1
|
Stobernack T, Dommershausen N, Alcolea-Rodríguez V, Ledwith R, Bañares MA, Haase A, Pink M, Dumit VI. Advancing Nanomaterial Toxicology Screening Through Efficient and Cost-Effective Quantitative Proteomics. SMALL METHODS 2024:e2400420. [PMID: 38813751 DOI: 10.1002/smtd.202400420] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/19/2024] [Revised: 05/17/2024] [Indexed: 05/31/2024]
Abstract
Proteomic investigations yield high-dimensional datasets, yet their application to large-scale toxicological assessments is hindered by reproducibility challenges due to fluctuating measurement conditions. To address these limitations, this study introduces an advanced tandem mass tag (TMT) labeling protocol. Although labeling approaches shorten data acquisition time by multiplexing samples compared to traditional label-free quantification (LFQ) methods in general, the associated costs may surge significantly with large sample sets, for example, in toxicological screenings. However, the introduced advanced protocol offers an efficient, cost-effective alternative, reducing TMT reagent usage (by a factor of ten) and requiring minimal biological material (1 µg), while demonstrating increased reproducibility compared to LFQ. To demonstrate its effectiveness, the advanced protocol is employed to assess the toxicity of nine benchmark nanomaterials (NMs) on A549 lung epithelial cells. While LFQ measurements identify 3300 proteins, they proved inadequate to reveal NM toxicity. Conversely, despite detecting 2600 proteins, the TMT protocol demonstrates superior sensitivity by uncovering alterations induced by NM treatment. In contrast to previous studies, the introduced advanced protocol allows simultaneous and straightforward assessment of multiple test substances, enabling prioritization, ranking, and grouping for hazard evaluation. Additionally, it fosters the development of New Approach Methodologies (NAMs), contributing to innovative methodologies in toxicological research.
Collapse
Affiliation(s)
- Tobias Stobernack
- German Federal Institute for Risk Assessment (BfR), Department of Chemical and Product Safety, Max-Dohrn-Straße 8-10, 10589, Berlin, Germany
| | - Nils Dommershausen
- German Federal Institute for Risk Assessment (BfR), Department of Chemical and Product Safety, Max-Dohrn-Straße 8-10, 10589, Berlin, Germany
| | - Víctor Alcolea-Rodríguez
- German Federal Institute for Risk Assessment (BfR), Department of Chemical and Product Safety, Max-Dohrn-Straße 8-10, 10589, Berlin, Germany
- Spanish National Research Council - Institute of Catalysis and Petrochemistry (ICP-CSIC), Spectroscopy and Industrial Catalysis group, Marie Curie, 2, Madrid, 28049, Spain
| | - Rico Ledwith
- German Federal Institute for Risk Assessment (BfR), Department of Chemical and Product Safety, Max-Dohrn-Straße 8-10, 10589, Berlin, Germany
| | - Miguel A Bañares
- Spanish National Research Council - Institute of Catalysis and Petrochemistry (ICP-CSIC), Spectroscopy and Industrial Catalysis group, Marie Curie, 2, Madrid, 28049, Spain
| | - Andrea Haase
- German Federal Institute for Risk Assessment (BfR), Department of Chemical and Product Safety, Max-Dohrn-Straße 8-10, 10589, Berlin, Germany
| | - Mario Pink
- German Federal Institute for Risk Assessment (BfR), Department of Chemical and Product Safety, Max-Dohrn-Straße 8-10, 10589, Berlin, Germany
| | - Verónica I Dumit
- German Federal Institute for Risk Assessment (BfR), Department of Chemical and Product Safety, Max-Dohrn-Straße 8-10, 10589, Berlin, Germany
| |
Collapse
|
2
|
Haroon H, Ho AMC, Gupta VK, Dasari S, Sellgren CM, Cervenka S, Engberg G, Eren F, Erhardt S, Sung J, Choi DS. Cerebrospinal fluid proteomic signatures are associated with symptom severity of first-episode psychosis. J Psychiatr Res 2024; 171:306-315. [PMID: 38340697 PMCID: PMC10995989 DOI: 10.1016/j.jpsychires.2024.02.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 01/04/2024] [Accepted: 02/01/2024] [Indexed: 02/12/2024]
Abstract
Apart from their diagnostic, monitoring, or prognostic utility in clinical settings, molecular biomarkers may be instrumental in understanding the pathophysiology of psychiatric disorders, including schizophrenia. Using untargeted metabolomics, we recently identified eight cerebrospinal fluid (CSF) metabolites unique to first-episode psychosis (FEP) subjects compared to healthy controls (HC). In this study, we sought to investigate the CSF proteomic signatures associated with FEP. We employed 16-plex tandem mass tag (TMT) mass spectrometry (MS) to examine the relative protein abundance in CSF samples of 15 individuals diagnosed with FEP and 15 age-and-sex-matched healthy controls (HC). Multiple linear regression model (MLRM) identified 16 differentially abundant CSF proteins between FEP and HC at p < 0.01. Among them, the two most significant CSF proteins were collagen alpha-2 (IV) chain (COL4A2: standard mean difference [SMD] = -1.12, p = 1.64 × 10-4) and neuron-derived neurotrophic factor (NDNF: SMD = -1.03, p = 4.52 × 10-4) both of which were down-regulated in FEP subjects compared to HC. We also identified several potential CSF proteins associated with the pathophysiology and the symptom profile and severity in FEP subjects, including COL4A2, NDNF, hornerin (HRNR), contactin-6 (CNTN6), voltage-dependent calcium channel subunit alpha-2/delta-3 (CACNA2D3), tropomyosin alpha-3 chain (TPM3 and TPM4). Moreover, several protein signatures were associated with cognitive performance. Although the results need replication, our exploratory study suggests that CSF protein signatures can be used to increase the understanding of the pathophysiology of psychosis.
Collapse
Affiliation(s)
- Humza Haroon
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic College of Medicine and Science, Rochester, MN, USA
| | - Ada Man-Choi Ho
- Department of Psychiatry and Psychology, Mayo Clinic College of Medicine and Science, Rochester, MN, USA
| | - Vinod K Gupta
- Division of Surgery Research, Department of Surgery, Rochester, MN, USA; Microbiome Program, Center for Individualized Medicine, Rochester, MN, USA
| | - Surendra Dasari
- Division of Biomedical Statistics and Informatics, Mayo Clinic College of Medicine and Science, Rochester, MN, USA
| | - Carl M Sellgren
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden; Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
| | - Simon Cervenka
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden; Department of Medical Sciences, Psychiatry, Uppsala University, Uppsala, Sweden
| | - Göran Engberg
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Feride Eren
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Sophie Erhardt
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Jaeyun Sung
- Division of Surgery Research, Department of Surgery, Rochester, MN, USA; Microbiome Program, Center for Individualized Medicine, Rochester, MN, USA; Division of Rheumatology, Department of Internal Medicine, Rochester, MN, USA
| | - Doo-Sup Choi
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic College of Medicine and Science, Rochester, MN, USA; Department of Psychiatry and Psychology, Mayo Clinic College of Medicine and Science, Rochester, MN, USA; Neuroscience Program, Mayo Clinic College of Medicine and Science, Rochester, MN, USA.
| |
Collapse
|
3
|
Koutsilieri S, Mickols E, Végvári Á, Lauschke VM. Proteomic workflows for deep phenotypic profiling of 3D organotypic liver models. Biotechnol J 2024; 19:e2300684. [PMID: 38509783 DOI: 10.1002/biot.202300684] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2023] [Revised: 02/07/2024] [Accepted: 02/15/2024] [Indexed: 03/22/2024]
Abstract
Organotypic human tissue models constitute promising systems to facilitate drug discovery and development. They allow to maintain native cellular phenotypes and functions, which enables long-term pharmacokinetic and toxicity studies, as well as phenotypic screening. To trace relevant phenotypic changes back to specific targets or signaling pathways, comprehensive proteomic profiling is the gold-standard. A multitude of proteomic workflows have been applied on 3D tissue models to quantify their molecular phenotypes; however, their impact on analytical results and biological conclusions in this context has not been evaluated. The performance of twelve mass spectrometry-based global proteomic workflows that differed in the amount of cellular input, lysis protocols and quantification methods was compared for the analysis of primary human liver spheroids. Results differed majorly between protocols in the total number and subcellular compartment bias of identified proteins, which is particularly relevant for the reliable quantification of transporters and drug metabolizing enzymes. Using a model of metabolic dysfunction-associated steatotic liver disease, we furthermore show that critical disease pathways are robustly identified using a standardized high throughput-compatible workflow based on thermal lysis, even using only individual spheroids (1500 cells) as input. The results increase the applicability of proteomic profiling to phenotypic screens in organotypic microtissues and provide a scalable platform for deep phenotyping from limited biological material.
