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Antimicrobial Agents and Chemotherapy Jun 2024Intrinsic resistance to macrolides in Gram-negative bacteria is primarily attributed to the low permeability of the outer membrane, though the underlying genetic and...
Intrinsic resistance to macrolides in Gram-negative bacteria is primarily attributed to the low permeability of the outer membrane, though the underlying genetic and molecular mechanisms remain to be fully elucidated. Here, we used transposon directed insertion-site sequencing (TraDIS) to identify chromosomal non-essential genes involved in intrinsic resistance to a macrolide antibiotic, tilmicosin. We constructed two highly saturated transposon mutant libraries of >290,000 and >390,000 unique Tn5 insertions in a clinical enterotoxigenic strain (ETEC5621) and in a laboratory strain (K-12 MG1655), respectively. TraDIS analysis identified genes required for growth of ETEC5621 and MG1655 under 1/8 MIC ( = 15 and 16, respectively) and 1/4 MIC ( = 38 and 32, respectively) of tilmicosin. For both strains, 23 genes related to lipopolysaccharide biosynthesis, outer membrane assembly, the Tol-Pal system, efflux pump, and peptidoglycan metabolism were enriched in the presence of the antibiotic. Individual deletion of genes ( = 10) in the wild-type strains led to a 64- to 2-fold reduction in MICs of tilmicosin, erythromycin, and azithromycin, validating the results of the TraDIS analysis. Notably, deletion of or , which impairs the outer membrane, led to the most significant decreases in MICs of all three macrolides in ETEC5621. Our findings contribute to a genome-wide understanding of intrinsic macrolide resistance in , shedding new light on the potential role of the peptidoglycan layer. They also provide an proof of concept that can be sensitized to macrolides by targeting proteins maintaining the outer membrane such as SurA and WaaG.
PubMed: 38940570
DOI: 10.1128/aac.00452-24 -
Applied and Environmental Microbiology Jun 2024Microbial source tracking leverages a wide range of approaches designed to trace the origins of fecal contamination in aquatic environments. Although source tracking...
Microbial source tracking leverages a wide range of approaches designed to trace the origins of fecal contamination in aquatic environments. Although source tracking methods are typically employed within the laboratory setting, computational techniques can be leveraged to advance microbial source tracking methodology. Herein, we present a logic regression-based supervised learning approach for the discovery of source-informative genetic markers within intergenic regions across the genome that can be used for source tracking. With just single intergenic loci, logic regression was able to identify highly source-specific (i.e., exceeding 97.00%) biomarkers for a wide range of host and niche sources, with sensitivities reaching as high as 30.00%-50.00% for certain source categories, including pig, sheep, mouse, and wastewater, depending on the specific intergenic locus analyzed. Restricting the source range to reflect the most prominent zoonotic sources of transmission (i.e., bovine, chicken, human, and pig) allowed for the generation of informative biomarkers for all host categories, with specificities of at least 90.00% and sensitivities between 12.50% and 70.00%, using the sequence data from key intergenic regions, including , and , that appear to be involved in antibiotic resistance. Remarkably, we were able to use this approach to classify 48 out of 113 river water isolates collected in Northwestern Sweden as either beaver, human, or reindeer in origin with a high degree of consensus-thus highlighting the potential of logic regression modeling as a novel approach for augmenting current source tracking efforts.IMPORTANCEThe presence of microbial contaminants, particularly from fecal sources, within water poses a serious risk to public health. The health and economic burden of waterborne pathogens can be substantial-as such, the ability to detect and identify the sources of fecal contamination in environmental waters is crucial for the control of waterborne diseases. This can be accomplished through microbial source tracking, which involves the use of various laboratory techniques to trace the origins of microbial pollution in the environment. Building on current source tracking methodology, we describe a novel workflow that uses logic regression, a supervised machine learning method, to discover genetic markers in , a common fecal indicator bacterium, that can be used for source tracking efforts. Importantly, our research provides an example of how the rise in prominence of machine learning algorithms can be applied to improve upon current microbial source tracking methodology.
PubMed: 38940567
DOI: 10.1128/aem.00227-24 -
Applied and Environmental Microbiology Jun 2024Enterotoxigenic (ETEC) is a diverse and poorly characterized pathotype that causes diarrhea in humans and animals. Phages have been proposed for the veterinary...
