An ISO-certified genomics workflow for identification and surveillance of antimicrobial resistance

Prevalence of opportunistic pathogens and anti-microbial resistance in urban aquaculture ponds

Bacterial antimicrobial resistance (AMR) has emerged as a significant concern worldwide. The microbial community profile and potential AMR level in aquaculture ponds are often undervalued and attract less attention than other aquatic environments. We used amplicon and metagenomic shotgun sequencing to study microbial communities and AMR in six freshwater polyculture ponds in rural and urban areas of Bangladesh. Amplicon sequencing revealed different community structures between rural and urban ponds, with urban ponds having a higher bacterial diversity and opportunistic pathogens including Streptococcus, Staphylococcus, and Corynebacterium. Despite proteobacterial dominance, Firmicutes was the most interactive in the community network, especially in the urban ponds. Metagenomes showed that drug resistance was the most common type of AMR found, while metal resistance was only observed in urban ponds. AMR and metal resistance genes were found mainly in beta and gamma-proteobacteria in urban ponds, while AMR was found primarily in alpha-proteobacteria in rural ponds. We identified potential pathogens with a high profile of AMR and metal resistance in urban aquaculture ponds. As these ponds provide a significant source of protein for humans, our results raise significant concerns for the environmental sustainability of this food source and the dissemination of AMR into the food chain.

Genomic investigation and clinical correlates of the in vitro β-lactam: NaHCO3 responsiveness phenotype among methicillin-resistant Staphylococcus aureus isolates from a randomized clinical trial

NaHCO3 responsiveness is a novel phenotype where some methicillin-resistant Staphylococcus aureus (MRSA) isolates exhibit significantly lower minimal inhibitory concentrations (MIC) to oxacillin and/or cefazolin in the presence of NaHCO3. NaHCO3 responsiveness correlated with treatment response to β-lactams in an endocarditis animal model. We investigated whether treatment of NaHCO3-responsive strains with β-lactams was associated with faster clearance of bacteremia. The CAMERA2 trial (Combination Antibiotics for Methicillin-Resistant Staphylococcus aureus) randomly assigned participants with MRSA bloodstream infections to standard therapy, or to standard therapy plus an anti-staphylococcal β-lactam (combination therapy). For 117 CAMERA2 MRSA isolates, we determined by broth microdilution the MIC of cefazolin and oxacillin, with and without 44 mM of NaHCO3. Isolates exhibiting ≥4-fold decrease in the MIC to cefazolin or oxacillin in the presence of NaHCO3 were considered "NaHCO3-responsive" to that agent. We compared the rate of persistent bacteremia among participants who had infections caused by NaHCO3-responsive and non-responsive strains, and that were assigned to combination treatment with a β-lactam. Thirty-one percent (36/117) and 25% (21/85) of MRSA isolates were NaHCO3-responsive to cefazolin and oxacillin, respectively. The NaHCO3-responsive phenotype was significantly associated with sequence type 93, SCCmec type IVa, and mecA alleles with substitutions in positions -7 and -38 in the regulatory region. Among participants treated with a β-lactam, there was no association between the NaHCO3-responsive phenotype and persistent bacteremia (cefazolin, P = 0.82; oxacillin, P = 0.81). In patients from a randomized clinical trial with MRSA bloodstream infection, isolates with an in vitro β-lactam-NaHCO3-responsive phenotype were associated with distinctive genetic signatures, but not with a shorter duration of bacteremia among those treated with a β-lactam.

Progress in the Computer-Aided Analysis in Multiple Aspects of Nanocatalysis Research

Making the utmost of the differences and advantages of multiple disciplines, interdisciplinary integration breaks the science boundaries and accelerates the progress in mutual quests. As an organic connection of material science, enzymology, and biomedicine, nanozyme-related research is further supported by computer technology, which injects in new vitality, and contributes to in-depth understanding, unprecedented insights, and broadened application possibilities. Utilizing computer-aided first-principles method, high-speed and high-throughput mathematic, physic, and chemic models are introduced to perform atomic-level kinetic analysis for nanocatalytic reaction process, and theoretically illustrate the underlying nanozymetic mechanism and structure-function relationship. On this basis, nanozymes with desirable properties can be designed and demand-oriented synthesized without repeated trial-and-error experiments. Besides that, computational analysis and device also play an indispensable role in nanozyme-based detecting methods to realize automatic readouts with improved accuracy and reproducibility. Here, this work focuses on the crossing of nanocatalysis research and computational technology, to inspire the research in computer-aided analysis in nanozyme field to a greater extent.

Displacement of Hospital-Acquired, Methicillin-Resistant Staphylococcus aureus Clones by Heterogeneous Community Strains in Kenya over a 13-Year Period

We determined antibiotic susceptibility and employed Oxford Nanopore whole-genome sequencing to explore strain diversity, resistance, and virulence gene carriage among methicillin-resistant Staphylococcus aureus (MRSA) strains from different infection sites and timepoints in a tertiary Kenyan hospital. Ninety-six nonduplicate clinical isolates recovered between 2010 and 2023, identified and tested for antibiotic susceptibility on the VITEK ID/AST platform, were sequenced. Molecular typing, antibiotic resistance, and virulence determinant screening were performed using the relevant bioinformatics tools. The strains, alongside those from previous studies, were stratified into two periods covering 2010-2017 and 2018-2023 and comparisons were made. Mirroring phenotypic profiles, aac(6')-aph(2″) [aminoglycosides]; gyrA (S84L) and grlA (S80Y) [fluoroquinolones]; dfrG [anti-folates]; and tet(K) [tetracycline] resistance determinants dominated the collection. While the proportion of ST239/241-t037-SCCmec III among MRSA reduced from 37.7% to 0% over the investigated period, ST4803-t1476-SCCmec IV and ST152-t355-SCCmec IV were pre-eminent. The prevalence of Panton-Valentine leucocidin (PVL) and arginine catabolic mobile element (ACME) genes was 38% (33/87) and 6.8% (6/87), respectively. We observed the displacement of HA-MRSA ST239/241-t037-SCCmec III with the emergence of ST152-t355-SCCmec IV and a greater clonal heterogeneity. The occurrence of PVL+/ACME+ CA-MRSA in recent years warrants further investigations into their role in the CA-MRSA virulence landscape, in a setting of high PVL prevalence.

