ARGNet: using deep neural networks for robust identification and classification of antibiotic resistance genes from sequences.

BACKGROUND: Emergence of antibiotic resistance in bacteria is an important threat to global health. Antibiotic resistance genes (ARGs) are some of the key components to define bacterial resistance and their spread in different environments. Identification of ARGs, particularly from high-throughput sequencing data of the specimens, is the state-of-the-art method for comprehensively monitoring their spread and evolution. Current computational methods to identify ARGs mainly rely on alignment-based sequence similarities with known ARGs. Such approaches are limited by choice of reference databases and may potentially miss novel ARGs. The similarity thresholds are usually simple and could not accommodate variations across different gene families and regions. It is also difficult to scale up when sequence data are increasing. RESULTS: In this study, we developed ARGNet, a deep neural network that incorporates an unsupervised learning autoencoder model to identify ARGs and a multiclass classification convolutional neural network to classify ARGs that do not depend on sequence alignment. This approach enables a more efficient discovery of both known and novel ARGs. ARGNet accepts both amino acid and nucleotide sequences of variable lengths, from partial (30-50 aa; 100-150 nt) sequences to full-length protein or genes, allowing its application in both target sequencing and metagenomic sequencing. Our performance evaluation showed that ARGNet outperformed other deep learning models including DeepARG and HMD-ARG in most of the application scenarios especially quasi-negative test and the analysis of prediction consistency with phylogenetic tree. ARGNet has a reduced inference runtime by up to 57% relative to DeepARG. CONCLUSIONS: ARGNet is flexible, efficient, and accurate at predicting a broad range of ARGs from the sequencing data. ARGNet is freely available at https://github.com/id-bioinfo/ARGNet , with an online service provided at https://ARGNet.hku.hk . Video Abstract.

Whole-genome analysis of Escherichia coli isolated from wild Amur tiger (Panthera tigris altaica) and North China leopard (Panthera pardus japonensis).

Background: Escherichia coli is an important intestinal flora, of which pathogenic E. coli is capable of causing many enteric and extra-intestinal diseases. Antibiotics are essential for the treatment of bacterial infections caused by pathogenic E. coli; however, with the widespread use of antibiotics, drug resistance in E. coli has become particularly serious, posing a global threat to human, animal, and environmental health. While the drug resistance and pathogenicity of E. coli carried by tigers and leopards in captivity have been studied intensively in recent years, there is an extreme lack of information on E. coli in these top predators in the wild environment. Methods: Whole genome sequencing data of 32 E. coli strains collected from the feces of wild Amur tiger (Panthera tigris altaica, n = 24) and North China leopard (Panthera pardus japonensis, n = 8) were analyzed in this article. The multi-locus sequence types, serotypes, virulence and resistance genotypes, plasmid replicon types, and core genomic SNPs phylogeny of these isolates were studied. Additionally, antimicrobial susceptibility testing (AST) was performed on these E. coli isolates. Results: Among the E. coli isolates studied, 18 different sequence types were identified, with ST939 (21.9%), ST10 (15.6%), and ST3246 (9.4%) being the most prevalent. A total of 111 virulence genes were detected, averaging about 54 virulence genes per sample. They contribute to invasion, adherence, immune evasion, efflux pump, toxin, motility, stress adaption, and other virulence-related functions of E. coli. Sixty-eight AMR genes and point mutations were identified. Among the detected resistance genes, those belonging to the efflux pump family were the most abundant. Thirty-two E. coli isolates showed the highest rate of resistance to tetracycline (14/32; 43.8%), followed by imipenem (4/32; 12.5%), ciprofloxacin (3/32; 9.4%), doxycycline (2/32; 6.3%), and norfloxacin (1/32; 3.1%). Conclusions: Our results suggest that E. coli isolates carried by wild Amur tigers and North China leopards have potential pathogenicity and drug resistance.

Antimicrobial resistance and genetic relatedness of Salmonella serotypes isolated from food, asymptomatic carriers, and clinical cases in Shiyan, China.

