Single nucleotide polymorphisms in genes encoding penicillin-binding proteins in β-lactamase-negative ampicillin-resistant Haemophilus influenzae in Japan

Resistance mechanism of Escherichia coli strains with different ampicillin resistance levels

Antibiotic resistance is an important problem that threatens medical treatment. Differences in the resistance levels of microorganisms cause great difficulties in understanding the mechanisms of antibiotic resistance. Therefore, the molecular reasons underlying the differences in the level of antibiotic resistance need to be clarified. For this purpose, genomic and transcriptomic analyses were performed on three Escherichia coli strains with varying degrees of adaptive resistance to ampicillin. Whole-genome sequencing of strains with different levels of resistance detected five mutations in strains with 10-fold resistance and two additional mutations in strains with 95-fold resistance. Overall, three of the seven mutations occurred as a single base change, while the other four occurred as insertions or deletions. While it was thought that 10-fold resistance was achieved by the effect of mutations in the ftsI, marAR, and rpoC genes, it was found that 95-fold resistance was achieved by the synergistic effect of five mutations and the ampC mutation. In addition, when the general transcriptomic profiles were examined, it was found that similar transcriptomic responses were elicited in strains with different levels of resistance. This study will improve our view of resistance mechanisms in bacteria with different levels of resistance and provide the basis for our understanding of the molecular mechanism of antibiotic resistance in ampicillin-resistant E. coli strains. KEY POINTS: •The mutation of the ampC promoter may act synergistically with other mutations and lead to higher resistance. •Similar transcriptomic responses to ampicillin are induced in strains with different levels of resistance. •Low antibiotic concentrations are the steps that allow rapid achievement of high antibiotic resistance.

Whole-genome sequencing of extensively drug-resistant Salmonella enterica serovar Typhi clinical isolates from the Peshawar region of Pakistan

BACKGROUND

Typhoid fever, caused by Salmonella enterica serovar Typhi, is a significant public health concern due to the escalating of antimicrobial resistance (AMR), with limited treatment options for extensively drug-resistant (XDR) S. Typhi strains pose a serious threat to disease management and control. This study aimed to investigate the genomic characteristics, epidemiology and AMR genes of XDR S. Typhi strains from typhoid fever patients in Pakistan.

METHODOLOGY

We assessed 200 patients with enteric fever symptoms, confirming 65 S. Typhi cases through culturing and biochemical tests. Subsequent antimicrobial susceptibility testing revealed 40 cases of extensively drug-resistant (XDR) and 25 cases of multi-drug resistance (MDR). Thirteen XDR strains were selected for whole-genome sequencing, to analyze their sequence type, phylogenetics, resistance genes, pathogenicity islands, and plasmid sequences using variety of data analysis resources. Pangenome analysis was conducted for 140 XDR strains, including thirteen in-house and 127 strains reported from other regions of Pakistan, to assess their genetic diversity and functional annotation.

RESULTS

MLST analysis classified all isolates as sequence type 1 (ST-1) with 4.3.1.1. P1 genotype characterization. Prophage and Salmonella Pathogenicity Island (SPI) analysis identified intact prophages and eight SPIs involved in Salmonella's invasion and replication within host cells. Genome data analysis revealed numerous AMR genes including dfrA7, sul1, qnrS1, TEM-1, Cat1, and CTX-M-15, and SNPs associated with antibiotics resistance. IncY, IncQ1, pMAC, and pAbTS2 plasmids, conferring antimicrobial resistance, were detected in a few XDR S. Typhi strains. Phylogenetic analysis inferred a close epidemiological linkage among XDR strains from different regions of Pakistan. Pangenome was noted closed among these strains and functional annotation highlighted genes related to metabolism and pathogenesis.

CONCLUSION

This study revealed a uniform genotypic background among XDR S. Typhi strains in Pakistan, signifying a persistence transmission of a single, highly antibiotic-resistant clone. The closed pan-genome observed underscores limited genetic diversity and highlights the importance of genomic surveillance for combating drug-resistant typhoid infections.

Study on the drug resistance and pathogenicity of Escherichia coli isolated from calf diarrhea and the distribution of virulence genes and antimicrobial resistance genes

Introduction

The unscientific and irrational use of antimicrobial drugs in dairy farms has led to the emergence of more serious drug resistance in Escherichia coli.

Methods

In this study, cases of calf diarrhea in cattle farms around the Hohhot area were studied, and Escherichia coli were identified by PCR and biochemical methods, while the distribution of virulence and drug resistance genes of the isolates was analyzed.

