Payoffs, not tradeoffs, in the adaptation of a virus to ostensibly conflicting selective pressures.

The genetic architecture of many phenotypic traits is such that genes often contribute to multiple traits, and mutations in these genes can therefore affect multiple phenotypes. These pleiotropic interactions often manifest as tradeoffs between traits where improvement in one property entails a cost in another. The life cycles of many pathogens include periods of growth within a host punctuated with transmission events, such as passage through a digestive tract or a passive stage of exposure in the environment. Populations exposed to such fluctuating selective pressures are expected to acquire mutations showing tradeoffs between reproduction within and survival outside of a host. We selected for individual mutations under fluctuating selective pressures for a ssDNA microvirid bacteriophage by alternating selection for increased growth rate with selection on biophysical properties of the phage capsid in high-temperature or low-pH conditions. Surprisingly, none of the seven unique mutations identified showed a pleiotropic cost; they all improved both growth rate and pH or temperature stability, suggesting that single mutations even in a simple genetic system can simultaneously improve two distinct traits. Selection on growth rate alone revealed tradeoffs, but some mutations still benefited both traits. Tradeoffs were therefore prevalent when selection acted on a single trait, but payoffs resulted when multiple traits were selected for simultaneously. We employed a molecular-dynamics simulation method to determine the mechanisms underlying beneficial effects for three heat-shock mutations. All three mutations significantly enhanced the affinities of protein-protein interfacial bindings, thereby improving capsid stability. The ancestral residues at the mutation sites did not contribute to protein-protein interfacial binding, indicating that these sites acquired a new function. Computational models, such as those used here, may be used in future work not only as predictive tools for mutational effects on protein stability but, ultimately, for evolution.

Epistasis between beneficial mutations and the phenotype-to-fitness Map for a ssDNA virus.

Epistatic interactions between genes and individual mutations are major determinants of the evolutionary properties of genetic systems and have therefore been well documented, but few quantitative data exist on epistatic interactions between beneficial mutations, presumably because such mutations are so much rarer than deleterious ones. We explored epistasis for beneficial mutations by constructing genotypes with pairs of mutations that had been previously identified as beneficial to the ssDNA bacteriophage ID11 and by measuring the effects of these mutations alone and in combination. We constructed 18 of the 36 possible double mutants for the nine available beneficial mutations. We found that epistatic interactions between beneficial mutations were all antagonistic-the effects of the double mutations were less than the sums of the effects of their component single mutations. We found a number of cases of decompensatory interactions, an extreme form of antagonistic epistasis in which the second mutation is actually deleterious in the presence of the first. In the vast majority of cases, recombination uniting two beneficial mutations into the same genome would not be favored by selection, as the recombinant could not outcompete its constituent single mutations. In an attempt to understand these results, we developed a simple model in which the phenotypic effects of mutations are completely additive and epistatic interactions arise as a result of the form of the phenotype-to-fitness mapping. We found that a model with an intermediate phenotypic optimum and additive phenotypic effects provided a good explanation for our data and the observed patterns of epistatic interactions.

An empirical test of the mutational landscape model of adaptation using a single-stranded DNA virus.

The primary impediment to formulating a general theory for adaptive evolution has been the unknown distribution of fitness effects for new beneficial mutations. By applying extreme value theory, Gillespie circumvented this issue in his mutational landscape model for the adaptation of DNA sequences, and Orr recently extended Gillespie's model, generating testable predictions regarding the course of adaptive evolution. Here we provide the first empirical examination of this model, using a single-stranded DNA bacteriophage related to phiX174, and find that our data are consistent with Orr's predictions, provided that the model is adjusted to incorporate mutation bias. Orr's work suggests that there may be generalities in adaptive molecular evolution that transcend the biological details of a system, but we show that for the model to be useful as a predictive or inferential tool, some adjustments for the biology of the system will be necessary.

A Study to Evaluate the Need for Comminution in the Preparation of Food Materials for Testing of Listeria monocytogenes, Staphylococcus Species, and Generic Escherichia coli.

BACKGROUND: Comminution reduces the sampling error arising from distributional heterogeneity of the target contaminant/target analyte in the material, facilitating the selection of a more representative test portion. A laboratory sampling method incorporating comminution prior to selection of the test portion (Sampling Method B) was compared to current sampling methods that used no comminution step (Sampling Method A). OBJECTIVE: This required the development of an efficient process for comminution of food samples prior to removal of the test portion for the detection and isolation of Listeria monocytogenes and the enumeration of Staphylococcus species and Escherichia coli. METHOD: From December 2016 to December 2017, 2742 tests were conducted on 778 unique food samples. For all food samples, a test portion (TPA) was first removed using Sampling Method A, and then the remainder of the material was comminuted and a second test portion (TPB) was removed using Sampling Method B and tested alongside the first portion. RESULTS: Across all food matrices and microbial targets, 17 additional targets were detected using only Sampling Method B, and positive detections of target analytes increased by 77% using Sampling Method B from the test portions taken using Sampling Method A. CONCLUSION: Utilizing a sample preparation method that includes a comminution step resulted in an increased number of pathogen detections. HIGHLIGHTS: The introduction of a comminution step in the preparation of food samples for detection of three common microbial contaminants resulted in an increase in the rate of detection of natural contaminates in a variety of ready to eat foods. An efficient aseptic process for commutation that can be adapted to a wide range of laboratory settings was identified.

