Characteristics and genomic epidemiology of colistin-resistant Enterobacterales from farmers, swine, and hospitalized patients in Thailand, 2014-2017.

BACKGROUND: Colistin is one of the last resort therapeutic options for treating carbapenemase-producing Enterobacterales, which are resistant to a broad range of beta-lactam antibiotics. However, the increased use of colistin in clinical and livestock farming settings in Thailand and China, has led to the inevitable emergence of colistin resistance. To better understand the rise of colistin-resistant strains in each of these settings, we characterized colistin-resistant Enterobacterales isolated from farmers, swine, and hospitalized patients in Thailand. METHODS: Enterobacterales were isolated from 149 stool samples or rectal swabs collected from farmers, pigs, and hospitalized patients in Thailand between November 2014-December 2017. Confirmed colistin-resistant isolates were sequenced. Genomic analyses included species identification, multilocus sequence typing, and detection of antimicrobial resistance determinants and plasmids. RESULTS: The overall colistin-resistant Enterobacterales colonization rate was 26.2% (n = 39/149). The plasmid-mediated colistin-resistance gene (mcr) was detected in all 25 Escherichia coli isolates and 9 of 14 (64.3%) Klebsiella spp. isolates. Five novel mcr allelic variants were also identified: mcr-2.3, mcr-3.21, mcr-3.22, mcr-3.23, and mcr-3.24, that were only detected in E. coli and Klebsiella spp. isolates from farmed pigs. CONCLUSION: Our data confirmed the presence of colistin-resistance genes in combination with extended spectrum beta-lactamase genes in bacterial isolates from farmers, swine, and patients in Thailand. Differences between the colistin-resistance mechanisms of Escherichia coli and Klebsiella pneumoniae in hospitalized patients were observed, as expected. Additionally, we identified mobile colistin-resistance mcr-1.1 genes from swine and patient isolates belonging to plasmids of the same incompatibility group. This supported the possibility that horizontal transmission of bacterial strains or plasmid-mediated colistin-resistance genes occurs between humans and swine.

Genomic and clinical characterisation of multidrug-resistant carbapenemase-producing ST231 and ST16 Klebsiella pneumoniae isolates colonising patients at Siriraj hospital, Bangkok, Thailand from 2015 to 2017.

BACKGROUND: Infections caused by carbapenemase-producing Enterobacteriaceae (CPE) have continually grown as a global public health threat, with significant mortality rates observed across the world. We examined the clinical data from patients with CPE infections and their outcomes, concentrating on Klebsiella pneumoniae isolates. We analysed the clinical information, performed antimicrobial susceptibility testing, and conducted molecular epidemiological and genomic analyses on the isolates to identify patterns in the data. METHODS: The clinical characteristics of 33 hospitalised patients with confirmed CPE, including patient-related factors associated with the development of CPE infections, were examined. Patients were divided according to whether they were "colonised" or "infected" with CPE and by the timing and frequency of their rectal swab collections, from which 45 swabs were randomly selected for analysis. CPE isolates were purified, and antimicrobial susceptibility tests performed. Whole genome sequences of these isolates were determined and analysed to compute bacterial multilocus sequence types and plasmid replicon types, infer phylogenetic relationships, and identify antimicrobial resistance and virulence genes. RESULTS: Altogether, 88.9% (40/45) of the CPE isolates were K. pneumoniae. The most abundant carbapenemase gene family in the K. pneumoniae isolates (33/39) was blaOXA-232, with blaNDM-1 additionally identified in 19 of them. All CPE isolates carrying either blaOXA-232 or blaNDM-1 were resistant to meropenem, but only 40 from 45 were susceptible to colistin. Among the CPE-infected patients (n = 18) and CPE-colonised patients who developed CPE infections during the study (n = 3), all but one received standard colistin-based combination therapy. Phylogenetic analysis revealed the polyclonal spread of carbapenemase-producing K. pneumoniae (CPKP) within the patient population, with the following two major subclades identified: ST16 (n = 15) and ST231 (n = 14). CPKP-ST231 had the highest virulence score of 4 and was associated with primary bacteraemia. The siderophores yersiniabactin and aerobactin, considered to be important virulence factors, were only identified in the CPKP-ST231 genomes. CONCLUSIONS: This study has revealed the genomic features of colonising CPE isolates, focusing on antimicrobial resistance and virulence determinants. This type of multi-layered analysis can be further exploited in Thailand and elsewhere to modify the regimes used for empirical antibiotic treatment and improve the management strategies for CPE infections in hospitalised patients.

ARGONAUT-I: Activity of Cefiderocol (S-649266), a Siderophore Cephalosporin, against Gram-Negative Bacteria, Including Carbapenem-Resistant Nonfermenters and Enterobacteriaceae with Defined Extended-Spectrum ß-Lactamases and Carbapenemases.

The activity of the siderophore cephalosporin cefiderocol is targeted against carbapenem-resistant Gram-negative bacteria. In this study, the activity of cefiderocol against characterized carbapenem-resistant Acinetobacter baumannii complex, Stenotrophomonas maltophilia, Pseudomonas aeruginosa, and Enterobacteriaceae strains was determined by microdilution in iron-depleted Mueller-Hinton broth. The MIC90s against A. baumannii, S. maltophilia, and P. aeruginosa were 1, 0.25, and 0.5 mg/liter, respectively. Against Enterobacteriaceae, the MIC90 was 1 mg/liter for the group harboring OXA-48-like, 2 mg/liter for the group harboring KPC-3, and 8 mg/liter for the group harboring TEM/SHV ESBL, NDM, and KPC-2.

MPrESS: An R-Package for Accurately Predicting Power for Comparisons of 16S rRNA Microbiome Taxa Distributions including Simulation by Dirichlet Mixture Modeling.

