Genome-Enabled Analysis of Population Dynamics and Virulence-Associated Loci in the Oat Crown Rust Fungus Puccinia coronata f. sp. avenae.

Puccinia coronata f. sp. avenae (Pca) is an important fungal pathogen causing crown rust that impacts oat production worldwide. Genetic resistance for crop protection against Pca is often overcome by the rapid virulence evolution of the pathogen. This study investigated the factors shaping adaptive evolution of Pca using pathogen populations from distinct geographic regions within the United States and South Africa. Phenotypic and genome-wide sequencing data of these diverse Pca collections, including 217 isolates, uncovered phylogenetic relationships and established distinct genetic composition between populations from northern and southern regions from the United States and South Africa. The population dynamics of Pca involve a bidirectional movement of inoculum between northern and southern regions of the United States and contributions from clonality and sexuality. The population from South Africa is solely clonal. A genome-wide association study (GWAS) employing a haplotype-resolved Pca reference genome was used to define 11 virulence-associated loci corresponding to 25 oat differential lines. These regions were screened to determine candidate Avr effector genes. Overall, the GWAS results allowed us to identify the underlying genetic factors controlling pathogen recognition in an oat differential set used in the United States to assign pathogen races (pathotypes). Key GWAS findings support complex genetic interactions in several oat lines, suggesting allelism among resistance genes or redundancy of genes included in the differential set, multiple resistance genes recognizing genetically linked Avr effector genes, or potentially epistatic relationships. A careful evaluation of the composition of the oat differential set accompanied by the development or implementation of molecular markers is recommended. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Phylogenomic analyses of the genus Drosophila reveals genomic signals of climate adaptation.

Many Drosophila species differ widely in their distributions and climate niches, making them excellent subjects for evolutionary genomic studies. Here, we have developed a database of high-quality assemblies for 46 Drosophila species and one closely related Zaprionus. Fifteen of the genomes were newly sequenced, and 20 were improved with additional sequencing. New or improved annotations were generated for all 47 species, assisted by new transcriptomes for 19. Phylogenomic analyses of these data resolved several previously ambiguous relationships, especially in the melanogaster species group. However, it also revealed significant phylogenetic incongruence among genes, mainly in the form of incomplete lineage sorting in the subgenus Sophophora but also including asymmetric introgression in the subgenus Drosophila. Using the phylogeny as a framework and taking into account these incongruences, we then screened the data for genome-wide signals of adaptation to different climatic niches. First, phylostratigraphy revealed relatively high rates of recent novel gene gain in three temperate pseudoobscura and five desert-adapted cactophilic mulleri subgroup species. Second, we found differing ratios of nonsynonymous to synonymous substitutions in several hundred orthologues between climate generalists and specialists, with trends for significantly higher ratios for those in tropical and lower ratios for those in temperate-continental specialists respectively than those in the climate generalists. Finally, resequencing natural populations of 13 species revealed tropics-restricted species generally had smaller population sizes, lower genome diversity and more deleterious mutations than the more widespread species. We conclude that adaptation to different climates in the genus Drosophila has been associated with large-scale and multifaceted genomic changes.

Genomic Evolution of the Marine Bacterium Phaeobacter inhibens during Biofilm Growth.

Phaeobacter inhibens 2.10 is an effective biofilm former on marine surfaces and has the ability to outcompete other microorganisms, possibly due to the production of the plasmid-encoded secondary metabolite tropodithietic acid (TDA). P. inhibens 2.10 biofilms produce phenotypic variants with reduced competitiveness compared to the wild type. In the present study, we used longitudinal, genome-wide deep sequencing to uncover the genetic foundation that contributes to the emergent phenotypic diversity in P. inhibens 2.10 biofilm dispersants. Our results show that phenotypic variation is not due to the loss of the plasmid that carries the genes for TDA synthesis but instead show that P. inhibens 2.10 biofilm populations become rapidly enriched in single nucleotide variations in genes involved in the synthesis of TDA. While variants in genes previously linked to other phenotypes, such as lipopolysaccharide production (i.e., rfbA) and cellular persistence (i.e., metG), also appear to be selected for during biofilm dispersal, the number and consistency of variations found for genes involved in TDA production suggest that this metabolite imposes a burden on P. inhibens 2.10 cells. Our results indicate a strong selection pressure for the loss of TDA in monospecies biofilm populations and provide insight into how competition (or a lack thereof) in biofilms might shape genome evolution in bacteria. IMPORTANCE Biofilm formation and dispersal are important survival strategies for environmental bacteria. During biofilm dispersal, cells often display stable and heritable variants from the parental biofilm. Phaeobacter inhibens is an effective colonizer of marine surfaces, in which a subpopulation of its biofilm dispersal cells displays a noncompetitive phenotype. This study aimed to elucidate the genetic basis of these phenotypic changes. Despite the progress made to date in characterizing the dispersal variants in P. inhibens, little is understood about the underlying genetic changes that result in the development of the specific variants. Here, P. inhibens phenotypic variation was linked to single nucleotide polymorphisms (SNPs), in particular in genes affecting the competitive ability of P. inhibens, including genes related to the production of the antibiotic tropodithietic acid (TDA) and bacterial cell-cell communication (e.g., quorum sensing). This work is significant as it reveals how the biofilm lifestyle might shape genome evolution in a cosmopolitan bacterium.

