To see the other types of publications on this topic, follow the link: Proteomics Peptides Bioinformatics. Tandem mass spectrometry.
Journal articles on the topic 'Proteomics Peptides Bioinformatics. Tandem mass spectrometry'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 journal articles for your research on the topic 'Proteomics Peptides Bioinformatics. Tandem mass spectrometry.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.
1
Choi, Seunghyuk, and Eunok Paek. "MutCombinator: identification of mutated peptides allowing combinatorial mutations using nucleotide-based graph search." Bioinformatics 36, Supplement_1 (July 1, 2020): i203—i209. http://dx.doi.org/10.1093/bioinformatics/btaa504.
Full textAbstract:
Abstract Motivation Proteogenomics has proven its utility by integrating genomics and proteomics. Typical approaches use data from next-generation sequencing to infer proteins expressed. A sample-specific protein sequence database is often adopted to identify novel peptides from matched mass spectrometry-based proteomics; nevertheless, there is no software that can practically identify all possible forms of mutated peptides suggested by various genomic information sources. Results We propose MutCombinator, which enables us to practically identify mutated peptides from tandem mass spectra allowing combinatorial mutations during the database search. It uses an upgraded version of a variant graph, keeping track of frame information. The variant graph is indexed by nine nucleotides for fast access. Using MutCombinator, we could identify more mutated peptides than previous methods, because combinations of point mutations are considered and also because it can be practically applied together with a large mutation database such as COSMIC. Furthermore, MutCombinator supports in-frame search for coding regions and three-frame search for non-coding regions. Availability and implementation https://prix.hanyang.ac.kr/download/mutcombinator.jsp. Supplementary information Supplementary data are available at Bioinformatics online.
2
Sulimov, Pavel, Anastasia Voronkova, and Attila Kertész-Farkas. "Annotation of tandem mass spectrometry data using stochastic neural networks in shotgun proteomics." Bioinformatics 36, no. 12 (March 24, 2020): 3781–87. http://dx.doi.org/10.1093/bioinformatics/btaa206.
Full textAbstract:
Abstract Motivation The discrimination ability of score functions to separate correct from incorrect peptide-spectrum-matches in database-searching-based spectrum identification is hindered by many superfluous peaks belonging to unexpected fragmentation ions or by the lacking peaks of anticipated fragmentation ions. Results Here, we present a new method, called BoltzMatch, to learn score functions using a particular stochastic neural networks, called restricted Boltzmann machines, in order to enhance their discrimination ability. BoltzMatch learns chemically explainable patterns among peak pairs in the spectrum data, and it can augment peaks depending on their semantic context or even reconstruct lacking peaks of expected ions during its internal scoring mechanism. As a result, BoltzMatch achieved 50% and 33% more annotations on high- and low-resolution MS2 data than XCorr at a 0.1% false discovery rate in our benchmark; conversely, XCorr yielded the same number of spectrum annotations as BoltzMatch, albeit with 4–6 times more errors. In addition, BoltzMatch alone does yield 14% more annotations than Prosit (which runs with Percolator), and BoltzMatch with Percolator yields 32% more annotations than Prosit at 0.1% FDR level in our benchmark. Availability and implementation BoltzMatch is freely available at: https://github.com/kfattila/BoltzMatch. Contact akerteszfarkas@hse.ru Supporting information Supplementary data are available at Bioinformatics online.
3
He, Qianqian, Xinmei Fang, Tianhui Zhu, Shan Han, Hanmingyue Zhu, and Shujiang Li. "Differential Proteomics Based on TMT and PRM Reveal the Resistance Response of Bambusa pervariabilis × Dendrocalamopisis grandis Induced by AP-Toxin." Metabolites 9, no. 8 (August 10, 2019): 166. http://dx.doi.org/10.3390/metabo9080166.
Full textAbstract:
Bambusa pervariabilis McClure × Dendrocalamopsis grandis (Q.H.Dai & X.l.Tao ex Keng f.) Ohrnb. blight is a widespread and dangerous forest fungus disease, and has been listed as a supplementary object of forest phytosanitary measures. In order to study the control of B. pervariabilis × D. grandis blight, this experiment was carried out. In this work, a toxin purified from the pathogen Arthrinium phaeospermum (Corda) Elli, which causes blight in B. pervariabilis × D. grandis, with homologous heterogeneity, was used as an inducer to increase resistance to B. pervariabilis × D. grandis. A functional analysis of the differentially expressed proteins after induction using a tandem mass tag labeling technique was combined with mass spectrometry and liquid chromatography mass spectrometry in order to effectively screen for the proteins related to the resistance of B. pervariabilis × D. grandis to blight. After peptide labeling, a total of 3320 unique peptides and 1791 quantitative proteins were obtained by liquid chromatography mass spectrometry analysis. Annotation and enrichment analysis of these peptides and proteins using the Gene ontology and Kyoto Encyclopedia of Genes and Genomes databases with bioinformatics software show that the differentially expressed protein functional annotation items are mainly concentrated on biological processes and cell components. Several pathways that are prominent in the Kyoto Encyclopedia of Genes and Genomes annotation and enrichment include metabolic pathways, the citrate cycle, and phenylpropanoid biosynthesis. In the Protein-protein interaction networks four differentially expressed proteins-sucrose synthase, adenosine triphosphate-citrate synthase beta chain protein 1, peroxidase, and phenylalanine ammonia-lyase significantly interact with multiple proteins and significantly enrich metabolic pathways. To verify the results of tandem mass tag, the candidate proteins were further verified by parallel reaction monitoring, and the results were consistent with the tandem mass tag data analysis results. It is confirmed that the data obtained by tandem mass tag technology are reliable. Therefore, the differentially expressed proteins and signaling pathways discovered here is the primary concern for subsequent disease resistance studies.
4
Karlsson, Roger, Annika Thorsell, Margarita Gomila, Francisco Salvà-Serra, Hedvig E. Jakobsson, Lucia Gonzales-Siles, Daniel Jaén-Luchoro, et al. "Discovery of Species-unique Peptide Biomarkers of Bacterial Pathogens by Tandem Mass Spectrometry-based Proteotyping." Molecular & Cellular Proteomics 19, no. 3 (January 15, 2020): 518–28. http://dx.doi.org/10.1074/mcp.ra119.001667.
Full textAbstract:
Mass spectrometry (MS) and proteomics offer comprehensive characterization and identification of microorganisms and discovery of protein biomarkers that are applicable for diagnostics of infectious diseases. The use of biomarkers for diagnostics is widely applied in the clinic and the use of peptide biomarkers is increasingly being investigated for applications in the clinical laboratory. Respiratory-tract infections are a predominant cause for medical treatment, although, clinical assessments and standard clinical laboratory protocols are time-consuming and often inadequate for reliable diagnoses. Novel methods, preferably applied directly to clinical samples, excluding cultivation steps, are needed to improve diagnostics of infectious diseases, provide adequate treatment and reduce the use of antibiotics and associated development of antibiotic resistance. This study applied nano-liquid chromatography (LC) coupled with tandem MS, with a bioinformatics pipeline and an in-house database of curated high-quality reference genome sequences to identify species-unique peptides as potential biomarkers for four bacterial pathogens commonly found in respiratory tract infections (RTIs): Staphylococcus aureus; Moraxella catarrhalis; Haemophilus influenzae and Streptococcus pneumoniae. The species-unique peptides were initially identified in pure cultures of bacterial reference strains, reflecting the genomic variation in the four species and, furthermore, in clinical respiratory tract samples, without prior cultivation, elucidating proteins expressed in clinical conditions of infection. For each of the four bacterial pathogens, the peptide biomarker candidates most predominantly found in clinical samples, are presented. Data are available via ProteomeXchange with identifier PXD014522. As proof-of-principle, the most promising species-unique peptides were applied in targeted tandem MS-analyses of clinical samples and their relevance for identifications of the pathogens, i.e. proteotyping, was validated, thus demonstrating their potential as peptide biomarker candidates for diagnostics of infectious diseases.
5
Golenko, Ye, A. Ismailova, and Ye Rais. "PROTEIN IDENTIFICATION USING SEQUENCE DATABASES." Scientific Journal of Astana IT University, no. 4 (December 25, 2020): 14–23. http://dx.doi.org/10.37943/aitu.2020.91.98.002.
Full textAbstract:
The bottom-up proteomics approach (also known as the shotgun approach), based on the digestion of proteins in peptides and their sequencing using tandem mass spectrometry (MS/MS), has become widespread. The identification of peptides from the obtained MS/MS data is most often done using available sequence databases. In this paper, we present a detailed overview of the peptide identification workflow and description of the main protein bioinformatics databases. Choosing the correct search parameters and the sequence database is essential to the success of this method, and we pay special attention to the practical aspects of searching for efficient analysis of MS/MS spectra. We also consider possible reasons why database search tools cannot find the correct sequence for some MS/MS spectra, and highlight the issues of misidentification that can significantly reduce the value of published data. To help assess the assignment of peptides to MS/MS spectra, we will look at the scoring algorithms that are used in the most popular database search tools. We also analyze statistical methods and computational tools for validating peptide compliance with MS/MS data. The final part describes the process of determining the identity of protein samples from a list of peptide identifications and discusses the limitations of bottom-up proteomics
6
Jabbour, Rabih E., Samir V. Deshpande, Mary Margaret Wade, Michael F. Stanford, Charles H. Wick, Alan W. Zulich, Evan W. Skowronski, and A. Peter Snyder. "Double-Blind Characterization of Non-Genome-Sequenced Bacteria by Mass Spectrometry-Based Proteomics." Applied and Environmental Microbiology 76, no. 11 (April 2, 2010): 3637–44. http://dx.doi.org/10.1128/aem.00055-10.
Full textAbstract:
ABSTRACT Due to the possibility of a biothreat attack on civilian or military installations, a need exists for technologies that can detect and accurately identify pathogens in a near-real-time approach. One technology potentially capable of meeting these needs is a high-throughput mass spectrometry (MS)-based proteomic approach. This approach utilizes the knowledge of amino acid sequences of peptides derived from the proteolysis of proteins as a basis for reliable bacterial identification. To evaluate this approach, the tryptic digest peptides generated from double-blind biological samples containing either a single bacterium or a mixture of bacteria were analyzed using liquid chromatography-tandem mass spectrometry. Bioinformatic tools that provide bacterial classification were used to evaluate the proteomic approach. Results showed that bacteria in all of the double-blind samples were accurately identified with no false-positive assignment. The MS proteomic approach showed strain-level discrimination for the various bacteria employed. The approach also characterized double-blind bacterial samples to the respective genus, species, and strain levels when the experimental organism was not in the database due to its genome not having been sequenced. One experimental sample did not have its genome sequenced, and the peptide experimental record was added to the virtual bacterial proteome database. A replicate analysis identified the sample to the peptide experimental record stored in the database. The MS proteomic approach proved capable of identifying and classifying organisms within a microbial mixture.