Enterotoxigenic (ETEC) is a diverse and poorly characterized pathotype that causes diarrhea in humans and animals. Phages have been proposed for the veterinary biocontrol of ETEC, but effective solutions require understanding of porcine ETEC diversity that affects phage infection. Here, we sequenced and analyzed the genomes of the PHAGEBio ETEC collection, gathering 79 diverse ETEC strains isolated from European pigs with post-weaning diarrhea (PWD). We identified the virulence factors characterizing the pathotype and several antibiotic resistance genes on plasmids, while phage resistance genes and other virulence factors were mostly chromosome encoded. We experienced that ETEC strains were highly resistant to phage infection. It was only by enrichment of numerous diverse samples with different media and conditions, using the 41 ETEC strains of our collection as hosts, that we could isolate two lytic phages that could infect a large part of our diverse ETEC collection: vB_EcoP_ETEP21B and vB_EcoS_ETEP102. Based on genome and host range analyses, we discussed the infection strategies of the two phages and identified components of lipopolysaccharides ( LPS) as receptors for the two phages. Our detailed computational structural analysis highlights several loops and pockets in the tail fibers that may allow recognition and binding of ETEC strains, also in the presence of O-antigens. Despite the importance of receptor recognition, the diversity of the ETEC strains remains a significant challenge for isolating ETEC phages and developing sustainable phage-based products to address ETEC-induced PWD.IMPORTANCEEnterotoxigenic (ETEC)-induced post-weaning diarrhea is a severe disease in piglets that leads to weight loss and potentially death, with high economic and animal welfare costs worldwide. Phage-based approaches have been proposed, but available data are insufficient to ensure efficacy. Genome analysis of an extensive collection of ETEC strains revealed that phage defense mechanisms were mostly chromosome encoded, suggesting a lower chance of spread and selection by phage exposure. The difficulty in isolating lytic phages and the molecular and structural analyses of two ETEC phages point toward a multifactorial resistance of ETEC to phage infection and the importance of extensive phage screenings specifically against clinically relevant strains. The PHAGEBio ETEC collection and these two phages are valuable tools for the scientific community to expand our knowledge on the most studied, but still enigmatic, bacterial species-.
PubMed: 38940562
DOI: 10.1128/aem.00807-24 -
MBio Jun 2024Conjugative type 4 secretion systems (T4SSs) are the main driver for the spread of antibiotic resistance genes and virulence factors in bacteria. To deliver the DNA...
Conjugative type 4 secretion systems (T4SSs) are the main driver for the spread of antibiotic resistance genes and virulence factors in bacteria. To deliver the DNA substrate to recipient cells, it must cross the cell envelopes of both donor and recipient bacteria. In the T4SS from the enterococcal conjugative plasmid pCF10, PrgK is known to be the active cell wall degrading enzyme. It has three predicted extracellular hydrolase domains: metallo-peptidase (LytM), soluble lytic transglycosylase (SLT), and cysteine, histidine-dependent amidohydrolases/peptidases (CHAP). Here, we report the structure of the LytM domain and show that its active site is degenerate and lacks the active site metal. Furthermore, we show that only the predicted SLT domain is functional and that it unexpectedly has a muramidase instead of a lytic transglycosylase activity. While we did not observe any peptidoglycan hydrolytic activity for the LytM or CHAP domain, we found that these domains downregulated the SLT muramidase activity. The CHAP domain was also found to be involved in PrgK dimer formation. Furthermore, we show that PrgK interacts with PrgL, which likely targets PrgK to the rest of the T4SS. The presented data provides important information for understanding the function of Gram-positive T4SSs.IMPORTANCEAntibiotic resistance is a large threat to human health and is getting more prevalent. One of the major contributors to the spread of antibiotic resistance among different bacteria is type 4 secretion systems (T4SS). However, mainly T4SSs from Gram-negative bacteria have been studied in detail. T4SSs from Gram-positive bacteria, which stand for more than half of all hospital-acquired infections, are much less understood. The significance of our research is in identifying the function and regulation of a cell wall hydrolase, a key component of the pCF10 T4SS from . This system is one of the best-studied Gram-positive T4SSs, and this added knowledge aids in our understanding of horizontal gene transfer in as well as other medically relevant Gram-positive bacteria.
