BUSCADOR RECOLECTA

Additional file 10: Table S10. Bayes factors, marginal posterior means and standard deviations of cage variance ratio for OTU influenced by cage effects together with the associated probability of these estimates being higher than 0.10. The frequency among the rabbit samples and the taxonomic assignment are also provided for each OTU., Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria Horizon 2020 Framework Programme Ministerio de Ciencia, Innovación y Universidades, Peer reviewed

Supplementary Figures.docx Supplementary Materials and Methods.docx Supplementary Table Legends.docx Supplementary Table S1.docx Supplementary Table S2.xlsx Supplementary Table S3.xlsx Supplementary Table S4.docx Supplementary Table S5.xlsx Supplementary Table S6.xlsx, Mass spectrometry (MS)-based proteomics profiling has undoubtedly increased the knowledge about cellular processes and functions. However, its applicability for paucicellular sample analyses is currently limited. Although new approaches have been developed for single-cell studies, most of them have not (yet) been standardized and/or require highly specific (often home-built) devices, thereby limiting their broad implementation, particularly in non-specialized settings. To select an optimal MS-oriented proteomics approach applicable in translational research and clinical settings, we assessed 10 different sample preparation procedures in paucicellular samples of closely-related cell types. Particularly, five cell lysis protocols using different chemistries and mechanical forces were combined with two sample clean-up techniques (C18 filter- and SP3-based), followed by tandem mass tag (TMT)-based protein quantification. The evaluation was structured in three phases: first, cell lines from hematopoietic (THP-1) and non-hematopoietic (HT-29) origins were used to test the approaches showing the combination of a urea-based lysis buffer with the SP3 bead-based clean-up system as the best performer. Parameters such as reproducibility, accessibility, spatial distribution, ease of use, processing time and cost were considered. In the second phase, the performance of the method was tested on maturation-related cell populations: three different monocyte subsets from peripheral blood and, for the first time, macrophages/microglia (MAC) from glioblastoma samples, together with T cells from both tissues. The analysis of 50,000 cells down to only 2,500 cells revealed different protein expression profiles associated with the distinct cell populations. Accordingly, a closer relationship was observed between non-classical monocytes and MAC, with the latter showing the co-expression of M1 and M2 macrophage markers, although pro-tumoral and anti-inflammatory proteins were more represented. In the third phase, the results were validated by high-end spectral flow cytometry on paired monocyte/MAC samples to further determine the sensitivity of the MS approach selected. Finally, the feasibility of the method was proven in 194 additional samples corresponding to 38 different cell types, including cells from different tissue origins, cellular lineages, maturation stages and stimuli. In summary, we selected a reproducible, easy-to-implement sample preparation method for MS-based proteomic characterization of paucicellular samples, also applicable in the setting of functionally closely-related cell populations., Peer reviewed

1 table., Additional file 1: Table S1. Metadata associated with the 425 rabbit cecal samples analyzed in this study., Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria Horizon 2020 Framework Programme Ministerio de Ciencia, Innovación y Universidades, Peer reviewed

1 table., Additional file 2: Table S2. Table of filtered and CSS-normalized OTU., Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria Horizon 2020 Framework Programme Ministerio de Ciencia, Innovación y Universidades, Peer reviewed

1 table., Additional file 3: Table S3. Taxonomic assignment of representative sequences of each OTU included in Additional file 2: Table S2., Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria Horizon 2020 Framework Programme Ministerio de Ciencia, Innovación y Universidades, Peer reviewed