Keeping up with the pathogens: improved antimicrobial resistance detection and prediction from Pseudomonas aeruginosa genomes

BACKGROUND

Antimicrobial resistance (AMR) is an intensifying threat that requires urgent mitigation to avoid a post-antibiotic era. Pseudomonas aeruginosa represents one of the greatest AMR concerns due to increasing multi- and pan-drug resistance rates. Shotgun sequencing is gaining traction for in silico AMR profiling due to its unambiguity and transferability; however, accurate and comprehensive AMR prediction from P. aeruginosa genomes remains an unsolved problem.

METHODS

We first curated the most comprehensive database yet of known P. aeruginosa AMR variants. Next, we performed comparative genomics and microbial genome-wide association study analysis across a Global isolate Dataset (n = 1877) with paired antimicrobial phenotype and genomic data to identify novel AMR variants. Finally, the performance of our P. aeruginosa AMR database, implemented in our AMR detection and prediction tool, ARDaP, was compared with three previously published in silico AMR gene detection or phenotype prediction tools-abritAMR, AMRFinderPlus, ResFinder-across both the Global Dataset and an analysis-naïve Validation Dataset (n = 102).

RESULTS

Our AMR database comprises 3639 mobile AMR genes and 728 chromosomal variants, including 75 previously unreported chromosomal AMR variants, 10 variants associated with unusual antimicrobial susceptibility, and 281 chromosomal variants that we show are unlikely to confer AMR. Our pipeline achieved a genotype-phenotype balanced accuracy (bACC) of 85% and 81% across 10 clinically relevant antibiotics when tested against the Global and Validation Datasets, respectively, vs. just 56% and 54% with abritAMR, 58% and 54% with AMRFinderPlus, and 60% and 53% with ResFinder. ARDaP's superior performance was predominantly due to the inclusion of chromosomal AMR variants, which are generally not identified with most AMR identification tools.

CONCLUSIONS

Our ARDaP software and associated AMR variant database provides an accurate tool for predicting AMR phenotypes in P. aeruginosa, far surpassing the performance of current tools. Implementation of ARDaP for routine AMR prediction from P. aeruginosa genomes and metagenomes will improve AMR identification, addressing a critical facet in combatting this treatment-refractory pathogen. However, knowledge gaps remain in our understanding of the P. aeruginosa resistome, particularly the basis of colistin AMR.

The mobilome of Staphylococcus aureus from wild ungulates reveals epidemiological links at the animal-human interface

Staphylococcus aureus thrives at animal-human-environment interfaces. A large-scale work from our group indicated that antimicrobial resistance (AMR) in commensal S. aureus strains from wild ungulates is associated with agricultural land cover and livestock farming, raising the hypothesis that AMR genes in wildlife strains may originate from different hosts, namely via exchange of mobile genetic elements (MGE). In this work, we generate the largest available dataset of S. aureus draft genomes from wild ungulates in Portugal and explore their mobilome, which can determine important traits such as AMR, virulence, and host specificity, to understand MGE exchange. Core genome multi-locus sequence typing based on 98 newly generated draft genomes and 101 publicly available genomes from Portugal demonstrated that the genomic relatedness of S. aureus from wild ungulates assigned to livestock-associated sequence types (ST) is greater compared to wild ungulate isolates assigned to human-associated STs. Screening of host specificity determinants disclosed the unexpected presence in wildlife of the immune evasion cluster encoded in φSa3 prophage, described as a human-specific virulence determinant. Additionally, two plasmids, pAVX and pETB, previously associated with avian species and humans, respectively, and the Tn553 transposon were detected. Both pETB and Tn553 encode penicillin resistance through blaZ. Pangenome analysis of wild ungulate isolates shows a core genome fraction of 2133 genes, with isolates assigned to ST72 and ST3224 being distinguished from the remaining by MGEs, although there is no reported role of these in adaptation to wildlife. AMR related gene clusters found in the shell genome are directly linked to resistance against penicillin, macrolides, fosfomycin, and aminoglycosides, and they represent mobile ARGs. Altogether, our findings support epidemiological interactions of human and non-human hosts at interfaces, with MGE exchange, including AMR determinants, associated with putative indirect movements of S. aureus among human and wildlife hosts that might be bridged by livestock.

Antimicrobial Resistance Genes in Respiratory Bacteria from Weaned Dairy Heifers

Bovine respiratory disease (BRD) is the leading cause of mortality and antimicrobial drug (AMD) use in weaned dairy heifers. Limited information is available regarding antimicrobial resistance (AMR) in respiratory bacteria in this population. This study determined AMR gene presence in 326 respiratory isolates (Pasteurella multocida, Mannheimia haemolytica, and Histophilus somni) from weaned dairy heifers using whole genome sequencing. Concordance between AMR genotype and phenotype was determined. Twenty-six AMR genes for 8 broad classes of AMD were identified. The most prevalent, medically important AMD classes used in calf rearing, to which these genes predict AMR among study isolates were tetracycline (95%), aminoglycoside (94%), sulfonamide (94%), beta-lactam (77%), phenicol (50%), and macrolide (44%). The co-occurrence of AMR genes within an isolate was common; the largest cluster of gene co-occurrence encodes AMR to phenicol, macrolide, elfamycin, β-lactam (cephalosporin, penam cephamycin), aminoglycoside, tetracycline, and sulfonamide class AMD. Concordance between genotype and phenotype varied (Matthew's Correlation Coefficient ranged from -0.57 to 1) by bacterial species, gene, and AMD tested, and was particularly poor for fluoroquinolones (no AMR genes detected) and ceftiofur (no phenotypic AMR classified while AMR genes present). These findings suggest a high genetic potential for AMR in weaned dairy heifers; preventing BRD and decreasing AMD reliance may be important in this population.

