Mili Estee Torok

Background. Rates of multidrug resistance (MDR) in Gram-negative bacteria (GNB), particularly those harbouring extended-spectrum beta-lactamases (ESBL) and/or carbapenemases, are increasing globally. Intensive care unit (ICU) patients are vulnerable to healthcare-associated infection (HCAI). Surveillance for carriage of multidrug-resistant Gram-negative bacteria (MDR GNB) is inconsistent, with differing practices amongst ICUs, hospitals and countries. Furthermore, the impact of asymptomatic carriage on HCAI rates is unclear. Methods. We conducted a 6-month prospective surveillance study of MDR GNB in a UK adult ICU. Screening samples were collected from all study participants on admission, once a week (depending on length of stay) and on discharge from the ICU. Whole-genome sequencing (WGS) was used to examine the population structure and antimicrobial resistance mechanisms of MDR GNB and to determine evidence of recent transmission between patients. Findings. Of 424 participants recruited between June and December 2016, 15% ( n =64) were positive for MDR GNB during admission screening to the ICU. The most frequently identified organisms were Pseudomonas aeruginosa , Escherichia coli and Klebsiella pneumoniae . In total, 10% ( n =42) of patients acquired an ESBL-producing or carbapenem-resistant MDR GNB during their ICU admission. WGS of the bacterial populations reflected national trends. An undetected outbreak of carbapenemase-producing K. pneumoniae , which had spread to several wards, was identified and controlled. Most positive patients carried identical lineages across multiple body sites. Interpretation. Our findings suggest that prospective screening for MDR GNB in ICU patients could be beneficial and be considered in other UK critical care settings. This would not only improve early detection but also enable the prompt institution of enhanced infection control measures.

BACKGROUND: Ciprofloxacin resistant Klebsiella pneumoniae is common or emerging in many geographies, and knowledge of local resistance rates is important for empirical therapy. Whilst there are known K. pneumoniae ciprofloxacin resistance determinants, there is a lack of systematic data on the effect of determinants, alone and in combination, and there are no publicly accessible tools for predicting resistance from whole genome sequence data. METHODS: The KlebNET-GSP AMR Genotype-Phenotype Group aggregated a matched genotype-phenotype dataset of n=12,167 K. pneumoniae species complex ( Kp SC) isolates from 27 countries between 2001-2021. We developed a rules-based classifier to predict ciprofloxacin resistance by categorizing the number of quinolone resistance determining regions mutations in gyrA and parC , the number of plasmid-mediated quinolone resistance genes, and the presence/absence of aac(6ʹ)-Ib-cr (which can acetylate ciprofloxacin). Predictive performance was assessed using the discovery dataset, for which we re-phenotyped discrepant isolates; and validated using externally contributed datasets (n=7,030 Kp SC isolates). RESULTS: The rules-based classifier predicted R vs S/I with categorical agreement, sensitivity, and specificity >96%, and major/very major error rates Kp SC sources (human, animal, other), species, and intra-species lineages. External validation of the classifier yielded overall 93.12% categorical agreement [95% confidence interval (CI), 92.50-93.74%], 8.65% major errors [95% CI, 7.34-9.97%], and 6.20% very major errors [95% CI, 5.51-6.90%]. We implemented the classifier in Kleborate, a command-line tool that is integrated into the Pathogenwatch web platform. Using this to assess the global distribution of ciprofloxacin resistance determinants in Kp SC genomes available in Pathogenwatch (n=31,319, from 109 countries between years 2000-2023), we observed a significant positive association between national quinolone consumption rates and predicted ciprofloxacin resistance (R ² =0.20, p=0.004). CONCLUSIONS Ciprofloxacin resistance phenotypes can be reasonably predicted from genotypes, which is sufficient for informing surveillance. However, unexplained resistance remains and accuracy is insufficient for clinical applications. We demonstrate the value of aggregating genotype-phenotype data to explore resistance mechanisms and develop predictors, but highlight complexities in combining phenotype data from different assays and standards.

