Applications of Mass Spectrometry in Proteomics

2013 ◽  
Vol 66 (7) ◽  
pp. 721 ◽  
Author(s):  
Izabela Sokolowska ◽  
Armand G. Ngounou Wetie ◽  
Alisa G. Woods ◽  
Costel C. Darie

Characterisation of proteins and whole proteomes can provide a foundation to our understanding of physiological and pathological states and biological diseases or disorders. Constant development of more reliable and accurate mass spectrometry (MS) instruments and techniques has allowed for better identification and quantification of the thousands of proteins involved in basic physiological processes. Therefore, MS-based proteomics has been widely applied to the analysis of biological samples and has greatly contributed to our understanding of protein functions, interactions, and dynamics, advancing our knowledge of cellular processes as well as the physiology and pathology of the human body. This review will discuss current proteomic approaches for protein identification and characterisation, including post-translational modification (PTM) analysis and quantitative proteomics as well as investigation of protein–protein interactions (PPIs).

2019 ◽  
Vol 36 (3) ◽  
pp. 859-864 ◽  
Author(s):  
Hongyang Li ◽  
Yuanfang Guan

Abstract Motivation Reversible protein phosphorylation is an essential post-translational modification regulating protein functions and signaling pathways in many cellular processes. Aberrant activation of signaling pathways often contributes to cancer development and progression. The mass spectrometry-based phosphoproteomics technique is a powerful tool to investigate the site-level phosphorylation of the proteome in a global fashion, paving the way for understanding the regulatory mechanisms underlying cancers. However, this approach is time-consuming and requires expensive instruments, specialized expertise and a large amount of starting material. An alternative in silico approach is predicting the phosphoproteomic profiles of cancer patients from the available proteomic, transcriptomic and genomic data. Results Here, we present a winning algorithm in the 2017 NCI-CPTAC DREAM Proteogenomics Challenge for predicting phosphorylation levels of the proteome across cancer patients. We integrate four components into our algorithm, including (i) baseline correlations between protein and phosphoprotein abundances, (ii) universal protein–protein interactions, (iii) shareable regulatory information across cancer tissues and (iv) associations among multi-phosphorylation sites of the same protein. When tested on a large held-out testing dataset of 108 breast and 62 ovarian cancer samples, our method ranked first in both cancer tissues, demonstrating its robustness and generalization ability. Availability and implementation Our code and reproducible results are freely available on GitHub: https://github.com/GuanLab/phosphoproteome_prediction. Supplementary information Supplementary data are available at Bioinformatics online.


Pathogens ◽  
2019 ◽  
Vol 8 (4) ◽  
pp. 173 ◽  
Author(s):  
Veyron-Churlet ◽  
Locht

Studies on protein–protein interactions (PPI) can be helpful for the annotation of unknown protein functions and for the understanding of cellular processes, such as specific virulence mechanisms developed by bacterial pathogens. In that context, several methods have been extensively used in recent years for the characterization of Mycobacterium tuberculosis PPI to further decipher tuberculosis (TB) pathogenesis. This review aims at compiling the most striking results based on in vivo methods (yeast and bacterial two-hybrid systems, protein complementation assays) for the specific study of PPI in mycobacteria. Moreover, newly developed methods, such as in-cell native mass resonance and proximity-dependent biotinylation identification, will have a deep impact on future mycobacterial research, as they are able to perform dynamic (transient interactions) and integrative (multiprotein complexes) analyses.


Biomolecules ◽  
2020 ◽  
Vol 10 (8) ◽  
pp. 1122
Author(s):  
Chen-Fan Sun ◽  
Yong-Quan Li ◽  
Xu-Ming Mao

Protein post-translational modification (PTM) is a reversible process, which can dynamically regulate the metabolic state of cells through regulation of protein structure, activity, localization or protein–protein interactions. Actinomycetes are present in the soil, air and water, and their life cycle is strongly determined by environmental conditions. The complexity of variable environments urges Actinomycetes to respond quickly to external stimuli. In recent years, advances in identification and quantification of PTMs have led researchers to deepen their understanding of the functions of PTMs in physiology and metabolism, including vegetative growth, sporulation, metabolite synthesis and infectivity. On the other hand, most donor groups for PTMs come from various metabolites, suggesting a complex association network between metabolic states, PTMs and signaling pathways. Here, we review the mechanisms and functions of PTMs identified in Actinomycetes, focusing on phosphorylation, acylation and protein degradation in an attempt to summarize the recent progress of research on PTMs and their important role in bacterial cellular processes.


