96 research outputs found
Finding needles in haystacks: linking scientific names, reference specimens and molecular data for Fungi
Inferring the Tree of Life: chopping a phylogenomic problem down to size?
The combination of molecular sequence data and bioinformatics has revolutionized phylogenetic inference over the past decade, vastly increasing the scope of the evolutionary trees that we are able to infer. A recent paper in BMC Biology describing a new phylogenomic pipeline to help automate the inference of evolutionary trees from public sequence databases provides another important tool in our efforts to derive the Tree of Life
Finding needles in haystacks: linking scientific names, reference specimens and molecular data for Fungi
DNA phylogenetic comparisons have shown that morphology-based species recognition often underestimates fungal diversity. Therefore, the need for accurate DNA sequence data, tied to both correct taxonomic names and clearly annotated specimen data, has never been greater. Furthermore, the growing number of molecular ecology and microbiome projects using high-throughput sequencing require fast and effective methods for en masse species assignments. In this article, we focus on selecting and re-annotating a set of marker reference sequences that represent each currently accepted order of Fungi. The particular focus is on sequences from the internal transcribed spacer region in the nuclear ribosomal cistron, derived from type specimens and/or ex-type cultures. Re-annotated and verified sequences were deposited in a curated public database at the National Center for Biotechnology Information (NCBI), namely the RefSeq Targeted Loci (RTL) database, and will be visible during routine sequence similarity searches with NR_prefixed accession numbers. A set of standards and protocols is proposed to improve the data quality of new sequences, and we suggest how type and other reference sequences can be used to improve identification of Fungi
A class-wide phylogenetic assessment of Dothideomycetes
We present a comprehensive phylogeny derived from 5 genes, nucSSU, nucLSU
rDNA, TEF1, RPB1 and RPB2, for 356 isolates and 41
families (six newly described in this volume) in Dothideomycetes. All
currently accepted orders in the class are represented for the first time in
addition to numerous previously unplaced lineages. Subclass
Pleosporomycetidae is expanded to include the aquatic order
Jahnulales. An ancestral reconstruction of basic nutritional modes
supports numerous transitions from saprobic life histories to plant associated
and lichenised modes and a transition from terrestrial to aquatic habitats are
confirmed. Finally, a genomic comparison of 6 dothideomycete genomes with
other fungi finds a high level of unique protein associated with the class,
supporting its delineation as a separate taxon
Combining Substrate Specificity Analysis with Support Vector Classifiers Reveals Feruloyl Esterase as a Phylogenetically Informative Protein Group
Our understanding of how fungi evolved to develop a variety of ecological niches, is limited but of fundamental biological importance. Specifically, the evolution of enzymes affects how well species can adapt to new environmental conditions. Feruloyl esterases (FAEs) are enzymes able to hydrolyze the ester bonds linking ferulic acid to plant cell wall polysaccharides. The diversity of substrate specificities found in the FAE family shows that this family is old enough to have experienced the emergence and loss of many activities. In this study we evaluate the relative activity of FAEs against a variety of model substrates as a novel predictive tool for Ascomycota taxonomic classification. Our approach consists of two analytical steps; (1) an initial unsupervised analysis to cluster the FAEs substrate specificity data which were generated by cultivation of 34 Ascomycota strains and then an analysis of the produced enzyme cocktail against 10 substituted cinnamate and phenylalkanoate methyl esters, (2) a second, supervised analysis for training a predictor built on these substrate activities. By applying both linear and non-linear models we were able to correctly predict the taxonomic Class (∼86% correct classification), Order (∼88% correct classification) and Family (∼88% correct classification) that the 34 Ascomycota belong to, using the activity profiles of the FAEs. The good correlation with the FAEs substrate specificities that we have defined via our phylogenetic analysis not only suggests that FAEs are phylogenetically informative proteins but it is also a considerable step towards improved FAEs functional prediction.published_or_final_versio
ChLae1 and ChVel1 Regulate T-toxin Production, Virulence, Oxidative Stress Response, and Development of the Maize Pathogen Cochliobolus heterostrophus
