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Journal articles on the topic 'Proteome proteomics'
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1
Krieg, Rene C., Cloud P. Paweletz, Lance A. Liotta, and Emanuel F. Petricoin. "Clinical Proteomics for Cancer Biomarker Discovery and Therapeutic Targeting." Technology in Cancer Research & Treatment 1, no. 4 (August 2002): 263–72. http://dx.doi.org/10.1177/153303460200100407.
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As we emerge into the post-genome era, proteomics finds itself as the driving force field as we translate the nucleic acid information archive into understanding how the cell actually works and how disease processes operate. Even so, the traditionally held view of proteomics as simply cataloging and developing lists of the cellular protein repertoire of a cell are now changing, especially in the sub-discipline of clinical proteomics. The most relevant information archive to clinical applications and drug development involves the elucidation of the information flow of the cell; the “software” of protein pathway networks and circuitry. The deranged circuitry of the cell as the drug target itself as well as the effect of the drug on not just the target, but also the entire network, is what we now are striving towards. Clinical proteomics, as a new and most exciting sub-discipline of proteomics, involves the bench-to-bedside clinical application of proteomic tools. Unlike the genome, there are potentially thousands of proteomes: each cell type has its own unique proteome. Moreover, each cell type can alter its proteome depending on the unique tissue microenvironment in which it resides, giving rise to multiple permutations of a single proteome. Since there is no polymerase chain reaction equivalent to proteomics- identifying and discovering the “wiring diagram” of a human diseased cell in a biopsy specimen remains a daunting challenge. New micro-proteomic technologies are being and still need to be developed to drill down into the proteomes of clinically relevant material. Cancer, as a model disease, provides a fertile environment to study the application of proteomics at the bedside. The promise of clinical proteomics and the new technologies that are developed is that we will detect cancer earlier through discovery of biomarkers, we will discover the next generation of targets and imaging biomarkers, and we can then apply this knowledge to patient-tailored therapy.
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Thanasupawat, Thatchawan, Aleksandra Glogowska, Christopher Pascoe, Sai Nivedita Krishnan, Maliha Munir, Farhana Begum, Jason Beiko, et al. "Slow Off-Rate Modified Aptamer (SOMAmer) Proteomic Analysis of Patient-Derived Malignant Glioma Identifies Distinct Cellular Proteomes." International Journal of Molecular Sciences 22, no. 17 (September 3, 2021): 9566. http://dx.doi.org/10.3390/ijms22179566.
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Malignant gliomas derive from brain glial cells and represent >75% of primary brain tumors. This includes anaplastic astrocytoma (grade III; AS), the most common and fatal glioblastoma multiforme (grade IV; GBM), and oligodendroglioma (ODG). We have generated patient-derived AS, GBM, and ODG cell models to study disease mechanisms and test patient-centered therapeutic strategies. We have used an aptamer-based high-throughput SOMAscan® 1.3K assay to determine the proteomic profiles of 1307 different analytes. SOMAscan® proteomes of AS and GBM self-organized into closely adjacent proteomes which were clearly distinct from ODG proteomes. GBM self-organized into four proteomic clusters of which SOMAscan® cluster 4 proteome predicted a highly inter-connected proteomic network. Several up- and down-regulated proteins relevant to glioma were successfully validated in GBM cell isolates across different SOMAscan® clusters and in corresponding GBM tissues. Slow off-rate modified aptamer proteomics is an attractive analytical tool for rapid proteomic stratification of different malignant gliomas and identified cluster-specific SOMAscan® signatures and functionalities in patient GBM cells.
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Sadeesh, Nithin, Mauro Scaravilli, and Leena Latonen. "Proteomic Landscape of Prostate Cancer: The View Provided by Quantitative Proteomics, Integrative Analyses, and Protein Interactomes." Cancers 13, no. 19 (September 27, 2021): 4829. http://dx.doi.org/10.3390/cancers13194829.
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Prostate cancer is the second most frequent cancer of men worldwide. While the genetic landscapes and heterogeneity of prostate cancer are relatively well-known already, methodological developments now allow for studying basic and dynamic proteomes on a large scale and in a quantitative fashion. This aids in revealing the functional output of cancer genomes. It has become evident that not all aberrations at the genetic and transcriptional level are translated to the proteome. In addition, the proteomic level contains heterogeneity, which increases as the cancer progresses from primary prostate cancer (PCa) to metastatic and castration-resistant prostate cancer (CRPC). While multiple aspects of prostate adenocarcinoma proteomes have been studied, less is known about proteomes of neuroendocrine prostate cancer (NEPC). In this review, we summarize recent developments in prostate cancer proteomics, concentrating on the proteomic landscapes of clinical prostate cancer, cell line and mouse model proteomes interrogating prostate cancer-relevant signaling and alterations, and key prostate cancer regulator interactomes, such as those of the androgen receptor (AR). Compared to genomic and transcriptomic analyses, the view provided by proteomics brings forward changes in prostate cancer metabolism, post-transcriptional RNA regulation, and post-translational protein regulatory pathways, requiring the full attention of studies in the future.
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Burat, Bastien, Audrey Reynaerts, Dominique Baiwir, Maximilien Fléron, Gauthier Eppe, Teresinha Leal, and Gabriel Mazzucchelli. "Characterization of the Human Eccrine Sweat Proteome—A Focus on the Biological Variability of Individual Sweat Protein Profiles." International Journal of Molecular Sciences 22, no. 19 (October 8, 2021): 10871. http://dx.doi.org/10.3390/ijms221910871.
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The potential of eccrine sweat as a bio-fluid of interest for diagnosis and personalized therapy has not yet been fully evaluated, due to the lack of in-depth sweat characterization studies. Thanks to recent developments in omics, together with the availability of accredited sweat collection methods, the analysis of human sweat may now be envisioned as a standardized, non-invasive test for individualized monitoring and personalized medicine. Here, we characterized individual sweat samples, collected from 28 healthy adult volunteers under the most standardized sampling methodology, by applying optimized shotgun proteomics. The thorough characterization of the sweat proteome allowed the identification of 983 unique proteins from which 344 were identified across all samples. Annotation-wise, the study of the sweat proteome unveiled the over-representation of newly addressed actin dynamics, oxidative stress and proteasome-related functions, in addition to well-described proteolysis and anti-microbial immunity. The sweat proteome composition correlated with the inter-individual variability of sweat secretion parameters. In addition, both gender-exclusive proteins and gender-specific protein abundances were highlighted, despite the high similarity between human female and male sweat proteomes. In conclusion, standardized sample collection coupled with optimized shotgun proteomics significantly improved the depth of sweat proteome coverage, far beyond previous similar studies. The identified proteins were involved in many diverse biological processes and molecular functions, indicating the potential of this bio-fluid as a valuable biological matrix for further studies. Addressing sweat variability, our results prove the proteomic profiling of sweat to be a promising bio-fluid analysis for individualized, non-invasive monitoring and personalized medicine.
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Senavirathna, Lakmini, Cheng Ma, Ru Chen, and Sheng Pan. "Spectral Library-Based Single-Cell Proteomics Resolves Cellular Heterogeneity." Cells 11, no. 15 (August 7, 2022): 2450. http://dx.doi.org/10.3390/cells11152450.
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Dissecting the proteome of cell types and states at single-cell resolution, while being highly challenging, has significant implications in basic science and biomedicine. Mass spectrometry (MS)-based single-cell proteomics represents an emerging technology for system-wide, unbiased profiling of proteins in single cells. However, significant challenges remain in analyzing an extremely small amount of proteins collected from a single cell, as a proteome-wide amplification of proteins is not currently feasible. Here, we report an integrated spectral library-based single-cell proteomics (SLB-SCP) platform that is ultrasensitive and well suited for a large-scale analysis. To overcome the low MS/MS signal intensity intrinsically associated with a single-cell analysis, this approach takes an alternative approach by extracting a breadth of information that specifically defines the physicochemical characteristics of a peptide from MS1 spectra, including monoisotopic mass, isotopic distribution, and retention time (hydrophobicity), and uses a spectral library for proteomic identification. This conceptually unique MS platform, coupled with the DIRECT sample preparation method, enabled identification of more than 2000 proteins in a single cell to distinguish different proteome landscapes associated with cellular types and heterogeneity. We characterized individual normal and cancerous pancreatic ductal cells (HPDE and PANC-1, respectively) and demonstrated the substantial difference in the proteomes between HPDE and PANC-1 at the single-cell level. A significant upregulation of multiple protein networks in cancer hallmarks was identified in the PANC-1 cells, functionally discriminating the PANC-1 cells from the HPDE cells. This integrated platform can be built on high-resolution MS and widely accepted proteomic software, making it possible for community-wide applications.
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Solovyeva, Elizaveta M., Julia A. Bubis, Irina A. Tarasova, Anna A. Lobas, Mark V. Ivanov, Alexey A. Nazarov, Ilya A. Shutkov, and Mikhail V. Gorshkov. "On the Feasibility of Using an Ultra-Fast DirectMS1 Method of Proteome-Wide Analysis for Searching Drug Targets in Chemical Proteomics." Biochemistry (Moscow) 87, no. 11 (November 2022): 1342–53. http://dx.doi.org/10.1134/s000629792211013x.
