Studying genetic and enzymatic constraints driving evolution of antibiotic resistance

World is heading towards a post-antibiotic era due to emergence of antibiotic resistance. Several fatal infectious diseases caused by antibiotic resistant bacteria cannot be treated anymore using the existing antibiotic surplus. Novel antibiotics or novel strategies to use antibiotic more efficiently are therefore crucial to combat against resistance. However, both of these approaches require a clear understanding of antibiotic resistance at molecular and genetic levels. Here in this study, we studied evolutionary dynamics of trimethoprim resistance under dynamically sustained drug selection. Using a custom made continuous culture device that we call the Morbidostat; we evolved drug sensitive Escherichia coli cells against increasing levels of trimethoprim adapting strong or mild dilution rates. First, using Illumina whole genome sequencing and Sanger sequencing, we identified trimethoprim resistance conferring mutations in dihydrofolate reductase (folA) gene and the order that these mutations appear in the population. Our results suggest that clonal interference between different genotypes is common and longer under strong dilution where trimethoprim stress is applied in shorter and steeper pulses. Second, we cloned and purified dihydrofolate reductase (DHFR) enzymes with single mutations and carried out biochemical assays to quantify mutant enzymes’ enzymatic activities. Our preliminary results showed that DHFR mutants have slightly worse substrate affinity (higher km values) but up to ~20 fold elevated catalysis rate (kcat/km) compared to their wild type ancestor. We conclude that trimethoprim-resistance-conferring DHFR mutations decrease affinity to both enzyme’s substrate and competing drug molecules, yet enzymatic activity, which is essential for folic acid synthesis, is still adequately efficient to maintain bacterial fitness

High-order epistasis in catalytic power of dihydrofolate reductase gives rise to a rugged fitness landscape in the presence of trimethoprim selection

Evolutionary fitness landscapes of several antibiotic target proteins have been comprehensively mapped showing strong high-order epistasis between mutations, but understanding these effects at the biochemical and structural levels remained open. Here, we carried out an extensive experimental and computational study to quantitatively understand the evolutionary dynamics of Escherichia coli dihydrofolate reductase (DHFR) enzyme in the presence of trimethopriminduced selection. To facilitate this, we developed a new in vitro assay for rapidly characterizing DHFR steady-state kinetics. Biochemical and structural characterization of resistance-conferring mutations targeting a total of ten residues spanning the substrate binding pocket of DHFR revealed distinct changes in the catalytic efficiencies of mutated DHFR enzymes. Next, we measured biochemical parameters (Km, Ki, and kcat) for a mutant library carrying all possible combinations of six resistance-conferring DHFR mutations and quantified epistatic interactions between them. We found that the high-order epistasis in catalytic power of DHFR (kcat and Km) creates a rugged fitness landscape under trimethoprim selection. Taken together, our data provide a concrete illustration of how epistatic coupling at the level of biochemical parameters can give rise to complex fitness landscapes, and suggest new strategies for developing mutant specific inhibitors

Strength of selection pressure is an important parameter contributing to the complexity of antibiotic resistance evolution

Revealing the genetic changes responsible for antibiotic resistance can be critical for developing novel antibiotic therapies. However, systematic studies correlating genotype to phenotype in the context of antibiotic resistance have been missing. In order to fill in this gap, we evolved 88 isogenic Escherichia coli populations against 22 antibiotics for 3 weeks. For every drug, two populations were evolved under strong selection and two populations were evolved under mild selection. By quantifying evolved populations' resistances against all 22 drugs, we constructed two separate cross-resistance networks for strongly and mildly selected populations. Subsequently, we sequenced representative colonies isolated from evolved populations for revealing the genetic basis for novel phenotypes. Bacterial populations that evolved resistance against antibiotics under strong selection acquired high levels of cross-resistance against several antibiotics, whereas other bacterial populations evolved under milder selection acquired relatively weaker cross-resistance. In addition, we found that strongly selected strains against aminoglycosides became more susceptible to five other drug classes compared with their wild-type ancestor as a result of a point mutation on TrkH, an ion transporter protein. Our findings suggest that selection strength is an important parameter contributing to the complexity of antibiotic resistance problem and use of high doses of antibiotics to clear infections has the potential to promote increase of cross-resistance in clinics

Rapid ultrasensitive detection platform for antimicrobial susceptibility testing.

Rapid detection and phenotyping of pathogenic microbes is critical for administration of effective antibiotic therapies and for impeding the spread of antibiotic resistance. Here, we present a novel platform, rapid ultrasensitive detector (RUSD), that utilizes the high reflectance coefficient at high incidence angles when light travels from low- to high-refractive-index media. RUSD leverages a principle that does not require complex manufacturing, labeling, or processing steps. Utilizing RUSD, we can detect extremely low cell densities (optical density [OD] ≥ 5 × 10-7) that correspond to approximately 20 bacterial cells or a single fungal cell in the detection volume, which is nearly 4 orders of magnitude more sensitive than standard OD methods. RUSD can measure minimum inhibitory concentrations (MICs) of commonly used antibiotics against gram-negative and gram-positive bacteria, including Staphylococcus aureus, Pseudomonas aeruginosa, and Escherichia coli, within 2 to 4 h. Here, we demonstrate that antibiotic susceptibility tests for several pathogens can rapidly be performed with RUSD using both small inoculum sizes (500 cells/mL) and larger inoculum sizes (5 × 105 cells/mL) used in standard antibiotic susceptibility tests. We anticipate that the RUSD system will be particularly useful for the cases in which antibiotic susceptibility tests have to be done with a limited number of bacterial cells that are available. Its compatibility with standard antibiotic susceptibility tests, simplicity, and low cost can make RUSD a viable and rapidly deployed diagnostic tool

