Resultados de investigación

Peer reviewed

Draft genome for the green microalgae species Coelastrella thermophila, structural annotation and sequening data., Peer reviewed

1H, 13C NMR spectra and HPLC chromatograms of the new synthesized compounds (Figures S1–S10); evaluation of the antiviral activity of compounds 1 and 2 against VSV pseudotyped with the Wuhan-Hu-1 S protein (Figure S11); evaluation of the antiviral activity of compounds 2 and 2-Na salt against different enveloped viruses (Figure S12); and evaluation of the effect of compounds 2 and 2-Na salt on cell health (Figure S13)., Peer reviewed

This archive includes data files associated with the paper "Fine-scale movement data reveal primarily surface foraging and nocturnal flight activity in the endangered Bermuda petrel" in Ecology and Evolution., The file "BEPE_2023_deployments.csv" contains metadata about each deployment. Each deployment has a unique identifier (dep_id) based off of the tag id, bird id and start date. The file "BEPE_acc_behaviour_classified.csv" includes the accelerometer derived metrics and behavioural classifications described in the paper. The "raw_data" folder contains files for each individual deployment named after the dep_id field. Biologging data have been trimmed to only include data collected while devices were on birds. All datetime data have been standardized to UTC. Data fields have been standardized across the three device types used. Each biologging file includes columns for all four data types recorded (GPS, TDR, ACC, MAG) to facilitate combining data across logger types for analysis., These data are from tracking Bermuda Petrels (BEPE) at Nonsuch Island during the incubation period in 2023 During the 2023 field season, there were 25 deployments of biologgers on BEPE, of which 18 deployments were successful. Three logger types were used that recorded GPS, TDR, accelerometer (ACC), and/or magnetometer (MAG) data: Axy5 (Technosmart - TDR, ACC, MAG), AxyTrek (Technomsart - GPS, TDR, MAG), and Nano Fix-GEO (PathTrack - GPS)., Peer reviewed

[CONTENT] This page contains four files: (1) 'InvaCost_database_v4.1' which contains 13,553 cost entries depicted by 66 descriptive columns; (2) ‘Descriptors 4.1’ provides full definition and details about the descriptive columns used in the database; (3) ‘Update_Invacost_4.1’ has details about the all the changes made between previous and current versions of InvaCost; (4) ‘InvaCost_template_4.1’ (downloadable file) provides an easier way of entering data in the spreadsheet, standardizing all the terms used on it as much as possible to avoid mistakes and saving time at post-refining stages (this file should be used by any external contributor to propose new cost data)., InvaCost is the most up-to-date, comprehensive, standardized and robust data compilation and description of economic cost estimates associated with invasive species worldwide1. InvaCost has been constructed to provide a contemporary and freely available repository of monetary impacts that can be relevant for both research and evidence-based policy making. The ongoing work made by the InvaCost consortium2,3,4 leads to constantly improving the structure and content of the database., AXA Research Fund Chair of Invasion Biology; Developing and applying scenarios of biological invasions (AlienScenarios) - FWF Austrian Science Fund; French National Research Agency (ANR-14-CE02-0021); BNP-Paribas Foundation Climate Initiative, Peer reviewed

Data S1. Letter-probability matrix for WRKY03 transcription factor binding sites (TFBS)., Figure S1. Monosaccharide compositions of cell wall extracts from flowers and berry skins of different grapevine genotypes. Figure S2. Phylogenetic tree of Arabidopsis thaliana and Vitis vinifera Pectin Methyl Esterase (PME) genes. Figure S3. Expression profiles of PME family genes across various grapevine organs and tissues at different developmental stages. Figure S4. Summary of RNA-seq results comparing Bc-infected and control flowers of ‘Souvigner Gris’ (SG) and ‘Teroldego’ (TE) at 24 h post-inoculation. Figure S5. Summary of on-target analysis of the PME10 knockout (KO) lines. Figure S6. Summary of the off-target analysis of the PME10 KO lines. Figure S7. Phenotypic characterisation of PME10 KO lines compared with control plants. Figure S8. Phenotypic characterisation of PME10 overexpressing (OE) lines compared with control plants. Figure S9. WRKY03 DAP-seq and DAP-qPCR analyses of the WRKY03-PME10 interaction. Figure S10. Melting curve analysis during qPCR assays using primers for PME10, PME11, and PME12. Table S1. Complete list of the 62 PME genes identified in the V. vinifera PN40024 reference genome. Table S2. Summary of the Illumina read processing and mapping to the concatenated V. vinifera PN40024 12X.v2 and B. cinerea DW1 genome assemblies. Table S3. Differentially expressed genes in ‘Souvigner Gris’ and V. vinifera ‘Teroldego’ flowers at 24 h post-inoculation with B. cinerea. Table S4. Metadata of publicly available RNA-seq experiments on B. cinerea-grapevine berry interactions, included in the Botrytis Stress Atlas Explorer. Table S5. Predicted PME10 off-target regions in V. vinifera ‘PN40024’ and ‘Sugraone’ genome assemblies. Table S6. WRKY03-binding events on PME genes detected by DAP-seq analysis. Table S7. PME10 DAP-seq qPCR conditions. Table S8. List of primers used throughout the study. Methods S1. Molecular analysis and acclimation procedures for PME10 OE and KO lines. Methods S2. Detailed procedures for Bc artificial inoculation assays. Methods S3. Detailed experimental procedures for biochemical and immunohistochemical analyses. Methods S4. Computational and gene expression analysis workflows. Methods S5. Detailed experimental procedures for DAP-seq and DAP-qPCR analyses, PME10 promoter analysis and cloning, and dual luciferase assay., Peer reviewed

