Project description:In this study, two multiantibiotic-resistant bacteria, Ochrobactrum intermedium (N1) and Stenotrophomonas acidaminiphila (N2), were isolated from the sludge of a PWWTP in Guangzhou, China. Whole-genome sequencing revealed that N1 and N2 had genome sizes of 0.52 Mb and 0.37 Mb, respectively, and harbored 33 and 24 ARGs, respectively. The main resistance mechanism in the identified ARGs included efflux pumps, enzymatic degradation, and target bypass, with the N1 strain possessing more multidrug-resistant efflux pumps than the N2 strain (22 vs 12). This also accounts for the broader resistance spectrum of N1 than of N2 in antimicrobial susceptibility tests. Additionally, both genomes contain numerous mobile genetic elements (89 and 21 genes, respectively) and virulence factors (276 and 250 factors, respectively), suggesting their potential for horizontal transfer and pathogenicity.
Project description:Incomplete antibiotic removal in pharmaceutical wastewater treatment plants (PWWTPs) could lead to the development and spread of antibiotic-resistant bacteria (ARBs) and genes (ARGs) in the environment, posing a growing public health threat. In this study, two multiantibiotic-resistant bacteria, Ochrobactrum intermedium (N1) and Stenotrophomonas acidaminiphila (N2), were isolated from the sludge of a PWWTP in Guangzhou, China. The N1 strain was highly resistant to ampicillin, cefazolin, chloramphenicol, tetracycline, and norfloxacin, while the N2 strain exhibited high resistance to ampicillin, chloramphenicol, and cefazolin. Whole-genome sequencing revealed that N1 and N2 had genome sizes of 0.52 Mb and 0.37 Mb, respectively, and harbored 33 and 24 ARGs, respectively. The main resistance mechanism in the identified ARGs included efflux pumps, enzymatic degradation, and target bypass, with the N1 strain possessing more multidrug-resistant efflux pumps than the N2 strain (22 vs 12). This also accounts for the broader resistance spectrum of N1 than of N2 in antimicrobial susceptibility tests. Additionally, both genomes contain numerous mobile genetic elements (89 and 21 genes, respectively) and virulence factors (276 and 250 factors, respectively), suggesting their potential for horizontal transfer and pathogenicity. Overall, this research provides insights into the potential risks posed by ARBs in pharmaceutical wastewater and emphasizes the need for further studies on their impact and mitigation strategies.
Project description:Escherichia coli is an important opportunistic pathogen associated with multidrug-resistant infections in humans and animals. In this study, we performed a global proteomic analysis of the isolateEC15 to characterize its whole-cell protein expression profile. Bacterial cells were cultured under standard laboratory conditions, and total proteins were extracted, digested with trypsin, and analyzed by high-resolution LC–MS/MS. The resulting dataset provides a comprehensive catalog of proteins expressed by Escherichia coli EC15 and a resource for further studies on antimicrobial resistance and virulence mechanisms in this strain.
Project description:Klebsiella pneumoniae is an important opportunistic pathogen associated with multidrug-resistant infections in humans and animals. In this study, we performed a global proteomic analysis of the isolate JX21CTR26 to characterize its whole-cell protein expression profile. Bacterial cells were cultured under standard laboratory conditions, and total proteins were extracted, digested with trypsin, and analyzed by high-resolution LC–MS/MS. The resulting dataset provides a comprehensive catalog of proteins expressed by K. pneumoniae JX21CTR26 and a resource for further studies on antimicrobial resistance and virulence mechanisms in this strain.
Project description:Cationic antimicrobial peptides (CAPs) are promising novel alternatives to conventional antibacterial agents, but the overlap in resistance mechanisms between small-molecule antibiotics and CAPs is unknown. Does evolution of antibiotic resistance decrease (cross-resistance) or increase (collateral sensitivity) susceptibility to CAPs? We systematically addressed this issue by studying the susceptibilities of a comprehensive set of antibiotic resistant Escherichia coli strains towards 24 antimicrobial peptides. Strikingly, antibiotic resistant bacteria frequently showed collateral sensitivity to CAPs, while cross-resistance was relatively rare. We identified clinically relevant multidrug resistance mutations that simultaneously elevate susceptibility to certain CAPs. Transcriptome and chemogenomic analysis revealed that such mutations frequently alter the lipopolysaccharide composition of the outer cell membrane and thereby increase the killing efficiency of membrane-interacting antimicrobial peptides. Furthermore, we identified CAP-antibiotic combinations that rescue the activity of existing antibiotics and slow down the evolution of resistance to antibiotics. Our work provides a proof of principle for the development of peptide based antibiotic adjuvants that enhance antibiotic action and block evolution of resistance.
