Evolutionary rescue by compensatory mutations is constrained by genomic and environmental backgrounds

Since deleterious mutations may be rescued by secondary mutations during evolution, compensatory evolution could identify genetic solutions leading to therapeutic targets. Here, we tested this hypothesis and examined whether these solutions would be universal or would need to be adapted to one's genetic and environmental makeups. We performed experimental evolutionary rescue in a yeast disease model for the Wiskott–Aldrich syndrome in two genetic backgrounds and carbon sources. We found that multiple aspects of the evolutionary rescue outcome depend on the genotype, the environment, or a combination thereof. Specifically, the compensatory mutation rate and type, the molecular rescue mechanism, the genetic target, and the associated fitness cost varied across contexts. The course of compensatory evolution is therefore highly contingent on the initial conditions in which the deleterious mutation occurs. In addition, these results reveal biologically favored therapeutic targets for the Wiskott–Aldrich syndrome, including the target of an unrelated clinically approved drug. Our results experimentally illustrate the importance of epistasis and environmental evolutionary constraints that shape the adaptive landscape and evolutionary rate of molecular networks.     

Pipeliner: software to evaluate the performance of bioinformatics pipelines for next‐generation resequencing

The choice of technology and bioinformatics approach is critical in obtaining accurate and reliable information from next‐generation sequencing (NGS) experiments. An increasing number of software and methodological guidelines are being published, but deciding upon which approach and experimental design to use can depend on the particularities of the species and on the aims of the study. This leaves researchers unable to produce informed decisions on these central questions. To address these issues, we developed pipeliner – a tool to evaluate, by simulation, the performance of NGS pipelines in resequencing studies. Pipeliner provides a graphical interface allowing the users to write and test their own bioinformatics pipelines with publicly available or custom software. It computes a number of statistics summarizing the performance in SNP calling, including the recovery, sensitivity and false discovery rate for heterozygous and homozygous SNP genotypes. Pipeliner can be used to answer many practical questions, for example, for a limited amount of NGS effort, how many more reliable SNPs can be detected by doubling coverage and halving sample size or what is the false discovery rate provided by different SNP calling algorithms and options. Pipeliner thus allows researchers to carefully plan their study's sampling design and compare the suitability of alternative bioinformatics approaches for their specific study systems. Pipeliner is written in C++ and is freely available from http://github.com/brunonevado/Pipeliner .     

Julius Sachs (1832–1897) and the Unity of Life

In 1865, the German botanist Julius Sachs published a seminal monograph entitled Experimental-Physiologie der Pflanzen (Experimental Physiology of Plants) and hence became the founder of a new scientific discipline that originated 150 y ago. Here, we outline the significance of the achievements of Sachs. In addition, we document, with reference to his Vorlesungen über Pflanzen-Physiologie (Lectures on the Physiology of Plants, 1882), that Sachs was one of the first experimentalists who proposed the functional unity of all organisms alive today (humans, animals, plants and other “vegetable” organisms, such as algae, cyanophyceae, fungi, myxomycetes, and bacteria).     

Place and Response Learning in the Open-field Tower Maze

This protocol describes how the Open-field Tower Maze (OFTM) paradigm is used to study spatial learning in rodents. This maze is especially useful for examining how rats learn to use a place- or response-learning to successfully navigate in an open-field arena. Additionally, this protocol describes how the OFTM differs from other behavioral maze paradigms that are commonly used to study spatial learning in rodents. The OFTM described in this article was adapted from the one previously described by Cole, Clipperton, and Walt (2007). Specifically, the OFTM was created to test spatial learning in rodents without the experimenter having to consider how “stress” might play a role as a confounding variable. Experiments have shown that stress-alone can significantly affect cognitive function¹. The representative results section contains data from an experiment that used the OFTM to examine the effects of estradiol treatment on place- and response-learning in adult female Sprague Dawley rats². Future studies will be designed to examine the role of the hippocampus and striatum in place- and response-learning in the OFTM.     

Adaptive laboratory evolution of microbial co‐cultures for improved metabolite secretion

Adaptive laboratory evolution has proven highly effective for obtaining microorganisms with enhanced capabilities. Yet, this method is inherently restricted to the traits that are positively linked to cell fitness, such as nutrient utilization. Here, we introduce coevolution of obligatory mutualistic communities for improving secretion of fitness‐costly metabolites through natural selection. In this strategy, metabolic cross‐feeding connects secretion of the target metabolite, despite its cost to the secretor, to the survival and proliferation of the entire community. We thus co‐evolved wild‐type lactic acid bacteria and engineered auxotrophic Saccharomyces cerevisiae in a synthetic growth medium leading to bacterial isolates with enhanced secretion of two B‐group vitamins, viz., riboflavin and folate. The increased production was specific to the targeted vitamin, and evident also in milk, a more complex nutrient environment that naturally contains vitamins. Genomic, proteomic and metabolomic analyses of the evolved lactic acid bacteria, in combination with flux balance analysis, showed altered metabolic regulation towards increased supply of the vitamin precursors. Together, our findings demonstrate how microbial metabolism adapts to mutualistic lifestyle through enhanced metabolite exchange.     