Interpreting the phenotypes of bla _SHV alleles in Klebsiella pneumoniae genomes is complex. Whilst all strains are expected to carry a chromosomal copy conferring resistance to ampicillin, they may also carry mutations in chromosomal bla _SHV alleles or additional plasmid-borne bla _SHV alleles that have extended-spectrum β-lactamase (ESBL) activity and/or β-lactamase inhibitor (BLI) resistance activity. In addition, the role of individual mutations/a changes is not completely documented or understood. This has led to confusion in the literature and in antimicrobial resistance (AMR) gene databases [e.g. the National Center for Biotechnology Information (NCBI) Reference Gene Catalog and the β-lactamase database (BLDB)] over the specific functionality of individual sulfhydryl variable (SHV) protein variants. Therefore, the identification of ESBL-producing strains from K. pneumoniae genome data is complicated. Here, we reviewed the experimental evidence for the expansion of SHV enzyme function associated with specific aa substitutions. We then systematically assigned SHV alleles to functional classes (WT, ESBL and BLI resistant) based on the presence of these mutations. This resulted in the re-classification of 37 SHV alleles compared with the current assignments in the NCBI’s Reference Gene Catalog and/or BLDB (21 to WT, 12 to ESBL and 4 to BLI resistant). Phylogenetic and comparative genomic analyses support that (i) SHV-1 (encoded by bla _SHV-1) is the ancestral chromosomal variant, (ii) ESBL- and BLI-resistant variants have evolved multiple times through parallel substitution mutations, (iii) ESBL variants are mostly mobilized to plasmids and (iv) BLI-resistant variants mostly result from mutations in chromosomal bla _SHV. We used matched genome–phenotype data from the KlebNET-GSP AMR Genotype-Phenotype Group to identify 3999 K. pneumoniae isolates carrying one or more bla _SHV alleles but no other acquired β-lactamases to assess genotype–phenotype relationships for bla _SHV. This collection includes human, animal and environmental isolates collected between 2001 and 2021 from 24 countries. Our analysis supports that mutations at Ambler sites 238 and 179 confer ESBL activity, whilst most omega-loop substitutions do not. Our data also provide support for the WT assignment of 67 protein variants, including 8 that were noted in public databases as ESBL. These eight variants were reclassified as WT because they lack ESBL-associated mutations, and our phenotype data support susceptibility to third-generation cephalosporins (SHV-27, SHV-38, SHV-40, SHV-41, SHV-42, SHV-65, SHV-164 and SHV-187). The approach and results outlined here have been implemented in Kleborate v2.4.1 (a software tool for genotyping K. pneumoniae), whereby known and novel bla _SHV alleles are classified based on causative mutations. Kleborate v2.4.1 was updated to include ten novel protein variants from the KlebNET-GSP dataset and all alleles in public databases as of November 2023. This study demonstrates the power of sharing AMR phenotypes alongside genome data to improve the understanding of resistance mechanisms.

The use of monoclonal antibodies for the control of drug resistant nosocomial bacteria may alleviate a reliance on broad spectrum antimicrobials for treatment of infection. We identify monoclonal antibodies that may prevent infection caused by carbapenem resistant Acinetobacter baumannii. We use human immune repertoire mice (Kymouse platform mice) as a surrogate for human B cell interrogation to establish an unbiased strategy to probe the antibody-accessible target landscape of clinically relevant A. baumannii. After immunisation of the Kymouse platform mice with A. baumannii derived outer membrane vesicles (OMV) we identify 297 antibodies and analyse 26 of these for functional potential. These antibodies target lipooligosaccharide (OCL1), the Oxa-23 protein, and the KL49 capsular polysaccharide. We identify a single monoclonal antibody (mAb1416) recognising KL49 capsular polysaccharide to demonstrate prophylactic in vivo protection against a carbapenem resistant A. baumannii lineage associated with neonatal sepsis mortality in Asia. Our end-to-end approach identifies functional monoclonal antibodies with prophylactic potential against major lineages of drug resistant bacteria accounting for phylogenetic diversity and clinical relevance without existing knowledge of a specific target antigen. Such an approach might be scaled for a additional clinically important bacterial pathogens in the post-antimicrobial era.