Results

The results showed that 21 strains of Escherichia coli were isolated from the diseased materials, and the isolation rate was 60%. The isolated strains belong to 15 ST types. The drug resistance levels of the isolated strains to 20 kinds of antimicrobial agent viz., penicillin, ampicillin, cefotaxime, cefepime, cefoxitin, and ceftriaxone were more than 50%. The resistance rate to meropenem was 10%. The resistance rates to tetracycline and doxycycline were 33% and 29%, to ciprofloxacin, levofloxacin and enrofloxacin were 48%, 33%, and 33%, to amikacin, kanamycin and gentamicin were 19%, 24% and 38%, to cotrimoxazole and erythromycin were 48% and 15%, to florfenicol, chloramphenicol and polymyxin B were 29%, 33%, and 5%. Nine strains of pathogenic calf diarrhea Escherichia coli were isolated by mouse pathogenicity test. The detection rates of virulence genes for the adhesion class were fimC (95%), IuxS (95%), eaeA (76%), fimA (62%), ompA (52%), and flu (24%). The detection rates for iron transporter protein like virulence genes were iroN (33%), iutA (19%), fyuA (14%), irp5 (9.5%), Iss (9.5%), and iucD (9.5%). The detection rates for toxin-like virulence genes were phoA (90%), Ecs3703 (57%), ropS (33%), hlyF (14%), and F17 (9.5%). The detection rates of tetracycline resistance genes in isolated strains were tetB (29%), tetA (19%) and tetD (14%). The detection rates for fluoroquinolone resistance genes were parC (Y305H, P333S, R355G) (9.5%), gyrA (S83L, D87N) (28%), qnrD (43%), and qnrS (9.5%). The detection rates for β-lactam resistance genes were bla _CTX-M (29%), bla _TEM (29%), and bla _SHV (9.5%). The detection rates for aminoglycoside resistance genes were strA-B (57%), aacC (33%), aac(3')-IIa (29%), and aadAI (24%). The detection rates of chloramphenicol resistance genes floR and sulfa resistance genes sul2 were 24 and 33%.

Conclusion

Pathogenic Escherichia coli causing diarrhea in calves contain abundant virulence genes and antibiotic resistance genes.

Pharmaceutical nanotechnology: Antimicrobial peptides as potential new drugs against WHO list of critical, high, and medium priority bacteria

Nanobiotechnology is a relatively unexplored area that has, nevertheless, shown relevant results in the fight against some diseases. Antimicrobial peptides (AMPs) are biomacromolecules with potential activity against multi/extensively drug-resistant bacteria, with a lower risk of generating bacterial resistance. They can be considered an excellent biotechnological alternative to conventional drugs. However, the application of several AMPs to biological systems is hampered by their poor stability and lifetime, inactivating them completely. Therefore, nanotechnology plays an important role in the development of new AMP-based drugs, protecting and carrying the bioactive to the target. This is the first review article on the different reported nanosystems using AMPs against bacteria listed on the WHO priority list. The current shortage of information implies a nanobiotechnological potential to obtain new drugs or repurpose drugs based on the AMP-drug synergistic effect.

Resistance determinants and their genetic context in enterobacteria from a longitudinal study of pigs reared under various husbandry conditions

Pigs are major reservoirs of resistant Enterobacteriaceae that can reach humans through consumption of contaminated meat or vegetables grown in manure-fertilized soil. Samples were collected from sows during lactation and their piglets at five time points spanning the production cycle. Cefotaxime-resistant bacteria were quantified and isolated from feed, feces, manures and carcasses of pigs reared with penicillin-using or antibiotic-free husbandries. The isolates were characterized by antibiotic susceptibility testing, whole genome sequencing and conjugation assays. The extended spectrum β-lactamase (ESBL) phenotype was more frequent in isolates originating from antibiotic-free animals, while the bacteria isolated from penicillin-using animals were on average resistant to a greater number of antibiotics. The ESBL-encoding genes identified were bla _CTX-M-1, bla _CTX-M-15 and bla _CMY-2 and they co-localised on plasmids with various genes encoding resistance to ß-lactams, co-trimoxazole, phenicols and tetracycline, all antibiotics used in pig production. Groups of genes conferring the observed resistance and the mobile elements disseminating multidrug resistance were determined. The observed resistance to ß-lactams was mainly due to the complementary actions of penicillin-binding proteins, an efflux pump and ß-lactamases. Most resistance determinants were shared by animals raised with or without antimicrobials. This suggests a key contribution of indigenous enterobacteria maternally transmitted along the sow lineage, regardless of antimicrobial use. It is unclear if the antimicrobial resistance observed in the enterobacteria populations of the commercial pig herds studied were present before the use of antibiotics, or the extent to which historical antimicrobial use exerted a selective pressure defining the resistant bacterial populations in farms using penicillin prophylaxis.Importance: Antimicrobial resistance is a global threat that needs to be fought on numerous fronts along the One Health continuum. Vast quantities of antimicrobials are used in agriculture to ensure animal welfare and productivity, and are arguably a driving force for the persistence of environmental and food-borne resistant bacteria. This study evaluated the impact of conventional, organic and other antibiotic-free husbandry practices on the frequency and nature of antimicrobial resistance genes and multidrug resistant enterobacteria. It provides knowledge about the relative contribution of specific resistance determinants to observed antibiotic resistance. It also showed the clear co-selection of genes coding for extended-spectrum beta-lactamases and genes coding for the resistance to antibiotics commonly used for prophylaxis or in curative treatments in pig operations.