7
Hu, Alex, William S. Noble, and Alejandro Wolf-Yadlin. "Technical advances in proteomics: new developments in data-independent acquisition." F1000Research 5 (March 31, 2016): 419. http://dx.doi.org/10.12688/f1000research.7042.1.
Full textAbstract:
The ultimate aim of proteomics is to fully identify and quantify the entire complement of proteins and post-translational modifications in biological samples of interest. For the last 15 years, liquid chromatography-tandem mass spectrometry (LC-MS/MS) in data-dependent acquisition (DDA) mode has been the standard for proteomics when sampling breadth and discovery were the main objectives; multiple reaction monitoring (MRM) LC-MS/MS has been the standard for targeted proteomics when precise quantification, reproducibility, and validation were the main objectives. Recently, improvements in mass spectrometer design and bioinformatics algorithms have resulted in the rediscovery and development of another sampling method: data-independent acquisition (DIA). DIA comprehensively and repeatedly samples every peptide in a protein digest, producing a complex set of mass spectra that is difficult to interpret without external spectral libraries. Currently, DIA approaches the identification breadth of DDA while achieving the reproducible quantification characteristic of MRM or its newest version, parallel reaction monitoring (PRM). In comparative de novo identification and quantification studies in human cell lysates, DIA identified up to 89% of the proteins detected in a comparable DDA experiment while providing reproducible quantification of over 85% of them. DIA analysis aided by spectral libraries derived from prior DIA experiments or auxiliary DDA data produces identification and quantification as reproducible and precise as that achieved by MRM/PRM, except on low‑abundance peptides that are obscured by stronger signals. DIA is still a work in progress toward the goal of sensitive, reproducible, and precise quantification without external spectral libraries. New software tools applied to DIA analysis have to deal with deconvolution of complex spectra as well as proper filtering of false positives and false negatives. However, the future outlook is positive, and various researchers are working on novel bioinformatics techniques to address these issues and increase the reproducibility, fidelity, and identification breadth of DIA.
8
Yang, Hao, Hao Chi, Wen-Feng Zeng, Wen-Jing Zhou, and Si-Min He. "pNovo 3: precise de novo peptide sequencing using a learning-to-rank framework." Bioinformatics 35, no. 14 (July 2019): i183—i190. http://dx.doi.org/10.1093/bioinformatics/btz366.
Full textAbstract:
AbstractMotivationDe novo peptide sequencing based on tandem mass spectrometry data is the key technology of shotgun proteomics for identifying peptides without any database and assembling unknown proteins. However, owing to the low ion coverage in tandem mass spectra, the order of certain consecutive amino acids cannot be determined if all of their supporting fragment ions are missing, which results in the low precision of de novo sequencing.ResultsIn order to solve this problem, we developed pNovo 3, which used a learning-to-rank framework to distinguish similar peptide candidates for each spectrum. Three metrics for measuring the similarity between each experimental spectrum and its corresponding theoretical spectrum were used as important features, in which the theoretical spectra can be precisely predicted by the pDeep algorithm using deep learning. On seven benchmark datasets from six diverse species, pNovo 3 recalled 29–102% more correct spectra, and the precision was 11–89% higher than three other state-of-the-art de novo sequencing algorithms. Furthermore, compared with the newly developed DeepNovo, which also used the deep learning approach, pNovo 3 still identified 21–50% more spectra on the nine datasets used in the study of DeepNovo. In summary, the deep learning and learning-to-rank techniques implemented in pNovo 3 significantly improve the precision of de novo sequencing, and such machine learning framework is worth extending to other related research fields to distinguish the similar sequences.Availability and implementationpNovo 3 can be freely downloaded from http://pfind.ict.ac.cn/software/pNovo/index.html.Supplementary informationSupplementary data are available at Bioinformatics online.
9
Li, Chuang, Kenli Li, Tao Chen, Yunping Zhu, and Qiang He. "SW-Tandem: a highly efficient tool for large-scale peptide identification with parallel spectrum dot product on Sunway TaihuLight." Bioinformatics 35, no. 19 (March 1, 2019): 3861–63. http://dx.doi.org/10.1093/bioinformatics/btz147.
Full textAbstract:
Abstract Summary Tandem mass spectrometry based database searching is a widely acknowledged and adopted method that identifies peptide sequence in shotgun proteomics. However, database searching is extremely computationally expensive, which can take days even weeks to process a large spectra dataset. To address this critical issue, this paper presents SW-Tandem, a new tool for large-scale peptide sequencing. SW-Tandem parallelizes the spectrum dot product scoring algorithm and leverages the advantages of Sunway TaihuLight, the No. 1 supercomputer in the world in 2017. Sunway TaihuLight is powered by the brand new many-core SW26010 processors and provides a peak computation performance greater than 100PFlops. To fully utilize the Sunway TaihuLights capacity, SW-Tandem employs three mechanisms to accelerate large-scale peptide identification, memory-access optimizations, double buffering and vectorization. The results of experiments conducted on multiple datasets demonstrate the performance of SW-Tandem against three state-of-the-art tools for peptide identification, including X!! Tandem, MR-Tandem and MSFragger. In addition, it shows high scalability in the experiments on extremely large datasets sized up to 12 GB. Availability and implementation SW-Tandem is an open source software tool implemented in C++. The source code and the parameter settings are available at https://github.com/Logic09/SW-Tandem. Supplementary information Supplementary data are available at Bioinformatics online.
10
Mastronunzio, J. E., Y. Huang, and D. R. Benson. "Diminished Exoproteome of Frankia spp. in Culture and Symbiosis." Applied and Environmental Microbiology 75, no. 21 (September 11, 2009): 6721–28. http://dx.doi.org/10.1128/aem.01559-09.
Full textAbstract:
ABSTRACT Frankia species are the most geographically widespread gram-positive plant symbionts, carrying out N2 fixation in root nodules of trees and woody shrubs called actinorhizal plants. Taking advantage of the sequencing of three Frankia genomes, proteomics techniques were used to investigate the population of extracellular proteins (the exoproteome) from Frankia, some of which potentially mediate host-microbe interactions. Initial two-dimensional sodium dodecyl sulfate-polyacrylamide gel electrophoresis analysis of culture supernatants indicated that cytoplasmic proteins appeared in supernatants as cells aged, likely because older hyphae lyse in this slow-growing filamentous actinomycete. Using liquid chromatography coupled to tandem mass spectrometry to identify peptides, 38 proteins were identified in the culture supernatant of Frankia sp. strain CcI3, but only three had predicted export signal peptides. In symbiotic cells, 42 signal peptide-containing proteins were detected from strain CcI3 in Casuarina cunninghamiana and Casuarina glauca root nodules, while 73 and 53 putative secreted proteins containing signal peptides were identified from Frankia strains in field-collected root nodules of Alnus incana and Elaeagnus angustifolia, respectively. Solute-binding proteins were the most commonly identified secreted proteins in symbiosis, particularly those predicted to bind branched-chain amino acids and peptides. These direct proteomics results complement a previous bioinformatics study that predicted few secreted hydrolytic enzymes in the Frankia proteome and provide direct evidence that the symbiosis succeeds partly, if not largely, because of a benign relationship.
11
Suvannasankha, Attaya, Colin D. Crean, Heather M. Sahm, Rafat Abonour, Sherif Farag, and Mu Wang. "A Potential Biomarker Panel of Multiple Myeloma Identified Using Label-Free Mass Spectrometry-Based Quantitative Proteomics." Blood 118, no. 21 (November 18, 2011): 2890. http://dx.doi.org/10.1182/blood.v118.21.2890.2890.
Full textAbstract:
Abstract Abstract 2890 Background: Multiple myeloma is an incurable and fatal hematologic malignancy. Recent gene microarray studies showed distinct gene expression profiles defining MM subgroups and their association with cytogenetic abnormalities and treatment outcome. However, aside from transcriptional control, a variety of post-transcriptional/post-translational modifications likely play an important role in regulating protein expression and function, and ultimately may prove informative for predicting tumor behavior. Objectives: We hypothesize that the protein profile in MM cells is different than normal plasma cells. Methodology: Normal plasma cells and myeloma cells were isolated using CD138 immune magnetic beads from bone marrow aspirates from healthy volunteers or patients with newly diagnosed MM, respectively. CD138+ cells were frozen and subsequently analyzed in one batch. Proteins were digested by trypsin. Tryptic peptides were injected onto an HPLC system and analyzed on a Thermo-Fisher LTQ mass spectrometer. Peptide identification and quantification were carried out using proprietary algorithms. Identified proteins were categorized into priority groups based on the quality of the peptide identification by tandem mass spectrometry. Proteins with significant changes in expression level were further analyzed by bioinformatics tools for the determination of the biological significance. Results: In the discovery phase of this study, 433 proteins were identified and their expression levels were quantitatively compared. 169 of these proteins demonstrated a significant difference between normal plasma cells and MM cells. Among the significantly changed proteins, 18 were identified and quantified with high confidence, and were therefore chosen for further validation. The identified proteins are known to be involved in the glycolysis/gluconeogenesis pathway, the oxidative phosphorylation pathway, cysteine metabolism and the pentose phosphate pathway. None of these proteins are known to be of prognostic value or being currently targeted for therapy in MM. A high-throughput LC/MS-based multiple-reaction-monitoring (MRM) assay for quantitative validation of these candidates with clinical samples is ongoing. To date, using the MRM assay, we were able to detect MRM peptides for 13 of the 18 targeted proteins in clinical samples. The quantification of these peptides will be further confirmed using a separate set of clinical samples. Conclusion: Significant differences in protein expression were observed between MM and normal plasma cells. The study presents an important step toward using proteomics as a tool to develop diagnostic and/or prognostic biomarkers in the clinical setting. However, both follow-up analytical and clinical validations are required before they can serve as disease-specific biomarkers. Disclosures: Abonour: Celgene: Membership on an entity's Board of Directors or advisory committees.