LaeA and VeA coordinate secondary metabolism and differentiation in response to light signals in Aspergillus spp. Their orthologs, ChLae1 and ChVel1, were identified in the maize pathogen Cochliobolus heterostrophus, known to produce a wealth of secondary metabolites, including the host selective toxin, T-toxin. Produced by race T, T-toxin promotes high virulence to maize carrying Texas male sterile cytoplasm (T-cms). T-toxin production is significantly increased in the dark in wild type (WT), whereas Chvel1 and Chlae1 mutant toxin levels are much reduced in the dark compared to WT. Correspondingly, expression of T-toxin biosynthetic genes (Tox1) is up-regulated in the dark in WT, while dark-induced expression is much reduced/minimal in Chvel1 and Chlae1 mutants. Toxin production and Tox1 gene expression are increased in ChVEL1 overexpression (OE) strains grown in the dark and in ChLAE1 strains grown in either light or dark, compared to WT. These observations establish ChLae1 and ChVel1 as the first factors known to regulate host selective toxin production. Virulence of Chlae1 and Chvel1 mutants and OE strains is altered on both T-cms and normal cytoplasm maize, indicating that both T-toxin mediated super virulence and basic pathogenic ability are affected. Deletion of ChLAE1 or ChVEL1 reduces tolerance to H2O2. Expression of CAT3, one of the three catalase genes, is reduced in the Chvel1 mutant. Chlae1 and Chvel1 mutants also show decreased aerial hyphal growth, increased asexual sporulation and female sterility. ChLAE1 OE strains are female sterile, while ChVEL1 OE strains are more fertile than WT. ChLae1 and ChVel1 repress expression of 1,8-dihydroxynaphthalene (DHN) melanin biosynthesis genes, and, accordingly, melanization is enhanced in Chlae1 and Chvel1 mutants, and reduced in OE strains. Thus, ChLae1 and ChVel1 positively regulate T-toxin biosynthesis, pathogenicity and super virulence, oxidative stress responses, sexual development, and aerial hyphal growth, and negatively control melanin biosynthesis and asexual differentiation
Mitochondrial phylogeography and population structure of the cattle tick Rhipicephalus appendiculatus in the African Great Lakes region
Abstract Background The ixodid tick Rhipicephalus appendiculatus is the main vector of Theileria parva, wich causes the highly fatal cattle disease East Coast fever (ECF) in sub-Saharan Africa. Rhipicephalus appendiculatus populations differ in their ecology, diapause behaviour and vector competence. Thus, their expansion in new areas may change the genetic structure and consequently affect the vector-pathogen system and disease outcomes. In this study we investigated the genetic distribution of R. appendiculatus across agro-ecological zones (AEZs) in the African Great Lakes region to better understand the epidemiology of ECF and elucidate R. appendiculatus evolutionary history and biogeographical colonization in Africa. Methods Sequencing was performed on two mitochondrial genes (cox1 and 12S rRNA) of 218 ticks collected from cattle across six AEZs along an altitudinal gradient in the Democratic Republic of Congo, Rwanda, Burundi and Tanzania. Phylogenetic relationships between tick populations were determined and evolutionary population dynamics models were assessed by mismach distribution. Results Population genetic analysis yielded 22 cox1 and 9 12S haplotypes in a total of 209 and 126 nucleotide sequences, respectively. Phylogenetic algorithms grouped these haplotypes for both genes into two major clades (lineages A and B). We observed significant genetic variation segregating the two lineages and low structure among populations with high degree of migration. The observed high gene flow indicates population admixture between AEZs. However, reduced number of migrants was observed between lowlands and highlands. Mismatch analysis detected a signature of rapid demographic and range expansion of lineage A. The star-like pattern of isolated and published haplotypes indicates that the two lineages evolve independently and have been subjected to expansion across Africa. Conclusions Two sympatric R. appendiculatus lineages occur in the Great Lakes region. Lineage A, the most diverse and ubiquitous, has experienced rapid population growth and range expansion in all AEZs probably through cattle movement, whereas lineage B, the less abundant, has probably established a founder population from recent colonization events and its occurrence decreases with altitude. These two lineages are sympatric in central and eastern Africa and allopatric in southern Africa. The observed colonization pattern may strongly affect the transmission system and may explain ECF endemic instability in the tick distribution fringes
The Tree versus the Forest: The Fungal Tree of Life and the Topological Diversity within the Yeast Phylome