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Abstract Protein quantitation in tissue cells or physiological fluids based on liquid chromatography/mass spectrometry is one of the key sources of information on the mechanisms of cell functioning during chemotherapeutic treatment. Information on significant changes in protein expression upon treatment can be obtained by chemical proteomics and requires analysis of the cellular proteomes, as well as development of experimental and bioinformatic methods for identification of the drug targets. Low throughput of whole proteome analysis based on liquid chromatography and tandem mass spectrometry is one of the main factors limiting the scale of these studies. The method of direct mass spectrometric identification of proteins, DirectMS1, is one of the approaches developed in recent years allowing ultrafast proteome-wide analyses employing minute-scale gradients for separation of proteolytic mixtures. Aim of this work was evaluation of both possibilities and limitations of the method for identification of drug targets at the level of whole proteome and for revealing cellular processes activated by the treatment. Particularly, the available literature data on chemical proteomics obtained earlier for a large set of onco-pharmaceuticals using multiplex quantitative proteome profiling were analyzed. The results obtained were further compared with the proteome-wide data acquired by the DirectMS1 method using ultrashort separation gradients to evaluate efficiency of the method in identifying known drug targets. Using ovarian cancer cell line A2780 as an example, a whole-proteome comparison of two cell lysis techniques was performed, including the freeze-thaw lysis commonly employed in chemical proteomics and the one based on ultrasonication for cell disruption, which is the widely accepted as a standard in proteomic studies. Also, the proteome-wide profiling was performed using ultrafast DirectMS1 method for A2780 cell line treated with lonidamine, followed by gene ontology analyses to evaluate capabilities of the method in revealing regulation of proteins in the cellular processes associated with drug treatment.
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Masood, Afshan, Hicham Benabdelkamel, and Assim Alfadda. "Obesity Proteomics: An Update on the Strategies and Tools Employed in the Study of Human Obesity." High-Throughput 7, no. 3 (September 12, 2018): 27. http://dx.doi.org/10.3390/ht7030027.
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Proteomics has become one of the most important disciplines for characterizing cellular protein composition, building functional linkages between protein molecules, and providing insight into the mechanisms of biological processes in a high-throughput manner. Mass spectrometry-based proteomic advances have made it possible to study human diseases, including obesity, through the identification and biochemical characterization of alterations in proteins that are associated with it and its comorbidities. A sizeable number of proteomic studies have used the combination of large-scale separation techniques, such as high-resolution two-dimensional gel electrophoresis or liquid chromatography in combination with mass spectrometry, for high-throughput protein identification. These studies have applied proteomics to comprehensive biochemical profiling and comparison studies while using different tissues and biological fluids from patients to demonstrate the physiological or pathological adaptations within their proteomes. Further investigations into these proteome-wide alterations will enable us to not only understand the disease pathophysiology, but also to determine signature proteins that can serve as biomarkers for obesity and related diseases. This review examines the different proteomic techniques used to study human obesity and discusses its successful applications along with its technical limitations.
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Oikonomou, Panos, Roberto Salatino, and Saeed Tavazoie. "In vivo mRNA display enables large-scale proteomics by next generation sequencing." Proceedings of the National Academy of Sciences 117, no. 43 (October 9, 2020): 26710–18. http://dx.doi.org/10.1073/pnas.2002650117.
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Large-scale proteomic methods are essential for the functional characterization of proteins in their native cellular context. However, proteomics has lagged far behind genomic approaches in scalability, standardization, and cost. Here, we introduce in vivo mRNA display, a technology that converts a variety of proteomics applications into a DNA sequencing problem. In vivo-expressed proteins are coupled with their encoding messenger RNAs (mRNAs) via a high-affinity stem-loop RNA binding domain interaction, enabling high-throughput identification of proteins with high sensitivity and specificity by next generation DNA sequencing. We have generated a high-coverage in vivo mRNA display library of the Saccharomyces cerevisiae proteome and demonstrated its potential for characterizing subcellular localization and interactions of proteins expressed in their native cellular context. In vivo mRNA display libraries promise to circumvent the limitations of mass spectrometry-based proteomics and leverage the exponentially improving cost and throughput of DNA sequencing to systematically characterize native functional proteomes.
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Stubbs, Keith A., and David J. Vocadlo. "Affinity-Based Proteomics Probes; Tools for Studying Carbohydrate-Processing Enzymes." Australian Journal of Chemistry 62, no. 6 (2009): 521. http://dx.doi.org/10.1071/ch09140.
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As more information becomes available through the efforts of high-throughput screens, there is increasing pressure on the three main ‘omic’ fields, genomics, proteomics, and metabolomics, to organize this material into useful libraries that enable further understanding of biological systems. Proteomics especially is faced with two highly challenging tasks. The first is assigning the activity of thousands of putative proteins, the existence of which has been suggested by genomics studies. The second is to serve as a link between genomics and metabolomics by demonstrating which enzymes play roles in specific metabolic pathways. Underscoring these challenges in one area are the thousands of putative carbohydrate-processing enzymes that have been bioinformatically identified, mostly in prokaryotes, but that have unknown or unverified activities. Using two brief examples, we illustrate how biochemical pathways within bacteria that involve carbohydrate-processing enzymes present interesting potential antimicrobial targets, offering a clear motivation for gaining a functional understanding of biological proteomes. One method for studying proteomes that has been developed recently is to use synthetic compounds termed activity-based proteomics probes. Activity-based proteomic profiling using such probes facilitates rapid identification of enzyme activities within proteomes and assignment of function to putative enzymes. Here we discuss the general design principles for these probes with particular reference to carbohydrate-processing enzymes and give an example of using such a probe for the profiling of a bacterial proteome.
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Tjalsma, Harold, Haike Antelmann, Jan D. H. Jongbloed, Peter G. Braun, Elise Darmon, Ronald Dorenbos, Jean-Yves F. Dubois, et al. "Proteomics of Protein Secretion by Bacillus subtilis: Separating the “Secrets” of the Secretome." Microbiology and Molecular Biology Reviews 68, no. 2 (June 2004): 207–33. http://dx.doi.org/10.1128/mmbr.68.2.207-233.2004.
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SUMMARY Secretory proteins perform a variety of important“ remote-control” functions for bacterial survival in the environment. The availability of complete genome sequences has allowed us to make predictions about the composition of bacterial machinery for protein secretion as well as the extracellular complement of bacterial proteomes. Recently, the power of proteomics was successfully employed to evaluate genome-based models of these so-called secretomes. Progress in this field is well illustrated by the proteomic analysis of protein secretion by the gram-positive bacterium Bacillus subtilis, for which ∼90 extracellular proteins were identified. Analysis of these proteins disclosed various“ secrets of the secretome,” such as the residence of cytoplasmic and predicted cell envelope proteins in the extracellular proteome. This showed that genome-based predictions reflect only∼ 50% of the actual composition of the extracellular proteome of B. subtilis. Importantly, proteomics allowed the first verification of the impact of individual secretion machinery components on the total flow of proteins from the cytoplasm to the extracellular environment. In conclusion, proteomics has yielded a variety of novel leads for the analysis of protein traffic in B. subtilis and other gram-positive bacteria. Ultimately, such leads will serve to increase our understanding of virulence factor biogenesis in gram-positive pathogens, which is likely to be of high medical relevance.
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Gerszten, Robert E., Frank Accurso, Gordon R. Bernard, Richard M. Caprioli, Eric W. Klee, George G. Klee, Iftikhar Kullo, et al. "Challenges in translating plasma proteomics from bench to bedside: update from the NHLBI Clinical Proteomics Programs." American Journal of Physiology-Lung Cellular and Molecular Physiology 295, no. 1 (July 2008): L16—L22. http://dx.doi.org/10.1152/ajplung.00044.2008.
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The emerging scientific field of proteomics encompasses the identification, characterization, and quantification of the protein content or proteome of whole cells, tissues, or body fluids. The potential for proteomic technologies to identify and quantify novel proteins in the plasma that can function as biomarkers of the presence or severity of clinical disease states holds great promise for clinical use. However, there are many challenges in translating plasma proteomics from bench to bedside, and relatively few plasma biomarkers have successfully transitioned from proteomic discovery to routine clinical use. Key barriers to this translation include the need for “orthogonal” biomarkers (i.e., uncorrelated with existing markers), the complexity of the proteome in biological samples, the presence of high abundance proteins such as albumin in biological samples that hinder detection of low abundance proteins, false positive associations that occur with analysis of high dimensional datasets, and the limited understanding of the effects of growth, development, and age on the normal plasma proteome. Strategies to overcome these challenges are discussed.
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Lapinel, Nicole, Jessie Guidry, Mary Varkey, Manish Rijal, Arnold Zea, and Juzar Ali. "76215 Implementation of Proteomics as a Diagnostic tool for Nontuberculous mycobacteria (NTM) Infection." Journal of Clinical and Translational Science 5, s1 (March 2021): 140–41. http://dx.doi.org/10.1017/cts.2021.759.