Author(s):  
Antony J. Burton ◽  
Ghaith M. Hamza ◽  
Andrew X. Zhang ◽  
Tom W. Muir

Protein–protein interactions (PPIs) in the nucleus play key roles in transcriptional regulation and ensure genomic stability. Critical to this are histone-mediated PPI networks, which are further fine-tuned through dynamic post-translational modification. Perturbation to these networks leads to genomic instability and disease, presenting epigenetic proteins as key therapeutic targets. This mini-review will describe progress in mapping the combinatorial histone PTM landscape, and recent chemical biology approaches to map histone interactors. Recent advances in mapping direct interactors of histone PTMs as well as local chromatin interactomes will be highlighted, with a focus on mass-spectrometry based workflows that continue to illuminate histone-mediated PPIs in unprecedented detail.


1999 ◽  
Vol 342 (2) ◽  
pp. 249-268 ◽  
Author(s):  
Damien d'AMOURS ◽  
Serge DESNOYERS ◽  
Icy d'SILVA ◽  
Guy G. POIRIER

Poly(ADP-ribosyl)ation is a post-translational modification of proteins. During this process, molecules of ADP-ribose are added successively on to acceptor proteins to form branched polymers. This modification is transient but very extensive in vivo, as polymer chains can reach more than 200 units on protein acceptors. The existence of the poly(ADP-ribose) polymer was first reported nearly 40 years ago. Since then, the importance of poly(ADP-ribose) synthesis has been established in many cellular processes. However, a clear and unified picture of the physiological role of poly(ADP-ribosyl)ation still remains to be established. The total dependence of poly(ADP-ribose) synthesis on DNA strand breaks strongly suggests that this post-translational modification is involved in the metabolism of nucleic acids. This view is also supported by the identification of direct protein-protein interactions involving poly(ADP-ribose) polymerase (113 kDa PARP), an enzyme catalysing the formation of poly(ADP-ribose), and key effectors of DNA repair, replication and transcription reactions. The presence of PARP in these multiprotein complexes, in addition to the actual poly(ADP-ribosyl)ation of some components of these complexes, clearly supports an important role for poly(ADP-ribosyl)ation reactions in DNA transactions. Accordingly, inhibition of poly(ADP-ribose) synthesis by any of several approaches and the analysis of PARP-deficient cells has revealed that the absence of poly(ADP-ribosyl)ation strongly affects DNA metabolism, most notably DNA repair. The recent identification of new poly(ADP-ribosyl)ating enzymes with distinct (non-standard) structures in eukaryotes and archaea has revealed a novel level of complexity in the regulation of poly(ADP-ribose) metabolism.


2019 ◽  
Vol 26 (21) ◽  
pp. 3890-3910 ◽  
Author(s):  
Branislava Gemovic ◽  
Neven Sumonja ◽  
Radoslav Davidovic ◽  
Vladimir Perovic ◽  
Nevena Veljkovic

Background: The significant number of protein-protein interactions (PPIs) discovered by harnessing concomitant advances in the fields of sequencing, crystallography, spectrometry and two-hybrid screening suggests astonishing prospects for remodelling drug discovery. The PPI space which includes up to 650 000 entities is a remarkable reservoir of potential therapeutic targets for every human disease. In order to allow modern drug discovery programs to leverage this, we should be able to discern complete PPI maps associated with a specific disorder and corresponding normal physiology. Objective: Here, we will review community available computational programs for predicting PPIs and web-based resources for storing experimentally annotated interactions. Methods: We compared the capacities of prediction tools: iLoops, Struck2Net, HOMCOS, COTH, PrePPI, InterPreTS and PRISM to predict recently discovered protein interactions. Results: We described sequence-based and structure-based PPI prediction tools and addressed their peculiarities. Additionally, since the usefulness of prediction algorithms critically depends on the quality and quantity of the experimental data they are built on; we extensively discussed community resources for protein interactions. We focused on the active and recently updated primary and secondary PPI databases, repositories specialized to the subject or species, as well as databases that include both experimental and predicted PPIs. Conclusion: PPI complexes are the basis of important physiological processes and therefore, possible targets for cell-penetrating ligands. Reliable computational PPI predictions can speed up new target discoveries through prioritization of therapeutically relevant protein–protein complexes for experimental studies.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Chun-Song Yang ◽  
Kasey Jividen ◽  
Teddy Kamata ◽  
Natalia Dworak ◽  
Luke Oostdyk ◽  
...  

