Remote homology clustering identifies lowly conserved families of effector proteins in plant-pathogenic fungi.
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ABSTRACT:
SUBMITTER: Jones DAB
PROVIDER: S-EPMC8715435 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Viruses are abundant, diverse and ancestral biological entities. Their diversity is high, both in terms of the number of different protein families encountered and in the sequence heterogeneity of each protein family. The recent increase in sequenced viral genomes constitutes a great opportunity to gain new insights into this diversity and consequently urges the development of annotation resources to help functional and comparative analysis. Here, we introduce PHROG (Prokaryotic Virus Remote Homologous Groups), a library of viral protein families generated using a new clustering approach based on remote homology detection by HMM profile-profile comparisons. Considering 17 473 reference (pro)viruses of prokaryotes, 868 340 of the total 938 864 proteins were grouped into 38 880 clusters that proved to be a 2-fold deeper clustering than using a classical strategy based on BLAST-like similarity searches, and yet to remain homogeneous. Manual inspection of similarities to various reference sequence databases led to the annotation of 5108 clusters (containing 50.6 % of the total protein dataset) with 705 different annotation terms, included in 9 functional categories, specifically designed for viruses. Hopefully, PHROG will be a useful tool to better annotate future prokaryotic viral sequences thus helping the scientific community to better understand the evolution and ecology of these entities.
| S-EPMC8341000 | biostudies-literature
Project description:UnlabelledRemote homology detection among proteins utilizing only the unlabelled sequences is a central problem in comparative genomics. The existing cluster kernel methods based on neighborhoods and profiles and the Markov clustering algorithms are currently the most popular methods for protein family recognition. The deviation from random walks with inflation or dependency on hard threshold in similarity measure in those methods requires an enhancement for homology detection among multi-domain proteins. We propose to combine spectral clustering with neighborhood kernels in Markov similarity for enhancing sensitivity in detecting homology independent of "recent" paralogs. The spectral clustering approach with new combined local alignment kernels more effectively exploits the unsupervised protein sequences globally reducing inter-cluster walks. When combined with the corrections based on modified symmetry based proximity norm deemphasizing outliers, the technique proposed in this article outperforms other state-of-the-art cluster kernels among all twelve implemented kernels. The comparison with the state-of-the-art string and mismatch kernels also show the superior performance scores provided by the proposed kernels. Similar performance improvement also is found over an existing large dataset. Therefore the proposed spectral clustering framework over combined local alignment kernels with modified symmetry based correction achieves superior performance for unsupervised remote homolog detection even in multi-domain and promiscuous domain proteins from Genolevures database families with better biological relevance. Source code available upon request.Contactsarkar@labri.fr.
| S-EPMC3574063 | biostudies-literature
Project description:The eukaryotic single-stranded DNA binding factor replication protein A (RPA) is essential for DNA replication, repair and recombination. RPA is a heterotrimer containing six related OB folds and a winged helix-turn-helix (wH) domain. The OB folds are designated DBD-A through DBD-F, with DBD-A through DBD-D being directly involved in ssDNA binding. DBD-C is located at the C-terminus of the RPA1 protein and has a distinctive structure that includes an integral C4 zinc finger, while the wH domain is found at the C-terminus of the RPA2 protein. Previously characterised archaeal RPA proteins fall into a number of classes with varying numbers of OB folds, but one widespread class includes proteins that contain a C4 or C3H zinc finger followed by a 100-120 amino acid C-terminal region reported to lack detectable sequence or structural similarity. Here, the sequences spanning this zinc finger and including the C-terminal region are shown to comprise a previously unrecognised DBD-C-like OB fold, confirming the evolutionary relatedness of this group of archaeal RPA proteins to eukaryotic RPA1. The evolutionary relationship between eukaryotic and archaeal RPA is further underscored by the presence of RPA2-like proteins comprising an OB fold and C-terminal winged helix (wH) domain in multiple species and crucially, suggests that several biochemically characterised archaeal RPA proteins previously thought to exist as monomers are likely to be RPA1-RPA2 heterodimers.
| S-EPMC8329085 | biostudies-literature
Project description:Homology of highly divergent genes often cannot be determined from sequence similarity alone. For example, we recently identified in the aphid Hormaphis cornu a family of rapidly evolving bicycle genes, which encode novel proteins implicated as plant gall effectors, and sequence similarity search methods yielded few putative bicycle homologs in other species. Coding sequence-independent features of genes, such as intron-exon boundaries, often evolve more slowly than coding sequences, however, and can provide complementary evidence for homology. We found that a linear logistic regression classifier using only structural features of bicycle genes identified many putative bicycle homologs in other species. Independent evidence from sequence features and intron locations supported homology assignments. To test the potential roles of bicycle genes in other aphids, we sequenced the genome of a second gall-forming aphid, Tetraneura nigriabdominalis and found that many bicycle genes are strongly expressed in the salivary glands of the gall forming foundress. In addition, bicycle genes are strongly overexpressed in the salivary glands of a non-gall forming aphid, Acyrthosiphon pisum, and in the non-gall forming generations of H. cornu. These observations suggest that Bicycle proteins may be used by multiple aphid species to manipulate plants in diverse ways. Incorporation of gene structural features into sequence search algorithms may aid identification of deeply divergent homologs, especially of rapidly evolving genes involved in host-parasite interactions.