Salmonella is a primary cause of foodborne diseases globally. Despite food contamination and clinical infections garnering substantial attention and research, asymptomatic Salmonella carriers, potential sources of infection, have been comparatively overlooked. In this study, we conducted a comparative analysis of serotype distribution, antimicrobial resistance phenotypes, and genetic profiles of archived Salmonella strains isolated from food (26), asymptomatic carriers (41), and clinical cases (47) in Shiyan City, China. Among the 114 Salmonella strains identified, representing 31 serotypes and 34 Sequence Types (STs), the most prevalent serovars included Typhimurium, Derby, Enteritidis, Thompson, and London, with the most predominant STs being ST11, ST40, ST26, ST34, and ST155. Antimicrobial resistance testing revealed that all strains were only sensitive to meropenem, with 74.6% showing antimicrobial resistance (AMR) and 53.5% demonstrating multidrug resistance (MDR). Strains resistant to five and six classes of antibiotics were the most common. Pearson's chi-square test showed no statistically significant difference in the occurrence of AMR (p = 0.105) or MDR (p = 0.326) among Salmonella isolates from the three sources. Our findings underscore associations and diversities among Salmonella strains isolated from food, asymptomatic carriers, and clinical patients, emphasizing the need for increased vigilance towards asymptomatic Salmonella carriers by authorities.

Co-localization of antibiotic resistance genes is widespread in the infant gut microbiome and associates with an immature gut microbial composition.

BACKGROUND: In environmental bacteria, the selective advantage of antibiotic resistance genes (ARGs) can be increased through co-localization with genes such as other ARGs, biocide resistance genes, metal resistance genes, and virulence genes (VGs). The gut microbiome of infants has been shown to contain numerous ARGs, however, co-localization related to ARGs is unknown during early life despite frequent exposures to biocides and metals from an early age. RESULTS: We conducted a comprehensive analysis of genetic co-localization of resistance genes in a cohort of 662 Danish children and examined the association between such co-localization and environmental factors as well as gut microbial maturation. Our study showed that co-localization of ARGs with other resistance and virulence genes is common in the early gut microbiome and is associated with gut bacteria that are indicative of low maturity. Statistical models showed that co-localization occurred mainly in the phylum Proteobacteria independent of high ARG content and contig length. We evaluated the stochasticity of co-localization occurrence using enrichment scores. The most common forms of co-localization involved tetracycline and fluoroquinolone resistance genes, and, on plasmids, co-localization predominantly occurred in the form of class 1 integrons. Antibiotic use caused a short-term increase in mobile ARGs, while non-mobile ARGs showed no significant change. Finally, we found that a high abundance of VGs was associated with low gut microbial maturity and that VGs showed even higher potential for mobility than ARGs. CONCLUSIONS: We found that the phenomenon of co-localization between ARGs and other resistance and VGs was prevalent in the gut at the beginning of life. It reveals the diversity that sustains antibiotic resistance and therefore indirectly emphasizes the need to apply caution in the use of antimicrobial agents in clinical practice, animal husbandry, and daily life to mitigate the escalation of resistance. Video Abstract.

Integrative and Conjugative Elements and Prophage DNA as Carriers of Resistance Genes in Erysipelothrix rhusiopathiae Strains from Domestic Geese in Poland.

Goose erysipelas is a serious problem in waterfowl breeding in Poland. However, knowledge of the characteristics of Erysipelothrix rhusiopathiae strains causing this disease is limited. In this study, the antimicrobial susceptibility and serotypes of four E. rhusiopathiae strains from domestic geese were determined, and their whole-genome sequences (WGSs) were analyzed to detect resistance genes, integrative and conjugative elements (ICEs), and prophage DNA. Sequence type and the presence of resistance genes and transposons were compared with 363 publicly available E. rhusiopathiae strains, as well as 13 strains of other Erysipelothrix species. Four strains tested represented serotypes 2 and 5 and the MLST groups ST 4, 32, 242, and 243. Their assembled circular genomes ranged from 1.8 to 1.9 kb with a GC content of 36-37%; a small plasmid was detected in strain 1023. Strains 1023 and 267 were multidrug-resistant. The resistance genes detected in the genome of strain 1023 were erm47, tetM, and lsaE-lnuB-ant(6)-Ia-spw cluster, while strain 267 contained the tetM and ermB genes. Mutations in the gyrA gene were detected in both strains. The tetM gene was embedded in a Tn916-like transposon, which in strain 1023, together with the other resistance genes, was located on a large integrative and conjugative-like element of 130 kb designated as ICEEr1023. A minor integrative element of 74 kb was identified in strain 1012 (ICEEr1012). This work contributes to knowledge about the characteristics of E. rhusiopathiae bacteria and, for the first time, reveals the occurrence of erm47 and ermB resistance genes in strains of this species. Phage infection appears to be responsible for the introduction of the ermB gene into the genome of strain 267, while ICEs most likely play a key role in the spread of the other resistance genes identified in E. rhusiopathiae.

Microbiome mapping in beef processing reveals safety-relevant variations in microbial diversity and genomic features.

