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71 results for “NLR”
Supplementary data files for exploring a diverse world of effector domains and amyloid signaling motifs in fungal NLR proteins
<p>This dataset includes 20 supplementary data files for manuscript <em>Exploring a diverse world of effector domains and amyloid signaling motifs in fungal NLR proteins </em>by Jakub W. Wojciechowski, Emirhan Tekoglu, Marlena Gąsior-Głogowska, Virginie Coustou, Natalia Szulc, Monika Szefczyk, Marta Kopaczyńska, Sven J. Saupe, and Witold Dyrka (under revision). </p> <ul> <li>SF2. Profile HMMs of NLR effector domains. The file includes previously unpublished models.</li> <li>SF3. Multiple sequence alignments of N-termini clusters. </li> <li>SF4. Tabularized results of N-termini annotation.</li> <li>SF5. Structure prediction of HeLo-/Goodbye-/MLKL-like domains. Full AlphaFold2/ColabFold outputs.</li> <li>SF6. Structure prediction of previously unannotated domains. Full AlphaFold2/ColabFold outputs.</li> <li>SF7. PCFGs for BASS. The file includes previously unpublished grammars and a sample scanning configuration.</li> <li>SF8. Candidate short NLR N-termini with ASMs. The FASTA file includes sequences from clusters with high content of ASM-like sequences, according to the BASS PCFGs (SF7).</li> <li>SF9. Profile HMMs of ASMs found in short NLR N-termini.</li> <li>SF10. Profile HMM of HeLo-related HRAMs.</li> <li>SF11. Genomic neighbors of candidate short N-termini NLRs with ASMs The list includes accessions of proteins encoded by genes within the neighborhood of 20kbp of genes encoding the query proteins (SF8).</li> <li>SF12. Short C-termini of 200–400 aa long proteins genomically neighboring candidate short NLR N-termini with ASMs. The FASTA file concerns target proteins listed in SF11.</li> <li>SF13. Pairwise hits of the same ASMs in N-termini of NLRs and C-termini of genomically neighboring proteins. The table is based on SF8–9 and SF11–12. </li> <li>SF14. Lists of HMMER domain hits of effector domain profiles. The lists were obtained through iterative searches in NCBI “nr” starting from Pfam profiles of known NLR effector domains.</li> <li>SF15. Short C-termini of effector proteins. The FASTA file concerns target proteins listed in SF14.</li> <li>SF16. Short N-termini of Pfam NACHT and NB-ARC proteins. The FASTA file concerns proteins from NCBI “nr” associated with the two families in the Pfam database.</li> <li>SF17. Profile HMMs of ASMs found both in effector C-termini and NLR N-termini of genomically neighboring proteins.</li> <li>SF18. Genomic neighbors of candidate short N-termini Pfam NACHT and NB-ARC proteins. The list includes accessions of proteins encoded by genes within the neighborhood of 20kbp of genes encoding the query proteins (SF16).</li> <li>SF19. Pairwise hits of the same ASMs in N-termini of NACHT/NB-ARC NLRs and C-termini of genomically neighboring effector proteins. The table is based on SF15–18. </li> <li>SF20. Pairwise hits of the same ASMs in N-termini of NLRs and C-termini of genomically co-occurring effector proteins. The table is based on SF8–9 and SF15. </li> <li>SF21. BaMLKL homologs identified with hmmsearch in Basidiomycota. A FASTA file.</li> </ul>
H2020 ENODISE: NLR Numerical aeroacoustic database configuration B3-flap