The dataset is made available under the Open Database License. Any rights in individual contents of the database are licensed under the Database Contents License. Please, read the full ODbL 1.0 license text for the exact terms that apply. Users of the dataset are free to: Share: copy, distribute and use the database, either commercially or non-commercially. Create: produce derivative works from the database. Adapt: modify, transform and build upon the database. Under the following conditions: Attribution: You must attribute any public use of the database, or works produced from the database. For any use or redistribution of the database, or works produced from it, you must make clear to others the license of the original database. Share-Alike: If you publicly use any adapted version of this database, or works produced from an adapted database, you must also offer that adapted database under the ODbL, This work was supported by grants PID2020-116940RB-I00 and CEX2021-001189-S funded by MCIN/AEI/10.13039/501100011033. T. J. received the ACIF/2019/214 predoctoral fellowship from “Generalitat Valenciana”., With funding from the Spanish government through the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX 2021-001189-S), Peer reviewed

1 figure., Additional file 4: Figure S1. Geweke z-statistics for genetic, litter and cage variance ratios computed for the microbial traits that were better adjusted with the normal linear mixed model., Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria Horizon 2020 Framework Programme Ministerio de Ciencia, Innovación y Universidades, Peer reviewed

Supplementary Table S10. Comparative analysis of -omics platforms Supplementary Table S10. Comparative analysis of -omics platforms Supplementary Table S7.xlsx Supplementary Table S8.xlsx Supplementary Table S9.xlsx, Mass spectrometry (MS)-based proteomics profiling has undoubtedly increased the knowledge about cellular processes and functions. However, its applicability for paucicellular sample analyses is currently limited. Although new approaches have been developed for single-cell studies, most of them have not (yet) been standardized and/or require highly specific (often home-built) devices, thereby limiting their broad implementation, particularly in non-specialized settings. To select an optimal MS-oriented proteomics approach applicable in translational research and clinical settings, we assessed 10 different sample preparation procedures in paucicellular samples of closely-related cell types. Particularly, five cell lysis protocols using different chemistries and mechanical forces were combined with two sample clean-up techniques (C18 filter- and SP3-based), followed by tandem mass tag (TMT)-based protein quantification. The evaluation was structured in three phases: first, cell lines from hematopoietic (THP-1) and non-hematopoietic (HT-29) origins were used to test the approaches showing the combination of a urea-based lysis buffer with the SP3 bead-based clean-up system as the best performer. Parameters such as reproducibility, accessibility, spatial distribution, ease of use, processing time and cost were considered. In the second phase, the performance of the method was tested on maturation-related cell populations: three different monocyte subsets from peripheral blood and, for the first time, macrophages/microglia (MAC) from glioblastoma samples, together with T cells from both tissues. The analysis of 50,000 cells down to only 2,500 cells revealed different protein expression profiles associated with the distinct cell populations. Accordingly, a closer relationship was observed between non-classical monocytes and MAC, with the latter showing the co-expression of M1 and M2 macrophage markers, although pro-tumoral and anti-inflammatory proteins were more represented. In the third phase, the results were validated by high-end spectral flow cytometry on paired monocyte/MAC samples to further determine the sensitivity of the MS approach selected. Finally, the feasibility of the method was proven in 194 additional samples corresponding to 38 different cell types, including cells from different tissue origins, cellular lineages, maturation stages and stimuli. In summary, we selected a reproducible, easy-to-implement sample preparation method for MS-based proteomic characterization of paucicellular samples, also applicable in the setting of functionally closely-related cell populations., Peer reviewed

The dataset contains data from the following platforms: Drifters; Underway-CTD. -- Differences between files: SURFACE: contains the data from CARTHE drifters 15m: contains the data from SVP drifters., This dataset has been used in the publication "Drifter observations reveal intense vertical velocity in a surface ocean front"., drifters_CALYPSO2019_15m_nofilt_cluster2.csv, drifters_CALYPSO2019_SURFACE_nofilt_cluster2.csv, uctd_calypso2019_cluster2.nc, Peer reviewed

Resources available on the publisher's site: http://dx.doi.org/10.1055/s-0042-1749328, 1-Supplementary Methods 1.1-Cohorts included in the study 2-e-Table legends 3-e-Figure legends 4-e-Tables 5-e-Figures 6-e-References, Peer reviewed