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Ramsbottom KA, Prakash A, Riverol YP, Camacho OM, Sun Z, Kundu DJ, Bowler-Barnett E, Martin M, Fan J, Chebotarov D, McNally KL, Deutsch EW, Vizcaíno JA, Jones AR. A meta-analysis of rice phosphoproteomics data to understand variation in cell signalling across the rice pan-genome. bioRxiv 2023:2023.11.17.567512. [PMID: 38014076 PMCID: PMC10680829 DOI: 10.1101/2023.11.17.567512] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
Phosphorylation is the most studied post-translational modification, and has multiple biological functions. In this study, we have re-analysed publicly available mass spectrometry proteomics datasets enriched for phosphopeptides from Asian rice (Oryza sativa). In total we identified 15,522 phosphosites on serine, threonine and tyrosine residues on rice proteins. We identified sequence motifs for phosphosites, and link motifs to enrichment of different biological processes, indicating different downstream regulation likely caused by different kinase groups. We cross-referenced phosphosites against the rice 3,000 genomes, to identify single amino acid variations (SAAVs) within or proximal to phosphosites that could cause loss of a site in a given rice variety. The data was clustered to identify groups of sites with similar patterns across rice family groups, for example those highly conserved in Japonica, but mostly absent in Aus type rice varieties - known to have different responses to drought. These resources can assist rice researchers to discover alleles with significantly different functional effects across rice varieties. The data has been loaded into UniProt Knowledge-Base - enabling researchers to visualise sites alongside other data on rice proteins e.g. structural models from AlphaFold2, PeptideAtlas and the PRIDE database - enabling visualisation of source evidence, including scores and supporting mass spectra.
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Affiliation(s)
- Kerry A Ramsbottom
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, L69 7BE, United Kingdom
| | - Ananth Prakash
- European Molecular Biology Laboratory, EMBL-European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridge, CB10 1SD, United Kingdom
| | - Yasset Perez Riverol
- European Molecular Biology Laboratory, EMBL-European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridge, CB10 1SD, United Kingdom
| | - Oscar Martin Camacho
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, L69 7BE, United Kingdom
| | - Zhi Sun
- Institute for Systems Biology, Seattle, Washington 98109, United States
| | - Deepti J. Kundu
- European Molecular Biology Laboratory, EMBL-European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridge, CB10 1SD, United Kingdom
| | - Emily Bowler-Barnett
- European Molecular Biology Laboratory, EMBL-European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridge, CB10 1SD, United Kingdom
| | - Maria Martin
- European Molecular Biology Laboratory, EMBL-European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridge, CB10 1SD, United Kingdom
| | - Jun Fan
- European Molecular Biology Laboratory, EMBL-European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridge, CB10 1SD, United Kingdom
| | - Dmytro Chebotarov
- International Rice Research Institute, DAPO 7777, Manila 1301, Philippines
| | - Kenneth L McNally
- International Rice Research Institute, DAPO 7777, Manila 1301, Philippines
| | - Eric W Deutsch
- Institute for Systems Biology, Seattle, Washington 98109, United States
| | - Juan Antonio Vizcaíno
- European Molecular Biology Laboratory, EMBL-European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridge, CB10 1SD, United Kingdom
| | - Andrew R Jones
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, L69 7BE, United Kingdom
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Turlo AJ, Hammond DE, Ramsbottom KA, Soul J, Gillen A, McDonald K, Peffers MJ. Mesenchymal Stromal Cell Secretome Is Affected by Tissue Source and Donor Age. Stem Cells 2023; 41:1047-1059. [PMID: 37591507 PMCID: PMC10631804 DOI: 10.1093/stmcls/sxad060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Accepted: 07/21/2023] [Indexed: 08/19/2023]
Abstract
Variation in mesenchymal stromal cell (MSC) function depending on their origin is problematic, as it may confound clinical outcomes of MSC therapy. Current evidence suggests that the therapeutic benefits of MSCs are attributed to secretion of biologically active factors (secretome). However, the effect of donor characteristics on the MSC secretome remains largely unknown. Here, we examined the influence of donor age, sex, and tissue source, on the protein profile of the equine MSC secretome. We used dynamic metabolic labeling with stable isotopes combined with liquid chromatography-tandem mass spectrometry (LC-MS/MS) to identify secreted proteins in MSC conditioned media (CM). Seventy proteins were classified as classically secreted based on the rate of label incorporation into newly synthesized proteins released into the extracellular space. Next, we analyzed CM of bone marrow- (n = 14) and adipose-derived MSCs (n = 16) with label-free LC-MS/MS. Clustering analysis of 314 proteins detected across all samples identified tissue source as the main factor driving variability in MSC CM proteomes. Linear modelling applied to the subset of 70 secreted proteins identified tissue-related difference in the abundance of 23 proteins. There was an age-related decrease in the abundance of CTHRC1 and LOX, further validated with orthogonal techniques. Due to the lack of flow cytometry characterization of MSC surface markers, the analysis could not account for the potential effect of cell population heterogeneity. This study provides evidence that tissue source and donor age contribute to differences in the protein composition of MSC secretomes which may influence the effects of MSC therapy.