PubMed: 38940556
DOI: 10.1128/mbio.00488-24 -
MSystems Jun 2024Relationships between bacterial taxa are traditionally defined using 16S rRNA nucleotide similarity or average nucleotide identity. Improvements in sequencing technology...
UNLABELLED
Relationships between bacterial taxa are traditionally defined using 16S rRNA nucleotide similarity or average nucleotide identity. Improvements in sequencing technology provide additional pairwise information on genome sequences, which may provide valuable information on genomic relationships. Mapping orthologous gene locations between genome pairs, known as synteny, is typically implemented in the discovery of new species and has not been systematically applied to bacterial genomes. Using a data set of 378 bacterial genomes, we developed and tested a new measure of synteny similarity between a pair of genomes, which was scaled onto 16S rRNA distance using covariance matrices. Based on the input gene functions used (i.e., core, antibiotic resistance, and virulence), we observed varying topological arrangements of bacterial relationship networks by applying (i) complete linkage hierarchical clustering and (ii) K-nearest neighbor graph structures to synteny-scaled 16S data. Our metric improved clustering quality comparatively to state-of-the-art average nucleotide identity metrics while preserving clustering assignments for the highest similarity relationships. Our findings indicate that syntenic relationships provide more granular and interpretable relationships for within-genera taxa compared to pairwise similarity measures, particularly in functional contexts.
IMPORTANCE
Given the prevalence and necessity of the 16S rRNA measure in bacterial identification and analysis, this additional analysis adds a functional and synteny-based layer to the identification of relatives and clustering of bacteria genomes. It is also of computational interest to model the bacterial genome as a graph structure, which presents new avenues of genomic analysis for bacteria and their closely related strains and species.
PubMed: 38940518
DOI: 10.1128/msystems.00497-24 -
MSphere Jun 2024Bacterial conjugation systems pose a major threat to human health through their widespread dissemination of mobile genetic elements (MGEs) carrying cargoes of antibiotic...
UNLABELLED
Bacterial conjugation systems pose a major threat to human health through their widespread dissemination of mobile genetic elements (MGEs) carrying cargoes of antibiotic resistance genes. Using the Cre Recombinase Assay for Translocation (CRAfT), we recently reported that the IncFV pED208 conjugation system also translocates at least 16 plasmid-encoded proteins to recipient bacteria. Here, we deployed a high-throughput CRAfT screen to identify the repertoire of chromosomally encoded protein substrates of the pED208 system. We identified 32 substrates encoded by the W3110 genome with functions associated with (i) DNA/nucleotide metabolism, (ii) stress tolerance/physiology, (iii) transcriptional regulation, or (iv) toxin inhibition. The respective gene deletions did not impact pED208 transfer proficiencies, nor did Group 1 (DNA/nucleotide metabolism) mutations detectably alter the SOS response elicited in new transconjugants upon acquisition of pED208. However, MC4100(pED208) donor cells intrinsically exhibit significantly higher SOS activation than plasmid-free MC4100 cells, and this plasmid carriage-induced stress response is further elevated in donor cells deleted of several Group 1 genes. Among 10 characterized substrates, we gained evidence of C-terminal or internal translocation signals that could function independently or synergistically for optimal protein transfer. Remarkably, nearly all tested proteins were also translocated through the IncN pKM101 and IncP RP4 conjugation systems. This repertoire of protein substrates, here termed the F plasmid "conjutome," is thus characterized by functions of potential benefit to new transconjugants, diverse TSs, and the capacity for promiscuous transfer through heterologous conjugation systems.
IMPORTANCE
Conjugation systems comprise a major subfamily of the type IV secretion systems (T4SSs) and are the progenitors of a second large T4SS subfamily dedicated to translocation of protein effectors. This study examined the capacity of conjugation machines to function as protein translocators. Using a high-throughput reporter screen, we determined that 32 chromosomally encoded proteins are delivered through an F plasmid conjugation system. The translocated proteins potentially enhance the establishment of the co-transferred F plasmid or mitigate mating-induced stresses. Translocation signals located C-terminally or internally conferred substrate recognition by the F system and, remarkably, many substrates also were translocated through heterologous conjugation systems. Our findings highlight the plasticity of conjugation systems in their capacities to co-translocate DNA and many protein substrates.
