scholarly journals Obesity Proteomics: An Update on the Strategies and Tools Employed in the Study of Human Obesity

2018 ◽  
Vol 7 (3) ◽  
pp. 27 ◽  
Author(s):  
Afshan Masood ◽  
Hicham Benabdelkamel ◽  
Assim Alfadda
Keyword(s):  
Mass Spectrometry ◽  
High Throughput ◽  
Large Scale ◽  
Protein Identification ◽  
Biochemical Characterization ◽  
Biological Fluids ◽  
Protein Composition ◽  
Cellular Protein ◽  
Human Obesity ◽  
Two Dimensional Gel Electrophoresis

Proteomics has become one of the most important disciplines for characterizing cellular protein composition, building functional linkages between protein molecules, and providing insight into the mechanisms of biological processes in a high-throughput manner. Mass spectrometry-based proteomic advances have made it possible to study human diseases, including obesity, through the identification and biochemical characterization of alterations in proteins that are associated with it and its comorbidities. A sizeable number of proteomic studies have used the combination of large-scale separation techniques, such as high-resolution two-dimensional gel electrophoresis or liquid chromatography in combination with mass spectrometry, for high-throughput protein identification. These studies have applied proteomics to comprehensive biochemical profiling and comparison studies while using different tissues and biological fluids from patients to demonstrate the physiological or pathological adaptations within their proteomes. Further investigations into these proteome-wide alterations will enable us to not only understand the disease pathophysiology, but also to determine signature proteins that can serve as biomarkers for obesity and related diseases. This review examines the different proteomic techniques used to study human obesity and discusses its successful applications along with its technical limitations.

Data Mining in Protein Identification by Tandem Mass Spectrometry

2011 ◽  
pp. 472-478
Author(s):  
Haipeng Wang
Keyword(s):  
Mass Spectrometry ◽  
Data Mining ◽  
Tandem Mass Spectrometry ◽  
Large Scale ◽  
Protein Identification ◽  
Peptide Fragmentation ◽  
Tandem Mass ◽  
Fragmentation Pattern ◽  
Post Translational Modification ◽  
Challenges And Opportunities

Protein identification (sequencing) by tandem mass spectrometry is a fundamental technique for proteomics which studies structures and functions of proteins in large scale and acts as a complement to genomics. Analysis and interpretation of vast amounts of spectral data generated in proteomics experiments present unprecedented challenges and opportunities for data mining in areas such as data preprocessing, peptide-spectrum matching, results validation, peptide fragmentation pattern discovery and modeling, and post-translational modification (PTM) analysis. This article introduces the basic concepts and terms of protein identification and briefly reviews the state-of-the-art relevant data mining applications. It also outlines challenges and future potential hot spots in this field.

scholarly journals High-Throughput Stool Metaproteomics: Method and Application to Human Specimens

mSystems ◽  
2020 ◽  
Vol 5 (3) ◽  
Author(s):  
Carlos G. Gonzalez ◽  
Hannah C. Wastyk ◽  
Madeline Topf ◽  
Christopher D. Gardner ◽  
Justin L. Sonnenburg ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
High Throughput ◽  
Clinical Studies ◽  
Large Scale ◽  
Dietary Intervention ◽  
Negative Impact ◽  
Mass Spectrometry Analysis ◽  
Careful Study ◽  
Stool Samples ◽  
Study Participants