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ABSTRACT IMPACT: Implementation of proteomics as a diagnostic tool for Nontuberculous mycobacteria (NTM) infection can provide a more accurate, efficient and cost-effective means for effectively diagnosing disease and enacting timely management decisions which can revolutionize patient care. OBJECTIVES/GOALS: Proteomic analysis is a proven diagnostic modality enabling rapid identification of microorganisms. We sought to apply proteomics to detect proteins unique to the most clinically relevant NTM. We then determined whether these unique proteomes could be used to successfully identify NTM species from in vitro cocktail preparations. METHODS/STUDY POPULATION: NTM reference strains for M. avium, m. intracellulare, m.chimaera, m. abscessus abscessus, m. abscessus massiliense and m. abscessus boletti were cultured in vitro and subjected to proteomic analysis using Liquid Chromatography tandem-Mass Spectrometry (LCMS). Tandem Mass Tag (TMT) data acquisition utilized an MS3 approach for data collection using Proteome Discoverer 2.4.A comparative analysis of the proteome of each of these six species was performed quantitatively using LCMS. The process was repeated for three technical replicates and analyzed using the SEQUEST algorithm. Only high scoring peptides were considered utilizing a false discovery rate (FDR) of 1%. Once species-specific proteins were identified, we validated detection in individual and mixed samples of the six reference strains. RESULTS/ANTICIPATED RESULTS: The proteomic profiling of the six NTM reference strains successfully demonstrated proteins unique to each of the MAC species and MABC subspecies. Proteomic MAC species analysis produced between 327 to 2,540 unique peptides for each of the 3 species. MABC proteomic analysis identified between 17-74 unique peptides for each of the 3 subspecies. Fifteen different mixed preparations of MAC and MABC were then subjected to LCMS analysis and compared against the proteome profiles already curated for the six strains. We accurately identified at least one NTM in the majority of the samples (10/15). In three samples (3/15), the NTM was not correctly identified; in two of the samples (2/15) we were unable to determine the identity of NTM within the preparation. Further database curation will be performed to hone these results. DISCUSSION/SIGNIFICANCE OF FINDINGS: Proteomic analysis of in vitro reference strains successfully demonstrated protein fingerprints specific to six common disease-causing strains of NTM. Such findings can be used to evaluate clinical samples enabling more efficient diagnostic specificity. Further research will focus on identification of NTM in sputum samples of infected patients.
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Pruess, Manuela, and Rolf Apweiler. "Bioinformatics Resources for In Silico Proteome Analysis." Journal of Biomedicine and Biotechnology 2003, no. 4 (2003): 231–36. http://dx.doi.org/10.1155/s1110724303209219.
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In the growing field of proteomics, tools for the in silico analysis of proteins and even of whole proteomes are of crucial importance to make best use of the accumulating amount of data. To utilise this data for healthcare and drug development, first the characteristics of proteomes of entire species—mainly the human—have to be understood, before secondly differentiation between individuals can be surveyed. Specialised databases about nucleic acid sequences, protein sequences, protein tertiary structure, genome analysis, and proteome analysis represent useful resources for analysis, characterisation, and classification of protein sequences. Different from most proteomics tools focusing on similarity searches, structure analysis and prediction, detection of specific regions, alignments, data mining, 2D PAGE analysis, or protein modelling, respectively, comprehensive databases like the proteome analysis database benefit from the information stored in different databases and make use of different protein analysis tools to provide computational analysis of whole proteomes.
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Unwin, Richard D., Duncan L. Smith, David Blinco, Claire L. Wilson, Crispin J. Miller, Caroline A. Evans, Ewa Jaworska, et al. "Quantitative proteomics reveals posttranslational control as a regulatory factor in primary hematopoietic stem cells." Blood 107, no. 12 (June 15, 2006): 4687–94. http://dx.doi.org/10.1182/blood-2005-12-4995.
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Abstract The proteome is determined by rates of transcription, translation, and protein turnover. Definition of stem cell populations therefore requires a stem cell proteome signature. However, the limit to the number of primary cells available has restricted extensive proteomic analysis. We present a mass spectrometric method using an isobaric covalent modification of peptides for relative quantification (iTRAQ), which was employed to compare the proteomes of approximately 1 million long-term reconstituting hematopoietic stem cells (Lin–Sca+Kit+; LSK+) and non–long-term reconstituting progenitor cells (Lin–Sca+Kit–; LSK–), respectively. Extensive 2-dimensional liquid chromatography (LC) peptide separation prior to mass spectrometry (MS) enabled enhanced proteome coverage with relative quantification of 948 proteins. Of the 145 changes in the proteome, 54% were not seen in the transcriptome. Hypoxia-related changes in proteins controlling metabolism and oxidative protection were observed, indicating that LSK+ cells are adapted for anaerobic environments. This approach can define proteomic changes in primary samples, thereby characterizing the molecular signature of stem cells and their progeny.
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Jenkins, Conor, and Benjamin Orsburn. "The Cannabis Proteome Draft Map Project." International Journal of Molecular Sciences 21, no. 3 (January 31, 2020): 965. http://dx.doi.org/10.3390/ijms21030965.
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Recently we have seen a relaxation of the historic restrictions on the use and subsequent research on the Cannabis plants, generally classified as Cannabis sativa and Cannabis indica. What research has been performed to date has centered on chemical analysis of plant flower products, namely cannabinoids and various terpenes that directly contribute to phenotypic characteristics of the female flowers. In addition, we have seen many groups recently completing genetic profiles of various plants of commercial value. To date, no comprehensive attempt has been made to profile the proteomes of these plants. We report herein our progress on constructing a comprehensive draft map of the Cannabis proteome. To date we have identified over 17,000 potential protein sequences. Unfortunately, no annotated genome of Cannabis plants currently exists. We present a method by which “next generation” DNA sequencing output and shotgun proteomics data can be combined to produce annotated FASTA files, bypassing the need for annotated genetic information altogether in traditional proteomics workflows. The resulting material represents the first comprehensive annotated protein FASTA for any Cannabis plant. Using this annotated database as reference we can refine our protein identifications, resulting in the confident identification of 13,000 proteins with putative function. Furthermore, we demonstrate that post-translational modifications play an important role in the proteomes of Cannabis flower, particularly lysine acetylation and protein glycosylation. To facilitate the evolution of analytical investigations into these plant materials, we have created a portal to host resources developed from our proteomic and metabolomic analysis of Cannabis plant material as well as our results integrating these resources.
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Yaacob, Mohamad Fakhri, Nur Anisah Johari, Alya Nur Athirah Kamaruzzaman, and Mohd Fakharul Zaman Raja Yahya. "Mass Spectrometry-Based Proteomic Investigation of Heterogeneous Biofilms: A Review." Scientific Research Journal 18, no. 2 (September 1, 2021): 67–87. http://dx.doi.org/10.24191/srj.v18i2.11718.
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Biofilm represents a major public health concern. It is a highly structured and heterogeneous microbial population that is well protected by a hydrated extracellular matrix. In most cases, the difficulties in combating a wide spectrum of biofilm-associated diseases are due to the presence of dormant cells and differential molecular expression. Proteomics is the large-scale and systematic study of cellular proteome expression at any given time by mass spectrometry. It allows high-sensitivity and high-specificity identification of differentially expressed proteins in the biofilms. Over the past few decades, multiple lines of proteomic works have successfully elucidated various aspects of the biofilm including developmental stages, antimicrobial resistance, and survival mechanisms. However, the heterogeneity of biofilms may contribute to inconsistent proteome expression throughout a proteomic experiment. This is due to the fact that the mature biofilm is often associated with the mixture between monolayer and multilayer biofilms, thick microbial population, and chemical gradient of nutrients. This review highlights the biofilm heterogeneities, the principle of mass spectrometry in proteomics, and the possible strategies for quantitative proteomic analysis of heterogeneous biofilms. It is suggested that isolation of monolayer biofilm, laser capture microdissection, flow cytometry, and subtractive proteome profiling may be considered for an accurate and reliable quantitative proteomics experiment.
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Zhan, Xianquan, Biao Li, Xiaohan Zhan, Hartmut Schlüter, Peter R. Jungblut, and Jens R. Coorssen. "Innovating the Concept and Practice of Two-Dimensional Gel Electrophoresis in the Analysis of Proteomes at the Proteoform Level." Proteomes 7, no. 4 (October 30, 2019): 36. http://dx.doi.org/10.3390/proteomes7040036.
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Two-dimensional gel electrophoresis (2DE) is an important and well-established technical platform enabling extensive top-down proteomic analysis. However, the long-held but now largely outdated conventional concepts of 2DE have clearly impacted its application to in-depth investigations of proteomes at the level of protein species/proteoforms. It is time to popularize a new concept of 2DE for proteomics. With the development and enrichment of the proteome concept, any given “protein” is now recognized to consist of a series of proteoforms. Thus, it is the proteoform, rather than the canonical protein, that is the basic unit of a proteome, and each proteoform has a specific isoelectric point (pI) and relative mass (Mr). Accordingly, using 2DE, each proteoform can routinely be resolved and arrayed according to its different pI and Mr. Each detectable spot contains multiple proteoforms derived from the same gene, as well as from different genes. Proteoforms derived from the same gene are distributed into different spots in a 2DE pattern. High-resolution 2DE is thus actually an initial level of separation to address proteome complexity and is effectively a pre-fractionation method prior to analysis using mass spectrometry (MS). Furthermore, stable isotope-labeled 2DE coupled with high-sensitivity liquid chromatography-tandem MS (LC-MS/MS) has tremendous potential for the large-scale detection, identification, and quantification of the proteoforms that constitute proteomes.
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Poetsch, Ansgar, and María Inés Marchesini. "Proteomics of Brucella." Proteomes 8, no. 2 (April 22, 2020): 8. http://dx.doi.org/10.3390/proteomes8020008.
