The trehalose 6-phosphate phosphatase family in plants.

Trehalose 6-phosphate (Tre6P), the intermediate of trehalose biosynthesis, is an essential signalling metabolite linking plant growth and development to carbon metabolism. While recent work has focused predominantly on the enzymes that produce Tre6P, little is known about the proteins that catalyse its degradation, the trehalose 6-phosphate phosphatases (TPPs). Often occurring in large protein families, TPPs exhibit cell-, tissue- and developmental stage-specific expression patterns, suggesting important regulatory functions in controlling local levels of Tre6P and trehalose as well as Tre6P signalling. Furthermore, growing evidence through gene expression studies and transgenic approaches shows that TPPs play an important role in integrating environmental signals with plant metabolism. This review highlights the large diversity of TPP isoforms in model and crop plants and identifies how modulating Tre6P metabolism in certain cell types, tissues, and at different developmental stages may promote stress tolerance, resilience and increased crop yield.

A Novel In Silico Method for Molecular Mimicry Detection Finds a Formin with the Potential to Manipulate the Maize Cell Cytoskeleton.

Molecular mimicry is one of the evolutionary strategies that parasites use to manipulate the host metabolism and perform an effective infection. This phenomenon has been observed in several animal and plant pathosystems. Despite the relevance of this mechanism in pathogenesis, little is known about it in fungus-plant interactions. For that reason, we performed an in silico method to select plausible mimicry candidates for the Ustilago maydis-maize interaction. Our methodology used a tripartite sequence comparison between the parasite, the host, and nonparasitic organisms' genomes. Furthermore, we used RNA sequencing information to identify gene coexpression, and we determined subcellular localization to detect potential cases of colocalization in the imitator-imitated pairs. With these approximations, we found a putative extracellular formin in U. maydis with the potential to rearrange the host cell cytoskeleton. In parallel, we detected at least two maize genes involved in the cytoskeleton rearrangement differentially expressed under U. maydis infection; thus, this find increases the expectation for the potential mimicry role of the fungal protein. The use of several sources of data led us to develop a strict and replicable in silico methodology to detect molecular mimicry in pathosystems with enough information available. Furthermore, this is the first time that a genomewide search has been performed to detect molecular mimicry in a U. maydis-maize system. Additionally, to allow the reproducibility of this experiment and the use of this pipeline, we created a Web server called Molecular Mimicry Finder.[Formula: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Multioutput Perturbation-Theory Machine Learning (PTML) Model of ChEMBL Data for Antiretroviral Compounds.

Retroviral infections, such as HIV, are, until now, diseases with no cure. Medicine and pharmaceutical chemistry need and consider it a huge goal to define target proteins of new antiretroviral compounds. ChEMBL manages Big Data features with a complex data set, which is hard to organize. This makes information difficult to analyze due to a big number of characteristics described in order to predict new drug candidates for retroviral infections. For this reason, we propose to develop a new predictive model combining perturbation theory (PT) bases and machine learning (ML) modeling to create a new tool that can take advantage of all the available information. The PTML model proposed in this work for the ChEMBL data set preclinical experimental assays for antiretroviral compounds consists of a linear equation with four variables. The PT operators used are founded on multicondition moving averages, combining different features and simplifying the difficulty to manage all data. More than 140 000 preclinical assays for 56 105 compounds with different characteristics or experimental conditions have been carried out and can be found in ChEMBL database, covering combinations with 359 biological activity parameters (c0), 55 protein accessions (c1), 83 cell lines (c2), 64 organisms of assay (c3), and 773 subtypes or strains. We have included 150 148 preclinical experimental assays for HIV virus, 1188 for HTLV virus, 84 for simian immunodeficiency virus, 370 for murine leukemia virus, 119 for Rous sarcoma virus, 1581 for MMTV, etc. We also included 5277 assays for hepatitis B virus. The developed PTML model reached considerable values in sensibility (73.05% for training and 73.10% for validation), specificity (86.61% for training and 87.17% for validation), and accuracy (75.84% for training and 75.98% for validation). We also compared alternative PTML models with different PT operators such as covariance, moments, and exponential terms. Finally, we made a comparison between literature ML models with our PTML model and also artificial neural network (ANN) nonlinear models. We conclude that this PTML model is the first one to consider multiple characteristics of preclinical experimental antiretroviral assays combined, generating a simple, useful, and adaptable instrument, which could reduce time and costs in antiretroviral drugs research.

