2022-0222-SK cell line infected by ZIKV（MR766,PRVABC.59)-1044
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo Sapiens
SUBMITTER: 
Yu Gu
PROVIDER: PXD050964 | iProX | Mon Mar 25 00:00:00 GMT 2024
REPOSITORIES: iProX
Publications
Identification of antiviral RNAi regulators, ILF3/DHX9, recruit at ZIKV stem loop B to protect against ZIKV induced microcephaly.
Lei Zhiwei Z Gu Yu Y Liu Ying Y Liu Hailiang H Lu Xiaohua X Chen Weijie W Zhou Lu L Pan Pan P Chen Zhuohong Z Yue Zhaoyang Z Ruan Jinhui J Zhu Leqing L Li Guangqiang G Xia Xichun X Yu Yang Y Dai Jianfeng J Chen Xin X
Nature communications 20250226 1
Zika virus (ZIKV) is a member of the Flaviviridae family and causes congenital microcephaly and Guillain-Barré syndrome. Currently, there is a lack of approved vaccines or therapies against ZIKV infection. In this study, we profile vRNA‒host protein interactomes at ZIKV stem‒loop B (SLB) and reveal that interleukin enhancer binding factor 3 (ILF3) and DEAH-box helicase 9 (DHX9) form positive regulators of antiviral RNA inference in undifferentiated human neuroblastoma cells and induced pluripote ...[more]
Similar Datasets
Project description:Over the past few decades cross-linking mass spectrometry (XLMS) has become a powerful tool for identification of protein-protein interactions and for gaining insight into the structures of proteins in living cells, tissues, and organelles. The development of new crosslinkers, enrichment strategies and data acquisition methods led to the establishment of numerous new software tools specifically for the analysis and interpretation of cross-linking data. We previously published one of these tools called MS Annika, a cross-linking search engine which can accurately identify cross-linked peptides in MS2 spectra from a variety of different MS-cleavable crosslinkers. In this publication we present an updated MS Annika and a new search algorithm that additionally supports processing of data from MS2-MS3-based approaches and identification of peptides from MS3 spectra. In the new MS2-MS3 search algorithm, MS3 spectra are matched to their corresponding precursor doublet peak in the MS2 scan to identify the crosslink modification and the monoisotopic peptide mass. This information is then used to adjust the MS3 spectra for search with MS Amanda, our in-house developed peptide search engine, to identify the cross-linked peptides. Peptides that are identified in the MS2 scan and one or more of the associated product MS3 scans are re-scored with a novel scoring function to reflect the increased confidence. Finally, the detected cross-links are validated by estimating the false discovery rate (FDR) using a target-decoy approach. We evaluated the MS3-search-capabilities of MS Annika on five different datasets covering a variety of experimental approaches and compared it to XlinkX and MaXLinker, two other cross-linking search engines that support MS3 crosslink identification. Three of the datasets were benchmark datasets of synthetic peptides that allow calculation of an experimentally validated FDR, and we show that MS Annika detects up to 4 times more true unique crosslinks than MaXLinker and up to 35% more than XlinkX while simultaneously yielding less false positive hits and therefore a more accurate FDR than the other two search engines. Additionally, for the other two datasets we could show that MS Annika finds between 74% to 2.5 times more crosslinks at 1% estimated FDR and reveals protein-protein interactions that are not detected by either XlinkX or MaXLinker.
2023-08-13 | PXD041955 | Pride
Project description:Here we designed a search-engine for single-cell epigenome profiles. We tested different application of search-engine using different data-sets including mESC scATAC-seq profile.