Collapse
Affiliation(s)
- Stefania Koutsilieri
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Evgeniya Mickols
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
- Department of Pharmacy, Uppsala University, Uppsala, Sweden
| | - Ákos Végvári
- Division of Chemistry I, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Volker M Lauschke
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
- Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany
- University of Tübingen, Tübingen, Germany
| |
Collapse
|
4
|
He Q, Sze SK, Ng KS, Koh CG. Paxillin interactome identified by SILAC and label-free approaches coupled to TurboID sheds light on the compositions of focal adhesions in mouse embryonic stem cells. Biochem Biophys Res Commun 2023; 680:73-85. [PMID: 37725837 DOI: 10.1016/j.bbrc.2023.09.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2023] [Revised: 08/25/2023] [Accepted: 09/08/2023] [Indexed: 09/21/2023]
Abstract
Self-renewal and differentiation of mouse embryonic stem cells (mESCs) are greatly affected by the extracellular matrix (ECM) environment; the composition and stiffness of which are sensed by the cells via integrin-associated focal adhesions (FAs) which link the cells to the ECM. Although FAs have been studied extensively in differentiated cells, their composition and function in mESCs are not as well elucidated. To gain more detailed knowledge of the molecular compositions of FAs in mESCs, we adopted the proximity-dependent biotinylation (BioID) proteomics approach. Paxillin, a known FA protein (FAP), is fused to the promiscuous biotin ligase TurboID as bait. We employed both SILAC- and label-free (LF)-based quantitative proteomics to strengthen as well as complement individual approach. The mass spectrometry data derived from SILAC and LF identified 38 and 443 proteins, respectively, with 35 overlapping candidates. Fifteen of these shared proteins are known FAPs based on literature-curated adhesome and 7 others are among the reported "meta-adhesome", suggesting the components of FAs are largely conserved between mESCs and differentiated cells. Furthermore, the LF data set contained an additional 18 literature-curated FAPs. Notably, the overlapped proteomics data failed to detect LIM-domain proteins such as zyxin family proteins, which suggests that FAs in mESCs are less mature than differentiated cells. Using the LF approach, we are able to identify PDLIM7, a LIM-domain protein, as a FAP in mESCs. This study illustrates the effectiveness of TurboID in mESCs. Importantly, we found that application of both SILAC and LF methods in combination allowed us to analyze the TurboID proteomics data in an unbiased, stringent and yet comprehensive manner.
Collapse
Affiliation(s)
- Qianqian He
- School of Biological Sciences, Nanyang Technological University, Singapore, 637551, Singapore
| | - Siu Kwan Sze
- School of Biological Sciences, Nanyang Technological University, Singapore, 637551, Singapore
| | - Kai Soon Ng
- School of Biological Sciences, Nanyang Technological University, Singapore, 637551, Singapore
| | - Cheng-Gee Koh
- School of Biological Sciences, Nanyang Technological University, Singapore, 637551, Singapore.
| |
Collapse
|
5
|
Höper T, Karkossa I, Dumit VI, von Bergen M, Schubert K, Haase A. A comparative proteomics analysis of four contact allergens in THP-1 cells shows distinct alterations in key metabolic pathways. Toxicol Appl Pharmacol 2023; 475:116650. [PMID: 37541627 DOI: 10.1016/j.taap.2023.116650] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 07/21/2023] [Accepted: 07/31/2023] [Indexed: 08/06/2023]
Abstract
Allergic contact dermatitis (ACD) is the predominant form of immunotoxicity in humans. The sensitizing potential of chemicals can be assessed in vitro. However, a better mechanistic understanding could improve the current OECD-validated test battery. The aim of this study was to get insights into toxicity mechanisms of four contact allergens, p-benzoquinone (BQ), 2,4-dinitrochlorobenzene (DNCB), p-nitrobenzyl bromide (NBB) and NiSO4, by analyzing differential proteome alterations in THP-1 cells using two common proteomics workflows, stable isotope labeling by amino acids in cell culture (SILAC) and label-free quantification (LFQ). Here, SILAC was found to deliver more robust results. Overall, the four allergens induced similar responses in THP-1 cells, which underwent profound metabolic reprogramming, including a striking upregulation of the TCA cycle accompanied by pronounced induction of the Nrf2 oxidative stress response pathway. The magnitude of induction varied between the allergens with DNCB and NBB being most potent. A considerable overlap between transcriptome-based signatures of the GARD assay and the proteins identified in our study was found. When comparing the results of this study to a previous proteomics study in human primary monocyte-derived dendritic cells, we found a rather low share in regulated proteins. However, on pathway level, the overlap was high, indicating that affected pathways rather than single proteins are more eligible to investigate proteomic changes induced by contact allergens. Overall, this study confirms the potential of proteomics to obtain a profound mechanistic understanding, which may help improving existing in vitro assays for skin sensitization.
Collapse
Affiliation(s)
- Tessa Höper
- Department of Chemical and Product Safety, German Federal Institute for Risk Assessment (BfR), Berlin, Germany; Department of Clinical Pharmacy and Biochemistry, Institute of Pharmacy, Freie Universität Berlin, Berlin, Germany
| | - Isabel Karkossa
- Department of Molecular Systems Biology, UFZ, Helmholtz-Centre for Environmental Research, Leipzig, Germany
| | - Verónica I Dumit
- Department of Chemical and Product Safety, German Federal Institute for Risk Assessment (BfR), Berlin, Germany
| | - Martin von Bergen
- Department of Molecular Systems Biology, UFZ, Helmholtz-Centre for Environmental Research, Leipzig, Germany; Institute of Biochemistry, Leipzig University, Leipzig, Germany; German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany
| | - Kristin Schubert
- Department of Molecular Systems Biology, UFZ, Helmholtz-Centre for Environmental Research, Leipzig, Germany
| | - Andrea Haase
- Department of Chemical and Product Safety, German Federal Institute for Risk Assessment (BfR), Berlin, Germany.
| |
Collapse
|
6
|
Porta EO, Steel PG. Activity-based protein profiling: A graphical review. CURRENT RESEARCH IN PHARMACOLOGY AND DRUG DISCOVERY 2023; 5:100164. [PMID: 37692766 PMCID: PMC10484978 DOI: 10.1016/j.crphar.2023.100164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 08/06/2023] [Accepted: 08/23/2023] [Indexed: 09/12/2023] Open
Abstract
Activity-based protein profiling (ABPP) is a chemoproteomic technology that employs small chemical probes to directly interrogate protein function within complex proteomes. Since its initial application almost 25 years ago, ABPP has proven to be a powerful and versatile tool for addressing numerous challenges in drug discovery, including the development of highly selective small-molecule inhibitors, the discovery of new therapeutic targets, and the illumination of target proteins in tissues and organisms. This graphical review provides an overview of the rapid evolution of ABPP strategies, highlighting the versatility of the approach with selected examples of its successful application.
Collapse
Affiliation(s)
| | - Patrick G. Steel
- Department of Chemistry, Durham University, Durham, DH1 3LE, United Kingdom
| |
Collapse
|
7
|
Juanes-Velasco P, Arias-Hidalgo C, Landeira-Viñuela A, Nuño-Soriano A, Fuentes-Vacas M, Góngora R, Hernández ÁP, Fuentes M. Functional proteomics based on protein microarray technology for biomedical research. ADVANCES IN PROTEIN CHEMISTRY AND STRUCTURAL BIOLOGY 2023; 138:49-65. [PMID: 38220432 DOI: 10.1016/bs.apcsb.2023.04.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/16/2024]
Abstract
This chapter traces a route through Proteomics from its origins to the present day. The different proteomics applications are discussed with a focus on microarray technology. Analytical microarrays, functional microarrays and reverse phase microarrays and their different applications are discussed. Several studies are mentioned where the great versatility of this approach is shown. Finally, the advantages and future challenges of microarray technology are outlined.
Collapse
Affiliation(s)
- Pablo Juanes-Velasco
- Department of Medicine and General Cytometry Service-Nucleus, CIBERONC, Cancer Research Centre (IBMCC/CSIC/USAL/IBSAL), Salamanca, Spain
| | - Carlota Arias-Hidalgo
- Department of Medicine and General Cytometry Service-Nucleus, CIBERONC, Cancer Research Centre (IBMCC/CSIC/USAL/IBSAL), Salamanca, Spain
| | - Alicia Landeira-Viñuela
- Department of Medicine and General Cytometry Service-Nucleus, CIBERONC, Cancer Research Centre (IBMCC/CSIC/USAL/IBSAL), Salamanca, Spain
| | - Ana Nuño-Soriano
- Department of Medicine and General Cytometry Service-Nucleus, CIBERONC, Cancer Research Centre (IBMCC/CSIC/USAL/IBSAL), Salamanca, Spain
| | - Marina Fuentes-Vacas
- Department of Medicine and General Cytometry Service-Nucleus, CIBERONC, Cancer Research Centre (IBMCC/CSIC/USAL/IBSAL), Salamanca, Spain
| | - Rafa Góngora
- Department of Medicine and General Cytometry Service-Nucleus, CIBERONC, Cancer Research Centre (IBMCC/CSIC/USAL/IBSAL), Salamanca, Spain
| | - Ángela-Patricia Hernández
- Department of Medicine and General Cytometry Service-Nucleus, CIBERONC, Cancer Research Centre (IBMCC/CSIC/USAL/IBSAL), Salamanca, Spain; Department of Pharmaceutical Sciences: Organic Chemistry, Faculty of Pharmacy, University of Salamanca, CIETUS, IBSAL, Salamanca, Spain
| | - Manuel Fuentes
- Department of Medicine and General Cytometry Service-Nucleus, CIBERONC, Cancer Research Centre (IBMCC/CSIC/USAL/IBSAL), Salamanca, Spain; Proteomics Unit, Cancer Research Centre (IBMCC/CSIC/USAL/IBSAL), Salamanca, Spain.