Antimicrobial susceptibility prediction from genomes: a dream come true?

Genome-based diagnostics provides relevant information to guide patient treatment and support pathogen and resistance surveillance. Recently, Coll et al. introduced a curated database for predicting antimicrobial resistance (AMR) from Enterococcus faecium genomics data, offering excellent predictive values for susceptibility to important antimicrobials. Challenges to predict resistance to last-resort antimicrobials remain.

Whole genome sequence datasets of Salmonella enterica serovar Saintpaul ST50 and serovar Worthington ST592 strains isolated from raw milk in Brazil

Herein we report the draft genome sequences of Salmonella enterica subsp. enterica serovars Saintpaul ST50 and Worthington ST592 isolated from raw milk samples in Northeastern Brazil. The 4,696,281 bp S. Saintpaul ST50 genome contained 4,628 genes in 33 contigs, while S. Worthington ST592 genome was 4,890,415 bp in length, comprising 4,951 genes in 46 contigs. S. Worthington ST592 carried a conserved Col(pHAD28) plasmid which contains the antimicrobial resistance determinants tet(C), acc(6')-Iaa, and a nonsynonymous point mutation in ParC (p.T57S). The data could support further evolutionary and epidemiologic studies involving Salmonella organisms.

City-scale monitoring of antibiotic resistance genes by digital PCR and metagenomics

BACKGROUND

Anthropogenic activities significantly contribute to the dissemination of antibiotic resistance genes (ARGs), posing a substantial threat to humankind. The development of methods that allow robust ARG surveillance is a long-standing challenge. Here, we use city-scale monitoring of ARGs by using two of the most promising cutting-edge technologies, digital PCR (dPCR) and metagenomics.

METHODS

ARG hot-spots were sampled from the urban water and wastewater distribution systems. Metagenomics was used to provide a broad view of ARG relative abundance and richness in the prokaryotic and viral fractions. From the city-core ARGs in all samples, the worldwide dispersed sul2 and tetW conferring resistance to sulfonamide and tetracycline, respectively, were monitored by dPCR and metagenomics.

RESULTS

The largest relative overall ARG abundance and richness were detected in the hospital wastewater and the WWTP inlet (up to ≈6,000 ARGs/Gb metagenome) with a large fraction of unclassified resistant bacteria. The abundance of ARGs in DNA and RNA contigs classified as viruses was notably lower, demonstrating a reduction of up to three orders of magnitude compared to contigs associated to prokaryotes. By metagenomics and dPCR, a similar abundance tendency of sul2 and tetW was obtained, with higher abundances in hospital wastewater and WWTP input (≈125-225 ARGs/Gb metagenome). dPCR absolute abundances were between 6,000 and 18,600 copies per ng of sewage DNA (≈105-7 copies/mL) and 6.8 copies/mL in seawater near the WWTP discharging point.

CONCLUSIONS

dPCR was more sensitive and accurate, while metagenomics provided broader coverage of ARG detection. While desirable, a reliable correlation of dPCR absolute abundance units into metagenomic relative abundance units was not obtained here (r2 < 0.4) suggesting methodological factors that introduce variability. Evolutionary pressure does not significantly select the targeted ARGs in natural aquatic environments.

Whole Genome Sequencing: Applications in Clinical Bacteriology

The success in determining the whole genome sequence of a bacterial pathogen was first achieved in 1995 by determining the complete nucleotide sequence of Haemophilus influenzae Rd using the chain-termination method established by Sanger et al. in 1977 and automated by Hood et al. in 1987. However, this technology was laborious, costly, and time-consuming. Since 2004, high-throughput next-generation sequencing technologies have been developed, which are highly efficient, require less time, and are cost-effective for whole genome sequencing (WGS) of all organisms, including bacterial pathogens. In recent years, the data obtained using WGS technologies coupled with bioinformatics analyses of the sequenced genomes have been projected to revolutionize clinical bacteriology. WGS technologies have been used in the identification of bacterial species, strains, and genotypes from cultured organisms and directly from clinical specimens. WGS has also helped in determining resistance to antibiotics by the detection of antimicrobial resistance genes and point mutations. Furthermore, WGS data have helped in the epidemiological tracking and surveillance of pathogenic bacteria in healthcare settings as well as in communities. This review focuses on the applications of WGS in clinical bacteriology.

"Smart markets": harnessing the potential of new technologies for endemic and emerging infectious disease surveillance in traditional food markets

Emerging and endemic zoonotic diseases continue to threaten human and animal health, our social fabric, and the global economy. Zoonoses frequently emerge from congregate interfaces where multiple animal species and humans coexist, including farms and markets. Traditional food markets are widespread across the globe and create an interface where domestic and wild animals interact among themselves and with humans, increasing the risk of pathogen spillover. Despite decades of evidence linking markets to disease outbreaks across the world, there remains a striking lack of pathogen surveillance programs that can relay timely, cost-effective, and actionable information to decision-makers to protect human and animal health. However, the strategic incorporation of environmental surveillance systems in markets coupled with novel pathogen detection strategies can create an early warning system capable of alerting us to the risk of outbreaks before they happen. Here, we explore the concept of "smart" markets that utilize continuous surveillance systems to monitor the emergence of zoonotic pathogens with spillover potential.IMPORTANCEFast detection and rapid intervention are crucial to mitigate risks of pathogen emergence, spillover and spread-every second counts. However, comprehensive, active, longitudinal surveillance systems at high-risk interfaces that provide real-time data for action remain lacking. This paper proposes "smart market" systems harnessing cutting-edge tools and a range of sampling techniques, including wastewater and air collection, multiplex assays, and metagenomic sequencing. Coupled with robust response pathways, these systems could better enable Early Warning and bolster prevention efforts.