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Brucella spp. are Gram negative intracellular bacteria responsible for brucellosis, a worldwide distributed zoonosis. A prominent aspect of the Brucella life cycle is its ability to invade, survive and multiply within host cells. Comprehensive approaches, such as proteomics, have aided in unravelling the molecular mechanisms underlying Brucella pathogenesis. Technological and methodological advancements such as increased instrument performance and multiplexed quantification have broadened the range of proteome studies, enabling new and improved analyses, providing deeper and more accurate proteome coverage. Indeed, proteomics has demonstrated its contribution to key research questions in Brucella biology, i.e., immunodominant proteins, host-cell interaction, stress response, antibiotic targets and resistance, protein secretion. Here, we review the proteomics of Brucella with a focus on more recent works and novel findings, ranging from reconfiguration of the intracellular bacterial proteome and studies on proteomic profiles of Brucella infected tissues, to the identification of Brucella extracellular proteins with putative roles in cell signaling and pathogenesis. In conclusion, proteomics has yielded copious new candidates and hypotheses that require future verification. It is expected that proteomics will continue to be an invaluable tool for Brucella and applications will further extend to the currently ill-explored aspects including, among others, protein processing and post-translational modification.
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Kozlowski, Lukasz Pawel. "Proteome-pI 2.0: proteome isoelectric point database update." Nucleic Acids Research 50, no. D1 (October 28, 2021): D1535—D1540. http://dx.doi.org/10.1093/nar/gkab944.
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Abstract Proteome-pI 2.0 is an update of an online database containing predicted isoelectric points and pKa dissociation constants of proteins and peptides. The isoelectric point—the pH at which a particular molecule carries no net electrical charge—is an important parameter for many analytical biochemistry and proteomics techniques. Additionally, it can be obtained directly from the pKa values of individual charged residues of the protein. The Proteome-pI 2.0 database includes data for over 61 million protein sequences from 20 115 proteomes (three to four times more than the previous release). The isoelectric point for proteins is predicted by 21 methods, whereas pKa values are inferred by one method. To facilitate bottom-up proteomics analysis, individual proteomes were digested in silico with the five most commonly used proteases (trypsin, chymotrypsin, trypsin + LysC, LysN, ArgC), and the peptides’ isoelectric point and molecular weights were calculated. The database enables the retrieval of virtual 2D-PAGE plots and customized fractions of a proteome based on the isoelectric point and molecular weight. In addition, isoelectric points for proteins in NCBI non-redundant (nr), UniProt, SwissProt, and Protein Data Bank are available in both CSV and FASTA formats. The database can be accessed at http://isoelectricpointdb2.org.
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Zecha, Jana, Chien-Yun Lee, Florian P. Bayer, Chen Meng, Vincent Grass, Johannes Zerweck, Karsten Schnatbaum, et al. "Data, Reagents, Assays and Merits of Proteomics for SARS-CoV-2 Research and Testing." Molecular & Cellular Proteomics 19, no. 9 (June 26, 2020): 1503–22. http://dx.doi.org/10.1074/mcp.ra120.002164.
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As the COVID-19 pandemic continues to spread, thousands of scientists around the globe have changed research direction to understand better how the virus works and to find out how it may be tackled. The number of manuscripts on preprint servers is soaring and peer-reviewed publications using MS-based proteomics are beginning to emerge. To facilitate proteomic research on SARS-CoV-2, the virus that causes COVID-19, this report presents deep-scale proteomes (10,000 proteins; >130,000 peptides) of common cell line models, notably Vero E6, Calu-3, Caco-2, and ACE2-A549 that characterize their protein expression profiles including viral entry factors such as ACE2 or TMPRSS2. Using the 9 kDa protein SRP9 and the breast cancer oncogene BRCA1 as examples, we show how the proteome expression data can be used to refine the annotation of protein-coding regions of the African green monkey and the Vero cell line genomes. Monitoring changes of the proteome on viral infection revealed widespread expression changes including transcriptional regulators, protease inhibitors, and proteins involved in innate immunity. Based on a library of 98 stable-isotope labeled synthetic peptides representing 11 SARS-CoV-2 proteins, we developed PRM (parallel reaction monitoring) assays for nano-flow and micro-flow LC–MS/MS. We assessed the merits of these PRM assays using supernatants of virus-infected Vero E6 cells and challenged the assays by analyzing two diagnostic cohorts of 24 (+30) SARS-CoV-2 positive and 28 (+9) negative cases. In light of the results obtained and including recent publications or manuscripts on preprint servers, we critically discuss the merits of MS-based proteomics for SARS-CoV-2 research and testing.
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Agarwal, Ashok, Manesh Kumar Panner Selvam, and Saradha Baskaran. "Proteomic Analyses of Human Sperm Cells: Understanding the Role of Proteins and Molecular Pathways Affecting Male Reproductive Health." International Journal of Molecular Sciences 21, no. 5 (February 27, 2020): 1621. http://dx.doi.org/10.3390/ijms21051621.
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Human sperm proteomics research has gained increasing attention lately, which provides complete information about the functional state of the spermatozoa. Changes in the sperm proteome are evident in several male infertility associated conditions. Global proteomic tools, such as liquid chromatography tandem mass spectrometry and matrix-assisted laser desorption/ionization time-of-flight, are used to profile the sperm proteins to identify the molecular pathways that are defective in infertile men. This review discusses the use of proteomic techniques to analyze the spermatozoa proteome. It also highlights the general steps involved in global proteomic approaches including bioinformatic analysis of the sperm proteomic data. Also, we have presented the findings of major proteomic studies and possible biomarkers in the diagnosis and therapeutics of male infertility. Extensive research on sperm proteome will help in understanding the role of fertility associated sperm proteins. Validation of the sperm proteins as biomarkers in different male infertility conditions may aid the physician in better clinical management.
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Balotf, Sadegh, Richard Wilson, Robert S. Tegg, David S. Nichols, and Calum R. Wilson. "Shotgun Proteomics as a Powerful Tool for the Study of the Proteomes of Plants, Their Pathogens, and Plant–Pathogen Interactions." Proteomes 10, no. 1 (January 19, 2022): 5. http://dx.doi.org/10.3390/proteomes10010005.
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The interaction between plants and pathogenic microorganisms is a multifaceted process mediated by both plant- and pathogen-derived molecules, including proteins, metabolites, and lipids. Large-scale proteome analysis can quantify the dynamics of proteins, biological pathways, and posttranslational modifications (PTMs) involved in the plant–pathogen interaction. Mass spectrometry (MS)-based proteomics has become the preferred method for characterizing proteins at the proteome and sub-proteome (e.g., the phosphoproteome) levels. MS-based proteomics can reveal changes in the quantitative state of a proteome and provide a foundation for understanding the mechanisms involved in plant–pathogen interactions. This review is intended as a primer for biologists that may be unfamiliar with the diverse range of methodology for MS-based shotgun proteomics, with a focus on techniques that have been used to investigate plant–pathogen interactions. We provide a summary of the essential steps required for shotgun proteomic studies of plants, pathogens and plant–pathogen interactions, including methods for protein digestion, identification, separation, and quantification. Finally, we discuss how protein PTMs may directly participate in the interaction between a pathogen and its host plant.
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Bespyatykh, Ju A., E. A. Shitikov, and E. N. Ilina. "Proteomics for the Investigation of Mycobacteria." Acta Naturae 9, no. 1 (March 15, 2017): 15–25. http://dx.doi.org/10.32607/20758251-2017-9-1-15-25.
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The physiology of Mycobacterium tuberculosis, the causative agent of tuberculosis, is being studied with intensity. However, despite the genomic and transcriptomic data available today, the pathogenic potential of these bacteria remains poorly understood. Therefore, proteomic approaches seem relevant in studying mycobacteria. This review covers the main stages in the proteomic analysis methods used to study mycobacteria. The main achievements in the area of M. tuberculosis proteomics are described in general. Special attention is paid to the proteomic features of the Beijing family, which is widespread in Russia. Considering that the proteome is a set of all the proteins in the cell, post-translational modifications of mycobacterium proteins are also described.
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Thelen, Jay J., and Ján A. Miernyk. "The proteomic future: where mass spectrometry should be taking us." Biochemical Journal 444, no. 2 (May 11, 2012): 169–81. http://dx.doi.org/10.1042/bj20110363.
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A newcomer to the -omics era, proteomics, is a broad instrument-intensive research area that has advanced rapidly since its inception less than 20 years ago. Although the ‘wet-bench’ aspects of proteomics have undergone a renaissance with the improvement in protein and peptide separation techniques, including various improvements in two-dimensional gel electrophoresis and gel-free or off-gel protein focusing, it has been the seminal advances in MS that have led to the ascension of this field. Recent improvements in sensitivity, mass accuracy and fragmentation have led to achievements previously only dreamed of, including whole-proteome identification, and quantification and extensive mapping of specific PTMs (post-translational modifications). With such capabilities at present, one might conclude that proteomics has already reached its zenith; however, ‘capability’ indicates that the envisioned goals have not yet been achieved. In the present review we focus on what we perceive as the areas requiring more attention to achieve the improvements in workflow and instrumentation that will bridge the gap between capability and achievement for at least most proteomes and PTMs. Additionally, it is essential that we extend our ability to understand protein structures, interactions and localizations. Towards these ends, we briefly focus on selected methods and research areas where we anticipate the next wave of proteomic advances.
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Campanati, Anna, Emanuela Martina, Federico Diotallevi, Giulia Radi, Andrea Marani, Davide Sartini, Monica Emanuelli, et al. "Saliva Proteomics as Fluid Signature of Inflammatory and Immune-Mediated Skin Diseases." International Journal of Molecular Sciences 22, no. 13 (June 29, 2021): 7018. http://dx.doi.org/10.3390/ijms22137018.