AbstractAndrogen signaling through the androgen receptor (AR) directs gene expression in both normal and prostate cancer cells. Androgen regulates multiple aspects of the AR life cycle, including its localization and post-translational modification, but understanding how modifications are read and integrated with AR activity has been difficult. Here, we show that ADP-ribosylation regulates AR through a nuclear pathway mediated by Parp7. We show that Parp7 mono-ADP-ribosylates agonist-bound AR, and that ADP-ribosyl-cysteines within the N-terminal domain mediate recruitment of the E3 ligase Dtx3L/Parp9. Molecular recognition of ADP-ribosyl-cysteine is provided by tandem macrodomains in Parp9, and Dtx3L/Parp9 modulates expression of a subset of AR-regulated genes. Parp7, ADP-ribosylation of AR, and AR-Dtx3L/Parp9 complex assembly are inhibited by Olaparib, a compound used clinically to inhibit poly-ADP-ribosyltransferases Parp1/2. Our study reveals the components of an androgen signaling axis that uses a writer and reader of ADP-ribosylation to regulate protein-protein interactions and AR activity.


Proteomes ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 16
Author(s):  
Shomeek Chowdhury ◽  
Stephen Hepper ◽  
Mudassir K. Lodi ◽  
Milton H. Saier ◽  
Peter Uetz

Glycolysis is regulated by numerous mechanisms including allosteric regulation, post-translational modification or protein-protein interactions (PPI). While glycolytic enzymes have been found to interact with hundreds of proteins, the impact of only some of these PPIs on glycolysis is well understood. Here we investigate which of these interactions may affect glycolysis in E. coli and possibly across numerous other bacteria, based on the stoichiometry of interacting protein pairs (from proteomic studies) and their conservation across bacteria. We present a list of 339 protein-protein interactions involving glycolytic enzymes but predict that ~70% of glycolytic interactors are not present in adequate amounts to have a significant impact on glycolysis. Finally, we identify a conserved but uncharacterized subset of interactions that are likely to affect glycolysis and deserve further study.


2021 ◽  
Author(s):  
Ameya J. Limaye ◽  
George N. Bendzunas ◽  
Eileen Kennedy

Protein Kinase C (PKC) is a member of the AGC subfamily of kinases and regulates a wide array of signaling pathways and physiological processes. Protein-protein interactions involving PKC and its...


2018 ◽  
Vol 25 (1) ◽  
pp. 5-21 ◽  
Author(s):  
Ylenia Cau ◽  
Daniela Valensin ◽  
Mattia Mori ◽  
Sara Draghi ◽  
Maurizio Botta

14-3-3 is a class of proteins able to interact with a multitude of targets by establishing protein-protein interactions (PPIs). They are usually found in all eukaryotes with a conserved secondary structure and high sequence homology among species. 14-3-3 proteins are involved in many physiological and pathological cellular processes either by triggering or interfering with the activity of specific protein partners. In the last years, the scientific community has collected many evidences on the role played by seven human 14-3-3 isoforms in cancer or neurodegenerative diseases. Indeed, these proteins regulate the molecular mechanisms associated to these diseases by interacting with (i) oncogenic and (ii) pro-apoptotic proteins and (iii) with proteins involved in Parkinson and Alzheimer diseases. The discovery of small molecule modulators of 14-3-3 PPIs could facilitate complete understanding of the physiological role of these proteins, and might offer valuable therapeutic approaches for these critical pathological states.


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