Robbery in progress: Historical museum collections bring to light a mitochondrial capture within a bird species widespread across southern Australia, the Copperback Quail-thrush Cinclosoma clarum.

We surveyed mitochondrial, autosomal, and Z chromosome diversity within and between the Copperback Quail-thrush Cinclosoma clarum and Chestnut Quail-thrush C. castanotum, which together span the arid and semi-arid zones of southern Australia, and primarily from specimens held in museum collections. We affirm the recent taxonomic separation of the two species and then focus on diversity within the more widespread of the two species, C. clarum. To guide further study of the system and what it offers to understanding the genomics of the differentiation and speciation processes, we develop and present a hypothesis to explain mitonuclear discordance that emerged in ourdata. Following a period of historical allopatry, secondary contact has resulted in an eastern mitochondrial genome replacing the western mitochondrial genome in western populations. This is predicted under a population-level invasion in the opposite direction, that of the western population invading the range of the eastern one. Mitochondrial captures can be driven by neutral, demographic processes, or adaptive mechanisms, and we favor the hypothesized capture being driven by neutral means. We cannot fully reject the adaptive process but suggest how these alternatives may be further tested. We acknowledge an alternative hypothesis, which finds some support in phenotypic data published elsewhere, namely that outcomes of secondary contact have been more complex than our current genomic data suggest. Discriminating and reconciling these two alternative hypotheses, which may not be mutually exclusive, could be tested with closer sampling at levels of population, individual, and nucleotide than has so far been possible. This would be further aided by knowledge of the genetic basis to phenotypic variation described elsewhere.

Causes and Consequences of a Variant Strain of Phaeobacter inhibens With Reduced Competition.

Phaeobacter inhibens 2.10 is an effective biofilm former and colonizer of marine surfaces and has the ability to outcompete other microbiota. During biofilm dispersal P. inhibens 2.10 produces heritable phenotypic variants, including those that have a reduced ability to inhibit the co-occurring bacterium Pseudoalteromonas tunicata. However, the genetic changes that underpin the phenotypic variation and what the ecological consequences are for variants within the population are unclear. To answer these questions we sequenced the genomes of strain NCV12a1, a biofilm variant of P. inhibens 2.10 with reduced inhibitory activity and the P. inhibens 2.10 WT parental strain. Genome wide analysis revealed point mutations in genes involved in synthesis of the antibacterial compound tropodithietic acid (TDA) and indirectly in extracellular polymeric substances (EPS) production. However, confocal laser scanning microscopy analyses found little differences in biofilm growth between P. inhibens 2.10 WT (parental) and NCV12a1. P. inhibens NCV12a1 was also not outcompeted in co-cultured biofilms with P. tunicata, despite its reduced inhibitory activity, rather these biofilms were thicker than those produced when the WT strain was co-cultured with P. tunicata. Notably, dispersal populations from biofilms of P. inhibens NCV12a1 had a higher proportion of WT-like morphotypes when co-cultured with P. tunicata. These observations may explain why the otherwise non-inhibiting variant persists in the presence of a natural competitor, adding to our understanding of the relative importance of genetic diversification in microbial biofilms.

Local adaptation of a bacterium is as important as its presence in structuring a natural microbial community.

