Biology subjects

van der Putten, B. C.

Publications and source records attributed to van der Putten, B. C..

6 recordsLinked to original sources

bioRxiv2023

The streptococcal phase-variable Type I Restriction-Modification system SsuCC20p dictates the methylome of Streptococcus suis and impacts virulence

Phase-variable Type I Restriction Modification (RM) systems are epigenetic regulatory systems that have been identified in numerous human bacterial pathogens. We previously showed that an emerging zoonotic lineage of Streptococcus suis acquired a phase-variable Type I RM system named SsuCC20p. The SsuCC20p locus was present in the genome of disease-associated isolates from multiple streptococcal species. This indicates that it is not restricted to S. suis and can be acquired through horizontal gene transfer. We demonstrate that SsuCC20p phase-variability relies on a recombinase present within the locus. In vitro, only SsuCC20p is responsible for the genome methylation profiles that were detected in the representative zoonotic S. suis isolate 861160. In addition, we show that, contrary to previous observations, hsdS genes located downstream of the hsdM gene and the recombinase gene, can contribute to the SsuCC20p genome methylation profile. SsuCC20p locked mutants expressing a single hsdS each showed unique genome methylation profiles. The differential genome methylation of the distinct locked mutants caused phase dependent differences in global gene expression in a growth condition dependent manner. We observed significant differences in virulence between hsdS locked mutants in a zebrafish larvae infection model. These data indicate that the streptococcal phase-variable Type I RM system SsuCC20p can impact bacterial virulence via epigenetic regulation of gene expression and potentially contributes to the zoonotic potential of S. suis. ImportancePhase-variation contributes to the virulence of bacterial pathogens as it allows a single strain to produce phenotypic diverse subpopulations. Phase-variable Restriction Modification (RM) systems are systems that allow for such phase-variation via epigenetic regulation of gene expression levels. The phase-variable RM system SsuCC20p was found in multiple streptococcal species and was acquired by an emerging zoonotic lineage of Streptococcus suis. We show that the phase-variability of SsuCC20p is dependent on a recombinase encoded within the SsuCC20p locus. We characterized the genome methylation profiles of the different phases of SsuCC20p and showed that the differential genome methylation within the phases causes differences in gene expression levels and virulence. Altogether, we show that the acquisition of a phase-variable RM system impacts virulence and can potentially contribute to the zoonotic potential of S. suis. Bacterial pathogens can increase their virulence through acquisition of mobile elements containing epigenetic regulatory systems such as RM systems.

microbiology↗

bioRxiv2023

Novel emm4 lineage associated with an upsurge in invasive group A streptococcal disease in the Netherlands, 2022

Invasive group A streptococcal (iGAS) disease cases increased in the first half year of 2022 in the Netherlands with a remarkably high proportion of emm4 isolates. Whole-genome sequence analysis of 66 emm4 isolates, 40 isolates from the pre-COVID-19-pandemic period 2009-2019 and 26 contemporary isolates from 2022, identified a novel Streptococcus pyogenes lineage (M4NL22), which accounted for 85% emm4 iGAS cases in 2022. Surprisingly, we detected few isolates of the emm4 hypervirulent clone, which has replaced nearly all other emm4 in the USA and the UK. M4NL22 displayed genetic differences compared to other emm4 strains, although these were of unclear biological significance. In publicly available data, we identified a single Norwegian isolate belonging to M4NL22, which was sampled after the isolates from this study, possibly suggesting export of M4NL22 to Norway. In conclusion, our study identified a novel S. pyogenes emm4 lineage underlying an increase of iGAS disease in early 2022 in the Netherlands and results have been promptly communicated with public health officials. Impact statementGroup A Streptococcus (predominantly comprising Streptococcus pyogenes) has a long history of causing disease in humans. Over the past decades, researchers have described various changes in the S. pyogenes population circulating in humans. In this study, we describe a shift in the S. pyogenes population within type emm4 in the Netherlands in early 2022. A novel lineage, which we termed M4NL22, became the predominant emm4 lineage during this period. This was surprising, as in other countries such as the USA and the UK, another recently emerged lineage became dominant. Our work informed public health officials on the possible causes of increased S. pyogenes cases in the Netherlands and underlines the added value of continued active bacteriological surveillance. Data summaryCode is freely available from https://github.com/boasvdp/GAS_M4. All sequencing data is freely available from BioProject PRJEB58654.

