Journal articles: 'Proteomics approaches'

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DePalma, Angelo. "Improving Proteomics Approaches." Genetic Engineering & Biotechnology News 33, no. 10 (May 15, 2013): 24–26. http://dx.doi.org/10.1089/gen.33.10.10.

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Kalvodova, Lucie. "Understanding the proteomes using non-proteomics approaches: Expanding the scope of PROTEOMICS." PROTEOMICS 17, no. 1-2 (January 2017): 1770013. http://dx.doi.org/10.1002/pmic.201770013.

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Mahajan, R., and P. Gupta. "Proteomics: taking over where genomics leaves off." Czech Journal of Genetics and Plant Breeding 46, No. 2 (June 29, 2010): 47–53. http://dx.doi.org/10.17221/34/2009-cjgpb.

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The proteomic studies are simultaneously developed in several directions and significantly influence our notions on the capabilities of biological sciences. The need for proteomics research is necessary as there are certain genes in a cell that encode proteins with specific functions. Using a variety of techniques, proteomics can be used to study how proteins interact within a system or how the protein expression changes in different parts of the body, in different stages of its life cycle and in different environmental conditions as every individual has one genome and many proteomes. Besides the qualitative and quantitative description of the expressed proteins, proteomics also deals with the analysis of mutual interactions of proteins. Thereby, candidate proteins can be identified which may be used as starting-points for diagnostic or even therapeutic approaches.

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Sokolowska, Izabela, Armand G. Ngounou Wetie, Alisa G. Woods, and Costel C. Darie. "Applications of Mass Spectrometry in Proteomics." Australian Journal of Chemistry 66, no. 7 (2013): 721. http://dx.doi.org/10.1071/ch13137.

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

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Roeraade, Johan. "Nanotechnology Approaches to Proteomics." Biochemical Society Transactions 27, no. 3 (June 1, 1999): A69. http://dx.doi.org/10.1042/bst027a069a.

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Vahkal, Brett, Jamie Kraft, Emanuela Ferretti, Minyoung Chung, Jean-François Beaulieu, and Illimar Altosaar. "Review of Methodological Approaches to Human Milk Small Extracellular Vesicle Proteomics." Biomolecules 11, no. 6 (June 3, 2021): 833. http://dx.doi.org/10.3390/biom11060833.

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Proteomics can map extracellular vesicles (EVs), including exosomes, across disease states between organisms and cell types. Due to the diverse origin and cargo of EVs, tailoring methodological and analytical techniques can support the reproducibility of results. Proteomics scans are sensitive to in-sample contaminants, which can be retained during EV isolation procedures. Contaminants can also arise from the biological origin of exosomes, such as the lipid-rich environment in human milk. Human milk (HM) EVs and exosomes are emerging as a research interest in health and disease, though the experimental characterization and functional assays remain varied. Past studies of HM EV proteomes have used data-dependent acquisition methods for protein detection, however, improvements in data independent acquisition could allow for previously undetected EV proteins to be identified by mass spectrometry. Depending on the research question, only a specific population of proteins can be compared and measured using isotope and other labelling techniques. In this review, we summarize published HM EV proteomics protocols and suggest a methodological workflow with the end-goal of effective and reproducible analysis of human milk EV proteomes.

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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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FOSTER, LEONARD J. "MASS SPECTROMETRY OUTGROWS SIMPLE BIOCHEMISTRY: NEW APPROACHES TO ORGANELLE PROTEOMICS." Biophysical Reviews and Letters 01, no. 02 (April 2006): 209–21. http://dx.doi.org/10.1142/s1793048006000057.

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Organelles are subcellular compartments or structures that typically carry out a defined set of functions within the cell. The functions of many organelles are known or predicted, but without knowing all the components of any recognized organelle it is difficult to fully understand them. Mass spectrometry-based proteomics now allows for routine identification of several hundreds or thousands of proteins in very complex samples; for cell biologists, organelles represent perhaps the most interesting class of cellular components to apply this new technology to. However, in order to analyze the proteome of an organelle it first must be purified, and the limitations in purifying any biological sample to homogeneity quickly become apparent to the vigilant mass spectrometrist. At the end of an organelle proteomic investigation, investigators are left with a long list of proteins whose location needs to be verified by an orthogonal method, a daunting prospect; or, they must accept an unknown and possibly very high level of incorrect localizations. Some of these caveats can be partially overcome by incorporating quantitative aspects into organelle proteomic studies. This review discusses some alternative approaches to organelle proteomics where questions of specificity and/or functional relevance are addressed by incorporating a quantitative dimension into the experiment.

