LOCUST: a custom sequence locus typer for classifying microbial isolates

Serum susceptibility of Escherichia coli and its association with patient clinical outcomes

The innate immune system eliminates bloodstream pathogens such as Escherichia coli in part through complement protein deposition and subsequent bacterial death (i.e., "serum killing"). Some E. coli strains have developed mechanisms to resist serum killing, though the extent of variation in serum killing among bloodstream infection (BSI) isolates and the clinical impact of this variation is not well understood. To address this issue, we developed a novel assay that uses flow cytometry to perform high throughput serum bactericidal assays (SBAs) with E. coli BSI isolates (n = 183) to define the proportion of surviving bacteria after exposure to serum. We further determined whether E. coli resistance to serum killing is associated with clinical outcomes (e.g., in-hospital attributable mortality, in-hospital total mortality, septic shock) and bacterial genotype in the corresponding patients with E. coli BSI. Our novel flow cytometry-based SBA performed similarly to a traditional SBA, though with significantly decreased hands-on bench work. Among E. coli BSI isolates, the mean proportion that survived exposure to 25% serum was 0.68 (Standard deviation 0.02, range 0.57-0.93). We did not identify associations between E. coli resistance to serum killing and clinical outcomes in our adjusted models. Together, this study describes a novel flow cytometry-based approach to the bacterial SBA that allowed for high-throughput testing of E. coli BSI isolates and identified high variability in resistance to serum killing among a large set of BSI isolates.

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.

AbGRI4, a novel antibiotic resistance island in multiply antibiotic-resistant Acinetobacter baumannii clinical isolates

OBJECTIVES

To investigate the genomic context of a novel resistance island (RI) in multiply antibiotic-resistant Acinetobacter baumannii clinical isolates and global isolates.

METHODS

Using a combination of long and short reads generated from the Oxford Nanopore and Illumina platforms, contiguous chromosomes and plasmid sequences were determined. BLAST-based analysis was used to identify the RI insertion target.

RESULTS

Genomes of four multiply antibiotic-resistant A. baumannii clinical strains, from a US hospital system, belonging to prevalent MLST ST2 (Pasteur scheme) and ST281 (Oxford scheme) clade F isolates were sequenced to completion. A class 1 integron carrying aadB (tobramycin resistance) and aadA2 (streptomycin/spectinomycin resistance) was identified. The class 1 integron was 6.8 kb, bounded by IS26 at both ends, and embedded in a new target location between an α/β-hydrolase and a reductase. Due to its novel insertion site and unique RI composition, we suggest naming this novel RI AbGRI4. Molecular analysis of global A. baumannii isolates identified multiple AbGRI4 RI variants in non-ST2 clonal lineages, including variations in the resistance gene cassettes, integron backbone and insertion breakpoints at the hydrolase gene.

CONCLUSIONS

A novel RI insertion target harbouring a class 1 integron was identified in a subgroup of ST2/ST281 clinical isolates. Variants of the RI suggested evolution and horizontal transfer of the RI across clonal lineages. Long- and short-read hybrid assembly technology completely resolved the genomic context of IS-bounded RIs, which was not possible using short reads alone.

BacWGSTdb 2.0: a one-stop repository for bacterial whole-genome sequence typing and source tracking

An increasing prevalence of hospital acquired infections and foodborne illnesses caused by pathogenic and multidrug-resistant bacteria has stimulated a pressing need for benchtop computational techniques to rapidly and accurately classify bacteria from genomic sequence data, and based on that, to trace the source of infection. BacWGSTdb (http://bacdb.org/BacWGSTdb) is a free publicly accessible database we have developed for bacterial whole-genome sequence typing and source tracking. This database incorporates extensive resources for bacterial genome sequencing data and the corresponding metadata, combined with specialized bioinformatics tools that enable the systematic characterization of the bacterial isolates recovered from infections. Here, we present BacWGSTdb 2.0, which encompasses several major updates, including (i) the integration of the core genome multi-locus sequence typing (cgMLST) approach, which is highly scalable and appropriate for typing isolates belonging to different lineages; (ii) the addition of a multiple genome analysis module that can process dozens of user uploaded sequences in a batch mode; (iii) a new source tracking module for comparing user uploaded plasmid sequences to those deposited in the public databases; (iv) the number of species encompassed in BacWGSTdb 2.0 has increased from 9 to 20, which represents bacterial pathogens of medical importance; (v) a newly designed, user-friendly interface and a set of visualization tools for providing a convenient platform for users are also included. Overall, the updated BacWGSTdb 2.0 bears great utility in continuing to provide users, including epidemiologists, clinicians and bench scientists, with a one-stop solution to bacterial genome sequence analysis.

