Project description:Acinetobacter baumannii is a nosocomial Gram-negative pathogen that often displays multidrug-resistance due to its robust outer membrane and its ability to acquire and retain extracellular DNA. Moreover, it can survive for prolonged durations on surfaces and is resistant to desiccation. Discovering new antibiotics against A. baumannii has proven challenging through conventional screening approaches. Fortunately, machine learning methods allow for the rapid exploration of chemical space, increasing the probability of discovering new chemical matter with antibacterial activity against this burdensome pathogen. Here, we screened ~7,500 molecules for those that inhibited the growth of A. baumannii in vitro. We trained a deep neural network with this growth inhibition dataset and performed predictions on the Drug Repurposing Hub for structurally novel molecules with activity against A. baumannii. Through this approach, we discovered abaucin, an antibacterial compound with narrow-spectrum activity against A. baumannii, which could overcome intrinsic and acquired resistance mechanisms in clinical isolates. Further investigations revealed that abaucin perturbs lipoprotein trafficking through a mechanism involving LolE, a functionally conserved protein that contributes to shuttling lipoproteins from the inner membrane to the outer membrane. Moreover, abaucin was able to control an A. baumannii infection in a murine wound model. Together, this work highlights the utility of machine learning in discovering new antibiotics and describes a promising lead with narrow-spectrum activity against a challenging Gram-negative pathogen.
Project description:Objectives: Colistin remains a last-line treatment for multidrug-resistant Acinetobacter baumannii and combined use of colistin and carbapenems has shown synergistic effects against multidrug-resistant strains. In order to understand the bacterial responses to these antibiotics we analysed the transcriptome of A. baumannii following exposure to each.
Project description:Using Nanopore sequencing, our study has revealed a close correlation between genomic methylation levels and antibiotic resistance rates in Acinetobacter Baumannii. Specifically, the combined genome-wide DNA methylome and transcriptome analysis revealed the first epigenetic-based antibiotic-resistance mechanism in A. baumannii. Our findings suggest that the precise location of methylation sites along the chromosome could provide new diagnostic markers and drug targets to improve the management of multidrug-resistant A. baumannii infections.
Project description:Cefiderocol (CFDC) is a novel chlorocatechol-substituted siderophore approved to treat complicated urinary tract infections and for hospital-acquired and ventilator-acquired pneumonia. In previous work, human fluids, were shown to increase the minimum inhibitory concentration (MICs) of Acinetobacter baumannii against CFDC and reduce the expression of genes related to iron uptake systems, which could explain the need for higher concentrations of CFDC to exert inhibitory action. Herein, we analyzed the impact of human urine (HU), which contains low albumin concentrations, on the expression of iron-uptake related genes and MIC values of two carbapenem-resistant A. baumannii. Levels of resistance to CFDC were not modified by HU in strain AMA40 but were reduced in the case of strain AB5075. Testing other carbapenem-resistant A. baumannii isolates showed that the CFDC MICs were unmodified or reduced in the presence of HU. The expression of piuA, pirA, bauA, and bfnH determined by qRT-PCR was enhanced in both strains when HU was present in the culture medium. All four tested genes are involved in recognizing ferric siderophore complexes or internalization into the cell’s cytosol. In contrast, the effect of HU on genes associated with resistance to β-lactams, antibiotics commonly used to treat urinary tract infections caused by A. baumannii, was variable; the transcriptional analysis of pbp1, pbp3, blaOXA-51-like, blaADC, and blaNDM-1 showed significant variation. In summary, HU, probably due to the albumin and free iron content, does not adversely impact or slightly improves the activity of CFDC when tested against A. baumannii in urine in contrast to other human bodily fluids.
Project description:RNA sequencing transcriptomics was performed on a highly multidrug resistant A. baumannii strain belonging to international clone I, AB5075_UW and a transposon insertion inactivated mutant of ABUW_1016 (cbl), which encodes a LysR-type transcriptional regulator.Transcriptomics suggests that Cbl controls expression of the genes involved in acquisition and reduction of various sulfur sources in A. baumannii.
2022-12-15 | GSE183337 | GEO
Project description:Study Network of Acinetobacter as a Carbapenem-Resistant Pathogen (SNAP)
| PRJNA667024 | ENA
Project description:Study Network of Acinetobacter as a Carbapenem-Resistant Pathogen (SNAP)
Project description:Acinetobacter baumannii is an emerging nosocomial pathogen that causes severe infections such as pneumonia or blood stream infections. As the incidence of multidrug-resistant A. baumannii infections in intensive care units increases, the pathogen is considered of greater clinical concern. Little is known about the molecular interaction of A. baumannii with its host yet. In order to study the host cell response upon A. baumannii infection, a complexome analysis was performed. For this, we identified a virulent ( A. baumannii 2778) and a non virulent (A. baumannii 1372) clinical isolate of genetic similarity > 95 % (both isolates from IC 2 harboring OXA 23). HUVECs were infected with each strain and enriched mitochondrial fraction was used for complexome profiling. Complexome analysis identified dramatic reduction of mitochondrial protein complexes in the strain of greater virulence.
