CoChat
Sign Up
Cited by 19Plant-Microbe Interactions and ImmunityFungal and yeast genetics researchImmune Response and Inflammation

The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.

Exploring a diverse world of effector domains and amyloid signaling motifs in fungal NLR proteins

Open access
Wojciechowski, Jakub W., Tekoglu, Emirhan, Gąsior-Głogowska, Marlena, Coustou, Virginie, Szulc, Natalia, Szefczyk, Monika, Kopaczyńska, Marta, Saupe, Sven J., Dyrka, Witold·2022·PLOS Computational Biology
DOI 10.1371/journal.pcbi.1010787PMC PMC9815663

Published version of a preprint

Open this paper in CoChat — free accountOpen PDF

Abstract

NLR proteins are intracellular receptors constituting a conserved component of the innate immune system of cellular organisms. In fungi, NLRs are characterized by high diversity of architectures and presence of amyloid signaling. Here, we explore the diverse world of effector and signaling domains of fungal NLRs using state-of-the-art bioinformatic methods including MMseqs2 for fast clustering, probabilistic context-free grammars for sequence analysis, and AlphaFold2 deep neural networks for structure prediction. In addition to substantially improving the overall annotation, especially in basidiomycetes, the study identifies novel domains and reveals the structural similarity of MLKL-related HeLo- and Goodbye-like domains forming the most abundant superfamily of fungal NLR effectors. Moreover, compared to previous studies, we found several times more amyloid motif instances, including novel families, and validated aggregating and prion-forming properties of the most abundant of them in vitro and in vivo . Also, through an extensive in silico search, the NLR-associated amyloid signaling was identified in basidiomycetes. The emerging picture highlights similarities and differences in the NLR architectures and amyloid signaling in ascomycetes, basidiomycetes and other branches of life.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1371/journal.pcbi.1010787

