7th joint conference "Joint Microbiology & Infection Conference 2024" of the DGHM and VAAM

Prof. Dr.

Chair

PD. Dr.

HyDRA - Identifying recently acquired antibiotic resistance genes using machine learning

Molecular Infection Epidemiology and Prediction of Antimicrobial Resistance 

The spread of antibiotic resistance poses a significant threat to humanity [1]. Rapid and accurate detection of antibiotic resistance is required to determine an appropriate antibiotic therapy. Current methods are solely based on cultivation and therefore only test a limited number of antibiotics.Our aim is to produce a detailed resistogram that will support the physicians to find a suitable treatment and render therapy more effective.For this purpose we are developing a fully automated Snakemake [2] workflow for reproducible genome analysis, called HyDRA - Hybrid De novo assembly for Resistance Analysis. This analysis is based on a combination of short and long reads generated by Illumina and Oxford Nanopore sequencing of bacterial isolates. These reads are used for a hybrid genome assembly, which then is screened for known antibiotic resistance genes (ARGs) using a well curated ARG specific database. In order to additionally identify newly acquired and hitherto unknown ARGs we are currently working on a machine learning classifier to reliably detect recently horizontally transferred genes.The best classifier so far was trained on E. coli K12 genome data from HGT-DB [3] and achieved credible results for different E. coli test data. However, this model does not work well for other tested organisms (see Fig.1). We are working on improving this classifier and creating more classifiers specialized on other bacteria. Furthermore, we are extending the workflow to metagenomics sequencing data to work directly with patient samples and skip the time-consuming cultivation.Conclusively, this workflow will rapidly provide the physicians detailed information to select an appropriate antibiotic treatment. This should prevent the unnecessary use of broad-spectrum antibiotics and thus help fight the emergence of antibiotic resistance.[1] ECDC &quot;Antimicrobial resistance in the EU/EEA (EARS-Net) - Annual epidemiological report for 2022&quot;, 2023[2] J. Koster and S. Rahmann, Bioinformatics, 2012, doi: 10.1093/bioinformatics/bts480[3] S. Garcia-Vallve et al., Nucleic Acids Res, 2003, doi: 10.1093/nar/gkg004

Oral Presentation

Professor

Prof. Dr. med.

Phylogenomics and genome-wide profiling to revisit mutational resistance to ampicillin and cefotaxime in Haemophilus influenzae

Background: Haemophilus influenzae, an opportunistic bacterial pathogen, can lead to severe respiratory tract infections, septicemia, and meningitis. The emergence of β-lactamase-negative ampicillin-resistant (BLNAR) strains and difficulties in correlating genotypic (gBLNAR) and phenotypic resistance complicate empirical treatment and patient management.Methods: We conducted a systematic meta-analysis of previously identified H. influenzae gBLNAR groups characterized by distinct substitution patterns in penicillin-binding protein 3 (PBP3), and analyzed their associations with ampicillin and cefotaxime resistance. In addition, we used phylogenomics and a genome-wide association study (GWAS) to identify novel mutations implicated in resistance in a public global cohort (n=555), and a new clinical cohort from three European centers (n=322), respectively.Results: Isolates characterized as gBLNAR groups II and III were associated with ampicillin resistance (p&lt;0.03), while only group III+/III-like+ isolates were associated with cefotaxime resistance (p&lt;0.03). However, group II isolates had low specificities (≤ 71%) to rule in resistance against ampicillin, challenging the currently endorsed clinical breakpoint for its ability to distinguish between gBLNAR and susceptible wildtype isolates. Known and newly identified PBP3 substitutions often occur step-wise and show patterns of positive selection, and convergent evolution in the two independent cohorts. Furthermore, we discovered new genes and novel combinations of PBP3 substitutions associated with ampicillin resistance.Conclusion: This study reveals new insights on molecular ampicillin resistance determinants in β-lactamase-negative H. influenzae isolates. We emphasize an artifact with the currently applied clinical breakpoints for ampicillin. Further investigations, including treatment outcome data, are crucial to understand the impact of bacterial genome variations on susceptibility to cefotaxime and other cephalosporins.

