Unraveling the adaptive strategies of Mycoplasma hominis through proteogenomic profiling of clinical isolates.

Introduction: Mycoplasma hominis (M. hominis) belongs to the class Mollicutes, characterized by a very small genome size, reduction of metabolic pathways, including transcription factors, and the absence of a cell wall. Despite this, they adapt well not only to specific niches within the host organism but can also spread throughout the body, colonizing various organs and tissues. The adaptation mechanisms of M. hominis, as well as their regulatory pathways, are poorly understood. It is known that, when adapting to adverse conditions, Mycoplasmas can undergo phenotypic switches that may persist for several generations. Methods: To investigate the adaptive properties of M. hominis related to survival in the host, we conducted a comparative phenotypic and proteogenomic analysis of eight clinical isolates of M. hominis obtained from patients with urogenital infections and the laboratory strain H-34. Results: We have shown that clinical isolates differ in phenotypic features from the laboratory strain, form biofilms more effectively and show resistance to ofloxacin. The comparative proteogenomic analysis revealed that, unlike the laboratory strain, the clinical isolates possess several features related to stress survival: they switch carbon metabolism, activating the energetically least advantageous pathway of nucleoside utilization, which allows slowing down cellular processes and transitioning to a starvation state; they reconfigure the repertoire of membrane proteins; they have integrative conjugative elements in their genomes, which are key mediators of horizontal gene transfer. The upregulation of the methylating subunit of the restriction-modification (RM) system type I and the additional components of RM systems found in clinical isolates suggest that DNA methylation may play a role in regulating the adaptation mechanisms of M. hominis in the host organism. It has been shown that based on the proteogenomic profile, namely the genome sequence, protein content, composition of the RM systems and additional subunits HsdM, HsdS and HsdR, composition and number of transposable elements, as well as the sequence of the main variable antigen Vaa, we can divide clinical isolates into two phenotypes: typical colonies (TC), which have a high growth rate, and atypical (aTC) mini-colonies, which have a slow growth rate and exhibit properties similar to persisters. Discussion: We believe that the key mechanism of adaptation of M. hominis in the host is phenotypic restructuring, leading to a slowing down cellular processes and the formation of small atypical colonies. This is due to a switch in carbon metabolism and activation the pathway of nucleoside utilization. We hypothesize that DNA methylation may play a role in regulating this switch.

Coexistence of plasmid-mediated quinolone resistance (PMQR) and extended-spectrum beta-lactamase (ESBL) genes among clinical Pseudomonas aeruginosa isolates in Egypt.

BACKGROUND: Data about the prevalence of plasmid-mediated quinolone resistance (PMQR) and extended-spectrum beta-lactamase (ESBL) production in P. aeruginosa compared to the Enterobacteriaceae family is limited. The availability of limited therapeutic options raises alarming concerns about the treatment of multidrug-resistant P. aeruginosa. This study aimed to assess the presence of PMQR and ESBL genes among P. aeruginosa strains. METHODS: Fifty-six P. aeruginosa strains were isolated from 330 patients with different clinical infections. Phenotypically fluoroquinolone-resistant isolates were tested by PCR for the presence of six PMQR genes. Then, blaTEM, blaSHV, and blaCTX-M type ESBL genes were screened to study the co-existence of different resistance determinants. RESULTS: Overall, 22/56 (39.3%) of the studied P. aeruginosa isolates were phenotypically resistant to fluoroquinolones. PMQR-producing P. aeruginosa isolates were identified in 20 isolates (90.9%). The acc(6')-Ib-cr was the most prevalent PMQR gene (77.3%). The qnr genes occurred in 72.7%, with the predominance of the qnrA gene at 54.5%, followed by the qnrS gene at 27.3%, then qnrB and qnrC at 22.7%. The qepA was not detected in any isolate. The acc(6')-Ib-cr was associated with qnr genes in 65% of positive PMQR isolates. Significant differences between the fluoroquinolone-resistant and fluoroquinolone-susceptible isolates in terms of the antibiotic resistance rates of amikacin, imipenem, and cefepime (P value < 0.0001) were found. The ESBL genes were detected in 52% of cephalosporin-resistant P. aeruginosa isolates. The most frequent ESBL gene was blaCTX-M (76.9%), followed by blaTEM (46.2%). No isolates carried the blaSHV gene. The acc(6')-Ib-cr gene showed the highest association with ESBL genes, followed by the qnrA gene. The correlation matrix of the detected PMQR and ESBL genes indicated overall positive correlations. The strongest and most highly significant correlation was between qnrA and acc(6')-Ib-cr (r = 0.602) and between qnrA and blaCTX-M (r = 0.519). CONCLUSION: A high prevalence of PMQR genes among the phenotypic fluoroquinolone-resistant P. aeruginosa isolates was detected, with the co-carriage of different PMQR genes. The most frequent PMQR was the acc(6')-Ib-cr gene. Co-existence between PMQR and ESBL genes was found, with 75% of PMQR-positive isolates carrying at least one ESBL gene. A high and significant correlation between the ESBL and PMQR genes was detected.