Deep sequencing has revealed that the 16S rRNA gene composition of the human microbiome can vary between populations. However, when existing data are insufficient to address the desired study questions due to limited sample sizes, Dirichlet mixture modeling (DMM) can simulate 16S rRNA gene predictions from experimental microbiome data. We examined the extent to which simulated 16S rRNA gene microbiome data can accurately reflect the diversity within that identified from experimental data and calculate the power. Even when experimental and simulated datasets differed by less than 10%, simulation by DMM consistently overestimates power, except when using only highly discriminating taxa. Admixtures of DMM with experimental data performed poorly compared to pure simulation and did not show the same correlation with experimental data p-value and power values. While multiple replications of random sampling remain the favored method of determining the power, when the estimated sample size required to achieve a certain power exceeds the sample number, then simulated samples based on DMM can be used. We introduce an R-Package, MPrESS, to assist in power calculation and sample size estimation for a 16S rRNA gene microbiome dataset to detect a difference between populations. MPrESS can be downloaded from GitHub.

Sampling from four geographically divergent young female populations demonstrates forensic geolocation potential in microbiomes.

Studies of human microbiomes using new sequencing techniques have increasingly demonstrated that their ecologies are partly determined by the lifestyle and habits of individuals. As such, significant forensic information could be obtained from high throughput sequencing of the human microbiome. This approach, combined with multiple analytical techniques demonstrates that bacterial DNA can be used to uniquely identify an individual and to provide information about their life and behavioral patterns. However, the transformation of these findings into actionable forensic information, including the geolocation of the samples, remains limited by incomplete understanding of the effects of confounding factors and the paucity of diverse sequences. We obtained 16S rRNA sequences of stool and oral microbiomes collected from 206 young and healthy females from four globally diverse populations, in addition to supporting metadata, including dietary and medical information. Analysis of these microbiomes revealed detectable geolocation signals between the populations, even for populations living within the same city. Accounting for other lifestyle variables, such as diet and smoking, lessened but does not remove the geolocation signal.

Forensic Microbiome Database: A Tool for Forensic Geolocation Meta-Analysis Using Publicly Available 16S rRNA Microbiome Sequencing.

The human microbiome has been proposed as a tool to investigate different forensic questions, including for the identification of multiple personal information. However, the fragmented state of the publicly available data has retarded the development of analysis techniques and, therefore, the implementation of microbiomes as a forensic tool. To address this, we introduce the forensic microbiome database (FMD), which is a collection of 16S rRNA data and associated metadata generated from publicly available data. The raw data was further normalized and processed using a pipeline to create a standardized data set for downstream analysis. We present a website allowing for the exploration of geolocation signals in the FMD. The website allows users to investigate the taxonomic differences between microbiomes harvested from different locations and to predict the geolocation of their data based on the FMD sequences. All the results are presented in dynamic graphics to allow for a rapid and intuitive investigation of the taxonomic distributions underpinning the geolocation signals and prediction between locations. Apart from the forensic aspect, the database also allows exploration and comparison of microbiome samples from different geolocation and between different body sites. The goal of the FMD is to provide the scientific and non-scientific communities with data and tools to explore the possibilities of microbiomes to answer forensic questions and serve as a model for any future such databases.

Spatial and Environmental Variation of the Human Hair Microbiota.

The skin is a complex living ecosystem harboring diverse microbial communities. Its highly variable properties and influence of intrinsic and extrinsic factors creates unique microenvironments where niche-specific microbes thrive. As part of the skin, hair supports its own microbial habitat that is also intra and inter-personal variable. This little explored substrate has significant potential in forensics microbiome research due to the unique signatures that are available on an individual. To further investigate this, we explored the hair microbiota from scalp and pubic regions in healthy adults to investigate how the hair shaft microenvironment varies microbially. Our results suggest that there are distinct differences between the microbial communities identified on hair shafts originating from different parts of the body. The taxonomic composition of the communities from different hair sources are most reminiscent of those identified from their associated cutaneous region. We further demonstrate that the hair microbiota varies by geographical origin and has the potential to be used to predict the source location of the hair.

Sequence heterogeneity of the PenA carbapenemase in clinical isolates of Burkholderia multivorans.

Multidrug-resistant gram-negative pathogens are a significant health threat. Burkholderia spp. encompass a complex subset of gram-negative bacteria with a wide range of biological functions that include human, animal, and plant pathogens. The treatment of infections caused by Burkholderia spp. is problematic due to their inherent resistance to multiple antibiotics. The major ß-lactam resistance determinant expressed in Burkholderia spp. is a class A ß-lactamase of the PenA family. In this study, significant amino acid sequence heterogeneity was discovered in PenA (37 novel variants) within a panel of 48 different strains of Burkholderia multivorans isolated from individuals with cystic fibrosis. Phylogenetic analysis distributed the 37 variants into 5 groups based on their primary amino acid sequences. Amino acid substitutions were present throughout the entire ß-lactamase and did not congregate to specific regions of the protein. The PenA variants possessed 5 to 17 single amino acid changes. The N189S and S286I substitutions were most prevalent and found in all variants. Due to the sequence heterogeneity in PenA, a highly conserved peptide (18 amino acids) within PenA was chosen as the antigen for polyclonal antibody production in order to measure expression of PenA within the 48 clinical isolates of B. multivorans. Characterization of the anti-PenA peptide antibody, using immunoblotting approaches, exposed several unique features of this antibody (i.e., detected <500 pg of purified PenA, all 37 PenA variants in B. multivorans, and Pen-like ß-lactamases from other species within the Burkholderia cepacia complex). The significant sequence heterogeneity found in PenA may have occurred due to selective pressure (e.g., exposure to antimicrobial therapy) within the host. The contribution of these changes warrants further investigation.