CompScore: Boosting Structure-Based Virtual Screening Performance by Incorporating Docking Scoring Function Components into Consensus Scoring.

Consensus scoring has become a commonly used strategy within structure-based virtual screening (VS) workflows with improved performance compared to those based in a single scoring function. However, no research has been devoted to analyze the worth of docking scoring functions components in consensus scoring. We implemented and tested a method that incorporates docking scoring functions components into the setting of high performance VS workflows. This method uses genetic algorithms for finding the combination of scoring components that maximizes the VS enrichment for any target. Our methodology was validated using a data set including ligands and decoys for 102 targets that have been widely used in VS validation studies. Results show that our approach outperforms other methods for all targets. It also boosts the initial enrichment performance of the traditional use of whole scoring functions in consensus scoring by an average of 45%. Our methodology showed to be outstandingly predictive when challenged to rescore external (previously unseen) data. Remarkably, CompScore was able not only to retain its performance after redocking with a different software, but also proved that the enrichment obtained was not artificial. CompScore is freely available at: http://bioquimio.udla.edu.ec/compscore/ .

A whole genome analysis reveals the presence of a plant PR1 sequence in the potato pathogen Streptomyces scabies and other Streptomyces species.

Streptomyces scabies is a common soil bacterium that causes scab symptoms in potatoes. Strong evidence indicates horizontal gene transfer (HGT) among bacteria has influenced the evolution of this plant pathogen and other Streptomyces spp. To extend the study of the HGT to the Streptomyces genus, we explored the effects of the inter-domain HGT in the S. scabies genome. We employed a semi-automatic pipeline based on BLASTp searches and phylogenetic reconstruction. The data show low impact of inter-domain HGT in the S. scabies genome; however, we found a putative plant pathogenesis related 1 (PR1) sequence in the genome of S. scabies and other species of the genus. It is possible that this gene could be used by S. scabies to out-compete other soil organisms.

A Fungal Effector With Host Nuclear Localization and DNA-Binding Properties Is Required for Maize Anthracnose Development.

Plant pathogens have the capacity to manipulate the host immune system through the secretion of effectors. We identified 27 putative effector proteins encoded in the genome of the maize anthracnose pathogen Colletotrichum graminicola that are likely to target the host's nucleus, as they simultaneously contain sequence signatures for secretion and nuclear localization. We functionally characterized one protein, identified as CgEP1. This protein is synthesized during the early stages of disease development and is necessary for anthracnose development in maize leaves, stems, and roots. Genetic, molecular, and biochemical studies confirmed that this effector targets the host's nucleus and defines a novel class of double-stranded DNA-binding protein. We show that CgEP1 arose from a gene duplication in an ancestor of a lineage of monocot-infecting Colletotrichum spp. and has undergone an intense evolution process, with evidence for episodes of positive selection. We detected CgEP1 homologs in several species of a grass-infecting lineage of Colletotrichum spp., suggesting that its function may be conserved across a large number of anthracnose pathogens. Our results demonstrate that effectors targeted to the host nucleus may be key elements for disease development and aid in the understanding of the genetic basis of anthracnose development in maize plants.

Exploring the genetic makeup of Xanthomonas species causing bacterial spot in Taiwan: evidence of population shift and local adaptation.

The introduction of plant pathogens can quickly reshape disease dynamics in island agro-ecologies, representing a continuous challenge for local crop management strategies. Xanthomonas pathogens causing tomato bacterial spot were probably introduced in Taiwan several decades ago, creating a unique opportunity to study the genetic makeup and adaptive response of this alien population. We examined the phenotypic and genotypic identity of 669 pathogen entries collected across different regions of Taiwan in the last three decades. The analysis detected a major population shift, where X. euvesicatoria and X. vesicatoria races T1 and T2 were replaced by new races of X. perforans. After its introduction, race T4 quickly became dominant in all tomato-growing areas of the island. The genomic analysis of 317 global genomes indicates that the Xanthomonas population in Taiwan has a narrow genetic background, most likely resulting from a small number of colonization events. However, despite the apparent genetic uniformity, X. perforans race T4 shows multiple phenotypic responses in tomato lines. Additionally, an in-depth analysis of effector composition suggests diversification in response to local adaptation. These include unique mutations on avrXv3 which might allow the pathogen to overcome Xv3/Rx4 resistance gene. The findings underscore the dynamic evolution of a pathogen when introduced in a semi-isolated environment and provide insights into the potential management strategies for this important disease of tomato.

