- Volume 8, Issue 12, 2022

Staphylococcus aureus is a leading cause of skin and soft tissue infections and systemic infections. Wall teichoic acids (WTAs) are cell wall-anchored glycopolymers that are important for S. aureus nasal colonization, phage-mediated horizontal gene transfer, and antibiotic resistance. WTAs consist of a polymerized ribitol phosphate (RboP) chain that can be glycosylated with N-acetylglucosamine (GlcNAc) by three glycosyltransferases: TarS, TarM, and TarP. TarS and TarP modify WTA with β-linked GlcNAc at the C-4 (β1,4-GlcNAc) and the C-3 position (β1,3-GlcNAc) of the RboP subunit, respectively, whereas TarM modifies WTA with α-linked GlcNAc at the C-4 position (α1,4-GlcNAc). Importantly, these WTA glycosylation patterns impact immune recognition and clearance of S. aureus . Previous studies suggest that tarS is near-universally present within the S. aureus population, whereas a smaller proportion co-contain either tarM or tarP. To gain more insight into the presence and genetic variation of tarS, tarM and tarP in the S. aureus population, we analysed a collection of 25 652 S . aureus genomes within the PubMLST database. Over 99 % of isolates contained tarS. Co-presence of tarS/tarM or tarS/tarP occurred in 37 and 7 % of isolates, respectively, and was associated with specific S. aureus clonal complexes. We also identified 26 isolates (0.1 %) that contained all three glycosyltransferase genes. At sequence level, we identified tar alleles with amino acid substitutions in critical enzymatic residues or with premature stop codons. Several tar variants were expressed in a S. aureus tar-negative strain. Analysis using specific monoclonal antibodies and human langerin showed that WTA glycosylation was severely attenuated or absent. Overall, our data provide a broad overview of the genetic diversity of the three WTA glycosyltransferases in the S. aureus population and the functional consequences for immune recognition.

Pantoea ananatis is a bacterium that is found in many agronomic crops and agricultural pests. Here, we isolated a P. ananatis strain (Lstr) from the rice planthopper Laodelphax striatellus, a notorious pest that feeds on rice plant sap and transmits rice viruses, in order to examine its genome and biology. P. ananatis Lstr is an insect symbiont that is pathogenic to the host insect and appears to mostly inhabit the gut. Its pathogenicity thus raises the possibility of using the Lstr strain as a biological agent. To this end, we analysed the genome of the Lstr strain and compared it with the genomes of other Pantoea species. Our analysis of these genomes shows that P. ananatis can be divided into two mono-phylogenetic clades (clades one and two). The Lstr strain belongs to clade two and is grouped with P. ananatis strains that were isolated from rice or rice-associated samples. A comparative genomic analysis shows that clade two differs from clade one in many genomic characteristics including genome structures, mobile elements, and categories of coding proteins. The genomes of clade two P . ananatis are significantly smaller, have much fewer coding sequences but more pseudogenes than those of clade one, suggesting that clade two species are at the early stage of genome reduction. On the other hand, P. ananatis has a type VI secretion system that is highly variable but cannot be separated by clades. These results clarify our understanding of P. ananatis ’ phylogenetic diversity and provide clues to the interactions between P. ananatis , host insect, and plant that may lead to advances in rice protection and pest control.

The Pacific oyster (PO), Crassostrea gigas, is an important commercial marine species but periodically experiences large stock losses due to disease events known as summer mortality. Summer mortality has been linked to environmental perturbations and numerous viral and bacterial agents, indicating this disease is multifactorial in nature. In 2013 and 2014, several summer mortality events occurred within the Port Stephens estuary (NSW, Australia). Extensive culture and molecular-based investigations were undertaken and several potentially pathogenic Vibrio species were identified. To improve species identification and genomically characterise isolates obtained from this outbreak, whole-genome sequencing (WGS) and subsequent genomic analyses were performed on 48 bacterial isolates, as well as a further nine isolates from other summer mortality studies using the same batch of juveniles. Average nucleotide identity (ANI) identified most isolates to the species level and included members of the Photobacterium , Pseudoalteromonas , Shewanella and Vibrio genera, with Vibrio species making up more than two-thirds of all species identified. Construction of a phylogenomic tree, ANI analysis, and pan-genome analysis of the 57 isolates represents the most comprehensive culture-based phylogenomic survey of Vibrios during a PO summer mortality event in Australian waters and revealed large genomic diversity in many of the identified species. Our analysis revealed limited and inconsistent associations between isolate species and their geographical origins, or host health status. Together with ANI and pan-genome results, these inconsistencies suggest that to determine the role that microbes may have in Pacific oyster summer mortality events, isolate identification must be at the taxonomic level of strain. Our WGS data (specifically, the accessory genomes) differentiated bacterial strains, and coupled with associated metadata, highlight the possibility of predicting a strain’s environmental niche and level of pathogenicity.