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Saliva is easy to access, non-invasive and a useful source of information useful for the diagnosis of serval inflammatory and immune-mediated diseases. Following the advent of genomic technologies and -omic research, studies based on saliva testing have rapidly increased and human salivary proteome has been partially characterized. As a proteomic protocol to analyze the whole saliva proteome is not currently available, the most common aim of the proteomic analysis is to discriminate between physiological and pathological conditions. The salivary proteome has been initially investigated in several diseases: oral squamous cell carcinoma and oral leukoplakia, chronic graft-versus-host disease, and Sjögren’s syndrome. Otherwise, salivary proteomics studies in the dermatological field are still in the initial phase, thus the aim of this review is to collect the best research evidence on the role of saliva proteomics analysis in immune-mediated skin diseases to understand the direction of research in this field. The results of PRISMA analysis reported herein suggest that human saliva analysis could provide significant data for the diagnosis and prognosis of several immune-mediated and inflammatory skin diseases in the next future.
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Gao, Xiaoguang, Dandan Zhao, Lin Wang, Yue Cui, Shijie Wang, Meng Lv, Fangbo Zang, and Ruitong Dai. "Proteomic Changes in Sarcoplasmic and Myofibrillar Proteins Associated with Color Stability of Ovine Muscle during Post-Mortem Storage." Foods 10, no. 12 (December 3, 2021): 2989. http://dx.doi.org/10.3390/foods10122989.
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The objective of this study was to investigate the proteomic characteristics for the sarcoplasmic and myofibrillar proteomes of M. longissimus lumborum (LL) and M. psoasmajor (PM) from Small-tailed Han Sheep. During post-mortem storage periods (1, 3, and 5 days), proteome analysis was applied to elucidate sarcoplasmic and myofibrillar protein changes in skeletal muscles with different color stability. Proteomic results revealed that the identified differentially abundant proteins were glycolytic enzymes, energy metabolism enzymes, chaperone proteins, and structural proteins. Through Pearson’s correlation analysis, a few of those identified proteins (Pyruvate kinase, Adenylate kinase isoenzyme 1, Creatine kinase M-type, and Carbonic anhydrase 3) were closely correlated to representative meat color parameters. Besides, bioinformatics analysis of differentially abundant proteins revealed that the proteins mainly participated in glycolysis and energy metabolism pathways. Some of these proteins may have the potential probability to be predictors of meat discoloration during post-mortem storage. Within the insight of proteomics, these results accumulated some basic theoretical understanding of the molecular mechanisms of meat discoloration.
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Bonomini, Mario, Luisa Pieroni, Maurizio Ronci, Vittorio Sirolli, and Andrea Urbani. "Blood Cell Proteomics in Chronic Kidney Disease." Open Urology & Nephrology Journal 11, no. 1 (July 31, 2018): 28–38. http://dx.doi.org/10.2174/1874303x01811010028.
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Background: The uremic syndrome mimes a systemic poisoning with the retention of numerous compounds which are normally removed by the kidney. The study of proteins and peptides, or proteomics, represents an important field of research for the investigation of blood and blood diseases. Methods and Materials: We focused our review on the results of proteomic investigations on blood cells of uremic patients with particular regard to the study of red blood cells, platelets, and monocytes. Results: In literature there are few, preliminary studies on platelets and monocytes while the knowledge on uremic erythrocytes is much wider. Proteomic investigations showed that erythrocyte membrane proteome of uremic patients, differs significantly from the proteome of healthy subjects, being characterized by an extensive remodeling which may influence visco-elastic properties of RBC such as deformability and involve diverse molecular pathways driving red blood cell signaling and removal. Conclusion: Proteomic technologies emerged as a useful tool in defining and characterizing both physiological and disease processes being able, among others, to give important insights into uremic anemia.
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Bhawal, Ruchika, Ann L. Oberg, Sheng Zhang, and Manish Kohli. "Challenges and Opportunities in Clinical Applications of Blood-Based Proteomics in Cancer." Cancers 12, no. 9 (August 27, 2020): 2428. http://dx.doi.org/10.3390/cancers12092428.
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Blood is a readily accessible biofluid containing a plethora of important proteins, nucleic acids, and metabolites that can be used as clinical diagnostic tools in diseases, including cancer. Like the on-going efforts for cancer biomarker discovery using the liquid biopsy detection of circulating cell-free and cell-based tumor nucleic acids, the circulatory proteome has been underexplored for clinical cancer biomarker applications. A comprehensive proteome analysis of human serum/plasma with high-quality data and compelling interpretation can potentially provide opportunities for understanding disease mechanisms, although several challenges will have to be met. Serum/plasma proteome biomarkers are present in very low abundance, and there is high complexity involved due to the heterogeneity of cancers, for which there is a compelling need to develop sensitive and specific proteomic technologies and analytical platforms. To date, liquid chromatography mass spectrometry (LC-MS)-based quantitative proteomics has been a dominant analytical workflow to discover new potential cancer biomarkers in serum/plasma. This review will summarize the opportunities of serum proteomics for clinical applications; the challenges in the discovery of novel biomarkers in serum/plasma; and current proteomic strategies in cancer research for the application of serum/plasma proteomics for clinical prognostic, predictive, and diagnostic applications, as well as for monitoring minimal residual disease after treatments. We will highlight some of the recent advances in MS-based proteomics technologies with appropriate sample collection, processing uniformity, study design, and data analysis, focusing on how these integrated workflows can identify novel potential cancer biomarkers for clinical applications.
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Mirza, Shama P., and Michael Olivier. "Methods and approaches for the comprehensive characterization and quantification of cellular proteomes using mass spectrometry." Physiological Genomics 33, no. 1 (March 2008): 3–11. http://dx.doi.org/10.1152/physiolgenomics.00292.2007.
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Proteomics has been proposed as one of the key technologies in the postgenomic era. So far, however, the comprehensive analysis of cellular proteomes has been a challenge because of the dynamic nature and complexity of the multitude of proteins in cells and tissues. Various approaches have been established for the analyses of proteins in a cell at a given state, and mass spectrometry (MS) has proven to be an efficient and versatile tool. MS-based proteomics approaches have significantly improved beyond the initial identification of proteins to comprehensive characterization and quantification of proteomes and their posttranslational modifications (PTMs). Despite these advances, there is still ongoing development of new technologies to profile and analyze cellular proteomes more completely and efficiently. In this review, we focus on MS-based techniques, describe basic approaches for MS-based profiling of cellular proteomes and analysis methods to identify proteins in complex mixtures, and discuss the different approaches for quantitative proteome analysis. Finally, we briefly discuss novel developments for the analysis of PTMs. Altered levels of PTM, sometimes in the absence of protein expression changes, are often linked to cellular responses and disease states, and the comprehensive analysis of cellular proteome would not be complete without the identification and quantification of the extent of PTMs of proteins.
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Matialu, Dewi D. L., Erwin G. Kristanto, and Johannis F. Mallo. "Proteomics sebagai Metode Identifikasi dalam Ilmu Kedokteran Forensik." Jurnal Biomedik:JBM 14, no. 1 (March 31, 2022): 61. http://dx.doi.org/10.35790/jbm.v14i1.37343.
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Abstract: DNA analysis is the gold standard in forensic identification, however there are some circumstances in which DNA has been degraded or uninformative that make proteomics has the potential to be an alternative method of forensic identification. This study used a literature review method using four databases (Pubmed, ScienceDirect, Proquest, and SpringerLink). The keywords used in the data search are Proteomics OR Analysis Proteome OR Protein-based Identification AND Forensic Identification. The data selection process using inclusion and exclusion criteria, resulted in 10 literatures (research article). There were 10 literatures that examine the implementation of proteomics as a method of identification in forensic cases using various samples such as hair, bone, muscle, blood plasma, body fluids, stomach content, organ fragments, vomit traces, nail scrapings, and fingerprints with significant research results. The development & implementation of proteomics as a method of forensic identification is currently undergoing several developments using spectrometry (MS) technology. With various significant research results, proteomics has great potential not only in identifying individuals, but in many other ways in forensic medicine.Keywords: Proteomics; Analysis Proteome; Protein-based Identification; Forensic IdentificationAbstrak: Analisis DNA merupakan gold standard dalam identifikasi forensik, tetapi ada beberapa keadaan dimana DNA sudah terdegradasi atau tidak informatif yang menjadikan proteomics berpotensi menjadi sebuah metode alternatif dalam identifikasi forensik. Penelitian ini menggunakan metode literature review dengan pencarian data menggunakan empat database (Pubmed, ScienceDirect, Proquest, dan SpringerLink). Kata kunci yang digunakan dalam pencarian adalah Proteomics OR Analysis Proteome OR Protein-based Identification AND Forensic Identification. Proses seleksi data dengan menggunakan kriteria inklusi dan ekslusi mendapatkan 10 literature (research article). Terdapat 10 literature yang meneliti tentang implementasi proteomics dalam proses identifikasi pada kasus forensik dengan menggunakan berbagai sampel seperti rambut, tulang, otot, plasma darah, cairan tubuh, zat dalam perut, fragmen organ, jejak muntah, kerokan kuku, dan sidik jari dengan hasil penelitian yang signifikan. Perkembangan & implementasi proteomics sebagai metode identifikasi forensik saat ini sudah mengalami beberapa perkembangan dengan menggunakan teknologi mass spectrometry (MS). Dengan berbagai hasil penelitian yang signifikan, maka proteomics memiliki potensi yang besar tidak hanya dalam mengidentifikasi individu, tetapi dalam berbagai hal lain dalam ilmu kedokteran forensik.Kata Kunci: Proteomik; Analisis Proteom; Identifikasi Berbasis Protein; Identifikasi Forensik
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Maxwell, Karen L., and Lori Frappier. "Viral Proteomics." Microbiology and Molecular Biology Reviews 71, no. 2 (June 2007): 398–411. http://dx.doi.org/10.1128/mmbr.00042-06.