Local adaptation of a species can affect community composition, yet the importance of local adaptation compared with species presence per se is unknown. Here we determine how a compost bacterial community exposed to elevated temperature changes over 2 months as a result of the presence of a focal bacterium, Pseudomonas fluorescens SBW25, that had been pre-adapted or not to the compost for 48 days. The effect of local adaptation on community composition is as great as the effect of species presence per se, with these results robust to the presence of an additional strong selection pressure: an SBW25-specific virus. These findings suggest that evolution occurring over ecological time scales can be a key driver of the structure of natural microbial communities, particularly in situations where some species have an evolutionary head start following large perturbations, such as exposure to antibiotics or crop planting and harvesting.

Strain-specific parallel evolution drives short-term diversification during Pseudomonas aeruginosa biofilm formation.

Generation of genetic diversity is a prerequisite for bacterial evolution and adaptation. Short-term diversification and selection within populations is, however, largely uncharacterised, as existing studies typically focus on fixed substitutions. Here, we use whole-genome deep-sequencing to capture the spectrum of mutations arising during biofilm development for two Pseudomonas aeruginosa strains. This approach identified single nucleotide variants with frequencies from 0.5% to 98.0% and showed that the clinical strain 18A exhibits greater genetic diversification than the type strain PA01, despite its lower per base mutation rate. Mutations were found to be strain specific: the mucoid strain 18A experienced mutations in alginate production genes and a c-di-GMP regulator gene; while PA01 acquired mutations in PilT and PilY1, possibly in response to a rapid expansion of a lytic Pf4 bacteriophage, which may use type IV pili for infection. The Pf4 population diversified with an evolutionary rate of 2.43 × 10(-3) substitutions per site per day, which is comparable to single-stranded RNA viruses. Extensive within-strain parallel evolution, often involving identical nucleotides, was also observed indicating that mutation supply is not limiting, which was contrasted by an almost complete lack of noncoding and synonymous mutations. Taken together, these results suggest that the majority of the P. aeruginosa genome is constrained by negative selection, with strong positive selection acting on an accessory subset of genes that facilitate adaptation to the biofilm lifecycle. Long-term bacterial evolution is known to proceed via few, nonsynonymous, positively selected mutations, and here we show that similar dynamics govern short-term, within-population bacterial diversification.

Deep sequencing of evolving pathogen populations: applications, errors, and bioinformatic solutions.

Deep sequencing harnesses the high throughput nature of next generation sequencing technologies to generate population samples, treating information contained in individual reads as meaningful. Here, we review applications of deep sequencing to pathogen evolution. Pioneering deep sequencing studies from the virology literature are discussed, such as whole genome Roche-454 sequencing analyses of the dynamics of the rapidly mutating pathogens hepatitis C virus and HIV. Extension of the deep sequencing approach to bacterial populations is then discussed, including the impacts of emerging sequencing technologies. While it is clear that deep sequencing has unprecedented potential for assessing the genetic structure and evolutionary history of pathogen populations, bioinformatic challenges remain. We summarise current approaches to overcoming these challenges, in particular methods for detecting low frequency variants in the context of sequencing error and reconstructing individual haplotypes from short reads.

Accurate single nucleotide variant detection in viral populations by combining probabilistic clustering with a statistical test of strand bias.

BACKGROUND: Deep sequencing is a powerful tool for assessing viral genetic diversity. Such experiments harness the high coverage afforded by next generation sequencing protocols by treating sequencing reads as a population sample. Distinguishing true single nucleotide variants (SNVs) from sequencing errors remains challenging, however. Current protocols are characterised by high false positive rates, with results requiring time consuming manual checking. RESULTS: By statistical modelling, we show that if multiple variant sites are considered at once, SNVs can be called reliably from high coverage viral deep sequencing data at frequencies lower than the error rate of the sequencing technology, and that SNV calling accuracy increases as true sequence diversity within a read length increases. We demonstrate these findings on two control data sets, showing that SNV detection is more reliable on a high diversity human immunodeficiency virus sample as compared to a moderate diversity sample of hepatitis C virus. Finally, we show that in situations where probabilistic clustering retains false positive SNVs (for instance due to insufficient sample diversity or systematic errors), applying a strand bias test based on a beta-binomial model of forward read distribution can improve precision, with negligible cost to true positive recall. CONCLUSIONS: By combining probabilistic clustering (implemented in the program ShoRAH) with a statistical test of strand bias, SNVs may be called from deeply sequenced viral populations with high accuracy.