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Pino, Lindsay K., Jacob Rose, Amy O'Broin, Samah Shah, and Birgit Schilling. "Emerging mass spectrometry-based proteomics methodologies for novel biomedical applications." Biochemical Society Transactions 48, no. 5 (October 20, 2020): 1953–66. http://dx.doi.org/10.1042/bst20191091.

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Research into the basic biology of human health and disease, as well as translational human research and clinical applications, all benefit from the growing accessibility and versatility of mass spectrometry (MS)-based proteomics. Although once limited in throughput and sensitivity, proteomic studies have quickly grown in scope and scale over the last decade due to significant advances in instrumentation, computational approaches, and bio-sample preparation. Here, we review these latest developments in MS and highlight how these techniques are used to study the mechanisms, diagnosis, and treatment of human diseases. We first describe recent groundbreaking technological advancements for MS-based proteomics, including novel data acquisition techniques and protein quantification approaches. Next, we describe innovations that enable the unprecedented depth of coverage in protein signaling and spatiotemporal protein distributions, including studies of post-translational modifications, protein turnover, and single-cell proteomics. Finally, we explore new workflows to investigate protein complexes and structures, and we present new approaches for protein–protein interaction studies and intact protein or top-down MS. While these approaches are only recently incipient, we anticipate that their use in biomedical MS proteomics research will offer actionable discoveries for the improvement of human health.

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Gnatenko, Dmitri V., Peter L. Perrotta, and Wadie F. Bahou. "Proteomic approaches to dissect platelet function: half the story." Blood 108, no. 13 (December 15, 2006): 3983–91. http://dx.doi.org/10.1182/blood-2006-06-026518.

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AbstractPlatelets play critical roles in diverse hemostatic and pathologic disorders and are broadly implicated in various biological processes that include inflammation, wound healing, and thrombosis. Recent progress in high-throughput mRNA and protein profiling techniques has advanced our understanding of the biological functions of platelets. Platelet proteomics has been adopted to decode the complex processes that underlie platelet function by identifying novel platelet-expressed proteins, dissecting mechanisms of signal or metabolic pathways, and analyzing functional changes of the platelet proteome in normal and pathologic states. The integration of transcriptomics and proteomics, coupled with progress in bioinformatics, provides novel tools for dissecting platelet biology. In this review, we focus on current advances in platelet proteomic studies, with emphasis on the importance of parallel transcriptomic studies to optimally dissect platelet function. Applications of these global profiling approaches to investigate platelet genetic diseases and platelet-related disorders are also addressed.

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Fung, Eric T., Scot R. Weinberger, Ed Gavin, and Fujun Zhang. "Bioinformatics approaches in clinical proteomics." Expert Review of Proteomics 2, no. 6 (December 2005): 847–62. http://dx.doi.org/10.1586/14789450.2.6.847.

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Liu, Brian CS, and Joshua R. Ehrlich. "Proteomics approaches to urologic diseases." Expert Review of Proteomics 3, no. 3 (June 2006): 283–96. http://dx.doi.org/10.1586/14789450.3.3.283.

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Manadas, Bruno, Vera M. Mendes, Jane English, and Michael J. Dunn. "Peptide fractionation in proteomics approaches." Expert Review of Proteomics 7, no. 5 (October 2010): 655–63. http://dx.doi.org/10.1586/epr.10.46.

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Zhou, M. "Proteomics approaches to biomarker detection." Briefings in Functional Genomics and Proteomics 4, no. 1 (January 1, 2005): 69–75. http://dx.doi.org/10.1093/bfgp/4.1.69.

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Thompson, D. C. "15 Methodological approaches in proteomics." Toxicology Letters 144 (September 2003): s4. http://dx.doi.org/10.1016/s0378-4274(03)90014-2.

