FPD: A comprehensive phosphorylation database in fungi

MFPSP: Identification of fungal species-specific phosphorylation site using offspring competition-based genetic algorithm

Protein phosphorylation is essential in various signal transduction and cellular processes. To date, most tools are designed for model organisms, but only a handful of methods are suitable for predicting task in fungal species, and their performance still leaves much to be desired. In this study, a novel tool called MFPSP is developed for phosphorylation site prediction in multi-fungal species. The amino acids sequence features were derived from physicochemical and distributed information, and an offspring competition-based genetic algorithm was applied for choosing the most effective feature subset. The comparison results shown that MFPSP achieves a more advanced and balanced performance to several state-of-the-art available toolkits. Feature contribution and interaction exploration indicating the proposed model is efficient in uncovering concealed patterns within sequence. We anticipate MFPSP to serve as a valuable bioinformatics tool and benefiting practical experiments by pre-screening potential phosphorylation sites and enhancing our functional understanding of phosphorylation modifications in fungi. The source code and datasets are accessible at https://github.com/AI4HKB/MFPSP/.

A Review of Machine Learning and Algorithmic Methods for Protein Phosphorylation Site Prediction

Post-translational modifications (PTMs) have key roles in extending the functional diversity of proteins and, as a result, regulating diverse cellular processes in prokaryotic and eukaryotic organisms. Phosphorylation modification is a vital PTM that occurs in most proteins and plays a significant role in many biological processes. Disorders in the phosphorylation process lead to multiple diseases, including neurological disorders and cancers. The purpose of this review is to organize this body of knowledge associated with phosphorylation site (p-site) prediction to facilitate future research in this field. At first, we comprehensively review all related databases and introduce all steps regarding dataset creation, data preprocessing, and method evaluation in p-site prediction. Next, we investigate p-site prediction methods, which are divided into two computational groups: algorithmic and machine learning (ML). Additionally, it is shown that there are basically two main approaches for p-site prediction by ML: conventional and end-to-end deep learning methods, both of which are given an overview. Moreover, this review introduces the most important feature extraction techniques, which have mostly been used in p-site prediction. Finally, we create three test sets from new proteins related to the released version of the database of protein post-translational modifications (dbPTM) in 2022 based on general and human species. Evaluating online p-site prediction tools on newly added proteins introduced in the dbPTM 2022 release, distinct from those in the dbPTM 2019 release, reveals their limitations. In other words, the actual performance of these online p-site prediction tools on unseen proteins is notably lower than the results reported in their respective research papers.

ScerePhoSite: An interpretable method for identifying fungal phosphorylation sites in proteins using sequence-based features

Protein phosphorylation plays a vital role in signal transduction pathways and diverse cellular processes. To date, a tremendous number of in silico tools have been designed for phosphorylation site identification, but few of them are suitable for the identification of fungal phosphorylation sites. This largely hampers the functional investigation of fungal phosphorylation. In this paper, we present ScerePhoSite, a machine learning method for fungal phosphorylation site identification. The sequence fragments are represented by hybrid physicochemical features, and then LGB-based feature importance combined with the sequential forward search method is used to choose the optimal feature subset. As a result, ScerePhoSite surpasses current available tools and shown a more robust and balanced performance. Furthermore, the impact and contribution of specific features on the model performance were investigated by SHAP values. We expect ScerePhoSite to be a useful bioinformatics tool that complements hands-on experiments for the pre-screening of possible phosphorylation sites and facilitates our functional understanding of phosphorylation modification in fungi. The source code and datasets are accessible at https://github.com/wangchao-malab/ScerePhoSite/.