Phenotypic and genotypic characterization of antimicrobial resistances reveals the effect of the production chain in reducing resistant lactic acid bacteria in an artisanal raw ewe milk PDO cheese.

Antimicrobial resistance (AMR) is a significant public health threat, with the food production chain, and, specifically, fermented products, as a potential vehicle for dissemination. However, information about dairy products, especially raw ewe milk cheeses, is limited. The present study analysed, for the first time, the occurrence of AMRs related to lactic acid bacteria (LAB) along a raw ewe milk cheese production chain for the most common antimicrobial agents used on farms (dihydrostreptomycin, benzylpenicillin, amoxicillin and polymyxin B). More than 200 LAB isolates were obtained and identified by Sanger sequencing (V1-V3 16S rRNA regions); these isolates included 8 LAB genera and 21 species. Significant differences in LAB composition were observed throughout the production chain (P ≤ 0.001), with Enterococcus (e.g., E. hirae and E. faecalis) and Bacillus (e.g., B. thuringiensis and B. cereus) predominating in ovine faeces and raw ewe milk, respectively, along with Lactococcus (L. lactis) in whey and fresh cheeses, while Lactobacillus and Lacticaseibacillus species (e.g., Lactobacillus sp. and L. paracasei) prevailed in ripened cheeses. Phenotypically, by broth microdilution, Lactococcus, Enterococcus and Bacillus species presented the greatest resistance rates (on average, 78.2 %, 56.8 % and 53.4 %, respectively), specifically against polymyxin B, and were more susceptible to dihydrostreptomycin. Conversely, Lacticaseibacillus and Lactobacillus were more susceptible to all antimicrobials tested (31.4 % and 39.1 %, respectively). Thus, resistance patterns and multidrug resistance were reduced along the production chain (P ≤ 0.05). Genotypically, through HT-qPCR, 31 antimicrobial resistance genes (ARGs) and 6 mobile genetic elements (MGEs) were detected, predominating Str, StrB and aadA-01, related to aminoglycoside resistance, and the transposons tnpA-02 and tnpA-01. In general, a significant reduction in ARGs and MGEs abundances was also observed throughout the production chain (P ≤ 0.001). The current findings indicate that LAB dynamics throughout the raw ewe milk cheese production chain facilitated a reduction in AMRs, which has not been reported to date.

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.

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.

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.

Knowing Our Enemy in the Antimicrobial Resistance Era: Dissecting the Molecular Basis of Bacterial Defense Systems.

Bacteria and their phage adversaries are engaged in an ongoing arms race, resulting in the development of a broad antiphage arsenal and corresponding viral countermeasures. In recent years, the identification and utilization of CRISPR-Cas systems have driven a renewed interest in discovering and characterizing antiphage mechanisms, revealing a richer diversity than initially anticipated. Currently, these defense systems can be categorized based on the bacteria's strategy associated with the infection cycle stage. Thus, bacterial defense systems can degrade the invading genetic material, trigger an abortive infection, or inhibit genome replication. Understanding the molecular mechanisms of processes related to bacterial immunity has significant implications for phage-based therapies and the development of new biotechnological tools. This review aims to comprehensively cover these processes, with a focus on the most recent discoveries.

Complete genome analysis of copper resistant bacteria Pseudoalteromonas sp. CuT4-3 isolated from a deep-sea hydrothermal vent.

Pseudoalteromonas sp. CuT4-3, a copper resistant bacterium, was isolated from deep-sea hydrothermal sulfides on the Southwest Indian Ridge (SWIR), is an aerobic, mesophilic and rod-shaped bacterium belonging to the family Pseudoalteromonadaceae (class Gammaproteobacteria, order Alteromonadales). In this study, we present the complete genome sequence of strain CuT4-3, which consists of a single circular chromosome comprising 3,660,538 nucleotides with 41.05% G + C content and two circular plasmids comprising 792,064 nucleotides with 40.36% G + C content and 65,436 nucleotides with 41.50% G + C content. In total, 4078 protein coding genes, 105 tRNA genes, and 25 rRNA genes were obtained. Genomic analysis of strain CuT4-3 identified numerous genes related to heavy metal resistance (especially copper) and EPS production. The genome of strain CuT4-3 will be helpful for further understanding of its adaptive strategies, particularly its ability to resist heavy metal, in the deep-sea hydrothermal vent environment.

Inferring diet, disease and antibiotic resistance from ancient human oral microbiomes.