12
Li, Feng, Bai Yang, Yanan Liu, Tianying Tang, Cun Wang, Mei Li, Siyi Lv, et al. "Acupuncture Regulates Serum Differentially Expressed Proteins in Patients with Chronic Atrophic Gastritis: A Quantitative iTRAQ Proteomics Study." Evidence-Based Complementary and Alternative Medicine 2021 (June 14, 2021): 1–19. http://dx.doi.org/10.1155/2021/9962224.
Full textAbstract:
Objective. To identify differentially expressed proteins (DEPs) in sera of patients with chronic atrophic gastritis (CAG) using isobaric tags for relative and absolute quantitation (iTRAQ) and to explore acupuncture’s mechanism in CAG. Methods. Peripheral sera from 8 healthy volunteers (HC), 8 chronic nonatrophic gastritis (NAG) patients, 8 CAG patients, and 8 CAG patients who underwent acupuncture treatment (CAG + ACU) were collected followed by labeling with iTRAQ reagent for protein identification and quantification using two-dimensional liquid chromatography-tandem mass spectrometry (2D-LC-MS/MS). Representative DEPs were selected through bioinformatics, and proteins were verified by enzyme-linked immunosorbent assay (ELISA). Results. A total of 4,448 unique peptides were identified, corresponding to 816 nonredundant proteins. A 1.4-fold difference was used as the threshold. Compared with the HC group, 75 and 106 DEPs were identified from CAG and NAG groups, respectively. Compared with the CAG group, 110 and 66 DEPs were identified from the NAG and CAG + ACU groups, respectively. The DEPs were mainly involved in protein binding and the Notch signaling pathway-related proteins, and the upregulated proteins included actin-binding proteins (thymosin beta-4, tropomyosin-4, profilin-1, transgelin-2), while the downregulated proteins included Notch2 and Notch3. After acupuncture, the expression of these proteins in CAG patients was less differentiated from that in healthy people. The level of the above 6 proteins were verified by ELISA, and the results were similar to the results of iTRAQ analysis. Conclusions. Actin-binding proteins and Notch signaling pathway-related proteins were correlated with the development and progression of CAG and thus are potential diagnostic markers for CAG. Acupuncture may play a role in regulating actin-binding proteins and Notch signaling pathway-related proteins to play a therapeutic role in CAG.
13
Pilolli, Rosa, Agata Gadaleta, Luigia Di Stasio, Antonella Lamonaca, Elisabetta De Angelis, Domenica Nigro, Maria De Angelis, Gianfranco Mamone, and Linda Monaci. "A Comprehensive Peptidomic Approach to Characterize the Protein Profile of Selected Durum Wheat Genotypes: Implication for Coeliac Disease and Wheat Allergy." Nutrients 11, no. 10 (October 1, 2019): 2321. http://dx.doi.org/10.3390/nu11102321.
Full textAbstract:
The wheat varietal selection undertaken by breeders in recent decades has been tailored mainly to improve technological and productivity-related traits; however, the latter has resulted in a considerable impoverishment of the genetic diversity of wheat-based products available on the market. This pitfall has encouraged researchers to revalue the natural diversity of cultivated and non-cultivated wheat genotypes in light of their different toxic/immunogenic potential for celiac disease and wheat-allergic patients. In the present investigation, an advanced proteomic approach was designed for the global characterization of the protein profile of selected tetraploid wheat genotypes (Triticum turgidum). The approach combined proteins/peptides sequence information retrieved by specific enzymatic digestions (single and dual proteolytic enzymes) with protein digestibility information disclosed by means of in-vitro simulated human gastroduodenal digestion experiments. In both cases, the peptide pools were characterized by discovery analysis with liquid chromatography high-resolution tandem mass spectrometry, and specific amino acid sequences were identified via commercial software. The peptide list was screened for in silico toxicity/immunogenicity risk assessment, with the aid of various open-source bioinformatics tools for epitopes matching. Given the global information provided by the designed proteomic approach, the in silico risk assessment not only tackled toxicity implication for celiac disease patients, but also scouted for immunogenic sequences relevant for wheat allergic patients, achieving a comprehensive characterization of the protein profile of the selected genotypes. These latter were assessed to encrypt a variable number of toxic/immunogenic epitopes for celiac disease and wheat allergy, and as such they could represent convenient bases for breeding practices and for the development of new detoxification strategies.
14
Balkhi, Mumtaz Y., Mulu Geletu, Maximilian Christopeit, Hermann M. Behre, and Gerhard Behre. "Proteomics of Acute Myeloid Leukemia: Cytogenetic Risk Groups Differ Specifically in Their Proteome, Interactome and Posttranslational Protein Modifications." Blood 106, no. 11 (November 16, 2005): 1223. http://dx.doi.org/10.1182/blood.v106.11.1223.1223.
Full textAbstract:
Abstract Acute Myeloid Leukemia (AML) is characterized by specific cytogenetic aberrations which are strong determinants of prognostic outcome and therapeutic response. Because the clinical outcome in AML cytogenetic groups differs considerably, we hypothesized that cytogenetic risk groups of AML might differ specifically in their proteome, protein interaction pathways and posttranslational modifications (PTMs). Thus, we determined the proteome of 30 AML patients belonging to various cytogenetic groups based on two-dimensional gel electrophoresis and Nano LC coupled MALDI-TOF-TOF tandem mass spectrometry. We could identify substantial differences in the proteome, protein expression and peak pattern between cytogenetic risk groups of AML. The interactome analysis based on computational bioinformatics using Ingenuity analysis revealed major regulating networks: MAPK8 and MYC for complex aberrant karyotype AML, TP53 for t(8;21)-AML, TP53- MYC- PRKAC for 11q23-AML, JUN and MYC for inv(16)-AML. Most interestingly, peak explorer analysis revealed a modification of O-linked acetyl glucosamine of hnRNPH1 in AML patients with a 11q23 translocation, an acetylation of calreticulin in t(8;21) translocation AML, an increased intensity of dimethylated peptide of hnRNPA2/B1 in AML patients with translocations of t(8;21) and inv(16) in comparison to healthy bone marrow. We show for the first time that cytogenetic risk groups of AML differ specifically both in their proteome, interactome and PTMs. These findings lead to a new thinking about the pathogenesis of AML and has major therapeutic implications because PTMs are the primary drug targets.
15
Mereuta, Oana M., Surendra Dasari, Jason D. Theis, Julie A. Vrana, Karen L. Grogg, Morie A. Gertz, Steven R. Zeldenrust, et al. "Mass Spectrometry-Based Proteomics Reveals Distinct Immunoglobulin Light Chain Variable Region Usage In Systemic Versus Localized AL Amyloidosis." Blood 122, no. 21 (November 15, 2013): 3142. http://dx.doi.org/10.1182/blood.v122.21.3142.3142.
Full textAbstract:
Abstract Background Immunoglobulin light chain-associated amyloidosis (AL) is caused by deposition of immunoglobulin light chain molecules with unique, clonotypic variable (V) regions. Detection and identification of the V region, however, has been challenging due heterogeneity inherent in V regions. We developed a new method for detecting IGKV and IGLV region fragments in AL deposits using protein mass spectrometry and novel bioinformatics approach. We report distinct IGKV and IGLV usage in localized versus systemic AL. Methods Shotgun protein mass spectrometry on amyloid plaques was performed as previously described (Blood. 2009; 114: 4957-9). Peptide tandem mass spectra (MS/MS) were searched against a composite sequence database containing SwissProt's human complete proteome augmented with 1764 IG V region sequences obtained from ImMunoGeneTics database and a Mayo Clinic internal database. Reversed sequences were appended to the database for estimating identification false discovery rates (FDRs). Peptide identifications were processed with Scaffold software. Confident protein identifications (probability > 0.9) with at least one unique peptide identifications and five MS/MS matches were considered. Detected variable gene family (if any) with most number of peptide and spectral matches is considered to be present in the deposit. The method was first validated in 8 cases of AL amyloidosis with known IGKV and IGLV region sequences and then applied on 1238 systemic and 393 localized AL cases. Differences between groups were measured by generating hypergeometric p-values. Results In all 8 AL cases with known IGKV and IGLV region usage, gene family identified in the AL deposit via proteomics matched the gene family inferred from bone marrow plasma cells by Sanger sequencing of IGLC genes. Armed with this method, we analyzed the amyloid proteomics data from 1238 patients with systemic AL amyloidosis and 393 patients with localized AL amyloidosis. The anatomical site distribution in systemic cohort was 296 GI tract, 364 heart, 225 kidney, 81 liver and 272 fat aspirate; Localized cohort has 78 bladder, 158 lung and 157 skin cases. Figure 1 shows the normalized frequency of the variable gene families detected between the systemic and localized AL amyloidosis. For AL-kappa, KV1 was more prevalent in systemic cases when compared to localized cases (p=7.2E-12) suggesting KV1 clones as a hallmark for systemic AL-kappa amyloidosis. KV3 was more frequently seen in localized AL-kappa cases when compared to systemic AL-kappa cases (p =2.8E-11). For AL-lambda, LV1 and LV2 gene families were more prevalent in localized cases when compared to systemic cases (p= 0.039 and 2.7E-05). LV6 was more prevalent in systemic AL-lambda cases (p=1.4E-07). We also detected a higher incidence of mixed AL/AH type in localized AL (18%) when compared to systemic AL (5%; Odds Ratio=4.2673, p<0.0001). We next turned to the organ specific IGKV and IGLV gene family usage patterns in patients with localized amyloidosis. For 147 localized AL-kappa cases, KV3 was most dominant in lung (64%) and KV1 was dominant in skin (38%). For 246 localized AL-lambda cases, LV2 was most prevalent in lung (34%) and LV3 was most prevalent in skin (36%). For bladder, both LV1 and LV2 had comparable prevalence (42% and 32%). For 361 systemic AL-kappa cases, KV1 consistently ranked at the top of gene families used in GI tract (55%), heart (71%), kidney (59%), liver (75%) and fat aspirate (50%). For 877 systemic AL-lambda cases, LV2 was predominant in GI tract (30%), LV3 in heart (35%) and LV6 in kidney (33%). The prevalence of LV1, LV2 and LV3 in liver is comparable (36%, 22% and 31%). LV6 and LV3 had comparable prevalence (22% and 24%) in AL-lambda fat aspirates. Conclusion The novel proteomics method detects IGLC V family usage in large cohorts of AL patients. It identifies unique profiles in systemic and localized cases, and in different organ sites. This information will be helpful in determining systemic versus localized nature of AL amyloidosis at diagnosis and to assess risk of specific end organ involvement. We found also a strong association between IGKV and IGLV gene usage and organ involvement. Disclosures: No relevant conflicts of interest to declare.