Evolutionary Divergence of Phosphorylation to Regulate Interactive Protein Networks in Lower and Higher Species

The phosphorylation of proteins affects their functions in extensively documented circumstances. However, the role of phosphorylation in many interactive networks of proteins remains very elusive due to the experimental limits of exploring the transient interaction in a large complex of assembled proteins induced by stimulation. Previous studies have suggested that phosphorylation is a recent evolutionary process that differently regulates ortholog proteins in numerous lineages of living organisms to create new functions. Despite the fact that numerous phospho-proteins have been compared between species, little is known about the organization of the full phospho-proteome, the role of phosphorylation to orchestrate large interactive networks of proteins, and the intertwined phospho-landscape in these networks. In this report, we aimed to investigate the acquired role of phosphate addition in the phenomenon of protein networking in different orders of living organisms. Our data highlighted the acquired status of phosphorylation in organizing large, connected assemblages in Homo sapiens. The protein networking guided by phosphorylation turned out to be prominent in humans, chaotic in yeast, and weak in flies. Furthermore, the molecular functions of GO annotation enrichment regulated by phosphorylation were found to be drastically different between flies, yeast, and humans, suggesting an evolutionary drift specific to each species.

Post-translational modifications drive secondary metabolite biosynthesis in Aspergillus: a review

Post‐translational modifications (PTMs) are important for protein function and regulate multiple cellular processes and secondary metabolites (SMs) in fungi. Aspergillus species belong to a genus renown for an abundance of bioactive secondary metabolites, many important as toxins, pharmaceuticals and in industrial production. The genes required for secondary metabolites are typically co‐localized in biosynthetic gene clusters (BGCs), which often localize in heterochromatic regions of genome and are ‘turned off’ under laboratory condition. Efforts have been made to ‘turn on’ these BGCs by genetic manipulation of histone modifications, which could convert the heterochromatic structure to euchromatin. Additionally, non‐histone PTMs also play critical roles in the regulation of secondary metabolism. In this review, we collate the known roles of epigenetic and PTMs on Aspergillus SM production. We also summarize the proteomics approaches and bioinformatics tools for PTM identification and prediction and provide future perspectives on the emerging roles of PTM on regulation of SM biosynthesis in Aspergillus and other fungi.

Updates on the Functions and Molecular Mechanisms of the Genes Involved in Aspergillus flavus Development and Biosynthesis of Aflatoxins

Aspergillus flavus (A. flavus) is a ubiquitous and opportunistic fungal pathogen that causes invasive and non-invasive aspergillosis in humans and animals. This fungus is also capable of infecting a large number of agriculture crops (e.g., peanuts, maze, cotton seeds, rice, etc.), causing economic losses and posing serious food-safety concerns when these crops are contaminated with aflatoxins, the most potent naturally occurring carcinogens. In particular, A. flavus and aflatoxins are intensely studied, and they continue to receive considerable attention due to their detrimental effects on humans, animals, and crops. Although several studies have been published focusing on the biosynthesis of the aforementioned secondary metabolites, some of the molecular mechanisms (e.g., posttranslational modifications, transcription factors, transcriptome, proteomics, metabolomics and transcriptome, etc.) involved in the fungal development and aflatoxin biosynthesis in A. flavus are still not fully understood. In this study, a review of the recently published studies on the function of the genes and the molecular mechanisms involved in development of A. flavus and the production of its secondary metabolites is presented. It is hoped that the information provided in this review will help readers to develop effective strategies to reduce A. flavus infection and aflatoxin production.

Effects of antifungal agents on the fungal proteome: informing on mechanisms of sensitivity and resistance

INTRODUCTION

Antifungal agents are essential in the fight against serious fungal disease, however emerging resistance is threatening an already limited collection of therapeutics. Proteomic analyses of effects of antifungal agents can expand our understanding of multifactorial mechanisms of action and have also proven valuable to elucidate proteomic changes associated with antifungal resistance.

AREAS COVERED

This review covers the application of proteomic techniques to examine sensitivity and resistance to antifungals including commonly used therapeutics, amphotericin B, echinocandins and the azoles, based predominantly on studies involving Aspergillus fumigatus, Candida albicans and Candida glabrata from the last 10 years. In addition, non-clinical antimicrobial agents are also discussed, which highlight the potential of proteomics to identify new antifungal targets.