<p>This dataset considers numerical aerodynamic and aeroacoustic data for an over-the-wing mounted propeller, denoted configuration B3-flap as defined in the H2020 ENODISE project (https://www.vki.ac.be/index.php/about-enodise).</p> <p>The dataset consists of</p> <p>- Aerodynamic data: propeller thrust and torque</p> <p>- Acoustic data: pressure Fourier modes at 1, 2, and 3 BPF</p> <p>both for the isolated propeller and the over-the-wing mounted propeller.</p> <p>An overview of the performed numerical simulation and a description of the dataset is given in the included PDF file (ENODISE_NLR_B3_flap_URANS.pdf). This file also includes the aerodynamic data.</p> <p>Experiments have also been performed by NLR for this configuration. See https://zenodo.org/record/8283630 for details and the experimental dataset.</p>
A root-specific NLR network confers resistance to plant parasitic nematodes - genomic sequences and annotations
<p>Sequence and annotation data associated with "A root-specific NLR network confers resistance to plant parasitic nematodes"</p>
AlphaFold Structures for: A wheat tandem kinase activates an NLR to trigger immunity
<p>AlphaFold Predictions used for analysis in "A wheat tandem kinase activates an NLR to trigger immunity".</p>
Dataset used in "Helper NLR immune protein NRC3 evolved to evade inhibition by a cyst nematode virulence effector"
<p><strong>[Figs 1 and S2]</strong></p> <p> </p> <p><strong>00_cloned_NRC123.fasta</strong></p> <p> </p> <p>FASTA file containing NRC1, NRC2 and NRC3 sequences tested in HR cell death assay.</p> <p> </p> <p><strong>01_NRCX0123_4species.fasta</strong></p> <p> </p> <p>FASTA file containing NRC0, NRC1, NRC2, NRC3 and NRCX of <em>N. benthamiana</em>, <em>C. annuum</em> (pepper), <em>S. tuberosum</em> (potato) and <em>S. lycopersicum</em> (tomato). In addition to a previously published dataset (Selvaraj et al., 2023), we included the NbNRC2, CaNRC3 and StNRC3 sequences from 00_cloned_NRC123.fasta.</p> <p> </p> <p><strong>02_NRCX0123_4species.local_aln.fasta</strong></p> <p> </p> <p>FASTA file containing the protein sequence alignment of 01_NRCX0123_4species.fasta. We used MAFFT for the alignment (Katoh & Standley, 2013).</p> <p> </p> <p><strong>03_NRCX0123_4species.local_aln.clip.fasta</strong></p> <p> </p> <p>FASTA file containing the trimmed protein sequence alignment of 02_NRCX0123_4species.local_aln.fasta. We used ClipKIT for trimming (Steenwyk et al., 2020).</p> <p> </p> <p><strong>04_NRCX0123_4species.local_aln.clip.fasta.treefile</strong></p> <p><strong> </strong></p> <p>Newick file containing the phylogenetic tree reconstructed based on 03_NRCX0123_4species.local_aln.clip.fasta. We used IQ-TREE to create a phylogenetic tree (Minh et al., 2020).</p> <p> </p> <p><strong>[Fig 2B]</strong></p> <p><strong> </strong></p> <p><strong>05_cloned_NRC123.local_aln.fasta</strong></p> <p><strong> </strong></p> <p>FASTA file containing the protein sequence alignment of 00_cloned_NRC123.fasta. We used MAFFT for the alignment (Katoh & Standley, 2013).</p> <p> </p> <p><strong>[Fig 5 and Table S1]</strong></p> <p> </p> <p><strong>06_NRCH_cds_23-06-20.min2400max2800.fasta</strong></p> <p><strong> </strong></p> <p>FASTA file containing the nucleotide sequences of helper NRC sequences from 124 Solanaceae genomes (Sugihara et al., 2023; Huang et al., 2023). We filtered out sequences shorter than 2,400 or longer than 2,800 bases, resulting in 1,748 sequences.