Review of antibiotic-resistant bacteria and antibiotic resistance genes within the one health framework

Background: The interdisciplinary One Health (OH) approach recognizes that human, animal, and environmental health are all interconnected. Its ultimate goal is to promote optimal health for all through the exploration of these relationships. Antibiotic resistance (AR) is a public health challenge that has been primarily addressed within the context of human health and clinical settings. However, it has become increasingly evident that antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs) that confer resistance are transmitted and circulated within humans, animals, and the environment. Therefore, to effectively address this issue, antibiotic resistance must also be considered an environmental and livestock/wildlife problem. Objective: This review was carried out to provide a broad overview of the existence of ARB and ARGs in One Health settings. Methods: Relevant studies that placed emphasis on ARB and ARGs were reviewed and key findings were accessed that illustrate the importance of One Health as a measure to tackle growing public and environmental threats. Results: In this review, we delve into the complex interplay of the three components of OH in relation to ARB and ARGs. Antibiotics used in animal husbandry and plants to promote growth, treat, and prevent infectious diseases lead to the development of antibiotic-resistant bacteria in animals. These bacteria are transmitted from animals to humans through food and environmental exposure. The environment plays a critical role in the circulation and persistence of antibiotic-resistant bacteria and genes, posing a significant threat to human and animal health. This article also highlights how ARGs are spread in the environment through the transfer of genetic material between bacteria. This transfer can occur naturally or through human activities such as the use of antibiotics in agriculture and waste management practices. Conclusion: It is important to integrate the One Health approach into the public health system to effectively tackle the emergence and spread of ARB and genes that code for resistance to different antibiotics.

Genomic surveillance for antimicrobial resistance - a One Health perspective

Antimicrobial resistance (AMR) - the ability of microorganisms to adapt and survive under diverse chemical selection pressures - is influenced by complex interactions between humans, companion and food-producing animals, wildlife, insects and the environment. To understand and manage the threat posed to health (human, animal, plant and environmental) and security (food and water security and biosecurity), a multifaceted 'One Health' approach to AMR surveillance is required. Genomic technologies have enabled monitoring of the mobilization, persistence and abundance of AMR genes and mutations within and between microbial populations. Their adoption has also allowed source-tracing of AMR pathogens and modelling of AMR evolution and transmission. Here, we highlight recent advances in genomic AMR surveillance and the relative strengths of different technologies for AMR surveillance and research. We showcase recent insights derived from One Health genomic surveillance and consider the challenges to broader adoption both in developed and in lower- and middle-income countries.

Hound: a novel tool for automated mapping of genotype to phenotype in bacterial genomes assembled de novo

Increasing evidence suggests that microbial species have a strong within species genetic heterogeneity. This can be problematic for the analysis of prokaryote genomes, which commonly relies on a reference genome to guide the assembly process. Differences between reference and sample genomes will therefore introduce errors in final assembly, jeopardizing the detection from structural variations to point mutations-critical for genomic surveillance of antibiotic resistance. Here we present Hound, a pipeline that integrates publicly available tools to assemble prokaryote genomes de novo, detect user-given genes by similarity to report mutations found in the coding sequence, promoter, as well as relative gene copy number within the assembly. Importantly, Hound can use the query sequence as a guide to merge contigs, and reconstruct genes that were fragmented by the assembler. To showcase Hound, we screened through 5032 bacterial whole-genome sequences isolated from farmed animals and human infections, using the amino acid sequence encoded by blaTEM-1, to detect and predict resistance to amoxicillin/clavulanate which is driven by over-expression of this gene. We believe this tool can facilitate the analysis of prokaryote species that currently lack a reference genome, and can be scaled either up to build automated systems for genomic surveillance or down to integrate into antibiotic susceptibility point-of-care diagnostics.

Genomic insights into ESBL-producing Escherichia coli isolated from non-human primates in the Peruvian Amazon

Introduction

Extended-spectrum beta-lactamase (ESBL)-producing Enterobacteriaceae are on the WHO priority pathogens list because they are associated with high mortality, health-care burden, and antimicrobial resistance (AMR), a serious problem that threatens global public health and should be addressed through the One Health approach. Non-human primates (NHP) have a high risk of acquiring these antibiotic-resistant bacteria due to their close phylogenetic relationship with humans and increased anthropogenic activities in their natural environments. This study aimed to detect and analyze the genomes of ESBL-producing Escherichia coli (ESBL-producing E. coli) in NHP from the Peruvian Amazon.

Materials and methods

We collected a total of 119 fecal samples from semi-captive Saguinus labiatus, Saguinus mystax, and Saimiri boliviensis, and captive Ateles chamek, Cebus unicolor, Lagothrix lagothricha, and Sapajus apella in the Loreto and Ucayali regions, respectively. Subsequently, we isolated and identified E. coli strains by microbiological methods, detected ESBL-producing E. coli through antimicrobial susceptibility tests following CLSI guidelines, and analyzed their genomes using previously described genomic methods.

Results

We detected that 7.07% (7/99) of E. coli strains: 5.45% (3/55) from Loreto and 9.09% (4/44) from Ucayali, expressed ESBL phenotype. Genomic analysis revealed the presence of high-risk pandemic clones, such as ST10 and ST117, carrying a broad resistome to relevant antibiotics, including three blaCTX-M variants: blaCTX-M-15, blaCTX-M-55, and blaCTX-M-65. Phylogenomic analysis confirmed the clonal relatedness of high-risk lineages circulating at the human-NHP interface. Additionally, two ESBL-producing E. coli strains were identified as EPEC (eae) and ExPEC according to their virulence profiles, and one more presented a hypermucoviscous phenotype.

Discussion

We report the detection and genomic analysis of seven ESBL-producing E. coli strains carrying broad resistome and virulence factors in NHP from two regions of the Peruvian Amazon. Some of these strains are closely related to high-risk pandemic lineages previously reported in humans and domestic animals, highlighting the negative impact of anthropogenic activities on Amazonian wildlife. To our knowledge, this is the first documentation of ESBL-producing E. coli in NHP from the Amazon, underscoring the importance of adopting the One Health approach to AMR surveillance and minimizing the potential transmission risk of antibiotic-resistant bacteria at the human-NHP interface.