| |
Collapse
|
8
|
Liao Y, Chin Chan S, Welsh EA, Fang B, Sun L, Schönbrunn E, Koomen JM, Duckett DR, Haura EB, Monastyrskyi A, Rix U. Chemical Proteomics with Novel Fully Functionalized Fragments and Stringent Target Prioritization Identifies the Glutathione-Dependent Isomerase GSTZ1 as a Lung Cancer Target. ACS Chem Biol 2023; 18:251-264. [PMID: 36630201 DOI: 10.1021/acschembio.2c00587] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
Photoreactive fragment-like probes have been applied to discover target proteins that constitute novel cellular vulnerabilities and to identify viable chemical hits for drug discovery. Through forming covalent bonds, functionalized probes can achieve stronger target engagement and require less effort for on-target mechanism validation. However, the design of probe libraries, which directly affects the biological target space that is interrogated, and effective target prioritization remain critical challenges of such a chemical proteomic platform. In this study, we designed and synthesized a diverse panel of 20 fragment-based probes containing natural product-based privileged structural motifs for small-molecule lead discovery. These probes were fully functionalized with orthogonal diazirine and alkyne moieties and used for protein crosslinking in live lung cancer cells, target enrichment via "click chemistry," and subsequent target identification through label-free quantitative liquid chromatography-tandem mass spectrometry analysis. Pair-wise comparison with a blunted negative control probe and stringent prioritization via individual cross-comparisons against the entire panel identified glutathione S-transferase zeta 1 (GSTZ1) as a specific and unique target candidate. DepMap database query, RNA interference-based gene silencing, and proteome-wide tyrosine reactivity profiling suggested that GSTZ1 cooperated with different oncogenic alterations by supporting survival signaling in refractory non-small cell lung cancer cells. This finding may form the basis for developing novel GSTZ1 inhibitors to improve the therapeutic efficacy of oncogene-directed targeted drugs. In summary, we designed a novel fragment-based probe panel and developed a target prioritization scheme with improved stringency, which allows for the identification of unique target candidates, such as GSTZ1 in refractory lung cancer.
Collapse
Affiliation(s)
- Yi Liao
- Department of Drug Discovery, H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida 33612, United States
| | - Sean Chin Chan
- Department of Drug Discovery, H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida 33612, United States.,Cancer Chemical Biology Ph.D. Program, University of South Florida, Tampa, Florida 33620, United States
| | - Eric A Welsh
- Biostatistics and Bioinformatics Shared Resource, H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida 33612, United States
| | - Bin Fang
- Proteomics and Metabolomics Core, H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida 33612, United States
| | - Luxin Sun
- Chemical Biology Core, H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida 33612, United States
| | - Ernst Schönbrunn
- Department of Drug Discovery, H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida 33612, United States.,Chemical Biology Core, H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida 33612, United States
| | - John M Koomen
- Department of Molecular Oncology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida 33612, United States.,Department of Oncologic Sciences, University of South Florida, Tampa, Florida 33620, United States
| | - Derek R Duckett
- Department of Drug Discovery, H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida 33612, United States.,Department of Oncologic Sciences, University of South Florida, Tampa, Florida 33620, United States
| | - Eric B Haura
- Department of Thoracic Oncology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida 33612, United States
| | - Andrii Monastyrskyi
- Department of Drug Discovery, H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida 33612, United States.,Department of Oncologic Sciences, University of South Florida, Tampa, Florida 33620, United States.,Department of Chemistry, University of South Florida, Tampa, Florida 33620, United States
| | - Uwe Rix
- Department of Drug Discovery, H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida 33612, United States.,Department of Oncologic Sciences, University of South Florida, Tampa, Florida 33620, United States
| |
Collapse
|
9
|
Long MJC, Liu J, Aye Y. Finding a vocation for validation: taking proteomics beyond association and location. RSC Chem Biol 2023; 4:110-120. [PMID: 36794020 PMCID: PMC9906375 DOI: 10.1039/d2cb00214k] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Accepted: 12/01/2022] [Indexed: 12/03/2022] Open
Abstract
First established in the seventies, proteomics, chemoproteomics, and most recently, spatial/proximity-proteomics technologies have empowered researchers with new capabilities to illuminate cellular communication networks that govern sophisticated decision-making processes. With an ever-growing inventory of these advanced proteomics tools, the onus is upon the researchers to understand their individual advantages and limitations, such that we can ensure rigorous implementation and conclusions derived from critical data interpretations backed up by orthogonal series of functional validations. This perspective-based on the authors' experience in applying varied proteomics workflows in complex living models-underlines key book-keeping considerations, comparing and contrasting most-commonly-deployed modern proteomics profiling technologies. We hope this article stimulates thoughts among expert users and equips new-comers with practical knowhow of what has become an indispensable tool in chemical biology, drug discovery, and broader life-science investigations.
Collapse
Affiliation(s)
- Marcus J. C. Long
- University of Lausanne (UNIL)Switzerland,NCCR Chemical Biology, University of Geneva (UNIGE)Switzerland
| | - Jinmin Liu
- Swiss Federal Institute of Technology Lausanne (EPFL) Switzerland .,NCCR Chemical Biology, University of Geneva (UNIGE) Switzerland
| | - Yimon Aye
- Swiss Federal Institute of Technology Lausanne (EPFL) Switzerland .,NCCR Chemical Biology, University of Geneva (UNIGE) Switzerland
| |
Collapse
|
10
|
Samant RS, Batista S, Larance M, Ozer B, Milton CI, Bludau I, Wu E, Biggins L, Andrews S, Hervieu A, Johnston HE, Al-Lazikhani B, Lamond AI, Clarke PA, Workman P. Native Size-Exclusion Chromatography-Based Mass Spectrometry Reveals New Components of the Early Heat Shock Protein 90 Inhibition Response Among Limited Global Changes. Mol Cell Proteomics 2023; 22:100485. [PMID: 36549590 PMCID: PMC9898794 DOI: 10.1016/j.mcpro.2022.100485] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Revised: 11/16/2022] [Accepted: 12/07/2022] [Indexed: 12/24/2022] Open
Abstract
The molecular chaperone heat shock protein 90 (HSP90) works in concert with co-chaperones to stabilize its client proteins, which include multiple drivers of oncogenesis and malignant progression. Pharmacologic inhibitors of HSP90 have been observed to exert a wide range of effects on the proteome, including depletion of client proteins, induction of heat shock proteins, dissociation of co-chaperones from HSP90, disruption of client protein signaling networks, and recruitment of the protein ubiquitylation and degradation machinery-suggesting widespread remodeling of cellular protein complexes. However, proteomics studies to date have focused on inhibitor-induced changes in total protein levels, often overlooking protein complex alterations. Here, we use size-exclusion chromatography in combination with mass spectrometry (SEC-MS) to characterize the early changes in native protein complexes following treatment with the HSP90 inhibitor tanespimycin (17-AAG) for 8 h in the HT29 colon adenocarcinoma cell line. After confirming the signature cellular response to HSP90 inhibition (e.g., induction of heat shock proteins, decreased total levels of client proteins), we were surprised to find only modest perturbations to the global distribution of protein elution profiles in inhibitor-treated HT29 cells at this relatively early time-point. Similarly, co-chaperones that co-eluted with HSP90 displayed no clear difference between control and treated conditions. However, two distinct analysis strategies identified multiple inhibitor-induced changes, including known and unknown components of the HSP90-dependent proteome. We validate two of these-the actin-binding protein Anillin and the mitochondrial isocitrate dehydrogenase 3 complex-as novel HSP90 inhibitor-modulated proteins. We present this dataset as a resource for the HSP90, proteostasis, and cancer communities (https://www.bioinformatics.babraham.ac.uk/shiny/HSP90/SEC-MS/), laying the groundwork for future mechanistic and therapeutic studies related to HSP90 pharmacology. Data are available via ProteomeXchange with identifier PXD033459.
Collapse
Affiliation(s)
- Rahul S Samant
- Centre for Cancer Drug Discovery, The Institute of Cancer Research, London, United Kingdom; Signalling Programme, The Babraham Institute, Cambridge, United Kingdom.
| | - Silvia Batista
- Centre for Cancer Drug Discovery, The Institute of Cancer Research, London, United Kingdom
| | - Mark Larance
- Centre for Gene Regulation & Expression, University of Dundee, Dundee, United Kingdom
| | - Bugra Ozer
- Centre for Cancer Drug Discovery, The Institute of Cancer Research, London, United Kingdom
| | - Christopher I Milton
- Centre for Cancer Drug Discovery, The Institute of Cancer Research, London, United Kingdom
| | - Isabell Bludau
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany
| | - Estelle Wu
- Signalling Programme, The Babraham Institute, Cambridge, United Kingdom
| | - Laura Biggins
- Bioinformatics Group, The Babraham Institute, Cambridge, United Kingdom
| | - Simon Andrews
- Bioinformatics Group, The Babraham Institute, Cambridge, United Kingdom
| | - Alexia Hervieu
- Centre for Cancer Drug Discovery, The Institute of Cancer Research, London, United Kingdom
| | - Harvey E Johnston
- Signalling Programme, The Babraham Institute, Cambridge, United Kingdom
| | - Bissan Al-Lazikhani
- Centre for Cancer Drug Discovery, The Institute of Cancer Research, London, United Kingdom; Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Angus I Lamond
- Centre for Gene Regulation & Expression, University of Dundee, Dundee, United Kingdom
| | - Paul A Clarke
- Centre for Cancer Drug Discovery, The Institute of Cancer Research, London, United Kingdom
| | - Paul Workman
- Centre for Cancer Drug Discovery, The Institute of Cancer Research, London, United Kingdom.