Canonical or noncanonical? Structural plasticity of serine protease-binding loops in Kunitz-STI protease inhibitors.

The Kunitz-Soybean Trypsin Inhibitor (Kunitz-STI) family is a large family of proteins with most of its members being protease inhibitors. The versatility of the inhibitory profile and the structural plasticity of these proteins, make this family a promising scaffold for designing new multifunctional proteins. Historically, Kunitz-STI inhibitors have been classified as canonical serine protease inhibitors, but new inhibitors with novel inhibition mechanisms have been described in recent years. Different inhibition mechanisms could be the result of different evolutionary pathways. In the present work, we performed a structural analysis of all the crystallographic structures available for Kunitz-STI inhibitors to characterize serine protease-binding loop structural features and locations. Our study suggests a relationship between the conformation of serine protease-binding loops and the inhibition mechanism, their location in the ß-trefoil fold, and the plant source of the inhibitors. The classical canonical inhibitors of this family are restricted to plants from the Fabales order and bind their targets via the ß4-ß5 loop, whereas serine protease-binding loops in inhibitors from other plants lie mainly in the ß5-ß6 and ß9-ß10 loops. In addition, we found that the ß5-ß6 loop is used to inhibit two different families of serine proteases through a steric blockade inhibition mechanism. This work will help to change the general perception that all Kunitz-STI inhibitors are canonical inhibitors and proteins with protease-binding loops adopting noncanonical conformations are exceptions. Additionally, our results will help in the identification of protease-binding loops in uncharacterized or newly discovered inhibitors, and in the design of multifunctional proteins.

A tool for the cheap and rapid screening of SARS-CoV-2 variants of concern (VoCs) by Sanger sequencing.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an emerging virus that, since March 2020, has been responsible for a global and ongoing pandemic. Its rapid spread over the past nearly 3 years has caused novel variants to arise. To monitor the circulation and emergence of SARS-CoV-2 variants, surveillance systems based on nucleotide mutations are required. In this regard, we searched in the spike, ORF8, and nucleocapsid genes to detect variable sites among SARS-CoV-2 variants. We describe polymorphic genetic regions that enable us to differentiate between the Alpha, Beta, Gamma, Delta, and Omicron variants of concern (VoCs). We found 21 relevant mutations, 13 of which are unique for Omicron lineages BA.1/BA.1.1, BA.2, BA.3, BA.4, and BA.5. This genetic profile enables the discrimination between VoCs using only four reverse transcription PCR fragments and Sanger sequencing, offering a cheaper and faster alternative to whole-genome sequencing for SARS-CoV-2 surveillance. IMPORTANCE Our work describes a new (Sanger sequencing-based) screening methodology for SARS-CoV-2, performing PCR amplifications of a few target regions to detect diagnostic mutations between virus variants. Using the methodology developed in this work, we were able to discriminate between the following VoCs: Alpha, Beta, Gamma, Delta, and Omicron (BA.1/BA.1.1, BA.2, BA.3, BA.4, and BA.5). This becomes important, especially in low-income countries where current methodologies like next-generation sequencing have prohibitive costs. Furthermore, rapid detection would allow sanitary authorities to take rapid measures to limit the spread of the virus and therefore reduce the probability of new virus dispersion. With this methodological approach, 13 previously unreported diagnostic mutations among several Omicron lineages were found.

Degradation of PET Bottles by an Engineered Ideonella sakaiensis PETase.

Extensive plastic production has become a serious environmental and health problem due to the lack of efficient treatment of plastic waste. Polyethylene terephthalate (PET) is one of the most used polymers and is accumulating in landfills or elsewhere in nature at alarming rates. In recent years, enzymatic degradation of PET by Ideonella sakaiensis PETase (IsPETase), a cutinase-like enzyme, has emerged as a promising strategy to completely depolymerize this polymer into its building blocks. Here, inspired by the architecture of cutinases and lipases homologous to IsPETase and using 3D structure information of the enzyme, we rationally designed three mutations in IsPETase active site for enhancing its PET-degrading activity. In particular, the S238Y mutant, located nearby the catalytic triad, showed a degradation activity increased by 3.3-fold in comparison to the wild-type enzyme. Importantly, this structural modification favoured the function of the enzyme in breaking down highly crystallized (~31%) PET, which is found in commercial soft drink bottles. In addition, microscopical analysis of enzyme-treated PET samples showed that IsPETase acts better when the smooth surface of highly crystalline PET is altered by mechanical stress. These results represent important progress in the accomplishment of a sustainable and complete degradation of PET pollution.