EXPERT COMMENTARY

Fungal proteomics has evolved in the last decade with increased genome availability and developments in mass spectrometry. Collectively, these have led to the advancement of proteomic techniques, allowing increased coverage of the proteome. Gel-based proteomics laid the foundation for these types of studies, which has now shifted to the more powerful gel-free proteomics. This has resulted in the identification of key mediators and potential biomarkers of antifungal resistance, as well as elucidating the mechanisms of action of novel and established antifungal agents.

Mitochondrial protein phosphorylation in yeast revisited

Protein phosphorylation is one of the best-known post-translational modifications occurring in all domains of life. In eukaryotes, protein phosphorylation affects all cellular compartments including mitochondria. High-throughput techniques of mass spectrometry combined with cell fractionation and biochemical methods yielded thousands of phospho-sites on hundreds of mitochondrial proteins. We have compiled the information on mitochondrial protein kinases and phosphatases and their substrates in Saccharomyces cerevisiae and provide the current state-of-the-art overview of mitochondrial protein phosphorylation in this model eukaryote. Using several examples, we describe emerging features of the yeast mitochondrial phosphoproteome and present challenges lying ahead in this exciting field.

Fungi.guru: Comparative genomic and transcriptomic resource for the fungi kingdom

The fungi kingdom is composed of eukaryotic heterotrophs, which are responsible for balancing the ecosystem and play a major role as decomposers. They also produce a vast diversity of secondary metabolites, which have antibiotic or pharmacological properties. However, our lack of knowledge of gene function in fungi precludes us from tailoring them to our needs and tapping into their metabolic diversity. To help remedy this, we gathered genomic and gene expression data of 19 most widely-researched fungi to build an online tool, fungi.guru, which contains tools for cross-species identification of conserved pathways, functional gene modules, and gene families. We exemplify how our tool can elucidate the molecular function, biological process and cellular component of genes involved in various biological processes, by identifying a secondary metabolite pathway producing gliotoxin in Aspergillus fumigatus, the catabolic pathway of cellulose in Coprinopsis cinerea and the conserved DNA replication pathway in Fusarium graminearum and Pyricularia oryzae. The tool is available at www.fungi.guru.

Yeast Ppz1 protein phosphatase toxicity involves the alteration of multiple cellular targets

Control of the protein phosphorylation status is a major mechanism for regulation of cellular processes, and its alteration often lead to functional disorders. Ppz1, a protein phosphatase only found in fungi, is the most toxic protein when overexpressed in Saccharomyces cerevisiae. To investigate the molecular basis of this phenomenon, we carried out combined genome-wide transcriptomic and phosphoproteomic analyses. We have found that Ppz1 overexpression causes major changes in gene expression, affecting ~ 20% of the genome, together with oxidative stress and increase in total adenylate pools. Concurrently, we observe changes in the phosphorylation pattern of near 400 proteins (mainly dephosphorylated), including many proteins involved in mitotic cell cycle and bud emergence, rapid dephosphorylation of Snf1 and its downstream transcription factor Mig1, and phosphorylation of Hog1 and its downstream transcription factor Sko1. Deletion of HOG1 attenuates the growth defect of Ppz1-overexpressing cells, while that of SKO1 aggravates it. Our results demonstrate that Ppz1 overexpression has a widespread impact in the yeast cells and reveals new aspects of the regulation of the cell cycle.

Phosphoproteomic analysis of STRIPAK mutants identifies a conserved serine phosphorylation site in PAK kinase CLA4 to be important in fungal sexual development and polarized growth

The highly conserved striatin-interacting phosphatases and kinases (STRIPAK) complex regulates phosphorylation/dephosphorylation of developmental proteins in eukaryotic microorganisms, animals and humans. To first identify potential targets of STRIPAK, we performed extensive isobaric tags for relative and absolute quantification-based proteomic and phosphoproteomic analyses in the filamentous fungus Sordaria macrospora. In total, we identified 4,193 proteins and 2,489 phosphoproteins, which are represented by 10,635 phosphopeptides. By comparing phosphorylation data from wild type and mutants, we identified 228 phosphoproteins to be regulated in all three STRIPAK mutants, thus representing potential targets of STRIPAK. To provide an exemplarily functional analysis of a STRIPAK-dependent phosphorylated protein, we selected CLA4, a member of the conserved p21-activated kinase family. Functional characterization of the ∆cla4 deletion strain showed that CLA4 controls sexual development and polarized growth. To determine the functional relevance of CLA4 phosphorylation and the impact of specific phosphorylation sites on development, we next generated phosphomimetic and -deficient variants of CLA4. This analysis identified (de)phosphorylation of a highly conserved serine (S685) residue in the catalytic domain of CLA4 as being important for fungal cellular development. Collectively, these analyses significantly contribute to the understanding of the mechanistic function of STRIPAK as a phosphatase and kinase signaling complex.