PubMed: 38940509
DOI: 10.1128/msphere.00354-24 -
MSphere Jun 2024is an enteric pathogen that can cause a range of illnesses from mild diarrhea to pseudomembranous colitis and even death. This pathogen often takes advantage of...
UNLABELLED
is an enteric pathogen that can cause a range of illnesses from mild diarrhea to pseudomembranous colitis and even death. This pathogen often takes advantage of microbial dysbiosis provoked by antibiotic use. With the increasing incidence and severity of infections, coupled with high recurrence rates, there is an urgent need to identify innovative therapies that can preserve the healthy state of the gut microbiota. In this study, we screened a microbial metabolite library against . From a collection of 527 metabolites, we identified 18 compounds with no previously identified antimicrobial activity and metabolites that exhibited potent activity against growth. Of these 18 hits, five drugs and three metabolites displayed the most potent anti-. activity and were subsequently assessed against 20 clinical isolates of . These potent agents included ecteinascidin 770 (minimum inhibitory concentration against 50% of isolates [MIC] ≤0.06 µg/mL); 8-hydroxyquinoline derivatives, such as broxyquinoline and choloroquinaldol (MIC = 0.125 µg/mL); ionomycin calcium salt, carbadox, and robenidine hydrochloride (MIC = 1 µg/mL); and dronedarone and milbemycin oxime (MIC = 4 µg/mL). Unlike vancomycin and fidaxomicin, which are the standard-of-care anti-. antibiotics, most of these metabolites showed robust bactericidal activity within 2-8 h with minimal impact on the growth of representative members of the normal gut microbiota. These results suggest that the drugs and microbial metabolite scaffolds may offer alternative avenues to address unmet needs in disease prevention and treatment.
IMPORTANCE
The most frequent infection associated with hospital settings is , which can cause fatal diarrhea and severe colitis, toxic megacolon, sepsis, and leaky gut. Those who have taken antibiotics for other illnesses that affect the gut's healthy microbiota are more susceptible to infection (CDI). Recently, some reports showed higher recurrence rates and resistance to anti-, which may compromise the efficacy of CDI treatment. Our study is significant because it is anticipated to discover novel microbial metabolites and drugs with microbial origins that are safe for the intestinal flora, effective against , and reduce the risk of recurrence associated with CDI.
PubMed: 38940508
DOI: 10.1128/msphere.00273-24 -
ACS Infectious Diseases Jun 2024The ability of pathogenic bacteria to evade antibiotic treatment is an intricate and multifaceted phenomenon. Over the years, treatment failure among patients due to... (Review)
Review
The ability of pathogenic bacteria to evade antibiotic treatment is an intricate and multifaceted phenomenon. Over the years, treatment failure among patients due to determinants of antimicrobial resistance (AMR) has been the focal point for the research and development of new therapeutic agents. However, the survival of bacteria by persisting under antibiotic stress has largely been overlooked. Bacterial persisters are a subpopulation of sensitive bacterial cells exhibiting a noninheritable drug-tolerant phenotype. They are linked to the recalcitrance of infections in healthcare settings, in turn giving rise to AMR variants. The importance of bacterial persistence in recurring infections has been firmly recognized. Fundamental work over the past decade has highlighted numerous unique tolerance factors contributing to the persister phenotype in many clinically relevant pathogens. This review summarizes contributing factors that could aid in developing new strategies against bacterial antibiotic persisters.
PubMed: 38940498
DOI: 10.1021/acsinfecdis.4c00270 -
Bioinformatics (Oxford, England) Jun 2024World Health Organization estimates that there were over 10 million cases of tuberculosis (TB) worldwide in 2019, resulting in over 1.4 million deaths, with a worrisome...
MOTIVATION
World Health Organization estimates that there were over 10 million cases of tuberculosis (TB) worldwide in 2019, resulting in over 1.4 million deaths, with a worrisome increasing trend yearly. The disease is caused by Mycobacterium tuberculosis (MTB) through airborne transmission. Treatment of TB is estimated to be 85% successful, however, this drops to 57% if MTB exhibits multiple antimicrobial resistance (AMR), for which fewer treatment options are available.