Evolutionary analysis of endogenous intronic retroviruses in primates reveals an enrichment in transcription binding sites associated with key regulatory processes.

Background: Endogenous retroviruses (ERVs) are the result of the integration of retroviruses into host DNA following germline infection. Endogenous retroviruses are made up of three main genes: gag, pol, and env, each of which encodes viral proteins that can be conserved or not. ERVs have been observed in a wide range of vertebrate genomes and their functions are associated with viral silencing and gene regulation. Results: In this work, we studied the evolutionary history of endogenous retroviruses associated with five human genes (INPP5B, DET1, PSMA1, USH2A, and MACROD2), which are located within intron sections. To verify the retroviral origin of the candidates, several approaches were used to detect and locate ERV elements. Both orthologous and paralogous genes were identified by Ensembl and then analyzed for ERV presence using RetroTector. A phylogenetic tree was reconstructed to identify the minimum time point of ERV acquisition. From that search, we detected ERVs throughout the primate lineage and in some other groups. Also, we identified the minimum origin of the ERVs from the parvorder Catarrhini to the Homininae subfamily. Conclusions: With the data collected, and by observing the transcription factors annotated inside ERVs, we propose that these elements play a relevant role in gene expression regulation and they probably possess important features for tumorigenesis control.

The search for molecular mimicry in proteins carried by extracellular vesicles secreted by cells infected with Plasmodium falciparum.

Red blood cells infected with Plasmodium falciparum secrete extracellular vesicles in order to facilitate the survival and infection of human cells. Various researchers have studied the composition of these extracellular vesicles and identified the proteins contained inside. In this work, we used that information to detect potential P. falciparum molecules that could be imitating host proteins. We carried out several searches to detect sequences and structural similarities between the parasite and host. Additionally, the possibility of functional mimicry was explored in line with the potential role that each candidate can perform for the parasite inside the host. Lastly, we determined a set of eight sequences (mainly moonlighting proteins) with a remarkable resemblance to human proteins. Due to the resemblance observed, this study proposes the possibility that certain P. falciparum molecules carried by extracellular vesicles could be imitating human proteins to manipulate the host cell's physiology.

Analysis of DNA Polymerases Reveals Specific Genes Expansion in Leishmania and Trypanosoma spp.

Leishmaniasis and trypanosomiasis are largely neglected diseases prevailing in tropical and subtropical conditions. These are an arthropod-borne zoonosis that affects humans and some animals and is caused by infection with protozoan of the genera Leishmania and Trypanosoma, respectively. These parasites present high genomic plasticity and are able to adapt themselves to adverse conditions like the attack of host cells or toxicity induced by drug exposure. Different mechanisms allow these adapting responses induced by stress, such as mutation, chromosomal rearrangements, establishment of mosaic ploidies, and gene expansion. Here we describe how a subset of genes encoding for DNA polymerases implied in repairing/translesion (TLS) synthesis are duplicated in some pathogenic species of the Trypanosomatida order and a free-living species from the Bodonida order. These enzymes are both able to repair DNA, but are also error-prone under certain situations. We discuss about the possibility that these enzymes can act as a source of genomic variation promoting adaptation in trypanosomatids.

SARS-CoV-2, an evolutionary perspective of interaction with human ACE2 reveals undiscovered amino acids necessary for complex stability.

The emergence of SARS-CoV-2 has resulted in nearly 1,280,000 infections and 73,000 deaths globally so far. This novel virus acquired the ability to infect human cells using the SARS-CoV cell receptor hACE2. Because of this, it is essential to improve our understanding of the evolutionary dynamics surrounding the SARS-CoV-2 hACE2 interaction. One way theory predicts selection pressures should shape viral evolution is to enhance binding with host cells. We first assessed evolutionary dynamics in select betacoronavirus spike protein genes to predict whether these genomic regions are under directional or purifying selection between divergent viral lineages, at various scales of relatedness. With this analysis, we determine a region inside the receptor-binding domain with putative sites under positive selection interspersed among highly conserved sites, which are implicated in structural stability of the viral spike protein and its union with human receptor ACE2. Next, to gain further insights into factors associated with recognition of the human host receptor, we performed modeling studies of five different betacoronaviruses and their potential binding to hACE2. Modeling results indicate that interfering with the salt bridges at hot spot 353 could be an effective strategy for inhibiting binding, and hence for the prevention of SARS-CoV-2 infections. We also propose that a glycine residue at the receptor-binding domain of the spike glycoprotein can have a critical role in permitting bat SARS-related coronaviruses to infect human cells.

