MaNmrA, a Negative Transcription Regulator in Nitrogen Catabolite Repression Pathway, Contributes to Nutrient Utilization, Stress Resistance, and Virulence in Entomopathogenic Fungus Metarhizium acridium

The NCR pathway plays an important regulatory role in the nitrogen metabolism of filamentous fungi. NmrA, a central negative regulatory protein in the NCR pathway and a key factor in sensing to the carbon metabolism, plays important roles in pathogenic fungal nutrition metabolism. In this study, we characterized the functions of MaNmrA in the insect pathogenic fungus M. acridum. Multiple sequence alignments found that the conserved domain (NAD/NADP binding domain) of MaNmrA was highly conservative with its homologues proteins. Deletion of MaNmrA improved the utilization of multiple carbon sources (such as glucose, mannose, sucrose, and trehalose) and non-preferred nitrogen sources (such as NaNO3 and urea), significantly delayed the conidial germination rate and reduced the conidial yield. The MaNmrA-disruption strain (ΔMaNmrA) significantly decreased tolerances to UV-B and heat-shock, and it also increased the sensitivity to the hypertonic substance sorbitol, oxygen stress substance H2O2, and cell wall destroyer calcofluor white, indicating that loss of MaNmrA affected cell wall integrity, tolerances to hypertonic and oxidative stress. Bioassays demonstrated that disruption of MaNmrA decreased the virulence in both topical inoculation and intrahemocoel injection tests. Further studies revealed that the appressorium formation, turgor pressure, and colonization in hemolymph were significantly reduced in the absence of MaNmrA. Our work will deepen the functional cognition of MaNmrA and make a contribution to the study of its homologous proteins.

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MaAreB, a GATA Transcription Factor, Is Involved in Nitrogen Source Utilization, Stress Tolerances and Virulence in Metarhizium acridum

Journal of Fungi ◽

10.3390/jof7070512 ◽

2021 ◽

Vol 7 (7) ◽

pp. 512

Author(s):

Chaochuang Li ◽

Qipei Zhang ◽

Yuxian Xia ◽

Kai Jin

Keyword(s):

Cell Wall ◽

Transcription Factor ◽

Functional Characterization ◽

Turgor Pressure ◽

Nitrogen Utilization ◽

Cell Wall Integrity ◽

Homologous Proteins ◽

Calcofluor White ◽

Metarhizium Acridum ◽

Gata Transcription Factor

The nitrogen catabolite repression (NCR) pathway is involved in nitrogen utilization, in which the global GATA transcription factor AreA plays an indispensable role and has been reported in many fungi. However, relatively few studies are focused on AreB, another GATA transcription factor in the NCR pathway and the functions of AreB are largely unknown in entomopathogenic fungi. Here, we characterized MaAreB in the model entomopathogenic fungus Metarhizium acridum. Sequence arrangement found that MaAreB had a conserved GATA zinc finger DNA binding domain and a leucine zipper domain. Disruption of MaAreB affected the nitrogen utilization and led to decelerated conidial germination and hyphal growth, decreased conidial yield, and lower tolerances to UV-B irradiation and heat-shock. Furthermore, the MaAreB mutant (ΔMaAreB) exhibited increased sensitivity to CFW (Calcofluor white), decreased cell wall contents (chitin and β-1,3-glucan) and reduced expression levels of some genes related to cell wall integrity, indicating that disruption of MaAreB affected the cell wall integrity. Bioassays showed that the virulence of the ΔMaAreB strain was decreased in topical inoculation but not in intra-hemocoel injection. Consistently, deletion of MaAreB severely impaired the appressorium formation and reduced the turgor pressure of appressorium. These results revealed that MaAreB regulated fungal nitrogen utilization, cell wall integrity and biological control potential, which would contribute to the functional characterization of AreB homologous proteins in other insect fungal pathogens, and even filamentous fungi.