Using whole genome sequencing to characterize Clostridioides difficile isolates at a tertiary center in Melbourne, Australia

Objective

Clostridioides difficile infection (CDI) is the commonest cause of healthcare-associated diarrhea and undergoes standardized surveillance and mandatory reporting in most Australian states and territories. Historically attributed to nosocomial spread, local and international whole genome sequencing (WGS) data suggest varied sources of acquisition. This study describes C. difficile genotypes isolated at a tertiary center in Melbourne, Australia, their likely source of acquisition, and common risk factors.

Design

Retrospective observational study.

Setting

The Royal Melbourne Hospital (RMH), a 570-bed tertiary center in Victoria, Australia.

Methods

Short-read whole genome sequencing was performed on 75 out of 137 C. difficile isolates obtained from 1/5/2021 to 28/2/2022 and compared to previous data from 8/11/2015 to 1/11/2016. Existing data from infection control surveillance and electronic medical records were used for epidemiological and risk factor analysis.

Results

Eighty-five (62.1%) of the 137 cases were defined as healthcare-associated from epidemiological data. On genome sequencing, 33 different multi-locus sequence type (MLST) subtypes were identified, with changes in population structure compared to the 2015-16 period. Risk factors for CDI were present in 130 (94.9%) cases, including 108 (78.8%) on antibiotics, 86 (62.8%) on acid suppression therapy, and 25 (18.2) on chemotherapy.

Conclusion

In both study periods, most C. difficile isolates were not closely related, suggesting varied sources of acquisition and that spread of C. difficile within the hospital was unlikely. Current infection control precautions may therefore warrant review. Underlying risk factors for CDI were common and may contribute to the proportion of healthcare-associated infections in the absence of proven hospital transmission.

Global emergence of a hypervirulent carbapenem-resistant Escherichia coli ST410 clone

Carbapenem-resistant Escherichia coli (CREC) ST410 has recently emerged as a major global health problem. Here, we report a shift in CREC prevalence in Chinese hospitals between 2017 and 2021 with ST410 becoming the most commonly isolated sequence type. Genomic analysis identifies a hypervirulent CREC ST410 clone, B5/H24RxC, which caused two separate outbreaks in a children's hospital. It may have emerged from the previously characterised B4/H24RxC in 2006 and has been isolated in ten other countries from 2015 to 2021. Compared with B4/H24RxC, B5/H24RxC lacks the blaOXA-181-bearing X3 plasmid, but carries a F-type plasmid containing blaNDM-5. Most of B5/H24RxC also carry a high pathogenicity island and a novel O-antigen gene cluster. We find that B5/H24RxC grew faster in vitro and is more virulent in vivo. The identification of this newly emerged but already globally disseminated hypervirulent CREC clone, highlights the ongoing evolution of ST410 towards increased resistance and virulence.

Omics for deciphering oral microecology

The human oral microbiome harbors one of the most diverse microbial communities in the human body, playing critical roles in oral and systemic health. Recent technological innovations are propelling the characterization and manipulation of oral microbiota. High-throughput sequencing enables comprehensive taxonomic and functional profiling of oral microbiomes. New long-read platforms improve genome assembly from complex samples. Single-cell genomics provides insights into uncultured taxa. Advanced imaging modalities including fluorescence, mass spectrometry, and Raman spectroscopy have enabled the visualization of the spatial organization and interactions of oral microbes with increasing resolution. Fluorescence techniques link phylogenetic identity with localization. Mass spectrometry imaging reveals metabolic niches and activities while Raman spectroscopy generates rapid biomolecular fingerprints for classification. Culturomics facilitates the isolation and cultivation of novel fastidious oral taxa using high-throughput approaches. Ongoing integration of these technologies holds the promise of transforming our understanding of oral microbiome assembly, gene expression, metabolites, microenvironments, virulence mechanisms, and microbe-host interfaces in the context of health and disease. However, significant knowledge gaps persist regarding community origins, developmental trajectories, homeostasis versus dysbiosis triggers, functional biomarkers, and strategies to deliberately reshape the oral microbiome for therapeutic benefit. The convergence of sequencing, imaging, cultureomics, synthetic systems, and biomimetic models will provide unprecedented insights into the oral microbiome and offer opportunities to predict, prevent, diagnose, and treat associated oral diseases.

Database resources of the National Center for Biotechnology Information

The National Center for Biotechnology Information (NCBI) provides online information resources for biology, including the GenBank® nucleic acid sequence database and the PubMed® database of citations and abstracts published in life science journals. NCBI provides search and retrieval operations for most of these data from 35 distinct databases. The E-utilities serve as the programming interface for most of these databases. Resources receiving significant updates in the past year include PubMed, PMC, Bookshelf, SciENcv, the NIH Comparative Genomics Resource (CGR), NCBI Virus, SRA, RefSeq, foreign contamination screening tools, Taxonomy, iCn3D, ClinVar, GTR, MedGen, dbSNP, ALFA, ClinicalTrials.gov, Pathogen Detection, antimicrobial resistance resources, and PubChem. These resources can be accessed through the NCBI home page at https://www.ncbi.nlm.nih.gov.

Genomic Analysis of a Community-Acquired Methicillin-Resistant Staphylococcus aureus Sequence Type 1 Associated with Caprine Mastitis

This study aimed to investigate the genomic and epidemiological features of a methicillin-resistant Staphylococcus aureus sequence type 1 (MRSA ST1) strain associated with caprine subclinical mastitis. An S. aureus strain was isolated from goat's milk with subclinical mastitis in Paraiba, Northeastern Brazil, by means of aseptic procedures and tested for antimicrobial susceptibility using the disk-diffusion method. Whole genome sequencing was performed using the Illumina MiSeq platform. After genome assembly and annotation, in silico analyses, including multilocus sequence typing (MLST), antimicrobial resistance and stress-response genes, virulence factors, and plasmids detection were performed. A comparative SNP-based phylogenetic analysis was performed using publicly available MRSA genomes. The strain showed phenotypic resistance to cefoxitin, penicillin, and tetracycline and was identified as sequence type 1 (ST1) and spa type 128 (t128). It harbored the SCCmec type IVa (2B), as well as the lukF-PV and lukS-PV genes. The strain was phylogenetically related to six community-acquired MRSA isolates (CA-MRSA) strains associated with human clinical disease in North America, Europe, and Australia. This is the first report of a CA-MRSA strain associated with milk in the Americas. The structural and epidemiologic features reported in the MRSA ST1 carrying a mecA-SCCmec type IVa suggest highly complex mechanisms of horizontal gene transfer in MRSA. The SNP-based phylogenetic analysis suggests a zooanthroponotic transmission, i.e., a strain of human origin.