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Sharma, Vipin Kumar, and Ravi Kumar. "Current applications of proteomics: a key and novel approach." International Journal of Advances in Medicine 6, no. 6 (November 25, 2019): 1953. http://dx.doi.org/10.18203/2349-3933.ijam20195259.

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Proteomics represented vital applications of technologies in the identification and quantification of high to moderate proteins (cellular signalling networks) found in biological matrix such as tissues, cells and fluids. Proteomics based technical knowledge is applied and verified in several preclinical research settings such as invention of diagnostic markers for specific disease and have shown to be increased in clinical applications. Extensive studies on proteomics resulted in detection of biomarkers that have been highly advanced in using diseases for cancer, lungs, cardiovascular, renal and neuro-regenerative and Parkinson's disease by introducing human origins for biocompatibility such as urine and serum. Advancement in the proteomic methods is conferring candidate right direction for clinical usage. In this review, recent developments and widely used proteomics approaches such as Mass Spectrometry (MS), Microarray chips are elaborately addressed and also focused merits and demerits of commonly used advanced approaches such as Selected Reaction Monitoring (SRM), Parallel Reaction Monitoring (PRM) and Data Independent Acquisition (DIA) and other used proteomics and that roles, in order to aid clinicians, were also discussed in the light of biomedical applications.

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Kalaiselvi, B., and M. Thangamani. "Computational Approaches for Understanding High Quality Mass Spectrometry Proteomic Data." Journal of Computational and Theoretical Nanoscience 16, no. 2 (February 1, 2019): 516–20. http://dx.doi.org/10.1166/jctn.2019.7761.

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Computational approach of proteomic data science is used to identification and quantification of protein and provides the high-throughput data, concentration changes, interactions, posttranslational modifications and cellular localizations. The high-quality mass spectrometry recall to understanding the different sources of unsigned high-quality spectra features. The iterative computational method is interrogating the high efficiency of mass spectrometry protein data. The approach contains several databases searching with different search parameters, spectral library searching, modified peptides using blind search and genomic database searching. The mass spectrometry computational method is analysis the proteomics data focusing the key concepts with explanations, mass spectral feature detection, identifying the peptides, protein inference and control the false discovery rate. Then the method discusses the quantification of peptides and proteins, the downstream data analysis on machine learning, network analysis and multiomics integration of protein data and finally discuss the future of computational proteomics data.

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Rodríguez-Ulloa, Arielis, Jeovanis Gil, Yassel Ramos, Lilian Hernández-Álvarez, Lisandra Flores, Brizaida Oliva, Dayana García, et al. "Proteomic Study to Survey the CIGB-552 Antitumor Effect." BioMed Research International 2015 (2015): 1–18. http://dx.doi.org/10.1155/2015/124082.

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CIGB-552 is a cell-penetrating peptide that exertsin vitroandin vivoantitumor effect on cancer cells. In the present work, the mechanism involved in such anticancer activity was studied using chemical proteomics and expression-based proteomics in culture cancer cell lines. CIGB-552 interacts with at least 55 proteins, as determined by chemical proteomics. A temporal differential proteomics based on iTRAQ quantification method was performed to identify CIGB-552 modulated proteins. The proteomic profile includes 72 differentially expressed proteins in response to CIGB-552 treatment. Proteins related to cell proliferation and apoptosis were identified by both approaches. In line with previous findings, proteomic data revealed that CIGB-552 triggers the inhibition of NF-κB signaling pathway. Furthermore, proteins related to cell invasion were differentially modulated by CIGB-552 treatment suggesting new potentialities of CIGB-552 as anticancer agent. Overall, the current study contributes to a better understanding of the antitumor action mechanism of CIGB-552.

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Cutillas, Pedro, Alma Burlingame, and Robert Unwin. "Proteomic Strategies and Their Application in Studies of Renal Function." Physiology 19, no. 3 (June 2004): 114–19. http://dx.doi.org/10.1152/nips.01515.2003.