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Cell Wall-Related Bionumbers and Bioestimates of Saccharomyces cerevisiae and Candida albicans

Eukaryotic Cell ◽

10.1128/ec.00250-13 ◽

2013 ◽

Vol 13 (1) ◽

pp. 2-9 ◽

Cited By ~ 58

Author(s):

Frans M. Klis ◽

Chris G. de Koster ◽

Stanley Brul

Keyword(s):

Saccharomyces Cerevisiae ◽

Cell Wall ◽

Candida Albicans ◽

Cell Size ◽

Pathogenic Fungus ◽

Turgor Pressure ◽

Hyphal Growth ◽

Biological Research ◽

Content Type ◽

Starting Point

ABSTRACTBionumbers and bioestimates are valuable tools in biological research. Here we focus on cell wall-related bionumbers and bioestimates of the budding yeastSaccharomyces cerevisiaeand the polymorphic, pathogenic fungusCandida albicans. We discuss the linear relationship between cell size and cell ploidy, the correlation between cell size and specific growth rate, the effect of turgor pressure on cell size, and the reason why using fixed cells for measuring cellular dimensions can result in serious underestimation ofin vivovalues. We further consider the evidence that individual buds and hyphae grow linearly and that exponential growth of the population results from regular formation of new daughter cells and regular hyphal branching. Our calculations show that hyphal growth allowsC. albicansto cover much larger distances per unit of time than the yeast mode of growth and that this is accompanied by strongly increased surface expansion rates. We therefore predict that the transcript levels of genes involved in wall formation increase during hyphal growth. Interestingly, wall proteins and polysaccharides seem barely, if at all, subject to turnover and replacement. A general lesson is how strongly most bionumbers and bioestimates depend on environmental conditions and genetic background, thus reemphasizing the importance of well-defined and carefully chosen culture conditions and experimental approaches. Finally, we propose that the numbers and estimates described here offer a solid starting point for similar studies of other cell compartments and other yeast species.

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Molecular Characterization of a Novel Fusarivirus Infecting the Plant-pathogenic Fungus Alternaria Solani

10.21203/rs.3.rs-216353/v1 ◽

2021 ◽

Author(s):

Jie Wei Gong ◽

Hong Liu ◽

Fei Xiao Zhu ◽

Yun Shi Zhao ◽

Le Jia Cheng ◽

...

Keyword(s):

Amino Acids ◽

Pathogenic Fungus ◽

Alternaria Solani ◽

Open Reading Frames ◽

Phytopathogenic Fungus ◽

Sequence Alignments ◽

Multiple Sequence ◽

Multiple Sequence Alignments ◽

Putative Protein

Abstract A novel mycovirus belonging to the proposed family "Fusariviridae" was discovered in Alternaria Solani by sequencing a double-stranded RNA extracted from this phytopathogenic fungus. The virus was tentatively named “Alternaria solani fusarivirus 1” (AsFV1). AsFV1 has a single-stranded positive-sense (+ssRNA) genome of 6,845 nucleotides containing three open reading frames (ORFs) and a poly(A) tail. The largest ORF, ORF1 encodes a large polypeptide of 1,556 amino acids (aa) with conserved RNA-dependent RNA polymerase and helicase domains. The ORF2 and ORF3 have overlapping regions, encoding a putative protein of 522 amino acids (aa) and a putative protein of 105 amino acids (aa) respectively, for which function is unknown now. Multiple sequence alignments and phylogenetic analysis revealed AsFV1 belonging to Fusariviridae. This is the first report of the full-length nucleotide sequence of a fusarivirus infected with Alternaria solani.

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HH-suite3 for fast remote homology detection and deep protein annotation

BMC Bioinformatics ◽

10.1186/s12859-019-3019-7 ◽

2019 ◽

Vol 20 (1) ◽

Cited By ~ 67

Author(s):

Martin Steinegger ◽

Markus Meier ◽

Milot Mirdita ◽

Harald Vöhringer ◽

Stephan J. Haunsberger ◽

...

Keyword(s):

Open Source ◽

Large Scale ◽

Message Passing Interface ◽

Viterbi Algorithm ◽

Sequence Similarity ◽

Pairwise Alignment ◽

Homology Detection ◽

Sequence Alignments ◽

Homologous Proteins ◽

Multiple Sequence

Abstract Background HH-suite is a widely used open source software suite for sensitive sequence similarity searches and protein fold recognition. It is based on pairwise alignment of profile Hidden Markov models (HMMs), which represent multiple sequence alignments of homologous proteins. Results We developed a single-instruction multiple-data (SIMD) vectorized implementation of the Viterbi algorithm for profile HMM alignment and introduced various other speed-ups. These accelerated the search methods HHsearch by a factor 4 and HHblits by a factor 2 over the previous version 2.0.16. HHblits3 is ∼10× faster than PSI-BLAST and ∼20× faster than HMMER3. Jobs to perform HHsearch and HHblits searches with many query profile HMMs can be parallelized over cores and over cluster servers using OpenMP and message passing interface (MPI). The free, open-source, GPLv3-licensed software is available at https://github.com/soedinglab/hh-suite. Conclusion The added functionalities and increased speed of HHsearch and HHblits should facilitate their use in large-scale protein structure and function prediction, e.g. in metagenomics and genomics projects.