Cites

5 of 5 references verified0 citation errors · 0 not checkable

Statistics

Figures

Fig 1 Fungal NLR N-termini. a) Major general architectures; b) N-termini length distribution with taxonomic division, c) Same data scaled to 100% for each length range; Annotation coverage with regard to d) N-terminus length, e) taxonomic division; f) Annotation coverage of the MMSeqs clustered N-termini with regard to presence of taxonomically distant homologs in UniRef top hits (see Results). Euk. denotes Eukaryota, off Euk. category includes Bacteria, Archaea and Viruses. Colored bars indicate fraction of Pfam & inhouse annotated sequences (blue: only direct Pfam hits, violet: direct and with clustering & HHblits, rose: only with clustering & HHblits). Inhouse profiles were used only for direct Pfam searches. g) Distribution of domain families. Additional non-Pfam annotations included, see Results and Methods. N-termini shorter than 20 amino acids are distinguished, as unlikely to contain functional domains.
Fig 1 Fungal NLR N-termini. a) Major general architectures; b) N-termini length distribution with taxonomic division, c) Same data scaled to 100% for each length range; Annotation coverage with regard to d) N-terminus length, e) taxonomic division; f) Annotation coverage of the MMSeqs clustered N-termini with regard to presence of taxonomically distant homologs in UniRef top hits (see Results). Euk. denotes Eukaryota, off Euk. category includes Bacteria, Archaea and Viruses. Colored bars indicate fraction of Pfam & inhouse annotated sequences (blue: only direct Pfam hits, violet: direct and with clustering & HHblits, rose: only with clustering & HHblits). Inhouse profiles were used only for direct Pfam searches. g) Distribution of domain families. Additional non-Pfam annotations included, see Results and Methods. N-termini shorter than 20 amino acids are distinguished, as unlikely to contain functional domains.CC BY · PubMed Central
Fig 2 MLKL-like N-termini. a) Fingerprint alignment of the doubly (Goodbye-like & Helo-like) annotated OBZ65626 cluster including non-redundant sequences with direct Pfam annotations. The alignment was truncated C-terminally. Darker shade implies higher conservation, while gaps are represented as lines. Columns matched with Pfam profiles of MLKL-like domains are indicated with brown bars. Columns corresponding to helices in a predicted OBZ65626 model are indicated with solid magenta boxes. Columns alignable to the human MLKL structure are framed with a brown dashed line. Columns corresponding to helices in the aligned MLKL structure are indicated with dashed magenta boxes. b) The human MLKL structure (pdb:6zvoA). c) Structural models of various MLKL-like domains predicted with AlphaFold2 (see Methods). Regions aligned to the human MLKL structure with TM-align are shown in brown. Rainbow colors indicate model quality in terms of pLDDT (below or 50: red, 60: yellow, 70: green, 80: cyan, above 90: blue).
Fig 2 MLKL-like N-termini. a) Fingerprint alignment of the doubly (Goodbye-like & Helo-like) annotated OBZ65626 cluster including non-redundant sequences with direct Pfam annotations. The alignment was truncated C-terminally. Darker shade implies higher conservation, while gaps are represented as lines. Columns matched with Pfam profiles of MLKL-like domains are indicated with brown bars. Columns corresponding to helices in a predicted OBZ65626 model are indicated with solid magenta boxes. Columns alignable to the human MLKL structure are framed with a brown dashed line. Columns corresponding to helices in the aligned MLKL structure are indicated with dashed magenta boxes. b) The human MLKL structure (pdb:6zvoA). c) Structural models of various MLKL-like domains predicted with AlphaFold2 (see Methods). Regions aligned to the human MLKL structure with TM-align are shown in brown. Rainbow colors indicate model quality in terms of pLDDT (below or 50: red, 60: yellow, 70: green, 80: cyan, above 90: blue).CC BY · PubMed Central
Fig 3 Amyloid-like motifs in short N-termini of NLRs. Clusters of N-termini containing sequences resembling bacterial amyloid signaling motifs were identified using a probabilistic grammatical model [52]. Motifs were extracted with MEME [88] and iteratively refined with profile HMMs. (a) Profile HMM-based motif logos—grouped according to overlapping hits in NLR N-termini, as shown in panel (b) Overlapping hits in NLR N-termini. See Results and Methods for details. (c) Stacked histogram of motif hits positions in NLR N-termini for the five largest motif families, color-coded as in panel (a)).
Fig 3 Amyloid-like motifs in short N-termini of NLRs. Clusters of N-termini containing sequences resembling bacterial amyloid signaling motifs were identified using a probabilistic grammatical model [52]. Motifs were extracted with MEME [88] and iteratively refined with profile HMMs. (a) Profile HMM-based motif logos—grouped according to overlapping hits in NLR N-termini, as shown in panel (b) Overlapping hits in NLR N-termini. See Results and Methods for details. (c) Stacked histogram of motif hits positions in NLR N-termini for the five largest motif families, color-coded as in panel (a)).CC BY · PubMed Central
Fig 4 Potentially interacting amyloid-like motifs in Agaricomycetes. (a) Motif logos, sequence alignments and domain architectures of selected motif instances. (b) Schematic representation of a cluster of amyloid-like motifs in contig SPHSTscaffold_52 from genome assembly GCA_000827215.1 of Sphaerobolus stellatus SS14. (c) Multiple sequence alignment of motif instances in (b).
Fig 4 Potentially interacting amyloid-like motifs in Agaricomycetes. (a) Motif logos, sequence alignments and domain architectures of selected motif instances. (b) Schematic representation of a cluster of amyloid-like motifs in contig SPHSTscaffold_52 from genome assembly GCA_000827215.1 of Sphaerobolus stellatus SS14. (c) Multiple sequence alignment of motif instances in (b).CC BY · PubMed Central
Fig 5 The PUASM motif. Alignment of the PUASM sequence pairs (a) from effector C-terminus (left) and NLR N-terminus (right). Colors indicate residue hydrophobicity, curly brackets—the motif ranges. Deconvolution of ATR–FTIR spectra of air-dried peptide films of EQB50682.1_332_355 (bc) and EQB50683.1_9_31 (de) in the amide bands region (1750–1500 cm−1). Spectra registered at 20°C (68°F) after dissolving (bd) or after 40 days of incubation at 37°C (98.6°F) (ce). AFM images with cross-section profiles of peptides EQB50682.1_332_355 (fh) and EQB50683.1_9_31 (gi). Samples imaged after dissolving (fg) or after 40 days of incubation at 37°C (98.6°F) (hi).
Fig 5 The PUASM motif. Alignment of the PUASM sequence pairs (a) from effector C-terminus (left) and NLR N-terminus (right). Colors indicate residue hydrophobicity, curly brackets—the motif ranges. Deconvolution of ATR–FTIR spectra of air-dried peptide films of EQB50682.1_332_355 (bc) and EQB50683.1_9_31 (de) in the amide bands region (1750–1500 cm−1). Spectra registered at 20°C (68°F) after dissolving (bd) or after 40 days of incubation at 37°C (98.6°F) (ce). AFM images with cross-section profiles of peptides EQB50682.1_332_355 (fh) and EQB50683.1_9_31 (gi). Samples imaged after dissolving (fg) or after 40 days of incubation at 37°C (98.6°F) (hi).CC BY · PubMed Central
Fig 6 Expression of GFP/RFP-fused PUASM motifs in Podospora anserina. a) Micrographs of P. anserina strains expressing molecular fusions of PUASM with GFP or RFP, as indicated on the left; scale bar: 5 μm. Strains were analyzed in their initial state after transfection (left panels marked) and either after several days of subculturing (middle panels, spontanous foci formation) or after cytoplasmic contact with a strain expressing GFP–PUASM in the foci state (right panels, induced foci formation). Note that the GFP–PUASM construct (but not PUASM–RFP and PUASM–GFP) leads to spontaneous and induced foci-formation. Quantification of the rate of foci formation is given in Table F in S1 Text. b) Micrographs of strains expressing GFP–BASS3—positive control for the spontanous foci formation (BASS3 motif of WP_037701008.1 of Streptomyces atratus, positions 70 to 124, left panel), and two GFP–BASS3 mutants—negative controls (Q113P, middle, and Q120P, right panel).
Fig 6 Expression of GFP/RFP-fused PUASM motifs in Podospora anserina. a) Micrographs of P. anserina strains expressing molecular fusions of PUASM with GFP or RFP, as indicated on the left; scale bar: 5 μm. Strains were analyzed in their initial state after transfection (left panels marked) and either after several days of subculturing (middle panels, spontanous foci formation) or after cytoplasmic contact with a strain expressing GFP–PUASM in the foci state (right panels, induced foci formation). Note that the GFP–PUASM construct (but not PUASM–RFP and PUASM–GFP) leads to spontaneous and induced foci-formation. Quantification of the rate of foci formation is given in Table F in S1 Text. b) Micrographs of strains expressing GFP–BASS3—positive control for the spontanous foci formation (BASS3 motif of WP_037701008.1 of Streptomyces atratus, positions 70 to 124, left panel), and two GFP–BASS3 mutants—negative controls (Q113P, middle, and Q120P, right panel).CC BY · PubMed Central