The microbiome of surfaces along the beef processing chain represents a critical nexus where microbial ecosystems play a pivotal role in meat quality and safety of end products. This study offers a comprehensive analysis of the microbiome along beef processing using whole metagenomics with a particular focus on antimicrobial resistance and virulence-associated genes distribution. Our findings highlighted that microbial communities change dynamically in the different steps along beef processing chain, influenced by the specific conditions of each micro-environment. Brochothrix thermosphacta, Carnobacterium maltaromaticum, Pseudomonas fragi, Psychrobacter cryohalolentis and Psychrobacter immobilis were identified as the key species that characterize beef processing environments. Carcass samples and slaughterhouse surfaces exhibited a high abundance of antibiotic resistance genes (ARGs), mainly belonging to aminoglycosides, ß-lactams, amphenicols, sulfonamides and tetracyclines antibiotic classes, also localized on mobile elements, suggesting the possibility to be transmitted to human pathogens. We also evaluated how the initial microbial contamination of raw beef changes in response to storage conditions, showing different species prevailing according to the type of packaging employed. We identified several genes leading to the production of spoilage-associated compounds, and highlighted the different genomic potential selected by the storage conditions. Our results suggested that surfaces in beef processing environments represent a hotspot for beef contamination and evidenced that mapping the resident microbiome in these environments may help in reducing meat microbial contamination, increasing shelf-life, and finally contributing to food waste restraint.

Sporadic clone Escherichia coli ST615 as a vector and reservoir for dissemination of crucial antimicrobial resistance genes.

There is scarce information concerning the role of sporadic clones in the dissemination of antimicrobial resistance genes (ARGs) within the nosocomial niche. We confirmed that the clinical Escherichia coli M19736 ST615 strain, one of the first isolates of Latin America that harbors a plasmid with an mcr-1 gene, could receive crucial ARG by transformation and conjugation using as donors critical plasmids that harbor bla CTX-M-15, bla KPC-2, bla NDM-5, bla NDM-1, or aadB genes. Escherichia coli M19736 acquired bla CTX-M-15, bla KPC-2, bla NDM-5, bla NDM-1, and aadB genes, being only blaNDM-1 maintained at 100% on the 10th day of subculture. In addition, when the evolved MDR-E. coli M19736 acquired sequentially bla CTX-M-15 and bla NDM-1 genes, the maintenance pattern of the plasmids changed. In addition, when the evolved XDR-E. coli M19736 acquired in an ulterior step the paadB plasmid, a different pattern of the plasmid's maintenance was found. Interestingly, the evolved E. coli M19736 strains disseminated simultaneously the acquired conjugative plasmids in different combinations though selection was ceftazidime in all cases. Finally, we isolated and characterized the extracellular vesicles (EVs) from the native and evolved XDR-E. coli M19736 strains. Interestingly, EVs from the evolved XDR-E. coli M19736 harbored bla CTX-M-15 though the pDCAG1-CTX-M-15 was previously lost as shown by WGS and experiments, suggesting that EV could be a relevant reservoir of ARG for susceptible bacteria. These results evidenced the genetic plasticity of a sporadic clone of E. coli such as ST615 that could play a relevant transitional link in the clinical dynamics and evolution to multidrug/extensively/pandrug-resistant phenotypes of superbugs within the nosocomial niche by acting simultaneously as a vector and reservoir of multiple ARGs which later could be disseminated.

Identification of novel single nucleotide variants in the drug resistance mechanism of Mycobacterium tuberculosis isolates by whole-genome analysis.

BACKGROUND: Tuberculosis (TB) represents a major global health challenge. Drug resistance in Mycobacterium tuberculosis (MTB) poses a substantial obstacle to effective TB treatment. Identifying genomic mutations in MTB isolates holds promise for unraveling the underlying mechanisms of drug resistance in this bacterium. METHODS: In this study, we investigated the roles of single nucleotide variants (SNVs) in MTB isolates resistant to four antibiotics (moxifloxacin, ofloxacin, amikacin, and capreomycin) through whole-genome analysis. We identified the drug-resistance-associated SNVs by comparing the genomes of MTB isolates with reference genomes using the MuMmer4 tool. RESULTS: We observed a strikingly high proportion (94.2%) of MTB isolates resistant to ofloxacin, underscoring the current prevalence of drug resistance in MTB. An average of 3529 SNVs were detected in a single ofloxacin-resistant isolate, indicating a mutation rate of approximately 0.08% under the selective pressure of ofloxacin exposure. We identified a set of 60 SNVs associated with extensively drug-resistant tuberculosis (XDR-TB), among which 42 SNVs were non-synonymous mutations located in the coding regions of nine key genes (ctpI, desA3, mce1R, moeB1, ndhA, PE_PGRS4, PPE18, rpsA, secF). Protein structure modeling revealed that SNVs of three genes (PE_PGRS4, desA3, secF) are close to the critical catalytic active sites in the three-dimensional structure of the coding proteins. CONCLUSION: This comprehensive study elucidates novel resistance mechanisms in MTB against antibiotics, paving the way for future design and development of anti-tuberculosis drugs.