</p> <p> </p> <p><strong>07_NRCH_cds_23-06-20.min2400max2800.aa.fasta</strong></p> <p> </p> <p>FASTA file of the amino acid sequences translated from 06_NRCH_cds_23-06-20.min2400max2800.fasta.</p> <p> </p> <p><strong>08_NRCH_cds_23-06-20.min2400max2800.aa.NBARC.fasta</strong></p> <p> </p> <p>FASTA file containing the amino acid sequences of NB-ARC module corresponding to the sequences in 07_NRCH_cds_23-06-20.min2400max2800.aa.fasta.</p> <p> </p> <p><strong>09_NRCH_cds_23-06-20.min2400max2800.aa.NBARC.local_aln.clip.fasta</strong></p> <p> </p> <p>FASTA file containing the trimmed protein sequence alignment of 02_NRCX0123_4species.local_aln.fasta. We used MAFFT and ClipKIT for the alignment and trimming, respectively (Katoh & Standley, 2013; Steenwyk et al., 2020).</p> <p> </p> <p><strong>10_NRCH_cds_23-06-20.min2400max2800.aa.NBARC.local_aln.clip.fasta.treefile</strong></p> <p> </p> <p>Newick file containing the phylogenetic tree reconstructed based on 09_NRCH_cds_23-06-20.min2400max2800.aa.NBARC.local_aln.clip.fasta. We used IQ-TREE to create a phylogenetic tree (Minh et al., 2020).</p> <p> </p> <p><strong>11_NRCX123_cds_23-06-20.min2400max2800.fasta</strong></p> <p> </p> <p>FASTA file containing the the nucleotide sequences of NRC1/2/3X clades identified based on 10_NRCH_cds_23-06-20.min2400max2800.aa.NBARC.local_aln.clip.fasta.treefile.</p> <p> </p> <p><strong>12_NRCX123_nt_codon_ancseq_v1.2.1.zip</strong></p> <p> </p> <p>Results of ancestral sequence reconstruction. We used ancseq to perform ancestral sequence reconsturction (Sugihara, 2024). "NRCX123_cds_23-06-20.min2400max2800.nt_codon.local_aln.manual.clip.uniq.rm_4sp.fasta" is an input alignment and "NRCX123_cds_23-06-20.min2400max2800.nt_codon.local_aln.manual.clip.uniq.rm_4sp.fasta.treefile" is a tree file. Regarding the output files for ancseq, please refer to the <a href="https://github.com/YuSugihara/ancseq?tab=readme-ov-file#outputs">GitHub repository</a>.</p> <p> </p> <p><strong>[Fig S7]</strong></p> <p> </p> <p><strong>13_logo_plot.zip</strong></p> <p> </p> <p>Sequence alignments and script used in Fig S7. To generate the consensus sequence shown in Fig S7, we concatenated interfaces 1, 2 and 3 with SS15 and visualized the results using logomaker (Tareen and Kinney, 2020).</p> <p> </p> <p><strong>References</strong></p> <p> </p> <p>Huang C-Y, Huang Y-S, Sugihara Y, Wang H-Y, Huang L-T, Lopez-Agudelo JC, Chen Y-F, Lin K-Y, Chiang B-J, Toghani A, Kourelis J, Derevnina L, Wu C-H. 2023. Functional divergence shaped the network architecture of plant immune receptors. <em>bioRxiv</em>. 2023:2023.12.12.571219. DOI: 10.1101/2023.12.12.571219.</p> <p>Katoh K, Standley DM. 2013. MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability. <em>Molecular Biology and Evolution</em> 30:772–780. DOI: 10.1093/molbev/mst010.</p> <p>Minh BQ, Schmidt HA, Chernomor O, Schrempf D, Woodhams MD, von Haeseler A, Lanfear R. 2020. IQ-TREE 2: New Models and Efficient Methods for Phylogenetic Inference in the Genomic Era. <em>Molecular Biology and Evolution</em> 37:1530–1534. DOI: 10.1093/molbev/msaa015.