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 5 references

Research works printed but not linked: 134

  1. JDG Jones, 2016, Intracellular innate immune surveillance devices in plants and animals, Science, 354, aaf6395, 10.1126/science.aaf6395 · DOI
  2. J Uehling, 2017, Do fungi have an innate immune response? An NLR-based comparison to plant and animal immune systems, PLoS Pathogens, 13, e1006578, 10.1371/journal.ppat.1006578 · DOI
  3. Z Duxbury, 2021, A Comparative Overview of the Intracellular Guardians of Plants and Animals: NLRs in Innate Immunity and Beyond, Annual Review of Plant Biology, 72, 155, 10.1146/annurev-arplant-080620-104948 · DOI
  4. EV Koonin, 2002, Origin and evolution of eukaryotic apoptosis: the bacterial connection, Cell Death & Differentiation, 9, 394, 10.1038/sj.cdd.4400991 · DOI
  5. A Daskalov, 2020, NLR Function in Fungi as Revealed by the Study of Self/Non-self Recognition Systems, 123
  6. Y Xiong, 2020, Resistosome and inflammasome: platforms mediating innate immunity, Current opinion in plant biology, 56, 47, 10.1016/j.pbi.2020.03.010 · DOI
  7. G Bi, 2021, Regulation of Cell Death and Signaling by Pore-Forming Resistosomes, Annual review of phytopathology, 59, 239, 10.1146/annurev-phyto-020620-095952 · DOI
  8. IML Saur, 2021, NOD-like receptor-mediated plant immunity: from structure to cell death, Nat Rev Immunol, 21, 305, 10.1038/s41577-020-00473-z · DOI
  9. EA van der Biezen, 1998, The NB-ARC domain: a novel signalling motif shared by plant resistance gene products and regulators of cell death in animals, Current Biology, 8, R226, 10.1016/S0960-9822(98)70145-9 · DOI
  10. E Koonin, 2000, The NACHT family—a new group of predicted NTPases implicated in apoptosis and MHC transcription activation, Trends in Biochemical Sciences, 25, 223, 10.1016/S0968-0004(00)01577-2 · DOI
  11. W Dyrka, 2014, Diversity and Variability of NOD-Like Receptors in Fungi, Genome Biology and Evolution, 6, 3137, 10.1093/gbe/evu251 · DOI
  12. W Dyrka, 2020, Identification of NLR-associated amyloid signaling motifs in bacterial genomes, Journal of Molecular Biology, 432, 6005, 10.1016/j.jmb.2020.10.004 · DOI
  13. LA Gao, 2022, Prokaryotic innate immunity through pattern recognition of conserved viral proteins, Science, 377, eabm4096, 10.1126/science.abm4096 · DOI
  14. S Saupe, 1995, A gene responsible for vegetative incompatibility in the fungus Podospora anserina encodes a protein with a GTP-binding motif and G beta homologous domain, Gene, 162, 135, 10.1016/0378-1119(95)00272-8 · DOI
  15. M Paoletti, 2016, Vegetative incompatibility in fungi: From recognition to cell death, whatever does the trick, Fungal Biol Rev, 30, 152, 10.1016/j.fbr.2016.08.002 · DOI
  16. AP Gonçalves, 2020, Conflict, Competition, and Cooperation Regulate Social Interactions in Filamentous Fungi, Annual Review of Microbiology, 74, 693, 10.1146/annurev-micro-012420-080905 · DOI
  17. JM Urbach, 2017, The NBS-LRR architectures of plant R-proteins and metazoan NLRs evolved in independent events, Proceedings of the National Academy of Sciences, 114, 1063, 10.1073/pnas.1619730114 · DOI
  18. E Espagne, 2002, HET-E and HET-D belong to a new subfamily of WD40 proteins involved in vegetative incompatibility specificity in the fungus Podospora anserina, Genetics, 161, 71, 10.1093/genetics/161.1.71 · DOI
  19. E Bastiaans, 2014, Natural variation of heterokaryon incompatibility gene het-c in Podospora anserina reveals diversifying selection, Molecular Biology and Evolution, 31, 962, 10.1093/molbev/msu047 · DOI
  20. MA Armant, 2002, Toll-like receptors: a family of pattern-recognition receptors in mammals, Genome biology, 3, REVIEWS3011, 10.1186/gb-2002-3-8-reviews3011 · DOI
  21. VY Toshchakov, 2020, A survey of TIR domain sequence and structure divergence, Immunogenetics, 72, 181, 10.1007/s00251-020-01157-7 · DOI
  22. D Lapin, 2022, Molecular innovations in plant TIR-based immunity signaling, The Plant Cell, 34, 1479, 10.1093/plcell/koac035 · DOI
  23. J Heller, 2018, NLR surveillance of essential SEC-9 SNARE proteins induces programmed cell death upon allorecognition in filamentous fungi, Proc Natl Acad Sci U S A, 115, E2292, 10.1073/pnas.1719705115 · DOI
  24. M Paoletti, 2009, Fungal incompatibility: Evolutionary origin in pathogen defense?, BioEssays, 31, 1201, 10.1002/bies.200900085 · DOI
  25. M Paoletti, 2007, Genesis of a Fungal Non-Self Recognition Repertoire, PLoS ONE, 2, e283, 10.1371/journal.pone.0000283 · DOI
  26. D Chevanne, 2010, WD-repeat instability and diversification of the Podospora anserina hnwd non-self recognition gene family, BMC Evolutionary Biology, 10, 134, 10.1186/1471-2148-10-134 · DOI
  27. OJ Rando, 2007, Timescales of Genetic and Epigenetic Inheritance, Cell, 128, 655, 10.1016/j.cell.2007.01.023 · DOI