The use of whole metagenomic data to infer the relative abundance of all its microbes is well established. The same data can be used to determine the replication rate of all eubacterial taxa with circular chromosomes. Despite their availability, the replication rate profiles (metareplicome) have not been fully exploited in microbiome analyses. Another relatively new approach is the application of causal inferencing to analyse microbiome data that goes beyond correlational studies. A novel scalable pipeline called MeRRCI (Metagenome, metaResistome, and metaReplicome for Causal Inferencing) was developed. MeRRCI combines efficient computation of the metagenome (bacterial relative abundance), metaresistome (antimicrobial gene abundance) and metareplicome (replication rates), and integrates environmental variables (metadata) for causality analysis using Bayesian networks. MeRRCI was applied to an infant gut microbiome data set to investigate the microbial community’s response to antibiotics. Our analysis suggests that the current treatment stratagem contributes to preterm infant gut dysbiosis, allowing a proliferation of pathobionts. The study highlights the specific antibacterial resistance genes that may contribute to exponential cell division in the presence of antibiotics for various pathogens, namely Klebsiella pneumoniae, Citrobacter freundii, Staphylococcus epidermidis, Veilonella parvula and Clostridium perfringens . These organisms often contribute to the harmful long-term sequelae seen in these young infants.

Escherichia coli bloodstream infections are typically attributed to a limited number of lineages that carry virulence factors associated with invasiveness. In Nigeria, the identity of circulating clones is largely unknown and surveillance of their antimicrobial resistance has been limited. We verified and whole-genome sequenced 68 2016–2018 bloodstream E. coli isolates from three sentinel sites in South-Western Nigeria and susceptibility tested 67 of them. Resistance to antimicrobials commonly used in Nigeria was high, with 67 (100 %), 62 (92.5 %), 53 (79.1 %) and 37 (55.2 %) showing resistance to trimethoprim, ampicillin, ciprofloxacin and aminoglycosides, respectively. Thirty-five (51 %) isolates carried extended-spectrum β-lactamase genes and 32 (91 %) of these were multidrug resistant. All the isolates were susceptible to carbapenems and colistin. The strain set included globally disseminated high-risk clones from sequence type (ST)12 (2), ST131 (12) and ST648 (4). Twenty-three (33.8 %) of the isolates clustered within two clades. The first of these consisted of ST131 strains, comprising O16:H5 and O25:H4 sub-lineages. The second was an ST10–ST167 complex clade comprising strains carrying O-antigen and capsular genes of likely Klebsiella origin, identical to those of avian pathogenic E. coli Sanji, and serotyped in silico as O89, O101 or ONovel32, depending on the tool used. Four temporally associated ST90 strains from one sentinel were closely related enough to suggest that at least some of them represented a retrospectively detected outbreak cluster. Our data implicate a broad repertoire of E. coli isolates associated with bloodstream infections in South-West Nigeria. Continued genomic surveillance is valuable for tracking clones of importance and for outbreak identification.

Clinical Enterobacteriaceae isolates that produce extended-spectrum β-lactamases (ESBLs) have been increasingly reported at a global scale. However, comprehensive data on the molecular epidemiology of ESBL-producing strains are limited and few studies have been conducted in non-outbreak situations.

We used whole-genome sequencing to describe the population structure of 294 ESBL-producing Escherichia coli and Klebsiella pneumoniae isolates that were recovered from a German community hospital throughout a 1 year sampling period in a non-outbreak situation.

We found a high proportion of E. coli isolates (61.5 %) belonged to the globally disseminated extraintestinal pathogenic ST131, whereas a wider diversity of STs was observed among K. pneumoniae isolates. The E. coli ST131 population in this study was shaped by multiple introductions of strains as demonstrated by contextual genomic analysis including ST131 strains from other geographical sources. While no recent common ancestor of the isolates of the current study and other international isolates was found, our clinical isolates clustered with those previously recovered in the region. Furthermore, we found that the isolation of ESBL-producing clinical strains in hospitalized patients could only rarely be associated with likely patient-to-patient transmission, indicating primarily a community and regional acquisition of strains.

Further genomic analyses of clinical, carriage and environmental isolates is needed to uncover hidden transmissions and thus discover the most common sources of ESBL-producing pathogen infections in our hospitals.