16
Deutsch, Eric W., Henry Lam, and Ruedi Aebersold. "Data analysis and bioinformatics tools for tandem mass spectrometry in proteomics." Physiological Genomics 33, no. 1 (March 2008): 18–25. http://dx.doi.org/10.1152/physiolgenomics.00298.2007.
Full textAbstract:
Data processing is a central and critical component of a successful proteomics experiment, and is often the most time-consuming step. There have been considerable advances in the field of proteomics informatics in the past 5 years, spurred mainly by free and open-source software tools. Along with the gains afforded by new software, the benefits of making raw data and processed results freely available to the community in data repositories are finally in evidence. In this review, we provide an overview of the general analysis approaches, software tools, and repositories that are enabling successful proteomics research via tandem mass spectrometry.
17
Sadygov, Rovshan G. "High Mass Accuracy Phosphopeptide Identification Using Tandem Mass Spectra." International Journal of Proteomics 2012 (July 15, 2012): 1–5. http://dx.doi.org/10.1155/2012/104681.
Full textAbstract:
Phosphoproteomics is a powerful analytical platform for identification and quantification of phosphorylated peptides and assignment of phosphorylation sites. Bioinformatics tools to identify phosphorylated peptides from their tandem mass spectra and protein sequence databases are important part of phosphoproteomics. In this work, we discuss general informatics aspects of mass-spectrometry-based phosphoproteomics. Some of the specifics of phosphopeptide identifications stem from the labile nature of phosphor groups and expanded peptide search space. Allowing for modifications of Ser, Thr, and Tyr residues exponentially increases effective database size. High mass resolution and accuracy measurements of precursor mass-to-charge ratios help to restrict the search space of candidate peptide sequences. The higher-order fragmentations of neutral loss ions enhance the fragment ion mass spectra of phosphorylated peptides. We show an example of a phosphopeptide identification where accounting for fragmentation from neutral loss species improves the identification scores in a database search algorithm by 50%.
18
Kim, Doeun, Sunjoo Kim, Ann-Yae Na, Chang Hwan Sohn, Sangkyu Lee, and Hye Suk Lee. "Identification of Decrease in TRiC Proteins as Novel Targets of Alpha-Amanitin-Derived Hepatotoxicity by Comparative Proteomic Analysis In Vitro." Toxins 13, no. 3 (March 9, 2021): 197. http://dx.doi.org/10.3390/toxins13030197.
Full textAbstract:
Alpha-amanitin (α-AMA) is a cyclic peptide and one of the most lethal mushroom amatoxins found in Amanita phalloides. α-AMA is known to cause hepatotoxicity through RNA polymerase II inhibition, which acts in RNA and DNA translocation. To investigate the toxic signature of α-AMA beyond known mechanisms, we used quantitative nanoflow liquid chromatography–tandem mass spectrometry analysis coupled with tandem mass tag labeling to examine proteome dynamics in Huh-7 human hepatoma cells treated with toxic concentrations of α-AMA. Among the 1828 proteins identified, we quantified 1563 proteins, which revealed that four subunits in the T-complex protein 1-ring complex protein decreased depending on the α-AMA concentration. We conducted bioinformatics analyses of the quantified proteins to characterize the toxic signature of α-AMA in hepatoma cells. This is the first report of global changes in proteome abundance with variations in α-AMA concentration, and our findings suggest a novel molecular regulation mechanism for hepatotoxicity.
19
Lu, Yang Young, Jeff Bilmes, Ricard A. Rodriguez-Mias, Judit Villén, and William Stafford Noble. "DIAmeter: matching peptides to data-independent acquisition mass spectrometry data." Bioinformatics 37, Supplement_1 (July 1, 2021): i434—i442. http://dx.doi.org/10.1093/bioinformatics/btab284.
Full textAbstract:
Abstract Motivation Tandem mass spectrometry data acquired using data independent acquisition (DIA) is challenging to interpret because the data exhibits complex structure along both the mass-to-charge (m/z) and time axes. The most common approach to analyzing this type of data makes use of a library of previously observed DIA data patterns (a ‘spectral library’), but this approach is expensive because the libraries do not typically generalize well across laboratories. Results Here, we propose DIAmeter, a search engine that detects peptides in DIA data using only a peptide sequence database. Although some existing library-free DIA analysis methods (i) support data generated using both wide and narrow isolation windows, (ii) detect peptides containing post-translational modifications, (iii) analyze data from a variety of instrument platforms and (iv) are capable of detecting peptides even in the absence of detectable signal in the survey (MS1) scan, DIAmeter is the only method that offers all four capabilities in a single tool. Availability and implementation The open source, Apache licensed source code is available as part of the Crux mass spectrometry analysis toolkit (http://crux.ms). Supplementary information Supplementary data are available at Bioinformatics online.
20
Peng, Gang, Rashaun Wilson, Yishuo Tang, TuKiet T. Lam, Angus C. Nairn, Kenneth Williams, and Hongyu Zhao. "ProteomicsBrowser: MS/proteomics data visualization and investigation." Bioinformatics 35, no. 13 (November 21, 2018): 2313–14. http://dx.doi.org/10.1093/bioinformatics/bty958.
Full textAbstract:
Abstract Summary Large-scale, quantitative proteomics data are being generated at ever increasing rates by high-throughput, mass spectrometry technologies. However, due to the complexity of these large datasets as well as the increasing numbers of post-translational modifications (PTMs) that are being identified, developing effective methods for proteomic visualization has been challenging. ProteomicsBrowser was designed to meet this need for comprehensive data visualization. Using peptide information files exported from mass spectrometry search engines or quantitative tools as input, the peptide sequences are aligned to an internal protein database such as UniProtKB. Each identified peptide ion including those with PTMs is then visualized along the parent protein in the Browser. A unique property of ProteomicsBrowser is the ability to combine overlapping peptides in different ways to focus analysis of sequence coverage, charge state or PTMs. ProteomicsBrowser includes other useful functions, such as a data filtering tool and basic statistical analyses to qualify quantitative data. Availability and implementation ProteomicsBrowser is implemented in Java8 and is available at https://medicine.yale.edu/keck/nida/proteomicsbrowser.aspx and https://github.com/peng-gang/ProteomicsBrowser. Supplementary information Supplementary data are available at Bioinformatics online.
21
Marissen, Rob, and Magnus Palmblad. "mzRecal: universal MS1 recalibration in mzML using identified peptides in mzIdentML as internal calibrants." Bioinformatics 37, no. 17 (February 4, 2021): 2768–69. http://dx.doi.org/10.1093/bioinformatics/btab056.
Full textAbstract:
Abstract Summary In mass spectrometry-based proteomics, accurate peptide masses improve identifications, alignment and quantitation. Getting the most out of any instrument therefore requires proper calibration. Here, we present a new stand-alone software, mzRecal, for universal automatic recalibration of data from all common mass analyzers using standard open formats and based on physical principles. Availability and implementation mzRecal is implemented in Go and freely available on https://github.com/524D/mzRecal. Supplementary information Supplementary data are available at Bioinformatics online.
22
Kall, L., J. D. Storey, and W. S. Noble. "Non-parametric estimation of posterior error probabilities associated with peptides identified by tandem mass spectrometry." Bioinformatics 24, no. 16 (August 9, 2008): i42—i48. http://dx.doi.org/10.1093/bioinformatics/btn294.
Full text
23
Kochanowski, Maciej, Mirosław Różycki, Joanna Dąbrowska, Aneta Bełcik, Jacek Karamon, Jacek Sroka, and Tomasz Cencek. "Proteomic and Bioinformatic Investigations of Heat-Treated Anisakis simplex Third-Stage Larvae." Biomolecules 10, no. 7 (July 16, 2020): 1066. http://dx.doi.org/10.3390/biom10071066.
Full textAbstract:
Anisakis simplex third-stage larvae are the main source of hidden allergens in marine fish products. Some Anisakis allergens are thermostable and, even highly processed, could cause hypersensitivity reactions. However, Anisakis proteome has not been studied under autoclaving conditions of 121 °C for 60 min, which is an important process in the food industry. The aim of the study was the identification and characterization of allergens, potential allergens, and other proteins of heat-treated A. simplex larvae. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to identify 470 proteins, including allergens—Ani s 1, Ani s 2, Ani s 3, Ani s 4, Ani s 5—and 13 potential allergens that were mainly homologs of Anisakis spp., Ascaris spp., and Acari allergens. Ani s 2, Ani s 3, Ani s 5, and three possible allergens were found among the top 25 most abundant proteins. The computational analysis allowed us to detect allergen epitopes, assign protein families, and domains as well as to annotate the localization of proteins. The predicted 3D models of proteins revealed similarities between potential allergens and homologous allergens. Despite the partial degradation of heated A. simplex antigens, their immunoreactivity with anti-A. simplex IgG antibodies was confirmed using a Western blot. In conclusion, identified epitopes of allergenic peptides highlighted that the occurrence of Anisakis proteins in thermally processed fish products could be a potential allergic hazard. Further studies are necessary to confirm the IgE immunoreactivity and thermostability of identified proteins.
24
Crockett, David K., Mark M. Kushnir, Joann L. Cloud, Edward R. Ashwood, and Alan L. Rockwood. "Identification of Histoplasma-Specific Peptides in Human Urine." International Journal of Peptides 2012 (March 26, 2012): 1–4. http://dx.doi.org/10.1155/2012/621329.
Full textAbstract:
Histoplasmosis is a severe dimorphic fungus infection, which is often difficult to diagnose due to similarity in symptoms to other diseases and lack of specific diagnostic tests. Urine samples from histoplasma-antigen-positive patients and appropriate controls were prepared using various sample preparation strategies including immunoenrichment, ultrafiltration, high-abundant protein depletion, deglycosylation, reverse-phase fractions, and digest using various enzymes. Samples were then analyzed by nanospray tandem mass spectrometry. Accurate mass TOF scans underwent molecular feature extraction and statistical analysis for unique disease makers, and acquired MS/MS data were searched against known human and histoplasma proteins. In human urine, some 52 peptides from 37 Histoplasma proteins were identified with high confidence. This is the first report of identification of a large number of Histoplasma-specific peptides from immunoassay-positive patient samples using tandem mass spectrometry and bioinformatics techniques. These findings may lead to novel diagnostic markers for histoplasmosis in human urine.