ShadowCaster: Compositional Methods under the Shadow of Phylogenetic Models to Detect Horizontal Gene Transfers in Prokaryotes.

Horizontal gene transfer (HGT) plays an important role for evolutionary innovations within prokaryotic communities and is a crucial event for their survival. Several computational approaches have arisen to identify HGT events in recipient genomes. However, this has been proven to be a complex task due to the generation of a great number of false positives and the prediction disagreement among the existing methods. Phylogenetic reconstruction methods turned out to be the most reliable ones, but they are not extensible to all genes/species and are computationally demanding when dealing with large datasets. In contrast, the so-called surrogate methods that use heuristic solutions either based on nucleotide composition patterns or phyletic distribution of BLAST hits can be applied easily to the genomic scale, but they fail in identifying common HGT events. Here, we present ShadowCaster, a hybrid approach that sequentially combines nucleotide composition-based predictions by support vector machines (SVMs) under the shadow of phylogenetic models independent of tree reconstruction, to improve the detection of HGT events in prokaryotes. ShadowCaster successfully predicted close and distant HGT events in both artificial and bacterial genomes. ShadowCaster detected HGT related to heavy metal resistance in the genome of Rhodanobacter denitrificans with higher accuracy than the most popular state-of-the-art computational approaches, encompassing most of the predicted cases made by other methods. ShadowCaster is released at the GitHub platform as an open-source software under the GPLv3 license.

A putative antimicrobial peptide from Hymenoptera in the megaplasmid pSCL4 of Streptomyces clavuligerus ATCC 27064 reveals a singular case of horizontal gene transfer with potential applications.

Streptomyces clavuligerus is a Gram-positive bacterium that is a high producer of secondary metabolites with industrial applications. The production of antibiotics such as clavulanic acid or cephamycin has been extensively studied in this species; nevertheless, other aspects, such as evolution or ecology, have received less attention. Furthermore, genes that arise from ancient events of lateral transfer have been demonstrated to be implicated in important functions of host species. This approximation discovered relevant genes that genomic analyses overlooked. Thus, we studied the impact of horizontal gene transfer in the S. clavuligerus genome. To perform this task, we applied whole-genome analysis to identify a laterally transferred sequence from different domains. The most relevant result was a putative antimicrobial peptide (AMP) with a clear origin in the Hymenoptera order of insects. Next, we determined that two copies of these genes were present in the megaplasmid pSCL4 but absent in the S. clavuligerus ATCC 27064 chromosome. Additionally, we found that these sequences were exclusive to the ATCC 27064 strain (and so were not present in any other bacteria) and we also verified the expression of the genes using RNAseq data. Next, we used several AMP predictors to validate the original annotation extracted from Hymenoptera sequences and explored the possibility that these proteins had post-translational modifications using peptidase cleavage prediction. We suggest that Hymenoptera AMP-like proteins of S. clavuligerus ATCC 27064 may be useful for both species adaptation and as an antimicrobial molecule with industrial applications.

DnaJ molecules as potential effectors in Meloidogyne arenaria. An unexplored group of proteins in plant parasitic nematodes.

Plant pathogenic organisms secrete proteins called effectors that recognize, infect and promote disease within host cells. Bacteria, like Pseudomona syringae, use effectors with DnaJ function to disrupt plant defenses. DnaJ proteins (also called Hsp40) are a group of co-chaperone molecules, which assist in the folding of proteins. Despite the described role of DnaJs as effectors in several groups of pathogens, this group of proteins has never been correlated with the infection process in plant parasitic nematodes. In this study, we analyze the importance of DnaJ for plant parasitic nematodes. To do that, we compare the number of DnaJ proteins in nematodes with different lifestyles. Then, we predict the secreted DnaJ proteins in order to detect effector candidates. We found that Meloidogyne species have more secreted DnaJs than the rest of the nematodes analyzed in the study. Particularly, M. arenaria possess the highest proportion of secreted DnaJ sequences in comparison to total DnaJ proteins. Furthermore, we found in this species at least five sequences with a putative nuclear localization signal, three of them with a serine rich region with an unknown function. Then, we chose one of these sequences (MG599854) to perform an expression analysis. We found that MG599854 is over-expressed from 3 days post inoculation onwards in tomato plants. Moreover, MG599854 seems to be enough to produce cell death in Nicotiana benthamiana under transient expression conditions. In concordance with our results, we propose that DnaJ proteins are a potential source of effector proteins in plant parasitic nematodes.