Interpreting phenotypes of bla _SHV alleles in Klebsiella pneumoniae genomes is complex. While all strains are expected to carry a chromosomal copy conferring resistance to ampicillin, they may also carry mutations in chromosomal bla _SHV alleles or additional plasmid-borne bla _SHV alleles that have extended-spectrum β-lactamase (ESBL) activity and/or β-lactamase inhibitor (BLI) resistance activity. In addition, the role of individual mutations/amino acid changes is not completely documented or understood. This has led to confusion in the literature and in antimicrobial resistance (AMR) gene databases (e.g., NCBI’s Reference Gene Catalog and the β-lactamase database (BLDB)) over the specific functionality of individual SHV protein variants. Therefore, identification of ESBL-producing strains from K. pneumoniae genome data is complicated. Here, we reviewed the experimental evidence for the expansion of SHV enzyme function associated with specific amino-acid substitutions. We then systematically assigned SHV alleles to functional classes (wildtype, ESBL, BLI-resistant) based on the presence of these mutations. This resulted in the re-classification of 37 SHV alleles compared with current assignments in NCBI’s Reference Gene Catalog and/or BLDB (21 to wildtype, 12 to ESBL, 4 to BLI-resistant). Phylogenetic and comparative genomic analyses support that; i) SHV-1 (encoded by bla _SHV-1 ) is the ancestral chromosomal variant; ii) ESBL and BLI-resistant variants have evolved multiple times through parallel substitution mutations; iii) ESBL variants are mostly mobilised to plasmids; iv) BLI-resistant variants mostly result from mutations in chromosomal bla _SHV . We used matched genome-phenotype data from the KlebNET-GSP Genotype-Phenotype Group to identify 3,999 K. pneumoniae isolates carrying one or more bla _SHV alleles but no other acquired β-lactamases, with which we assessed genotype-phenotype relationships for bla _SHV . This collection includes human, animal, and environmental isolates collected between 2001 to 2021 from 24 countries across six continents. Our analysis supports that mutations at Ambler sites 238 and 179 confer ESBL activity, while most omega-loop substitutions do not. Our data also provide direct support for wildtype assignment of 67 protein variants, including eight that were noted in public databases as ESBL. We reclassified these eight variants as wildtype, because they lack ESBL-associated mutations, and our phenotype data support susceptibility to 3GCs (SHV-27, SHV-38, SHV-40, SHV-41, SHV-42, SHV-65, SHV-164, SHV-187). The approach and results outlined here have been implemented in Kleborate v2.4.1 (a software tool for genotyping K. pneumoniae from genome assemblies), whereby known and novel bla _SHV alleles are classified based on causative mutations. Kleborate v2.4.1 was also updated to include ten novel protein variants from the KlebNET-GSP dataset and all alleles in public databases as of November 2023. This study demonstrates the power of sharing AMR phenotypes alongside genome data to improve understanding of resistance mechanisms. Impact statement: Since every K. pneumoniae genome has an intrinsic SHV β-lactamase and may also carry additional mobile forms, the correct interpretation of bla _SHV genes detected in genome data can be challenging and can lead to K. pneumoniae being misclassified as ESBL-producing. Here, we use matched K. pneumoniae genome and drug susceptibility data contributed from dozens of studies, together with systematic literature review of experimental evidence, to improve our understanding of bla _SHV allele variation and mapping of genotype to phenotype. This study shows the value of coordinated data sharing, in this case via the KlebNET-GSP Genotype-Phenotype Group, to improve our understanding of the evolutionary history and functionality of bla _SHV genes. The results are captured in an open-source AMR dictionary utilised by the Kleborate genotyping tool, that could easily be incorporated into or used to update other tools and AMR gene databases. This work is part of the wider efforts of the KlebNET-GSP group to develop and support a unified platform tailored for the analysis and interpretation of K. pneumoniae genomes by a wide range of stakeholders. Data summary: Bla _SHV allele sequences and class assignments are distributed with Kleborate, v2.4.1, DOI:10.5281/zenodo.10469001. Table S1 provides a summary of bla _SHV alleles, including primary accessions, class-modifying mutations, and supporting evidence for class assignments that differ from NCBI’s Reference Gene Catalog or BLDB. Whole genome sequence data are publicly available as reads and/or assemblies, individual accessions are given in Table S2 ; corresponding genotypes and antibiotic susceptibility phenotypes and measurements are available in Tables S3 and S4 , respectively.