Genomic insights into the diversity, virulence, and antimicrobial resistance of group B Streptococcus clinical isolates from Saudi Arabia.

Introduction: Detailed assessment of the population structure of group B Streptococcus (GBS) among adults is still lacking in Saudi Arabia. Here we characterized a representative collection of isolates from colonized and infected adults. Methods: GBS isolates (n=89) were sequenced by Illumina and screened for virulence and antimicrobial resistance determinants. Genetic diversity was assessed by single nucleotide polymorphisms and core-genome MLST analyses. Results: Genome sequences revealed 28 sequence types (STs) and nine distinct serotypes, including uncommon serotypes VII and VIII. Majority of these STs (n=76) belonged to the human-associated clonal complexes (CCs) CC1 (33.71%), CC19 (25.84%), CC17 (11.24%), CC10/CC12 (7.87%), and CC452 (6.74%). Major CCs exhibited intra-lineage serotype diversity, except for the hypervirulent CC17, which exclusively expressed serotype III. Virulence profiling revealed that nearly all isolates (94.38%) carried at least one of the four alpha family protein genes (i.e., alphaC, alp1, alp2/3, and rib), and 92.13% expressed one of the two serine-rich repeat surface proteins Srr1 or Srr2. In addition, most isolates harbored the pilus island (PI)-2a alone (15.73%) or in combination with PI-1 (62.92%), and those carrying PI-2b alone (10.11%) belonged to CC17. Phylogenetic analysis grouped the sequenced isolates according to CCs and further subdivided them along with their serotypes. Overall, isolates across all CC1 phylogenetic clusters expressed Srr1 and carried the PI-1 and PI-2a loci, but differed in genes encoding the alpha-like proteins. CC19 clusters were dominated by the III/rib/srr1/PI-1+PI-2a (43.48%, 10/23) and V/alp1/srr1/PI-1+PI-2a (34.78%, 8/23) lineages, whereas most CC17 isolates (90%, 9/10) had the same III/rib/srr2/P1-2b genetic background. Interestingly, genes encoding the CC17-specific adhesins HvgA and Srr2 were detected in phylogenetically distant isolates belonging to ST1212, suggesting that other highly virulent strains might be circulating within the species. Resistance to macrolides and/or lincosamides across all major CCs (n=48) was associated with the acquisition of erm(B) (62.5%, 30/48), erm(A) (27.1%, 13/48), lsa(C) (8.3%, 4/48), and mef(A) (2.1%, 1/48) genes, whereas resistance to tetracycline was mainly mediated by presence of tet(M) (64.18%, 43/67) and tet(O) (20.9%, 14/67) alone or in combination (13.43%, 9/67). Discussion: These findings underscore the necessity for more rigorous characterization of GBS isolates causing infections.

Design and Validation of Primer Sets for the Detection and Quantification of Antibiotic Resistance Genes in Environmental Samples by Quantitative PCR.

The high prevalence of antibiotic resistant bacteria (ARB) in several environments is a great concern threatening human health. Particularly, wastewater treatment plants (WWTP) become important contributors to the dissemination of ARB to receiving water bodies, due to the inefficient management or treatment of highly antibiotic-concentrated wastewaters. Hence, it is vital to develop molecular tools that allow proper monitoring of the genes encoding resistances to these important therapeutic compounds (antibiotic resistant genes, ARGs). For an accurate quantification of ARGs, there is a need for sensitive and robust qPCR assays supported by a good design of primers and validated protocols. In this study, eleven relevant ARGs were selected as targets, including aadA and aadB (conferring resistance to aminoglycosides); ampC, blaTEM, blaSHV, and mecA (resistance to beta-lactams); dfrA1 (resistance to trimethoprim); ermB (resistance to macrolides); fosA (resistance to fosfomycin); qnrS (resistance to quinolones); and tetA(A) (resistance to tetracyclines). The in silico design of the new primer sets was performed based on the alignment of all the sequences of the target ARGs (orthology grade > 70%) deposited in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, allowing higher coverages of the ARGs' biodiversity than those of several primers described to date. The adequate design and performance of the new molecular tools were validated in six samples, retrieved from both natural and engineered environments related to wastewater treatment. The hallmarks of the optimized qPCR assays were high amplification efficiency (> 90%), good linearity of the standard curve (R2 > 0.980), repeatability and reproducibility across experiments, and a wide linear dynamic range. The new primer sets and methodology described here are valuable tools to upgrade the monitorization of the abundance and emergence of the targeted ARGs by qPCR in WWTPs and related environments.