  28. M Iotti, 2012, Self/nonself recognition in Tuber melanosporum is not mediated by a heterokaryon incompatibility system, Fungal Biology, 116, 261, 10.1016/j.funbio.2011.11.009 · DOI
  29. RD Finn, 2016, The Pfam protein families database: towards a more sustainable future, Nucleic Acids Research
  30. SJ Saupe, 2020, Amyloid Signaling in Filamentous Fungi and Bacteria, Annual Review of Microbiology, 74, 673, 10.1146/annurev-micro-011320-013555 · DOI
  31. DL Ollis, 1992, The alpha/beta hydrolase fold, Protein Engineering, Design and Selection, 5, 197, 10.1093/protein/5.3.197 · DOI
  32. A Mushegian, 1994, Unexpected sequence similarity between nucleosidases and phosphoribosyltransferases of different specificity, Protein science: a publication of the Protein Society, 3, 1081, 10.1002/pro.5560030711 · DOI
  33. C Mao, 1997, The crystal structure of Escherichia coli purine nucleoside phosphorylase: a comparison with the human enzyme reveals a conserved topology, Structure (London, England: 1993), 5, 1373, 10.1016/S0969-2126(97)00287-6 · DOI
  34. A Balguerie, 2003, Domain organization and structure-function relationship of the HET-s prion protein of Podospora anserina, The EMBO Journal, 22, 2071, 10.1093/emboj/cdg213 · DOI
  35. ND Fedorova, 2005, Comparative analysis of programmed cell death pathways in filamentous fungi, BMC Genomics, 6, 177, 10.1186/1471-2164-6-177 · DOI
  36. J Greenwald, 2010, The mechanism of prion inhibition by HET-S, Molecular Cell, 38, 889, 10.1016/j.molcel.2010.05.019 · DOI
  37. A Daskalov, 2012, Genomic Clustering and Homology between HET-S and the NWD2 STAND Protein in Various Fungal Genomes, PLoS ONE, 7, e34854, 10.1371/journal.pone.0034854 · DOI
  38. A Daskalov, 2016, Identification of a novel cell death-inducing domain reveals that fungal amyloid-controlled programmed cell death is related to necroptosis, Proceedings of the National Academy of Sciences of the United States of America, 113, 2720, 10.1073/pnas.1522361113 · DOI
  39. J Wang, 2019, Reconstitution and structure of a plant NLR resistosome conferring immunity, Science, 364, eaav5870, 10.1126/science.aav5870 · DOI
  40. G Bi, 2021, The ZAR1 resistosome is a calcium-permeable channel triggering plant immune signaling, Cell, 184, 3528, 10.1016/j.cell.2021.05.003 · DOI
  41. A Daskalov, 2015, Signal transduction by a fungal NOD-like receptor based on propagation of a prion amyloid fold, PLoS Biology, 13, e1002059, 10.1371/journal.pbio.1002059 · DOI
  42. C Wasmer, 2008, Amyloid Fibrils of the HET-s(218–289) Prion Form a Beta Solenoid with a Triangular Hydrophobic Core, Science, 319, 1523, 10.1126/science.1151839 · DOI
  43. H van Melckebeke, 2010, Atomic-Resolution Three-Dimensional Structure of HET-s(218–289) Amyloid Fibrils by Solid-State NMR Spectroscopy, Journal of the American Chemical Society, 132, 13765, 10.1021/ja104213j · DOI
  44. C Seuring, 2012, The mechanism of toxicity in HET-S/HET-s prion incompatibility, PLoS Biology, 10, e1001451, 10.1371/journal.pbio.1001451 · DOI
  45. A Daskalov, 2015, Theme and variations: evolutionary diversification of the HET-s functional amyloid motif, Scientific Reports, 5, 12494, 10.1038/srep12494 · DOI
  46. A Daskalov, 2021, Structural and molecular basis of cross-seeding barriers in amyloids, Proceedings of the National Academy of Sciences, 118, 10.1073/pnas.2014085118 · DOI
  47. S Graziani, 2004, Bistability and hysteresis of the ‘Secteur’ differentiation are controlled by a two-gene locus in Nectria haematococca, BMC Biology, 2, 18, 10.1186/1741-7007-2-18 · DOI
  48. X Sun, 2002, Identification of a novel homotypic interaction motif required for the phosphorylation of receptor-interacting protein (RIP) by RIP3, The Journal of Biological Chemistry, 277, 9505, 10.1074/jbc.M109488200 · DOI
  49. M Rebsamen, 2009, DAI/ZBP1 recruits RIP1 and RIP3 through RIP homotypic interaction motifs to activate NF-kB, EMBO reports, 10, 916, 10.1038/embor.2009.109 · DOI
  50. AV Kajava, 2014, Evolutionary link between metazoan RHIM motif and prion-forming domain of fungal heterokaryon incompatibility factor HET-s/HET-s, Scientific Reports, 4, 1, 10.1038/srep07436 · DOI
  51. AB Ahmed, 2015, A structure-based approach to predict predisposition to amyloidosis, Alzheimer’s & Dementia, 11, 681, 10.1016/j.jalz.2014.06.007 · DOI
  52. W Dyrka, 2021, Searching for universal model of amyloid signaling motifs using probabilistic context-free grammars, BMC Bioinformatics, 22, 222, 10.1186/s12859-021-04139-y · DOI
  53. C Clavé, 2022, Fungal gasdermin-like proteins are controlled by proteolytic cleavage, Proceedings of the National Academy of Sciences, 119, e2109418119, 10.1073/pnas.2109418119 · DOI
