bioRxiv Science⌕ Search

bioRxiv · 10.1101/2021.05.01.442230

Evaluation of Antibiotic Tolerance in Pseudomonas aeruginosa for Aminoglycosides and its Prediction of Resistance Development Through In-silico Transcriptomic Analysis

Abstract

Pseudomonas aeruginosa causes chronic infections like cystic fibrosis, endocarditis, bacteremia and sepsis, which are life-threatening and difficult to treat. The lack of antibiotic response in P. aeruginosa is due to adaptive resistance mechanism, which prevents the entry of antibiotics into cytosol of the cell to achieve tolerance. Among different groups of antibiotics, aminoglycosides are used as a parental antibiotic for treatment of P. aeruginosa. This study aims to determine the kinetics of antibiotic tolerance and gene expression changes in P. aeruginosa exposed to amikacin, gentamicin, and tobramycin. These antibiotics were exposed to P. aeruginosa at their MICs and the experimental setup was monitored till 72 hours, followed by the measurement of optical density in the interval of every 12 hours. The growth of P. aeruginosa in MICs of antibiotics represents the kinetics of antibiotic tolerance in amikacin, gentamicin, and tobramycin. Transcriptomic profile of antibiotic exposed P. aeruginosa PA14 was taken from Gene Expression Omnibus (GEO), NCBI as microarray datasets. The gene expressions of two datasets were compared by test versus control. Tobramycin exposed P. aeruginosa failed to develop tolerance in MICs 0.5{micro}g/mL, 1{micro}g/mL and 1.5{micro}g/mL. Whereas amikacin and gentamicin treated P. aeruginosa developed tolerance in MICs. This depicts the superior in vitro response of tobramycin over the gentamicin and amikacin. Further, in silico transcriptomic analysis of tobramycin treated P. aeruginosa resulted in low expression of 16s rRNA Methyltransferase E, B & L, alginate biosynthesis genes and several proteins of Type 2 Secretory System (T2SS) and Type 3 Secretory System (T3SS). The Differentially Expressed Genes (DEGs) of alginate biosynthesis, and RNA Methyltransferases suggests increased antibiotic response and low probability of developing resistance. The use of tobramycin as a parental antibiotic with its synergistic combination might combat P. aeruginosa with increased response.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Kumar B, A., Thankappan, B., Jayaraman, A., Gupta, A.. 2021-05-01. Evaluation of Antibiotic Tolerance in Pseudomonas aeruginosa for Aminoglycosides and its Prediction of Resistance Development Through In-silico Transcriptomic Analysis. https://doi.org/10.1101/2021.05.01.442230

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

A population-scale landscape of the subgingival microbiome reveals divergent routes to periodontal dysbiosis

Periodontitis is an archetypical mucosal inflammatory disease in which microbiome dysbiosis at the tooth-epithelial interface interacts with host genetic and behavioral risk factors to drive immune-mediated tissue destruction. Although subgingival microbiome compositional shifts are thought to parallel disease severity, microbiome variation at the population-level and its relationship to periodontal clinical phenotypes and disease-modifying factors remain poorly defined. Here, we use unsupervised manifold learning to map the compositional landscape of the subgingival microbiome in 1,355 adults spanning periodontal health to severe periodontitis. We identified eight latent microbiome states organized along a branching continuum from eubiosis to dysbiosis. An intermediate microbial configuration marked ecological destabilization and bifurcation into two distinct periodontitis-associated dysbiotic trajectories, distinguished by links to gingival inflammation and smoking. Although the microbiome trajectories broadly tracked periodontal destruction, a minority of individuals showed discordant microbiome-clinical phenotypes, with some individuals with periodontitis retaining otherwise eubiotic microbiomes enriched for low-abundance pathobionts, while some cases of health or mild disease had highly dysbiotic communities, suggesting distinct host susceptibility. Together, these findings define a population-scale ecological landscape of the subgingival microbiome, reveal divergent trajectories to periodontal dysbiosis, and highlight heterogeneity in the relationship between microbial community structure and clinical disease expression.

microbiology↗

Beta-lactam enhancement against methicillin-resistant Staphylococcus aureus by cell wall blockade is autolysis-dependent: a butyrolactone derivative as case in point

Methicillin-resistant Staphylococcus aureus (MRSA) is non-susceptible to beta-lactams. Blockade of cell wall biosynthesis is a potential target for beta-lactam enhancement but requires further investigation. A butyrolactone derivative enhanced beta-lactams against MRSA strains by reducing the availability of D-Ala-D-Ala. Unlike D-cycloserine, it did not inhibit D-Ala-D-Ala ligase (Ddl). Nor did it show an additive or synergistic effect when combined with cycloserine, indicating a unique mechanism for blocking cell wall precursor production that does not involve the traditional Lipid II pathway. Notably, beta-lactam potentiation by our chemical or D-cycloserine was highly dependent on the intrinsic autolytic ability of the tested MRSA strains. Strains that resisted lysis upon Triton X-100 exposure showed a minimal increase in beta-lactam susceptibility, whereas highly autolytic strains showed significant changes in their beta-lactam MICs. We have thus identified autolytic ability as the Achilles Heel in the strategy of targeting cell wall biosynthesis for beta-lactam potentiation.

microbiology↗

Rapid and largely reversible shifts in the canine fecal metabolome during dietary change

Diet can rapidly change the fecal metabolome, but less is known about recovery after the original diet is restored. We used untargeted UPLC-MS metabolomics to analyze 72 fecal samples from nine Pumi dogs during an owner-managed switch from dry food to raw food and back to dry food. Diet phase accounted for a large proportion of variation in both ionization modes. More than 13,000 LC-MS features changed at the first sampling point after the switch to raw food, with a similarly large response after return to dry food. Among features significant in both comparisons, more than 99% changed in opposite directions. At the final sampling point, no positive-mode (ESI+) features and only 13 negative-mode (ESI-) features differed from the second dry-food baseline under the same threshold. BARF-associated patterns persisted in analyses excluding individual dogs and in pedigree-adjusted candidate models, although individual feature effects depended on normalization. Putative metabolites from several biochemical classes differed in their response and recovery. The fecal metabolome therefore changed rapidly and returned largely toward baseline, with differences among dogs.

microbiology↗