Mass Spectrometry-Based Quantitative Proteomics

A special issue of Proteomes (ISSN 2227-7382).

Deadline for manuscript submissions: closed (30 November 2021) | Viewed by 14681

Special Issue Editor

Department of Comparative Pathobiology, College of Veterinary Medicine, Purdue University, West Lafayette, IN 47907, USA
Interests: mass spectrometry; proteomics; phosphoproteomics; cellular senescence; aging; type 2 diabetes; plant proteomics; protein complexes; protein–protein interactions
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues, 

Organisms adapt their cellular activities to internal and external environments by regulating gene and protein expression as well as a series of protein post-translational modifications and protein–protein interactions. In recent years, proteomics has emerged as the key technology to understand how proteins work together in a coordinated fashion to execute biological functions. In addition, remarkable technological advances have been achieved due to improvements in proteomic sample preparation and mass spectrometry analysis, which allow refining the coverage of total proteomes and sub-proteomes from small amounts of starting material and characterizing post-translational modifications and protein–protein interactions. Furthermore, quantitative spatial and temporal proteomics now provides detailed information on organ- and tissue-specific regulatory mechanisms responding to a variety of individual stresses or stress combinations during the cell life cycle. Finally, the development of computational and bioinformatic tools allows managing the tremendous amount of data generated by mass spectrometers to deliver relevant biological information. Thus, powerful mass spectrometry-based proteomics technologies now provide unprecedented insights into the composition, structure, function, and control of the proteome, shedding light on complex biological processes and phenotypes. 

This Special issue of Proteomes on “Mass Spectrometry-Based Quantitative Proteomics” welcomes submissions of original research or review articles aiming at deciphering mechanistic and quantitative physiological processes with the use of proteomics tools. Authors are welcome to submit contributions focusing on the dynamic changes of protein expression in their native and modified forms, analyzed by combining several “omics” approaches in contrasted physiological or stress situations as well as by applying technical advances in the proteomic field. Multidisciplinary articles dealing with model or non-model organisms in all areas of plant and animal biology, plant and animal health, as well as abiotic and biotic stress responses will be accepted for this Special Issue.  

Dr. Uma K. Aryal
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Proteomes is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Mass spectrometry
  • Global and targeted proteome
  • Phosphoproteome
  • Glycoproteome
  • SUMOylome
  • Acetylome
  • Secretome
  • Plasma and serum proteome
  • Plant proteome
  • Microbial proteome
  • Native protein complexes
  • Protein–protein interactions
  • Spatial or organelle proteome
  • Inflammation and cell signaling
  • Bioinformatics
  • Omics data integration
  • Proteomics and human health
  • Proteome dynamics

Published Papers (4 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

13 pages, 1396 KiB  
Article
Comparison of Different Label-Free Techniques for the Semi-Absolute Quantification of Protein Abundance
Proteomes 2022, 10(1), 2; https://doi.org/10.3390/proteomes10010002 - 07 Jan 2022
Cited by 10 | Viewed by 3493
Abstract
In proteomics, it is essential to quantify proteins in absolute terms if we wish to compare results among studies and integrate high-throughput biological data into genome-scale metabolic models. While labeling target peptides with stable isotopes allow protein abundance to be accurately quantified, the [...] Read more.
In proteomics, it is essential to quantify proteins in absolute terms if we wish to compare results among studies and integrate high-throughput biological data into genome-scale metabolic models. While labeling target peptides with stable isotopes allow protein abundance to be accurately quantified, the utility of this technique is constrained by the low number of quantifiable proteins that it yields. Recently, label-free shotgun proteomics has become the “gold standard” for carrying out global assessments of biological samples containing thousands of proteins. However, this tool must be further improved if we wish to accurately quantify absolute levels of proteins. Here, we used different label-free quantification techniques to estimate absolute protein abundance in the model yeast Saccharomyces cerevisiae. More specifically, we evaluated the performance of seven different quantification methods, based either on spectral counting (SC) or extracted-ion chromatogram (XIC), which were applied to samples from five different proteome backgrounds. We also compared the accuracy and reproducibility of two strategies for transforming relative abundance into absolute abundance: a UPS2-based strategy and the total protein approach (TPA). This study mentions technical challenges related to UPS2 use and proposes ways of addressing them, including utilizing a smaller, more highly optimized amount of UPS2. Overall, three SC-based methods (PAI, SAF, and NSAF) yielded the best results because they struck a good balance between experimental performance and protein quantification. Full article
(This article belongs to the Special Issue Mass Spectrometry-Based Quantitative Proteomics)
Show Figures