Genomics for public health and international surveillance of antimicrobial resistance

Historically, epidemiological investigation and surveillance for bacterial antimicrobial resistance (AMR) has relied on low-resolution isolate-based phenotypic analyses undertaken at local and national reference laboratories. Genomic sequencing has the potential to provide a far more high-resolution picture of AMR evolution and transmission, and is already beginning to revolutionise how public health surveillance networks monitor and tackle bacterial AMR. However, the routine integration of genomics in surveillance pipelines still has considerable barriers to overcome. In 2022, a workshop series and online consultation brought together international experts in AMR and pathogen genomics to assess the status of genomic applications for AMR surveillance in a range of settings. Here we focus on discussions around the use of genomics for public health and international AMR surveillance, noting the potential advantages of, and barriers to, implementation, and proposing recommendations from the working group to help to drive the adoption of genomics in public health AMR surveillance. These recommendations include the need to build capacity for genome sequencing and analysis, harmonising and standardising surveillance systems, developing equitable data sharing and governance frameworks, and strengthening interactions and relationships among stakeholders at multiple levels.

Discordance between different bioinformatic methods for identifying resistance genes from short-read genomic data, with a focus on Escherichia coli

Several bioinformatics genotyping algorithms are now commonly used to characterize antimicrobial resistance (AMR) gene profiles in whole-genome sequencing (WGS) data, with a view to understanding AMR epidemiology and developing resistance prediction workflows using WGS in clinical settings. Accurately evaluating AMR in Enterobacterales, particularly Escherichia coli, is of major importance, because this is a common pathogen. However, robust comparisons of different genotyping approaches on relevant simulated and large real-life WGS datasets are lacking. Here, we used both simulated datasets and a large set of real E. coli WGS data (n=1818 isolates) to systematically investigate genotyping methods in greater detail. Simulated constructs and real sequences were processed using four different bioinformatic programs (ABRicate, ARIBA, KmerResistance and SRST2, run with the ResFinder database) and their outputs compared. For simulation tests where 3079 AMR gene variants were inserted into random sequence constructs, KmerResistance was correct for 3076 (99.9 %) simulations, ABRicate for 3054 (99.2 %), ARIBA for 2783 (90.4 %) and SRST2 for 2108 (68.5 %). For simulation tests where two closely related gene variants were inserted into random sequence constructs, KmerResistance identified the correct alleles in 35 338/46 318 (76.3 %) simulations, ABRicate identified them in 11 842/46 318 (25.6 %) simulations, ARIBA identified them in 1679/46 318 (3.6 %) simulations and SRST2 identified them in 2000/46 318 (4.3 %) simulations. In real data, across all methods, 1392/1818 (76 %) isolates had discrepant allele calls for at least 1 gene. In addition to highlighting areas for improvement in challenging scenarios, (e.g. identification of AMR genes at <10× coverage, identifying multiple closely related AMR genes present in the same sample), our evaluations identified some more systematic errors that could be readily soluble, such as repeated misclassification (i.e. naming) of genes as shorter variants of the same gene present within the reference resistance gene database. Such naming errors accounted for at least 2530/4321 (59 %) of the discrepancies seen in real data. Moreover, many of the remaining discrepancies were likely 'artefactual', with reporting of cut-off differences accounting for at least 1430/4321 (33 %) discrepants. Whilst we found that comparing outputs generated by running multiple algorithms on the same dataset could identify and resolve these algorithmic artefacts, the results of our evaluations emphasize the need for developing new and more robust genotyping algorithms to further improve accuracy and performance.

Whole genome sequencing in the palm of your hand: how to implement a MinION Galaxy-based workflow in a food safety laboratory for rapid Salmonella spp. serotyping, virulence, and antimicrobial resistance gene identification

Introduction

Whole Genome Sequencing (WGS) implementation in food safety laboratories is a significant advancement in food pathogen control and outbreak tracking. However, the initial investment for acquiring next-generation sequencing platforms and the need for bioinformatic skills represented an obstacle for the widespread use of WGS. Long-reading technologies, such as the one developed by Oxford Nanopore Technologies, can be easily implemented with a minor initial investment and with simple protocols that can be performed with basic laboratory equipment.

Methods

Herein, we report a simple MinION Galaxy-based workflow with analysis parameters that allow its implementation in food safety laboratories with limited computer resources and without previous knowledge in bioinformatics for rapid Salmonella serotyping, virulence, and identification of antimicrobial resistance genes. For that purpose, the single use Flongle flow cells, along with the MinION Mk1B for WGS, and the community-driven web-based analysis platform Galaxy for bioinformatic analysis was used. Three strains belonging to three different serotypes, monophasic S. Typhimurium, S. Grancanaria, and S. Senftenberg, were sequenced.

Results

After 24 h of sequencing, enough coverage was achieved in order to perform de novo assembly in all three strains. After evaluating different tools, Flye de novo assemblies with medaka polishing were shown to be optimal for in silico Salmonella spp. serotyping with SISRT tool followed by antimicrobial and virulence gene identification with ABRicate.

Discussion

The implementation of the present workflow in food safety laboratories with limited computer resources allows a rapid characterization of Salmonella spp. isolates.