| |
Collapse
|
11
|
Punetha A, Kotiya D. Advancements in Oncoproteomics Technologies: Treading toward Translation into Clinical Practice. Proteomes 2023; 11:2. [PMID: 36648960 PMCID: PMC9844371 DOI: 10.3390/proteomes11010002] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2022] [Revised: 01/03/2023] [Accepted: 01/04/2023] [Indexed: 01/12/2023] Open
Abstract
Proteomics continues to forge significant strides in the discovery of essential biological processes, uncovering valuable information on the identity, global protein abundance, protein modifications, proteoform levels, and signal transduction pathways. Cancer is a complicated and heterogeneous disease, and the onset and progression involve multiple dysregulated proteoforms and their downstream signaling pathways. These are modulated by various factors such as molecular, genetic, tissue, cellular, ethnic/racial, socioeconomic status, environmental, and demographic differences that vary with time. The knowledge of cancer has improved the treatment and clinical management; however, the survival rates have not increased significantly, and cancer remains a major cause of mortality. Oncoproteomics studies help to develop and validate proteomics technologies for routine application in clinical laboratories for (1) diagnostic and prognostic categorization of cancer, (2) real-time monitoring of treatment, (3) assessing drug efficacy and toxicity, (4) therapeutic modulations based on the changes with prognosis and drug resistance, and (5) personalized medication. Investigation of tumor-specific proteomic profiles in conjunction with healthy controls provides crucial information in mechanistic studies on tumorigenesis, metastasis, and drug resistance. This review provides an overview of proteomics technologies that assist the discovery of novel drug targets, biomarkers for early detection, surveillance, prognosis, drug monitoring, and tailoring therapy to the cancer patient. The information gained from such technologies has drastically improved cancer research. We further provide exemplars from recent oncoproteomics applications in the discovery of biomarkers in various cancers, drug discovery, and clinical treatment. Overall, the future of oncoproteomics holds enormous potential for translating technologies from the bench to the bedside.
Collapse
Affiliation(s)
- Ankita Punetha
- Department of Microbiology, Biochemistry and Molecular Genetics, Rutgers New Jersey Medical School, Rutgers University, 225 Warren St., Newark, NJ 07103, USA
| | - Deepak Kotiya
- Department of Pharmacology and Nutritional Sciences, University of Kentucky, 900 South Limestone St., Lexington, KY 40536, USA
| |
Collapse
|
12
|
Zhou Y, Liu Y, Gupta S, Paramo MI, Hou Y, Mao C, Luo Y, Judd J, Wierbowski S, Bertolotti M, Nerkar M, Jehi L, Drayman N, Nicolaescu V, Gula H, Tay S, Randall G, Wang P, Lis JT, Feschotte C, Erzurum SC, Cheng F, Yu H. A comprehensive SARS-CoV-2-human protein-protein interactome reveals COVID-19 pathobiology and potential host therapeutic targets. Nat Biotechnol 2023; 41:128-139. [PMID: 36217030 PMCID: PMC9851973 DOI: 10.1038/s41587-022-01474-0] [Citation(s) in RCA: 57] [Impact Index Per Article: 57.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2022] [Accepted: 08/15/2022] [Indexed: 01/25/2023]
Abstract
Studying viral-host protein-protein interactions can facilitate the discovery of therapies for viral infection. We use high-throughput yeast two-hybrid experiments and mass spectrometry to generate a comprehensive SARS-CoV-2-human protein-protein interactome network consisting of 739 high-confidence binary and co-complex interactions, validating 218 known SARS-CoV-2 host factors and revealing 361 novel ones. Our results show the highest overlap of interaction partners between published datasets and of genes differentially expressed in samples from COVID-19 patients. We identify an interaction between the viral protein ORF3a and the human transcription factor ZNF579, illustrating a direct viral impact on host transcription. We perform network-based screens of >2,900 FDA-approved or investigational drugs and identify 23 with significant network proximity to SARS-CoV-2 host factors. One of these drugs, carvedilol, shows clinical benefits for COVID-19 patients in an electronic health records analysis and antiviral properties in a human lung cell line infected with SARS-CoV-2. Our study demonstrates the value of network systems biology to understand human-virus interactions and provides hits for further research on COVID-19 therapeutics.
Collapse
Affiliation(s)
- Yadi Zhou
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Yuan Liu
- Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, NY, USA
- Center for Advanced Proteomics, Cornell University, Ithaca, NY, USA
| | - Shagun Gupta
- Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, NY, USA
- Center for Advanced Proteomics, Cornell University, Ithaca, NY, USA
- Department of Computational Biology, Cornell University, Ithaca, NY, USA
| | - Mauricio I Paramo
- Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, NY, USA
- Center for Advanced Proteomics, Cornell University, Ithaca, NY, USA
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY, USA
| | - Yuan Hou
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Chengsheng Mao
- Division of Health and Biomedical Informatics, Department of Preventive Medicine, Northwestern University, Chicago, IL, USA
| | - Yuan Luo
- Division of Health and Biomedical Informatics, Department of Preventive Medicine, Northwestern University, Chicago, IL, USA
| | - Julius Judd
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY, USA
| | - Shayne Wierbowski
- Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, NY, USA
- Center for Advanced Proteomics, Cornell University, Ithaca, NY, USA
- Department of Computational Biology, Cornell University, Ithaca, NY, USA
| | - Marta Bertolotti
- Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, NY, USA
- Center for Advanced Proteomics, Cornell University, Ithaca, NY, USA
| | - Mriganka Nerkar
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY, USA
| | - Lara Jehi
- Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Nir Drayman
- Department of Molecular Biology and Biochemistry, University of California, Irvine, Irvine, CA, USA
| | - Vlad Nicolaescu
- Department of Microbiology, Ricketts Laboratory, University of Chicago, Chicago, IL, USA
| | - Haley Gula
- Department of Microbiology, Ricketts Laboratory, University of Chicago, Chicago, IL, USA
| | - Savaş Tay
- Pritzker School of Molecular Engineering, University of Chicago, Chicago, IL, USA
| | - Glenn Randall
- Department of Microbiology, Ricketts Laboratory, University of Chicago, Chicago, IL, USA
| | - Peihui Wang
- Key Laboratory for Experimental Teratology of Ministry of Education and Advanced Medical Research Institute, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - John T Lis
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY, USA
| | - Cédric Feschotte
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY, USA
| | | | - Feixiong Cheng
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA.
- Case Comprehensive Cancer Center, School of Medicine, Case Western Reserve University, Cleveland, OH, USA.
- Department of Molecular Medicine, Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, OH, USA.
| | - Haiyuan Yu
- Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, NY, USA.
- Center for Advanced Proteomics, Cornell University, Ithaca, NY, USA.
- Department of Computational Biology, Cornell University, Ithaca, NY, USA.
| |
Collapse
|
13
|
Smith IR, Eng JK, Barente AS, Hogrebe A, Llovet A, Rodriguez-Mias RA, Villén J. Coisolation of Peptide Pairs for Peptide Identification and MS/MS-Based Quantification. Anal Chem 2022; 94:15198-15206. [PMID: 36306373 PMCID: PMC9851627 DOI: 10.1021/acs.analchem.2c01711] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
Stable-isotope labeling with amino acids in cell culture (SILAC)-based metabolic labeling is a widely adopted proteomics approach that enables quantitative comparisons among a variety of experimental conditions. Despite its quantitative capacity, SILAC experiments analyzed with data-dependent acquisition (DDA) do not fully leverage peptide pair information for identification and suffer from undersampling compared to label-free proteomic experiments. Herein, we developed a DDA strategy that coisolates and fragments SILAC peptide pairs and uses y-ions for their relative quantification. To facilitate the analysis of this type of data, we adapted the Comet sequence database search engine to make use of SILAC peptide paired fragments and developed a tool to annotate and quantify MS/MS spectra of coisolated SILAC pairs. This peptide pair coisolation approach generally improved expectation scores compared to the traditional DDA approach. Fragment ion quantification performed similarly well to precursor quantification in the MS1 and achieved more quantifications. Lastly, our method enables reliable MS/MS quantification of SILAC proteome mixtures with overlapping isotopic distributions. This study shows the feasibility of the coisolation approach. Coupling this approach with intelligent acquisition strategies has the potential to improve SILAC peptide sampling and quantification.
Collapse
Affiliation(s)
- Ian R Smith
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, United States
| | - Jimmy K Eng
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, United States
| | - Anthony S Barente
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, United States
| | - Alexander Hogrebe
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, United States
| | - Ariadna Llovet
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, United States
| | - Ricard A Rodriguez-Mias
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, United States
| | - Judit Villén
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, United States
| |
Collapse
|
14
|
James Sanford E, Bustamante Smolka M. A field guide to the proteomics of post-translational modifications in DNA repair. Proteomics 2022; 22:e2200064. [PMID: 35695711 PMCID: PMC9950963 DOI: 10.1002/pmic.202200064] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Revised: 05/19/2022] [Accepted: 05/30/2022] [Indexed: 12/15/2022]
Abstract
All cells incur DNA damage from exogenous and endogenous sources and possess pathways to detect and repair DNA damage. Post-translational modifications (PTMs), in the past 20 years, have risen to ineluctable importance in the study of the regulation of DNA repair mechanisms. For example, DNA damage response kinases are critical in both the initial sensing of DNA damage as well as in orchestrating downstream activities of DNA repair factors. Mass spectrometry-based proteomics revolutionized the study of the role of PTMs in the DNA damage response and has canonized PTMs as central modulators of nearly all aspects of DNA damage signaling and repair. This review provides a biologist-friendly guide for the mass spectrometry analysis of PTMs in the context of DNA repair and DNA damage responses. We reflect on the current state of proteomics for exploring new mechanisms of PTM-based regulation and outline a roadmap for designing PTM mapping experiments that focus on the DNA repair and DNA damage responses.