Figure 1

13 pages, 1446 KiB  
Article
Impact of Exposure to Chronic Light–Dark Phase Shifting Circadian Rhythm Disruption on Muscle Proteome in Periparturient Dairy Cows
Proteomes 2021, 9(3), 35; https://doi.org/10.3390/proteomes9030035 - 29 Jul 2021
Cited by 3 | Viewed by 3224
Abstract
Muscle tissue serves as a key nutrient reservoir that dairy cows utilize to meet energy and amino acid requirements for fetal growth and milk production. Circadian clocks act as homeostatic regulators so that organisms can anticipate regular environmental changes. The objective of this [...] Read more.
Muscle tissue serves as a key nutrient reservoir that dairy cows utilize to meet energy and amino acid requirements for fetal growth and milk production. Circadian clocks act as homeostatic regulators so that organisms can anticipate regular environmental changes. The objective of this study was to use liquid chromatography tandem mass spectrometry (LC-MS/MS) to determine how chronic circadian disruption in late gestation affected the muscle tissue proteome. At five weeks before expected calving (BEC), multiparous Holstein cows were assigned to either a control (CON, n = 8) or a 6 h forward phase shift (PS, n = 8) of the light–dark cycle every 3 days. At calving, all animals were exposed to CON light–dark cycles. Muscle biopsies were collected from longissimus dorsi muscles at 21 days BEC and at 21 days postpartum (PP). At p < 0.1, 116 and 121 proteins were differentially abundant between PS and CON at 21 days BEC and 21 days PP, respectively. These proteins regulate beta oxidation and glycolysis. Between pregnancy and lactation, 134 and 145 proteins were differentially abundant in CON and PS cows, respectively (p < 0.1). At both timepoints, PS cows exhibited an oxidative stress signature. Thus, dairy cattle management strategies that minimize circadian disruptions may ensure optimal health and production performance. Full article
(This article belongs to the Special Issue Mass Spectrometry-Based Quantitative Proteomics)
Show Figures

Figure 1

15 pages, 1033 KiB  
Article
A Novel Urinary Proteomics Classifier for Non-Invasive Evaluation of Interstitial Fibrosis and Tubular Atrophy in Chronic Kidney Disease
Proteomes 2021, 9(3), 32; https://doi.org/10.3390/proteomes9030032 - 13 Jul 2021
Cited by 20 | Viewed by 3635
Abstract
Non-invasive urinary peptide biomarkers are able to detect and predict chronic kidney disease (CKD). Moreover, specific urinary peptides enable discrimination of different CKD etiologies and offer an interesting alternative to invasive kidney biopsy, which cannot always be performed. The aim of this study [...] Read more.
Non-invasive urinary peptide biomarkers are able to detect and predict chronic kidney disease (CKD). Moreover, specific urinary peptides enable discrimination of different CKD etiologies and offer an interesting alternative to invasive kidney biopsy, which cannot always be performed. The aim of this study was to define a urinary peptide classifier using mass spectrometry technology to predict the degree of renal interstitial fibrosis and tubular atrophy (IFTA) in CKD patients. The urinary peptide profiles of 435 patients enrolled in this study were analyzed using capillary electrophoresis coupled with mass spectrometry (CE-MS). Urine samples were collected on the day of the diagnostic kidney biopsy. The proteomics data were divided into a training (n = 200) and a test (n = 235) cohort. The fibrosis group was defined as IFTA ≥ 15% and no fibrosis as IFTA < 10%. Statistical comparison of the mass spectrometry data enabled identification of 29 urinary peptides with differential occurrence in samples with and without fibrosis. Several collagen fragments and peptide fragments of fetuin-A and others were combined into a peptidomic classifier. The classifier separated fibrosis from non-fibrosis patients in an independent test set (n = 186) with area under the curve (AUC) of 0.84 (95% CI: 0.779 to 0.889). A significant correlation of IFTA and FPP_BH29 scores could be observed Rho = 0.5, p < 0.0001. We identified a peptidomic classifier for renal fibrosis containing 29 peptide fragments corresponding to 13 different proteins. Urinary proteomics analysis can serve as a non-invasive tool to evaluate the degree of renal fibrosis, in contrast to kidney biopsy, which allows repeated measurements during the disease course. Full article
(This article belongs to the Special Issue Mass Spectrometry-Based Quantitative Proteomics)
Show Figures

Figure 1

14 pages, 4644 KiB  
Article
A Novel Proximity Biotinylation Assay Based on the Self-Associating Split GFP1–10/11
Proteomes 2020, 8(4), 37; https://doi.org/10.3390/proteomes8040037 - 02 Dec 2020
Cited by 2 | Viewed by 3249
Abstract
Proximity biotinylation was developed to detect physiologically relevant protein–protein interactions in living cells. In this method, the protein of interest is tagged with a promiscuous biotin ligase, such as BioID or BioID2, which produces activated biotin that reacts with nearby proteins; these proteins [...] Read more.
Proximity biotinylation was developed to detect physiologically relevant protein–protein interactions in living cells. In this method, the protein of interest is tagged with a promiscuous biotin ligase, such as BioID or BioID2, which produces activated biotin that reacts with nearby proteins; these proteins can subsequently be purified and identified by mass spectrometry. Here we report a novel modification of this technique by combining it with a self-associating split-GFP system in which we exploit the high-affinity interaction between GFP1–10 and GFP11 to recruit BioID2 to the protein of interest. As a test case, we fused GFP11 to clathrin light chain (CLTB) and BioID2 to GFP1–10. Co-expression of GFP11-CLTB and BioID2-GFP1–10 yielded a green fluorescent complex that co-localized with clathrin heavy chain. To facilitate removal of non-specifically biotinylated proteins, we generated an inducible cell line expressing BioID2-GFP1–10. Proximity biotinylation in this cell line with GFP11-CLTB yielded a higher percentage of biologically relevant interactions than direct fusion of BioID2 to CLTB. Thus, this system can be used to monitor expression and localization of BioID bait proteins and to identify protein–protein interactions. Full article
(This article belongs to the Special Issue Mass Spectrometry-Based Quantitative Proteomics)
Show Figures

Figure 1

Back to TopTop