EPSD: a well-annotated data resource of protein phosphorylation sites in eukaryotes

As an important post-translational modification (PTM), protein phosphorylation is involved in the regulation of almost all of biological processes in eukaryotes. Due to the rapid progress in mass spectrometry-based phosphoproteomics, a large number of phosphorylation sites (p-sites) have been characterized but remain to be curated. Here, we briefly summarized the current progresses in the development of data resources for the collection, curation, integration and annotation of p-sites in eukaryotic proteins. Also, we designed the eukaryotic phosphorylation site database (EPSD), which contained 1 616 804 experimentally identified p-sites in 209 326 phosphoproteins from 68 eukaryotic species. In EPSD, we not only collected 1 451 629 newly identified p-sites from high-throughput (HTP) phosphoproteomic studies, but also integrated known p-sites from 13 additional databases. Moreover, we carefully annotated the phosphoproteins and p-sites of eight model organisms by integrating the knowledge from 100 additional resources that covered 15 aspects, including phosphorylation regulator, genetic variation and mutation, functional annotation, structural annotation, physicochemical property, functional domain, disease-associated information, protein-protein interaction, drug-target relation, orthologous information, biological pathway, transcriptional regulator, mRNA expression, protein expression/proteomics and subcellular localization. We anticipate that the EPSD can serve as a useful resource for further analysis of eukaryotic phosphorylation. With a data volume of 14.1 GB, EPSD is free for all users at http://epsd.biocuckoo.cn/.

Insights into an unusual Auxiliary Activity 9 family member lacking the histidine brace motif of lytic polysaccharide monooxygenases

Lytic polysaccharide monooxygenases (LPMOs) are redox-enzymes involved in biomass degradation. All characterized LPMOs possess an active site of two highly conserved histidine residues coordinating a copper ion (the histidine brace), which are essential for LPMO activity. However, some protein sequences that belong to the AA9 LPMO family display a natural N-terminal His to Arg substitution (Arg-AA9). These are found almost entirely in the phylogenetic fungal class Agaricomycetes, associated with wood decay, but no function has been demonstrated for any Arg-AA9. Through bioinformatics, transcriptomic, and proteomic analyses we present data, which suggest that Arg-AA9 proteins could have a hitherto unidentified role in fungal degradation of lignocellulosic biomass in conjunction with other secreted fungal enzymes. We present the first structure of an Arg-AA9, LsAA9B, a naturally occurring protein from Lentinus similis The LsAA9B structure reveals gross changes in the region equivalent to the canonical LPMO copper-binding site, whereas features implicated in carbohydrate binding in AA9 LPMOs have been maintained. We obtained a structure of LsAA9B with xylotetraose bound on the surface of the protein although with a considerably different binding mode compared with other AA9 complex structures. In addition, we have found indications of protein phosphorylation near the N-terminal Arg and the carbohydrate-binding site, for which the potential function is currently unknown. Our results are strong evidence that Arg-AA9s function markedly different from canonical AA9 LPMO, but nonetheless, may play a role in fungal conversion of lignocellulosic biomass.

Transcriptome analysis of virulence-differentiated Fusarium oxysporum f. sp. cucumerinum isolates during cucumber colonisation reveals pathogenicity profiles

BACKGROUND

Cucumber Fusarium wilt, caused by Fusarium oxysporum f. sp. cucumerinum (Foc), is one of the most notorious diseases in cucumber production. Our previous research showed the virulence of Foc significantly increases over consecutive rounds of infection in a resistant cultivar. To understand the virulence variation of Foc under host pressure, the mildly virulent strain foc-3b (WT) and its virulence-enhanced variant Ra-4 (InVir) were selected and their transcriptome profiles in infected cucumber roots were analyzed at 24 h after inoculation (hai) and 120 hai.