Viral recombination blurs taxonomic lines: examination of single-stranded DNA viruses in a wastewater treatment plant.

Understanding the structure and dynamics of microbial communities, especially those of economic concern, is of paramount importance to maintaining healthy and efficient microbial communities at agricultural sites and large industrial cultures, including bioprocessors. Wastewater treatment plants are large bioprocessors which receive water from multiple sources, becoming reservoirs for the collection of many viral families that infect a broad range of hosts. To examine this complex collection of viruses, full-length genomes of circular ssDNA viruses were isolated from a wastewater treatment facility using a combination of sucrose-gradient size selection and rolling-circle amplification and sequenced on an Illumina MiSeq. Single-stranded DNA viruses are among the least understood groups of microbial pathogens due to genomic biases and culturing difficulties, particularly compared to the larger, more often studied dsDNA viruses. However, the group contains several notable well-studied examples, including agricultural pathogens which infect both livestock and crops (Circoviridae and Geminiviridae), and model organisms for genetics and evolution studies (Microviridae). Examination of the collected viral DNA provided evidence for 83 unique genotypic groupings, which were genetically dissimilar to known viral types and exhibited broad diversity within the community. Furthermore, although these genomes express similarities to known viral families, such as Circoviridae, Geminiviridae, and Microviridae, many are so divergent that they may represent new taxonomic groups. This study demonstrated the efficacy of the protocol for separating bacteria and large viruses from the sought after ssDNA viruses and the ability to use this protocol to obtain an in-depth analysis of the diversity within this group.

Environment determines epistatic patterns for a ssDNA virus.

Despite the accumulation of substantial quantities of information about epistatic interactions among both deleterious and beneficial mutations in a wide array of experimental systems, neither consistent patterns nor causal explanations for these interactions have yet emerged. Furthermore, the effects of mutations depend on the environment in which they are characterized, implying that the environment may also influence epistatic interactions. Recent work with beneficial mutations for the single-stranded DNA bacteriophage ID11 demonstrated that interactions between pairs of mutations could be understood by means of a simple model that assumes that mutations have additive phenotypic effects and that epistasis arises through a nonlinear phenotype-fitness map with a single intermediate optimum. To determine whether such a model could also explain changes in epistatic patterns associated with changes in environment, we measured epistatic interactions for these same mutations under conditions for which we expected to find the wild-type ID11 at different distances from its phenotypic optimum by assaying fitnesses at three different temperatures: 33°, 37°, and 41°. Epistasis was present and negative under all conditions, but became more pronounced as temperature increased. We found that the additive-phenotypes model explained these patterns as changes in the parameters of the phenotype-fitness map, but that a model that additionally allows the phenotypes to vary across temperatures performed significantly better. Our results show that ostensibly complex patterns of fitness effects and epistasis across environments can be explained by assuming a simple structure for the genotype-phenotype relationship.

A high-throughput venom-gland transcriptome for the Eastern Diamondback Rattlesnake (Crotalus adamanteus) and evidence for pervasive positive selection across toxin classes.

Despite causing considerable human mortality and morbidity, animal toxins represent a valuable source of pharmacologically active macromolecules, a unique system for studying molecular adaptation, and a powerful framework for examining structure-function relationships in proteins. Snake venoms are particularly useful in the latter regard as they consist primarily of a moderate number of proteins and peptides that have been found to belong to just a handful of protein families. As these proteins and peptides are produced in dedicated glands, transcriptome sequencing has proven to be an effective approach to identifying the expressed toxin genes. We generated a venom-gland transcriptome for the Eastern Diamondback Rattlesnake (Crotalus adamanteus) using Roche 454 sequencing technology. In the current work, we focus on transcripts encoding toxins. We identified 40 unique toxin transcripts, 30 of which have full-length coding sequences, and 10 have only partial coding sequences. These toxins account for 24% of the total sequencing reads. We found toxins from 11 previously described families of snake-venom toxins and have discovered two putative, previously undescribed toxin classes. The most diverse and highly expressed toxin classes in the C. adamanteus venom-gland transcriptome are the serine proteinases, metalloproteinases, and C-type lectins. The serine proteinases are the most abundant class, accounting for 35% of the toxin sequencing reads. Metalloproteinases are the most diverse; 11 different forms have been identified. Using our sequences and those available in public databases, we detected positive selection in seven of the eight toxin families for which sufficient sequences were available for the analysis. We find that the vast majority of the genes that contribute directly to this vertebrate trait show evidence for a role for positive selection in their evolutionary history.