionary distance can provide a clear indication of ecological dynamics, capable of quantifying the relative roles played by niche and neutral forces. We apply this technique to six gastrointestinal microbiomes drawn from three different domesticated vertebrates, using high-resolution surveys of microbial species abundance obtained from carefully curated deep 16S rRNA hypervariable tag sequencing data. Although the species abundance patterns are seemingly well fit by the neutral theory of metacommunity assembly, we show that this theory cannot account for the evolutionary patterns in the genomic data; moreover, our analyses strongly suggest that these microbiomes have, in fact, been assembled through processes that involve a significant nonneutral (niche) contribution. Our results demonstrate that high-resolution genomics can remove the ambiguities of process inference inherent in classic ecological measures and permits quantification of the forces shaping complex microbial communities.