SummaryTrypanosoma brucei is an extracellular parasite that causes sleeping sickness. In mammalian hosts, trypanosomes are thought to exist in two major niches: early in infection, they populate the blood; later, they breach the blood-brain barrier. Working with a well-established mouse model, we discovered that adipose tissue constitutes a third major reservoir for T. brucei. Parasites from adipose tissue, here termed adipose tissue forms (ATFs), can replicate and were capable of infecting a naive animal. ATFs were transcriptionally distinct from bloodstream forms, and the genes upregulated included putative fatty acid β-oxidation enzymes. Consistent with this, ATFs were able to utilize exogenous myristate and form β-oxidation intermediates, suggesting that ATF parasites can use fatty acids as an external carbon source. These findings identify the adipose tissue as a niche for T. brucei during its mammalian life cycle and could potentially explain the weight loss associated with sleeping sickness.
The evolution of multiple antibiotic resistance is an increasing global problem. Resistance mutations are known to impair fitness, and the evolution of resistance to multiple drugs depends both on their costs individually and on how they interact—epistasis. Information on the level of epistasis between antibiotic resistance mutations is of key importance to understanding epistasis amongst deleterious alleles, a key theoretical question, and to improving public health measures. Here we show that in an antibiotic-free environment the cost of multiple resistance is smaller than expected, a signature of pervasive positive epistasis among alleles that confer resistance to antibiotics. Competition assays reveal that the cost of resistance to a given antibiotic is dependent on the presence of resistance alleles for other antibiotics. Surprisingly we find that a significant fraction of resistant mutations can be beneficial in certain resistant genetic backgrounds, that some double resistances entail no measurable cost, and that some allelic combinations are hotspots for rapid compensation. These results provide additional insight as to why multi-resistant bacteria are so prevalent and reveal an extra layer of complexity on epistatic patterns previously unrecognized, since it is hidden in genome-wide studies of genetic interactions using gene knockouts.
Trypanosoma brucei gambiense causes human African trypanosomiasis (HAT). Between 1990 and 2015, almost 440 000 cases were reported. Large-scale screening of populations at risk, drug donations, and efforts by national and international stakeholders have brought the epidemic under control with <2200 cases in 2016. The World Health Organization (WHO) has set the goals of gambiense-HAT elimination as a public health problem for 2020, and of interruption of transmission to humans for 2030. Latent human infections and possible animal reservoirs may challenge these goals. It remains largely unknown whether, and to what extend, they have an impact on gambiense-HAT transmission. We argue that a better understanding of the contribution of human and putative animal reservoirs to gambiense-HAT epidemiology is mandatory to inform elimination strategies.
Knowledge of the mutational parameters that affect the evolution of organisms is of key importance in understanding the evolution of several characteristics of many natural populations, including recombination and mutation rates. In this study, we estimated the rate and mean effect of spontaneous mutations that affect fitness in a mutator strain of Escherichia coli and review some of the estimation methods associated with mutation accumulation (MA) experiments. We performed an MA experiment where we followed the evolution of 50 independent mutator lines that were subjected to repeated bottlenecks of a single individual for approximately 1150 generations. From the decline in mean fitness and the increase in variance between lines, we estimated a minimum mutation rate to deleterious mutations of 0.005 (+0.001 with 95% confidence) and a maximum mean fitness effect per deleterious mutation of 0.03 (+0.01 with 95% confidence). We also show that any beneficial mutations that occur during the MA experiment have a small effect on the estimate of the rate and effect of deleterious mutations, unless their rate is extremely large. Extrapolating our results to the wild-type mutation rate, we find that our estimate of the mutational effects is slightly larger and the inferred deleterious mutation rate slightly lower than previous estimates obtained for non-mutator E. coli.
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