Extended-Spectrum β-Lactamases in Human Isolates of Multidrug-Resistant Non-typhoidal Salmonella enterica

A total of 291 non-duplicate isolates of non-typhoidal Salmonella (NTS) were collected from the fecal samples of patients with salmonellosis in Armenia and Georgia during 1996–2016. The isolates were tested for resistance to antimicrobials, including extended-spectrum β-lactamases (ESBL). The high prevalence of multidrug-resistance (MDR) and ESBL-producer phenotypes was detected among Salmonella enterica subsp. enterica serovar Typhimurium (S. Typhimurium) isolates collected from patients in Armenia between 1996 and 2016. A total of 36 MDR NTS isolates were subjected to whole genome sequencing (WGS) to determine the genetic background of antimicrobial resistance (AMR) and mobile genetic elements. All ESBL-producing S. Typhimurium isolates belonged to the same sequence type (ST328). The ESBL-producer phenotype was associated with plasmid-encoded CTX-M-5 production. A range of other plasmids was associated with resistance to other antimicrobials, including the MDR phenotype.

Evaluation of the adequacy of the antimicrobial therapy of invasive Haemophilus influenzae infections: A pharmacokinetic/pharmacodynamic perspective

INTRODUCTION

In Europe, non-typeable H. influenzae (NTHi) is the leading cause of invasive H. influenzae disease in adults and is associated with high mortality. The goal of this study was to determine whether current antimicrobial treatments for H. influenzae infection in Spain are suitable based on their probability of achieving pharmacokinetic/pharmacodynamic (PK/PD) targets.

METHODS

Pharmacokinetic parameters for the antibiotics studied (amoxicillin, amoxicillin/clavulanic acid, ampicillin, cefotaxime, ceftriaxone, imipenem and ciprofloxacin) and susceptibility data for H. influenzae were obtained from literature. A Monte Carlo simulation was used to estimate the probability of target attainment (PTA), defined as the probability that at least a specific value of a PK/PD index is achieved at a certain MIC, and the cumulative fraction of response (CFR), defined as the expected population PTA for a specific drug dose and a specific microorganism population.

RESULTS

Regardless of dosing regimen, all antibiotics yielded CFR values of 100% or nearly 100% for all strains, including BL+, BL- and BLNAR, except amoxicillin and ampicillin for BL+. Thus, if an infection is caused by BL+ strains, treatment with amoxicillin and ampicillin has a high probability of failure (CFR≤8%). For standard doses of amoxicillin, amoxicillin/clavulanic acid and imipenem, PK/PD breakpoints were consistent with EUCAST clinical breakpoints. For the other antimicrobials, PK/PD breakpoints were higher than EUCAST clinical breakpoints.

CONCLUSIONS

Our study confirms by PK/PD analysis that, with the antimicrobials used as empirical treatment of invasive H. influenzae disease, a high probability of therapeutic success can be expected.

Identification of Primary Antimicrobial Resistance Drivers in Agricultural Nontyphoidal Salmonella enterica Serovars by Using Machine Learning

Nontyphoidal Salmonella (NTS) is a leading global cause of bacterial foodborne morbidity and mortality. Our ability to treat severe NTS infections has been impaired by increasing antimicrobial resistance (AMR). To understand and mitigate the global health crisis AMR represents, we need to link the observed resistance phenotypes with their underlying genomic mechanisms. Broiler chickens represent a key reservoir and vector for NTS infections, but isolates from this setting have been characterized in only very low numbers relative to clinical isolates. In this study, we sequenced and assembled 97 genomes encompassing 7 serotypes isolated from broiler chicken in farms in British Columbia between 2005 and 2008. Through application of machine learning (ML) models to predict the observed AMR phenotype from this genomic data, we were able to generate highly (0.92 to 0.99) precise logistic regression models using known AMR gene annotations as features for 7 antibiotics (amoxicillin-clavulanic acid, ampicillin, cefoxitin, ceftiofur, ceftriaxone, streptomycin, and tetracycline). Similarly, we also trained "reference-free" k-mer-based set-covering machine phenotypic prediction models (0.91 to 1.0 precision) for these antibiotics. By combining the inferred k-mers and logistic regression weights, we identified the primary drivers of AMR for the 7 studied antibiotics in these isolates. With our research representing one of the largest studies of a diverse set of NTS isolates from broiler chicken, we can thus confirm that the AmpC-like CMY-2 β-lactamase is a primary driver of β-lactam resistance and that the phosphotransferases APH(6)-Id and APH(3″-Ib) are the principal drivers of streptomycin resistance in this important ecosystem.IMPORTANCE Antimicrobial resistance (AMR) represents an existential threat to the function of modern medicine. Genomics and machine learning methods are being increasingly used to analyze and predict AMR. This type of surveillance is very important to try to reduce the impact of AMR. Machine learning models are typically trained using genomic data, but the aspects of the genomes that they use to make predictions are rarely analyzed. In this work, we showed how, by using different types of machine learning models and performing this analysis, it is possible to identify the key genes underlying AMR in nontyphoidal Salmonella (NTS). NTS is among the leading cause of foodborne illness globally; however, AMR in NTS has not been heavily studied within the food chain itself. Therefore, in this work we performed a broad-scale analysis of the AMR in NTS isolates from commercial chicken farms and identified some priority AMR genes for surveillance.