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Affiliation(s)
- Agnieszka J Turlo
- Department of Musculoskeletal and Ageing Science, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, UK
| | - Dean E Hammond
- epartment of Cellular and Molecular Physiology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
| | - Kerry A Ramsbottom
- Computational Biology Facility, Liverpool Shared Research Facilities, Faculty of Health and Life Sciences, University of Liverpool, Liverpool, UK
| | - Jamie Soul
- Computational Biology Facility, Liverpool Shared Research Facilities, Faculty of Health and Life Sciences, University of Liverpool, Liverpool, UK
| | - Alexandra Gillen
- Department of Veterinary Science, Philip Leverhulme Equine Hospital, University of Liverpool, UK
| | | | - Mandy J Peffers
- Department of Musculoskeletal and Ageing Science, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, UK
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Camacho OM, Ramsbottom KA, Collins A, Jones AR. Assessing Multiple Evidence Streams to Decide on Confidence for Identification of Post-Translational Modifications, within and Across Data Sets. J Proteome Res 2023. [PMID: 37099386 DOI: 10.1021/acs.jproteome.2c00823] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/27/2023]
Abstract
Phosphorylation is a post-translational modification of great interest to researchers due to its relevance in many biological processes. LC-MS/MS techniques have enabled high-throughput data acquisition, with studies claiming identification and localization of thousands of phosphosites. The identification and localization of phosphosites emerge from different analytical pipelines and scoring algorithms, with uncertainty embedded throughout the pipeline. For many pipelines and algorithms, arbitrary thresholding is used, but little is known about the actual global false localization rate in these studies. Recently, it has been suggested to use decoy amino acids to estimate global false localization rates of phosphosites, among the peptide-spectrum matches reported. Here, we describe a simple pipeline aiming to maximize the information extracted from these studies by objectively collapsing from peptide-spectrum match to the peptidoform-site level, as well as combining findings from multiple studies while maintaining track of false localization rates. We show that the approach is more effective than current processes that use a simpler mechanism for handling phosphosite identification redundancy within and across studies. In our case study using eight rice phosphoproteomics data sets, 6368 unique sites were confidently identified using our decoy approach compared to 4687 using traditional thresholding in which false localization rates are unknown.