Project description:Tuberculosis (TB) is one of the deadliest infectious disorders in the world. To effectively TB manage, an essential step is to gain insight into the lineage of Mycobacterium tuberculosis (MTB) strains and the distribution of drug resistance. Although the Campania region is declared a cluster area for the infection, to contribute to the effort to understand TB evolution and transmission, still poorly known, we have generated a dataset of 159 genomes of MTB strains, from Campania region collected during 2018-2021, obtained from the analysis of whole genome sequence data. The results show that the most frequent MTB lineage is the 4 according for 129 strains (81.11%). Regarding drug resistance, 139 strains (87.4%) were classified as multi susceptible, while the remaining 20 (12.58%) showed drug resistance. Among the drug-resistance strains, 8 were isoniazid-resistant MTB (HR-MTB), 7 were resistant only to one antibiotic (3 were resistant only to ethambutol and 3 isolate to streptomycin while one isolate showed resistance to fluoroquinolones), 4 multidrug-resistant MTB, while only one was classified as pre-extensively drug-resistant MTB (pre-XDR). This dataset expands the existing available knowledge on drug resistance and evolution of MTB, contributing to further TB-related genomics studies to improve the management of TB infection.
Project description:Mycobacteroides abscessus (Mabc) is a rapidly growing nontuberculous mycobacterium that poses a considerable challenge as a multidrug-resistant pathogen causing chronic human infection. Effective therapeutics that enhance protective immune responses to Mabc are urgently needed. This study introduces trans-3,5,4′-trimethoxystilbene (V46), a novel resveratrol analogue with autophagy-activating properties and antimicrobial activity against Mabc infection, including multidrug-resistant strains. Among the resveratrol analogues tested, V46 markedly inhibited the growth of both rough and smooth Mabc strains in murine bone marrow-derived macrophages and in the lungs of infected mice. Additionally, V46 significantly reduced Mabc-induced increases in chemokine and pro inflammatory cytokine levels in macrophages and in vivo during infection. Mechanistic analysis showed that V46 suppressed the activation of the AKT-mammalian target of rapamycin signaling pathway and enhanced AMP-activated protein kinase signaling in Mabc-infected cells. Notably, V46 activated autophagy and nuclear translocation of transcription factor EB, which is crucial for antimicrobial host defenses against Mabc. Furthermore, V46 upregulated genes associated with autophagy and lysosomal biogenesis in Mabc-infected bone marrow-derived macrophages. The combination of V46 and rifabutin exerted a synergistic antimicrobial effect. These findings identify V46 as a candidate host-directed therapeutic for Mabc infection that activates autophagy and lysosomal function via transcription factor EB.
Project description:Antimicrobial peptides (AMPs) are promising alternatives to conventional antibiotics for the treatment of multidrug-resistant (MDR) pathogens; however, their clinical translation is limited by proteolytic degradation.
Project description:Antibiotic use can lead to expansion of multi-drug resistant pathobionts within the gut microbiome that can cause life-threatening infections. Selective alternatives to conventional antibiotics are in dire need. Here, we describe a Klebsiella PhageBank that enables the rapid design of antimicrobial bacteriophage cocktails to treat multi-drug resistant Klebsiella pneumoniae. Using a transposon library in carbapenem-resistant K. pneumoniae, we identified host factors required for phage infection in major Klebsiella phage families. Leveraging the diversity of the PhageBank and experimental evolution strategies, we formulated combinations of phages that minimize the occurrence of phage resistance in vitro. Optimized bacteriophage cocktails selectively suppressed the burden of multi-drug resistant K. pneumoniae in the mouse gut microbiome and drove bacterial populations to lose key virulence factors that act as phage receptors. Further, phage-mediated diversification of bacterial populations in the gut enabled co-evolution of phage variants with higher virulence and a broader host range. Altogether, the Klebsiella PhageBank represents a roadmap for both phage researchers and clinicians to enable phage therapy against a critical multidrug-resistant human pathogen.
Project description:Neisseria gonorrhoeae is a Gram-negative, sexually transmitted pathogen that poses a major public health threat due to rapidly increasing resistance to all recommended antibiotics. Addressing this crisis requires more efficient approaches to antibiotic discovery and the replenishment of the dwindling drug development pipeline. Here, we demonstrate that deep learning models can augment high-throughput screening to identify readily available molecules with narrow-spectrum activity against multidrug-resistant N. gonorrhoeae. We phenotypically tested 38,650 small molecules for growth inhibition and used these data to train a predictive graph neural network (GNN). Benchmarking against alternative architectures, including large language models, revealed that GNNs most effectively identified active, drug-like molecules that were structurally distinct from both the training set and known antibiotics. Applying the model to ~6 million compounds in silico, we prioritized 213 for experimental testing and found that 83 (38%) inhibited N. gonorrhoeae growth. Two compounds were structurally novel, potent against all tested multidrug-resistant strains, displayed favorable selectivity indices, and were rapidly bactericidal with low frequencies of resistance. Multi-omics analyses revealed that these compounds circumvent resistance by targeting previously unexploited pathways in N. gonorrhoeae. Our findings establish a paradigm for deep learning–enabled discovery of selective antibacterial agents and provide a promising path toward addressing the urgent threat of antimicrobial resistance in N. gonorrhoeae.