Characterization of Pneumococcal Colonization Dynamics and Antimicrobial Resistance Using Shotgun Metagenomic Sequencing in Intensively Sampled South African Infants

Background: There remains a significant proportion of deaths due to pneumococcal pneumonia in infants from low- and middle-income countries despite the marginal global declines recorded in the past decade. Monitoring changes in pneumococcal carriage is key to understanding vaccination-induced shifts in the ecology of carriage, patterns of antimicrobial resistance, and impact on health. We longitudinally investigated pneumococcal carriage dynamics in PCV-13 vaccinated infants by collecting nasopharyngeal (NP) samples at 2-weekly intervals from birth through the first year of life from 137 infants. As a proof of concept, 196 NP samples were retrieved from a subset of 23 infants to explore strain-level pneumococcal colonization patterns and associated antimicrobial-resistance determinants. These were selected on the basis of changes in serotype and antibiogram over time. NP samples underwent short-term enrichment for streptococci prior to total nucleic acid extraction and whole metagenome shotgun sequencing (WMGS). Reads were assembled and aligned to pneumococcal reference genomes for the extraction of pneumococcal and non-pneumococcal bacterial reads. Pneumococcal contigs were aligned to the Antibiotic Resistance Gene-ANNOTation database of acquired AMR genes. In silico pneumococcal capsular and multilocus sequence typing were performed.

Results: Of the 196 samples sequenced, 174 had corresponding positive cultures for pneumococci, of which, 152 were assigned an in silico serotype. Metagenomic sequencing detected a single pneumococcal serotype in 85% (129/152), and co-colonization in 15% (23/152) of the samples. Twenty-two different pneumococcal serotypes were identified, with 15B/15C and 16F being the most common non-PCV13 serotypes, while 23F and 19A were the most common PCV13 serotypes. Twenty-six different sequence types (STs), including four novel STs were identified in silico. Mutations in the folA and folP genes, associated with cotrimoxazole resistance, were detected in 89% (87/98) of cotrimoxazole-non-susceptible pneumococci, as well as in the pbp1a and pbp2x genes, in penicillin non-susceptible ST7052^15B/15C isolates.

Conclusions: Metagenomic sequencing of NP samples is a valuable culture-independent technique for a detailed evaluation of the pneumococcal component and resistome of the NP microbiome. This method allowed for the detection of novel STs, as well as co-colonization, with a predominance of non-PCV13 serotypes in this cohort. Forty-eight resistance genes, as well as mutations associated with resistance were detected, but the correlation with phenotypic non-susceptibility was lower than expected.

GGRaSP: a R-package for selecting representative genomes using Gaussian mixture models

Motivation

The vast number of available sequenced bacterial genomes occasionally exceeds the facilities of comparative genomic methods or is dominated by a single outbreak strain, and thus a diverse and representative subset is required. Generation of the reduced subset currently requires a priori supervised clustering and sequence-only selection of medoid genomic sequences, independent of any additional genome metrics or strain attributes.

Results

The Gaussian Genome Representative Selector with Prioritization (GGRaSP) R-package described below generates a reduced subset of genomes that prioritizes maintaining genomes of interest to the user as well as minimizing the loss of genetic variation. The package also allows for unsupervised clustering by modeling the genomic relationships using a Gaussian mixture model to select an appropriate cluster threshold. We demonstrate the capabilities of GGRaSP by generating a reduced list of 315 genomes from a genomic dataset of 4600 Escherichia coli genomes, prioritizing selection by type strain and by genome completeness.

Availability and implementaion

GGRaSP is available at https://github.com/JCVenterInstitute/ggrasp/.

Supplementary information

Supplementary data are available at Bioinformatics online.

Rapid Replacement of Acinetobacter baumannii Strains Accompanied by Changes in Lipooligosaccharide Loci and Resistance Gene Repertoire