RESULTS
We develop a robust machine-learning classifier using both linear and nonlinear models (i.e. LASSO logistic regression (LR) and random forests (RF)) to predict the phenotypic resistance of Mycobacterium tuberculosis (MTB) for a broad range of antibiotic drugs. We use data from the CRyPTIC consortium to train our classifier, which consists of whole genome sequencing and antibiotic susceptibility testing (AST) phenotypic data for 13 different antibiotics. To train our model, we assemble the sequence data into genomic contigs, identify all unique 31-mers in the set of contigs, and build a feature matrix M, where M[i, j] is equal to the number of times the ith 31-mer occurs in the jth genome. Due to the size of this feature matrix (over 350 million unique 31-mers), we build and use a sparse matrix representation. Our method, which we refer to as MTB++, leverages compact data structures and iterative methods to allow for the screening of all the 31-mers in the development of both LASSO LR and RF. MTB++ is able to achieve high discrimination (F-1 >80%) for the first-line antibiotics. Moreover, MTB++ had the highest F-1 score in all but three classes and was the most comprehensive since it had an F-1 score >75% in all but four (rare) antibiotic drugs. We use our feature selection to contextualize the 31-mers that are used for the prediction of phenotypic resistance, leading to some insights about sequence similarity to genes in MEGARes. Lastly, we give an estimate of the amount of data that is needed in order to provide accurate predictions.
AVAILABILITY
The models and source code are publicly available on Github at https://github.com/M-Serajian/MTB-Pipeline.
Topics: Mycobacterium tuberculosis; Machine Learning; Drug Resistance, Bacterial; Microbial Sensitivity Tests; Anti-Bacterial Agents; Whole Genome Sequencing; Genome, Bacterial; Humans
PubMed: 38940175
DOI: 10.1093/bioinformatics/btae243 -
Annals of Agricultural and... Jun 2024Escherichia coli is one of the most common bacteria isolated from urine samples collected from dogs and cats with urinary tract infection (UTI). Uncomplicated UTIs in...
INTRODUCTION AND OBJECTIVE
Escherichia coli is one of the most common bacteria isolated from urine samples collected from dogs and cats with urinary tract infection (UTI). Uncomplicated UTIs in dogs and cats can be treated with short courses of first-line antimicrobial drugs, e.g. amoxicillin, amoxicillin with clavulanic acid, or trimethoprim/sulfonamide. Recurrent or complicated UTIs often require long-term treatment with broad-spectrum antibiotics. However, the choice of drug should be based on antimicrobial susceptibility.
MATERIAL AND METHODS
Between March - September 2022, E. coli isolates cultured from the urine of 66 dogs and 41 cats with UTI symptoms were tested for antimicrobial resistance by using Minimum Inhibitory Concentration (MIC). Antimicrobial susceptibility was tested for ampicillin, ampicillin/sulbactam, cefazolin, cefuroxime, aztreonam, gentamycin, amikacin, colistin, trimethoprim/sulfamethoxazole, ciprofloxacin, chloramphenicol and tetracycline.
RESULTS
The highest prevalence of resistance was documented for ampicillin (68% in dogs, 100% in cats) and ampicillin with sulbactam (59% in dogs, 54% in cats). The most common antimicrobial resistance patterns of E. coli were ampicillin alone (12 isolates, 29.3% in cats) and beta-lactams, including aztreonam (14 isolates, 21.2% in dogs).
CONCLUSIONS
High resistance to aztreonam (61% and 32% of isolates from dogs and cats, respectively), other beta-lactams, and fluoroquinolones should cause be alarm due to zoonotic potential and cross-transmission of antimicrobial-resistant microorganisms between animals and humans.
Topics: Dogs; Cats; Animals; Urinary Tract Infections; Cat Diseases; Escherichia coli; Dog Diseases; Anti-Bacterial Agents; Microbial Sensitivity Tests; Drug Resistance, Multiple, Bacterial; Escherichia coli Infections; Urinary Bladder; Female; Male
PubMed: 38940100
DOI: 10.26444/aaem/176843