  54. AG Johnson, 2022, Bacterial gasdermins reveal an ancient mechanism of cell death, Science, 375, 221, 10.1126/science.abj8432 · DOI
  55. E Gluck-Thaler, 2022, Giant Starship Elements Mobilize Accessory Genes in Fungal Genomes, Molecular Biology and Evolution, 39, 10.1093/molbev/msac109 · DOI
  56. J Li, 2012, The RIP1/RIP3 necrosome forms a functional amyloid signaling complex required for programmed necrosis, Cell, 150, 339, 10.1016/j.cell.2012.06.019 · DOI · Paper page
  57. A Kleino, 2017, Peptidoglycan-Sensing Receptors Trigger the Formation of Functional Amyloids of the Adaptor Protein Imd to Initiate Drosophila NF-kB Signaling, Immunity, 47, 635, 10.1016/j.immuni.2017.09.011 · DOI
  58. M Steinegger, 2017, MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets, Nature Biotechnology, 35, 1026, 10.1038/nbt.3988 · DOI · Paper page
  59. M Mirdita, 2016, Uniclust databases of clustered and deeply annotated protein sequences and alignments, Nucleic Acids Research, 45, D170, 10.1093/nar/gkw1081 · DOI
  60. M Remmert, 2012, HHblits: lightning-fast iterative protein sequence searching by HMM-HMM alignment, Nature Methods, 9, 173, 10.1038/nmeth.1818 · DOI · Paper page
  61. R Oliva, 2010, Recent developments in effector biology of filamentous plant pathogens, Cellular Microbiology, 12, 705, 10.1111/j.1462-5822.2010.01471.x · DOI
  62. T Liu, 2011, Two host cytoplasmic effectors are required for pathogenesis of Phytophthora sojae by suppression of host defenses, Plant physiology, 155, 490, 10.1104/pp.110.166470 · DOI
  63. D Zhang, 2016, Transposons to toxins: the provenance, architecture and diversification of a widespread class of eukaryotic effectors, Nucleic Acids Research, 44, 3513, 10.1093/nar/gkw221 · DOI
  64. S Voss, 2018, RiCRN1, a Crinkler Effector From the Arbuscular Mycorrhizal Fungus Rhizophagus irregularis, Functions in Arbuscule Development, Frontiers in microbiology, 9, 2068, 10.3389/fmicb.2018.02068 · DOI
  65. A Hetmann, 2019, Supresja odporności podstawowej typu PTI przez syntetyzowane w fitopatogenach białka efektorowe wprowadzane do wnętrza komórek infekowanej rośliny, Postępy Biochemii, 65, 58, 10.18388/pb.2019_257 · DOI
  66. SJ Grimshaw, 2004, Structure of the sterile alpha motif (SAM) domain of the Saccharomyces cerevisiae mitogen-activated protein kinase pathway-modulating protein STE50 and analysis of its interaction with the STE11 SAM, The Journal of Biological Chemistry, 279, 2192, 10.1074/jbc.M305605200 · DOI
  67. S Ray, 2020, Sterile α-motif domain requirement for cellular signaling and survival, Journal of Biological Chemistry, 295, 7113, 10.1074/jbc.RA119.011895 · DOI
  68. LAJ O’Neill, 2007, The family of five: TIR-domain-containing adaptors in Toll-like receptor signalling, Nature reviews Immunology, 7, 353, 10.1038/nri2079 · DOI · Paper page
  69. Q Zhang, 2011, TIR domain-containing adaptor SARM is a late addition to the ongoing microbe-host dialog, Developmental and comparative immunology, 35, 461, 10.1016/j.dci.2010.11.013 · DOI
  70. ND Peterson, 2022, Pathogen infection and cholesterol deficiency activate the C. elegans p38 immune pathway through a TIR-1/SARM1 phase transition, eLife, 11, e74206, 10.7554/eLife.74206 · DOI
  71. S Detke, 1998, Cloning of the Candida albicans nucleoside transporter by complementation of nucleoside transport-deficient Saccharomyces, Yeast, 14, 1257, 10.1002/(SICI)1097-0061(1998100)14:14<1257::AID-YEA326>3.0.CO;2-6 · DOI
  72. S Lu, 2019, CDD/SPARCLE: the conserved domain database in 2020, Nucleic Acids Research, 48, D265, 10.1093/nar/gkz991 · DOI
  73. J Soeding, 2005, Protein homology detection by HMM-HMM comparison, Bioinformatics, 21, 951, 10.1093/bioinformatics/bti125 · DOI
  74. L Zimmermann, 2018, A Completely Reimplemented MPI Bioinformatics Toolkit with a New HHpred Server at its Core, Journal of Molecular Biology, 430, 2237, 10.1016/j.jmb.2017.12.007 · DOI · Paper page
  75. M Rübbelke, 2020, Locking mixed-lineage kinase domain-like protein in its auto-inhibited state prevents necroptosis, Proceedings of the National Academy of Sciences, 117, 33272, 10.1073/pnas.2017406117 · DOI
  76. M Mirdita, 2022, ColabFold: making protein folding accessible to all, Nature Methods, 19, 679, 10.1038/s41592-022-01488-1 · DOI · Paper page
  77. Y Zhang, 2005, TM-align: a protein structure alignment algorithm based on the TM-score, Nucleic Acids Research, 33, 2302, 10.1093/nar/gki524 · DOI · Paper page
  78. M Landau, 2005, ConSurf 2005: the projection of evolutionary conservation scores of residues on protein structures, Nucleic Acids Research, 33, W299, 10.1093/nar/gki370 · DOI
  79. H Ashkenazy, 2016, ConSurf 2016: an improved methodology to estimate and visualize evolutionary conservation in macromolecules, Nucleic Acids Research, 44, W344, 10.1093/nar/gkw408 · DOI · Paper page