| S-EPMC9168663 | biostudies-literature
Project description:The lipid transporter Arv1 regulates sterol trafficking, and glycosylphosphatidylinositol and sphingolipid biosyntheses in Saccharomyces cerevisiae. ScArv1 contains an Arv1 homology domain (AHD) that is conserved at the amino acid level in the pathogenic fungal species, Candida albicans and Candida glabrata. Here we show S. cerevisiae cells lacking Arv1 are highly susceptible to antifungal drugs. In the presence of drug, Scarv1 cells are unable to induce ERG gene expression, have an altered pleiotrophic drug response, and are defective in multi-drug resistance efflux pump expression. All phenotypes are remediated by ectopic expression of CaARV1 or CgARV1. The AHDs of these pathogenic fungi are required for specific drug tolerance, demonstrating conservation of function. In order to understand how Arv1 regulates antifungal susceptibility, we examined sterol trafficking. CaARV1/CgARV1 expression suppressed the sterol trafficking defect of Scarv1 cells. Finally, we show that C. albicansarv1/arv1 cells are avirulent using a BALB/c disseminated mouse model. We suggest that overall cell survival in response to antifungal treatment requires the lipid transporter function of Arv1.
| S-EPMC3278566 | biostudies-literature
Project description:BackgroundScab, caused by the biotrophic fungus Venturia inaequalis, is the most economically important disease of apples worldwide. During infection, V. inaequalis occupies the subcuticular environment, where it secretes virulence factors, termed effectors, to promote host colonization. Consistent with other plant-pathogenic fungi, many of these effectors are expected to be non-enzymatic proteins, some of which can be recognized by corresponding host resistance proteins to activate plant defences, thus acting as avirulence determinants. To develop durable control strategies against scab, a better understanding of the roles that these effector proteins play in promoting subcuticular growth by V. inaequalis, as well as in activating, suppressing, or circumventing resistance protein-mediated defences in apple, is required.ResultsWe generated the first comprehensive RNA-seq transcriptome of V. inaequalis during colonization of apple. Analysis of this transcriptome revealed five temporal waves of gene expression that peaked during early, mid, or mid-late infection. While the number of genes encoding secreted, non-enzymatic proteinaceous effector candidates (ECs) varied in each wave, most belonged to waves that peaked in expression during mid-late infection. Spectral clustering based on sequence similarity determined that the majority of ECs belonged to expanded protein families. To gain insights into function, the tertiary structures of ECs were predicted using AlphaFold2. Strikingly, despite an absence of sequence similarity, many ECs were predicted to have structural similarity to avirulence proteins from other plant-pathogenic fungi, including members of the MAX, LARS, ToxA and FOLD effector families. In addition, several other ECs, including an EC family with sequence similarity to the AvrLm6 avirulence effector from Leptosphaeria maculans, were predicted to adopt a KP6-like fold. Thus, proteins with a KP6-like fold represent another structural family of effectors shared among plant-pathogenic fungi.ConclusionsOur study reveals the transcriptomic profile underpinning subcuticular growth by V. inaequalis and provides an enriched list of ECs that can be investigated for roles in virulence and avirulence. Furthermore, our study supports the idea that numerous sequence-unrelated effectors across plant-pathogenic fungi share common structural folds. In doing so, our study gives weight to the hypothesis that many fungal effectors evolved from ancestral genes through duplication, followed by sequence diversification, to produce sequence-unrelated but structurally similar proteins.
| S-EPMC9632046 | biostudies-literature
Project description:We are presenting a quantitative proteomics tally of the most commonly expressed conserved fungal proteins of the cytosol, the cell wall, and the secretome. It was our goal to identify fungi-typical proteins that do not share significant homology with human proteins. Such fungal proteins are of interest to the development of vaccines or drug targets. Protein samples were derived from 13 fungal species, cultured in rich or in minimal media; these included clinical isolates of Aspergillus, Candida, Mucor, Cryptococcus, and Coccidioides species. Proteomes were analyzed by quantitative MSE (Mass Spectrometry-Elevated Collision Energy). Several thousand proteins were identified and quantified in total across all fractions and culture conditions. The 42 most abundant proteins identified in fungal cell walls or supernatants shared no to very little homology with human proteins. In contrast, all but five of the 50 most abundant cytosolic proteins had human homologs with sequence identity averaging 59%. Proteomic comparisons of the secreted or surface localized fungal proteins highlighted conserved homologs of the Aspergillus fumigatus proteins 1,3-β-glucanosyltransferases (Bgt1, Gel1-4), Crf1, Ecm33, EglC, and others. The fact that Crf1 and Gel1 were previously shown to be promising vaccine candidates, underlines the value of the proteomics data presented here.
