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1
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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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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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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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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Zheng, Ying, Lindsay Olita, McIver Nivens, Abby Chiang, Shreya Ahuja, Matthew Glover, John Bullen, Elaine Hurt, and Wenyan Zhong. "Abstract 2285: Mass spectrometry-based proteomics profiling reveals differential proteome composition in tumor and normal tissues, with implications for normalization." Cancer Research 84, no. 6_Supplement (March 22, 2024): 2285. http://dx.doi.org/10.1158/1538-7445.am2024-2285.
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Abstract The composition of the proteome varies significantly across different tissues and disease states creating a challenge of how best to compare expression levels of each protein across these tissue types. Traditionally, a median approach to normalization has been used, but this could obscure meaningful biological differences between tissues. Here, we present a quantitative proteomic study analyzing proteome composition across tumor and normal tissues in order to assess normalization methods. Human proteomes covering 7 cancer indications (244 samples) and 12 normal tissue organs (370 samples) were analyzed by data-independent acquisition mass spectrometry. On average, over 8,000 proteins were quantified across the study cohorts. Comparison of proteomes revealed an average of 11.4% higher protein identification in tumors compared to matched normal tissues (6 tumor types all p<0.003). Tissue origin strongly influenced proteome composition, most notably in bone marrow, while cancer tissues displayed less proteomic composition variation than normal tissues. Compared to global median normalization, riBAQ and tissue-specific quantile normalization reduced technical variances while maintaining biological differences between tissue types. By revealing tissue-specific proteome signatures as well as systemic proteomic alterations in tumors, this study lays the groundwork for appropriate comparative approaches accounting for tissue origins, and establishes a framework for discovery of tissue-specific biomarkers, which may facilitate the development of novel diagnostic and prognostic tests, and guide therapeutic interventions for cancer. Citation Format: Ying Zheng, Lindsay Olita, McIver Nivens, Abby Chiang, Shreya Ahuja, Matthew Glover, John Bullen, Elaine Hurt, Wenyan Zhong. Mass spectrometry-based proteomics profiling reveals differential proteome composition in tumor and normal tissues, with implications for normalization [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2285.
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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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Hulahan, Taylor S., Laura Spruill, Elizabeth N. Wallace, Yeonhee Park, Robert B. West, Jeffrey R. Marks, E. Shelley Hwang, Richard R. Drake, and Peggi M. Angel. "Extracellular Microenvironment Alterations in Ductal Carcinoma In Situ and Invasive Breast Cancer Pathologies by Multiplexed Spatial Proteomics." International Journal of Molecular Sciences 25, no. 12 (June 19, 2024): 6748. http://dx.doi.org/10.3390/ijms25126748.
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Ductal carcinoma in situ (DCIS) is a heterogeneous breast disease that remains challenging to treat due to its unpredictable progression to invasive breast cancer (IBC). Contemporary literature has become increasingly focused on extracellular matrix (ECM) alterations with breast cancer progression. However, the spatial regulation of the ECM proteome in DCIS has yet to be investigated in relation to IBC. We hypothesized that DCIS and IBC present distinct ECM proteomes that could discriminate between these pathologies. Tissue sections of pure DCIS, mixed DCIS-IBC, or pure IBC (n = 22) with detailed pathological annotations were investigated by multiplexed spatial proteomics. Across tissues, 1,005 ECM peptides were detected in pathologically annotated regions and their surrounding extracellular microenvironments. A comparison of DCIS to IBC pathologies demonstrated 43 significantly altered ECM peptides. Notably, eight fibrillar collagen peptides could distinguish with high specificity and sensitivity between DCIS and IBC. Lesion-targeted proteomic imaging revealed heterogeneity of the ECM proteome surrounding individual DCIS lesions. Multiplexed spatial proteomics reported an invasive cancer field effect, in which DCIS lesions in closer proximity to IBC shared a more similar ECM profile to IBC than distal counterparts. Defining the ECM proteomic microenvironment provides novel molecular insights relating to DCIS and IBC.