Increased substrate affinity in the escherichia coli L28R dihydrofolate reductase mutant causes trimethoprim resistance

Dihydrofolate reductase (DHFR) is a ubiquitous enzyme with an essential role in cell metabolism. DHFR catalyzes the reduction of dihydrofolate to tetrahydrofolate, which is a precursor for purine and thymidylate synthesis. Several DHFR targeting antifolate drugs including trimethoprim, a competitive antibacterial inhibitor, have therefore been developed and are clinically used. Evolution of resistance against antifolates is a common public health problem rendering these drugs ineffective. To combat the resistance problem, it is important to understand resistance-conferring changes in the DHFR structure and accordingly develop alternative strategies. Here, we structurally and dynamically characterize Escherichia coli DHFR in its wild type (WT) and trimethoprim resistant L28R mutant forms in the presence of the substrate and its inhibitor trimethoprim. We use molecular dynamics simulations to determine the conformational space, loop dynamics and hydrogen bond distributions at the active site of DHFR for the WT and the L28R mutant. We also report their experimental kcat, Km, and Ki values, accompanied by isothermal titration calorimetry measurements of DHFR that distinguish enthalpic and entropic contributions to trimethoprim binding. Although mutations that confer resistance to competitive inhibitors typically make enzymes more promiscuous and decrease affinity to both the substrate and the inhibitor, strikingly, we find that the L28R mutant has a unique resistance mechanism. While the binding affinity differences between the WT and the mutant for the inhibitor and the substrate are small, the newly formed extra hydrogen bonds with the aminobenzoyl glutamate tail of DHF in the L28R mutant leads to increased barriers for the dissociation of the substrate and the product. Therefore, the L28R mutant indirectly gains resistance by enjoying prolonged binding times in the enzyme-substrate complex. While this also leads to slower product release and decreases the catalytic rate of the L28R mutant, the overall effect is the maintenance of a sufficient product formation rate. Finally, the experimental and computational analyses together reveal the changes that occur in the energetic landscape of DHFR upon the resistance-conferring L28R mutation. We show that the negative entropy associated with the binding of trimethoprim in WT DHFR is due to water organization at the binding interface. Our study lays the framework to study structural changes in other trimethoprim resistant DHFR mutants

Fourier transform infrared spectroscopy as a novel approach for analyzing the biochemical effects of anionic surfactants on a surfactant-degrading arcobacter butzleri strain

Anionic surfactant-biodegrading capability of an Arcobacter butzleri strain was analyzed under aerobic conditions. The A. butzleri isolate displayed efficient surfactant-biodegrading capacity for sodium dodecyl sulfate (SDS) at concentrations of up to 100 mg/L in 6 days, corresponding to 99.0% removal efficiency. Fourier transform infrared spectroscopy was applied to observe the effects of varying concentrations of SDS on the biochemistry of bacterial cells. Results suggest that protein secondary structures were altered in bacterial cells at sufficiently high SDS concentrations, concurrent with SDS biodegradation

Sequence-Specific Targeting of Bacterial Resistance Genes Increases Antibiotic Efficacy

The lack of effective and well-tolerated therapies against antibiotic-resistant bacteria is a global public health problem leading to prolonged treatment and increased mortality. To improve the efficacy of existing antibiotic compounds, we introduce a new method for strategically inducing antibiotic hypersensitivity in pathogenic bacteria. Following the systematic verification that the AcrAB-TolC efflux system is one of the major determinants of the intrinsic antibiotic resistance levels in Escherichia coli, we have developed a short antisense oligomer designed to inhibit the expression of acrA and increase antibiotic susceptibility in E. coli. By employing this strategy, we can inhibit E. coli growth using 2- to 40-fold lower antibiotic doses, depending on the antibiotic compound utilized. The sensitizing effect of the antisense oligomer is highly specific to the targeted gene’s sequence, which is conserved in several bacterial genera, and the oligomer does not have any detectable toxicity against human cells. Finally, we demonstrate that antisense oligomers improve the efficacy of antibiotic combinations, allowing the combined use of even antagonistic antibiotic pairs that are typically not favored due to their reduced activities

Targeting resistance genes with <i>acrA</i>-PPMO increases efficacy of antibiotic combinations and even makes the use of antagonistic antibiotic pairs possible.

<p>(A) Conceptual representation of the possible effects of efflux inhibition on the use of antibiotics pairs. Blue and black lines represent the MIC lines in two-dimensional gradients of drug pairs for bacteria with and without <i>acrA</i>-PPMO, respectively. The left panel represents an increase in susceptibility to antibiotic B, the middle panel represents an increase to antibiotic A, and the right panel represents an increase to both antibiotics. (B) MIC lines determined in two-dimensional gradients of (left) trimethoprim-sulfamethoxazole and (right) trimethoprim-piperacillin/tazobactam for wild type <i>E</i>. <i>coli</i> (black line), with 10 μM <i>acrA</i>-PPMO (blue line), or the <i>acrA</i> deletion mutant (cyan line). (C) Bar graphs demonstrating the efficacy of antibiotic combinations shown in (B). Area under the MIC curves in (B) are significantly reduced relative to the wild type <i>E</i>. <i>coli</i> (bars with black diagonal lines) for both antibiotic combinations when 10 μM <i>acrA</i>-PPMO (blue bars) is used or <i>acrA</i> (cyan bars) is physically deleted. All measurements were done in triplicate, and <i>p</i>-values for significance were calculated with Student’s <i>t</i>-test.</p