A fast machine-learning-guided primer design pipeline for selective whole genome amplification.

Addressing many of the major outstanding questions in the fields of microbial evolution and pathogenesis will require analyses of populations of microbial genomes. Although population genomic studies provide the analytical resolution to investigate evolutionary and mechanistic processes at fine spatial and temporal scales-precisely the scales at which these processes occur-microbial population genomic research is currently hindered by the practicalities of obtaining sufficient quantities of the relatively pure microbial genomic DNA necessary for next-generation sequencing. Here we present swga2.0, an optimized and parallelized pipeline to design selective whole genome amplification (SWGA) primer sets. Unlike previous methods, swga2.0 incorporates active and machine learning methods to evaluate the amplification efficacy of individual primers and primer sets. Additionally, swga2.0 optimizes primer set search and evaluation strategies, including parallelization at each stage of the pipeline, to dramatically decrease program runtime. Here we describe the swga2.0 pipeline, including the empirical data used to identify primer and primer set characteristics, that improve amplification performance. Additionally, we evaluate the novel swga2.0 pipeline by designing primer sets that successfully amplify Prevotella melaninogenica, an important component of the lung microbiome in cystic fibrosis patients, from samples dominated by human DNA.

Phylogeographic dynamics of the arthropod vector, the blacklegged tick (Ixodes scapularis).

BACKGROUND: The emergence of vector-borne pathogens in novel geographic areas is regulated by the migration of their arthropod vectors. Blacklegged ticks (Ixodes scapularis) and the pathogens they vector, including the causative agents of Lyme disease, babesiosis and anaplasmosis, continue to grow in their population sizes and to expand in geographic range. Migration of this vector over the previous decades has been implicated as the cause of the re-emergence of the most prevalent infectious diseases in North America. METHODS: We systematically collected ticks from across New York State (hereafter referred to as New York) from 2004 to 2017 as part of routine tick-borne pathogen surveillance in the state. This time frame corresponds with an increase in range and incidence of tick-borne diseases within New York. We randomly sampled ticks from this collection to explore the evolutionary history and population dynamics of I. scapularis. We sequenced the mitochondrial genomes of each tick to characterize their current and historical spatial genetic structure and population growth using phylogeographic methods. RESULTS: We sequenced whole mitochondrial genomes from 277 ticks collected across New York between 2004 and 2017. We found evidence of population genetic structure at a broad geographic scale due to differences in the relative abundance, but not the composition, of haplotypes among sampled ticks. Ticks were often most closely related to ticks from the same and nearby collection sites. The data indicate that both short- and long-range migration events shape the population dynamics of blacklegged ticks in New York. CONCLUSIONS: We detailed the population dynamics of the blacklegged tick (Ixodes scapularis) in New York during a time frame in which tick-borne diseases were increasing in range and incidence. Migration of ticks occurred at both coarse and fine scales in the recent past despite evidence of limits to gene flow. Past and current tick population dynamics have implications for further range expansion as habitat suitability for ticks changes due to global climate change. Analyses of mitochondrial genome sequencing data will expound upon previously identified drivers of tick presence and abundance as well as identify additional drivers. These data provide a foundation on which to generate testable hypotheses on the drivers of tick population dynamics occurring at finer scales.

Evolutionary Genetics of Borrelia.

The genus Borrelia consists of evolutionarily and genetically diverse bacterial species that cause a variety of diseases in humans and domestic animals. These vector-borne spirochetes can be classified into two major evolutionary groups, the Lyme borreliosis clade and the relapsing fever clade, both of which have complex transmission cycles during which they interact with multiple host species and arthropod vectors. Molecular, ecological, and evolutionary studies have each provided significant contributions towards our understanding of the natural history, biology and evolutionary genetics of Borrelia species; however, integration of these studies is required to identify the evolutionary causes and consequences of the genetic variation within and among Borrelia species. For example, molecular and genetic studies have identified the adaptations that maximize fitness components throughout the Borrelia lifecycle and enhance transmission efficacy but provide limited insights into the evolutionary pressures that have produced them. Ecological studies can identify interactions between Borrelia species and the vertebrate hosts and arthropod vectors they encounter and the resulting impact on the geographic distribution and abundance of spirochetes but not the genetic or molecular basis underlying these interactions. In this review we discuss recent findings on the evolutionary genetics from both of the evolutionarily distinct clades of Borrelia species. We focus on connecting molecular interactions to the ecological processes that have driven the evolution and diversification of Borrelia species in order to understand the current distribution of genetic and molecular variation within and between Borrelia species.

Evolutionary ecology of Lyme Borrelia.

The bacterial genus, Borrelia, is comprised of vector-borne spirochete species that infect and are transmitted from multiple host species. Some Borrelia species cause highly-prevalent diseases in humans and domestic animals. Evolutionary, ecological, and molecular research on many Borrelia species have resulted in tremendous progress toward understanding the biology and natural history of these species. Yet, many outstanding questions, such as how Borrelia populations will be impacted by climate and land-use change, will require an interdisciplinary approach. The evolutionary ecology research framework incorporates theory and data from evolutionary, ecological, and molecular studies while overcoming common assumptions within each field that can hinder integration across these disciplines. Evolutionary ecology offers a framework to evaluate the ecological consequences of evolved traits and to predict how present-day ecological processes may result in further evolutionary change. Studies of microbes with complex transmission cycles, like Borrelia, which interact with multiple vertebrate hosts and arthropod vectors, are poised to leverage the power of the evolutionary ecology framework to identify the molecular interactions involved in ecological processes that result in evolutionary change. Using existing data, we outline how evolutionary ecology theory can delineate how interactions with other species and the physical environment create selective forces or impact migration of Borrelia populations and result in micro-evolutionary changes. We further discuss the ecological and molecular consequences of those micro-evolutionary changes. While many of the currently outstanding questions will necessitate new experimental designs and additional empirical data, many others can be addressed immediately by integrating existing molecular and ecological data within an evolutionary ecology framework.

Variation at an adhesin locus suggests sociality in natural populations of the yeast Saccharomyces cerevisiae.

Microbes engage in numerous social behaviours that are critical for survival and reproduction, and that require individuals to act as a collective. Various mechanisms ensure that collectives are composed of related, cooperating cells, thus allowing for the evolution and stability of these traits, and for selection to favour traits beneficial to the collective. Since microbes are difficult to observe directly, sociality in natural populations can instead be investigated using evolutionary genetic signatures, as social loci can be evolutionary hotspots. The budding yeast has been studied for over a century, yet little is known about its social behaviour in nature. Flo11 is a highly regulated cell adhesin required for most laboratory social phenotypes; studies suggest it may function in cell recognition and its heterogeneous expression may be adaptive for collectives such as biofilms. We investigated this locus and found positive selection in the areas implicated in cell-cell interaction, suggesting selection for kin discrimination. We also found balancing selection at an upstream activation site, suggesting selection on the level of variegated gene expression. Our results suggest this model yeast is surprisingly social in natural environments and is probably engaging in various forms of sociality. By using genomic data, this research provides a glimpse of otherwise unobservable interactions.