25
Shen, Changyu, Zhiping Wang, Ganesh Shankar, Xiang Zhang, and Lang Li. "A hierarchical statistical model to assess the confidence of peptides and proteins inferred from tandem mass spectrometry." Bioinformatics 24, no. 2 (November 17, 2007): 202–8. http://dx.doi.org/10.1093/bioinformatics/btm555.
Full text
26
Heller, Manfred, Mingliang Ye, Philippe E. Michel, Patrick Morier, Daniel Stalder, Martin A. Jünger, Ruedi Aebersold, Frédéric Reymond, and Joël S. Rossier. "Added Value for Tandem Mass Spectrometry Shotgun Proteomics Data Validation through Isoelectric Focusing of Peptides." Journal of Proteome Research 4, no. 6 (December 2005): 2273–82. http://dx.doi.org/10.1021/pr050193v.
Full text
27
Pham, Thang V., Sander R. Piersma, Marc Warmoes, and Connie R. Jimenez. "On the beta-binomial model for analysis of spectral count data in label-free tandem mass spectrometry-based proteomics." Bioinformatics 26, no. 3 (December 9, 2009): 363–69. http://dx.doi.org/10.1093/bioinformatics/btp677.
Full text
28
Bąchor, Remigiusz, Mateusz Waliczek, Piotr Stefanowicz, and Zbigniew Szewczuk. "Trends in the Design of New Isobaric Labeling Reagents for Quantitative Proteomics." Molecules 24, no. 4 (February 15, 2019): 701. http://dx.doi.org/10.3390/molecules24040701.
Full textAbstract:
Modern mass spectrometry is one of the most frequently used methods of quantitative proteomics, enabling determination of the amount of peptides in a sample. Although mass spectrometry is not inherently a quantitative method due to differences in the ionization efficiency of various analytes, the application of isotope-coded labeling allows relative quantification of proteins and proteins. Over the past decade, a new method for derivatization of tryptic peptides using isobaric labels has been proposed. The labels consist of reporter and balanced groups. They have the same molecular weights and chemical properties, but differ in the distribution of stable heavy isotopes. These tags are designed in such a way that during high energy collision induced dissociation (CID) by tandem mass spectrometry, the isobaric tag is fragmented in the specific linker region, yielding reporter ions with different masses. The mass shifts among the reporter groups are compensated by the balancing groups so that the overall mass is the same for all forms of the reagent. Samples of peptides are labeled with the isobaric mass tags in parallel and combined for analysis. Quantification of individual peptides is achieved by comparing the intensity of reporter ions in the tandem mass (MS/MS) spectra. Isobaric markers have found a wide range of potential applications in proteomics. However, the currently available isobaric labeling reagents have some drawbacks, such as high cost of production, insufficient selectivity of the derivatization, and relatively limited enhancement of sensitivity of the analysis. Therefore, efforts have been devoted to the development of new isobaric markers with increased usability. The search for new isobaric markers is focused on developing a more selective method of introducing a tag into a peptide molecule, increasing the multiplexicity of markers, lowering the cost of synthesis, and increasing the sensitivity of measurement by using ionization tags containing quaternary ammonium salts. Here, the trends in the design of new isobaric labeling reagents for quantitative proteomics isobaric derivatization strategies in proteomics are reviewed, with a particular emphasis on isobaric ionization tags. The presented review focused on different types of isobaric reagents used in quantitative proteomics, their chemistry, and advantages offer by their application.
29
Hinkelbein, Jochen, Lennert Böhm, Oliver Spelten, David Sander, Stefan Soltész, and Stefan Braunecker. "Hyperoxia-Induced Protein Alterations in Renal Rat Tissue: A Quantitative Proteomic Approach to Identify Hyperoxia-Induced Effects in Cellular Signaling Pathways." Disease Markers 2015 (2015): 1–12. http://dx.doi.org/10.1155/2015/964263.
Full textAbstract:
Introduction. In renal tissue as well as in other organs, supranormal oxygen pressure may lead to deleterious consequences on a cellular level. Additionally, hyperoxia-induced effect in cells and related free radicals may potentially contribute to renal failure. The aim of this study was to analyze time-dependent alterations of rat kidney protein expression after short-term normobaric hyperoxia using proteomics and bioinformatic approaches.Material and Methods.N=36Wistar rats were randomized into six different groups: three groups with normobaric hyperoxia (exposure to 100% oxygen for 3 h) and three groups with normobaric normoxia (NN; room air). After hyperoxia exposure, kidneys were removed immediately, after 3 days and after 7 days. Kidney lysates were analyzed by two-dimensional gel electrophoresis followed by peptide mass fingerprinting using tandem mass spectrometry. Statistical analysis was performed with DeCyder 2D software (p<0.01). Biological functions of differential regulated proteins were studied using functional network analysis (Ingenuity Pathways Analysis and PathwayStudio).Results. Expression of 14 proteins was significantly altered(p<0.01): eight proteins (MEP1A_RAT, RSSA_RAT, F16P1_RAT, STML2_RAT, BPNT1_RAT, LGMN_RAT, ATPA_RAT, and VDAC1_RAT) were downregulated and six proteins (MTUS1_RAT, F16P1_RAT, ACTG_RAT, ACTB_RAT, 2ABA_RAT, and RAB1A_RAT) were upregulated. Bioinformatic analyses revealed an association of regulated proteins with inflammation.Conclusions. Significant alterations in renal protein expression could be demonstrated for up to 7 days even after short-term hyperoxia. The identified proteins indicate an association with inflammation signaling cascades. MEP1A and VDAC1 could be promising candidates to identify hyperoxic injury in kidney cells.
30
Crasto, Chiquito, Chandrahas Narne, Mikako Kawai, Landon Wilson, and Stephen Barnes. "MRMPath and MRMutation, Facilitating Discovery of Mass Transitions for Proteotypic Peptides in Biological Pathways Using a Bioinformatics Approach." Advances in Bioinformatics 2013 (January 29, 2013): 1–10. http://dx.doi.org/10.1155/2013/527295.
Full textAbstract:
Quantitative proteomics applications in mass spectrometry depend on the knowledge of the mass-to-charge ratio (m/z) values of proteotypic peptides for the proteins under study and their product ions. MRMPath and MRMutation, web-based bioinformatics software that are platform independent, facilitate the recovery of this information by biologists. MRMPath utilizes publicly available information related to biological pathways in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. All the proteins involved in pathways of interest are recovered and processed in silico to extract information relevant to quantitative mass spectrometry analysis. Peptides may also be subjected to automated BLAST analysis to determine whether they are proteotypic. MRMutation catalogs and makes available, following processing, known (mutant) variants of proteins from the current UniProtKB database. All these results, available via the web from well-maintained, public databases, are written to an Excel spreadsheet, which the user can download and save. MRMPath and MRMutation can be freely accessed. As a system that seeks to allow two or more resources to interoperate, MRMPath represents an advance in bioinformatics tool development. As a practical matter, the MRMPath automated approach represents significant time savings to researchers.
31
Leung, Felix, Marcus Q. Bernardini, Kun Liang, Ihor Batruch, Marjan Rouzbahman, Eleftherios P. Diamandis, and Vathany Kulasingam. "Unraveling endometriosis-associated ovarian carcinomas using integrative proteomics." F1000Research 7 (February 14, 2018): 189. http://dx.doi.org/10.12688/f1000research.13863.1.
Full textAbstract:
Background: To elucidate potential markers of endometriosis and endometriosis-associated endometrioid and clear cell ovarian carcinomas using mass spectrometry-based proteomics. Methods: A total of 21 fresh, frozen tissues from patients diagnosed with clear cell carcinoma, endometrioid carcinoma, endometriosis and benign endometrium were subjected to an in-depth liquid chromatography-tandem mass spectrometry analysis on the Q-Exactive Plus. Protein identification and quantification were performed using MaxQuant, while downstream analyses were performed using Perseus and various bioinformatics databases. Results: Approximately 9000 proteins were identified in total, representing the first in-depth proteomic investigation of endometriosis and its associated cancers. This proteomic data was shown to be biologically sound, with minimal variation within patient cohorts and recapitulation of known markers. While moderate concordance with genomic data was observed, it was shown that such data are limited in their abilities to represent tumours on the protein level and to distinguish tumours from their benign precursors. Conclusions: The proteomic data suggests that distinct markers may differentiate endometrioid and clear cell carcinoma from endometriosis. These markers may be indicators of pathobiology but will need to be further investigated. Ultimately, this dataset may serve as a basis to unravel the underlying biology of the endometrioid and clear cell cancers with respect to their endometriotic origins.
32
Leung, Felix, Marcus Q. Bernardini, Kun Liang, Ihor Batruch, Marjan Rouzbahman, Eleftherios P. Diamandis, and Vathany Kulasingam. "Unraveling endometriosis-associated ovarian carcinomas using integrative proteomics." F1000Research 7 (June 20, 2018): 189. http://dx.doi.org/10.12688/f1000research.13863.2.
Full textAbstract:
Background: To elucidate potential markers of endometriosis and endometriosis-associated endometrioid and clear cell ovarian carcinomas using mass spectrometry-based proteomics. Methods: A total of 21 fresh, frozen tissues from patients diagnosed with clear cell carcinoma, endometrioid carcinoma, endometriosis and benign endometrium were subjected to an in-depth liquid chromatography-tandem mass spectrometry analysis on the Q-Exactive Plus. Protein identification and quantification were performed using MaxQuant, while downstream analyses were performed using Perseus and various bioinformatics databases. Results: Approximately 9000 proteins were identified in total, representing the first in-depth proteomic investigation of endometriosis and its associated cancers. This proteomic data was shown to be biologically sound, with minimal variation within patient cohorts and recapitulation of known markers. While moderate concordance with genomic data was observed, it was shown that such data are limited in their abilities to represent tumours on the protein level and to distinguish tumours from their benign precursors. Conclusions: The proteomic data suggests that distinct markers may differentiate endometrioid and clear cell carcinoma from endometriosis. These markers may be indicators of pathobiology but will need to be further investigated. Ultimately, this dataset may serve as a basis to unravel the underlying biology of the endometrioid and clear cell cancers with respect to their endometriotic origins.