The population structure of health care-associated pathogens reflects patterns of diversification, selection, and dispersal over time. Empirical data detailing the long-term population dynamics of nosocomial pathogens provide information about how pathogens adapt in the face of exposure to diverse antimicrobial agents and other host and environmental pressures and can inform infection control priorities. Extensive sequencing of clinical isolates from one hospital spanning a decade and a second hospital in the Cleveland, OH, metropolitan area over a 3-year time period provided high-resolution genomic analysis of the Acinetobacter baumannii metapopulation. Genomic analysis demonstrated an almost complete replacement of the predominant strain groups with a new, genetically distinct strain group during the study period. The new group, termed clade F, differs from other global clone 2 (GC2) strains of A. baumannii in several ways, including its antibiotic resistance and lipooligosaccharide biosynthesis genes. Clade F strains are part of a large phylogenetic group with broad geographic representation. Phylogenetic analysis of single-nucleotide variants in core genome regions showed that although the Cleveland strains are phylogenetically distinct from those isolated from other locations, extensive intermixing of strains from the two hospital systems was apparent, suggesting either substantial exchange of strains or a shared, but geographically restricted, external pool from which infectious isolates were drawn. These findings document the rapid evolution of A. baumannii strains in two hospitals, with replacement of the predominant clade by a new clade with altered lipooligosaccharide loci and resistance gene repertoires.IMPORTANCE Multidrug-resistant (MDR) A. baumannii is a difficult-to-treat health care-associated pathogen. Knowing the resistance genes present in isolates causing infection aids in empirical treatment selection. Furthermore, knowledge of the genetic background can assist in tracking patterns of transmission to limit the spread of infections in hospitals. The appearance of a new genetic background in A. baumannii strains with a different set of resistance genes and cell surface structures suggests that strong selective pressures exist, even in highly MDR pathogens. Because the new strains have levels of antimicrobial resistance similar to those of the strains that were displaced, we hypothesize that other features, including host colonization and infection, may confer additional selective advantages and contribute to their increased prevalence.

Emergence of New Delhi Metallo-β-Lactamase (NDM-5) in Klebsiella quasipneumoniae from Neonates in a Nigerian Hospital

Outbreaks of infection occur more often than they are reported in most developing countries, largely due to poor diagnostic services. A Klebsiella species bacteremia outbreak in a newborn unit with high mortality was recently encountered at a location being surveilled for childhood bacteremia. These surveillance efforts offered the opportunity to determine the cause of this neonatal outbreak. In this report, we present the whole-genome sequences of New Delhi metallo-β-lactamase (NDM-5)-containing Klebsiella quasipneumoniae subsp. similipneumoniae bloodstream isolates from a neonatal bacteremia outbreak at a tertiary hospital in Nigeria and as part of the largest collection of K. pneumoniae bloodstream isolates from children in Africa. Comparative analysis of the genetic environment surrounding the NDM-5 genes revealed nearly perfect sequence identity to blaNDM-5-bearing IncX3-type plasmids from other members of the EnterobacteriaceaeIMPORTANCE Carbapenem-resistant Klebsiella pneumoniae is of global health importance, yet there is a paucity of genome-based studies in Africa. Here we report fatal blood-borne NDM-5-producing K. quasipneumoniae subsp. similipneumoniae infections from Nigeria, Africa. New Delhi metallo-β-lactamase (NDM)-producing Klebsiella spp. are responsible for high mortality and morbidity, with the NDM-5 variant showing elevated carbapenem resistance. The prevalence of NDM-5 in Klebsiella has been limited primarily to K. pneumoniae, with only one isolate being collected from Africa. During an outbreak of sepsis in a teaching hospital in Nigeria, five NDM-5-producing K. quasipneumoniae subsp. similipneumoniae sequence type 476 isolates were identified. Given the increased resistance profile of these strains, this study highlights the emerging threat of blaNDM-5 dissemination in hospital environments. The observation of these NDM-5-producing isolates in Africa stresses the urgency to improve monitoring and clinical practices to reduce or prevent the further spread of resistance.

Closed Genome Sequences of Clinical Neisseria gonorrhoeae Strains Obtained from Combined Oxford Nanopore and Illumina Sequencing

Neisseria gonorrhoeae is the etiological agent of gonorrhea, the second most common notifiable disease in the United States. Here, we used a hybrid approach combining Oxford Nanopore Technologies MinION and Illumina MiSeq sequencing data to obtain closed genome sequences of nine clinical N. gonorrhoeae isolates.

Neisseria gonorrhoeae is the etiological agent of gonorrhea, the second most common notifiable disease in the United States. Here, we used a hybrid approach combining Oxford Nanopore Technologies MinION and Illumina MiSeq sequencing data to obtain closed genome sequences of nine clinical N. gonorrhoeae isolates.

