Changes in the Carbon Metabolism of Escherichia coli During the Evolution of Doxycycline Resistance

Abstract

Despite our continuous improvement in understanding the evolution of antibiotic resistance, the changes in the carbon metabolism during the evolution of antibiotic resistance remains unclear. To investigate the evolution of antibiotic resistance and the changes in carbon metabolism under antibiotic pressure, Escherichia coli K-12 was evolved for 38 passages under a concentration gradient of doxycycline (DOX). The 0th-passage sensitive strain W0, the 20th-passage moderately resistant strain M20, and the 38th-passage highly resistant strain E38 were selected for the determination of biofilm formation, colony area, and carbon metabolism levels, as well as genome and transcriptome sequencing. The MIC of DOX with E. coli significantly increased from 4 to 96 μg/ml, and the IC50 increased from 2.18 ± 0.08 to 64.79 ± 0.75 μg/ml after 38 passages of domestication. Compared with the sensitive strain W0, the biofilm formation amount of the resistant strains M20 and E38 was significantly increased (p < 0.05). Single-nucleotide polymorphisms (SNPs) were distributed in antibiotic resistance-related genes such as ribosome targets, cell membranes, and multiple efflux pumps. In addition, there were no mutated genes related to carbon metabolism. However, the genes involved in the biosynthesis of secondary metabolites and carbon metabolism pathway were downregulated, showing a significant decrease in the metabolic intensity of 23 carbon sources (p < 0.05). The results presented here show that there may be a correlation between the evolution of E. coli DOX resistance and the decrease of carbon metabolism, and the mechanism was worthy of further research, providing a theoretical basis for the prevention and control of microbial resistance.

Proteomic and Transcriptomic Analyses Indicate Reduced Biofilm-Forming Abilities in Cefiderocol-Resistant Klebsiella pneumoniae

“…Carbon source utilization of K. pneumoniae was determined using the Biolog-ECO technique described by Wen et al (2021) . Metabolism of 31 carbon sources was determined using the method described by Yang et al (2019) . Each WT or cefiderocol-treated strain was incubated in LB broth at 37°C and 220 rpm for 12 h, and washed with the same volume of PBS for 3 times.…”

Gut Microbial Profiles in Nereis succinea and Their Contribution to the Degradation of Organic Pollutants

“…For the CLPP tests, the gut bacterial suspensions (OD 600 = 0.2) were added to the EcoPlate (120 μL in each well), and the plate was incubated at 25 °C in the darkness for 7 d. The OD readings at 590 and 750 nm (OD 590 and OD 750 ) were recorded for each well every 24 h in the 7-d time course. OD 590 was used to represent the color and turbidity of the well, while OD 750 represented the turbidity only. , For quantitatively characterizing the CLPP, single well color development (SWCD), average well color development (AWCD), Shannon’s diversity index ( H ′), evenness ( E ), and Simpson’s diversity index ( D ) were calculated according to the following equations where n equals 31, which is the total number of substrates. C i and C 0 are the differentials of the OD readings at 590 and 750 nm (i.e., OD 590 –OD 750 ) of the i th well and the control, respectively …”

“…OD 590 was used to represent the color and turbidity of the well, while OD 750 represented the turbidity only. 31,32 For quantitatively characterizing the CLPP, single well color development (SWCD), average well color development (AWCD), Shannon's diversity index (H′), evenness (E), and Simpson's diversity index (D) were calculated according to the following equations…”

Genome-Scale Metabolic Models and Machine Learning Reveal Genetic Determinants of Antibiotic Resistance in Escherichia coli and Unravel the Underlying Metabolic Adaptation Mechanisms

“…The opportunistic pathogen Escherichia coli plays a major role in the antimicrobial resistance (AMR) global health crisis. First, the ability of E. coli to acquire resistance via single nucleotide polymorphisms (SNPs) in its existing genome ( 4 – 7 ) and via acquisition of resistance genes through horizontal gene transfer (HGT) from surrounding species ( 8 – 10 ) has resulted in increased levels of resistance to many antibiotic classes, including penicillins, carbapenems, cephalosporins, fluoroquinolones, aminoglycosides, and tetracyclines ( 11 – 15 ). Second, the ease of its transmission from humans and environmental sources has resulted in alarming numbers of multidrug-resistant E. coli strains being reported worldwide ( 16 , 17 ).…”