ABSTRACT Stool-based proteomics is capable of significantly augmenting our understanding of host-gut microbe interactions. However, compared to competing technologies, such as metagenomics and 16S rRNA sequencing, it is underutilized due to its low throughput and the negative impact sample contaminants can have on highly sensitive mass spectrometry equipment. Here, we present a new stool proteomic processing pipeline that addresses these shortcomings in a highly reproducible and quantitative manner. Using this method, 290 samples from a dietary intervention study were processed in approximately 1.5 weeks, largely done by a single researcher. These data indicated a subtle but distinct monotonic increase in the number of significantly altered proteins between study participants on fiber- or fermented food-enriched diets. Lastly, we were able to classify study participants based on their diet-altered proteomic profiles and demonstrated that classification accuracies of up to 89% could be achieved by increasing the number of subjects considered. Taken together, this study represents the first high-throughput proteomic method for processing stool samples in a technically reproducible manner and has the potential to elevate stool-based proteomics as an essential tool for profiling host-gut microbiome interactions in a clinical setting. IMPORTANCE Widely available technologies based on DNA sequencing have been used to describe the kinds of microbes that might correlate with health and disease. However, mechanistic insights might be best achieved through careful study of the dynamic proteins at the interface between the foods we eat, our microbes, and ourselves. Mass spectrometry-based proteomics has the potential to revolutionize our understanding of this complex system, but its application to clinical studies has been hampered by low-throughput and laborious experimentation pipelines. In response, we developed SHT-Pro, the first high-throughput pipeline designed to rapidly handle large stool sample sets. With it, a single researcher can process over one hundred stool samples per week for mass spectrometry analysis, conservatively approximately 10× to 100× faster than previous methods, depending on whether isobaric labeling is used or not. Since SHT-Pro is fairly simple to implement using commercially available reagents, it should be easily adaptable to large-scale clinical studies.

N-terminal Cyclization of Peptides in Large-scale Protein Identification Based on Biological Mass Spectrometry

2009 ◽  
Vol 37 (7) ◽  
pp. 950-954
Author(s):  
Zhuang LU ◽  
Li-Yan ZHAO ◽  
Yang-Jun ZHANG ◽  
Yun CAI ◽  
Yu-Lin DENG ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Large Scale ◽  
Protein Identification ◽  
Biological Mass Spectrometry

scholarly journals Ultrafast and Reproducible Proteomics from Small Amounts of Heart Tissue Enabled by Azo and timsTOF Pro

2021 ◽  
Author(s):  
Timothy J Aballo ◽  
David S Roberts ◽  
Jake A Melby ◽  
Kevin M Buck ◽  
Kyle A Brown ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Large Scale ◽  
Protein Identification ◽  
Heart Tissue ◽  
Tryptic Digestion ◽  
Bottom Up ◽  
Preparation Methods ◽  
Liquid Chromatography Tandem Mass ◽  
And Function ◽  
Identification And Quantification

Global bottom-up mass spectrometry (MS)-based proteomics is widely used for protein identification and quantification to achieve a comprehensive understanding of the composition, structure, and function of the proteome. However, traditional sample preparation methods are time-consuming, typically including overnight tryptic digestion, extensive sample clean-up to remove MS-incompatible surfactants, and offline sample fractionation to reduce proteome complexity prior to online liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis. Thus, there is a need for a fast, robust, and reproducible method for protein identification and quantification from complex proteomes. Herein, we developed an ultrafast bottom-up proteomics method enabled by Azo, a photocleavable, MS-compatible surfactant that effectively solubilizes proteins and promotes rapid tryptic digestion, combined with the Bruker timsTOF Pro, which enables deeper proteome coverage through trapped ion mobility spectrometry (TIMS) and parallel accumulation-serial fragmentation (PASEF) of peptides. We applied this method to analyze the complex human cardiac proteome and identified nearly 4,000 protein groups from as little as 1 mg of human heart tissue in a single one-dimensional LC-TIMS-MS/MS run with high reproducibility. Overall, we anticipate this ultrafast, robust, and reproducible bottom-up method empowered by both Azo and the timsTOF Pro will be generally applicable and greatly accelerate the throughput of large-scale quantitative proteomic studies. Raw data are available via the MassIVE repository with identifier MSV000087476.

185 HIGH-THROUGHPUT PROTEOMIC ASSESSMENT OF FROZEN - THAWED BOAR SPERMATOZOA

2011 ◽  
Vol 23 (1) ◽  
pp. 194 ◽  
Author(s):  
J. M. Feugang ◽  
K. Pendarvis ◽  
M. Crenshaw ◽  
S. T. Willard ◽  
P. L. Ryan
Keyword(s):  
High Throughput ◽  
Protein Identification ◽  
Molecular Mechanisms ◽  
Protein Composition ◽  
Differentially Expressed ◽  
Sperm Function ◽  
Total Proteins ◽  
Semen Storage ◽  
Discontinuous Percoll Gradient ◽  
Boar Spermatozoa