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SUMMARY Viruses have long been studied not only for their pathology and associated disease but also as model systems for molecular processes and as tools for identifying important cellular regulatory proteins and pathways. Recent advances in mass spectrometry methods coupled with the development of proteomic approaches have greatly facilitated the detection of virion components, protein interactions in infected cells, and virally induced changes in the cellular proteome, resulting in a more comprehensive understanding of viral infection. In addition, a rapidly increasing number of high-resolution structures for viral proteins have provided valuable information on the mechanism of action of these proteins as well as aided in the design and understanding of specific inhibitors that could be used in antiviral therapies. In this paper, we discuss proteomic studies conducted on all eukaryotic viruses and bacteriophages, covering virion composition, viral protein structures, virus-virus and virus-host protein interactions, and changes in the cellular proteome upon viral infection.
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Daniel-Fischer, Lisa, Isabel J. Sobieszek, Anja Wagner, Juan Manuel Sacnun, Bruno Watschinger, Christoph Aufricht, Klaus Kratochwill, and Rebecca Herzog. "In-Depth Analysis of the Extracorporeal Proteome Adsorbed to Dialysis Membranes during Hemodialysis." Membranes 12, no. 11 (November 9, 2022): 1120. http://dx.doi.org/10.3390/membranes12111120.
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Used hemodialysis membranes (HD-M) are a valuable reservoir of biological information. Proteins bind to HD-M, but whether this process depends on the type of membrane or patient factors or selectively affects specific protein classes has not been adequately elucidated. State-of-the-art proteomics techniques are capable of identifying and quantifying this therapy-specific subproteome to enable the analysis of disease- or membrane-induced pathophysiologies. We demonstrate the feasibility of the deep proteomic characterization of the extracorporeal proteome adsorbed to HD-M. A shotgun proteomics approach using nano-flow liquid chromatography coupled to mass-spectrometry identified 1648 unique proteins eluted by a chaotropic buffer from the HD-M of eight patients. In total, 995 proteins were present in all eluates; a more stringent approach showed that a core proteome of 310 proteins could be identified independently in all samples. Stability of the dialyzer proteome was demonstrated by a >90% re-identification rate on longitudinal samples of a single patient. The core proteome showed an overrepresentation of pathways of hemostasis and the immune system, and showed differences in membrane materials (polysulfone vs. helixone). This study demonstrates that optimized conditions combined with high-performance proteomics enable the in-depth exploration of the subproteome bound to HD-M, yielding a stable core proteome that can be exploited to study patient-specific factors and improve hemodialysis therapy.
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Moghieb, Ahmed, Geremy Clair, Hugh D. Mitchell, Joseph Kitzmiller, Erika M. Zink, Young-Mo Kim, Vladislav Petyuk, et al. "Time-resolved proteome profiling of normal lung development." American Journal of Physiology-Lung Cellular and Molecular Physiology 315, no. 1 (July 1, 2018): L11—L24. http://dx.doi.org/10.1152/ajplung.00316.2017.
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Biochemical networks mediating normal lung morphogenesis and function have important implications for ameliorating morbidity and mortality in premature infants. Although several transcript-level studies have examined normal lung development, corresponding protein-level analyses are lacking. Here we performed proteomics analysis of murine lungs from embryonic to early adult ages to identify the molecular networks mediating normal lung development. We identified 8,932 proteins, providing a deep and comprehensive view of the lung proteome. Analysis of the proteomics data revealed discrete modules and the underlying regulatory and signaling network modulating their expression during development. Our data support the cell proliferation that characterizes early lung development and highlight responses of the lung to exposure to a nonsterile oxygen-rich ambient environment and the important role of lipid (surfactant) metabolism in lung development. Comparison of dynamic regulation of proteomic and recent transcriptomic analyses identified biological processes under posttranscriptional control. Our study provides a unique proteomic resource for understanding normal lung formation and function and can be freely accessed at Lungmap.net.
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Maguire, P. B., M. Foy, and D. J. Fitzgerald. "Using proteomics to identify potential therapeutic targets in platelets." Biochemical Society Transactions 33, no. 2 (April 1, 2005): 409–12. http://dx.doi.org/10.1042/bst0330409.
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Proteomics has provided powerful new insights into the complex events of the anucleate platelet and has revealed many potential protein targets in the search for suitable agents for thrombotic disease. In the present study, we summarize recent proteomic approaches to analyse specific platelet subproteomes, such as the platelet releasate, the platelet phosphotyrosine proteome and characterization of the proteins associated with membrane lipid rafts.
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Han, Mee-Jung, and Sang Yup Lee. "The Escherichia coli Proteome: Past, Present, and Future Prospects." Microbiology and Molecular Biology Reviews 70, no. 2 (June 2006): 362–439. http://dx.doi.org/10.1128/mmbr.00036-05.
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SUMMARY Proteomics has emerged as an indispensable methodology for large-scale protein analysis in functional genomics. The Escherichia coli proteome has been extensively studied and is well defined in terms of biochemical, biological, and biotechnological data. Even before the entire E. coli proteome was fully elucidated, the largest available data set had been integrated to decipher regulatory circuits and metabolic pathways, providing valuable insights into global cellular physiology and the development of metabolic and cellular engineering strategies. With the recent advent of advanced proteomic technologies, the E. coli proteome has been used for the validation of new technologies and methodologies such as sample prefractionation, protein enrichment, two-dimensional gel electrophoresis, protein detection, mass spectrometry (MS), combinatorial assays with n-dimensional chromatographies and MS, and image analysis software. These important technologies will not only provide a great amount of additional information on the E. coli proteome but also synergistically contribute to other proteomic studies. Here, we review the past development and current status of E. coli proteome research in terms of its biological, biotechnological, and methodological significance and suggest future prospects.
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Vítámvás, P., K. Kosová, and I. T. Prášil. "Proteome analysis in plant stress research: a review." Czech Journal of Genetics and Plant Breeding 43, No. 1 (January 7, 2008): 1–6. http://dx.doi.org/10.17221/1903-cjgpb.
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Proteomic techniques that allow the identification and quantification of stress-related proteins, mapping of dynamics of their expression and posttranslational modifications represent an important approach in the research of plant stresses. In this review, we show an outline of proteomics methods and their applications in the research of plant resistance to various types of stresses.
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Wareth, Gamal, Mathias W. Pletz, Heinrich Neubauer, and Jayaseelan Murugaiyan. "Proteomics of Brucella: Technologies and Their Applications for Basic Research and Medical Microbiology." Microorganisms 8, no. 5 (May 20, 2020): 766. http://dx.doi.org/10.3390/microorganisms8050766.
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Brucellosis is a global zoonosis caused by Gram-negative, facultative intracellular bacteria of the genus Brucella (B.). Proteomics has been used to investigate a few B. melitensis and B. abortus strains, but data for other species and biovars are limited. Hence, a comprehensive analysis of proteomes will significantly contribute to understanding the enigmatic biology of brucellae. For direct identification and typing of Brucella, matrix-assisted laser desorption ionization—time of flight mass spectrometry (MALDI—TOF MS) has become a reliable tool for routine diagnosis due to its ease of handling, price and sensitivity highlighting the potential of proteome-based techniques. Proteome analysis will also help to overcome the historic but still notorious Brucella obstacles of infection medicine, the lack of safe and protective vaccines and sensitive serologic diagnostic tools by identifying the most efficient protein antigens. This perspective summarizes past and recent developments in Brucella proteomics with a focus on species identification and serodiagnosis. Future applications of proteomics in these fields are discussed.
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Saei, Amir Ata, Pierre Sabatier, Ülkü Güler Tokat, Alexey Chernobrovkin, Mohammad Pirmoradian, and Roman A. Zubarev. "Comparative Proteomics of Dying and Surviving Cancer Cells Improves the Identification of Drug Targets and Sheds Light on Cell Life/Death Decisions." Molecular & Cellular Proteomics 17, no. 6 (March 23, 2018): 1144–55. http://dx.doi.org/10.1074/mcp.ra118.000610.
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Chemotherapeutics cause the detachment and death of adherent cancer cells. When studying the proteome changes to determine the protein target and mechanism of action of anticancer drugs, the still-attached cells are normally used, whereas the detached cells are usually ignored. To test the hypothesis that proteomes of detached cells contain valuable information, we separately analyzed the proteomes of detached and attached HCT-116, A375, and RKO cells treated for 48 h with 5-fluorouracil, methotrexate and paclitaxel. Individually, the proteomic data on attached and detached cells had comparable performance in target and drug mechanism deconvolution, whereas the combined data significantly improved the target ranking for paclitaxel. Comparative analysis of attached versus detached proteomes provided further insight into cell life and death decision making. Six proteins consistently up- or downregulated in the detached versus attached cells regardless of the drug and cell type were discovered; their role in cell death/survival was tested by silencing them with siRNA. Knocking down USP11, CTTN, ACAA2, and EIF4H had anti-proliferative effects, affecting UHRF1 additionally sensitized the cells to the anticancer drugs, while knocking down RNF-40 increased cell survival against the treatments. Therefore, adding detached cells to the expression proteomics analysis of drug-treated cells can significantly increase the analytical value of the approach. The data have been deposited to the ProteomeXchange with identifier PXD007686.