Automatic identification of optimal marker genes for phenotypic and taxonomic groups of microorganisms

Finding optimal markers for microorganisms important in the medical, agricultural, environmental or ecological fields is of great importance. Thousands of complete microbial genomes now available allow us, for the first time, to exhaustively identify marker proteins for groups of microbial organisms. In this work, we model the biological task as the well-known mathematical “hitting set” problem, solving it based on both greedy and randomized approximation algorithms. We identify unique markers for 17 phenotypic and taxonomic microbial groups, including proteins related to the nitrite reductase enzyme as markers for the non-anammox nitrifying bacteria group, and two transcription regulation proteins, nusG and yhiF, as markers for the Archaea and Escherichia/Shigella taxonomic groups, respectively. Additionally, we identify marker proteins for three subtypes of pathogenic E. coli, which previously had no known optimal markers. Practically, depending on the completeness of the database this algorithm can be used for identification of marker genes for any microbial group, these marker genes may be prime candidates for the understanding of the genetic basis of the group's phenotype or to help discover novel functions which are uniquely shared among a group of microbes. We show that our method is both theoretically and practically efficient, while establishing an upper bound on its time complexity and approximation ratio; thus, it promises to remain efficient and permit the identification of marker proteins that are specific to phenotypic or taxonomic groups, even as more and more bacterial genomes are being sequenced.

MentaLiST - A fast MLST caller for large MLST schemes

MLST (multi-locus sequence typing) is a classic technique for genotyping bacteria, widely applied for pathogen outbreak surveillance. Traditionally, MLST is based on identifying sequence types from a small number of housekeeping genes. With the increasing availability of whole-genome sequencing data, MLST methods have evolved towards larger typing schemes, based on a few hundred genes [core genome MLST (cgMLST)] to a few thousand genes [whole genome MLST (wgMLST)]. Such large-scale MLST schemes have been shown to provide a finer resolution and are increasingly used in various contexts such as hospital outbreaks or foodborne pathogen outbreaks. This methodological shift raises new computational challenges, especially given the large size of the schemes involved. Very few available MLST callers are currently capable of dealing with large MLST schemes. We introduce MentaLiST, a new MLST caller, based on a k-mer voting algorithm and written in the Julia language, specifically designed and implemented to handle large typing schemes. We test it on real and simulated data to show that MentaLiST is faster than any other available MLST caller while providing the same or better accuracy, and is capable of dealing with MLST schemes with up to thousands of genes while requiring limited computational resources. MentaLiST source code and easy installation instructions using a Conda package are available at https://github.com/WGS-TB/MentaLiST.

Strain Level Streptococcus Colonization Patterns during the First Year of Life

Pneumococcal pneumonia has decreased significantly since the implementation of the pneumococcal conjugate vaccine (PCV), nevertheless, in many developing countries pneumonia mortality in infants remains high. We have undertaken a study of the nasopharyngeal (NP) microbiome during the first year of life in infants from The Philippines and South Africa. The study entailed the determination of the Streptococcus sp. carriage using a lytA qPCR assay, whole metagenomic sequencing, and in silico serotyping of Streptococcus pneumoniae, as well as 16S rRNA amplicon based community profiling. The lytA carriage in both populations increased with infant age and lytA+ samples ranged from 24 to 85% of the samples at each sampling time point. We next developed informatic tools for determining Streptococcus community composition and pneumococcal serotype from metagenomic sequences derived from a subset of longitudinal lytA-positive Streptococcus enrichment cultures from The Philippines (n = 26 infants, 50% vaccinated) and South African (n = 7 infants, 100% vaccinated). NP samples from infants were passaged in enrichment media, and metagenomic DNA was purified and sequenced. In silico capsular serotyping of these 51 metagenomic assemblies assigned known serotypes in 28 samples, and the co-occurrence of serotypes in 5 samples. Eighteen samples were not typeable using known serotypes but did encode for capsule biosynthetic cluster genes similar to non-encapsulated reference sequences. In addition, we performed metagenomic assembly and 16S rRNA amplicon profiling to understand co-colonization dynamics of Streptococcus sp. and other NP genera, revealing the presence of multiple Streptococcus species as well as potential respiratory pathogens in healthy infants. A range of virulence and drug resistant elements were identified as circulating in the NP microbiomes of these infants. This study revealed the frequent co-occurrence of multiple S. pneumoniae strains along with Streptococcus sp. and other potential pathogens such as S. aureus in the NP microbiome of these infants. In addition, the in silico serotype analysis proved powerful in determining the serotypes in S. pneumoniae carriage, and may lead to developing better targeted vaccines to prevent invasive pneumococcal disease (IPD) in these countries. These findings suggest that NP colonization by S. pneumoniae during the first years of life is a dynamic process involving multiple serotypes and species.