A recurrent topic in phylogenomics is the combination of various sequence alignments to reconstruct a tree that describes the evolutionary relationships within a group of species. However, such approach has been criticized for not being able to properly represent the topological diversity found among gene trees. To evaluate the representativeness of species trees based on concatenated alignments, we reconstruct several fungal species trees and compare them with the complete collection of phylogenies of genes encoded in the Saccharomyces cerevisiae genome. We found that, despite high levels of among-gene topological variation, the species trees do represent widely supported phylogenetic relationships. Most topological discrepancies between gene and species trees are concentrated in certain conflicting nodes. We propose to map such information on the species tree so that it accounts for the levels of congruence across the genome. We identified the lack of sufficient accuracy of current alignment and phylogenetic methods as an important source for the topological diversity encountered among gene trees. Finally, we discuss the implications of the high levels of topological variation for phylogeny-based orthology prediction strategies
Genomic and Proteomic Analyses of the Fungus Arthrobotrys oligospora Provide Insights into Nematode-Trap Formation
Nematode-trapping fungi are “carnivorous” and attack their hosts using specialized trapping devices. The morphological development of these traps is the key indicator of their switch from saprophytic to predacious lifestyles. Here, the genome of the nematode-trapping fungus Arthrobotrys oligospora Fres. (ATCC24927) was reported. The genome contains 40.07 Mb assembled sequence with 11,479 predicted genes. Comparative analysis showed that A. oligospora shared many more genes with pathogenic fungi than with non-pathogenic fungi. Specifically, compared to several sequenced ascomycete fungi, the A. oligospora genome has a larger number of pathogenicity-related genes in the subtilisin, cellulase, cellobiohydrolase, and pectinesterase gene families. Searching against the pathogen-host interaction gene database identified 398 homologous genes involved in pathogenicity in other fungi. The analysis of repetitive sequences provided evidence for repeat-induced point mutations in A. oligospora. Proteomic and quantitative PCR (qPCR) analyses revealed that 90 genes were significantly up-regulated at the early stage of trap-formation by nematode extracts and most of these genes were involved in translation, amino acid metabolism, carbohydrate metabolism, cell wall and membrane biogenesis. Based on the combined genomic, proteomic and qPCR data, a model for the formation of nematode trapping device in this fungus was proposed. In this model, multiple fungal signal transduction pathways are activated by its nematode prey to further regulate downstream genes associated with diverse cellular processes such as energy metabolism, biosynthesis of the cell wall and adhesive proteins, cell division, glycerol accumulation and peroxisome biogenesis. This study will facilitate the identification of pathogenicity-related genes and provide a broad foundation for understanding the molecular and evolutionary mechanisms underlying fungi-nematodes interactions
Detecting Network Communities: An Application to Phylogenetic Analysis
This paper proposes a new method to identify communities in generally weighted
complex networks and apply it to phylogenetic analysis. In this case, weights
correspond to the similarity indexes among protein sequences, which can be used
for network construction so that the network structure can be analyzed to
recover phylogenetically useful information from its properties. The analyses
discussed here are mainly based on the modular character of protein similarity
networks, explored through the Newman-Girvan algorithm, with the help of the
neighborhood matrix . The most relevant
networks are found when the network topology changes abruptly revealing distinct
modules related to the sets of organisms to which the proteins belong. Sound
biological information can be retrieved by the computational routines used in
the network approach, without using biological assumptions other than those
incorporated by BLAST. Usually, all the main bacterial phyla and, in some cases,
also some bacterial classes corresponded totally (100%) or to a great
extent (>70%) to the modules. We checked for internal consistency in
the obtained results, and we scored close to 84% of matches for community
pertinence when comparisons between the results were performed. To illustrate
how to use the network-based method, we employed data for enzymes involved in
the chitin metabolic pathway that are present in more than 100 organisms from an
original data set containing 1,695 organisms, downloaded from GenBank on May 19,
2007. A preliminary comparison between the outcomes of the network-based method
and the results of methods based on Bayesian, distance, likelihood, and
parsimony criteria suggests that the former is as reliable as these commonly
used methods. We conclude that the network-based method can be used as a
powerful tool for retrieving modularity information from weighted networks,
which is useful for phylogenetic analysis
- …