</p> <p>Selvaraj M, Toghani A, Pai H, Sugihara Y, Kourelis J, Yuen ELH, Ibrahim T, Zhao H, Xie R, Maqbool A, Concepcion JCD la, Banfield MJ, Derevnina L, Petre B, Lawson DM, Bozkurt TO, Wu C-H, Kamoun S, Contreras MP. 2023. Activation of plant immunity through conversion of a helper NLR homodimer into a resistosome. <em>bioRxiv</em>. 2023:2023.12.17.572070. DOI: 10.1101/2023.12.17.572070.</p> <p>Steenwyk JL, Iii TJB, Li Y, Shen X-X, Rokas A. 2020. ClipKIT: A multiple sequence alignment trimming software for accurate phylogenomic inference. <em>PLOS Biology</em> 18:e3001007. DOI: 10.1371/journal.pbio.3001007.</p> <p>Sugihara Y. 2024. YuSugihara/ancseq: v1.2.1. <em>Zenodo</em>. DOI: 10.5281/zenodo.10808871.</p> <p>Sugihara Y, Toghani A, Kamoun S, Kourelis J. 2023. NLRome dataset from 124 genomes of plants in the Solanaceae family. <em>Zenodo</em>. DOI: 10.5281/zenodo.10354350.</p> <p>Tareen A, Kinney JB. 2020. Logomaker: beautiful sequence logos in Python. Bioinformatics 36:2272–2274. doi:10.1093/bioinformatics/btz921</p> <p> </p>
AlphaFold 3 predicted NLR resistosome structures
<p><strong>Abstract</strong></p> <p>In our paper "A disease resistance protein triggers oligomerization of its NLR helper into a hexameric resistosome to mediate innate immunity," we used the NbNRC2 hexamer structure to evaluate the capabilities of the newly introduced AlphaFold 3 in predicting activated CC-NLR oligomers. Our analysis highlights AlphaFold 3 effectiveness in confidently modelling the N-terminal alpha1-helices of NbNRC2 and other CC-NLRs, a structurally elusive region critical for NLR function but challenging to resolve through conventional structural methods. This study not only underscores the utility of AlphaFold 3 in enhancing our understanding of plant immune receptors but also extends its application to complex oligomerization processes in innate immunity. Here, we provide the Supplementary data accompanying the paper which includes metadata and predicted structures for 29 NLR immune receptors, providing valuable resources for further research in plant pathogen resistance.</p> <p> </p> <p><strong>Index:</strong></p> <ul> <li>Metadata:</li> <li> <ul> <li>Metadata, sequence, and model statistics of all modelled NLRs: <ul> <li>Data S1.xlsx</li> </ul> </li> </ul> </li> </ul> <p> </p> <ul> <li>Predicted structures:</li> <li> <ul> <li>AlphaFold 2 vs 3 vs 3+lipids comparison for NbNRC2: <ul> <li>AF_benchmark.zip</li> </ul> </li> </ul> </li> </ul> <ul> <li> <ul> <li>[AlphaFold 3] NRC2 oliogmoeric type benchmarks (N = 10): <ol> <li>NRC2_tetramers.zip</li> <li>NRC2_pentamers.zip</li> <li>NRC2_hexamers.zip</li> <li>NRC2_heptamers.zip</li> <li>NRC2_octamers.zip</li> </ol> </li> </ul> </li> </ul> <ul> <li> <ul> <li>[AlphaFold 3] Pentamer vs Hexamer comparison for 11 representative NRC proteins: <ul> <li>NRCs.zip</li> </ul> </li> <li>[AlphaFold 3] Pnetamer vs Hexamer comparison for AtZAR1 (PDB:6j5t) and TmSr35 (PDB:7xe0) experimentally validated cryo-EM structure: <ul> <li>Benchmarks.zip</li> </ul> </li> <li>[AlphaFold 3] Pentamer vs Hexamer comparison for a selection of 8 CC, 6 CCG10, and 2 CCR-NLRs: <ul> <li>CC.zip</li> <li>CCG10.zip</li> <li>CCR.zip</li> </ul> </li> </ul> </li> </ul>
Angiosperm NLR Synteny Network Databases
<p>PEP and BED Files of 124 Angiosperm Employed in the Study 'Deciphering Plant NLR Genomic Evolution: A Synteny-Informed Classification Reveals Insights into TNL Gene Loss'</p>