33
Theodorou, Andria, Marios Phylactides, Eleni Katsantoni, Kostas Vougas, Spyros D. Garbis, Pavlos Fanis, Maria Sitarou, Swee Lay Thein, and Marina Kleanthous. "Proteomic Studies for the Investigation of γ-Globin Induction by Decitabine in Human Primary Erythroid Progenitor Cultures." Journal of Clinical Medicine 9, no. 1 (January 3, 2020): 134. http://dx.doi.org/10.3390/jcm9010134.
Full textAbstract:
Reactivation of γ-globin is considered a promising approach for the treatment of β-thalassemia and sickle cell disease. Therapeutic induction of γ-globin expression, however, is fraught with lack of suitable therapeutic targets. The aim of this study was to investigate the effects that treatment with decitabine has on the proteome of human primary erythroid cells from healthy and thalassemic volunteers, as a means of identifying new potential pharmacological targets. Decitabine is a known γ-globin inducer, which is not, however, safe enough for clinical use. A proteomic approach utilizing isobaric tags for relative and absolute quantitation (iTRAQ) analysis, in combination with high-pH reverse phase peptide fractionation followed by liquid chromatography-tandem mass spectrometry (LC-MS/MS), was employed to investigate the effects of decitabine treatment. Bioinformatics analysis making use of the Database for Annotation, Visualization and Integrated Discovery (DAVID) was employed for functional annotation of the 192 differentially expressed proteins identified. The data are available via ProteomeXchange with identifier PXD006889. The proteins fall into various biological pathways, such as the NF-κB signaling pathway, and into many functional categories including regulation of cell proliferation, transcription factor and DNA binding, protein stabilization, chromatin modification and organization, and oxidative stress proteins.
34
McDonald, W. Hayes, and John R. Yates. "Shotgun Proteomics and Biomarker Discovery." Disease Markers 18, no. 2 (2002): 99–105. http://dx.doi.org/10.1155/2002/505397.
Full textAbstract:
Coupling large-scale sequencing projects with the amino acid sequence information that can be gleaned from tandem mass spectrometry (MS/MS) has made it much easier to analyze complex mixtures of proteins. The limits of this “shotgun” approach, in which the protein mixture is proteolytically digested before separation, can be further expanded by separating the resulting mixture of peptides prior to MS/MS analysis. Both single dimensional high pressure liquid chromatography (LC) and multidimensional LC (LC/LC) can be directly interfaced with the mass spectrometer to allow for automated collection of tremendous quantities of data. While there is no single technique that addresses all proteomic challenges, the shotgun approaches, especially LC/LC-MS/MS-based techniques such as MudPIT (multidimensional protein identification technology), show advantages over gel-based techniques in speed, sensitivity, scope of analysis, and dynamic range. Advances in the ability to quantitate differences between samples and to detect for an array of post-translational modifications allow for the discovery of classes of protein biomarkers that were previously unassailable.
35
Dittrich, Julia, Susen Becker, Max Hecht, and Uta Ceglarek. "Sample preparation strategies for targeted proteomics via proteotypic peptides in human blood using liquid chromatography tandem mass spectrometry." PROTEOMICS - Clinical Applications 9, no. 1-2 (December 28, 2014): 5–16. http://dx.doi.org/10.1002/prca.201400121.
Full text
36
Golenko, Y. S., and A. A. Ismailova. "MODERN COMPUTATIONAL STRATEGIES FOR PROTEIN INFERENCE IN SHOTGUN PROTEOMIC." PHYSICO-MATHEMATICAL SERIES 2, no. 336 (April 15, 2021): 56–65. http://dx.doi.org/10.32014/2021.2518-1726.21.
Full textAbstract:
Today, shotgun proteomics is a powerful approach to characterize proteomes in biological samples. Unlike the top-down proteomics strategy, shotgun proteomics is characterized by high separation efficiency and mass spectral sensitivity. At the same time, it places higher demands on the computational and statistical methods required for peptide identification, protein identification, and label-free quantification. The main purpose of shotgun proteomics is to identify the shape and amount of each protein by combining liquid chromatography with tandem mass spectrometry. The analysis and interpretation of experimental data is the final and most important stage in proteomics; they also generate a large number of problems that require complex computational solutions. One of the most important tasks, of course, is the identification of proteins present in the experimental sample. As a rule, this task is divided into two main components: the stage of assigning experimental tandem mass spectra to peptides obtained from the protein database, and the stage of comparing peptides with proteins and quantitative assessment of the reliability of the identified proteins. It is also worth considering that the assessment of the reliability of the data obtained can be a separate, no less important and complex task. In this article, we propose to consider protein identification only as a problem of statistical inference, and also describe a number of methods that can be used to solve it. We classify the existing approaches into (1) rule-based methods, (2) combinatorial optimization methods, and (3) probabilistic inference methods. Integer programming and Bayesian inference frameworks are used to represent methods. We also discuss the main problems of protein identification and suggest possible solutions to these problems.
37
Deutsch, D. R., T. Fröhlich, K. A. Otte, A. Beck, F. A. Habermann, E. Wolf, and G. J. Arnold. "83 STAGE-SPECIFIC PROTEOME SIGNATURES IN EARLY BOVINE EMBRYO DEVELOPMENT." Reproduction, Fertility and Development 27, no. 1 (2015): 134. http://dx.doi.org/10.1071/rdv27n1ab83.
Full textAbstract:
Development of early embryonic stages before activation of the embryonic genome depends on sufficiently stored products of the maternal genome and adequate activation, deactivation, and relocation of proteins. To establish protein function, several posttranslational events (e.g. proteolytic activation, phosphorylation, or secretion) are frequently essential and thereby prevent prediction of protein abundance from transcript abundance. Consequently, proteomic studies are indispensable to characterise the molecular processes governing early embryonic development and to establish corresponding regulatory networks. Here, we present a quantitative proteome analysis of bovine zygotes and embryos at the 2-cell and 4-cell stage. Cumulus-oocyte complexes (COC) were prepared from bovine ovaries obtained from a local abattoir and selected for a compact layer of cumulus cells. In vitro maturation, fertilization, and embryo production were performed according to standard procedures. For quantitative isobaric tags for relative and absolute quantitation (iTRAQ)-liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis, protein from batches of 50 MII oocytes (serving as a reference), zygotes, 2-cell and 4-cell stage embryos, respectively, was extracted. Quantitative proteome analysis of iTRAQ-labelled tryptic peptides was performed on an Orbitrap XL instrument (Thermo Fisher, Waltham, MA, USA) coupled to an Eksigent nano-liquid chromatography system (AB Sciex, Framingham, MA, USA). The tandem MS data were analysed by MASCOT and filtered for a false discovery rate (FDR) of <1%. Quantification of iTRAQ signals was accomplished with the Q+ module of the Scaffold software (Proteome Software Inc., Portland, OR, USA). t-Tests, ANOVA and principal component analysis (PCA) analysis were performed using R (R Core Development Team, Vienna, Austria). From 4 biological replicates, 1072 proteins were identified and quantified. Eighty-seven differed significantly in abundance between the 4 stages (log2 fold change ≥ |0.6|, P ≤ 0.05). The proteomes of 2-cell and 4-cell embryos differed most from the reference MII oocyte, and a considerable fraction of proteins continuously increases in abundance during the stages analysed. Bioinformatic analysis of abundance altered proteins provided evidence that the proteins RPS14 and HNRNPK involved in the p53 pathway play a major role during early development, as well as proteins of the lipid metabolism, in particular APOA1. Furthermore, a group of proteins (e.g. SPTBN1, PPP1CC, RABGAP1, STMN1, and WEE2) is engaged in mitosis. In addition, we detected relevant differences between transcript and protein abundance levels; for example, for WEE2. In conclusion, this study identified and quantified numerous proteins important for early embryogenesis so far not described in the mammalian system, and contributed protein profiles for key players previously described. Our results highlight the importance of innovative proteomic tools and workflows to complement transcriptome data of early embryogenesis.
38
Shih, Yi-Chen, Jhih-Ting Hsiao, and Fuu Sheu. "Feasibility of Utilizing Stable-Isotope Dimethyl Labeling in Liquid Chromatography–Tandem Mass Spectrometry-Based Determination for Food Allergens—Case of Kiwifruit." Molecules 24, no. 10 (May 18, 2019): 1920. http://dx.doi.org/10.3390/molecules24101920.
Full textAbstract:
Stable-isotope dimethyl labeling is a highly reactive and cost-effective derivatization procedure that could be utilized in proteomics analysis. In this study, a liquid chromatography– tandem mass spectrometry in multiple reaction monitoring mode (LC-MS-MRM) platform for the quantification of kiwi allergens was first developed using this strategy. Three signature peptides for target allergens Act d 1, Act d 5, and Act d 11 were determined and were derivatized with normal and deuterated formaldehyde as external calibrants and internal standards, respectively. The results showed that sample preparation with the phenol method provided comprehensive protein populations. Recoveries at four different levels ranging from 72.5–109.3% were achieved for the H-labeled signature peptides of Act d 1 (SPA1-H) and Act d 5 (SPA5-H) with precision ranging from 1.86–9.92%. The limit of quantification (LOQ) was set at 8 pg mL−1 for SPA1-H and at 8 ng mL−1 for SPA5-H. The developed procedure was utilized to analyze seven kinds of hand-made kiwi foods containing 0.0175–0.0515 mg g−1 of Act d 1 and 0.0252–0.0556 mg g−1 of Act d 5. This study extended the applicability of stable-isotope dimethyl labeling to the economical and precise determination of food allergens and peptides.
39
Kwon, Dami, Jong-Moon Park, Van-An Duong, Seong-Joo Hong, Byung-Kwan Cho, Choul-Gyun Lee, Hyung-Kyoon Choi, Dong-Myung Kim, and Hookeun Lee. "Comparative Proteomic Profiling of Marine and Freshwater Synechocystis Strains Using Liquid Chromatography-Tandem Mass Spectrometry." Journal of Marine Science and Engineering 8, no. 10 (October 12, 2020): 790. http://dx.doi.org/10.3390/jmse8100790.