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Prediction of Protein Sites and Physicochemical Properties Related to Functional Specificity

Bioengineering ◽

10.3390/bioengineering8120201 ◽

2021 ◽

Vol 8 (12) ◽

pp. 201

Author(s):

Florencio Pazos

Keyword(s):

Physicochemical Properties ◽

A Posteriori ◽

Sequence Alignments ◽

Homologous Proteins ◽

Functional Specificity ◽

Multiple Sequence ◽

Multiple Sequence Alignments ◽

Functional Sites ◽

Specificity Determining Positions ◽

Physicochemical Basis

Specificity Determining Positions (SDPs) are protein sites responsible for functional specificity within a family of homologous proteins. These positions are extracted from a family’s multiple sequence alignment and complement the fully conserved positions as predictors of functional sites. SDP analysis is now routinely used for locating these specificity-related sites in families of proteins of biomedical or biotechnological interest with the aim of mutating them to switch specificities or design new ones. There are many different approaches for detecting these positions in multiple sequence alignments. Nevertheless, existing methods report the potential SDP positions but they do not provide any clue on the physicochemical basis behind the functional specificity, which has to be inferred a-posteriori by manually inspecting these positions in the alignment. In this work, a new methodology is presented that, concomitantly with the detection of the SDPs, automatically provides information on the amino-acid physicochemical properties more related to the change in specificity. This new method is applied to two different multiple sequence alignments of homologous of the well-studied RasH protein representing different cases of functional specificity and the results discussed in detail.

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Rapid Redistribution of Phosphatidylinositol-(4,5)-Bisphosphate and Septins during the Candida albicans Response to Caspofungin

Antimicrobial Agents and Chemotherapy ◽

10.1128/aac.00112-12 ◽

2012 ◽

Vol 56 (9) ◽

pp. 4614-4624 ◽

Cited By ~ 24

Author(s):

Hassan Badrane ◽

M. Hong Nguyen ◽

Jill R. Blankenship ◽

Shaoji Cheng ◽

Binghua Hao ◽

...

Keyword(s):

Cell Wall ◽

Candida Albicans ◽

Fluorescent Protein ◽

Expression Patterns ◽

Regulatory Protein ◽

Wall Material ◽

Pleckstrin Homology Domain ◽

Calcofluor White ◽

Content Type ◽

Green Fluorescent

ABSTRACTWe previously showed that phosphatidylinositol-(4,5)-bisphosphate [PI(4,5)P2] and septin regulation play major roles in maintainingCandida albicanscell wall integrity in response to caspofungin and other stressors. Here, we establish a link between PI(4,5)P2 signaling and septin localization and demonstrate that rapid redistribution of PI(4,5)P2 and septins is part of the natural response ofC. albicansto caspofungin. First, we studied caspofungin-hypersusceptibleC. albicans irs4andinp51mutants, which have elevated PI(4,5)P2 levels due to loss of PI(4,5)P2-specific 5′-phosphatase activity. PI(4,5)P2 accumulated in discrete patches, rather than uniformly, along surfaces of mutants in yeast and filamentous morphologies, as visualized with a green fluorescent protein (GFP)-pleckstrin homology domain. The patches also contained chitin (calcofluor white staining) and cell wall protein Rbt5 (Rbt5-GFP). By transmission electron microscopy, patches corresponded to plasma membrane invaginations that incorporated cell wall material. Fluorescently tagged septins Cdc10 and Sep7 colocalized to these sites, consistent with well-described PI(4,5)P2-septin physical interactions. Based on expression patterns of cell wall damage response genes,irs4andinp51mutants were firmly positioned within a group of caspofungin-hypersusceptible, septin-regulatory protein kinase mutants.irs4andinp51were linked most closely to thegin4mutant by expression profiling, PI(4,5)P2-septin-chitin redistribution and other phenotypes. Finally, sublethal 5-min exposure of wild-typeC. albicansto caspofungin resulted in redistribution of PI(4,5)P2 and septins in a manner similar to those ofirs4,inp51, andgin4mutants. Taken together, our data suggest that theC. albicansIrs4-Inp51 5′-phosphatase complex and Gin4 function upstream of PI(4,5)P2 and septins in a pathway that helps govern responses to caspofungin.