Ensemble-Based Modeling of Chemical Compounds with Antimalarial Activity.

BACKGROUND: Malaria or Paludism is a tropical disease caused by parasites of the Plasmodium genre and transmitted to humans through the bite of infected mosquitos of the Anopheles genre. This pathology is considered one of the first causes of death in tropical countries and, despite several existing therapies, they have a high toxicity. Computational methods based on Quantitative Structure- Activity Relationship studies have been widely used in drug design work flows. OBJECTIVE: The main goal of the current research is to develop computational models for the identification of antimalarial hit compounds. MATERIALS AND METHODS: For this, a data set suitable for the modeling of the antimalarial activity of chemical compounds was compiled from the literature and subjected to a thorough curation process. In addition, the performance of a diverse set of ensemble-based classification methodologies was evaluated and one of these ensembles was selected as the most suitable for the identification of antimalarial hits based on its virtual screening performance. Data curation was conducted to minimize noise. Among the explored ensemble-based methods, the one combining Genetic Algorithms for the selection of the base classifiers and Majority Vote for their aggregation showed the best performance. RESULTS: Our results also show that ensemble modeling is an effective strategy for the QSAR modeling of highly heterogeneous datasets in the discovery of potential antimalarial compounds. CONCLUSION: It was determined that the best performing ensembles were those that use Genetic Algorithms as a method of selection of base models and Majority Vote as the aggregation method.

The dilemma of bacterial expansins evolution. The unusual case of Streptomyces acidiscabies and Kutzneria sp. 744.

Expansins are a superfamily of proteins mainly present in plants that are also found in bacteria, fungi and amoebozoa. Expansin proteins bind the plant cells wall and relax the cellulose microfibrils without any enzymatic action. The evolution of this kind of proteins exposes a complex pattern of horizontal gene transferences that makes difficult to determine the precise origin of non-plant expansins. We performed a genome-wide search of inter-domain horizontal gene transfer events using Streptomyces species and found a plant-like expansin in the Streptomyces acidiscabies proteome. This finding leads us to study in deep the origin and the characteristics of this peculiar protein, also present in the species Kutzneria sp.744. Using phylogenetic analyses, we determine that indeed S. acidiscabies and Kutzneria sp.744 expansins are located inside the plants expansins A clade. Using secondary and tertiary structural information, we observed that the electrostatic potentials and the folding of expansins are similar, independently of the proteins' origin. Using all this information, we conclude that S. acidiscabies and Kutzneria sp.744 expansins have a plant origin but differ from plant and bacterial canonical expansins. This finding suggests that the experimental research around this kind of expansins can be promissory in the future.

Horizontal transfer of a subtilisin gene from plants into an ancestor of the plant pathogenic fungal genus Colletotrichum.

The genus Colletotrichum contains a large number of phytopathogenic fungi that produce enormous economic losses around the world. The effect of horizontal gene transfer (HGT) has not been studied yet in these organisms. Inter-Kingdom HGT into fungal genomes has been reported in the past but knowledge about the HGT between plants and fungi is particularly limited. We describe a gene in the genome of several species of the genus Colletotrichum with a strong resemblance to subtilisins typically found in plant genomes. Subtilisins are an important group of serine proteases, widely distributed in all of the kingdoms of life. Our hypothesis is that the gene was acquired by Colletotrichum spp. through (HGT) from plants to a Colletotrichum ancestor. We provide evidence to support this hypothesis in the form of phylogenetic analyses as well as a characterization of the similarity of the subtilisin at the primary, secondary and tertiary structural levels. The remarkable level of structural conservation of Colletotrichum plant-like subtilisin (CPLS) with plant subtilisins and the differences with the rest of Colletotrichum subtilisins suggests the possibility of molecular mimicry. Our phylogenetic analysis indicates that the HGT event would have occurred approximately 150-155 million years ago, after the divergence of the Colletotrichum lineage from other fungi. Gene expression analysis shows that the gene is modulated during the infection of maize by C. graminicola suggesting that it has a role in plant disease. Furthermore, the upregulation of the CPLS coincides with the downregulation of several plant genes encoding subtilisins. Based on the known roles of subtilisins in plant pathogenic fungi and the gene expression pattern that we observed, we postulate that the CPLSs have an important role in plant infection.