Full textAbstract:
Freshwater Synechocystis sp. PCC 6803 has been considered to be a platform for the production of the next generation of biofuels and is used as a model organism in various fields. Various genomics, transcriptomics, metabolomics, and proteomics studies have been performed on this strain, whereas marine Synechocystis sp. PCC 7338 has not been widely studied despite its wide distribution. This study analyzed the proteome profiles of two Synechocystis strains using a liquid chromatography–tandem mass spectrometry-based bottom-up proteomic approach. Proteomic profiling of Synechocystis sp. PCC 7338 was performed for the first time with a data-dependent acquisition method, revealing 18,779 unique peptides and 1794 protein groups. A data-independent acquisition method was carried out for the comparative quantitation of Synechocystis sp. PCC 6803 and 7338. Among 2049 quantified proteins, 185 up- and 211 down-regulated proteins were defined in Synechocystis sp. PCC 7338. Some characteristics in the proteome of Synechocystis sp. PCC 7338 were revealed, such as its adaptation to living conditions, including the down-regulation of some photosynthesis proteins, the up-regulation of kdpB, and the use of osmolyte glycine as a substrate in C1 metabolism for the regulation of carbon flow. This study will facilitate further studies on Synechocystis 7338 to define in depth the proteomic differences between it and other Synechocystis strains.
40
Lasch, Peter, Andy Schneider, Christian Blumenscheit, and Joerg Doellinger. "Identification of Microorganisms by Liquid Chromatography-Mass Spectrometry (LC-MS1) and in Silico Peptide Mass Libraries." Molecular & Cellular Proteomics 19, no. 12 (September 30, 2020): 2125–38. http://dx.doi.org/10.1074/mcp.tir120.002061.
Full textAbstract:
Over the past decade, modern methods of MS (MS) have emerged that allow reliable, fast and cost-effective identification of pathogenic microorganisms. Although MALDI-TOF MS has already revolutionized the way microorganisms are identified, recent years have witnessed also substantial progress in the development of liquid chromatography (LC)-MS based proteomics for microbiological applications. For example, LC-tandem MS (LC-MS2) has been proposed for microbial characterization by means of multiple discriminative peptides that enable identification at the species, or sometimes at the strain level. However, such investigations can be laborious and time-consuming, especially if the experimental LC-MS2 data are tested against sequence databases covering a broad panel of different microbiological taxa. In this proof of concept study, we present an alternative bottom-up proteomics method for microbial identification. The proposed approach involves efficient extraction of proteins from cultivated microbial cells, digestion by trypsin and LC–MS measurements. Peptide masses are then extracted from MS1 data and systematically tested against an in silico library of all possible peptide mass data compiled in-house. The library has been computed from the UniProt Knowledgebase covering Swiss-Prot and TrEMBL databases and comprises more than 12,000 strain-specific in silico profiles, each containing tens of thousands of peptide mass entries. Identification analysis involves computation of score values derived from correlation coefficients between experimental and strain-specific in silico peptide mass profiles and compilation of score ranking lists. The taxonomic positions of the microbial samples are then determined by using the best-matching database entries. The suggested method is computationally efficient – less than 2 mins per sample - and has been successfully tested by a test set of 39 LC-MS1 peak lists obtained from 19 different microbial pathogens. The proposed method is rapid, simple and automatable and we foresee wide application potential for future microbiological applications.
41
Menikou, Stephanie, Andrew J. McArdle, Ming-Shi Li, Myrsini Kaforou, Paul R. Langford, and Michael Levin. "A proteomics-based method for identifying antigens within immune complexes." PLOS ONE 15, no. 12 (December 23, 2020): e0244157. http://dx.doi.org/10.1371/journal.pone.0244157.
Full textAbstract:
A novel approach to recover and identify immune complexes (ICs) was developed using size exclusion chromatography (SEC) and affinity chromatography on immunoglobulin binding columns (HiTrap Protein G). The purification process was monitored by 1D SDS-PAGE, protein staining, Western blotting and, finally, liquid chromatography tandem mass spectrometry (LC MS/MS) was used to identify the recovered antigens. This approach was applied to serum with artificially created immune complexes (ICs) comprising vaccine antigen (influenza) and antibody, which led to recovery and identification of influenza peptides within the recovered ICs. This approach was compared with the established method for IC detection and recovery, polyethylene glycol (PEG) precipitation, followed by LC MS/MS. Both approaches successfully enabled capture, recovery and characterization of immunoglobulins and influenza antigen(s) in complex with the immunoglobulins. However, PEG precipitation has the advantage of simplicity and is more suited for large scale studies.
42
Holman, Stephen W., Dean E. Hammond, Deborah M. Simpson, John Waters, Jane L. Hurst, and Robert J. Beynon. "Protein turnover measurement using selected reaction monitoring-mass spectrometry (SRM-MS)." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 374, no. 2079 (October 28, 2016): 20150362. http://dx.doi.org/10.1098/rsta.2015.0362.
Full textAbstract:
Protein turnover represents an important mechanism in the functioning of cells, with deregulated synthesis and degradation of proteins implicated in many diseased states. Therefore, proteomics strategies to measure turnover rates with high confidence are of vital importance to understanding many biological processes. In this study, the more widely used approach of non-targeted precursor ion signal intensity (MS1) quantification is compared with selected reaction monitoring (SRM), a data acquisition strategy that records data for specific peptides, to determine if improved quantitative data would be obtained using a targeted quantification approach. Using mouse liver as a model system, turnover measurement of four tricarboxylic acid cycle proteins was performed using both MS1 and SRM quantification strategies. SRM outperformed MS1 in terms of sensitivity and selectivity of measurement, allowing more confident determination of protein turnover rates. SRM data are acquired using cheaper and more widely available tandem quadrupole mass spectrometers, making the approach accessible to a larger number of researchers than MS1 quantification, which is best performed on high mass resolution instruments. SRM acquisition is ideally suited to focused studies where the turnover of tens of proteins is measured, making it applicable in determining the dynamics of proteins complexes and complete metabolic pathways. This article is part of the themed issue ‘Quantitative mass spectrometry’.
43
de Oliveira, José Miguel P. Ferreira, Mark W. J. van Passel, Peter J. Schaap, and Leo H. de Graaff. "Shotgun Proteomics of Aspergillus niger Microsomes upon d-Xylose Induction." Applied and Environmental Microbiology 76, no. 13 (May 7, 2010): 4421–29. http://dx.doi.org/10.1128/aem.00482-10.
Full textAbstract:
ABSTRACT Protein secretion plays an eminent role in cell maintenance and adaptation to the extracellular environment of microorganisms. Although protein secretion is an extremely efficient process in filamentous fungi, the mechanisms underlying protein secretion have remained largely uncharacterized in these organisms. In this study, we analyzed the effects of the d-xylose induction of cellulase and hemicellulase enzyme secretion on the protein composition of secretory organelles in Aspergillus niger. We aimed to systematically identify the components involved in the secretion of these enzymes via mass spectrometry of enriched subcellular microsomal fractions. Under each condition, fractions enriched for secretory organelles were processed for tandem mass spectrometry, resulting in the identification of peptides that originate from 1,081 proteins, 254 of which—many of them hypothetical proteins—were predicted to play direct roles in the secretory pathway. d-Xylose induction led to an increase in specific small GTPases known to be associated with polarized growth, exocytosis, and endocytosis. Moreover, the endoplasmic-reticulum-associated degradation (ERAD) components Cdc48 and all 14 of the 20S proteasomal subunits were recruited to the secretory organelles. In conclusion, induction of extracellular enzymes results in specific changes in the secretory subproteome of A. niger, and the most prominent change found in this study was the recruitment of the 20S proteasomal subunits to the secretory organelles.
44
Liu, Yiwen, Changlin Wang, Renqiang Yu, Jianfeng Fan, Weilai Jin, Yuting Zhu, Yingzuo Shi, et al. "Peptidomics Analysis Discloses That Novel Bioactive Peptides Participate in Necrotizing Enterocolitis in a Rat Model." BioMed Research International 2020 (December 31, 2020): 1–15. http://dx.doi.org/10.1155/2020/4705149.
Full textAbstract:
Necrotizing enterocolitis (NEC) is a common devastating gastrointestinal disease in premature infants, the molecular mechanisms of which have not been fully elucidated. Recently, endogenous peptides have garnered much attention owing to their role in diagnosis and treatment. However, changes in the peptide expression of NEC intestinal tissues remain poorly understood. In the present study, a comparative peptidomics profiling analysis was performed between NEC and control intestinal tissues via liquid chromatography-tandem mass spectrometry (LC-MS). In total, 103 upregulated and 73 downregulated peptides were identified in the intestinal tissues ( fold change ≥ 1.5 , p < 0.05 ). Bioinformatics analysis revealed that these differentially expressed peptides were significantly associated with NEC pathophysiology, including apoptosis, the TGF-β signaling pathway, the Wnt signaling pathway, and the MAPK signaling pathway. Furthermore, two putative peptides could inhibit apoptosis and promote the migration of intestinal epithelial cells induced by lipopolysaccharide; these peptides were derived from the protein domains MT1 and EZRI, respectively. In conclusion, our study revealed that endogenous peptides are involved in the pathophysiologic mechanism of NEC; nevertheless, further exploration is required in this regard.
45
Lisitsa, A. V., V. G. Zgoda, N. A. Petushkova, M. A. Pyatnitskiy, O. V. Larina, M. P. Klimenko, A. L. Kaysheva, P. A. Klimenko, and O. A. Latyshkevich. "Proteomics of the Human First Trimester Chorionic Villi Associated with Anembryonic Pregnancy." Biomedical Chemistry: Research and Methods 1, no. 4 (2018): e00076. http://dx.doi.org/10.18097/bmcrm00076.
Full textAbstract:
In this study, the proteomic approach based on high performance liquid chromatography connected with tandem mass spectrometry (LC-MS/MS) and bioinformatics analysis were applied to identify differentially abundant proteins in chorionic villus samples (CVS) from women with blighted ovum and normal pregnancy. We identified about 600 proteins in the solubilized fraction of CVS. Comparative proteomic analysis revealed differences in the content (Average Normalized Abundances) of 187 proteins in blighted ovum. These included 134 down-regulated proteins and 53 up-regulated proteins. According to bioinformatics analysis these proteins participate in a variety of metabolic processes, including alcohol and tricarboxylic acid metabolism, response to endoplasmic reticulum stress, small molecular catabolic process, cellular respiration, and others. Proteins that demonstrated growing content in blighted ovum were mainly encoded by genes located on chromosomes 7 and 16 whereas proteins which demonstrated reducing abundance were mainly encoded by genes located on chromosomes 1, 2, and 11. We also revealed changes in the content of proteins encoded by genes located on the human chromosome 18; they are involved in apoptotic and drug metabolic processes with an important role in early pregnancy loss. Our pilot results demonstrate the efficiency of the LC-MS/MS approach for detecting the differences at the qualitative and semi-quantitative levels in the protein profiles of the CVS at anembryonic pregnancy compared to normal gestation. We conclude that globally profiled and differentially regulated proteins of CVS are helpful in obtaining molecular insights into biological processes of the pregnancy pathology.