Draft genome sequence of the chronic, nonclonal cystic fibrosis isolate Pseudomonas aeruginosa strain 18A.

Pseudomonas aeruginosa strain 18A is a clinical, nonclonal isolate retrieved from the sputum of a chronically infected cystic fibrosis patient. The genome of 18A was sequenced for comparison with environmental and clinical isolates to identify genes that might facilitate its persistence during infection.

Reconstruction of ribosomal RNA genes from metagenomic data.

Direct sequencing of environmental DNA (metagenomics) has a great potential for describing the 16S rRNA gene diversity of microbial communities. However current approaches using this 16S rRNA gene information to describe community diversity suffer from low taxonomic resolution or chimera problems. Here we describe a new strategy that involves stringent assembly and data filtering to reconstruct full-length 16S rRNA genes from metagenomicpyrosequencing data. Simulations showed that reconstructed 16S rRNA genes provided a true picture of the community diversity, had minimal rates of chimera formation and gave taxonomic resolution down to genus level. The strategy was furthermore compared to PCR-based methods to determine the microbial diversity in two marine sponges. This showed that about 30% of the abundant phylotypes reconstructed from metagenomic data failed to be amplified by PCR. Our approach is readily applicable to existing metagenomic datasets and is expected to lead to the discovery of new microbial phylotypes.

GemSIM: general, error-model based simulator of next-generation sequencing data.

BACKGROUND: GemSIM, or General Error-Model based SIMulator, is a next-generation sequencing simulator capable of generating single or paired-end reads for any sequencing technology compatible with the generic formats SAM and FASTQ (including Illumina and Roche/454). GemSIM creates and uses empirically derived, sequence-context based error models to realistically emulate individual sequencing runs and/or technologies. Empirical fragment length and quality score distributions are also used. Reads may be drawn from one or more genomes or haplotype sets, facilitating simulation of deep sequencing, metagenomic, and resequencing projects. RESULTS: We demonstrate GemSIM's value by deriving error models from two different Illumina sequencing runs and one Roche/454 run, and comparing and contrasting the resulting error profiles of each run. Overall error rates varied dramatically, both between individual Illumina runs, between the first and second reads in each pair, and between datasets from Illumina and Roche/454 technologies. Indels were markedly more frequent in Roche/454 than Illumina and both technologies suffered from an increase in error rates near the end of each read.The effects of these different profiles on low-frequency SNP-calling accuracy were investigated by analysing simulated sequencing data for a mixture of bacterial haplotypes. In general, SNP-calling using VarScan was only accurate for SNPs with frequency > 3%, independent of which error model was used to simulate the data. Variation between error profiles interacted strongly with VarScan's 'minumum average quality' parameter, resulting in different optimal settings for different sequencing runs. CONCLUSIONS: Next-generation sequencing has unprecedented potential for assessing genetic diversity, however analysis is complicated as error profiles can vary noticeably even between different runs of the same technology. Simulation with GemSIM can help overcome this problem, by providing insights into the error profiles of individual sequencing runs and allowing researchers to assess the effects of these errors on downstream data analysis.

Contribution of intra- and interhost dynamics to norovirus evolution.

Norovirus (NoV) is an emerging RNA virus that has been associated with global epidemics of gastroenteritis. Each global epidemic arises with the emergence of novel antigenic variants. While the majority of NoV infections are mild and self-limiting, in the young, elderly, and immunocompromised, severe and prolonged illness can result. As yet, there is no vaccine or therapeutic treatment to prevent or control infection. In order to design effective control strategies, it is important to understand the mechanisms and source of the new antigenic variants. In this study, we used next-generation sequencing (NGS) technology to investigate genetic diversification in three contexts: the impact of a NoV transmission event on viral diversity and the contribution to diversity of intrahost evolution over both a short period of time (10 days), in accordance with a typical acute NoV infection, and a prolonged period of time (288 days), as observed for NoV chronic infections of immunocompromised individuals. Investigations of the transmission event revealed that minor variants at frequencies as low as 0.01% were successfully transmitted, indicating that transmission is an important source of diversity at the interhost level of NoV evolution. Our results also suggest that chronically infected immunocompromised subjects represent a potential reservoir for the emergence of new viral variants. In contrast, in a typical acute NoV infection, the viral population was highly homogenous and relatively stable. These results indicate that the evolution of NoV occurs through multiple mechanisms.