A molecular cluster of multidrug-resistant Mycobacterium tuberculosis strains among patients arriving in Germany from the Ukraine

IntroductionEmerging multidrug-resistant (MDR) and extensively drug-resistant (XDR) tuberculosis (TB) create significant challenges for TB control, particularly in Eastern European countries such as the Ukraine. International spread of highly resistant Mycobacterium tuberculosis complex (Mtbc) strains potentially impacts the MDR TB epidemiology in low incidence countries in Europe.Materials &amp; MethodSince 2020, WGS of Mtbc strains was carried out as part of the integrated molecular surveillance of TB (IMS-TB) by the Robert Koch Institute (RKI) and the National Reference Center (NRC) for Mycobacteria. Including retrospective data (years 1993 – 2019), whole genome sequencing (WGS) data of more than 11,000 Mtbc strains from Germany, containing more than 5,000 datasets from 2020 to 2023, are available at the NRC. Genome sequencing data were used for phylogenetic strain classifications, genomic resistance predictions based on the extended WHO catalogue (2021) and allele-based core genome cluster analysis using a threshold of 12 Alleles.ResultsAmong the dataset, 67 rifampicin resistant (RR) lineage 2 (Beijing) Mtbc strains were identified between 2000 and 2023 (analyses for 2023 ongoing) based on their particular mutation profile (e.g. embB Y334H mutation) that also show a close genomic relationship with a pairwise distance of 16. Since the beginning of the war in Ukraine, 13 isolates were detected in 2022 and 9 in 2023. Out of all isolates, 35 were RR/MDR, 28 pre-XDR (MDR plus fluoroquinolone resistance), and four XDR. Cluster analysis with a threshold of 5 alleles revealed substructures with 7 clusters ranging in size from 2 to 22 isolates. Similarity analysis linked all isolates to a previously described MDR strain detected in Ukraine. Of the 22 isolates from 2022 and 2023, 16 cases were born in Ukraine, while 6 were born in other countries outside of Germany.SummaryOur data suggest that the emergence of the described highly resistant MDR Mtbc isolates in Germany is linked to migration from Ukraine. Prospective surveillance is crucial to monitor potential long-term impacts on the MDR TB epidemiology in Germany.

Deciphering the secondary resistome of Methicillin-Resistant Staphylococcus aureus (MRSA) to Beta-lactams - a Multi-Omics Approach

Introduction: Antimicrobial resistance (AMR) is a significant global health issue, impacting both human and livestock populations. Methicillin-resistant Staphylococcus aureus (MRSA), a common multidrug-resistant bacterium, has been identified as a high-priority pathogen for the development of new antibiotics. The approach of restoring susceptibility to existing antimicrobials presents a promising strategy in the battle against AMR, as the full expression of resistance relies on auxiliary enzymes. Goal: This study aims to identify the auxiliary genes and proteins involved in the resistance of MRSA to oxacillin, which could potentially serve as targets for re-establishing susceptibility. Materials and Methods: Using Transposon-Directed Insertion site Sequencing (TraDIS), we screened a large MRSA transposon mutant library post-exposure to subinhibitory concentrations of oxacillin and cefazolin. The output reads were analyzed via the BioTradis pipeline. Subsequently, label-free quantitative proteomics was performed on the antibiotic-exposed cultures, the mass spectrometer data was processed using Proteome Discoverer, and a comprehensive statistical analysis was conducted with Perseus v1.6.Results: Our high-throughput transposon mutagenesis assay identified a set of conditionally essential genes potentially contributing to beta-lactam resistance. Subsequently, Post-antimicrobial exposure proteomics analysis highlighted significant alterations in protein expression, notably within the methionine and D-alanylation pathways of wall teichoic acid, which are linked to peptidoglycan integrity. Our findings underscore a limited overlap between TraDIS and proteomics results.Conclusion: Our investigation sheds light on the identification of auxiliary genes and proteins linked to beta-lactam resistance in MRSA. By merging large-scale transposon mutagenesis and proteomics, we provide valuable data about the secondary resistome and potential targets for tackling antimicrobial resistance. These insights set the stage for devising novel strategies to reinstate MRSA"s susceptibility to existing antimicrobials, addressing the pressing global health issue of AMR.

Dr. med.

Prof.Dr.