Antimicrobial resistance and AmpC production in ESBL-producing Klebsiella pneumoniae and Klebsiella quasipneumoniae: A retrospective study in Japanese clinical isolates.

INTRODUCTION: The study of Klebsiella quasipneumoniae, Klebsiella variicola, and AmpC production in extended-spectrum ß-lactamase (ESBL)-producing Klebsiella in Japan is limited, and existing data are insufficient. This study aims to characterize Klebsiella species, determine AmpC production rates, and analyze antimicrobial resistance patterns in ESBL-producing Klebsiella isolates in Japan. METHODS: A total of 139 clinical isolates of ESBL-producing Klebsiella were collected in Japan, along with their corresponding antimicrobial susceptibility profiles. The isolates were identified using a web-based tool. ESBL genes within the isolates were identified using multiplex PCR. Screening for AmpC-producing isolates was performed using cefoxitin disks, followed by multiplex PCR to detect the presence of AmpC genes. Antimicrobial resistance patterns were analyzed across the predominant ESBL genotypes. RESULTS: The web-based tool identified 135 isolates (97.1%) as Klebsiella pneumoniae and 4 (2.9%) as K. quasipneumoniae subsp. similipneumoniae, with no instances of K. variicola detected. Among K. pneumoniae, the CTX-M-1 group emerged as the predominant genotype (83/135, 61.5%), followed by K. quasipneumoniae subsp. similipneumoniae (3/4, 75.0%). The CTX-M-9 group was the second most prevalent genotype in K. pneumoniae (45/135, 33.3%). The high resistance rates were observed for quinolones (ranging from 46.7% to 63.0%) and trimethoprim/sulfamethoxazole (78.5%). The CTX-M-1 group exhibited higher resistance to ciprofloxacin (66/83, 79.5%) compared to the CTX-M-9 group (18/45, 40.0%), a trend also observed for levofloxacin and trimethoprim/sulfamethoxazole. Among the 16 isolates that tested positive during AmpC screening, only one K. pneumoniae isolates (0.7%) were confirmed to carry the AmpC gene. CONCLUSION: Klebsiella pneumoniae with the CTX-M-1 group is the most common ESBL-producing Klebsiella in Japan and showed a low proportion of AmpC production. These isolates are resistant to quinolones and trimethoprim/sulfamethoxazole, highlighting the challenge of managing this pathogen. The findings underscore the importance of broader research and continuous monitoring to address the resistance patterns of ESBL-producing Klebsiella.

First detection and characterization of mcr-1 colistin resistant E. coli from wild rat in Bangladesh.

Colistin resistance is a global concern warning for a one health approach to combat the challenge. Colistin resistant E. coli and their resistance determinants are widely distributed in the environment, and rats could be a potential source of these isolates and resistant determinants to a diverse environmental setting. This study was aimed to determine the presence of colistin resistant E. coli (CREC) in wild rats, their antimicrobial resistance (AMR) phenotypes, and genotypic analysis of mcr-1 CREC through whole genome sequencing (WGS). A total of 39 rats were examined and CREC was isolated from their fecal pellets onto MacConkey agar containing colistin sulfate (1 µg/ mL). AMR of the CREC was determined by disc diffusion and broth microdilution was employed to determine MIC to colistin sulfate. CREC were screened for mcr genes (mcr-1 to mcr-8) and phylogenetic grouping by PCR. Finally, WGS of one mcr-1 CREC was performed to explore its genetic characteristics especially resistomes and virulence determinants. 43.59% of the rats carried CREC with one (2.56%) of them carrying CREC with mcr-1 gene among the mcr genes examined. Examination of seventeen (17) isolates from the CREC positive rats (n = 17) revealed that majority of them belonging to the pathogenic phylogroup D (52.94%) and B2 (11.76%). 58.82% of the CREC were MDR on disc diffusion test. Shockingly, the mcr-1 CREC showed phenotypic resistance to 16 antimicrobials of 8 different classes and carried the ARGs in its genome. The mcr-1 gene was located on a 60 kb IncI2 plasmid. On the other hand, ARGs related to aminoglycosides, phenicols, sulfonamides, tetracyclines and trimethoprims were located on a 288 kb mega-plasmid separately. The mcr-1 CREC carried 58 virulence genes including genes related to adhesion, colonization, biofilm formation, hemolysis and immune-evasion. The isolate belonged to ST224 and closely related to E. coli from different sources including UPEC clinical isolates from human based on cgMLST analysis. The current research indicates that rats might be a possible source of CREC, and the presence of mcr-1 and other ARGs on plasmid increases the risk of ARGs spreading and endangering human health and other environmental components through this infamous pest.