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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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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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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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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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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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Ozorun, Gulsev, Alexander Eckersley, Eleanor Bradley, Rachel Watson, Michael Sherrat, and Joe Swift. "P28 Data-independent acquisition mass spectrometry improves spatially resolved analysis of the human skin proteome." British Journal of Dermatology 190, no. 6 (May 17, 2024): e92-e92. http://dx.doi.org/10.1093/bjd/ljae105.050.
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Abstract Introduction and aims Proteomic analysis of the extracellular matrix (ECM) presents challenges because of the highly crosslinked and low-solubility nature of ECM proteins. Traditional homogenization and protein digestion approaches result in the loss of crucial information regarding protein localization and spatial relationships. To address this, spatially resolved proteomics emerges as a powerful tool for exploring heterogeneity within bulk tissues. This study aims to determine the minimum tissue volume required for comprehensive proteome coverage using data-independent acquisition mass spectrometry (DIA-MS) on skin tissue. The study focused on optimizing spatially resolved proteomic techniques to enhance depth-of-analysis while preserving spatial specificity. Methods Human abdominal skin biopsies were obtained from a single individual and subsequently cryosectioned. Histological assessment was performed through haematoxylin and eosin staining for visualization purposes. Laser-capture microdissection coupled with mass spectrometry facilitated the precise isolation of target regions. Comparative analyses were performed between data-dependent acquisition mass spectrometry (DDA-MS) and DIA-MS, with a particular emphasis on ECM proteins within the dermis. Results Our findings revealed an improvement in proteome coverage with DIA-MS compared with DDA-MS, in addition to clear scaling relationships between the depth-of-analysis and sample concentration. The Results demonstrated the superiority of DIA-MS in achieving robust and comprehensive proteomic profiles, even with minimal tissue volumes. Preliminary findings suggest the capability of DIA-MS in elucidating the complexities of the skin proteome with spatial resolution. Conclusions In conclusion, our study highlights the efficacy of DIA-MS in spatially resolved proteomics on skin tissue. The optimized approach presented here offers a reliable and efficient method for obtaining in-depth proteome information with minimal tissue requirements. These Results form the foundation for ongoing experiments, utilizing DIA-MS to advance spatially resolved proteomic analyses of human skin.
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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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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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Eckersall, David. "321 ASAS-EAAP Talk: Quantitative proteomics in animal and veterinary science: a pipeline for exploiting advanced analytical technology." Journal of Animal Science 98, Supplement_4 (November 3, 2020): 55–56. http://dx.doi.org/10.1093/jas/skaa278.100.
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Abstract Application of proteomic investigation to veterinary and animal sciences has grown over the last decade, but has still not reached its full potential of application in animal health and production research [1]. Nevertheless, establishing a versatile methodology has allowed the application of quantitative proteomics for increased understanding of physiological and pathophysiological challenges, and especially to identify potential biomarkers of disease in a range of animal species. A pipeline of sample preparation and mass spectrometry followed by statistical, bioinformatic and biochemical analyses has been established to deal with biofluids and tissue samples from cattle, sheep, pigs, chickens, dogs and cats as well as wild animals. Quantitative proteomic investigation of milk in an experimental model of Streptococcus uberis mastitis of dairy cows has identified potential novel biomarkers with implications for diagnosis and treatment of this major disease. Proteins in milk which have potential as disease biomarkers, such as cathelicidin, haptoglobin and mammary associated serum amyloid A3, are significantly increased in abundance during bovine mastitis. Proteomic investigation has confirmed that these biomarkers are also increased in milk during subclinical and clinical mastitis. Proteomic analysis of plasma from chicken following stimulation of the inflammatory response to Escherichia coli lipopolysaccharide endotoxin has characterised major changes in the chicken plasma proteome. Novel biomarker candidates of hemopexin and fatty acid binding protein have been identified. This proteomic pipeline can be incorporated into many areas of research, providing novel findings at the forefront of animal and veterinary science. Such proteomic investigation requires close interdisciplinary collaboration between experts in mass spectrometry, bioinformatics, statistics and animal production in order to fully exploit recent technological advances in the omic sciences.[1] P. Bilic, et al, Proteomics in Veterinary Medicine and Animal Science: Neglected Scientific Opportunities with Immediate Impact, Proteomics. 47 (2018) 1–7. doi:10.1002/pmic.201800047.