Background: In the past decade, molecular diagnostic syndromic arrays incorporating a range of bacterial and viral pathogens have been described. It is unclear how paediatric intensive care unit (PICU) staff diagnose lower respiratory tract infection (LRTI) and integrate diagnostic array results into antimicrobial decision-making. Methods: An online survey with eleven questions was distributed throughout paediatric intensive care societies in the UK, continental Europe and Australasia with a total of 755 members. Participants were asked to rate the clinical factors and investigations they used when prescribing for LRTI. Semi-structured interviews were undertaken with staff who participated in a single-centre observational study of a 52-pathogen diagnostic array. Results: Seventy-two survey responses were received; most responses were from senior doctors. Whilst diagnostic arrays were used less frequently than routine investigations (i.e. microbiological culture), they were of comparable perceived utility when making antimicrobial decisions. Prescribers reported that for arrays to be clinically impactful, they would need to deliver results within 6 h for stable patients and within 1 h for unstable patients to inform their immediate decision to prescribe antimicrobials. From 16 staff interviews, we identified that arrays were helpful for the diagnosis and screening of bacterial LRTI. Staff reported it could be challenging to interpret results in some cases due to the high sensitivity of the test. Therefore, results were considered within the context of the patient and discussed within the multidisciplinary team. Conclusions: Diagnostic arrays were considered of comparable value to microbiological investigations by PICU prescribers. Our findings support the need for further clinical and economic evaluation of diagnostic arrays in a randomised control trial. Trial registration: Clinicaltrials.gov, NCT04233268. Registered on 18 January 2020.

Healthcare-associated infections (HCAIs) affect the most vulnerable people in society and are increasingly difficult to treat in the face of mounting antimicrobial resistance (AMR). Routine surveillance represents an effective way of understanding the circulation and burden of bacterial resistance and transmission in hospital settings. Here, we used whole-genome sequencing (WGS) to retrospectively analyse carbapenemase-producing Gram-negative bacteria from a single hospital in the UK over 6 years (n=165). We found that the vast majority of isolates were either hospital-onset (HAI) or HCAI. Most carbapenemase-producing organisms were carriage isolates, with 71 % isolated from screening (rectal) swabs. Using WGS, we identified 15 species, the most common being Escherichia coli and Klebsiella pneumoniae . Only one significant clonal outbreak occurred during the study period and involved a sequence type (ST)78 K . pneumoniae carrying bla _NDM-1 on an IncFIB/IncHI1B plasmid. Contextualization with public data revealed little evidence of this ST outside of the study hospital, warranting ongoing surveillance. Carbapenemase genes were found on plasmids in 86 % of isolates, the most common types being bla _NDM- and bla _OXA-type alleles. Using long-read sequencing, we determined that approximately 30 % of isolates with carbapenemase genes on plasmids had acquired them via horizontal transmission. Overall, a national framework to collate more contextual genomic data, particularly for plasmids and resistant bacteria in the community, is needed to better understand how carbapenemase genes are transmitted in the UK.

Purpose: Respiratory infections are the most common reason for admission to paediatric intensive care units (PICU). Most patients with lower respiratory tract infection (LRTI) receive broad-spectrum antimicrobials, despite low rates of bacterial culture confirmation. Here, we evaluated a molecular diagnostic test for LRTI to inform the better use of antimicrobials. Methods: The Rapid Assay for Sick Children with Acute Lung infection Study was a single-centre, prospective, observational cohort study of mechanically ventilated children (> 37/40 weeks corrected gestation to 18 years) with suspected community acquired or ventilator-associated LRTI. We evaluated the use of a 52-pathogen custom TaqMan Array Card (TAC) to identify pathogens in non-bronchoscopic bronchoalveolar lavage (mini-BAL) samples. TAC results were compared to routine microbiology testing. Primary study outcomes were sensitivity and specificity of TAC, and time to result. Results: We enrolled 100 patients, all of whom were tested with TAC and 91 of whom had matching culture samples. TAC had a sensitivity of 89.5% (95% confidence interval (CI₉₅) 66.9–98.7) and specificity of 97.9% (CI₉₅ 97.2–98.5) compared to routine bacterial and fungal culture. TAC took a median 25.8 h (IQR 9.1–29.8 h) from sample collection to result. Culture was significantly slower: median 110.4 h (IQR 85.2–141.6 h) for a positive result and median 69.4 h (IQR 52.8–78.6) for a negative result. Conclusions: TAC is a reliable and rapid adjunct diagnostic approach for LRTI in critically ill children, with the potential to aid early rationalisation of antimicrobial therapy.