Comparison of contemporary invasive and non-invasive Streptococcus pneumoniae isolates reveals new insights into circulating anti-microbial resistance determinants

Streptococcus pneumoniae is a major human pathogen with a high burden of disease. Non-invasive isolates (those found in non-sterile sites) are thought to be a key source of invasive isolates (those found in sterile sites) and a reservoir of anti-microbial resistance (AMR) determinants. Despite this, pneumococcal surveillance has almost exclusively focused on invasive isolates. We aimed to compare contemporaneous invasive and non-invasive isolate populations to understand how they interact and identify differences in AMR gene distribution. We used a combination of whole-genome sequencing and phenotypic anti-microbial susceptibility testing and a data set of invasive (n = 1,288) and non-invasive (n = 186) pneumococcal isolates, collected in Victoria, Australia, between 2018 and 2022. The non-invasive population had increased levels of antibiotic resistance to multiple classes of antibiotics including beta-lactam antibiotics penicillin and ceftriaxone. We identified genomic intersections between the invasive and non-invasive populations and no distinct phylogenetic clustering of the two populations. However, this analysis revealed sub-populations overrepresented in each population. The sub-populations that had high levels of AMR were overrepresented in the non-invasive population. We determined that WamR-Pneumo was the most accurate in silico tool for predicting resistance to the antibiotics tested. This tool was then used to assess the allelic diversity of the penicillin-binding protein genes, which acquire mutations leading to beta-lactam antibiotic resistance, and found that they were highly conserved (≥80% shared) between the two populations. These findings show the potential of non-invasive isolates to serve as reservoirs of AMR determinants.

Current Uses and Future Perspectives of Genomic Technologies in Clinical Microbiology

Recent advancements in sequencing technology and data analytics have led to a transformative era in pathogen detection and typing. These developments not only expedite the process, but also render it more cost-effective. Genomic analyses of infectious diseases are swiftly becoming the standard for pathogen analysis and control. Additionally, national surveillance systems can derive substantial benefits from genomic data, as they offer profound insights into pathogen epidemiology and the emergence of antimicrobial-resistant strains. Antimicrobial resistance (AMR) is a pressing global public health issue. While clinical laboratories have traditionally relied on culture-based antimicrobial susceptibility testing, the integration of genomic data into AMR analysis holds immense promise. Genomic-based AMR data can furnish swift, consistent, and highly accurate predictions of resistance phenotypes for specific strains or populations, all while contributing invaluable insights for surveillance. Moreover, genome sequencing assumes a pivotal role in the investigation of hospital outbreaks. It aids in the identification of infection sources, unveils genetic connections among isolates, and informs strategies for infection control. The One Health initiative, with its focus on the intricate interconnectedness of humans, animals, and the environment, seeks to develop comprehensive approaches for disease surveillance, control, and prevention. When integrated with epidemiological data from surveillance systems, genomic data can forecast the expansion of bacterial populations and species transmissions. Consequently, this provides profound insights into the evolution and genetic relationships of AMR in pathogens, hosts, and the environment.

Evaluation of metagenomic assembly methods for the detection and characterization of antimicrobial resistance determinants and associated mobilizable elements

Antimicrobial resistance genes (ARGs) can be transferred between members of a bacterial population by mobile genetic elements (MGE). Understanding the risk of these transfer events is important in monitoring and predicting antimicrobial resistance (AMR), especially in the context of a One Health Continuum. However, there is no universally accepted method for detection of ARGs and MGEs, and especially for determining their linkages. This study used publicly available shotgun metagenomic DNA short-read (Illumina, 100 bp paired-end) sequence data from samples across the One Health Continuum (including beef cattle composite feces from feedlots, catch basin water at feedlots, agricultural soil from feedlot manured surrounding fields, and urban/municipal sewage influent from two municipal wastewater treatment plants) to develop a workflow to identify and associate ARGs and MGEs. ARG- and MGE-based targeted-assemblies with available short-read data were unable to meet this analysis goal. In contrast, de novo assembly of contigs provided enough sequence context to associate ARGs and MGEs, without compromising discovery rate. However, to estimate the relative abundance of these elements, unassembled sequence data must still be used.

Rapid metagenomic sequencing for diagnosis and antimicrobial sensitivity prediction of canine bacterial infections

Antimicrobial resistance is a major threat to human and animal health. There is an urgent need to ensure that antimicrobials are used appropriately to limit the emergence and impact of resistance. In the human and veterinary healthcare setting, traditional culture and antimicrobial sensitivity testing typically requires 48-72 h to identify appropriate antibiotics for treatment. In the meantime, broad-spectrum antimicrobials are often used, which may be ineffective or impact non-target commensal bacteria. Here, we present a rapid, culture-free, diagnostics pipeline, involving metagenomic nanopore sequencing directly from clinical urine and skin samples of dogs. We have planned this pipeline to be versatile and easily implementable in a clinical setting, with the potential for future adaptation to different sample types and animals. Using our approach, we can identify the bacterial pathogen present within 5 h, in some cases detecting species which are difficult to culture. For urine samples, we can predict antibiotic sensitivity with up to 95 % accuracy. Skin swabs usually have lower bacterial abundance and higher host DNA, confounding antibiotic sensitivity prediction; an additional host depletion step will likely be required during the processing of these, and other types of samples with high levels of host cell contamination. In summary, our pipeline represents an important step towards the design of individually tailored veterinary treatment plans on the same day as presentation, facilitating the effective use of antibiotics and promoting better antimicrobial stewardship.