SIGN EPISTASIS LIMITS EVOLUTIONARY TRADE‐OFFS AT THE CONFLUENCE OF SINGLE‐ AND MULTI‐CARBON METABOLISM IN METHYLOBACTERIUM EXTORQUENS AM1

Adaptation of one set of traits is often accompanied by attenuation of traits important in other selective environments, leading to fitness trade‐offs. The mechanisms that either promote or prevent the emergence of trade‐offs remain largely unknown, and are difficult to discern in most systems. Here, we investigate the basis of trade‐offs that emerged during experimental evolution of Methylobacterium extorquens AM1 to distinct growth substrates. After 1500 generations of adaptation to a multi‐carbon substrate, succinate (S), many lineages had lost the ability to use one‐carbon compounds such as methanol (M), generating a mixture of M⁺ and M^? evolved phenotypes. We show that trade‐offs in M^? strains consistently arise via antagonistic pleiotropy through recurrent selection for loss‐of‐function mutations to ftfL (formate‐tetrahydrofolate ligase), which improved growth on S while simultaneously eliminating growth on M. But if loss of FtfL was beneficial, why were M trade‐offs not found in all populations? We discovered that eliminating FtfL was not universally beneficial on S, as it was neutral or even deleterious in certain evolved lineages that remained M⁺. This suggests that sign epistasis with earlier arising mutations prevented the emergence of mutations that drove trade‐offs through antagonistic pleiotropy, limiting the evolution of metabolic specialists in some populations.     

Geography disentangles introgression from ancestral polymorphism in Lake Malawi cichlids

Phenotypically diverse Lake Malawi cichlids exhibit similar genomes. The extensive sharing of genetic polymorphism among forms has both intrigued and frustrated biologists trying to understand the nature of diversity in this and other rapidly evolving systems. Shared polymorphism might result from hybridization and/or the retention of ancestrally polymorphic alleles. To examine these alternatives, we used new genomic tools to characterize genetic differentiation in widespread, geographically structured populations of Labeotropheus fuelleborni and Metriaclima zebra. These phenotypically distinct species share mitochondrial DNA (mtDNA) haplotypes and show greater mtDNA differentiation among localities than between species. However, Bayesian analysis of nuclear single nucleotide polymorphism (SNP) data revealed two distinct genetic clusters corresponding perfectly to morphologically diagnosed L. fuelleborni and M. zebra. This result is a function of the resolving power of the multi‐locus dataset, not a conflict between nuclear and mitochondrial partitions. Locus‐by‐locus analysis showed that mtDNA differentiation between species (F_CT) was nearly identical to the median single‐locus SNP F_CT. Finally, we asked whether there is evidence for gene flow at sites of co‐occurrence. We used simulations to generate a null distribution for the level of differentiation between co‐occurring populations of L. fuelleborni and M. zebra expected if there was no hybridization. The null hypothesis was rejected for the SNP data; populations that co‐occur at rock reef sites were slightly more similar than expected by chance, suggesting recent gene flow. The coupling of numerous independent markers with extensive geographic sampling and simulations utilized here provides a framework for assessing the prevalence of gene flow in recently diverged species.     

Integrating biological information into the statistical analysis and design of microarray experiments

Microarray technology is a powerful tool for animal functional genomics studies, with applications spanning from gene identification and mapping, to function and control of gene expression. Microarray assays, however, are complex and costly, and hence generally performed with relatively small number of animals. Nevertheless, they generate data sets of unprecedented complexity and dimensionality. Therefore, such trials require careful planning and experimental design, in addition to tailored statistical and computational tools for their appropriate data mining. In this review, we discuss experimental design and data analysis strategies, which incorporate prior genomic and biological knowledge, such as genotypes and gene function and pathway membership. We focus the discussion on the design of genetical genomics studies, and on significance testing for detection of differential expression. It is shown that the use of prior biological information can improve the efficiency of microarray experiments.     

解纤维梭菌培养条件的优化

解纤维梭菌Clostridium cellulolyticum是产纤维小体的专性厌氧菌,由于其培养困难,目前仍难以实现高效培养.文中采用响应面法对产纤维小体的解纤维梭菌C.cellulolyticum高细胞密度培养的条件进行了优化.首先用Plackett-Burman实验设计对影响因素效应进行评价,筛选出的显著影响因素分别为:酵母提取物浓度、纤维二糖浓度及培养温度.之后用最陡爬坡实验设计逼近菌体最佳生长条件的区域范围.最后通过中心组合实验设计和响应面分析方法确定显著影响因素的水平和C.cellulolyticum的最优培养条件.优化后的显著影响因素酵母提取物浓度、纤维二糖浓度和培养温度分别为3 g/L、7 g/L和34℃.在最优条件下,摇瓶培养的菌体浓度OD600值由0.303提高到了0.586,增加了93.4％.在发酵罐批次培养条件下,菌体OD600值达到了3.432,比文献报道值高出了2.8倍.研究结果为C.cellulolyticum培养及应用研究提供了基础.