ST1299/vanA is the new kid on the block! Analysis of the explosive regional expansion of a new strain of vancomycin-resistant Enterococcus faecium

Introduction: Understanding dynamics and spreading patterns of novel vancomycin-resistant enterococci (VRE) strains could be the key to stopping their worldwide spread. The occurrence and explosive expansion of the novel strain ST1299 in Germany and Upper Austria gives us the opportunity to gain a more detailed insight.Methods: The surveillance at a tertiary care hospital in southern Germany includes identification by mass spectrometry and vanA/B-PCR, then whole-genome sequencing (WGS) of at least one VRE isolate per van-genotype, patient and year since 2004. Isolates were identified by database inquiry for &quot;ST1299&quot;, followed by selection of one isolate per patient and year. Further ST1299 isolate sources are 1) a further tertiary care hospital in Regensburg, 2) the National Reference Center for Enterococci, and 2.) outbreak isolates from Upper Austria.Results: From 2018 - 2022, 622 VRE isolates were assigned to ST1299 with 100% vanA-genotype (488 Regensburg County, 98 Germany other, 34 Upper Austria). In Regensburg most isolates were detected in rectal swabs (58.4%), urine (24.0%) or blood cultures (5.3%). The first four isolates were detected in 2018, but explosive expansion started April 2019 substantiated by an outbreak in a COVID-19 quarantine department. Thereafter spread was accelerated by several outbreaks throughout the hospital. ST1299 numbers culminated in January-March 2022 (overall 79 isolates), whereas the most common complex type (CT) was ST1299/CT1903 (67.3%). This strain also reached Upper Austria by December 2021, where it caused four hospital outbreaks with up to 25 patients. ST1299/CT3109, the second most common CT (24.0%), was only detected starting 2020, but had a similarly dynamic expansion and even surpassed ST1299/CT1903 in Regensburg during Q1/2022. Overall, only 54 isolates were assigned to other CTs. Currently, further data acquisition on strain dynamics and clinical outbreaks is still in progress.Conclusion: Since its first appearance in 2018, the strain ST1299 has proven highly transmissible, and has managed to expand throughout southeastern Germany and Upper Austria.

How to define an infection cluster? - cluster dynamics of S. Typhimurium in Germany.

Introduction: In Germany, salmonellosis is the second most frequently reported bacterial diarrheal disease and the zoonotic Salmonella cause many regional and multinational food-borne outbreaks. Among the reported Salmonella serovars in Germany, S. Typhimurium is the 2nd most common, responsible for 20-30% of cases each year and therefore has become one of the prioritized organisms for a comprehensive genome-based surveillance.Goals: In this study we analyzed S. Typhimurium infection clusters epidemiologically and technically, in order to asses different cluster types, cluster plausibility of an epidemiological link, cross-sectoral relevance, and best suitable thresholds for cluster definition.Methods: 2020-2023, the NRC for Salmonella received 14,252 unique clinical Salmonella isolates, of which 4,111 were S. Typhimurium (28.8% of all received isolates). Bioinformatic analysis of raw sequencing data and subsequent cgMLST (3.002 alleles) and cluster analysis were performed using Ridom SeqSphere+. Salmonella isolates of animal or food origin, matching clinical Salmonella clusters, were obtained from the NRL for Salmonella at the German Federal Institute for Risk Assessment.Results: From 2020-2023, a total of 3,320 S. Typhimurium isolates were analyzed, covering 61% of received isolates in 2020 up to 97.5% in 2023. 1,205 isolates were attributed into curated clusters, resulting in 81 clusters of variable size (4-97 isolates per cluster). Plausibility of an epidemiological link has been assessed for these clusters. Matching with isolates of non-human origin was possible in many cases. However, automatically assignment of clusters using variable threshold settings led to expanded and deviating clusters, highlighting the need for carefully selected and constantly reviewed cluster definitions.Summary: Intensified genome-based surveillance of S. Typhimurium led to an increase in cluster observations and cluster size. The number of clusters, their growth kinetics and regional distribution varied between different years of analysis and depended on the ratio of sequenced/received isolates and are strongly influenced by cluster definitions and detection methods.

Oral Session
Molecular Infection Epidemiology and Prediction of Antimicrobial Resistance

Appointment

Chair

Topic

Programme

Oral SessionMolecular Infection Epidemiology and Prediction of Antimicrobial Resistance

Appointment

Chair

Topic

Programme

Oral Session
Molecular Infection Epidemiology and Prediction of Antimicrobial Resistance