Rapid Direct Identification of Microbial Pathogens and Antimicrobial Resistance Genes in Positive Blood Cultures Using a Fully Automated Multiplex PCR Assay.

This study assessed the performance of the BioFire Blood Culture Identification 2 (BCID2) panel in identifying microorganisms and antimicrobial resistance (AMR) profiles in positive blood cultures (BCs) and its influence on turnaround time (TAT) compared with conventional culture methods. We obtained 117 positive BCs, of these, 102 (87.2%) were correctly identified using BCID2. The discordance was due to off-panel pathogens detected by culture (n = 13), and additional pathogens identified by BCID2 (n = 2). On-panel pathogen concordance between the conventional culture and BCID2 methods was 98.1% (102/104). The conventional method detected 19 carbapenemase-producing organisms, 14 extended-spectrum beta-lactamase-producing Enterobacterales, 18 methicillin-resistant Staphylococcus spp., and four vancomycin-resistant Enterococcus faecium. BCID2 correctly predicted 53 (96.4%) of 55 phenotypic resistance patterns by detecting AMR genes. The TAT for BCID2 was significantly lower than that for the conventional method. BCID2 rapidly identifies pathogens and AMR genes in positive BCs.

Defining the phylogenetics and resistome of the major Clostridioides difficile ribotypes circulating in Australia.

Clostridioides difficile infection (CDI) remains a significant public health threat globally. New interventions to treat CDI rely on an understanding of the evolution and epidemiology of circulating strains. Here we provide longitudinal genomic data on strain diversity, transmission dynamics and antimicrobial resistance (AMR) of C. difficile ribotypes (RTs) 014/020 (n=169), 002 (n=77) and 056 (n=36), the three most prominent C. difficile strains causing CDI in Australia. Genome scrutiny showed that AMR was uncommon in these lineages, with resistance-conferring alleles present in only 15/169 RT014/020 strains (8.9 %), 1/36 RT056 strains (2.78 %) and none of 77 RT002 strains. Notably, ~90 % of strains were resistant to MLSB agents in vitro, but only ~5.9 % harboured known resistance alleles, highlighting an incongruence between AMR genotype and phenotype. Core genome analyses revealed all three RTs contained genetically heterogeneous strain populations with limited evidence of clonal transmission between CDI cases. The average number of pairwise core genome SNP (cgSNP) differences within each RT group ranged from 23.3 (RT056, ST34, n=36) to 115.6 (RT002, ST8, n=77) and 315.9 (RT014/020, STs 2, 13, 14, 49, n=169). Just 19 clonal groups (encompassing 40 isolates), defined as isolates differing by ≤2 cgSNPs, were identified across all three RTs (RT014/020, n=14; RT002, n=3; RT056, n=2). Of these clonal groups, 63 % (12/19) comprised isolates from the same Australian State and 37 % (7/19) comprised isolates from different States. The low number of plausible transmission events found for these major RTs (and previously documented populations in animal and environmental sources/reservoirs) points to widespread and persistent community sources of diverse C. difficile strains as opposed to ongoing nationwide healthcare outbreaks dominated by a single clone. Together, these data provide new insights into the evolution of major lineages causing CDI in Australia and highlight the urgent need for enhanced surveillance, and for public health interventions to move beyond the healthcare setting and into a One Health paradigm to effectively combat this complex pathogen.

Blue light-mediated gene expression as a promising strategy to reduce antibiotic resistance in Escherichia coli.

The discovery of antibiotics has noticeably promoted the development of human civilization; however, antibiotic resistance in bacteria caused by abusing and overusing greatly challenges human health and food safety. Considering the worsening situation, it is an urgent demand to develop emerging nontraditional technologies or methods to address this issue. With the expanding of synthetic biology, optogenetics exhibits a tempting prospect for precisely regulating gene expression in many fields. Consequently, it is attractive to employ optogenetics to reduce the risk of antibiotic resistance. Here, a blue light-controllable gene expression system was established in Escherichia coli based on a photosensitive DNA-binding protein (EL222). Further, this strategy was successfully applied to repress the expression of ß-lactamase gene (bla) using blue light illumination, resulting a dramatic reduction of ampicillin resistance in engineered E. coli. Moreover, blue light was utilized to induce the expression of the mechanosensitive channel of large conductance (MscL), triumphantly leading to the increase of streptomycin susceptibility in engineered E. coli. Finally, the increased susceptibility of ampicillin and streptomycin was simultaneously induced by blue light in the same E. coli cell, revealing the excellent potential of this strategy in controlling multidrug-resistant (MDR) bacteria. As a proof of concept, our work demonstrates that light can be used as an alternative tool to prolong the use period of common antibiotics without developing new antibiotics. And this novel strategy based on optogenetics shows a promising foreground to combat antibiotic resistance in the future.