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Proteomics is a promising new tool for functional genomics. In addition to two-dimensional gel electrophoresis, other methods that are based on liquid chromatography and mass spectrometry are now available to study proteins. In this brief article, we review the strengths and limitations of the proteomic approaches currently available to the researcher, and we provide examples of how proteomics has been, and can in the future be, used to study the kidney.

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Abdallah, Cosette, Eliane Dumas-Gaudot, Jenny Renaut, and Kjell Sergeant. "Gel-Based and Gel-Free Quantitative Proteomics Approaches at a Glance." International Journal of Plant Genomics 2012 (November 20, 2012): 1–17. http://dx.doi.org/10.1155/2012/494572.

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Two-dimensional gel electrophoresis (2-DE) is widely applied and remains the method of choice in proteomics; however, pervasive 2-DE-related concerns undermine its prospects as a dominant separation technique in proteome research. Consequently, the state-of-the-art shotgun techniques are slowly taking over and utilising the rapid expansion and advancement of mass spectrometry (MS) to provide a new toolbox of gel-free quantitative techniques. When coupled to MS, the shotgun proteomic pipeline can fuel new routes in sensitive and high-throughput profiling of proteins, leading to a high accuracy in quantification. Although label-based approaches, either chemical or metabolic, gained popularity in quantitative proteomics because of the multiplexing capacity, these approaches are not without drawbacks. The burgeoning label-free methods are tag independent and suitable for all kinds of samples. The challenges in quantitative proteomics are more prominent in plants due to difficulties in protein extraction, some protein abundance in green tissue, and the absence of well-annotated and completed genome sequences. The goal of this perspective assay is to present the balance between the strengths and weaknesses of the available gel-based and -free methods and their application to plants. The latest trends in peptide fractionation amenable to MS analysis are as well discussed.

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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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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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Tracz, Joanna, and Magdalena Luczak. "Applying Proteomics and Integrative “Omics” Strategies to Decipher the Chronic Kidney Disease-Related Atherosclerosis." International Journal of Molecular Sciences 22, no. 14 (July 13, 2021): 7492. http://dx.doi.org/10.3390/ijms22147492.

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Patients with chronic kidney disease (CKD) are at increased risk of atherosclerosis and premature mortality, mainly due to cardiovascular events. However, well-known risk factors, which promote “classical” atherosclerosis are alone insufficient to explain the high prevalence of atherosclerosis-related to CKD (CKD-A). The complexity of the molecular mechanisms underlying the acceleration of CKD-A is still to be defied. To obtain a holistic picture of these changes, comprehensive proteomic approaches have been developed including global protein profiling followed by functional bioinformatics analyses of dysregulated pathways. Furthermore, proteomics surveys in combination with other “omics” techniques, i.e., transcriptomics and metabolomics as well as physiological assays provide a solid ground for interpretation of observed phenomena in the context of disease pathology. This review discusses the comprehensive application of various “omics” approaches, with emphasis on proteomics, to tackle the molecular mechanisms underlying CKD-A progression. We summarize here the recent findings derived from global proteomic approaches and underline the potential of utilizing integrative systems biology, to gain a deeper insight into the pathogenesis of CKD-A and other disorders.

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Kondo, Tadashi, Daisuke Kubota, and Akira Kawai. "Application of Proteomics to Soft Tissue Sarcomas." International Journal of Proteomics 2012 (June 19, 2012): 1–15. http://dx.doi.org/10.1155/2012/876401.

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Soft tissue sarcomas are rare and account for less than 1% of all malignant cancers. Other than development of intensive therapies, the clinical outcome of patients with soft tissue sarcoma remains very poor, particularly when diagnosed at a late stage. Unique mutations have been associated with certain soft tissue sarcomas, but their etiologies remain unknown. The proteome is a functional translation of a genome, which directly regulates the malignant features of tumors. Thus, proteomics is a promising approach for investigating soft tissue sarcomas. Various proteomic approaches and clinical materials have been used to address clinical and biological issues, including biomarker development, molecular target identification, and study of disease mechanisms. Several cancer-associated proteins have been identified using conventional technologies such as 2D-PAGE, mass spectrometry, and array technology. The functional backgrounds of proteins identified were assessed extensively using in vitro experiments, thus supporting expression analysis. These observations demonstrate the applicability of proteomics to soft tissue sarcoma studies. However, the sample size in each study was insufficient to allow conclusive results. Given the low frequency of soft tissue sarcomas, multi-institutional collaborations are required to validate the results of proteomic approaches.