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Recent Advances in Protein Homology Detection Propelled by Inter-Residue Interaction Map Threading

Frontiers in Molecular Biosciences ◽

10.3389/fmolb.2021.643752 ◽

2021 ◽

Vol 8 ◽

Author(s):

Sutanu Bhattacharya ◽

Rahmatullah Roche ◽

Md Hossain Shuvo ◽

Debswapna Bhattacharya

Keyword(s):

Structure Prediction ◽

Accurate Estimation ◽

Protein Homology ◽

Homology Detection ◽

Sequence Alignments ◽

Homologous Proteins ◽

Multiple Sequence ◽

Additional Information ◽

Residue Interaction ◽

Interaction Map

Sequence-based protein homology detection has emerged as one of the most sensitive and accurate approaches to protein structure prediction. Despite the success, homology detection remains very challenging for weakly homologous proteins with divergent evolutionary profile. Very recently, deep neural network architectures have shown promising progress in mining the coevolutionary signal encoded in multiple sequence alignments, leading to reasonably accurate estimation of inter-residue interaction maps, which serve as a rich source of additional information for improved homology detection. Here, we summarize the latest developments in protein homology detection driven by inter-residue interaction map threading. We highlight the emerging trends in distant-homology protein threading through the alignment of predicted interaction maps at various granularities ranging from binary contact maps to finer-grained distance and orientation maps as well as their combination. We also discuss some of the current limitations and possible future avenues to further enhance the sensitivity of protein homology detection.

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Enhancing coevolution-based contact prediction by imposing structural self-consistency of the contacts

10.1101/279190 ◽

2018 ◽

Author(s):

Maher M. Kassem ◽

Lars B. Christoffersen ◽

Andrea Cavalli ◽

Kresten Lindorff-Larsen

Keyword(s):

False Positive ◽

Structure Prediction ◽

Structural Information ◽

Protein Structures ◽

Sequence Alignments ◽

Homologous Proteins ◽

Multiple Sequence ◽

Contact Prediction ◽

Interaction Sites ◽

Self Consistency

AbstractBased on the development of new algorithms and growth of sequence databases, it has recently become possible to build robust and informative higher-order statistical sequence models based on large sets of aligned protein sequences. By disentangling direct and indirect effects, such models have proven useful to assess phenotypic landscapes, determine protein-protein interaction sites, and in de novo structure prediction. In the context of structure prediction, the sequence models are used to find pairs of residues that co-vary during evolution, and hence are likely to be in spatial proximity in the functional native protein. The accuracy of these algorithms, however, drop dramatically when the number of sequences in the alignment is small, and thus the highest ranking pairs may include a substantial number of false positive predictions. We have developed a method that we termed CE-YAPP (CoEvolution-YAPP), that is based on YAPP (Yet Another Peak Processor), which has been shown to solve a similar problem in NMR spectroscopy. By simultaneously performing structure prediction and contact assignment, CE-YAPP uses structural self-consistency as a filter to remove false positive contacts. At the same time CE-YAPP solves another problem, namely how many contacts to choose from the ordered list of covarying amino acid pairs. Our results show that CE-YAPP consistently and substantially improves contact prediction from multiple sequence alignments, in particular for proteins that are difficult targets. We further show that CE-YAPP can be integrated with many different contact prediction methods, and thus will benefit also from improvements in algorithms for sequence analyses. Finally, we show that the structures determined from CE-YAPP are also in better agreement with those determined using traditional methods in structural biology.Author summaryHomologous proteins generally have similar functions and three-dimensional structures. This in turn means that it is possible to extract structural information from a detailed analysis of a multiple sequence alignment of a protein sequence. In particular, it has been shown that global statistical analyses of such sequence alignments allows one to find pairs of residues that have covaried during evolution, and that such pairs are likely to be in close contact in the folded protein structure. Although these insights have led to important developments in our ability to predict protein structures, these methods generally result in many false positive contacts predicted when the number of homologous sequences is not large. To deal with this issue, we have developed CE-YAPP, a method that can take a noisy set of predicted contacts as input and robustly detect many incorrectly predicted contacts within these. More specifically, our method performs simultaneous structure prediction and contact assignment so as to use structural self-consistency as a filter for erroneous predictions. In this way, CE-YAPP improves contact and structure predictions, and thus advances our ability to extract structural information from analyses of the evolutionary record of a protein.

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