Peer reviewed

Experimental data has been divided in folders as follows: PEPSIN: QUAL PEPS: LC-MS data files in mzml format (Rep 1 and Rep 4) from qualitative analysis of pepsin-digested samples. SRM PEPS: LC-MS data files in mzml format (Cal, mix, Rep and QC batches) from quantitative SRM analysis of pepsin-digested samples. --THERMOLYSIN: QUAL THERM: LC-MS data files in mzml format (Rep 1 and Rep 4) from qualitative analysis of thermolysin-digested samples. SRM THERM: LC-MS data files in mzml format (Cal, mix, Rep and QC batches) from quantitative SRM analysis of thermolysin-digested samples. -- TRYPSIN: QUAL TRYPS: LC-MS data files in mzml format (Rep 1 and Rep 4) from qualitative analysis of trypsin-digested samples. SRM TRYPS: LC-MS data files in mzml format (Cal, mix, Rep and QC batches) from quantitative SRM analysis of trypsin-digested samples., Beta-casein (β-CN) encoded by CSN2 gene is a milk protein composed of 209 amino acids. The most common genotype in European dairy cattle is A1A2, producing both A1 and A2 variants, merged in most of traded bovine milks. Current evidence indicates that individuals who are neither lactose intolerant nor allergic to milk proteins but still experience digestive discomfort with conventional milk may digest milk containing only the A2 β-CN variant more easily. Thus, a premium A2 milk category emerged worldwide through the selection of A2A2-genotyped cows to produce added-value milk and dairy products. Absence of A1 variant in bovine milk was assessed by a straightforward and cost-effective bottom-up low-resolution liquid chromatography-mass spectrometry (LC-MS) methodology powered by ion-trap analysis. A preliminary data-dependent MS/MS exploratory approach characterized A1 and A2 variants in A1A1 and A2A2 milk extracts digested with trypsin, pepsin and thermolysin. Relative quantitation of selected peptide biomarkers yielded by proteases assayed was subsequently performed through a targeted Selected Reaction Monitoring (SRM) analysis, detecting levels of 0.1% of A1 β-CN variant in A1A1 and A2A2 milk mixtures. Besides good results from tryptic digestion, alternative thermolysin treatment yielded short peptides of different lengths that facilitated optimization of chromatographic separation and detection, while acidic pepsin hydrolysis can be of interest for developing low-cost sampling procedures in milk proteomics. Sensitivity, efficiency and robustness shown by this affordable proteomic strategy favor its implementation by food control laboratories addressing authentication of A2 milk, resulting an interesting tool for the creation of accessible insights into food proteomics., The Ministry of Education, Universities and Employment of the Generalitat Valenciana for LRB´s postdoctoral fellowship (CIAPOS/2023/313). IATA-CSIC as Center of Excellence Accreditation Severo Ochoa (CEX2021-001189-S/MCIU/AEI/ 10.13039/501100011033) via IMPULSA-IATA project call., With funding from the Spanish government through the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2021-001189-S)., Peer reviewed

Supporting figures and tables: dispersion analysis by variable, photography’s of AuNC@GSH dispersion, normal Q–Q plot of standardized residuals with AdaBoost, and tables containing the predicted and experimental values of the different tests., Peer reviewed

Figure S1: Different peptides released after the simulated hydrolysis of 11S seed globulin – Chenopodium quinoa (AAS67037.1) – with stem bromelain. Figure S2. Molecular docking, a general view of protein-ligand interactions showing the residues from the active site involved in making the interactions with the ligand (quinoa peptides).Figure S3: Mass spectrum analysis of quinoa-derived peptides (from simulated hydrolysis with stem bromelain) YDDER, NIYQIS, and QDQHQKIR after being chemically synthesized., Peer reviewed