Genetic variations of penicillin-binding protein 1A: insights into the current status of amoxicillin-based regimens for Helicobacter pylori eradication in Malaysia.

Introduction. Resistance towards amoxicillin in Helicobacter pylori causes significant therapeutic impasse in healthcare settings worldwide. In Malaysia, the standard H. pylori treatment regimen includes a 14-day course of high-dose proton-pump inhibitor (rabeprazole, 20 mg) with amoxicillin (1000 mg) dual therapy.Hypothesis/Gap Statement. The high eradication rate with amoxicillin-based treatment could be attributed to the primary resistance rates of amoxicillin being relatively low at 0%, however, a low rate of secondary resistance has been documented in Malaysia recently.Aim. This study aims to investigate the amino acid mutations and related genetic variants in PBP1A of H. pylori, correlating with amoxicillin resistance in the Malaysian population.Methodology. The full-length pbp1A gene was amplified via PCR from 50 genomic DNA extracted from gastric biopsy samples of H. pylori-positive treatment-naïve Malaysian patients. The sequences were then compared with reference H. pylori strain ATCC 26695 for mutation and variant detection. A phylogenetic analysis of 50 sequences along with 43 additional sequences from the NCBI database was performed. These additional sequences included both amoxicillin-resistant strains (n=20) and amoxicillin-sensitive strains (n=23).Results. There was a total of 21 variants of amino acids, with three of them located in or near the PBP-motif (SKN402-404). The percentages of these three variants are as follows: K403X, 2%; S405I, 2% and E406K, 16%. Based on the genetic markers identified, the resistance rate for amoxicillin in our sample remained at 0%. The phylogenetic examination suggested that H. pylori might exhibit unique conserved pbp1A sequences within the Malaysian context.Conclusions. Overall, the molecular analysis of PBP1A supported the therapeutic superiority of amoxicillin-based regimens. Therefore, it is crucial to continue monitoring the amoxicillin resistance background of H. pylori with a larger sample size to ensure the sustained effectiveness of amoxicillin-based treatments in Malaysia.

Dental plaque microbiota sequence counts for microbial profiling and resistance genes detection.

Shotgun metagenomics sequencing experiments are finding a wide range of applications. Nonetheless, there are still limited guidelines regarding the number of sequences needed to acquire meaningful information for taxonomic profiling and antimicrobial resistance gene (ARG) identification. In this study, we explored this issue in the context of oral microbiota by sequencing with a very high number of sequences (~ 100 million), four human plaque samples, and one microbial community standard and by evaluating the performance of microbial identification and ARGs detection through a downsampling procedure. When investigating the impact of a decreasing number of sequences on quantitative taxonomic profiling in the microbial community standard datasets, we found some discrepancies in the identified microbial species and their abundances when compared to the expected ones. Such differences were consistent throughout downsampling, suggesting their link to taxonomic profiling methods limitations. Overall, results showed that the number of sequences has a great impact on metagenomic samples at the qualitative (i.e., presence/absence) level in terms of loss of information, especially in experiments having less than 40 million reads, whereas abundance estimation was minimally affected, with only slight variations observed in low-abundance species. The presence of ARGs was also assessed: a total of 133 ARGs were identified. Notably, 23% of them inconsistently resulted as present or absent across downsampling datasets of the same sample. Moreover, over half of ARGs were lost in datasets having less than 20 million reads. This study highlights the importance of carefully considering sequencing aspects and suggests some guidelines for designing shotgun metagenomics experiments with the final goal of maximizing oral microbiome analyses. Our findings suggest varying optimized sequence numbers according to different study aims: 40 million for microbiota profiling, 50 million for low-abundance species detection, and 20 million for ARG identification. KEY POINTS: • Forty million sequences are a cost-efficient solution for microbiota profiling • Fifty million sequences allow low-abundance species detection • Twenty million sequences are recommended for ARG identification.

Omics technology draws a comprehensive heavy metal resistance strategy in bacteria.