  80. H Adachi, 2019, An N-terminal motif in NLR immune receptors is functionally conserved across distantly related plant species, eLife, 8, e49956, 10.7554/eLife.49956 · DOI
  81. DE McNamara, 2019, Direct Activation of Human MLKL by a Select Repertoire of Inositol Phosphate Metabolites, Cell Chemical Biology, 26, 863, 10.1016/j.chembiol.2019.03.010 · DOI
  82. B Wu, 2012, Evolution of prokaryotic homologues of the eukaryotic SEFIR protein domain, Gene, 492, 160, 10.1016/j.gene.2011.10.033 · DOI
  83. F Jacob, 2013, Evolution and Conservation of Plant NLR Functions, Frontiers in Immunology, 4, 297, 10.3389/fimmu.2013.00297 · DOI
  84. Y Guo, 2018, Fungus-Bacterium Symbionts Promote Plant Health and Performance, Microbes and Environments, 33, 239, 10.1264/jsme2.ME3303rh · DOI
  85. TL Bailey, 2009, MEME Suite: tools for motif discovery and searching, Nucleic Acids Research, 37, W202, 10.1093/nar/gkp335 · DOI · Paper page
  86. N Alkan, 2013, Global Aspects of pacC Regulation of Pathogenicity Genes in Colletotrichum gloeosporioides as Revealed by Transcriptome Analysis, Molecular Plant-Microbe Interactions, 26, 1345, 10.1094/MPMI-03-13-0080-R · DOI · Paper page
  87. R Sarroukh, 2013, ATR-FTIR: a “rejuvenated” tool to investigate amyloid proteins, Biochimica et biophysica acta, 1828, 2328, 10.1016/j.bbamem.2013.04.012 · DOI
  88. JM Ruysschaert, 2018, ATR-FTIR analysis of amyloid proteins, Methods Mol Biol, 1777, 69, 10.1007/978-1-4939-7811-3_3 · DOI
  89. FS Ruggeri, 2019, Atomic force microscopy for single molecule characterisation of protein aggregation, Archives of Biochemistry and Biophysics, 664, 134, 10.1016/j.abb.2019.02.001 · DOI
  90. M Biancalana, 2010, Molecular mechanism of Thioflavin-T binding to amyloid fibrils, Biochimica et Biophysica Acta (BBA)—Proteins and Proteomics, 1804, 1405, 10.1016/j.bbapap.2010.04.001 · DOI
  91. C Xue, 2017, Thioflavin T as an amyloid dye: fibril quantification, optimal concentration and effect on aggregation, Royal Society Open Science, 4, 160696, 10.1098/rsos.160696 · DOI
  92. MR Nilsson, 2004, Techniques to study amyloid fibril formation in vitro, Methods, 34, 151, 10.1016/j.ymeth.2004.03.012 · DOI
  93. H Li, 2009, Encyclopedia of Analytical Chemistry
  94. PM Martins, 2020, MIRRAGGE—Minimum Information Required for Reproducible AGGregation Experiments, Frontiers in Molecular Neuroscience, 13, 222, 10.3389/fnmol.2020.582488 · DOI
  95. N Wilkosz, 2020, Molecular Spectroscopic Markers of Abnormal Protein Aggregation, Molecules, 25, 10.3390/molecules25112498 · DOI
  96. R Khurana, 2000, Do Parallel β-Helix Proteins Have a Unique Fourier Transform Infrared Spectrum?, Biophysical Journal, 78, 994, 10.1016/S0006-3495(00)76657-4 · DOI
  97. Y Zou, 2013, Parallel β-Sheet Fibril and Antiparallel β-Sheet Oligomer: New Insights into Amyloid Formation of Hen Egg White Lysozyme under Heat and Acidic Condition from FTIR Spectroscopy, The Journal of Physical Chemistry B, 117, 4003, 10.1021/jp4003559 · DOI
  98. M Grelich-Mucha, 2021, Autofluorescence of Amyloids Determined by Enantiomeric Composition of Peptides, The Journal of Physical Chemistry B, 125, 5502, 10.1021/acs.jpcb.1c00808 · DOI
  99. K Berthelot, 2011, In Vivo and In Vitro Analyses of Toxic Mutants of HET-s: FTIR Antiparallel Signature Correlates with Amyloid Toxicity, Journal of Molecular Biology, 412, 137, 10.1016/j.jmb.2011.07.009 · DOI
  100. JR Requena, 2014, The structure of the infectious prion protein, Prion, 8, 60, 10.4161/pri.28368 · DOI
  101. SD Moran, 2014, How to Get Insight into Amyloid Structure and Formation from Infrared Spectroscopy, The journal of physical chemistry letters, 5, 1984, 10.1021/jz500794d · DOI
  102. T Bardin, 2021, Partial Prion Cross-Seeding between Fungal and Mammalian Amyloid Signaling Motifs, mBio, 12, e02782, 10.1128/mBio.02782-20 · DOI
  103. M Paoletti, 2007, The Fungus-Specific HET Domain Mediates Programmed Cell Death in Podospora anserina, Eukaryotic Cell, 6, 2001, 10.1128/EC.00129-07 · DOI
  104. W Dyrka, 2009, A Stochastic Context Free Grammar based Framework for Analysis of Protein Sequences, BMC Bioinformatics, 10, 323, 10.1186/1471-2105-10-323 · DOI
  105. GW Wilburn, 2020, Remote homology search with hidden Potts models, PLOS Computational Biology, 16, 1, 10.1371/journal.pcbi.1008085 · DOI
  106. AP Muntoni, 2020, Aligning biological sequences by exploiting residue conservation and coevolution, Phys Rev E, 102, 062409, 10.1103/PhysRevE.102.062409 · DOI
  107. H Talibart, 2021, PPalign: optimal alignment of Potts models representing proteins with direct coupling information, BMC Bioinformatics, 22, 317, 10.1186/s12859-021-04222-4 · DOI