Sequential bottlenecks drive viral evolution in early acute hepatitis C virus infection.

Hepatitis C is a pandemic human RNA virus, which commonly causes chronic infection and liver disease. The characterization of viral populations that successfully initiate infection, and also those that drive progression to chronicity is instrumental for understanding pathogenesis and vaccine design. A comprehensive and longitudinal analysis of the viral population was conducted in four subjects followed from very early acute infection to resolution of disease outcome. By means of next generation sequencing (NGS) and standard cloning/Sanger sequencing, genetic diversity and viral variants were quantified over the course of the infection at frequencies as low as 0.1%. Phylogenetic analysis of reassembled viral variants revealed acute infection was dominated by two sequential bottleneck events, irrespective of subsequent chronicity or clearance. The first bottleneck was associated with transmission, with one to two viral variants successfully establishing infection. The second occurred approximately 100 days post-infection, and was characterized by a decline in viral diversity. In the two subjects who developed chronic infection, this second bottleneck was followed by the emergence of a new viral population, which evolved from the founder variants via a selective sweep with fixation in a small number of mutated sites. The diversity at sites with non-synonymous mutation was higher in predicted cytotoxic T cell epitopes, suggesting immune-driven evolution. These results provide the first detailed analysis of early within-host evolution of HCV, indicating strong selective forces limit viral evolution in the acute phase of infection.

Characterisation of a large family of polymorphic collagen-like proteins in the endospore-forming bacterium Pasteuria ramosa.

Collagen-like proteins containing glycine-X-Y repeats have been identified in several pathogenic bacteria potentially involved in virulence. Recently, a collagen-like surface protein, Pcl1a, was identified in Pasteuria ramosa, a spore-forming parasite of Daphnia. Here we characterise 37 novel putative P. ramosa collagen-like protein genes (PCLs). PCR amplification and sequencing across 10 P. ramosa strains showed they were polymorphic, distinguishing genotypes matching known differences in Daphnia/P. ramosa interaction specificity. Thirty PCLs could be divided into four groups based on sequence similarity, conserved N- and C-terminal regions and G-X-Y repeat structure. Group 1, Group 2 and Group 3 PCLs formed triplets within the genome, with one member from each group represented in each triplet. Maximum-likelihood trees suggested that these groups arose through multiple instances of triplet duplication. For Group 1, 2, 3 and 4 PCLs, X was typically proline and Y typically threonine, consistent with other bacterial collagen-like proteins. The amino acid composition of Pcl2 closely resembled Pcl1a, with X typically being glutamic acid or aspartic acid and Y typically being lysine or glutamine. Pcl2 also showed sequence similarity to Pcl1a and contained a predicted signal peptide, cleavage site and transmembrane domain, suggesting that it is a surface protein.

Identification of a polymorphic collagen-like protein in the crustacean bacteria Pasteuria ramosa.

Pasteuria ramosa is a spore-forming bacterium that infects Daphnia species. Previous results demonstrated a high specificity of host clone/parasite genotype interactions. Surface proteins of bacteria often play an important role in attachment to host cells prior to infection. We analyzed surface proteins of P. ramosa spores by two-dimensional gel electrophoresis. For the first time, we prove that two isolates selected for their differences in infectivity reveal few but clear-cut differences in protein patterns. Using internal sequencing and LC/MS/MS, we identified a collagen-like protein named Pcl1a (Pasteuria collagen-like protein 1a). This protein, reconstructed with the help of Pasteuria genome sequences, contains three domains: a 75-amino-acid amino-terminal domain with a potential transmembrane helix domain, a central collagen-like region (CLR) containing Gly-Xaa-Yaa (GXY) repeats, and a 7-amino-acid carboxy-terminal domain. The CLR region is polymorphic among the two isolates with amino-acid substitutions and a variable number of GXY triplets. Collagen-like proteins are rare in prokaryotes, although they have been described in several pathogenic bacteria, including Bacillus cereus, Bacillus anthracis and Bacillus thuringiensis, closely related to Pasteuria species, in which they could be involved in the adherence of bacteria to host cells.