Valeria Bortolaia

In 2023, an increase of OXA-48-producing Klebsiella pneumoniae was noticed by the Lithuanian National Public Health Surveillance Laboratory. Whole genome sequencing (WGS) of 106 OXA-48-producing K. pneumoniae isolates revealed three distinct clusters of carbapenemase-producing K. pneumoniae high-risk clones, including sequence type (ST) 45 (n = 35 isolates), ST392 (n = 32) and ST395 (n = 28), involving six, six and nine hospitals in different regions, respectively. These results enabled targeted investigation and control, and underscore the value of national WGS-based surveillance for antimicrobial resistance.

SUMMARY: Novel solutions are needed to reduce the risk of transmission of extended spectrum β-lactamase and AmpC β-lactamase producing Escherichia coli (ESBL/AmpC E. coli ) in livestock to humans. Since phages are promising biocontrol agents, we established a collection of 28 phages against ESBL/AmpC E. coli and showed by whole genome sequencing that all phages were unique and could be assigned to 15 different genera. Host range analysis showed that 82% of 198 strains, representing the genetic diversity of ESBL/AmpC E. coli , were sensitive to at least one phage. Identifying receptors used for initial binding experimentally as well as in silico predictions, allowed us to combine phages into two different cocktails with broad host range targeting diverse receptors. These phage cocktails inhibit growth and kill ESBL/AmpC E. coli in vitro , thus suggesting the potential of phages as promising biocontrol agents. HIGHLIGHTS: 28 unique phages infecting ESBL/AmpC E. coli were isolated and characterized Broad host range phages targeting different receptors were used to compose phage cocktails Phage cocktails efficiently inhibit growth of ESBL/AmpC E. coli in vitro

Antimicrobial susceptibility testing (AST) should be fast and accurate, leading to proper interventions and therapeutic success. Clinical microbiology laboratories rely on phenotypic methods, but the continuous improvement and decrease in the cost of whole-genome sequencing (WGS) technologies make them an attractive alternative. Studies evaluating the performance of WGS-based prediction of antimicrobial resistance (AMR) for selected bacterial species have shown promising results. There are, however, significant gaps in the literature evaluating the applicability of WGS as a diagnostics method in real-life clinical settings against the range of bacterial pathogens experienced there. Thus, we compared standard phenotypic AST results with WGS-based predictions of AMR profiles in bacterial isolates without preselection of defined species, to evaluate the applicability of WGS as a diagnostics method in clinical settings. We collected all bacterial isolates processed by all Danish Clinical Microbiology Laboratories in 1 day. We randomly selected 500 isolates without any preselection of species. We performed AST through standard broth microdilution (BMD) for 488 isolates (n = 6,487 phenotypic AST results) and compared results with in silico antibiograms obtained through WGS (Illumina NextSeq) followed by bioinformatics analyses using ResFinder 4.0 (n = 5,229 comparisons). A higher proportion of AMR was observed for Gram-negative bacteria (10.9%) than for Gram-positive bacteria (6.1%). Comparison of BMD with WGS data yielded a concordance of 91.7%, with discordant results mainly due to phenotypically susceptible isolates harboring genetic AMR determinants. These cases correspond to 6.2% of all isolate-antimicrobial combinations analyzed and to 6.8% of all phenotypically susceptible combinations. We detected fewer cases of phenotypically resistant isolates without any known genetic resistance mechanism, particularly 2.1% of all combinations analyzed, which corresponded to 26.4% of all detected phenotypic resistances. Most discordances were observed for specific combinations of species-antimicrobial: macrolides and tetracycline in streptococci, ciprofloxacin and β-lactams in combination with β-lactamase inhibitors in Enterobacterales, and most antimicrobials in Pseudomonas aeruginosa. WGS has the potential to be used for surveillance and routine clinical microbiology. However, in clinical microbiology settings and especially for certain species and antimicrobial agent combinations, further developments in AMR gene databases are needed to ensure higher concordance between in silico predictions and expected phenotypic AMR profiles.