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Affiliation(s)
- Oscar M Camacho
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, U.K
| | - Kerry A Ramsbottom
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, U.K
| | - Andrew Collins
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, U.K
| | - Andrew R Jones
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, U.K
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Ramsbottom KA, Prakash A, Riverol YP, Camacho OM, Martin MJ, Vizcaíno JA, Deutsch EW, Jones AR. Method for Independent Estimation of the False Localization Rate for Phosphoproteomics. J Proteome Res 2022; 21:1603-1615. [PMID: 35640880 PMCID: PMC9251759 DOI: 10.1021/acs.jproteome.1c00827] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
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Phosphoproteomic
methods are commonly employed to identify and
quantify phosphorylation sites on proteins. In recent years, various
tools have been developed, incorporating scores or statistics related
to whether a given phosphosite has been correctly identified or to
estimate the global false localization rate (FLR) within a given data
set for all sites reported. These scores have generally been calibrated
using synthetic datasets, and their statistical reliability on real
datasets is largely unknown, potentially leading to studies reporting
incorrectly localized phosphosites, due to inadequate statistical
control. In this work, we develop the concept of scoring modifications
on a decoy amino acid, that is, one that cannot be modified, to allow
for independent estimation of global FLR. We test a variety of amino
acids, on both synthetic and real data sets, demonstrating that the
selection can make a substantial difference to the estimated global
FLR. We conclude that while several different amino acids might be
appropriate, the most reliable FLR results were achieved using alanine
and leucine as decoys. We propose the use of a decoy amino acid to
control false reporting in the literature and in public databases
that re-distribute the data. Data are available via ProteomeXchange
with identifier PXD028840.
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Affiliation(s)
- Kerry A Ramsbottom
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 3BX, U.K
| | - Ananth Prakash
- European Molecular Biology Laboratory, EMBL-European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridge CB10 1SD, U.K
| | - Yasset Perez Riverol
- European Molecular Biology Laboratory, EMBL-European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridge CB10 1SD, U.K
| | - Oscar Martin Camacho
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 3BX, U.K
| | - Maria-Jesus Martin
- European Molecular Biology Laboratory, EMBL-European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridge CB10 1SD, U.K
| | - Juan Antonio Vizcaíno
- European Molecular Biology Laboratory, EMBL-European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridge CB10 1SD, U.K
| | - Eric W Deutsch
- Institute for Systems Biology, Seattle, Washington 98109, United States
| | - Andrew R Jones
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 3BX, U.K
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Ramsbottom KA, Carr DF, Rigden DJ, Jones AR. Informatics investigations into anti-thyroid drug induced agranulocytosis associated with multiple HLA-B alleles. PLoS One 2020; 15:e0220754. [PMID: 32027661 PMCID: PMC7004376 DOI: 10.1371/journal.pone.0220754] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2019] [Accepted: 01/22/2020] [Indexed: 11/18/2022] Open
Abstract
INTRODUCTION Adverse drug reactions have been linked with HLA alleles in different studies. These HLA proteins play an essential role in the adaptive immune response for the presentation of self and non-self peptides. Anti-thyroid drugs methimazole and propylthiouracil have been associated with drug induced agranulocytosis (severe lower white blood cell count) in patients with B*27:05, B*38:02 and DRB1*08:03 alleles in different populations: Taiwanese, Vietnamese, Han Chinese and Caucasian. METHODS In this study, informatics methods were used to investigate if any sequence or structural similarities exist between the two associated HLA-B alleles, compared with a set of "control" alleles assumed not be associated, which could help explain the molecular basis of the adverse drug reaction. We demonstrated using MHC Motif Viewer and MHCcluster that the two alleles do not have a propensity to bind similar peptides, and thus at a gross level the structure of the antigen presentation region of the two alleles are not similar. We also performed multiple sequence alignment to identify polymorphisms shared by the risk but not by the control alleles and molecular docking to compare the predicted binding poses of the drug-allele combinations. RESULTS Two residues, Cys67 and Thr80, were identified from the multiple sequence alignments to be unique to these risk alleles alone. The molecular docking showed the poses of the risk alleles to favour the F-pocket of the peptide binding groove, close to the Thr80 residue, with the control alleles generally favouring a different pocket. The data are thus suggestive that Thr80 may be a critical residue in HLA-mediated anti-thyroid drug induced agranulocytosis, and thus can guide future research and risk assessment.