SupplementaryData_A_helper_NLR_targets_organellar_membranes_to_trigger_immunity
<p>Supplementary data for "A_helper_NLR_targets_organellar_membranes_to_trigger_immunity" including:</p> <p>1.Phylogenetics analysis - Data S1 to 6) - Fig. 1A and S1</p> <p>2.AlphaFold3 Models - Data S7 - Fig. 1B and S2</p> <p>3.NRG1_delta14(Nb)_delta16(At) alignment - Data S8</p> <p>4.nrg1 KO plants genotyping (Data S9) - more details in Materials and Methods.</p> <p>5.HR_index_data - Data S10 - raw HR data presented in manuscript.</p> <p>6.Movie S1 - NRG1 puncta upon XopQ activation.</p>
Tracing the Path from Conservation to Expansion Evolutionary Insights into NLR Genes in Oleaceae
<p>Supplementary data files for the family Oleaceae, including the NLR gene outputs and Ka/Ks analysis result files.</p>
Development of a Predictive Model for In-Hospital Mortality in COVID-19 Patients Using CAR, IL-6, IL-6/LY, and NLR: A Single-Center Study in Indonesia
<p>Figure 1. ROC Curve of CAR, IL-6, IL-6/LY, and NLR</p> <p> </p> <p>Figure 2. Kaplan Meier curve of (a) CAR (b) IL-6 (c) IL-6/LY (d) NLR blue line represents group above cut off and green one represents group below cut-off</p> <p> </p>
The N-terminal executioner domains of NLR immune receptors are structurally and functionally conserved across major plant lineages: Extended Data
<p>Raw data and supporting files for an updated version of the manuscript now entitled "The N-terminal executioner domains of NLR immune receptors are structurally and functionally conserved across major plant lineages".</p> <p>Related to an original version of the bioRxiv preprint: https://www.biorxiv.org/content/10.1101/2022.10.19.512840v1 </p>
Development of a Predictive Model for In-Hospital Mortality in COVID-19 Patients Using CAR, IL-6, IL-6/LY, and NLR: A Single-Center Study in Indonesia
<p>Table 1. Demographic data of the subject</p> <p><sup>*</sup>mean (+SD); <sup>#</sup>median (Q1-Q3)</p> <p> </p> <p>Table 2. CAR, IL-6, IL-6/LY, NLR cut-off values and performance in determining mortality</p>
NLR and Emergency Surgery
ClinicalTrials.gov study NCT06549101. IPD Sharing: NO. Countries: 1. Publications: 1.
The Role of NLR in the Diagnosis and Prognosis of Sepsis
ClinicalTrials.gov study NCT05636202. IPD Sharing: NO. Countries: 1. Publications: 18.
Relation Between NLR and IMR in STEMI Patients
ClinicalTrials.gov study NCT02828137. IPD Sharing: UNDECIDED. Countries: 0. Publications: 1.
Prognostic Value of NLR, TLR, and ALC in Predicting ToF Primary Repair Outcome
ClinicalTrials.gov study NCT05976204. IPD Sharing: NO. Countries: 1. Publications: 1.
Relationship Between NLR and Prealbumin Levels With Diaphragm Thickness
ClinicalTrials.gov study NCT04014439. IPD Sharing: UNDECIDED. Countries: 1. Publications: 5.
NLR AND CRP Useful as Cost-Effective Preliminary Prognostic Markers in ST-Elevation Myocardial Infarction
ClinicalTrials.gov study NCT06491667. IPD Sharing: UNDECIDED. Countries: 1. Publications: 4.
Hs-CRP and NLR as Markers of Perioperative Stress
ClinicalTrials.gov study NCT03594695. IPD Sharing: NO. Countries: 1. Publications: 2.
Inflammatory Response Under Spinal vs General Anesthesia in PCNL: NLR, RDW, LAR.
ClinicalTrials.gov study NCT07205224. IPD Sharing: NO. Countries: 1. Publications: 3.
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