Animals are considered important sources of ESBL/AmpC-producing bacteria in humans. We analyzed indications of transfer of ESBL/AmpC genes between pigs and pig farmers in Vietnam by analyzing whole genome sequences of 114 ESBL/AmpC-producing E. coli isolated from the two hosts, and performed conjugation experiments and plasmid profiling to confirm that such transfer could have happened. ESBL-encoding genes detected in pigs and pig farmers included bla_CTX–M-55, bla_CTX-M-27, bla_CTX-M-65, bla_CTX-M-15, bla_CTX-M-14, bla_CTX-M-3, bla_CTX-M-24, and bla_CARB-2, and AmpC β-lactamases included bla_CMY-2, bla_DHA-1, and bla_CMY-42. The most frequent ESBL gene, bla_CTX-M-55, was carried on plasmid with replicons types IncF, IncX, IncH, IncN, IncR, and IncP. The insertion transposases downstream of the bla_CTX-M-55 gene were different in plasmids carried by different strains. The second most detected gene, bla_CTX-M-27, is found in a stable genetic arrangement with the same flanking transposons seen across strains, and the gene was located on similar conjugal IncF plasmid types, suggesting a horizontal spread of these plasmids. In three strains, we observed a novel bla_CTX-M-27 harboring IncF type of plasmid which had not been reported before. Its closest reference in NCBI was the non-ESBL Salmonella Typhimurium plasmid pB71 that might have experienced an insertion of bla_CTX-M-27. Our data also point to an emergence of plasmids co-carrying ESBL genes, mcr genes, quinolones and other antimicrobials resistance determinants, and such plasmids require special attention. Plasmids phylogeny confirmed that the bla_CTX-M-55 encoding plasmids varied considerably, while those encoding bla_CTX-M-27 were closely related. Plasmids harboring both ESBL genes were confirmed to be conjugative and not to differ in transfer efficacy. The isolates carrying the plasmids, even those with plasmids of similar types, showed wide genetic variation with high number of SNPs, suggesting horizontal spread of plasmids into different clonal lines. Their virulence profiles did not confirm to known pathotypes, suggesting that unrelated commensals are a main reservoir for ESBL and AmpC β-lactamases in both humans and pigs. Overall, despite evidence of transferability of plasmids in the analyzed strains, our findings do not support that ESBL-producing E. coli from pigs or their ESBL/AmpC encoding plasmids are commonly spread to workers in close contact with the animals.

Bacteriophage-encoded endolysins degrading the bacterial peptidoglycan are promising antibacterials for combating antibiotic-resistant bacteria. However, endolysins have limited use against Gram-negative bacteria, since the outer membrane prevents access to the peptidoglycan. Here, we present Innolysins, an innovative concept for engineering endolysins to exert antibacterial activity against Gram-negative bacteria. Innolysins combine the enzymatic activity of endolysins with the binding capacity of phage receptor binding proteins (RBPs). As proof-of-concept, we constructed 12 Innolysins by fusing phage T5 endolysin and RBP Pb5 in different configurations. One of these, Innolysin Ec6 displayed antibacterial activity against Escherichia coli only in the presence of Pb5 receptor FhuA, leading to 1.22 ± 0.12 log reduction in cell counts. Accordingly, other bacterial species carrying FhuA homologs such as Shigella sonnei and Pseudomonas aeruginosa were sensitive to Innolysin Ec6. To enhance the antibacterial activity, we further constructed 228 novel Innolysins by fusing 23 endolysins with Pb5. High-throughput screening allowed to select Innolysin Ec21 as the best antibacterial candidate, leading to 2.20 ± 0.09 log reduction in E. coli counts. Interestingly, Innolysin Ec21 also displayed bactericidal activity against E. coli resistant to third-generation cephalosporins, reaching a 3.31 ± 0.53 log reduction in cell counts. Overall, the Innolysin approach expands previous endolysin-engineering strategies, allowing customization of endolysins by exploiting phage RBPs to specifically target Gram-negative bacteria.

One Health surveillance of antimicrobial resistance (AMR) depends on a harmonized method for detection of AMR. Metagenomics-based surveillance offers the possibility to compare resistomes within and between different target populations. Its potential to be embedded into policy in the future calls for a timely and integrated knowledge dissemination strategy. We developed a blended training (e-learning and a workshop) on the use of metagenomics in surveillance of pathogens and AMR. The objectives were to highlight the potential of metagenomics in the context of integrated surveillance, to demonstrate its applicability through hands-on training and to raise awareness to bias factors¹. The target participants included staff of competent authorities responsible for AMR monitoring and academic staff. The training was organized in modules covering the workflow, requirements, benefits and challenges of surveillance by metagenomics. The training had 41 participants. The face-to-face workshop was essential to understand the expectations of the participants about the transition to metagenomics-based surveillance. After revision of the e-learning, we released it as a Massive Open Online Course (MOOC), now available at https://www.coursera.org/learn/metagenomics. This course has run in more than 20 sessions, with more than 3,000 learners enrolled, from more than 120 countries. Blended learning and MOOCs are useful tools to deliver knowledge globally and across disciplines. The released MOOC can be a reference knowledge source for international players in the application of metagenomics in surveillance.

Machine learning is a proven method to predict AMR; however, the performance of any machine learning model depends on the quality of the input data. Therefore, we evaluated different methods of representing information about mutations as well as mobilizable genes, so that the information can serve as input for a robust model. We combined data from multiple bacterial species in order to develop species-independent machine learning models that can predict resistance profiles for multiple antimicrobials and species with high performance.

Corrigendum: Occurrence and Characterization of mcr-1-Positive Escherichia coli Isolated From Food-Producing Animals in Poland, 2011–2016