Collapse
Key Words
- LC-MS/MS, technology, bottom-up proteomics, technology, signal transduction, cell biology
- phosphoproteomics, technology, post-translational modification analysis, technology, post-translational modifications, cell biology, mass spectrometry
Collapse
Affiliation(s)
- Ethan James Sanford
- Department of Molecular Biology and Genetics, Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, NY 14853
| | - Marcus Bustamante Smolka
- Department of Molecular Biology and Genetics, Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, NY 14853,Corresponding author:
| |
Collapse
|
15
|
Zeng X, Lan Y, Xiao J, Hu L, Tan L, Liang M, Wang X, Lu S, Peng T, Long F. Advances in phosphoproteomics and its application to COPD. Expert Rev Proteomics 2022; 19:311-324. [PMID: 36730079 DOI: 10.1080/14789450.2023.2176756] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
INTRODUCTION Chronic obstructive pulmonary disease (COPD) was the third leading cause of global death in 2019, causing a huge economic burden to society. Therefore, it is urgent to identify specific phenotypes of COPD patients through early detection, and to promptly treat exacerbations. The field of phosphoproteomics has been a massive advancement, compelled by the developments in mass spectrometry, enrichment strategies, algorithms, and tools. Modern mass spectrometry-based phosphoproteomics allows understanding of disease pathobiology, biomarker discovery, and predicting new therapeutic modalities. AREAS COVERED In this article, we present an overview of phosphoproteomic research and strategies for enrichment and fractionation of phosphopeptides, identification of phosphorylation sites, chromatographic separation and mass spectrometry detection strategies, and the potential application of phosphorylated proteomic analysis in the diagnosis, treatment, and prognosis of COPD disease. EXPERT OPINION The role of phosphoproteomics in COPD is critical for understanding disease pathobiology, identifying potential biomarkers, and predicting new therapeutic approaches. However, the complexity of COPD requires the more comprehensive understanding that can be achieved through integrated multi-omics studies. Phosphoproteomics, as a part of these multi-omics approaches, can provide valuable insights into the underlying mechanisms of COPD.
Collapse
Affiliation(s)
- Xiaoyin Zeng
- Sino-French Hoffmann Institute, School of Basic Medical Science, State Key Laboratory of Respiratory Disease, Guangzhou Medical University, Guangzhou, China
| | - Yanting Lan
- Sino-French Hoffmann Institute, School of Basic Medical Science, State Key Laboratory of Respiratory Disease, Guangzhou Medical University, Guangzhou, China
| | - Jing Xiao
- Sino-French Hoffmann Institute, School of Basic Medical Science, State Key Laboratory of Respiratory Disease, Guangzhou Medical University, Guangzhou, China
| | - Longbo Hu
- Sino-French Hoffmann Institute, School of Basic Medical Science, State Key Laboratory of Respiratory Disease, Guangzhou Medical University, Guangzhou, China
| | - Long Tan
- Sino-French Hoffmann Institute, School of Basic Medical Science, State Key Laboratory of Respiratory Disease, Guangzhou Medical University, Guangzhou, China
| | - Mengdi Liang
- Sino-French Hoffmann Institute, School of Basic Medical Science, State Key Laboratory of Respiratory Disease, Guangzhou Medical University, Guangzhou, China
| | - Xufei Wang
- Sino-French Hoffmann Institute, School of Basic Medical Science, State Key Laboratory of Respiratory Disease, Guangzhou Medical University, Guangzhou, China
| | - Shaohua Lu
- Sino-French Hoffmann Institute, School of Basic Medical Science, State Key Laboratory of Respiratory Disease, Guangzhou Medical University, Guangzhou, China
| | - Tao Peng
- Sino-French Hoffmann Institute, School of Basic Medical Science, State Key Laboratory of Respiratory Disease, Guangzhou Medical University, Guangzhou, China.,Guangdong South China Vaccine Co. Ltd, Guangzhou, China
| | - Fei Long
- Sino-French Hoffmann Institute, School of Basic Medical Science, State Key Laboratory of Respiratory Disease, Guangzhou Medical University, Guangzhou, China
| |
Collapse
|
16
|
HarmonizR enables data harmonization across independent proteomic datasets with appropriate handling of missing values. Nat Commun 2022; 13:3523. [PMID: 35725563 PMCID: PMC9209422 DOI: 10.1038/s41467-022-31007-x] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Accepted: 05/25/2022] [Indexed: 01/01/2023] Open
Abstract
Dataset integration is common practice to overcome limitations in statistically underpowered omics datasets. Proteome datasets display high technical variability and frequent missing values. Sophisticated strategies for batch effect reduction are lacking or rely on error-prone data imputation. Here we introduce HarmonizR, a data harmonization tool with appropriate missing value handling. The method exploits the structure of available data and matrix dissection for minimal data loss, without data imputation. This strategy implements two common batch effect reduction methods—ComBat and limma (removeBatchEffect()). The HarmonizR strategy, evaluated on four exemplarily analyzed datasets with up to 23 batches, demonstrated successful data harmonization for different tissue preservation techniques, LC-MS/MS instrumentation setups, and quantification approaches. Compared to data imputation methods, HarmonizR was more efficient and performed superior regarding the detection of significant proteins. HarmonizR is an efficient tool for missing data tolerant experimental variance reduction and is easily adjustable for individual dataset properties and user preferences. Dataset integration is common practice to overcome limitations in statistically underpowered omics datasets. Here the authors present “HarmonizR”, a tool for missing data tolerant experimental variance reduction in large, integrated but independently generated datasets without data imputation, adjustable for individual dataset modalities, correction algorithm, and user preferences.
Collapse
|
17
|
Mizero B, Villacrés C, Spicer V, Viner R, Saba J, Patel B, Snovida S, Jensen P, Huhmer A, Krokhin OV. Retention Time Prediction for TMT-Labeled Peptides in Proteomic LC-MS Experiments. J Proteome Res 2022; 21:1218-1228. [PMID: 35363494 DOI: 10.1021/acs.jproteome.1c00833] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
We present the first detailed study of chromatographic behavior of peptides labeled with tandem mass tags (TMT and TMTpro) in 2D LC for proteomic applications. Carefully designed experimental procedures have permitted generating data sets of over 100,000 nonlabeled and TMT-labeled peptide pairs for the low pH RP in the second separation dimension and data sets of over 10,000 peptide pairs for high-pH RP, HILIC (amide and silica), and SCX separations in the first separation dimension. The average increase in peptide RPLC (0.1% formic acid) retention upon TMT labeling was found to be 3.3% acetonitrile (linear water/acetonitrile gradients), spanning a range of -4 to 10.3%. In addition to the bulk peptide properties such as length, hydrophobicity, and the number of labeled residues, we found several sequence-dependent features mostly associated with differences in N-terminal chemistry. The behavior of TMTpro-labeled peptides was found to be very similar except for a slightly higher hydrophobicity: an average retention shift of 3.7% acetonitrile. The respective versions of the sequence-specific retention calculator (SSRCalc) model have been developed to accommodate both TMT chemistries, showing identical prediction accuracy (R2 ∼ 0.98) for labeled and nonlabeled peptides. Higher retention for TMT-labeled peptides was observed for high-pH RP and HILIC separations, while SCX selectivity remained virtually unchanged.
Collapse
Affiliation(s)
- Benilde Mizero
- Department of Chemistry, University of Manitoba, Winnipeg R3T 2N2, Canada
| | - Carina Villacrés
- Manitoba Centre for Proteomics and Systems Biology, Winnipeg R3E 3P4, Canada
| | - Victor Spicer
- Manitoba Centre for Proteomics and Systems Biology, Winnipeg R3E 3P4, Canada
| | - Rosa Viner
- Thermo Fisher Scientific, San Jose, California 95134, United States
| | - Julian Saba
- Thermo Fisher Scientific, San Jose, California 95134, United States
| | | | - Sergei Snovida
- Thermo Fisher Scientific, Rockford, Illinois 61101, United States
| | - Penny Jensen
- Thermo Fisher Scientific, Rockford, Illinois 61101, United States
| | - Andreas Huhmer
- Thermo Fisher Scientific, San Jose, California 95134, United States
| | - Oleg V Krokhin
- Department of Chemistry, University of Manitoba, Winnipeg R3T 2N2, Canada.,Manitoba Centre for Proteomics and Systems Biology, Winnipeg R3E 3P4, Canada.,Department of Internal Medicine, University of Manitoba, Winnipeg R3E 3P4, Canada
| |
Collapse
|
18
|
Pienkowski T, Kowalczyk T, Garcia-Romero N, Ayuso-Sacido A, Ciborowski M. Proteomics and metabolomics approach in adult and pediatric glioma diagnostics. Biochim Biophys Acta Rev Cancer 2022; 1877:188721. [PMID: 35304294 DOI: 10.1016/j.bbcan.2022.188721] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Revised: 03/10/2022] [Accepted: 03/11/2022] [Indexed: 12/26/2022]
Abstract
The diagnosis of glioma is mainly based on imaging methods that do not distinguish between stage and subtype prior to histopathological analysis. Patients with gliomas are generally diagnosed in the symptomatic stage of the disease. Additionally, healing scar tissue may be mistakenly identified based on magnetic resonance imaging (MRI) as a false positive tumor recurrence in postoperative patients. Current knowledge of molecular alterations underlying gliomagenesis and identification of tumoral biomarkers allow for their use as discriminators of the state of the organism. Moreover, a multiomics approach provides the greatest spectrum and the ability to track physiological changes and can serve as a minimally invasive method for diagnosing asymptomatic gliomas, preceding surgery and allowing for the initiation of prophylactic treatment. It is important to create a vast biomarker library for adults and pediatric patients due to their metabolic differences. This review focuses on the most promising proteomic, metabolomic and lipidomic glioma biomarkers, their pathways, the interactions, and correlations that can be considered characteristic of tumor grade or specific subtype.