2022-12-27 | GSE192644 | GEO
Project description:A comprehensive proteome map is essential to elucidate molecular pathways and protein functions. Although great improvements in sample preparation, instrumentation and data analysis already yield-ed impressive results, current studies suffer from a limited proteomic depth and dynamic range there-fore lacking low abundant or highly hydrophobic proteins. Here, we combine and benchmark advanced micro pillar array columns (µPAC) operated at nanoflow with wide window acquisition (WWA) and the AI-based CHIMERYS search engine for data analysis to maximize chromatographic separation power, sensitivity and proteome coverage. The wide window acquisition method merges the strengths of DDA and DIA. WWA uses a broad isolation window (≥4 Th) for data-dependent precursor selection. Similar to DIA, precursor ions close to those selected are co-fragmented, producing chimeric spectra that boost IDs and improve coverage of low-abundance peptides, which would otherwise be missed. WWA is particularly powerful when combined with the AI-driven CHIMERYS search algorithm, which allows confident identification of up to eleven peptides from a single chimeric spectrum. Developed by MSAID, the CHIMERYS algorithm makes use of accurate fragment spectrum predictions trained on millions of spectra, which allows to utilize additional spectral properties such as relative signal intensities for drastically improved identification rates. Entrapment experiments were conducted searching mouse immunoprecipitation samples with MS Amanda 2.0 and CHIMERYS by applying an additional custom-made decoy database, which demonstrated excellent protein, peptide and PSM FDR control from 1% upwards for both search engines. Combining wide precursor isolation widths of 4-12 Th with the CHIMERYS search engine identified 51-74% more proteins and 59-150% more peptides for single cell, immunoprecipitation and multi-species samples in comparison to a standard proteomics workflow employing MS Amanda 2.0 and an isolation width of 1 Th. Application of different isolation widths revealed that the optimal isolation window size varies according to sample amount and complexity with 12 Th resulting in the highest number of identifications for single cell-equivalent injection amounts, while 4 Th provided best results for classical bulk inputs of 400ng. Evaluation of coefficients of variation also yielded improved results for WWA over classical DDA when assessing single cell, 40 cell and 250pg bulk HeLa lysates. Overall, WWA and CHIMERYS resulted in substantially improved proteomic depth and quantification for all sample types tested and will provide a highly valuable toolset for the proteomics community.
2024-02-13 | PXD045500 | Pride
Project description:Discovery of human leukocyte antigen (HLA) class I presented peptides of bacterial origin is essential to discover bacterial antigen targets as putative vaccine constituents. However, reliable identification of such HLA-presented bacterial epitopes are extremely low abundant compared to the host proteome. Here, we describe an upgraded bioinformatical workflow to enhance the confident detection of bacterial immunopeptides. Re-analysis of Listeria monocytogenes (Listeria)-infected cell cultures was searched by four search engines in parallel with follow-up by rescoring by MS2Rescore and integration of all search results. Boosting identification by both rescoring and integration, this delivered an additional 18 Listeria peptides (+26.5%) matching 15 different proteins (+35.7%) compared to the initial analysis. Moreover, conflicts between search engine results uncovered ambiguities in spectra-to-peptide assignments, in some cases with spectra assigned to human and Listeria peptides. Finally, we demonstrate how our workflow is compatible with timsTOF data acquisition, incorporating rescoring of ion mobility features using TIMS2Rescore.
2025-02-05 | PXD055547 | Pride
Project description:More than half of the mass spectra could not be identified in most proteome mass spectrometry experiments. Various modifications have been considered as a major reason. Open search strategy was then introduced to solve this problem, however, lacking thorough quality assessment using independent information. Here, we used the “Suspicious Discovery Rate (SDR)” based on the translatome sequencing (RNC-seq) as an independent source to assess the proteome open search strategy. We found that the open search strategy increased the spectra utilization with the cost of increasing suspicious identifications that lacks translation evidence. We further suggested that restricting the peptide FDR below 0.1% would efficiently control the suspicious identifications of open search methods and enhanced the confidence of the peptide identification with modifications than the narrow window search. These results facilitated the proper use of open search methods for higher quality of proteome identifications with the information of post-translational modifications and single amino acid polymorphisms
2018-10-04 | GSE112623 | GEO
Project description:Unconventional epitopes presented by HLA class I complexes are emerging targets for T cell targeted immunotherapies. Their identification by mass spectrometry required development of novel methods to cope with the large number of theoretical candidates. Methods to identify post-translationally spliced peptides led to a broad range of outcomes. We here investigated the impact of three common database search engines – i.e. Mascot, Mascot+Percolator and PEAKS DB – as final identification step, as well as the features of target database on the ability to correctly identify non-spliced and cis-spliced peptides. We used ground truth datasets measured by mass spectrometry to benchmark methods’ performance and extended the analysis to HLA class I immunopeptidomes. PEAKS DB showed better precision and recall of cis-spliced peptides and larger number of identified peptides in HLA class I immunopeptidomes than the other search engine strategies. The better performance of PEAKS DB appears to result from better discrimination between target and decoy hits and hence a more robust FDR estimation, and seems independent to peptide and spectrum features here investigated. Head of the research group Molecular Immunology at King’s College London and the Francis Crick Institute, London (UK). Email: michele.mishto@kcl.ac.uk,
2022-04-06 | PXD031709 | Pride
Project description:The continuing ‘desire’ in obtaining more quantitative and detailed information from cellular proteomics experiments in regards to proteome coverage and protein modifications asks for a systematic investigation of the protein extraction and digestion protocols, in particular when working with unicellular organisms with a strong cell wall such as the model yeast S. cerevisiae. The selection of a suitable sample preparation workflow is crucial to obtain in-depth proteome coverage, as the use of certain sample preparation protocols may bias the protein identification or induce (unexpected) peptide modifications. Here, we made an extensive comparison of preparation workflows commonly applied to S. cerevisiae. Workflows were compared on the basis of identified MS/MS spectra, peptide sequences and number and type of modifications using both restricted (Peaks) and unrestricted (TagGraph) database search approaches. The proteome coverage was mainly affected by the sample collection approach, while it was maximized using a FASP. Extensive reagent specific peptide modifications were detected when using formic acid, but also when using acetone. Such artefacts split the analyte mass signals and generate additional chemical noise that may also elute differently compared to the native peptide. The use of both an unrestricted and restricted database search increased identification rates significantly and resulted in the identification of approximately 70% of the MS2 spectra for the best protocol. The unidentified spectra were assessed by their de novo sequencing score. This confirmed that those spectra consisted by a majority of very low quality spectra, insufficient to match to database sequences. However, a small fraction of the unidentified spectra showed high quality, which presumably derive from unknown sequence variants not present in the database. This study demonstrates the high importance of the sample preparation workflow and the obtained results will guide researchers in the field to optimize sample preparation procedures.