46
Ji, Chengjie, Zhengping Wang, and Liang Li. "Protein mass measurement combined with mass spectrometric sequencing of protein digests for detection and characterization of protein modifications1." Canadian Journal of Chemistry 84, no. 7 (July 1, 2006): 986–97. http://dx.doi.org/10.1139/v06-114.
Full textAbstract:
A method for the characterization of modifications of low molecular weight proteins (<20 kDa) extracted from a microorganism based on the use of multiple separation tools and mass spectrometric techniques is described. In this method, intact proteins from cell extracts are first separated and fractionated by liquid chromatography (LC). Individual fractions are then analyzed by matrix-assisted laser desorption ionization (MALDI) mass spectrometry (MS) to provide intact protein mass information. The fractions are further characterized by using trypsin digestion and LC electrospray ionization (ESI) MS/MS analysis of the resultant peptides to identify the proteins. Gel electrophoresis of a fraction is also carried out to estimate the molecular masses of the proteins. The gel bands are identified by in-gel digestion and peptide mass mapping and sequencing using MALDI-MS and MALDI-MS/MS. The combined information generated from these experiments is interpreted for detecting and characterizing modified proteins. This method has been developed and applied to the analysis of posttranslational modifications (PTMs) of low-mass proteins (5–20 kDa) extracted from a relatively well-characterized microorganism, Escherichia coli. Using this method, not only previously reported PTMs involving acetylation, methylation, oxidation, and the removal of signal peptides, but also two novel PTMs, namely loss of N-terminal Met-Thr-Met (MTM) and hydroxylation of arginine, were identified. It is envisaged that this method should be applicable to other relatively simple microorganisms for the discovery of new PTMs.Key words: top-down proteomics, protein modification, HPLC, gel electrophoresis, tandem mass spectrometry.
47
Batiston, Weliton, and Emanuel Carrilho. "The Importance and Challenges for Analytical Chemistry in Proteomics Analysis." Brazilian Journal of Analytical Chemistry 8, no. 10Years (June 2021): 51–73. http://dx.doi.org/10.30744/brjac.2179-3425.rv-64-2020.
Full textAbstract:
Although Linus Pauling had an exceptional scientific contribution to the study of chemical bonds, reported in his book The Nature of Chemical Bond, the lousy image he got for the X-ray diffraction drove him to an unstable structure with an unreal DNA triple helix publication. Oppositely, for the consecration of James Watson & Francis Crick, they had the opportunity to enter science history using the right image of X-ray to propose the famous DNA double helix structure correctly. This chapter of science is an excellent example of how analytical chemistry performance affects horizons and scientific advances. Today the complexity of the systems is more significant and understanding how all proteins truly work into cells and organisms is the current challenge from proteomics. Comprehending how analysis is carried out and how instruments work could promote new insights to improve the analytical performance in proteomics. Here we described an overview based on our expertise on the analytical chemistry toolkit for proteomics analysis: shotgun, bottom-up, middle-down, top-down, and native proteomics, and their inherent instrumentation technologies. In addition, a detailed discussion of the analytical figures of merit in proteomics analysis is provided. We also address the limitations in multidimensional liquid chromatography and tandem mass spectrometry platforms. Furthermore, we present some perspectives in bioinformatics, mathematical modeling simulations, and chemometrics tools, as well.
48
Vrana, Julie A., Steven R. Zeldenrust, Jason D. Theis, Jeffrey D. Gamez, Paul J. Kurtin, and Ahmet Dogan. "Diagnosis and Classification of Amyloidosis in Abdominal Subcutaneous Fat Aspiration Specimens Using Mass Spectrometry Based Proteomics." Blood 112, no. 11 (November 16, 2008): 2710. http://dx.doi.org/10.1182/blood.v112.11.2710.2710.
Full textAbstract:
Abstract Abdominal subcutaneous fat aspiration is one of the most practical, sensitive and specific methods for the diagnosis of systemic amyloidosis. One limitation of this method, compared to more invasive tissue biopsy based approaches, remains the technical difficulties in further classification of the amyloidosis as commonly used methods, such as immunohistochemistry, are not readily applicable to fat aspiration specimens. To overcome these difficulties we developed a method using nano-flow liquid chromatography electrospray tandem mass spectrometry (LC-MS/MS) that could identify amyloid subtypes in freshly obtained Congo Red positive fat aspirate specimens with great accuracy. Abdominal subcutaneous fat aspirate specimens were obtained from 73 patients with clinical suspicion for systemic amyloidosis. One half of the specimen was stained with Congo red and used for diagnosis of amyloidosis and the other half was processed and enzyme digested for LC-MS/MS analysis. The resulting LC-MS/MS data was correlated to theoretical fragmentation patterns of tryptic peptide sequences from the Swissprot database using Scaffold (Mascot, Sequest, and X!Tandem search algorithms). Peptide identifications were accepted if they could be established at greater than 90.0% probability and protein identifications were accepted if they could be established at greater than 90.0% probability and contain at least 2 identified spectra. The identified proteins were subsequently examined for the presence or absence of amyloid related peptides. Of the 73 cases studied, 41 were positive for Congo red consistent with systemic amyloidosis. In Congo red positive cases, LC-MS/MS peptide profiles consistent with AL-lambda (28/31), AL-kappa (6/7), and ATTR (2/3) were observed. Only one case in the Congo red negative control group (31/32) gave a kappa light chain profile which was attributed to a high level of kappa in the serum (285 mg/dL). Of the 35 out of 41 cases of systemic amyloidosis successfully classified by LC-MS/MS, additional clinical and pathology data validating the amyloid type was available. In each of these cases the MS/MS results accurately predicted the amyloid type. In conclusion, LC-MS/MS proteomic analysis of abdominal subcutaneous fat aspiration specimens involved by amyloidosis provides a highly specific (97% specificity) and sensitive (>85% sensitivity) method for diagnosis and classification of amyloidosis. The method is rapid and readily applicable in a clinical setting and will greatly improve the clinical management of amyloidosis patients.
49
CUTILLAS, Pedro R., Anthony G. W. NORDEN, Rainer CRAMER, Alma L. BURLINGAME, and Robert J. UNWIN. "Detection and analysis of urinary peptides by on-line liquid chromatography and mass spectrometry: application to patients with renal Fanconi syndrome." Clinical Science 104, no. 5 (May 1, 2003): 483–90. http://dx.doi.org/10.1042/cs20020342.
Full textAbstract:
Urinary proteomics has become a topical and potentially valuable field of study in relation to normal and abnormal renal function. Filtered bioactive peptides present in high concentration in the nephron of patients with tubular proteinuria may have downstream effects on renal tubular function. In renal Fanconi syndromes, such as Dent's disease, peptides implicated in altered tubular function or injury have recently been measured in urine by immunochemical methods. However, the limited availability of antibodies means that only certain peptides can be detected in this way. We have used nanoflow liquid chromatography and tandem mass spectrometry (nanoLC-MS/MS) as a complementary technique to analyse urinary peptides. Urine was desalted by solid-phase extraction (SPE) and its peptides were then separated from neutral and acidic compounds by strong cation-exchange chromatography (SCX), which was also used to fractionate the peptide mixture. Fractions from the SCX step were separated further by reversed-phase LC and analysed on-line by MS/MS. Extraction by SPE showed a good recovery of small peptides. We detected over 100 molecular species in urine samples from three individuals with Dent's disease. In addition to plasma and known urinary proteins, we identified some novel proteins and potentially bioactive peptides in urine from these patients, which were not present in normal urine. These data show that nanoLC-MS/MS complements existing techniques for the identification of polypeptides in urine. This approach is a potentially powerful tool to discover new markers and/or causative factors in renal disease; in addition, its sensitivity may also make it applicable to the direct ultramicroanalysis of renal tubule fluid.
50
Zhang, Yaqiong, Zhiping Jia, Yunyang Liu, Xinwen Zhou, and Yi Kong. "Characterization of Venoms of Deinagkistrodon acutus and Bungarus multicinctus Using Proteomics and Peptidomics." Current Proteomics 17, no. 3 (March 24, 2020): 241–54. http://dx.doi.org/10.2174/1570164617666191121112319.
Full textAbstract:
Background: Deinagkistrodon acutus (D. acutus) and Bungarus multicinctus (B. multicinctus) as traditional medicines have been used for hundreds of years in China. The venoms of these two species have strong toxicity on the victims. Objective: The objective of this study is to reveal the profile of venom proteins and peptides of D. acutus and B. multicinctus. Method: Ultrafiltration, SDS-PAGE coupled with in-gel tryptic digestion and Liquid Chromatography- Electrospray Ionization-Tandem Mass Spectrometry (LC-ESI-MS/MS) were used to characterize proteins and peptides of venoms of D. acutus and B. multicinctus. Results: In the D. acutus venom, 67 proteins (16 protein families) were identified, and snake venom metalloproteinases (SVMPs, 38.0%) and snake venom C-type lectins (snaclecs, 36.7%) were dominated proteins. In the B. multicinctus venom, 47 proteins (15 protein families) were identified, and three-finger toxins (3FTxs, 36.3%) and Kunitz-type Serine Protease Inhibitors (KSPIs, 32.8%) were major components. In addition, both venoms contained small amounts of other proteins, such as Snake Venom Serine Proteinases (SVSPs), Phospholipases A2 (PLA2s), Cysteine-Rich Secreted Proteins (CRISPs), 5'nucleotidases (5'NUCs), Phospholipases B (PLBs), Phosphodiesterases (PDEs), Phospholipase A2 Inhibitors (PLIs), Dipeptidyl Peptidases IV (DPP IVs), L-amino Acid Oxidases (LAAOs) and Angiotensin-Converting Enzymes (ACEs). Each venom also had its unique proteins, Nerve Growth Factors (NGFs) and Hyaluronidases (HYs) in D. acutus, and Cobra Venom Factors (CVFs) in B. multicinctus. In the peptidomics, 1543 and 250 peptides were identified in the venoms of D. acutus and B. multicinctus, respectively. Some peptides showed high similarity with neuropeptides, ACE inhibitory peptides, Bradykinin- Potentiating Peptides (BPPs), LAAOs and movement related peptides. Conclusion: Characterization of venom proteins and peptides of D. acutus and B. multicinctus will be helpful for the treatment of envenomation and drug discovery.