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He, Fuchu. "Microbial Proteomics: Approaches, Advances, and Applications." Journal of Bioinformatics and Proteomics Review 2, no. 2 (2016): 1–7. http://dx.doi.org/10.15436/2381-0793.16.004.

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CLANCY, OLIVIA, and JENNY E. MYERS. "PROTEOMICS APPROACHES IN PRE-ECLAMPSIA RESEARCH." Fetal and Maternal Medicine Review 20, no. 2 (May 2009): 143–60. http://dx.doi.org/10.1017/s0965539509002319.

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Much of our current understanding of human gestation is largely based on information extracted from animal and cell models. Although this information has been fundamental for progression of reproductive research, much of it examines biological molecules in isolation rather than the integrated manner in which they function. Disruption to these fundamental processes is the source of pregnancy complications, of which for many (including pre-eclampsia) the exact aetiology has not been fully elucidated. We need to re-examine the limited way by which we approach these problems, and aim to understand pathophysiology in a more inclusive/holistic way.

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Liu, Brian C., Shuzhen Qin, Cindy Williams, and Michael P. O'Leary. "306: Proteomics Approaches to Interstitial Cystitis." Journal of Urology 173, no. 4S (April 2005): 84–85. http://dx.doi.org/10.1016/s0022-5347(18)34571-3.

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Schulenborg, T., O. Schmidt, A. van Hall, H. E. Meyer, M. Hamacher, and K. Marcus. "Proteomics in neurodegeneration – disease driven approaches." Journal of Neural Transmission 113, no. 8 (July 13, 2006): 1055–73. http://dx.doi.org/10.1007/s00702-006-0512-8.

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Yan, Guokai, and Xianghua Yan. "Ribosomal proteomics: Strategies, approaches, and perspectives." Biochimie 113 (June 2015): 69–77. http://dx.doi.org/10.1016/j.biochi.2015.03.024.

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Gajahin Gamage, Nadeeka Thushari, Rina Miyashita, Kazutaka Takahashi, Shuichi Asakawa, and Jayan Duminda Mahesh Senevirathna. "Proteomic Applications in Aquatic Environment Studies." Proteomes 10, no. 3 (September 1, 2022): 32. http://dx.doi.org/10.3390/proteomes10030032.

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Genome determines the unique individualities of organisms; however, proteins play significant roles in the generation of the colorful life forms below water. Aquatic systems are usually complex and multifaceted and can take on unique modifications and adaptations to environmental changes by altering proteins at the cellular level. Proteomics is an essential strategy for exploring aquatic ecosystems due to the diverse involvement of proteins, proteoforms, and their complexity in basic and advanced cellular functions. Proteomics can expedite the analysis of molecular mechanisms underlying biological processes in an aquatic environment. Previous proteomic studies on aquatic environments have mainly focused on pollution assessments, ecotoxicology, their role in the food industry, and extraction and identification of natural products. Aquatic protein biomarkers have been comprehensively reported and are currently extensively applied in the pharmaceutical and medical industries. Cellular- and molecular-level responses of organisms can be used as indicators of environmental changes and stresses. Conversely, environmental changes are expedient in predicting aquatic health and productivity, which are crucial for ecosystem management and conservation. Recent advances in proteomics have contributed to the development of sustainable aquaculture, seafood safety, and high aquatic food production. Proteomic approaches have expanded to other aspects of the aquatic environment, such as protein fingerprinting for species identification. In this review, we encapsulated current proteomic applications and evaluated the potential strengths, weaknesses, opportunities, and threats of proteomics for future aquatic environmental studies. The review identifies both pros and cons of aquatic proteomics and projects potential challenges and recommendations. We postulate that proteomics is an emerging, powerful, and integrated omics approach for aquatic environmental studies.