The White–Kauffmann–Le Minor (WKL) scheme is the most widely used Salmonella typing scheme for reporting the disease prevalence of the enteric pathogen. With the advent of whole-genome sequencing (WGS), in silico methods have increasingly replaced traditional serotyping due to reproducibility, speed and coverage. However, despite integrating genomic-based typing by in silico serotyping tools such as SISTR, in silico serotyping in certain contexts remains ambiguous and insufficiently informative. Specifically, in silico serotyping does not attempt to resolve polyphyly. Furthermore, in spite of the widespread acknowledgement of polyphyly from genomic studies, the prevalence of polyphyletic serovars is not well characterized. Here, we applied a genomics approach to acquire the necessary resolution to classify genetically discordant serovars and propose an alternative typing scheme that consistently reflect natural Salmonella populations. By accessing the unprecedented volume of bacterial genomic data publicly available in GenomeTrakr and PubMLST databases (>180 000 genomes representing 723 serovars), we characterized the global Salmonella population structure and systematically identified putative non-monophyletic serovars. The proportion of putative non-monophyletic serovars was estimated higher than previous reports, reinforcing the inability of antigenic determinants to depict the complexity of Salmonella evolutionary history. We explored the extent of genetic diversity masked by serotyping labels and found significant intra-serovar molecular differences across many clinically important serovars. To avoid false discovery due to incorrect in silico serotyping calls, we cross-referenced reported serovar labels and concluded a low error rate in in silico serotyping. The combined application of clustering statistics and genome-wide association methods demonstrated effective characterization of stable bacterial populations and explained functional differences. The collective methods adopted in our study have practical values in establishing genomic-based typing nomenclatures for an entire microbial species or closely related subpopulations. Ultimately, we foresee an improved typing scheme to be a hybrid that integrates both genomic and antigenic information such that the resolution from WGS is leveraged to improve the precision of subpopulation classification while preserving the common names defined by the WKL scheme.

The antibiotic formulary is threatened by high rates of antimicrobial resistance (AMR) among enteropathogens. Enteric bacteria are exposed to anaerobic conditions within the gastrointestinal tract, yet little is known about how oxygen exposure influences AMR. The facultative anaerobe Vibrio cholerae was chosen as a model to address this knowledge gap. We obtained V. cholerae isolates from 66 cholera patients, sequenced their genomes, and grew them under anaerobic and aerobic conditions with and without three clinically relevant antibiotics (ciprofloxacin, azithromycin, doxycycline). For ciprofloxacin and azithromycin, the minimum inhibitory concentration (MIC) increased under anaerobic conditions compared to aerobic conditions. Using standard resistance breakpoints, the odds of classifying isolates as resistant increased over 10 times for ciprofloxacin and 100 times for azithromycin under anaerobic conditions compared to aerobic conditions. For doxycycline, nearly all isolates were sensitive under both conditions. Using genome-wide association studies, we found associations between genetic elements and AMR phenotypes that varied by oxygen exposure and antibiotic concentrations. These AMR phenotypes were more heritable, and the AMR-associated genetic elements were more often discovered, under anaerobic conditions. These AMR-associated genetic elements are promising targets for future mechanistic research. Our findings provide a rationale to determine whether increased MICs under anaerobic conditions are associated with therapeutic failures and/or microbial escape in cholera patients. If so, there may be a need to determine new AMR breakpoints for anaerobic conditions.

Comparing obligate endosymbionts with their free-living relatives is a powerful approach to investigate the evolution of symbioses, and it has led to the identification of several genomic traits consistently associated with the establishment of symbiosis. ‘Candidatus Nebulobacter yamunensis’ is an obligate bacterial endosymbiont of the ciliate Euplotes that seemingly depends on its host for survival. A subsequently characterized bacterial strain with an identical 16S rRNA gene sequence, named Fastidiosibacter lacustris , can instead be maintained in pure culture. We analysed the genomes of ‘Candidatus Nebulobacter’ and Fastidiosibacter seeking to identify key differences between their functional traits and genomic structure that might shed light on a recent transition to obligate endosymbiosis. Surprisingly, we found almost no such differences: the two genomes share a high level of sequence identity, the same overall structure, and largely overlapping sets of genes. The similarities between the genomes of the two strains are at odds with their different ecological niches, confirmed here with a parallel growth experiment. Although other pairs of closely related symbiotic/free-living bacteria have been compared in the past, ‘Candidatus Nebulobacter’ and Fastidiosibacter represent an extreme example proving that a small number of (unknown) factors might play a pivotal role in the earliest stages of obligate endosymbiosis establishment.