microbiology↗

bioRxiv2021

Benchmarking topological accuracy of bacterial phylogenomic workflows using in silico evolution

Phylogenetic analyses are widely used in microbiological research, for example to trace the progression of bacterial outbreaks based on whole-genome sequencing data. In practice, multiple analysis steps such as de novo assembly, alignment and phylogenetic inference are combined to form phylogenetic workflows. Comprehensive benchmarking of the accuracy of complete phylogenetic workflows is lacking. To benchmark different phylogenetic workflows, we simulated bacterial evolution under a wide range of evolutionary models, varying the relative rates of substitution, insertion, deletion, gene duplication, gene loss and lateral gene transfer events. The generated datasets corresponded to a genetic diversity usually observed within bacterial species ([≥]95% average nucleotide identity). We replicated each simulation three times to assess replicability. In total, we benchmarked seventeen distinct phylogenetic workflows using 8 different simulated datasets. We found that recently developed k-mer alignment methods such as kSNP and SKA achieve similar accuracy as reference mapping. The high accuracy of k-mer alignment methods can be explained by the large fractions of genomes these methods can align, relative to other approaches. We also found that the choice of de novo assembly algorithm influences the accuracy of phylogenetic reconstruction, with workflows employing SPAdes or SKESA outperforming those employing Velvet. Finally, we found that the results of phylogenetic benchmarking are highly variable between replicates. We conclude that for phylogenomic reconstruction k-mer alignment methods are relevant alternatives to reference mapping at species level, especially in the absence of suitable reference genomes. We show de novo genome assembly accuracy to be an underappreciated parameter required for accurate phylogenomic reconstruction. Impact statementPhylogenetic analyses are crucial to understand the evolution and spread of microbes. Among their many applications is the reconstruction of transmission events which can provide information on the progression of pathogen outbreaks. For example, to investigate foodborne outbreaks such as the 2011 outbreak of Escherichia coli O104:H4 across Europe. As different microbes evolve differently, it is important to know which phylogenetic workflows are most accurate when working with diverse bacterial data. However, benchmarks usually consider only a limited dataset. We therefore employed a range of simulated evolutionary scenarios and benchmarked seventeen phylogenetic workflows on these simulated datasets. An advantage of our simulation approach is that we know a priori what the outcome of the analyses should be, allowing us to benchmark accuracy. We found significant differences between phylogenetic workflows and were able to dissect which factors contribute to phylogenetic analysis accuracy. Taken together, this new information will hopefully enable more accurate phylogenetic analysis of bacterial outbreaks. Data summaryA Zenodo repository is available at https://doi.org/10.5281/zenodo.5036179 containing all simulated genomes, all alignments produced by phylogenetic workflows and .csv files summarising the topological accuracies of phylogenies produced based on these alignments. Code is available at https://github.com/niekh-13/phylogenetic_workflows.

genomics↗

bioRxiv2020

Extraintestinal pathogenic (ExPEC) lineages explain prolonged faecal carriage of travel-acquired extended-spectrum β-lactamase-producing Escherichia coli

ObjectivesExtended-spectrum {beta}-lactamase-producing Escherichia coli (ESBL-Ec) are frequently acquired during international travel, contributing to the global spread of antimicrobial resistance. Human-adapted ESBL-Ec are predicted to exhibit increased intestinal carriage duration, resulting in a higher likelihood of onward human-to-human transmission. Yet, bacterial determinants of increased carriage duration are unknown. Previous studies analysed small traveler cohorts, with short follow-up times, or did not employ high-resolution molecular typing, and were thus unable to identify bacterial traits associated with long-term carriage. MethodsIn a prospective cohort study of 2001 international travelers, we analysed 160 faecal ESBL-Ec isolates from all 38 travelers who acquired ESBL-Ec during travel and subsequently carried ESBL-Ec for at least 12 months after return, by whole-genome sequencing. For 17 travelers, we confirmed the persistence of ESBL-Ec strains through single nucleotide variant typing. To identify determinants of increased carriage duration, we compared the 17 long-term carriers ([≥]12 months carriage) with 33 age-, sex- and destination-matched short-term carriers (<1 month carriage). Long-read sequencing was employed to investigate ESBL plasmid persistence. ResultsWe show that in healthy travelers with very low antibiotic usage, extraintestinal pathogenic lineages of E. coli (ExPEC) are significantly more likely to persist than other E. coli lineages. The long-term carriage of E. coli from ExPEC lineages is mainly driven by sequence type 131 and phylogroup D E. coli. ConclusionsAlthough ExPEC frequently cause extra-intestinal infections such as bloodstream infections, our results imply that ExPEC are also efficient intestinal colonizers, which potentially contributes to their onward transmission.