Cryopreservation is a tool of choice for seedstock constitution of genetically superior males. Its successful application in swine AI industries is limited because of the poor freezability of boar semen. Indeed, a subset of boars exists that can be successfully frozen–thawed for AI, whereas another group appears highly cryosusceptible, and therefore unusable for long-term semen storage. The reasons for such differences are unknown, and the full characterisation of the protein composition of boar spermatozoa will help determine potential cryosensitive proteins. Here, we performed high-throughput proteomic analyses of boar spermatozoa and compared the proteome profiles of ‘good’ and ‘poor’ freezer boars. Eight commercially proven fertile boars were selected based on conception rates after AI using fresh semen. Semen from 3 independent ejaculations was collected from 4 good and 4 poor freezer boars and frozen in 5-mL straws for the study. Frozen–thawed semen was diluted in the thawing solution and centrifuged through a discontinuous Percoll gradient (90/45) to remove seminal plasma, freezing extender, somatic cells, and dead sperm cells. Purified motile spermatozoa were washed 3 times with cold PBS and pooled in pellets of 3 × 108 spermatozoa per boar. Protein samples were digested with trypsin and prepared for LC-MS/MS analysis. Peptides yielding probability scores lower than 0.05 were subjected to protein identification, and the significance of differentially expressed protein was fixed at P < 0.05. More than 3000 proteins were identified in each group of spermatozoa. Proportions of 63 and 61% total proteins were exclusively detected in good and poor freezer boars, respectively. Many of the identified proteins were related to different cellular compartments and important molecular mechanisms related to sperm function, such as cell death regulation, macromolecule metabolism, and energy-related pathways. Approximately 5% of total proteins, representing 163 to 182 individual proteins, were detected at higher levels in both semen groups. Half of these highly abundant proteins were differentially expressed between good and poor freezer boars. Only 8 appeared partially annotated and 11 were predicted. The remaining list of fully annotated proteins included candidates such as transferrin, albumin, and fascin3, which were significantly (P < 0.05) abundant in good freezer boars, and outer dense fibre (ODF) 2, protamine (PRM) 2, and calmodulin (CALM) 1, which were significantly (P < 0.05) abundant in poor freezer boars. Overall, the results indicate that boar spermatozoa contain large amount of proteins whose susceptibility to cryopreservation and implications for sperm function are still to be characterised. Our findings are particularly important for 1) the search for potential biomarkers of semen freezability, and 2) improvement of semen freezing-thawing extenders for boars and other species with similar issues. Funded by USDA-ARS Special Initiative No. 58-6402-3-0120 and Mississippi Agriculture and Forestry Experiment Station.

scholarly journals Identification of an Arginase II Inhibitor via RapidFire Mass Spectrometry Combined with Hydrophilic Interaction Chromatography

2018 ◽  
Vol 24 (4) ◽  
pp. 457-465 ◽  
Author(s):  
Wataru Asano ◽  
Yu Takahashi ◽  
Motoaki Kawano ◽  
Yoshiji Hantani
Keyword(s):  
Mass Spectrometry ◽  
High Throughput ◽  
High Throughput Screening ◽  
Large Scale ◽  
Hydrophilic Interaction Chromatography ◽  
Label Free ◽  
Hydrophilic Interaction ◽  
High Concentration ◽  
Allosteric Site ◽  
Arginase Ii

Peripheral arterial disease (PAD) is an occlusive disease that can lead to atherosclerosis. The involvement of arginase II (Arg II) in PAD progression has been proposed. However, no promising drugs targeting Arg II have been developed to date for the treatment of PAD. In this study, we established a method for detecting the activity of Arg II via high-throughput label-free RapidFire mass spectrometry using hydrophilic interaction chromatography, which enables the direct measurement of l-ornithine produced by Arg II. This approach facilitated a robust high-concentration screening of fragment compounds and the identification of a fragment that inhibits the activity of Arg II. We further confirmed binding of the fragment to the potential allosteric site of Arg II using a surface plasmon resonance assay. We concluded that the identified fragment is a promising compound that may lead to novel drugs to treat PAD, and our method for detecting the activity of Arg II can be applied to large-scale high-throughput screening to identify other structural types of Arg II inhibitors.

Sign in / Sign up

Export Citation Format

Share Document