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Project description:Phytopathogenic ascomycete fungi possess huge effector repertoires that are dominated by hundreds of sequence-unrelated small secreted proteins. The molecular function of these effectors and the evolutionary mechanisms that generate this tremendous number of singleton genes are largely unknown. To get a deeper understanding of fungal effectors, we determined by NMR spectroscopy the 3-dimensional structures of the Magnaporthe oryzae effectors AVR1-CO39 and AVR-Pia. Despite a lack of sequence similarity, both proteins have very similar 6 β-sandwich structures that are stabilized in both cases by a disulfide bridge between 2 conserved cysteins located in similar positions of the proteins. Structural similarity searches revealed that AvrPiz-t, another effector from M. oryzae, and ToxB, an effector of the wheat tan spot pathogen Pyrenophora tritici-repentis have the same structures suggesting the existence of a family of sequence-unrelated but structurally conserved fungal effectors that we named MAX-effectors (Magnaporthe Avrs and ToxB like). Structure-informed pattern searches strengthened this hypothesis by identifying MAX-effector candidates in a broad range of ascomycete phytopathogens. Strong expansion of the MAX-effector family was detected in M. oryzae and M. grisea where they seem to be particularly important since they account for 5-10% of the effector repertoire and 50% of the cloned avirulence effectors. Expression analysis indicated that the majority of M. oryzae MAX-effectors are expressed specifically during early infection suggesting important functions during biotrophic host colonization. We hypothesize that the scenario observed for MAX-effectors can serve as a paradigm for ascomycete effector diversity and that the enormous number of sequence-unrelated ascomycete effectors may in fact belong to a restricted set of structurally conserved effector families.
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Project description:Rust fungi are obligate biotrophic pathogens that cause considerable damage on crop plants. Puccinia graminis f. sp. tritici, the causal agent of wheat stem rust, and Melampsora larici-populina, the poplar leaf rust pathogen, have strong deleterious impacts on wheat and poplar wood production, respectively. Filamentous pathogens such as rust fungi secrete molecules called disease effectors that act as modulators of host cell physiology and can suppress or trigger host immunity. Current knowledge on effectors from other filamentous plant pathogens can be exploited for the characterisation of effectors in the genome of recently sequenced rust fungi. We designed a comprehensive in silico analysis pipeline to identify the putative effector repertoire from the genome of two plant pathogenic rust fungi. The pipeline is based on the observation that known effector proteins from filamentous pathogens have at least one of the following properties: (i) contain a secretion signal, (ii) are encoded by in planta induced genes, (iii) have similarity to haustorial proteins, (iv) are small and cysteine rich, (v) contain a known effector motif or a nuclear localization signal, (vi) are encoded by genes with long intergenic regions, (vii) contain internal repeats, and (viii) do not contain PFAM domains, except those associated with pathogenicity. We used Markov clustering and hierarchical clustering to classify protein families of rust pathogens and rank them according to their likelihood of being effectors. Using this approach, we identified eight families of candidate effectors that we consider of high value for functional characterization. This study revealed a diverse set of candidate effectors, including families of haustorial expressed secreted proteins and small cysteine-rich proteins. This comprehensive classification of candidate effectors from these devastating rust pathogens is an initial step towards probing plant germplasm for novel resistance components.
| S-EPMC3253089 | biostudies-literature
Project description:COMPASS is a method for homology detection and local alignment construction based on the comparison of multiple sequence alignments (MSAs). The method derives numerical profiles from given MSAs, constructs local profile-profile alignments and analytically estimates E-values for the detected similarities. Until now, COMPASS was only available for download and local installation. Here, we present a new web server featuring the latest version of COMPASS, which provides (i) increased sensitivity and selectivity of homology detection; (ii) longer, more complete alignments; and (iii) faster computational speed. After submission of the query MSA or single sequence, the server performs searches versus a user-specified database. The server includes detailed and intuitive control of the search parameters. A flexible output format, structured similarly to BLAST and PSI-BLAST, provides an easy way to read and analyze the detected profile similarities. Brief help sections are available for all input parameters and output options, along with detailed documentation. To illustrate the value of this tool for protein structure-functional prediction, we present two examples of detecting distant homologs for uncharacterized protein families. Available at http://prodata.swmed.edu/compass.
| S-EPMC1933213 | biostudies-literature