microbiology↗

bioRxiv2019

Genomic evidence for revising the Escherichia genus and description of Escherichia ruysiae sp. nov.

The Escherichia genus comprises four species and at least five lineages currently not assigned to any species, termed Escherichia cryptic clades. We isolated an Escherichia strain from an international traveller and resolved the complete DNA sequence of the chromosome and an IncI multi-drug resistance plasmid using Illumina and Nanopore whole-genome sequencing (WGS). Strain OPT1704T can be differentiated from existing Escherichia spp. using biochemical (VITEK2) and genomic tests (average nucleotide identity [ANI] and digital DNA:DNA hybridisation [dDDH]). Phylogenetic analysis based on alignment of 16S rRNA sequences and 682 concatenated core genes showed similar results. Our analysis further revealed that strain OPT1704T falls within Escherichia cryptic clade IV, and is closely related to cryptic clade III. Combining our analyses with publicly available WGS data of cryptic clades III and IV from Enterobase confirmed the close relationship between clades III and IV (>96% interclade ANI), warranting assignment of both clades to the same novel species. We propose E. ruysiae sp. nov. as a novel species, encompassing Escherichia cryptic clades III and IV (type strain OPT1704T = NCCB 100732T = NCTC 14359T). Author notesThe Genbank accession number for the 16S rRNA gene sequence of strain OPT1704T is LR745848. The Genbank accession number for the complete genome sequence of strain OPT1704T is CABVLQ000000000.

microbiology↗

bioRxiv2018

Quantifying the contribution of four resistance mechanisms to ciprofloxacin minimum inhibitory concentration in Escherichia coli: a systematic review

SynopsisO_ST_ABSIntroductionC_ST_ABSCiprofloxacin resistance in Escherichia coli is widespread and adds to the burden of E. coli infections. Reviews assessing the genetic basis of ciprofloxacin resistance have mostly been qualitative. However, to allow for the prediction of a resistance phenotype of clinical relevance based on genotypic characteristics, it is essential to quantify the contribution of prevalent genotypic determinants to resistance. We carried out a systematic review to assess the relative contribution of currently known genomic resistance determinants to the minimum inhibitory concentration (MIC) of ciprofloxacin in E. coli.\n\nMethodsPubMed and Web of Science were searched for English language studies that assessed both ciprofloxacin MIC and the presence or introduction of genetic determinants of ciprofloxacin resistance in E. coli. We included experimental and observational studies without time restrictions. Medians and ranges of MIC fold changes were calculated for each resistance determinant and for combinations of determinants.\n\nResultsWe included 66 studies, describing 604 E. coli isolates that carried at least one genetic resistance determinant. Genes coding for targets of ciprofloxacin (gyrA and parC) are strongest contributors to ciprofloxacin resistance, with median MIC fold increases ranging from 24 (range 4-133) for single Ser83Leu (gyrA) mutants to 1533 (range 256-8533) for triple Ser83Leu, Asp87Asn/Gly (gyrA) and Ser80Ile/Arg (parC) mutants. Other resistance mechanisms, including efflux, physical blocking or enzymatic modification, conferred smaller increases in ciprofloxacin MIC (median MIC fold increases typically around 15, range 1-125). However, the (combined) presence of these other resistance mechanisms further increases resistance with median MIC fold increases of up to 4000, and even in the absence of gyrA and parC mutations up to 250.\n\nConclusionThis report provides a comprehensive and quantitative overview of the contribution of different genomic determinants to ciprofloxacin resistance in E. coli. Additionally, the data demonstrate the complexity of resistance phenotype prediction from genomic data and could serve as a reference point for studies aiming to address ciprofloxacin resistance prediction using genomics, in E. coli.

microbiology↗