2022-03-31 | PXD026806 | Pride
Project description:Chemical cross-linking has emerged as a powerful approach for the structural characterization of proteins and protein complexes. However, the correct identification of covalently linked (cross-linked) peptides analyzed by tandem mass spectrometry is still an open challenge. Here we present SIM-XL, a software tool that can analyze data generated through commonly used cross-linkers (e.g., BS3/DSS, etc.). Our software introduces a new paradigm for search-space reduction, which ultimately accounts for its increase in speed and sensitivity. Moreover, our search engine is the first to capitalize on reporter ions for selecting tandem mass spectra derived from cross-linked peptides. It also makes available a 2D interaction map and a spectrum-annotation tool unmatched by any of its kind. We show SIM-XL to be more sensitive and faster than a competing tool when analyzing a dataset obtained from the human HSP90. The software is freely available for academic use at http://patternlabforproteomics.org/sim-xl.
2015-02-02 | PXD001677 | Pride
Project description:Most bottom-up proteomics experiments share two features: The use of trypsin to digest proteins for mass spectrometry and the statistic driven matching of the measured peptide fragment spectra against protein database derived in silico generated spectra. While this extremely powerful approach in combination with latest generation mass spectrometers facilitates very deep proteome coverage, the assumptions made have to be met to generate meaningful results. One of these assumptions is that the measured spectra indeed have a match in the search space, since the search engine will always report the best match. However, one of the most abundant proteins in the sample, the protease, is often not represented in the employed database. It is therefore widely accepted in the community to include the protease and other common contaminants in the database to avoid false positive matches. Although this approach accounts for unmodified trypsin peptides, the most widely employed trypsin preparations are chemically modified to prevent autolysis and premature activity loss of the protease. In this study we observed numerous spectra of modified trypsin derived peptides in samples from our laboratory as well as in datasets downloaded from public repositories. In many cases the spectra were assigned to other proteins, often with good statistical significance. We therefore designed a new database search strategy employing an artificial amino acid which accounts for these peptides with a minimal increase in search space and the concomitant loss of statistical significance. Moreover, this approach can be easily implemented into existing workflows for many widely used search engines.
2016-04-15 | PXD002726 | Pride
Project description:Purpose: The identification of protein isoforms in complex biological samples is challenging. We, therefore, used a mass spectrometry (MS) approach to unambiguously identify cardiac myofilament protein isoforms based on the observation of a tryptic peptide consisting of a sequence unique to a particular isoform. Experimental design: Three different workflows were used to isolate and fractionate the rat cardiac myofilament subproteomes. All fractions were analyzed on an LTQ-Orbitrap MS, proteins were identified using various search engines (Mascot, X!Tandem, X!Tandem Kscore and OMSSA) with results combined via PepArML Meta-Search Engine, and a post-search analysis performed by MASPECTRAS. Results: The combination of multiple workflows and search engines resulted in a larger number of non-redundant proteins identified than individual methods. A total of 461 proteins were observed overlapping in two or three of the workflows. Literature search for myofilament presence with manual validation of the MS spectra was carried out for unambiguous identification: 10 cardiac myofilament and 17 cardiac myofilament-associated proteins were confirmed to have multiple isoforms or sub-isoforms. Conclusion and clinical relevance: We have identified multiple isoforms of myofilament proteins that are present in cardiac tissue using unique tryptic peptides. Changes of distribution of these protein isoforms under pathological conditions could ultimately allow for clinical diagnostics or as therapeutic targets.
2014-08-28 | PXD000874 | Pride