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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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Sobolev, Vladimir V., Anna G. Soboleva, Elena V. Denisova, Eva A. Pechatnikova, Eugenia Dvoryankova, Irina M. Korsunskaya, and Alexandre Mezentsev. "Proteomic Studies of Psoriasis." Biomedicines 10, no. 3 (March 7, 2022): 619. http://dx.doi.org/10.3390/biomedicines10030619.
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In this review paper, we discuss the contribution of proteomic studies to the discovery of disease-specific biomarkers to monitor the disease and evaluate available treatment options for psoriasis. Psoriasis is one of the most prevalent skin disorders driven by a Th17-specific immune response. Although potential patients have a genetic predisposition to psoriasis, the etiology of the disease remains unknown. During the last two decades, proteomics became deeply integrated with psoriatic research. The data obtained in proteomic studies facilitated the discovery of novel mechanisms and the verification of many experimental hypotheses of the disease pathogenesis. The detailed data analysis revealed multiple differentially expressed proteins and significant changes in proteome associated with the disease and drug efficacy. In this respect, there is a need for proteomic studies to characterize the role of the disease-specific biomarkers in the pathogenesis of psoriasis, develop clinical applications to choose the most efficient treatment options and monitor the therapeutic response.
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Alaa, Maram, Nouran Al-Shehaby, Ali Mostafa Anwar, Nesma Farid, Mustafa Shaban Shawky, Manal Zamzam, Iman Zaky, Ahmed Elghounimy, Shahenda El-Naggar, and Sameh Magdeldin. "Comparative Shotgun Proteomics Reveals the Characteristic Protein Signature of Osteosarcoma Subtypes." Cells 12, no. 17 (August 30, 2023): 2179. http://dx.doi.org/10.3390/cells12172179.
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Osteosarcoma is a primary malignant bone tumor affecting adolescents and young adults. This study aimed to identify proteomic signatures that distinguish between different osteosarcoma subtypes, providing insights into their molecular heterogeneity and potential implications for personalized treatment approaches. Using advanced proteomic techniques, we analyzed FFPE tumor samples from a cohort of pediatric osteosarcoma patients representing four various subtypes. Differential expression analysis revealed a significant proteomic signature that discriminated between these subtypes, highlighting distinct molecular profiles associated with different tumor characteristics. In contrast, clinical determinants did not correlate with the proteome signature of pediatric osteosarcoma. The identified proteomics signature encompassed a diverse array of proteins involved in focal adhesion, ECM-receptor interaction, PI3K-Akt signaling pathways, and proteoglycans in cancer, among the top enriched pathways. These findings underscore the importance of considering the molecular heterogeneity of osteosarcoma during diagnosis or even when developing personalized treatment strategies. By identifying subtype-specific proteomics signatures, clinicians may be able to tailor therapy regimens to individual patients, optimizing treatment efficacy and minimizing adverse effects.
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Fels, Ursula, Patrick Willems, Margaux De Meyer, Kris Gevaert, and Petra Van Damme. "Shift in vacuolar to cytosolic regime of infecting Salmonella from a dual proteome perspective." PLOS Pathogens 19, no. 8 (August 3, 2023): e1011183. http://dx.doi.org/10.1371/journal.ppat.1011183.
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By applying dual proteome profiling to Salmonella enterica serovar Typhimurium (S. Typhimurium) encounters with its epithelial host (here, S. Typhimurium infected human HeLa cells), a detailed interdependent and holistic proteomic perspective on host-pathogen interactions over the time course of infection was obtained. Data-independent acquisition (DIA)-based proteomics was found to outperform data-dependent acquisition (DDA) workflows, especially in identifying the downregulated bacterial proteome response during infection progression by permitting quantification of low abundant bacterial proteins at early times of infection when bacterial infection load is low. S. Typhimurium invasion and replication specific proteomic signatures in epithelial cells revealed interdependent host/pathogen specific responses besides pointing to putative novel infection markers and signalling responses, including regulated host proteins associated with Salmonella-modified membranes.