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Kalantari, Shiva, Ameneh Jafari, Raheleh Moradpoor, Elmira Ghasemi, and Ensieh Khalkhal. "Human Urine Proteomics: Analytical Techniques and Clinical Applications in Renal Diseases." International Journal of Proteomics 2015 (November 29, 2015): 1–17. http://dx.doi.org/10.1155/2015/782798.
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Urine has been in the center of attention among scientists of clinical proteomics in the past decade, because it is valuable source of proteins and peptides with a relative stable composition and easy to collect in large and repeated quantities with a noninvasive procedure. In this review, we discuss technical aspects of urinary proteomics in detail, including sample preparation, proteomic technologies, and their advantage and disadvantages. Several recent experiments are presented which applied urinary proteome for biomarker discovery in renal diseases including diabetic nephropathy, immunoglobulin A (IgA) nephropathy, focal segmental glomerulosclerosis, lupus nephritis, membranous nephropathy, and acute kidney injury. In addition, several available databases in urinary proteomics are also briefly introduced.
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Vidal, Bernardo C., Joseph V. Bonventre, and Stephen I-Hong Hsu. "Towards the application of proteomics in renal disease diagnosis." Clinical Science 109, no. 5 (October 24, 2005): 421–30. http://dx.doi.org/10.1042/cs20050085.
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Proteomics is widely envisioned as playing a significant role in the translation of genomics to clinically useful applications, especially in the areas of diagnostics and prognostics. In the diagnosis and treatment of kidney disease, a major priority is the identification of disease-associated biomarkers. Proteomics, with its high-throughput and unbiased approach to the analysis of variations in protein expression patterns (actual phenotypic expression of genetic variation), promises to be the most suitable platform for biomarker discovery. Combining such classic analytical techniques as two-dimensional gel electrophoresis with more sophisticated techniques, such as MS, has enabled considerable progress to be made in cataloguing and quantifying proteins present in urine and various kidney tissue compartments in both normal and diseased physiological states. Despite these accomplishments, there remain a number of important challenges that will need to be addressed in order to pave the way for the universal acceptance of proteomics as a clinically relevant diagnostic tool. We discuss issues related to three such critical developmental tasks as follows: (i) completely defining the proteome in the various biological compartments (e.g. tissues, serum and urine) in both health and disease, which presents a major challenge given the dynamic range and complexity of such proteomes; (ii) achieving the routine ability to accurately and reproducibly quantify proteomic expression profiles; and (iii) developing diagnostic platforms that are readily applicable and technically feasible for use in the clinical setting that depend on the fruits of the preceding two tasks to profile multiple disease biomarkers.
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Kruse, Rikke, Navid Sahebekhtiari, and Kurt Højlund. "The Mitochondrial Proteomic Signatures of Human Skeletal Muscle Linked to Insulin Resistance." International Journal of Molecular Sciences 21, no. 15 (July 28, 2020): 5374. http://dx.doi.org/10.3390/ijms21155374.
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Introduction: Mitochondria are essential in energy metabolism and cellular survival, and there is growing evidence that insulin resistance in chronic metabolic disorders, such as obesity, type 2 diabetes (T2D), and aging, is linked to mitochondrial dysfunction in skeletal muscle. Protein profiling by proteomics is a powerful tool to investigate mechanisms underlying complex disorders. However, despite significant advances in proteomics within the past two decades, the technologies have not yet been fully exploited in the field of skeletal muscle proteome. Area covered: Here, we review the currently available studies characterizing the mitochondrial proteome in human skeletal muscle in insulin-resistant conditions, such as obesity, T2D, and aging, as well as exercise-mediated changes in the mitochondrial proteome. Furthermore, we outline technical challenges and limitations and methodological aspects that should be considered when planning future large-scale proteomics studies of mitochondria from human skeletal muscle. Authors’ view: At present, most proteomic studies of skeletal muscle or isolated muscle mitochondria have demonstrated a reduced abundance of proteins in several mitochondrial biological processes in obesity, T2D, and aging, whereas the beneficial effects of exercise involve an increased content of muscle proteins involved in mitochondrial metabolism. Powerful mass-spectrometry-based proteomics now provides unprecedented opportunities to perform in-depth proteomics of muscle mitochondria, which in the near future is expected to increase our understanding of the complex molecular mechanisms underlying the link between mitochondrial dysfunction and insulin resistance in chronic metabolic disorders.
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Gao, Xing-Huang, Ling Li, Marc Parisien, Jing Wu, Ilya Bederman, Zhaofeng Gao, Dawid Krokowski, et al. "Discovery of a Redox Thiol Switch: Implications for Cellular Energy Metabolism." Molecular & Cellular Proteomics 19, no. 5 (March 4, 2020): 852–70. http://dx.doi.org/10.1074/mcp.ra119.001910.
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The redox-based modifications of cysteine residues in proteins regulate their function in many biological processes. The gas molecule H2S has been shown to persulfidate redox sensitive cysteine residues resulting in an H2S-modified proteome known as the sulfhydrome. Tandem Mass Tags (TMT) multiplexing strategies for large-scale proteomic analyses have become increasingly prevalent in detecting cysteine modifications. Here we developed a TMT-based proteomics approach for selectively trapping and tagging cysteine persulfides in the cellular proteomes. We revealed the natural protein sulfhydrome of two human cell lines, and identified insulin as a novel substrate in pancreatic beta cells. Moreover, we showed that under oxidative stress conditions, increased H2S can target enzymes involved in energy metabolism by switching specific cysteine modifications to persulfides. Specifically, we discovered a Redox Thiol Switch, from protein S-glutathioinylation to S-persulfidation (RTSGS). We propose that the RTSGS from S-glutathioinylation to S-persulfidation is a potential mechanism to fine tune cellular energy metabolism in response to different levels of oxidative stress.
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Mischak, Harald, Eric Schiffer, Petra Zürbig, Mohammed Dakna, and Jochen Metzger. "Urinary Proteome Analysis using Capillary Electrophoresis Coupled to Mass Spectrometry: A Powerful Tool in Clinical Diagnosis, Prognosis and Therapy Evaluation." Journal of Medical Biochemistry 28, no. 4 (October 1, 2009): 223–34. http://dx.doi.org/10.2478/v10011-009-0020-0.
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Urinary Proteome Analysis using Capillary Electrophoresis Coupled to Mass Spectrometry: A Powerful Tool in Clinical Diagnosis, Prognosis and Therapy EvaluationProteome analysis has emerged as a powerful tool to decipher (patho) physiological processes, resulting in the establishment of the field of clinical proteomics. One of the main goals is to discover biomarkers for diseases from tissues and body fluids. Due to the enormous complexity of the proteome, a separation step is required for mass spectrometry (MS)-based proteome analysis. In this review, the advantages and limitations of protein separation by two-dimensional gel electrophoresis, liquid chromatography, surface-enhanced laser desorption/ionization and capillary electrophoresis (CE) for proteomic analysis are described, focusing on CE-MS. CE-MS enables separation and detection of the small molecular weight proteome in biological fluids with high reproducibility and accuracy in one single processing step and in a short time. As sensitive and specific single biomarkers generally may not exist, a strategy to overcome this diagnostic void is shifting from single analyte detection to simultaneous analysis of multiple analytes that together form a disease-specific pattern. Such approaches, however, are accompanied with additional challenges, which we will outline in this review. Besides the choice of adequate technological platforms, a high level of standardization of proteomic measurements and data processing is also necessary to establish proteomic profiling. In this regard, demands concerning study design, choice of specimens, sample preparation, proteomic data mining, and clinical evaluation should be considered before performing a proteomic study.
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Vowinckel, Jakob, Thomas Corwin, Jonathan Woodsmith, Tobias Treiber, Roland Bruderer, Lukas Reiter, Eike-Christin von Leitner, Karel Novy, Hartmut Juhl, and Oliver Rinner. "Proteome and phospho-proteome profiling for deeper phenotype characterization of colorectal cancer heterogeneity." Journal of Clinical Oncology 39, no. 15_suppl (May 20, 2021): e15536-e15536. http://dx.doi.org/10.1200/jco.2021.39.15_suppl.e15536.
