Trichomonas vaginalis extracellular vesicles up-regulate and directly transfer adherence factors promoting host cell colonization.

Trichomonas vaginalis, a common sexually transmitted parasite that colonizes the human urogenital tract, secretes extracellular vesicles (TvEVs) that are taken up by human cells and are speculated to be taken up by parasites as well. While the crosstalk between TvEVs and human cells has led to insight into host:parasite interactions, roles for TvEVs in infection have largely been one-sided, with little known about the effect of TvEV uptake by T. vaginalis. Approximately 11% of infections are found to be coinfections of multiple T. vaginalis strains. Clinical isolates often differ in their adherence to and cytolysis of host cells, underscoring the importance of understanding the effects of TvEV uptake within the parasite population. To address this question, our lab tested the ability of a less adherent strain of T. vaginalis, G3, to take up fluorescently labeled TvEVs derived from both itself (G3-EVs) and TvEVs from a more adherent strain of the parasite (B7RC2-EVs). Here, we showed that TvEVs generated from the more adherent strain are internalized more efficiently compared to the less adherent strain. Additionally, preincubation of G3 parasites with B7RC2-EVs increases parasite aggregation and adherence to host cells. Transcriptomics revealed that TvEVs up-regulate expression of predicted parasite membrane proteins and identified an adherence factor, heteropolysaccharide binding protein (HPB2). Finally, using comparative proteomics and superresolution microscopy, we demonstrated direct transfer of an adherence factor, cadherin-like protein, from TvEVs to the recipient parasite's surface. This work identifies TvEVs as a mediator of parasite:parasite communication that may impact pathogenesis during mixed infections.

Adaptive Processes Change as Multiple Functions Evolve.

Epistasis influences the gene-environment interactions that shape bacterial fitness through antibiotic exposure, which can ultimately affect the availability of certain resistance phenotypes to bacteria. The substitutions present within blaTEM-50 confer both cephalosporin and ß-lactamase inhibitor resistance. We wanted to compare the evolution of blaTEM-50 with that of another variant, blaTEM-85, which differs in that blaTEM-85 contains only substitutions that contribute to cephalosporin resistance. Differences between the landscapes and epistatic interactions of these TEM variants are important for understanding their separate evolutionary responses to antibiotics. We hypothesized the substitutions within blaTEM-50 would result in more epistatic interactions than for blaTEM-85 As expected, we found more epistatic interactions between the substitutions present in blaTEM-50 than in blaTEM-85 Our results suggest that selection from many cephalosporins is required to achieve the full potential resistance to cephalosporins but that a single ß-lactam and inhibitor combination will drive evolution of the full potential resistance phenotype. Surprisingly, we also found significantly positive increases in growth rates as antibiotic concentration increased for some of the strains expressing blaTEM-85 precursor genotypes but not the blaTEM-50 variants. This result further suggests that additive interactions more effectively optimize phenotypes than epistatic interactions, which means that exposure to numerous cephalosporins actually increases the ability of a TEM enzyme to confer resistance to any single cephalosporin.

Adaptive Landscapes of Resistance Genes Change as Antibiotic Concentrations Change.

Most studies on the evolution of antibiotic resistance are focused on selection for resistance at lethal antibiotic concentrations, which has allowed the detection of mutant strains that show strong phenotypic traits. However, solely focusing on lethal concentrations of antibiotics narrowly limits our perspective of antibiotic resistance evolution. New high-resolution competition assays have shown that resistant bacteria are selected at relatively low concentrations of antibiotics. This finding is important because sublethal concentrations of antibiotics are found widely in patients undergoing antibiotic therapies, and in nonmedical conditions such as wastewater treatment plants, and food and water used in agriculture and farming. To understand the impacts of sublethal concentrations on selection, we measured 30 adaptive landscapes for a set of TEM ß-lactamases containing all combinations of the four amino acid substitutions that exist in TEM-50 for 15 ß-lactam antibiotics at multiple concentrations. We found that there are many evolutionary pathways within this collection of landscapes that lead to nearly every TEM-genotype that we studied. While it is known that the pathways change depending on the type of ß-lactam, this study demonstrates that the landscapes including fitness optima also change dramatically as the concentrations of antibiotics change. Based on these results we conclude that the presence of multiple concentrations of ß-lactams in an environment result in many different adaptive landscapes through which pathways to nearly every genotype are available. Ultimately this may increase the diversity of genotypes in microbial populations.

Rational design of antibiotic treatment plans: a treatment strategy for managing evolution and reversing resistance.

The development of reliable methods for restoring susceptibility after antibiotic resistance arises has proven elusive. A greater understanding of the relationship between antibiotic administration and the evolution of resistance is key to overcoming this challenge. Here we present a data-driven mathematical approach for developing antibiotic treatment plans that can reverse the evolution of antibiotic resistance determinants. We have generated adaptive landscapes for 16 genotypes of the TEM ß-lactamase that vary from the wild type genotype "TEM-1" through all combinations of four amino acid substitutions. We determined the growth rate of each genotype when treated with each of 15 ß-lactam antibiotics. By using growth rates as a measure of fitness, we computed the probability of each amino acid substitution in each ß-lactam treatment using two different models named the Correlated Probability Model (CPM) and the Equal Probability Model (EPM). We then performed an exhaustive search through the 15 treatments for substitution paths leading from each of the 16 genotypes back to the wild type TEM-1. We identified optimized treatment paths that returned the highest probabilities of selecting for reversions of amino acid substitutions and returning TEM to the wild type state. For the CPM model, the optimized probabilities ranged between 0.6 and 1.0. For the EPM model, the optimized probabilities ranged between 0.38 and 1.0. For cyclical CPM treatment plans in which the starting and ending genotype was the wild type, the probabilities were between 0.62 and 0.7. Overall this study shows that there is promise for reversing the evolution of resistance through antibiotic treatment plans.