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Mittapelly, Priyanka, and Swapna Priya Rajarapu. "Applications of Proteomic Tools to Study Insect Vector–Plant Virus Interactions." Life 10, no. 8 (August 7, 2020): 143. http://dx.doi.org/10.3390/life10080143.
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Proteins are crucial players of biological interactions within and between the organisms and thus it is important to understand the role of proteins in successful partnerships, such as insect vectors and their plant viruses. Proteomic approaches have identified several proteins at the interface of virus acquisition and transmission by their insect vectors which could be potential molecular targets for sustainable pest and viral disease management strategies. Here we review the proteomic techniques used to study the interactions of insect vector and plant virus. Our review will focus on the techniques available to identify the infection, global changes at the proteome level in insect vectors, and protein-protein interactions of insect vectors and plant viruses. Furthermore, we also review the integration of other techniques with proteomics and the available bioinformatic tools to analyze the proteomic data.
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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.
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Semančíková, E., S. Tkáčiková, I. Talian, M. Bencková, E. Pálová, and J. Sabo. "In Search of Possible Peripheral Biomarkers for Suicide: Similarities Between Platelet and Cerebrospinal Fluid Proteome (Preliminary Results)." European Psychiatry 41, S1 (April 2017): S638. http://dx.doi.org/10.1016/j.eurpsy.2017.01.1051.
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Despite the fact that proteomic analysis is becoming widely used in various medical branches its use in psychiatry is still very limited. Majority of psychiatric proteomic research is still oriented mostly on Alzheimer's disease, schizophrenia and depression but very few studies focus on suicidality. We decided, based on the current knowledge, to study suicidal behaviour with the use of proteomics to compare cerebrospinal fluid and platelets. We hypothesized that the same protein group can be detected in pathways that are part of platelet degranulation process in the platelet proteome and cerebrospinal fluid proteome. Based on these findings we suppose, that with use of proteomic analysis a specific protein (group of proteins) can be identified in both, cerebrospinal fluid and platelet proteome in patients with suicidal behavior.Group of proteins identified in our sample in the reactome pathway database (release of platelet secretary granule components and exocytosis of platelet granule contents) supports the idea of link between central nervous system and platelets (“the periphery”). Further research is needed to clarify whether the identified group of proteins taking part in platelet pathways can be used as peripheral biomarkers for suicidal behavior.Disclosure of interestThe authors have not supplied their declaration of competing interest.
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Petriz, Bernardo A., and Octavio L. Franco. "Effects of Hypertension and Exercise on Cardiac Proteome Remodelling." BioMed Research International 2014 (2014): 1–14. http://dx.doi.org/10.1155/2014/634132.
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Left ventricle hypertrophy is a common outcome of pressure overload stimulus closely associated with hypertension. This process is triggered by adverse molecular signalling, gene expression, and proteome alteration. Proteomic research has revealed that several molecular targets are associated with pathologic cardiac hypertrophy, including angiotensin II, endothelin-1 and isoproterenol. Several metabolic, contractile, and stress-related proteins are shown to be altered in cardiac hypertrophy derived by hypertension. On the other hand, exercise is a nonpharmacologic agent used for hypertension treatment, where cardiac hypertrophy induced by exercise training is characterized by improvement in cardiac function and resistance against ischemic insult. Despite the scarcity of proteomic research performed with exercise, healthy and pathologic heart proteomes are shown to be modulated in a completely different way. Hence, the altered proteome induced by exercise is mostly associated with cardioprotective aspects such as contractile and metabolic improvement and physiologic cardiac hypertrophy. The present review, therefore, describes relevant studies involving the molecular characteristics and alterations from hypertensive-induced and exercise-induced hypertrophy, as well as the main proteomic research performed in this field. Furthermore, proteomic research into the effect of hypertension on other target-demerged organs is examined.
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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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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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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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Angi, Martina, Helen Kalirai, Sarah E. Coupland, Bertil E. Damato, Francesco Semeraro, and Mario R. Romano. "Proteomic Analyses of the Vitreous Humour." Mediators of Inflammation 2012 (2012): 1–7. http://dx.doi.org/10.1155/2012/148039.