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Steele, Joel R., Carly J. Italiano, Connor R. Phillips, Jake P. Violi, Lisa Pu, Kenneth J. Rodgers, and Matthew P. Padula. "Misincorporation Proteomics Technologies: A Review." Proteomes 9, no. 1 (January 21, 2021): 2. http://dx.doi.org/10.3390/proteomes9010002.

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Proteinopathies are diseases caused by factors that affect proteoform conformation. As such, a prevalent hypothesis is that the misincorporation of noncanonical amino acids into a proteoform results in detrimental structures. However, this hypothesis is missing proteomic evidence, specifically the detection of a noncanonical amino acid in a peptide sequence. This review aims to outline the current state of technology that can be used to investigate mistranslations and misincorporations whilst framing the pursuit as Misincorporation Proteomics (MiP). The current availability of technologies explored herein is mass spectrometry, sample enrichment/preparation, data analysis techniques, and the hyphenation of approaches. While many of these technologies show potential, our review reveals a need for further development and refinement of approaches is still required.

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Bowman, John P. "Proteomic applications in microbial identification." Microbiology Australia 32, no. 2 (2011): 77. http://dx.doi.org/10.1071/ma11077.

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Proteomics-based approaches have been used in microbial taxonomy for the last several decades. Recent improvements in instruments and software have led to the appearance of mass spectrometric fingerprinting and peptide survey approaches allowing for highly rapid and accurate taxonomic diagnoses suitable for high-throughput laboratories as well as means to deeply analyse entire proteomes.

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Monti, Maria, Stefania Orrù, Daniela Pagnozzi, and Piero Pucci. "Interaction Proteomics." Bioscience Reports 25, no. 1-2 (February 4, 2005): 45–56. http://dx.doi.org/10.1007/s10540-005-2847-z.

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The term proteome is traditionally associated with the identification of a large number of proteins within complex mixtures originating from a given organelle, cell or even organism. Current proteome investigations are basically focused on two major areas, expression proteomics and functional proteomics. Both approaches rely on the fractionation of protein mixtures essentially by two-dimensional polyacrylamide gel electrophoresis (2D-gel) and the identification of individual protein bands by mass spectrometric techniques (2D-MS). Functional proteomics approaches are basically addressing two main targets, the elucidation of the biological function of unknown proteins and the definition of cellular mechanisms at the molecular level. In the cell many processes are governed not only by the relative abundance of proteins but also by rapid and transient regulation of activity, association and localization of proteins and protein complexes. The association of an unknown protein with partners belonging to a specific protein complex involved in a particular process would then be strongly suggestive of its biological function. The identification of interacting proteins in stable complexes in a cellular system is essentially achieved by affinity-based procedures. Different strategies relying on this simple concept have been developed and a brief overview of the main approaches presently used in functional proteomics studies is described.

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Nichols, Heather L., Ning Zhang, and Xuejun Wen. "Proteomics and genomics of microgravity." Physiological Genomics 26, no. 3 (August 2006): 163–71. http://dx.doi.org/10.1152/physiolgenomics.00323.2005.

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Many serious adverse physiological changes occur during spaceflight. In the search for underlying mechanisms and possible new countermeasures, many experimental tools and methods have been developed to study microgravity caused physiological changes, ranging from in vitro bioreactor studies to spaceflight investigations. Recently, genomic and proteomic approaches have gained a lot of attention; after major scientific breakthroughs in the fields of genomics and proteomics, they are now widely accepted and used to understand biological processes. Understanding gene and/or protein expression is the key to unfolding the mechanisms behind microgravity-induced problems and, ultimately, finding effective countermeasures to spaceflight-induced alterations. Significant progress has been made in identifying the genes/proteins responsible for these changes. Although many of these genes and/or proteins were observed to be either upregulated or downregulated, however, no large-scale genomics and proteomics studies have been published so far. This review aims at summarizing the current status of microgravity-related genomics and proteomics studies and stimulating large-scale proteomics and genomics research activities.

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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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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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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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Mohanasundaram, Sugumar, Deepa Dhatwalia, P. Vijayaraghavan, Laith H. Alzubaidi, and Khamdamova Makhzuna. "Bioinformatics: Computational Approaches for Genomics and Proteomics." E3S Web of Conferences 399 (2023): 04042. http://dx.doi.org/10.1051/e3sconf/202339904042.