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Affiliation(s)
- Kerry A. Ramsbottom
- Institute of Integrative Biology, University of Liverpool, Liverpool, United Kingdom
| | - Daniel F. Carr
- Institute of Translational Medicine, University of Liverpool, Liverpool, United Kingdom
| | - Daniel J. Rigden
- Institute of Integrative Biology, University of Liverpool, Liverpool, United Kingdom
| | - Andrew R. Jones
- Institute of Integrative Biology, University of Liverpool, Liverpool, United Kingdom
- * E-mail:
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Ramsbottom KA, Carr DF, Jones AR, Rigden DJ. Critical assessment of approaches for molecular docking to elucidate associations of HLA alleles with adverse drug reactions. Mol Immunol 2018; 101:488-499. [PMID: 30125869 PMCID: PMC6148408 DOI: 10.1016/j.molimm.2018.08.003] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2018] [Revised: 07/27/2018] [Accepted: 08/03/2018] [Indexed: 01/11/2023]
Abstract
All software assessed could dock Abacavir back into the risk allele structure but not always predict the exact binding mode. Most docking software assessed can distinguish between risk and control alleles. Docking performance can be degraded by using a homology model. Receptor flexibility can negatively affect the docking performance for complex HLA examples. Using AutoDockFR cannot compensate for the added difficulty of docking to the unbound target.
Adverse drug reactions have been linked with genetic polymorphisms in HLA genes in numerous different studies. HLA proteins have an essential role in the presentation of self and non-self peptides, as part of the adaptive immune response. Amongst the associated drugs-allele combinations, anti-HIV drug Abacavir has been shown to be associated with the HLA-B*57:01 allele, and anti-epilepsy drug Carbamazepine with B*15:02, in both cases likely following the altered peptide repertoire model of interaction. Under this model, the drug binds directly to the antigen presentation region, causing different self peptides to be presented, which trigger an unwanted immune response. There is growing interest in searching for evidence supporting this model for other ADRs using bioinformatics techniques. In this study, in silico docking was used to assess the utility and reliability of well-known docking programs when addressing these challenging HLA-drug situations. The overall aim was to address the uncertainty of docking programs giving different results by completing a detailed comparative study of docking software, grounded in the MHC-ligand experimental structural data – for Abacavir and to a lesser extent Carbamazepine - in order to assess their performance. Four docking programs: SwissDock, ROSIE, AutoDock Vina and AutoDockFR, were used to investigate if each software could accurately dock the Abacavir back into the crystal structure for the protein arising from the known risk allele, and if they were able to distinguish between the HLA-associated and non-HLA-associated (control) alleles. The impact of using homology models on the docking performance and how using different parameters, such as including receptor flexibility, affected the docking performance were also investigated to simulate the approach where a crystal structure for a given HLA allele may be unavailable. The programs that were best able to predict the binding position of Abacavir were then used to recreate the docking seen for Carbamazepine with B*15:02 and controls alleles. It was found that the programs investigated were sometimes able to correctly predict the binding mode of Abacavir with B*57:01 but not always. Each of the software packages that were assessed could predict the binding of Abacavir and Carbamazepine within the correct sub-pocket and, with the exception of ROSIE, was able to correctly distinguish between risk and control alleles. We found that docking to homology models could produce poorer quality predictions, especially when sequence differences impact the architecture of predicted binding pockets. Caution must therefore be used as inaccurate structures may lead to erroneous docking predictions. Incorporating receptor flexibility was found to negatively affect the docking performance for the examples investigated. Taken together, our findings help characterise the potential but also the limitations of computational prediction of drug-HLA interactions. These docking techniques should therefore always be used with care and alongside other methods of investigation, in order to be able to draw strong conclusions from the given results.
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Affiliation(s)
- Kerry A Ramsbottom
- Institute of Integrative Biology, University of Liverpool, Liverpool, UK
| | - Daniel F Carr
- MRC Centre for Drug Safety Science, Institute of Translational Medicine, University of Liverpool, Liverpool, UK
| | - Andrew R Jones
- Institute of Integrative Biology, University of Liverpool, Liverpool, UK
| | - Daniel J Rigden
- Institute of Integrative Biology, University of Liverpool, Liverpool, UK.
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