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257 results for “Proteomic analysis”
Comparative proteomics analysis of whole-cell catalyst of K. rhizophila strain SA117 catabolism of SMX
<p><span>Sulfamethoxazole (SMX), an oral sulfonamide antibiotic, presents significant environmental challenges due to its persistence and potential role in promoting antibiotic resistance. The bacterial strain <em><span>Kocuria rhizophila</span></em> SA117, isolated from polluted soils, has demonstrated a remarkable capability to metabolize SMX. Proteomic analysis revealed the presence of various enzymes and metabolic pathways that may contribute to SMX degradation, including those involved in para-aminobenzoate condensation and protocatechuate metabolism. Notably, the genome of SA117 harbors eight monooxygenase genes, including those related to antibiotic biosynthesis and flavin family monooxygenases. Additionally, several cytochrome c-encoding genes, known for their role in respiratory versatility and potential application in bioremediation, were identified. Genes associated with sulfur metabolism, including an iron-sulfur cluster gene cluster (SufB, C, D, R, E) linked to oxidative stress response, were also found. A comparative proteomic study under SMX exposure highlighted significant upregulation of stress-related proteins. These findings underscore the metabolic adaptability of <em><span>Kocuria rhizophila</span></em> SA117 and its potential application in the bioremediation of SMX-contaminated environments.</span></p>
Supplementary Files for "Proteomic analysis of the sponge Aggregation Factor implicates an ancient toolkit for allorecognition and adhesion in animals"
<p>This repository hosts supplemental files for the Manuscript "Proteomic analysis of the sponge Aggregation Factor implicates an ancient toolkit for allorecognition and adhesion in animals" by Ruperti, et al., 2024.</p> <ul> <li><strong>Suppl_File_wreath_domain_model.pdb</strong>: AlphaFold3 model for the <em>C. prolifera</em> MAFp3 wreath domain (aa 33 - 317)</li> <li><strong>Suppl_File_MAFAP1_Cterm_model.cif</strong>: AlphaFold3 model for the <em>C. prolifera</em> MAFAP1 C-terminal domain, region 1 and 2</li> <li><strong>Suppl_File_AFInteracting_hmm.hmm</strong>: HMM sequence profile of AF-interacting region of C. prolifera proteins</li> <li><strong>XXX_Foldseek.zip</strong>: Foldseek raw search results, separated by target databases (Swissprot, AFDB, CATH50)</li> </ul>
Proteomic analysis reveals different molecular mechanisms to face water deficit in mycorrhizal and nonmycorrhizal sorghum plants
<p>Differential accumulated proteins in response to water deficit in mycorrhizal and nonmycorrhizal sorghum plants were recovered from 2D gels and identified by HPLC-MSMS. MS analysis was performed by a Nano acquity nanoflow LC system (Waters, Milford, MA, USA) coupled to a linear ion trap (LTQ) velos mass spectrometer (Thermo Fisher Scientific, Bremen, Germany) equipped with a nanoelectrospray ion source.</p>
Proteomic analysis of silenced cathepsin B expression suggests non-proteolytic cathepsin B functionality.
<p>A list of human protein uniprot IDs. The proteins were identified by LC-MS/MS in the cellular supernatant of MDA-MB-231 cells, originally published in:</p> <p>F.C. Sigloch, J.D. Knopf, J. Weißer, A. Gomez-Auli, M.L. Biniossek, A. Petrera, et al., Proteomic analysis of silenced cathepsin B expression suggests non-proteolytic cathepsin B functionality, Biochim. Biophys. Acta - Mol. Cell Res. 1863 (2016) 2700–2709. doi:10.1016/j.bbamcr.2016.08.005. https://www.ncbi.nlm.nih.gov/pubmed/27526672</p>
Proteome analysis of Corynebacterium diphtheriae - macrophage interaction
<p>Contact of <em>Corynebacterium diphtheriae</em> with macrophages induce adaptations on both bacterial and cellular sides. Using an experimental design involving gentamicin protection and liquid chromagraphy followed by mass-spectrometry, a multi-species proteomic dataset was analyzed at different time points of the infection assay. Several previously undescribed <em>Corynebacterium </em>proteins were differentially regulated, as well as key macrophage components of the phagolysosome. Overall, Bacteria responded to phagocytosis by changes in DNA repair, transcription and cell wall synthesis proteins, while macrophages showed changes in components of the innate immune system.</p> <p>This dataset consists of:</p> <ul> <li> Raw protein abundance data for Macrophage THP-1 cells (M0) obtained by LC-MS/MS followed by peptide sequencing using Proteome Discoverer (ThermoFisher) -see .zip folder.</li> <li>Raw protein abundance data for Macrophage <em>C. diphtheriae </em>ISS3319 (CD) obtained by LC-MS/MS followed by peptide sequencing using Proteome Discoverer (ThermoFisher) - see .zip folder.</li> <li>Differential protein abundance analysis for CD and M0 using LIMMA. </li> <li>Data underlying the growth curves observed in CD in RPMI + 10% FBS conditions (infection assay conditions).</li> <li>BLASTP searches, PFAM clans, and InterPro annotations for CD.</li> <li>STRING-based PPI network (baseline) and APSPs between differentially abundant proteins in CD. </li> <li>Related R scripts.</li> </ul>
Code to generate figures 3 and 4 of: "A comprehensive LFQ benchmark dataset to validate data analysis pipelines on modern day acquisition strategies in proteomics."