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Bioinformatics is a fast evolving field that combines biology, computer science, and statistics to analyze and comprehend enormous volumes of biological data. As a result of the introduction of high-throughput technologies like next-generation sequencing and mass spectrometry, genomic and proteomics research has generated enormous volumes of data, necessitating the development of computational tools to process and extract useful insights from these datasets. This presentation presents a survey of computational approaches in bioinformatics with a particular emphasis on their application to genomics and proteomics. The study of the entire genome is a topic covered in the discipline of genomics, which also includes genome annotation, assembly, and comparative genomics. Proteomics focuses on the investigation of proteins, including their identification, quantification, structural analysis, and functional characterization. Consequently, the importance of the area of bioinformatics has increased.

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González-Fernández, Raquel, Elena Prats, and Jesús V. Jorrín-Novo. "Proteomics of Plant Pathogenic Fungi." Journal of Biomedicine and Biotechnology 2010 (2010): 1–36. http://dx.doi.org/10.1155/2010/932527.

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Plant pathogenic fungi cause important yield losses in crops. In order to develop efficient and environmental friendly crop protection strategies, molecular studies of the fungal biological cycle, virulence factors, and interaction with its host are necessary. For that reason, several approaches have been performed using both classical genetic, cell biology, and biochemistry and the modern, holistic, and high-throughput, omic techniques. This work briefly overviews the tools available for studying Plant Pathogenic Fungi and is amply focused on MS-based Proteomics analysis, based on original papers published up to December 2009. At a methodological level, different steps in a proteomic workflow experiment are discussed. Separate sections are devoted to fungal descriptive (intracellular, subcellular, extracellular) and differential expression proteomics and interactomics. From the work published we can conclude that Proteomics, in combination with other techniques, constitutes a powerful tool for providing important information about pathogenicity and virulence factors, thus opening up new possibilities for crop disease diagnosis and crop protection.

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Koppel, Indrek, and Mike Fainzilber. "Omics approaches for subcellular translation studies." Molecular Omics 14, no. 6 (2018): 380–88. http://dx.doi.org/10.1039/c8mo00172c.

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Warren, Chad M., David L. Geenen, Donald L. Helseth,, Hua Xu, and R. John Solaro. "Sub-proteomic fractionation, iTRAQ, and OFFGEL-LC–MS/MS approaches to cardiac proteomics." Journal of Proteomics 73, no. 8 (June 2010): 1551–61. http://dx.doi.org/10.1016/j.jprot.2010.03.016.

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Paul, Debasish, Avinash Kumar, Akshada Gajbhiye, Manas K. Santra, and Rapole Srikanth. "Mass Spectrometry-Based Proteomics in Molecular Diagnostics: Discovery of Cancer Biomarkers Using Tissue Culture." BioMed Research International 2013 (2013): 1–16. http://dx.doi.org/10.1155/2013/783131.

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Accurate diagnosis and proper monitoring of cancer patients remain a key obstacle for successful cancer treatment and prevention. Therein comes the need for biomarker discovery, which is crucial to the current oncological and other clinical practices having the potential to impact the diagnosis and prognosis. In fact, most of the biomarkers have been discovered utilizing the proteomics-based approaches. Although high-throughput mass spectrometry-based proteomic approaches like SILAC, 2D-DIGE, and iTRAQ are filling up the pitfalls of the conventional techniques, still serum proteomics importunately poses hurdle in overcoming a wide range of protein concentrations, and also the availability of patient tissue samples is a limitation for the biomarker discovery. Thus, researchers have looked for alternatives, and profiling of candidate biomarkers through tissue culture of tumor cell lines comes up as a promising option. It is a rich source of tumor cell-derived proteins, thereby, representing a wide array of potential biomarkers. Interestingly, most of the clinical biomarkers in use today (CA 125, CA 15.3, CA 19.9, and PSA) were discovered through tissue culture-based system and tissue extracts. This paper tries to emphasize the tissue culture-based discovery of candidate biomarkers through various mass spectrometry-based proteomic approaches.