RESULTS

A series of differentially expressed genes (DEGs) potentially involved in fungal pathogenicity and pathogenicity variation were identified and prove mainly involved in metabolic, transport, oxidation-reduction, cell wall degradation, macromolecules modification, and stress and defense. Among these DEGs, 190 up- and 360 down-regulated genes were expressed in both strains, indicating their importance in Foc infection. Besides, 286 and 366 DEGs showed up-regulated expression, while 492 and 214 showed down-regulated expression in InVir at 24 and 120 hai, respectively. These DEGs may be involved in increased virulence. Notably, transposases were more active in InVir than WT, indicating transposons may contribute to adaptive evolution.

CONCLUSIONS

By a comparative transcriptome analysis of the mildly and highly virulent strains of Foc during infection of cucumber, a series of DEGs were identified that may be associated with virulence. Hence, this study provides new insight into the transcriptomic profile underlying pathogenicity and virulence differentiation of Foc.

The Effect of FG-Nup Phosphorylation on NPC Selectivity: A One-Bead-Per-Amino-Acid Molecular Dynamics Study

Nuclear pore complexes (NPCs) are large protein complexes embedded in the nuclear envelope separating the cytoplasm from the nucleoplasm in eukaryotic cells. They function as selective gates for the transport of molecules in and out of the nucleus. The inner wall of the NPC is coated with intrinsically disordered proteins rich in phenylalanine-glycine repeats (FG-repeats), which are responsible for the intriguing selectivity of NPCs. The phosphorylation state of the FG-Nups is controlled by kinases and phosphatases. In the current study, we extended our one-bead-per-amino-acid (1BPA) model for intrinsically disordered proteins to account for phosphorylation. With this, we performed molecular dynamics simulations to probe the effect of phosphorylation on the Stokes radius of isolated FG-Nups, and on the structure and transport properties of the NPC. Our results indicate that phosphorylation causes a reduced attraction between the residues, leading to an extension of the FG-Nups and the formation of a significantly less dense FG-network inside the NPC. Furthermore, our simulations show that upon phosphorylation, the transport rate of inert molecules increases, while that of nuclear transport receptors decreases, which can be rationalized in terms of modified hydrophobic, electrostatic, and steric interactions. Altogether, our models provide a molecular framework to explain how extensive phosphorylation of FG-Nups decreases the selectivity of the NPC.

Computational prediction and analysis of species-specific fungi phosphorylation via feature optimization strategy

Protein phosphorylation is a reversible and ubiquitous post-translational modification that primarily occurs at serine, threonine and tyrosine residues and regulates a variety of biological processes. In this paper, we first briefly summarized the current progresses in computational prediction of eukaryotic protein phosphorylation sites, which mainly focused on animals and plants, especially on human, with a less extent on fungi. Since the number of identified fungi phosphorylation sites has greatly increased in a wide variety of organisms and their roles in pathological physiology still remain largely unknown, more attention has been paid on the identification of fungi-specific phosphorylation. Here, experimental fungi phosphorylation sites data were collected and most of the sites were classified into different types to be encoded with various features and trained via a two-step feature optimization method. A novel method for prediction of species-specific fungi phosphorylation-PreSSFP was developed, which can identify fungi phosphorylation in seven species for specific serine, threonine and tyrosine residues (http://computbiol.ncu.edu.cn/PreSSFP). Meanwhile, we critically evaluated the performance of PreSSFP and compared it with other existing tools. The satisfying results showed that PreSSFP is a robust predictor. Feature analyses exhibited that there have some significant differences among seven species. The species-specific prediction via two-step feature optimization method to mine important features for training could considerably improve the prediction performance. We anticipate that our study provides a new lead for future computational analysis of fungi phosphorylation.