<p>Code to generate figures 3 and 4 of the manuscript titled "A comprehensive LFQ benchmark dataset to validate data analysis pipelines on modern day acquisition strategies in proteomics."</p> <p> </p>
Source data to publication "Benchmarking of Analysis Strategies for Data-Independent Acquisition Proteomics Using a Large-Scale Dataset Comprising Inter-Patient Heterogeneity"
<p>Source data to publication "Benchmarking of Analysis Strategies for Data-Independent Acquisition Proteomics Using a Large-Scale Dataset Comprising Inter-Patient Heterogeneity".</p> <p>Data and further information at GitHub repository https://github.com/kreutz-lab/dia-benchmarking (DOI: 10.5281/zenodo.6371925)</p>
Proteomic data sets after selecting mitochondrial proteins from the scaffold software for Ingenuity Pathway analysis (IPA Qiagen)
<p>List of fold change proteomic data sets of dFCM- 39 vs. 12Day and105 vs. 12Day, cFCM- 40 vs. 12Day and115 vs. 12Day , mouse heart 90 vs. 1 day after selecting mitochondrial proteins from the scaffold software for Ingenuity Pathway Analysis (IPA Qiagen)</p>
Fig. 6 in Salivary gland proteome analysis of developing adult female HaemaphYSaliS longiCorniS ticks: molecular motor and TCA cycle-related proteins play an important role throughout development
Fig. 6 Phenotype associated with dynein, kinesin, isocitrate dehydrogenase and citrate synthase mRNA subjected to RNAi in female ticks via injection with the corresponding dsRNA. a Dynein dsRNA injection. b Kinesin dsRNA injection. c Isocitrate dehydrogenase dsRNA injection. d Citrate synthase dsRNA injection. e GFP dsRNA injection, control. f No injection, control. Scale-bars: 5 mm
Fig. 7 in Salivary gland proteome analysis of developing adult female HaemaphYSaliS longiCorniS ticks: molecular motor and TCA cycle-related proteins play an important role throughout development
Fig. 7 Digital micrographs of salivary gland acinar morphological changes in unfed female H. longicornis after RNAi.The time at which the tick bit the host and began sucking blood was recorded as day 0. a–e Dynein dsRNA injection. f–j Kinesin dsRNA injection. k–o Isocitrate dehydrogenase dsRNA injection. p–t Citrate synthase dsRNA injection. u–y GFP dsRNA injection, control. Scale-bars: 25 µm
Fig. 4 in Salivary gland proteome analysis of developing adult female HaemaphYSaliS longiCorniS ticks: molecular motor and TCA cycle-related proteins play an important role throughout development
Fig. 4 KEGG pathway enrichment analysis of the differentially expressed proteins in 5 different Clusters. Terms with a P-value <0.05 were used to draw the column diagrams. a–e KEGG pathway enrichment for the proteins in Cluster 1 to Cluster 5
Fig. 3 in Salivary gland proteome analysis of developing adult female HaemaphYSaliS longiCorniS ticks: molecular motor and TCA cycle-related proteins play an important role throughout development
Fig. 3 GO functional annotations for all the differentially expressed proteins. a–c GO annotations of differentially expressed proteins in the salivary glands of partially fed ticks compared with unfed ticks (115:114). d–f GO annotations of differentially expressed proteins in the salivary glands of mated semi-engorged ticks compared with partially fed ticks (116:115). g–i GO annotations of differentially expressed proteins in the salivary glands of engorged ticks compared with mated semi-engorged ticks (117:116). Abbreviations: BP, biological process; CC, cellular component; MF, molecular function; CO, cellular component organization or biogenesis
Fig. 5 in Salivary gland proteome analysis of developing adult female HaemaphYSaliS longiCorniS ticks: molecular motor and TCA cycle-related proteins play an important role throughout development
Fig. 5 RT-qPCR analyzed the mRNA expression levels of dynein, kinesin, isocitrate dehydrogenase, and citrate synthase during the four feeding stages of salivary gland development