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Kazieva, L. Sh, T. E. Farafonova, and V. G. Zgoda. "Antibody proteomics." Biomeditsinskaya Khimiya 69, no. 1 (2023): 5–18. http://dx.doi.org/10.18097/pbmc20236901005.

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Antibodies represent an essential component of humoral immunity; therefore their study is important for molecular biology and medicine. The unique property of antibodies to specifically recognize and bind a certain molecular target (an antigen) determines their widespread application in treatment and diagnostics of diseases, as well as in laboratory and biotechnological practices. High specificity and affinity of antibodies is determined by the presence of primary structure variable regions, which are not encoded in the human genome and are unique for each antibody-producing B cell clone. Hence, there is little or no information about amino acid sequences of the variable regions in the databases. This differs identification of antibody primary structure from most of the proteomic studies because it requires either B cell genome sequencing or de novo amino acid sequencing of the antibody. The present review demonstrates some examples of proteomic and proteogenomic approaches and the methodological arsenal that proteomics can offer for studying antibodies, in particular, for identification of primary structure, evaluation of posttranslational modifications and application of bioinformatics tools for their decoding.

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Rroji, Merita, Andreja Figurek, and Goce Spasovski. "Proteomic Approaches and Potential Applications in Autosomal Dominant Polycystic Kidney Disease and Fabry Disease." Diagnostics 13, no. 6 (March 17, 2023): 1152. http://dx.doi.org/10.3390/diagnostics13061152.

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Although rare, hereditary diseases, such as autosomal dominant polycystic kidney disease (ADPKD) and Fabry disease (FD) may significantly progress towards severe nephropathy. It is crucial to characterize it accurately, predict the course of the illness and estimate treatment effectiveness. A huge effort has been undertaken to find reliable biomarkers that might be useful for an early prevention of the disease progression and/or any invasive diagnostic procedures. The study of proteomics, or the small peptide composition of a sample, is a field of study under continuous development. Over the past years, several strategies have been created to study and define the proteome of samples from widely varying origins. However, urinary proteomics has become essential for discovering novel biomarkers in kidney disease. Here, the extracellular vesicles in human urine that contain cell-specific marker proteins from every segment of the nephron, offer a source of potentially valuable urinary biomarkers, and may play an essential role in kidney development and kidney disease. This review summarizes the relevant literature investigating the proteomic approaches and potential applications in the regular studies of ADPKD and FD.

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Xu, Kai, and Peter D. Nagy. "Dissecting Virus-Plant Interactions Through Proteomics Approaches." Current Proteomics 7, no. 4 (December 1, 2010): 316–27. http://dx.doi.org/10.2174/157016410793611792.

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Kapoor, Isha, Pooja Pal, Savita Lochab, Jitendra Kumar Kanaujiya, and Arun Kumar Trivedi. "Proteomics approaches for myeloid leukemia drug discovery." Expert Opinion on Drug Discovery 7, no. 12 (September 13, 2012): 1165–75. http://dx.doi.org/10.1517/17460441.2012.724055.

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Korte, Robin, and Jens Brockmeyer. "Novel mass spectrometry approaches in food proteomics." TrAC Trends in Analytical Chemistry 96 (November 2017): 99–106. http://dx.doi.org/10.1016/j.trac.2017.07.010.

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Gingras, Anne-Claude, and Cassandra JJ Wong. "Proteomics approaches to decipher new signaling pathways." Current Opinion in Structural Biology 41 (December 2016): 128–34. http://dx.doi.org/10.1016/j.sbi.2016.07.008.

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Raghothama, Chaerkady, H. C. Harsha, C. K. Prasad, and Akhilesh Pandey. "Bioinformatics and Proteomics Approaches for Aging Research." Biogerontology 6, no. 4 (July 2005): 227–32. http://dx.doi.org/10.1007/s10522-005-2617-0.

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Ong, S. "Mass spectrometric-based approaches in quantitative proteomics." Methods 29, no. 2 (February 2003): 124–30. http://dx.doi.org/10.1016/s1046-2023(02)00303-1.

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Journal articles on the topic 'Proteomics approaches'

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