  108. Merrill W, Weiss G, Goldberg Y, Schwartz R, Smith NA, Yahav E. A Formal Hierarchy of RNN Architectures. In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Online: Association for Computational Linguistics; 2020. p. 443–459. · DOI
  109. Bhattamishra S, Patel A, Goyal N. On the Computational Power of Transformers and Its Implications in Sequence Modeling. In: Proceedings of the 24th Conference on Computational Natural Language Learning. Online: Association for Computational Linguistics; 2020. p. 455–475. · DOI
  110. Merrill W. Formal Language Theory Meets Modern NLP. CoRR. 2021;abs/2102.10094.
  111. Nambiar A, Heflin M, Liu S, Maslov S, Hopkins M, Ritz A. Transforming the Language of Life: Transformer Neural Networks for Protein Prediction Tasks. In: Proceedings of the 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics. BCB’20. New York, NY, USA: Association for Computing Machinery; 2020. · DOI
  112. N Brandes, 2022, ProteinBERT: A universal deep-learning model of protein sequence and function, Bioinformatics, 38, 2102, 10.1093/bioinformatics/btac020 · DOI · Paper page
  113. SF Altschul, 1997, Gapped BLAST and PSI-BLAST: a new generation of protein database search programs, Nucleic Acids Research, 25, 3389, 10.1093/nar/25.17.3389 · DOI · Paper page
  114. F Sievers, 2011, Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega, Molecular Systems Biology, 7, 539, 10.1038/msb.2011.75 · DOI
  115. TU Consortium, 2020, UniProt: the universal protein knowledgebase in 2021, Nucleic Acids Research, 49, D480, 10.1093/nar/gkaa1100 · DOI · Paper page
  116. W Dyrka, 2019, Estimating probabilistic context-free grammars for proteins using contact map constraints, PeerJ, 7, e6559, 10.7717/peerj.6559 · DOI
  117. W Li, 2006, Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences, Bioinformatics, 22, 1658, 10.1093/bioinformatics/btl158 · DOI
  118. L Fu, 2012, CD-HIT: accelerated for clustering the next-generation sequencing data, Bioinformatics, 28, 3150, 10.1093/bioinformatics/bts565 · DOI · Paper page
  119. Bailey TL, Elkan C. Fitting a mixture model by expectation maximization to discover motifs in biopolymers. In: Proceedings of the Second International Conference on Intelligent Systems for Molecular Biology. AAAI Press, Menlo Park, California; 1994. p. 28–36.
  120. SR Eddy, 2011, Accelerated Profile HMM Searches, PLoS Computational Biology, 7, e1002195, 10.1371/journal.pcbi.1002195 · DOI · Paper page
  121. K Katoh, 2013, MAFFT multiple sequence alignment software version 7: improvements in performance and usability, Molecular Biology and Evolution, 30, 772, 10.1093/molbev/mst010 · DOI · Paper page
  122. S Capella-Gutierrez, 2009, trimAl: a tool for automated alignment trimming in large-scale phylogenetic analyses, Bioinformatics, 25, 1972, 10.1093/bioinformatics/btp348 · DOI
  123. NR Coordinators, 2017, Database resources of the National Center for Biotechnology Information, Nucleic Acids Research, 46, D8, 10.1093/nar/gkx1095 · DOI
  124. PW Harrison, 2020, The European Nucleotide Archive in 2020, Nucleic Acids Research, 49, D82, 10.1093/nar/gkaa1028 · DOI
  125. McKinney W. Data Structures for Statistical Computing in Python. In: St fan van der Walt, Jarrod Millman, editors. Proceedings of the 9th Python in Science Conference; 2010. p. 56–61. · DOI
  126. JD Hunter, 2007, Matplotlib: A 2D graphics environment, Computing in Science & Engineering, 9, 90, 10.1109/MCSE.2007.55 · DOI · Paper page
  127. ML Waskom, 2021, seaborn: statistical data visualization, Journal of Open Source Software, 6, 3021, 10.21105/joss.03021 · DOI · Paper page
  128. E Beitz, 2000, TeXshade: shading and labeling of multiple sequence alignments using LaTeX2e, Bioinformatics, 16, 135, 10.1093/bioinformatics/16.2.135 · DOI
  129. ER Gansner, 2000, An open graph visualization system and its applications to software engineering, Software Practice and Experience, 30, 1203, 10.1002/1097-024X(200009)30:11<1203::AID-SPE338>3.0.CO;2-N · DOI
  130. RA Sayle, 1995, RASMOL: biomolecular graphics for all, Trends in Biochemical Sciences, 20, 374, 10.1016/S0968-0004(00)89080-5 · DOI
  131. A Savitzky, 1964, Smoothing and differentiation of data by simplified least squares procedures, Analytical Chemistry, 36, 1627, 10.1021/ac60214a047 · DOI · Paper page
  132. A Balguerie, 2004, The sequences appended to the amyloid core region of the HET-s prion protein determine higher-order aggregate organization in vivo, Journal of Cell Science, 117, 2599, 10.1242/jcs.01116 · DOI
  133. T Bergès, 1989, Heat Shock at an Elevated Temperature Improves Transformation Efficiency of Protoplasts from Podospora anserina, Microbiology, 135, 601, 10.1099/00221287-135-3-601 · DOI
  134. L Benkemoun, 2006, Methods for the in vivo and in vitro analysis of [Het-s] prion infectivity, Methods, 39, 61, 10.1016/j.ymeth.2006.04.006 · DOI