The rapid industrial revolution significantly increased heavy metal pollution, becoming a major global environmental concern. This pollution is considered as one of the most harmful and toxic threats to all environmental components (air, soil, water, animals, and plants until reaching to human). Therefore, scientists try to find a promising and eco-friendly technique to solve this problem i.e., bacterial bioremediation. Various heavy metal resistance mechanisms were reported. Omics technologies can significantly improve our understanding of heavy metal resistant bacteria and their communities. They are a potent tool for investigating the adaptation processes of microbes in severe conditions. These omics methods provide unique benefits for investigating metabolic alterations, microbial diversity, and mechanisms of resistance of individual strains or communities to harsh conditions. Starting with genome sequencing which provides us with complete and comprehensive insight into the resistance mechanism of heavy metal resistant bacteria. Moreover, genome sequencing facilitates the opportunities to identify specific metal resistance genes, operons, and regulatory elements in the genomes of individual bacteria, understand the genetic mechanisms and variations responsible for heavy metal resistance within and between bacterial species in addition to the transcriptome, proteome that obtain the real expressed genes. Moreover, at the community level, metagenome, meta transcriptome and meta proteome participate in understanding the microbial interactive network potentially novel metabolic pathways, enzymes and gene species can all be found using these methods. This review presents the state of the art and anticipated developments in the use of omics technologies in the investigation of microbes used for heavy metal bioremediation.

Assessing computational predictions of antimicrobial resistance phenotypes from microbial genomes.

The advent of rapid whole-genome sequencing has created new opportunities for computational prediction of antimicrobial resistance (AMR) phenotypes from genomic data. Both rule-based and machine learning (ML) approaches have been explored for this task, but systematic benchmarking is still needed. Here, we evaluated four state-of-the-art ML methods (Kover, PhenotypeSeeker, Seq2Geno2Pheno and Aytan-Aktug), an ML baseline and the rule-based ResFinder by training and testing each of them across 78 species-antibiotic datasets, using a rigorous benchmarking workflow that integrates three evaluation approaches, each paired with three distinct sample splitting methods. Our analysis revealed considerable variation in the performance across techniques and datasets. Whereas ML methods generally excelled for closely related strains, ResFinder excelled for handling divergent genomes. Overall, Kover most frequently ranked top among the ML approaches, followed by PhenotypeSeeker and Seq2Geno2Pheno. AMR phenotypes for antibiotic classes such as macrolides and sulfonamides were predicted with the highest accuracies. The quality of predictions varied substantially across species-antibiotic combinations, particularly for beta-lactams; across species, resistance phenotyping of the beta-lactams compound, aztreonam, amoxicillin/clavulanic acid, cefoxitin, ceftazidime and piperacillin/tazobactam, alongside tetracyclines demonstrated more variable performance than the other benchmarked antibiotics. By organism, Campylobacter jejuni and Enterococcus faecium phenotypes were more robustly predicted than those of Escherichia coli, Staphylococcus aureus, Salmonella enterica, Neisseria gonorrhoeae, Klebsiella pneumoniae, Pseudomonas aeruginosa, Acinetobacter baumannii, Streptococcus pneumoniae and Mycobacterium tuberculosis. In addition, our study provides software recommendations for each species-antibiotic combination. It furthermore highlights the need for optimization for robust clinical applications, particularly for strains that diverge substantially from those used for training.

Prevalence and molecular characterization of colistin resistance in Pseudomonas aeruginosa isolates: insights from a study in Ardabil hospitals.

BACKGROUND: Pseudomonas aeruginosa is a common cause of nosocomial infections. However, the emergence of multidrug-resistant strains has complicated the treatment of P. aeruginosa infections. While polymyxins have been the mainstay for treatment, there is a global increase in resistance to these antibiotics. Therefore, our study aimed to determine the prevalence and molecular details of colistin resistance in P. aeruginosa clinical isolates collected between June 2019 and May 2023, as well as the genetic linkage of colistin-resistant P. aeruginosa isolates. RESULTS: The resistance rate to colistin was 9% (n = 18) among P. aeruginosa isolates. All 18 colistin-resistant isolates were biofilm producers and carried genes associated with biofilm formation. Furthermore, the presence of genes encoding efflux pumps, TCSs, and outer membrane porin was observed in all colistin-resistant P. aeruginosa strains, while the mcr-1 gene was not detected. Amino acid substitutions were identified only in the PmrB protein of multidrug- and colistin-resistant strains. The expression levels of mexA, mexC, mexE, mexY, phoP, and pmrA genes in the 18 colistin-resistant P. aeruginosa strains were as follows: 88.8%, 94.4%, 11.1%, 83.3%, 83.3%, and 38.8%, respectively. Additionally, down-regulation of the oprD gene was observed in 44.4% of colistin-resistant P. aeruginosa strains. CONCLUSION: This study reports the emergence of colistin resistance with various mechanisms among P. aeruginosa strains in Ardabil hospitals. We recommend avoiding unnecessary use of colistin to prevent potential future increases in colistin resistance.