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e15536 Background: The rise of precision oncology therapeutics requires deep understanding of the molecular mechanisms implicated in cancer biology. Colorectal cancer (CRC) is one of the first solid tumors to be molecularly characterized by defined genes and pathways. Advances in tumor profiling have revealed a profound molecular heterogeneity in CRC leading to the definition of several consensus molecular subtypes (CMS). However, this molecular heterogeneity is still largely defined on the genomic and transcriptomics level. To complement the understanding of genetically defined molecular subgroups, we performed large-scale deep proteomic and phospho-proteomic profiling of CRC patient biopsies and adjacent healthy control tissue, which has enabled to explore the phenotype and obtain more functional insights in cancer biology. Methods: Sample processing from 5-10 mg of tissue per sample was performed using a liquid handling robot. Phospho-peptide enrichment was carried out with a Kingfisher Flex device and MagReSyn Ti-IMAC magnetic beads. Data-Independent Acquisition (DIA) LC-MS/MS was performed on multiple platforms consisting of a Thermo Scientific Q Exactive HF-X mass spectrometer coupled to a Waters M-Class LC. Chromatography was operating at 5 µL/min, and separation was achieved using 45 min (whole proteome) and 60 min (phospho-proteome) gradients. Results: Indivumed has built IndivuType, the world’s first multi-omics database for individualized cancer therapy, analyzing the highest quality cancer biospecimens to generate the most comprehensive dataset, including genomics, transcriptomics, proteomics, and clinical outcome information. Enabled by the DIA technology, a mass spectrometric method developed by Biognosys that obtains peptide fragmentation data in a highly parallelized way with high sensitivity, more than 7,000 proteins in the whole proteome and 20,000 phospho-peptides in the phospho-proteome workflow were profiled across more than 900 resected tissue samples of various CMS of CRC. The resulting proteome and phospho-proteome data were integrated into the IndivuType database and cross-analyzed with genomic and transcriptomic markers. Through this combined analysis, novel insights in clinically relevant signaling pathways in CRC subtypes were revealed. Conclusions: The deep phenotypic profiling of cancer samples, using next generation proteomics and phospho-proteomics, has enabled us to go beyond the genomic level in the characterization of tumor molecular heterogeneity. This multi-omics approach provides a solid foundation to advance the understanding of cancer biology, unravel key molecular events, and support the identification of novel therapeutic targets for precision medicine in CRC.
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Pitteri, Sharon, and Sam Hanash. "A Systems Approach to the Proteomic Identification of Novel Cancer Biomarkers." Disease Markers 28, no. 4 (2010): 233–39. http://dx.doi.org/10.1155/2010/270859.
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The proteomics field has experienced rapid growth with technologies achieving ever increasing accuracy, sensitivity, and throughput, and with availability of computational tools to address particular applications. Given that the proteome represents the most functional component encoded for in the genome, a systems approach to disease investigations and biomarker identification benefits substantially from integration of proteome level studies. Here we present proteomic approaches that have allowed systematic searches for potential cancer markers by integrating cancer cell profiling with additional sources of data, as illustrated with recent studies of ovarian cancer.
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Eligini, Sonia, Erica Gianazza, Alice Mallia, Stefania Ghilardi, and Cristina Banfi. "Macrophage Phenotyping in Atherosclerosis by Proteomics." International Journal of Molecular Sciences 24, no. 3 (January 30, 2023): 2613. http://dx.doi.org/10.3390/ijms24032613.
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Macrophages are heterogeneous and plastic cells, able to adapt their phenotype and functions to changes in the microenvironment. They are involved in several homeostatic processes and also in many human diseases, including atherosclerosis, where they participate in all the stages of the disease. For these reasons, macrophages have been studied extensively using different approaches, including proteomics. Proteomics, indeed, may be a powerful tool to better understand the behavior of these cells, and a careful analysis of the proteome of different macrophage phenotypes can help to better characterize the role of these phenotypes in atherosclerosis and provide a broad view of proteins that might potentially affect the course of the disease. In this review, we discuss the different proteomic techniques that have been used to delineate the proteomic profile of macrophage phenotypes and summarize some results that can help to elucidate the roles of macrophages and develop new strategies to counteract the progression of atherosclerosis and/or promote regression.
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Peck Justice, Sarah A., Monica P. Barron, Guihong D. Qi, H. R. Sagara Wijeratne, José F. Victorino, Ed R. Simpson, Jonah Z. Vilseck, Aruna B. Wijeratne, and Amber L. Mosley. "Mutant thermal proteome profiling for characterization of missense protein variants and their associated phenotypes within the proteome." Journal of Biological Chemistry 295, no. 48 (September 2, 2020): 16219–38. http://dx.doi.org/10.1074/jbc.ra120.014576.
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Temperature-sensitive (TS) missense mutants have been foundational for characterization of essential gene function. However, an unbiased approach for analysis of biochemical and biophysical changes in TS missense mutants within the context of their functional proteomes is lacking. We applied MS-based thermal proteome profiling (TPP) to investigate the proteome-wide effects of missense mutations in an application that we refer to as mutant thermal proteome profiling (mTPP). This study characterized global impacts of temperature sensitivity–inducing missense mutations in two different subunits of the 26S proteasome. The majority of alterations identified by RNA-Seq and global proteomics were similar between the mutants, which could suggest that a similar functional disruption is occurring in both missense variants. Results from mTPP, however, provide unique insights into the mechanisms that contribute to the TS phenotype in each mutant, revealing distinct changes that were not obtained using only steady-state transcriptome and proteome analyses. Computationally, multisite λ-dynamics simulations add clear support for mTPP experimental findings. This work shows that mTPP is a precise approach to measure changes in missense mutant–containing proteomes without the requirement for large amounts of starting material, specific antibodies against proteins of interest, and/or genetic manipulation of the biological system. Although experiments were performed under permissive conditions, mTPP provided insights into the underlying protein stability changes that cause dramatic cellular phenotypes observed at nonpermissive temperatures. Overall, mTPP provides unique mechanistic insights into missense mutation dysfunction and connection of genotype to phenotype in a rapid, nonbiased fashion.
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Hohn, Andreas, Ivan Iovino, Fabrizio Cirillo, Hendrik Drinhaus, Kathrin Kleinbrahm, Lennert Boehm, Edoardo De Robertis, and Jochen Hinkelbein. "Bioinformatical Analysis of Organ-Related (Heart, Brain, Liver, and Kidney) and Serum Proteomic Data to Identify Protein Regulation Patterns and Potential Sepsis Biomarkers." BioMed Research International 2018 (March 21, 2018): 1–11. http://dx.doi.org/10.1155/2018/3576157.
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During the last years, proteomic studies have revealed several interesting findings in experimental sepsis models and septic patients. However, most studies investigated protein alterations only in single organs or in whole blood. To identify possible sepsis biomarkers and to evaluate the relationship between protein alteration in sepsis affected organs and blood, proteomics data from the heart, brain, liver, kidney, and serum were analysed. Using functional network analyses in combination with hierarchical cluster analysis, we found that protein regulation patterns in organ tissues as well as in serum are highly dynamic. In the tissue proteome, the main functions and pathways affected were the oxidoreductive activity, cell energy generation, or metabolism, whereas in the serum proteome, functions were associated with lipoproteins metabolism and, to a minor extent, with coagulation, inflammatory response, and organ regeneration. Proteins from network analyses of organ tissue did not correlate with statistically significantly regulated serum proteins or with predicted proteins of serum functions. In this study, the combination of proteomic network analyses with cluster analyses is introduced as an approach to deal with high-throughput proteomics data to evaluate the dynamics of protein regulation during sepsis.
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Chalmel, Frédéric, and Antoine D. Rolland. "Linking transcriptomics and proteomics in spermatogenesis." REPRODUCTION 150, no. 5 (November 2015): R149—R157. http://dx.doi.org/10.1530/rep-15-0073.
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Spermatogenesis is a complex and tightly regulated process leading to the continuous production of male gametes, the spermatozoa. This developmental process requires the sequential and coordinated expression of thousands of genes, including many that are testis-specific. The molecular networks underlying normal and pathological spermatogenesis have been widely investigated in recent decades, and many high-throughput expression studies have studied genes and proteins involved in male fertility. In this review, we focus on studies that have attempted to correlate transcription and translation during spermatogenesis by comparing the testicular transcriptome and proteome. We also discuss the recent development and use of new transcriptomic approaches that provide a better proxy for the proteome, from both qualitative and quantitative perspectives. Finally, we provide illustrations of how testis-derived transcriptomic and proteomic data can be integrated to address new questions and how the ‘proteomics informed by transcriptomics’ technique, by combining RNA-seq and MS-based proteomics, can contribute significantly to the discovery of new protein-coding genes or new protein isoforms expressed during spermatogenesis.
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Nguyen, Nam H. K., Huiyun Wu, Haiyan Tan, Junmin Peng, Jeffrey E. Rubnitz, Xueyuan Cao, Stanley Pounds, and Jatinder K. Lamba. "Global Proteomic Profiling of Pediatric AML: A Pilot Study." Cancers 13, no. 13 (June 24, 2021): 3161. http://dx.doi.org/10.3390/cancers13133161.
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Acute Myeloid Leukemia (AML) is a heterogeneous disease with several recurrent cytogenetic abnormalities. Despite genomics and transcriptomics profiling efforts to understand AML’s heterogeneity, studies focused on the proteomic profiles associated with pediatric AML cytogenetic features remain limited. Furthermore, the majority of biological functions within cells are operated by proteins (i.e., enzymes) and most drugs target the proteome rather than the genome or transcriptome, thus, highlighting the significance of studying proteomics. Here, we present our results from a pilot study investigating global proteomic profiles of leukemic cells obtained at diagnosis from 16 pediatric AML patients using a robust TMT-LC/LC-MS/MS platform. The proteome profiles were compared among patients with or without core binding factor (CBF) translocation indicated by a t(8;21) or inv(16) cytogenetic abnormality, minimal residual disease status at the end of the first cycle of chemotherapy (MRD1), and in vitro chemosensitivity of leukemic cells to cytarabine (Ara-C LC50). Our results established proteomic differences between CBF and non-CBF AML subtypes, providing insights to AML subtypes physiology, and identified potential druggable proteome targets such as THY1 (CD90), NEBL, CTSF, COL2A1, CAT, MGLL (MAGL), MACROH2A2, CLIP2 (isoform 1 and 2), ANPEP (CD13), MMP14, and AK5.