Collapse
Affiliation(s)
- Tomasz Pienkowski
- Clinical Research Centre, Medical University of Bialystok, M. Sklodowskiej-Curie 24a, 15-276 Bialystok, Poland.
| | - Tomasz Kowalczyk
- Clinical Research Centre, Medical University of Bialystok, M. Sklodowskiej-Curie 24a, 15-276 Bialystok, Poland; Department of Medical Microbiology and Nanobiomedical Engineering, Medical University of Bialystok, Mickiewicza 2C, 15-222 Bialystok, Poland
| | - Noemi Garcia-Romero
- Faculty of Experimental Sciences, Universidad Francisco de Vitoria, 28223 Madrid, Spain; Brain Tumor Laboratory, Fundación Vithas, Grupo Hospitales Vithas, 28043 Madrid, Spain
| | - Angel Ayuso-Sacido
- Faculty of Experimental Sciences, Universidad Francisco de Vitoria, 28223 Madrid, Spain; Brain Tumor Laboratory, Fundación Vithas, Grupo Hospitales Vithas, 28043 Madrid, Spain; Faculty of Medicine, Universidad Francisco de Vitoria, 28223 Madrid, Spain
| | - Michal Ciborowski
- Clinical Research Centre, Medical University of Bialystok, M. Sklodowskiej-Curie 24a, 15-276 Bialystok, Poland
| |
Collapse
|
19
|
Urban J. A review on recent trends in the phosphoproteomics workflow. From sample preparation to data analysis. Anal Chim Acta 2022; 1199:338857. [DOI: 10.1016/j.aca.2021.338857] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2021] [Revised: 07/14/2021] [Accepted: 07/15/2021] [Indexed: 12/12/2022]
|
20
|
Abstract
To absolutely and relatively quantitate the alteration of a posttranslationally modified (PTM) proteome in response to a specific internal or external signal, a 15N-stable isotope labeling in Arabidopsis (SILIA) protocol has been integrated into the 4C quantitative PTM proteomics, named as SILIA-based 4C quantitative PTM proteomics (S4Quap). The isotope metabolic labeling produces both forward (F) and reciprocal (R) mixings of either 14N/15N-coded tissues or the 14N/15N-coded total cellular proteins. Plant protein is isolated using a urea-based extraction buffer (UEB). The presence of 8 M urea, 2% polyvinylpolypyrrolidone (PVPP), and 5 mM ascorbic acid allows to instantly denature protein, remove the phenolic compounds, and curb the oxidation by free radicals once plant cells are broken. The total cellular proteins are routinely processed into peptides by trypsin. The PTM peptide yield of affinity enrichment and preparation is 0.1-0.2% in general. Ion exchange chromatographic fractionation prepares the PTM peptides for LC-MS/MS analysis. The collected mass spectrograms are subjected to a target-decoy sequence analysis using various search engines. The computational programs are subsequently applied to analyze the ratios of the extracted ion chromatogram (XIC) of the 14N/15N isotope-coded PTM peptide ions and to perform the statistical evaluation of the quantitation results. The Student t-test values of ratios of quantifiable 14N/15N-coded PTM peptides are normally corrected using a Benjamini-Hochberg (BH) multiple hypothesis test to select the significantly regulated PTM peptide groups (BH-FDR < 5%). Consequently, the highly selected prospect candidate(s) of PTM proteins are confirmed and validated using biochemical, molecular, cellular, and transgenic plant analysis.
Collapse
Affiliation(s)
- Emily Oi Ying Wong
- Division of Life Science, The Hong Kong University of Science and Technology, Hong Kong, SAR, China.,Shenzhen Research Institute, The Hong Kong University of Science and Technology, Hong Kong, SAR, China
| | - Ning Li
- Division of Life Science, The Hong Kong University of Science and Technology, Hong Kong, SAR, China. .,Shenzhen Research Institute, The Hong Kong University of Science and Technology, Hong Kong, SAR, China.
| |
Collapse
|
21
|
NTRK1/TrkA Signaling in Neuroblastoma Cells Induces Nuclear Reorganization and Intra-Nuclear Aggregation of Lamin A/C. Cancers (Basel) 2021; 13:cancers13215293. [PMID: 34771457 PMCID: PMC8582546 DOI: 10.3390/cancers13215293] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Accepted: 10/19/2021] [Indexed: 11/17/2022] Open
Abstract
Simple Summary Neuroblastoma (NB) accounts for 15% of all cancer-related deaths of children. While the amplification of the Myc-N proto-oncogene (MYCN) is a major driver of aggressive NB, the expression of the neurotrophin receptor, NTRK1/TrkA, has been shown to be associated with an excellent outcome. MYCN downregulates NTRK1 expression, but it is unknown if the molecular effects of NTRK1 signaling also affect MYCN-induced networks. The aim of this study was to decipher NTRK1 signaling using an unbiased proteome and phosphoproteome approach. To this end, we realized inducible ectopic NTRK1 expression in a NB cell line with MYCN amplification and analyzed the proteomic changes upon NTRK1 activation in a time-dependent manner. In line with the phenotypes observed, NTRK1 activation induced markers of neuronal differentiation and cell cycle arrest. Most prominently, NTRK1 upregulated the expression and phosphorylation of the nuclear lamina component Lamin A/C. Moreover, NTRK1 signaling also induced the aggregation of LMNA within nucleic foci, which accompanies differentiation in other cell types. Abstract (1) Background: Neuroblastomas (NBs) are the most common extracranial solid tumors of children. The amplification of the Myc-N proto-oncogene (MYCN) is a major driver of NB aggressiveness, while high expression of the neurotrophin receptor NTRK1/TrkA is associated with mild disease courses. The molecular effects of NTRK1 signaling in MYCN-amplified NB, however, are still poorly understood and require elucidation. (2) Methods: Inducible NTRK1 expression was realized in four NB cell lines with (IMR5, NGP) or without MYCN amplification (SKNAS, SH-SY5Y). Proteome and phosphoproteome dynamics upon NTRK1 activation by its ligand, NGF, were analyzed in a time-dependent manner in IMR5 cells. Target validation by immunofluorescence staining and automated image processing was performed using the three other NB cell lines. (3) Results: In total, 230 proteins and 134 single phosphorylated class I phosphosites were found to be significantly regulated upon NTRK1 activation. Among known NTRK1 targets, Stathmin and the neurosecretory protein VGF were recovered. Additionally, we observed the upregulation and phosphorylation of Lamin A/C (LMNA) that accumulated inside nuclear foci. (4) Conclusions: We provide a comprehensive picture of NTRK1-induced proteome and phosphoproteome dynamics. The phosphorylation of LMNA within nucleic aggregates was identified as a prominent feature of NTRK1 signaling independent of the MYCN status of NB cells.
Collapse
|
22
|
Kulyyassov A, Fresnais M, Longuespée R. Targeted liquid chromatography-tandem mass spectrometry analysis of proteins: Basic principles, applications, and perspectives. Proteomics 2021; 21:e2100153. [PMID: 34591362 DOI: 10.1002/pmic.202100153] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Revised: 09/08/2021] [Accepted: 09/24/2021] [Indexed: 12/25/2022]
Abstract
Liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) is now the main analytical method for the identification and quantification of peptides and proteins in biological samples. In modern research, identification of biomarkers and their quantitative comparison between samples are becoming increasingly important for discovery, validation, and monitoring. Such data can be obtained following specific signals after fragmentation of peptides using multiple reaction monitoring (MRM) and parallel reaction monitoring (PRM) methods, with high specificity, accuracy, and reproducibility. In addition, these methods allow measurement of the amount of post-translationally modified forms and isoforms of proteins. This review article describes the basic principles of MRM assays, guidelines for sample preparation, recent advanced MRM-based strategies, applications and illustrative perspectives of MRM/PRM methods in clinical research and molecular biology.