The interaction between a host and its microbiome is an area of intense study. For the human host, it is known that the various body-site-associated microbiomes impact heavily on health and disease states. For instance, the oral microbiome is a source of various pathogens and potential antibiotic resistance gene pools. The effect of historical changes to the human host and environment to the associated microbiome, however, has been less well explored. In this review, we characterize several historical and prehistoric events which are considered to have impacted the oral environment and therefore the bacterial communities residing within it. The link between evolutionary changes to the oral microbiota and the significant societal and behavioural changes occurring during the pre-Neolithic, Agricultural Revolution, Industrial Revolution and Antibiotic Era is outlined. While previous studies suggest the functional profile of these communities may have shifted over the centuries, there is currently a gap in knowledge that needs to be filled. Biomolecular archaeological evidence of innate antimicrobial resistance within the oral microbiome shows an increase in the abundance of antimicrobial resistance genes since the advent and widespread use of antibiotics in the modern era. Nevertheless, a lack of research into the prevalence and evolution of antimicrobial resistance within the oral microbiome throughout history hinders our ability to combat antimicrobial resistance in the modern era.

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.

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.

Genomic epidemiology reveals multiple mechanisms of linezolid resistance in clinical enterococci in China.

BACKGROUND: Infections caused by linezolid-resistant enterococci (LRE) are clinically difficult to treat and threaten patient health. However, there is a lack of studies on long time-span LRE strains in China. For this reason, our study comprehensively revealed the resistance mechanisms of LRE strains collected in a Chinese tertiary care hospital from 2011 to 2022. METHODS: Enterococcal strains were screened and verified after retrospective analysis of microbial data. Subsequently, 65 LRE strains (61 Enterococcus faecalis and 4 Enterococcus faecium, MIC ≥ 8 µg/ml), 1 linezolid-intermediate Enterococcus faecium (MIC = 4 µg/ml) and 1 linezolid-susceptible Enterococcus faecium (MIC = 1.5 µg/ml) were submitted for whole-genome sequencing (WGS) analysis and bioinformatics analysis. RESULTS: The optrA gene was found to be the most common linezolid resistance mechanism in our study. We identified the wild-type OptrA and various OptrA variants in 98.5% of LRE strains (61 Enterococcus faecalis and 3 Enterococcus faecium). We also found one linezolid-resistant Enterococcus faecium strain carried both optrA and cfr(D) gene, while one linezolid-resistant Enterococcus faecium only harbored the poxtA gene. Most optrA genes (55/64) were located on plasmids, with impB-fexA-optrA, impB-fexA-optrA-erm(A), fexA-optrA-erm(A), and fexA-optrA segments. A minority of optrA genes (9/64) were found on chromosomes with the Tn6674-like platform. Besides, other possible linezolid resistance-associated mechanisms (mutations in the rplC and rplD genes) were also found in 26 enterococcal strains. CONCLUSIONS: Our study suggested that multiple mechanisms of linezolid resistance exist among clinical LRE strains in China.

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.

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.

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.

Mechanisms of Bacterial Drug Resistance with Special Emphasis on Phenotypic and Molecular Characterization of Extended Spectrum Beta-lactamase.

Antibiotics are designed to effectively treat bacterial infections while minimizing harm to the human body. They work by targeting specific components of bacteria or by disrupting essential processes such as cell wall synthesis, membrane function, protein production, and metabolic pathways. However, the misuse and overuse of antibiotics have led to the emergence of drug resistance in humans, animals, and agriculture, contributing to the global spread of this problem. Drug resistance can be either innate or acquired, with acquired resistance involving changes in the bacterial chromosomes or transferable elements. Bacterial species employ various mechanisms of drug resistance, including modifying the antibiotic targets, inactivating the drug, reducing uptake or increasing efflux, overexpressing the target, utilizing alternative pathways, and forming biofilms. One significant concern in the realm of drug resistance revolves around the emergence and proliferation of extended-spectrum beta-lactamases (ESBLs), a gene that is found in most gram-negative bacteria, primarily carried by Escherichia coli and Klebsiella pneumoniae in healthcare settings. ESBL-mediated resistance poses challenges for diagnosis, treatment, infection control, and antibiotic stewardship. Accurate detection of ESBL genes is crucial, and phenotypic methods are commonly used for initial screening. However, these methods have limitations, and confirmatory molecular techniques such as PCR and DNA sequencing are employed to accurately identify ESBL genes. Despite the significant global concerns surrounding ESBLs, they have spread worldwide, mainly facilitated by healthcare settings, inappropriate antimicrobial use, and host susceptibility. Addressing this issue requires implementing comprehensive measures, including enhanced surveillance, strict infection control practices, antibiotic stewardship programs, rapid diagnostic methods, alternative therapies, public education initiatives, and research focused on developing new drugs. Furthermore, collaboration among the healthcare, public health, and research sectors is pivotal in effectively combating the escalating threat posed by ESBL-mediated resistance. Antibiotics have revolutionized medical care by effectively treating bacterial infections. However, the emergence of ESBL gene resistance poses a global challenge that requires an integrated approach to prevent a threatening future.