Fig. 2 in Salivary gland proteome analysis of developing adult female HaemaphYSaliS longiCorniS ticks: molecular motor and TCA cycle-related proteins play an important role throughout development
Fig. 2 Statistics and cluster analysis for the identified proteins and their expression levels in the salivary glands of female H. longicornis. a Venn diagram showing the number of proteins (with CV <20%) identified in the three experiments. b Venn diagram showing the number of proteins with quantitative information. c Cluster analysis according to trends in protein expression in the salivary glands of female ticks
Fig. 1 in Salivary gland proteome analysis of developing adult female HaemaphYSaliS longiCorniS ticks: molecular motor and TCA cycle-related proteins play an important role throughout development
Fig. 1 Workflow for quantitative proteomics analysis of changes in protein expression in the salivary glands of female H. longicornis during the blood-feeding process
Scripts and analysis files for categorization of PKZILLA matching proteomic peptides into protein-unique, protein-multimatch & exon-unique, exon-multimatch categories.
<p>A .zip file containing the source data files & Jupyter notebook for analysis of the <em>Prymnesium parvum</em> 12B1 PKZILLA-detecting proteomic results (<a href="https://doi.org/10.5281/zenodo.10023441">https://doi.org/10.5281/zenodo.10023441</a>), and the resulting files from the workflow. See "Analysis of proteomic results" section of the manuscript Materials and Methods for further detail. </p> <p><strong>Key files:</strong></p> <ul> <li>'PKZILLA-1_classify_peptides.txt' - A plaintext report of the # of classified peptides for PKZILLA-1</li> <li>'PKZILLA-2_classify_peptides.txt' - A plaintext report of the # of classified peptides for PKZILLA-2</li> <li>'./hierarchical_classified_xlsx/' - Excel spreadsheets with the classified peptides for PKZILLA-1 and PKZILLA-2</li> <li>'./Process_into_polypeptide_coordinates/' - Workflow, results, and plots for back-alignment of peptides back to PKZILLA-1 and PKZILLA-2 genomic loci</li> </ul>
Proteomic data set of the analysis of black poplar (Populus nigra L.) seed storability
<p>Proteomic data set containing protein identification parameters (ESI MS/MS) and GO annotation functional classification (UniProt and QuickGO). Identification parameters of differentially abundant proteins of black poplar (<em>Populus nigra</em> L.) seeds stored in different temperature (3, -3, -20 and -196°C) and time (12 and 24 months) conditions. Proteins were extracted and separated according to their isoelectric point (pI) and mass using 2-dimensional electrophoresis. Proteins that varied in abundance for temperature and time of storage were identified by mass spectrometry (ESI MS/MS). The mascot search algorithm (http://www.matrixscience.com) was used for protein identification against the NCBInr (http://www.ncbi.nig.gov) databases.Identified proteins were grouped due to biological process, molecular function and subcellular localization according to the gene ontology (GO) annotation using UniProt database and QuickGO search (https://www.ebi.ac.uk/QuickGO/).</p>
Fig. 4 in Proteomic analysis of the venom of the social wasp Apoica pallens (Hymenoptera: Vespidae)
Fig. 4. Identified proteins of social wasp Apoica pallens venom and their functions according to the literature.
Fig. 2 in Proteomic analysis of the venom of the social wasp Apoica pallens (Hymenoptera: Vespidae)
Fig. 2. Two-dimensional reference gel (14%) of the venom of the social wasp Apoica pallens, showing the proteins identified by MALDI-TOF/TOF analysis.
Fig. 3 in Proteomic analysis of the venom of the social wasp Apoica pallens (Hymenoptera: Vespidae)
Fig. 3. Classification of proteins according to the representativity in number of proteins identified in the Apoica pallens venom.
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
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