Collapse
Affiliation(s)
| | - Margaux Fresnais
- Department of Clinical Pharmacology and Pharmacoepidemiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Rémi Longuespée
- Department of Clinical Pharmacology and Pharmacoepidemiology, Heidelberg University Hospital, Heidelberg, Germany
| |
Collapse
|
23
|
Levitsky LI, Bubis JA, Gorshkov MV, Tarasova IA. AA_stat: Intelligent profiling of in vivo and in vitro modifications from open search results. J Proteomics 2021; 248:104350. [PMID: 34389500 DOI: 10.1016/j.jprot.2021.104350] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Revised: 07/21/2021] [Accepted: 08/04/2021] [Indexed: 11/18/2022]
Abstract
Characterization of post-translational modifications is among the most challenging tasks in tandem mass spectrometry-based proteomics which has yet to find an efficient solution. The ultra-tolerant (open) database search attempts to meet this challenge. However, interpretation of the mass shifts observed in open search still requires an effective and automated solution. We have previously introduced the AA_stat tool for analysis of amino acid frequencies at different mass shifts and generation of hypotheses on unaccounted in vitro modifications. Here, we report on the new version of AA_stat, which now complements amino acid frequency statistics with a number of new features: (1) MS/MS-based localization of mass shifts and localization scoring, including shifts which are the sum of modifications; (2) inferring fixed modifications to increase method sensitivity; (3) inferring monoisotopic peak assignment errors and variable modifications based on abundant mass shift localizations to increase the yield of closed search; (4) new mass calibration algorithm to account for partial systematic shifts; (5) interactive integration of all results and a rated list of possible mass shift interpretations. With these options, we improve interpretation of open search results and demonstrate the utility of AA_stat for profiling of abundant and rare amino acid modifications. AA_stat is implemented in Python as an open-source command-line tool available at https://github.com/SimpleNumber/aa_stat. SIGNIFICANCE: Mass spectrometry-based PTM characterization has a long history, yet most of the methods rely on a priori knowledge of modifications of interest and do not provide a whole proteome modification landscape in a blind manner. The open database search is an efficient attempt to address this challenge by identifying peptides with mass shifts corresponding to possible modifications. Then, interpreting these mass shifts is required. Therefore, development of bioinformatics software for post-processing of the open search results, which is capable of detection and accurate annotation of new or unexpected modifications, from characterization of sample preparation efficiency and quality control to discovery of rare post-translational modifications, is of high importance.
Collapse
Affiliation(s)
- Lev I Levitsky
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 119334 Moscow, Russia
| | - Julia A Bubis
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 119334 Moscow, Russia
| | - Mikhail V Gorshkov
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 119334 Moscow, Russia
| | - Irina A Tarasova
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 119334 Moscow, Russia.
| |
Collapse
|
24
|
Integrated mass spectrometry-based multi-omics for elucidating mechanisms of bacterial virulence. Biochem Soc Trans 2021; 49:1905-1926. [PMID: 34374408 DOI: 10.1042/bst20191088] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Revised: 07/19/2021] [Accepted: 07/21/2021] [Indexed: 11/17/2022]
Abstract
Despite being considered the simplest form of life, bacteria remain enigmatic, particularly in light of pathogenesis and evolving antimicrobial resistance. After three decades of genomics, we remain some way from understanding these organisms, and a substantial proportion of genes remain functionally unknown. Methodological advances, principally mass spectrometry (MS), are paving the way for parallel analysis of the proteome, metabolome and lipidome. Each provides a global, complementary assay, in addition to genomics, and the ability to better comprehend how pathogens respond to changes in their internal (e.g. mutation) and external environments consistent with infection-like conditions. Such responses include accessing necessary nutrients for survival in a hostile environment where co-colonizing bacteria and normal flora are acclimated to the prevailing conditions. Multi-omics can be harnessed across temporal and spatial (sub-cellular) dimensions to understand adaptation at the molecular level. Gene deletion libraries, in conjunction with large-scale approaches and evolving bioinformatics integration, will greatly facilitate next-generation vaccines and antimicrobial interventions by highlighting novel targets and pathogen-specific pathways. MS is also central in phenotypic characterization of surface biomolecules such as lipid A, as well as aiding in the determination of protein interactions and complexes. There is increasing evidence that bacteria are capable of widespread post-translational modification, including phosphorylation, glycosylation and acetylation; with each contributing to virulence. This review focuses on the bacterial genotype to phenotype transition and surveys the recent literature showing how the genome can be validated at the proteome, metabolome and lipidome levels to provide an integrated view of organism response to host conditions.
Collapse
|
25
|
Gerritsen JS, White FM. Phosphoproteomics: a valuable tool for uncovering molecular signaling in cancer cells. Expert Rev Proteomics 2021; 18:661-674. [PMID: 34468274 PMCID: PMC8628306 DOI: 10.1080/14789450.2021.1976152] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Accepted: 08/31/2021] [Indexed: 10/20/2022]
Abstract
INTRODUCTION Many pathologies, including cancer, have been associated with aberrant phosphorylation-mediated signaling networks that drive altered cell proliferation, migration, metabolic regulation, and can lead to systemic inflammation. Phosphoproteomics, the large-scale analysis of protein phosphorylation sites, has emerged as a powerful tool to define signaling network regulation and dysregulation in normal and pathological conditions. AREAS COVERED We provide an overview of methodology for global phosphoproteomics as well as enrichment of specific subsets of the phosphoproteome, including phosphotyrosine and phospho-motif enrichment of kinase substrates. We review quantitative methods, advantages and limitations of different mass spectrometry acquisition formats, and computational approaches to extract biological insight from phosphoproteomics data. Throughout, we discuss various applications and their challenges in implementation. EXPERT OPINION Over the past 20 years the field of phosphoproteomics has advanced to enable deep biological and clinical insight through the quantitative analysis of signaling networks. Future areas of development include Clinical Laboratory Improvement Amendments (CLIA)-approved methods for analysis of clinical samples, continued improvements in sensitivity to enable analysis of small numbers of rare cells and tissue microarrays, and computational methods to integrate data resulting from multiple systems-level quantitative analytical methods.
Collapse
Affiliation(s)
- Jacqueline S Gerritsen
- Koch Institute for Integrative Cancer Research; Center for Precision Cancer Medicine; Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, U.S.A
| | - Forest M White
- Koch Institute for Integrative Cancer Research; Center for Precision Cancer Medicine; Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, U.S.A
| |
Collapse
|
26
|
Application of SILAC Labeling in Phosphoproteomics Analysis. Methods Mol Biol 2021. [PMID: 33950491 DOI: 10.1007/978-1-0716-1024-4_13] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register]
Abstract
The analysis of disease-related changes in the phosphorylation status of cellular signal transduction networks is of major interest to biomedical researchers. Mass spectrometry-based proteomics allows the analysis of phosphorylation in a global manner. However, several technical challenges need to be addressed when the phosphorylation of proteins is analyzed. Low-abundant phosphopeptides need to be enriched before analysis, thereby introducing additional steps in sample preparation. Consequently, the applied quantification strategies should be robust towards elaborate sampling handling, rendering label-based quantification strategies the methods of choice in many experiments. Here, we present a protocol for SILAC labeling and the subsequent isolation of phosphopeptides using TiO2 affinity chromatography. We outline the corresponding LC-MS/MS analysis and the essential steps of data processing.
Collapse
|
27
|
Abstract
The abundance, localization, modifications, and protein-protein interactions of many host cell and virus proteins can change dynamically throughout the course of any viral infection. Studying these changes is critical for a comprehensive understanding of how viruses replicate and cause disease, as well as for the development of antiviral therapeutics and vaccines. Previously, we developed a mass spectrometry-based technique called quantitative temporal viromics (QTV), which employs isobaric tandem mass tags (TMTs) to allow precise comparative quantification of host and virus proteomes through a whole time course of infection. In this review, we discuss the utility and applications of QTV, exemplified by numerous studies that have since used proteomics with a variety of quantitative techniques to study virus infection through time. Expected final online publication date for the Annual Review of Virology, Volume 8 is September 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
Collapse
Affiliation(s)
| | - Michael P Weekes
- Cambridge Institute for Medical Research, University of Cambridge, Cambridge CB2 0XY, United Kingdom;
| |
Collapse
|
28
|
Palomba A, Abbondio M, Fiorito G, Uzzau S, Pagnozzi D, Tanca A. Comparative Evaluation of MaxQuant and Proteome Discoverer MS1-Based Protein Quantification Tools. J Proteome Res 2021; 20:3497-3507. [PMID: 34038140 PMCID: PMC8280745 DOI: 10.1021/acs.jproteome.1c00143] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
![]()
MS1-based label-free
quantification can compare precursor ion peaks
across runs, allowing reproducible protein measurements. Among bioinformatic
platforms enabling MS1-based quantification, MaxQuant (MQ) is one
of the most used, while Proteome Discoverer (PD) has recently introduced
the Minora tool. Here, we present a comparative evaluation of six
MS1-based quantification methods available in MQ and PD. Intensity
(MQ and PD) and area (PD only) of the precursor ion peaks were measured
and then subjected or not to normalization. The six methods were applied
to data sets simulating various differential proteomics scenarios
and covering a wide range of protein abundance ratios and amounts.
PD outperformed MQ in terms of quantification yield, dynamic range,
and reproducibility, although neither platform reached a fully satisfactory
quality of measurements at low-abundance ranges. PD methods including
normalization were the most accurate in estimating the abundance ratio
between groups and the most sensitive when comparing groups with a
narrow abundance ratio; on the contrary, MQ methods generally reached
slightly higher specificity, accuracy, and precision values. Moreover,
we found that applying an optimized log ratio-based threshold can
maximize specificity, accuracy, and precision. Taken together, these
results can help researchers choose the most appropriate MS1-based
protein quantification strategy for their studies.