Metadata

Authors
Wojciechowski, J. W., Tekoglu, E., Gąsior-Głogowska, M., Coustou, V., Szulc, N., Szefczyk, M., Kopaczyńska, M., Saupe, S. J., & Dyrka, W.
Affiliations
  • Wrocław University of Science and Technology (PL)
  • Centre National de la Recherche Scientifique (FR)
Corresponding author
  • Saupe, Sven J.
  • Dyrka, Witold
ORCID
Venue
PLOS Computational Biology
Publisher
Public Library of Science (PLoS)
Published
2022-12-21
Volume
18
Issue
12
Pages
e1010787
ISSN
  • 1553-734X (ISSN-L)
  • 1553-7358
DOI
10.1371/journal.pcbi.1010787
PMC
PMC9815663
OpenAlex
W4312064942
Cited by
19
References
5
Citations by year
2026: 2 · 2025: 10 · 2024: 1 · 2023: 6
FWCI
2.34
Type
journal article
Language
en
Update notices
new_version (2023-01-05)
Open access
Licence
Locations
  • PLoS Computational Biology (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • HAL (submittedVersion, other-oa)
  • RePEc: Research Papers in Economics (submittedVersion)
  • Digital Collections portal (Koç University) (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Funders
  • Narodowe Centrum Nauki (2019/35/B/NZ2/03997)
  • Wroclawskie Centrum Sieciowo-Superkomputerowe, Politechnika Wroclawska (98)
  • Narodowe Centrum Badań i Rozwoju (POWR.03.02.00-00-I003/16)
  • Agence Nationale de la Recherche (SFAS, R-17-CE11-0035)
Topics
  • Life Sciences › Agricultural and Biological Sciences › Plant Science › Plant-Microbe Interactions and Immunity
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Fungal and yeast genetics research
  • Life Sciences › Immunology and Microbiology › Immunology › Immune Response and Inflammation
Keywords
NLR proteins, effector domain, Basidiomycota, Ascomycota, prion formation, protein aggregation, domain architecture, protein structure prediction, sequence clustering
MeSH terms
NLR Proteins, Amyloid, Fungal Proteins, Amyloidogenic Proteins

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Exploring a diverse world of effector domains and amyloid signaling motifs in fungal NLR proteins. https://app.cochat.ai/papers/10.1371/journal.pcbi.1010787
The paper
Wojciechowski, J. W., Tekoglu, E., Gąsior-Głogowska, M., Coustou, V., Szulc, N., Szefczyk, M., Kopaczyńska, M., Saupe, S. J., & Dyrka, W. (2022). Exploring a diverse world of effector domains and amyloid signaling motifs in fungal NLR proteins. PLOS Computational Biology. https://doi.org/10.1371/journal.pcbi.1010787