Population structure, serotype distribution and antibiotic resistance of Streptococcus pneumoniae causing invasive disease in Victoria, Australia

Streptococcus pneumoniae is a major human pathogen and can cause a range of conditions from asymptomatic colonization to invasive pneumococcal disease (IPD). The epidemiology and distribution of IPD-causing serotypes in Australia has undergone large changes following the introduction of the 7-valent pneumococcal conjugate vaccine (PCV) in 2005 and the 13-valent PCV in 2011. In this study, to provide a contemporary understanding of the IPD causing population in Victoria, Australia, we aimed to examine the population structure and prevalence of antimicrobial resistance using whole-genome sequencing and comprehensive antimicrobial susceptibility data of 1288 isolates collected between 2018 and 2022. We observed high diversity among the isolates with 52 serotypes, 203 sequence types (STs) and 70 Global Pneumococcal Sequencing Project Clusters (GPSCs) identified. Serotypes contained in the 13v-PCV represented 35.3 % (n=405) of isolates. Antimicrobial resistance (AMR) to at least one antibiotic was identified in 23.8 % (n=358) of isolates with penicillin resistance the most prevalent (20.3 %, n=261 using meningitis breakpoints and 5.1 % n=65 using oral breakpoints). Of the AMR isolates, 28 % (n=101) were multidrug resistant (MDR) (resistant to three or more drug classes). Vaccination status of cases was determined for a subset of isolates with 34 cases classified as vaccine failure events (fully vaccinated IPD cases of vaccine serotype). However, no phylogenetic association with failure events was observed. Within the highly diverse IPD population, we identified six high-risk sub-populations of public health concern characterized by high prevalence, high rates of AMR and MDR, or serotype inclusion in vaccines. High-risk serotypes included serotypes 3, 19F, 19A, 14, 11A, 15A and serofamily 23. In addition, we present our data validating seroBA for in silico serotyping to facilitate ISO-accreditation of this test in routine use in a public health reference laboratory and have made this data set available. This study provides insights into the population dynamics, highlights non-vaccine serotypes of concern that are highly resistant, and provides a genomic framework for the ongoing surveillance of IPD in Australia which can inform next-generation IPD prevention strategies.

Whole Genome Sequencing of Avian Pathogenic Escherichia coli Causing Bacterial Chondronecrosis and Osteomyelitis in Australian Poultry

Bacterial chondronecrosis with osteomyelitis (BCO) impacts animal welfare and productivity in the poultry industry worldwide, yet it has an understudied pathogenesis. While Avian Pathogenic Escherichia coli (APEC) are known to be one of the main causes, there is a lack of whole genome sequence data, with only a few BCO-associated APEC (APEC_BCO) genomes available in public databases. In this study, we conducted an analysis of 205 APEC_BCO genome sequences to generate new baseline phylogenomic knowledge regarding the diversity of E. coli sequence types and the presence of virulence associated genes (VAGs). Our findings revealed the following: (i) APEC_BCO are phylogenetically and genotypically similar to APEC that cause colibacillosis (APEC_colibac), with globally disseminated APEC sequence types ST117, ST57, ST69, and ST95 being predominate; (ii) APEC_BCO are frequent carriers of ColV-like plasmids that carry a similar set of VAGs as those found in APEC_colibac. Additionally, we performed genomic comparisons, including a genome-wide association study, with a complementary collection of geotemporally-matched genomes of APEC from multiple cases of colibacillosis (APEC_colibac). Our genome-wide association study found no evidence of novel virulence loci unique to APEC_BCO. Overall, our data indicate that APEC_BCO and APEC_colibac are not distinct subpopulations of APEC. Our publication of these genomes substantially increases the available collection of APEC_BCO genomes and provides insights for the management and treatment strategies of lameness in poultry.

Reduced selection for antibiotic resistance in community context is maintained despite pressure by additional antibiotics

Selection for antibiotic resistance at very low antibiotic concentrations has been demonstrated for individual antibiotics in single species experiments. Furthermore, selection in these focal strains is reduced when taking place in complex microbial community context. However, in the environment, bacteria are rarely exposed to single, but rather complex mixtures of selective agents. Here, we explored how the presence of a second selective agent affects selection dynamics between isogenic pairs of focal E. coli strains, differing exclusively in a single resistance determinant, in the absence and presence of a model wastewater community across a gradient of antibiotics. An additional antibiotic that exclusively affects the model wastewater community, but to which the focal strains are resistant to, was chosen as the second selective agent. This allowed exploring how inhibition alters the community's ability to reduce selection. In the presence of the community, the selection coefficient at specific antibiotic concentrations was consistently decreased compared to the absence of the community. While pressure through the second antibiotic significantly decreased the activity and diversity of the community, its ability to reduce selection was consistently maintained at levels comparable to those recorded in absence of the second antibiotic. This indicates that the observed effects of community context on selection dynamics are rather based on competitive or protective effects between the focal strains and a small proportion of bacteria within the community, than on general competition for nutrients. These findings have implications for our understanding of the evolution and selection for multi-drug resistant strains.

Salmonella Durban meningitis: case report and genomics study

BACKGROUND

Bacterial meningitis caused by non-typhoid Salmonella can be a fatal condition which is more common in low and middle-income countries.

CASE PRESENTATION

We report the case of a Salmonella meningitis in a Belgian six-month old male infant. The first clinical examination was reassuring, but after a few hours, his general state deteriorated. A blood test and a lumbar puncture were therefore performed. The cerebrospinal fluid analysis was compatible with a bacterial meningitis which was later identified by the NRC (National Reference Center) as Salmonella enterica serovar Durban.

CONCLUSIONS

In this paper, we present the clinical presentation, genomic typing, and probable sources of infection for an unusually rare serovar of Salmonella. Through an extended genomic analysis, we established its relationship to historical cases with links to Guinea.

Integrative omics identifies conserved and pathogen-specific responses of sepsis-causing bacteria

Even in the setting of optimal resuscitation in high-income countries severe sepsis and septic shock have a mortality of 20-40%, with antibiotic resistance dramatically increasing this mortality risk. To develop a reference dataset enabling the identification of common bacterial targets for therapeutic intervention, we applied a standardized genomic, transcriptomic, proteomic and metabolomic technological framework to multiple clinical isolates of four sepsis-causing pathogens: Escherichia coli, Klebsiella pneumoniae species complex, Staphylococcus aureus and Streptococcus pyogenes. Exposure to human serum generated a sepsis molecular signature containing global increases in fatty acid and lipid biosynthesis and metabolism, consistent with cell envelope remodelling and nutrient adaptation for osmoprotection. In addition, acquisition of cholesterol was identified across the bacterial species. This detailed reference dataset has been established as an open resource to support discovery and translational research.