Collapse
Affiliation(s)
- Antonio Palomba
- Porto Conte Ricerche, Loc. Tramariglio, 07041 Alghero, Italy
| | - Marcello Abbondio
- Department of Biomedical Sciences, University of Sassari, Viale San Pietro 43/B, 07100 Sassari, Italy
| | - Giovanni Fiorito
- Department of Biomedical Sciences, University of Sassari, Viale San Pietro 43/B, 07100 Sassari, Italy.,MRC Centre for Environment and Health, Imperial College London, Norfolk Place, W2 1PG London, U.K
| | - Sergio Uzzau
- Department of Biomedical Sciences, University of Sassari, Viale San Pietro 43/B, 07100 Sassari, Italy
| | | | - Alessandro Tanca
- Department of Biomedical Sciences, University of Sassari, Viale San Pietro 43/B, 07100 Sassari, Italy
| |
Collapse
|
29
|
Phenotypic screening with target identification and validation in the discovery and development of E3 ligase modulators. Cell Chem Biol 2021; 28:283-299. [PMID: 33740433 DOI: 10.1016/j.chembiol.2021.02.011] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2020] [Revised: 12/17/2020] [Accepted: 02/12/2021] [Indexed: 02/07/2023]
Abstract
The use of phenotypic screening was central to the discovery and development of novel thalidomide analogs, the IMiDs (immunomodulatory drugs) agents. With the discovery that these agents bind the E3 ligase, CRL4CRBN, and alter its substrate specificity, there has been a great deal of endeavor to discover other small molecules that can modulate alternative E3 ligases. Furthermore, the chemical properties necessary for drug discovery and the rules by which neo-substrates are selected for degradation are being defined in the context of phenotypic alterations in specific cellular systems. This review gives a detailed summary of these recent advances and the methodologies being exploited to understand the mechanism of action of emerging protein degradation therapies.
Collapse
|
30
|
Taverna D, Gaspari M. A critical comparison of three MS-based approaches for quantitative proteomics analysis. JOURNAL OF MASS SPECTROMETRY : JMS 2021; 56:e4669. [PMID: 33128495 DOI: 10.1002/jms.4669] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Revised: 09/07/2020] [Accepted: 10/10/2020] [Indexed: 06/11/2023]
Abstract
MS-based proteomics is expanding its role as a routine tool for biological discovery. Nevertheless, the task of accurately and precisely quantifying thousands of analytes in a single experiment remains challenging. In this study, the diagnostic accuracy of three popular data-dependent methods for protein relative quantification (label-free [LF], dimethyl labelling [DML] and tandem mass tags [TMT]) has been assessed using a mixed species proteome (three species) and five experimental replicates per condition. Data were produced using a quadrupole-Orbitrap mass spectrometer and analysed using a single platform (the MaxQuant/Perseus software suite). The whole comparative analysis was repeated three times over a period of 6 months, in order to assess the consistency of the reported findings. As expected, label-based methods reproducibly provided a lower false positives rate, whereas TMT and LF performed similarly, and significantly better than DML, in terms of proteome coverage using the same instrument time. Although parameters like proteome coverage and precision were consistent in between replicates, other parameters like sensitivity, intended as the capacity of correctly classifying true positives (regulated proteins), were found to be less reproducible, especially at challenging fold-changes (1.5). Collectively, data suggest that an increased interest in data reproducibility would be desirable in the quantitative proteomics field.
Collapse
Affiliation(s)
- Domenico Taverna
- Research Centre for Advanced Biochemistry and Molecular Biology, Department of Experimental and Clinical Medicine, Magna Graecia University of Catanzaro, Catanzaro, Italy
| | - Marco Gaspari
- Research Centre for Advanced Biochemistry and Molecular Biology, Department of Experimental and Clinical Medicine, Magna Graecia University of Catanzaro, Catanzaro, Italy
| |
Collapse
|
31
|
Rauh T, Brameyer S, Kielkowski P, Jung K, Sieber SA. MS-Based in Situ Proteomics Reveals AMPylation of Host Proteins during Bacterial Infection. ACS Infect Dis 2020; 6:3277-3289. [PMID: 33259205 PMCID: PMC9558369 DOI: 10.1021/acsinfecdis.0c00740] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
![]()
Bacteria utilize versatile strategies
to propagate infections within
human cells, e.g., by the injection of effector proteins,
which alter crucial signaling pathways. One class of such virulence-associated
proteins is involved in the AMPylation of eukaryotic Rho GTPases with
devastating effects on viability. In order to get an inventory of
AMPylated proteins, several technologies have been developed. However,
as they were designed for the analysis of cell lysates, knowledge
about AMPylation targets in living cells is largely lacking. Here,
we implement a chemical-proteomic method for deciphering AMPylated
host proteins in situ during bacterial infection.
HeLa cells treated with a previously established cell permeable pronucleotide
probe (pro-N6pA) were infected with Vibrio parahaemolyticus, and modified host proteins were identified upon probe enrichment
and LC-MS/MS analysis. Three already known targets of the AMPylator
VopS—Rac1, RhoA, and Cdc42—could be confirmed, and several
other Rho GTPases were additionally identified. These hits were validated
in comparative studies with V. parahaemolyticus wild type and a mutant producing an inactive VopS (H348A). The method
further allowed to decipher the sites of modification and facilitated
a time-dependent analysis of AMPylation during infection. Overall,
the methodology provides a reliable detection of host AMPylation in situ and thus a versatile tool in monitoring infection
processes.
Collapse
Affiliation(s)
- Theresa Rauh
- Department of Chemistry, Chair of Organic Chemistry II, Center for Functional Protein Assemblies (CPA), Technische Universität München, Lichtenbergstraße 4, 85748 Garching, Germany
| | - Sophie Brameyer
- Department of Biology I, Microbiology, Ludwig-Maximilians-Universität München, 82152 Martinsried, Germany
| | - Pavel Kielkowski
- Department of Chemistry, Ludwig-Maximilians-Universität München, 81377 München, Germany
| | - Kirsten Jung
- Department of Biology I, Microbiology, Ludwig-Maximilians-Universität München, 82152 Martinsried, Germany
| | - Stephan A. Sieber
- Department of Chemistry, Chair of Organic Chemistry II, Center for Functional Protein Assemblies (CPA), Technische Universität München, Lichtenbergstraße 4, 85748 Garching, Germany
| |
Collapse
|
32
|
Wang Z, Karkossa I, Großkopf H, Rolle-Kampczyk U, Hackermüller J, von Bergen M, Schubert K. Comparison of quantitation methods in proteomics to define relevant toxicological information on AhR activation of HepG2 cells by BaP. Toxicology 2020; 448:152652. [PMID: 33278487 DOI: 10.1016/j.tox.2020.152652] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Revised: 11/19/2020] [Accepted: 11/27/2020] [Indexed: 02/06/2023]
Abstract
The application of quantitative proteomics provides a new and promising tool for standardized toxicological research. However, choosing a suitable quantitative method still puzzles many researchers because the optimal method needs to be determined. In this study, we investigated the advantages and limitations of two of the most commonly used global quantitative proteomics methods, namely label-free quantitation (LFQ) and tandem mass tags (TMT). As a case study, we exposed hepatocytes (HepG2) to the environmental contaminant benzo[a]pyrene (BaP) using a concentration of 2 μM. Our results revealed that both methods yield a similar proteome coverage, in which for LFQ a wider range of fold changes was observed but with less significant p-values compared to TMT. We detected 37 and 47 significantly enriched pathways by LFQ and TMT, respectively, with 17 overlapping pathways. To define the minimally required effort in proteomics as a benchmark, we artificially reduced the LFQ, and TMT data sets stepwise and compared the pathway enrichment. Thereby, we found that fewer proteins are necessary for detecting significant enrichment of pathways in TMT compared to LFQ, which might be explained by the higher reproducibility of the TMT data that was observed. In summary, we showed that the TMT approach is the preferable one when investigating toxicological questions because it offers a high reproducibility and sufficient proteome coverage in a comparably short time.
Collapse
Affiliation(s)
- Zhipeng Wang
- Department of Molecular Systems Biology, Helmholtz-Centre for Environmental Research - UFZ, Leipzig, Germany
| | - Isabel Karkossa
- Department of Molecular Systems Biology, Helmholtz-Centre for Environmental Research - UFZ, Leipzig, Germany
| | - Henning Großkopf
- Department of Molecular Systems Biology, Helmholtz-Centre for Environmental Research - UFZ, Leipzig, Germany
| | - Ulrike Rolle-Kampczyk
- Department of Molecular Systems Biology, Helmholtz-Centre for Environmental Research - UFZ, Leipzig, Germany
| | - Jörg Hackermüller
- Department of Molecular Systems Biology, Helmholtz-Centre for Environmental Research - UFZ, Leipzig, Germany
| | - Martin von Bergen
- Department of Molecular Systems Biology, Helmholtz-Centre for Environmental Research - UFZ, Leipzig, Germany; Institute of Biochemistry, Leipzig University, Leipzig, Germany
| | - Kristin Schubert
- Department of Molecular Systems Biology, Helmholtz-Centre for Environmental Research - UFZ, Leipzig, Germany.
| |
Collapse
|