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The human vitreous humour (VH) is a transparent, highly hydrated gel, which occupies the posterior segment of the eye between the lens and the retina. Physiological and pathological conditions of the retina are reflected in the protein composition of the VH, which can be sampled as part of routine surgical procedures. Historically, many studies have investigated levels of individual proteins in VH from healthy and diseased eyes. In the last decade, proteomics analyses have been performed to characterise the proteome of the human VH and explore networks of functionally related proteins, providing insight into the aetiology of diabetic retinopathy and proliferative vitreoretinopathy. Recent proteomic studies on the VH from animal models of autoimmune uveitis have identified new signalling pathways associated to autoimmune triggers and intravitreal inflammation. This paper aims to guide biological scientists through the different proteomic techniques that have been used to analyse the VH and present future perspectives for the study of intravitreal inflammation using proteomic analyses.
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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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Roy, Marcia, Oksana Sorokina, Colin McLean, Silvia Tapia-González, Javier DeFelipe, J. Armstrong, and Seth Grant. "Regional Diversity in the Postsynaptic Proteome of the Mouse Brain." Proteomes 6, no. 3 (August 1, 2018): 31. http://dx.doi.org/10.3390/proteomes6030031.
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The proteome of the postsynaptic terminal of excitatory synapses comprises over one thousand proteins in vertebrate species and plays a central role in behavior and brain disease. The brain is organized into anatomically distinct regions and whether the synapse proteome differs across these regions is poorly understood. Postsynaptic proteomes were isolated from seven forebrain and hindbrain regions in mice and their composition determined using proteomic mass spectrometry. Seventy-four percent of proteins showed differential expression and each region displayed a unique compositional signature. These signatures correlated with the anatomical divisions of the brain and their embryological origins. Biochemical pathways controlling plasticity and disease, protein interaction networks and individual proteins involved with cognition all showed differential regional expression. Combining proteomic and connectomic data shows that interconnected regions have specific proteome signatures. Diversity in synapse proteome composition is key feature of mouse and human brain structure.
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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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Soleymani, Nooshinmehr, Soheil Sadr, Cinzia Santucciu, Shiva Dianaty, Narges Lotfalizadeh, Ashkan Hajjafari, Fatemeh Heshmati, and Hassan Borji. "Unveiling Novel Insights in Helminth Proteomics: Advancements, Applications, and Implications for Parasitology and Beyond." Biologics 4, no. 3 (September 19, 2024): 314–44. http://dx.doi.org/10.3390/biologics4030020.
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Helminths have developed intricate mechanisms to survive and evade the host’s immune responses. Hence, understanding the excretory-secretory products (ESPs) by helminths is crucial for developing control tools, including drug targets, vaccines, and potential therapies for inflammatory and metabolic disorders caused by them. Proteomics, the large-scale analysis of proteins, offers a powerful approach to unravel the complex proteomes of helminths and gain insights into their biology. Proteomics, as a science that delves into the functions of proteins, has the potential to revolutionize clinical therapies against parasitic infections that have developed anthelminthic resistance. Proteomic technologies lay a framework for accompanying genomic, reverse genetics, and pharmacokinetic approaches to provide more profound or broader coverage of the cellular mechanisms that underlie the response to anthelmintics. With the development of vaccines against helminth infections, proteomics has brought a major change to parasitology. The proteome of helminths can be analyzed comprehensively, revealing the complex network of proteins that enable parasite survival and pathogenicity. Furthermore, it reveals how parasites interact with hosts’ immune systems. The current article reviews the latest advancements in helminth proteomics and highlights their valuable contributions to the search for anthelminthic vaccines.
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Woodland, Breyer, Aleksandar Necakov, and Jens R. Coorssen. "Optimized Proteome Reduction for Integrative Top–Down Proteomics." Proteomes 11, no. 1 (March 6, 2023): 10. http://dx.doi.org/10.3390/proteomes11010010.
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Integrative top–down proteomics is an analytical approach that fully addresses the breadth and complexity needed for effective and routine assessment of proteomes. Nonetheless, any such assessments also require a rigorous review of methodology to ensure the deepest possible quantitative proteome analyses. Here, we establish an optimized general protocol for proteome extracts to improve the reduction of proteoforms and, thus, resolution in 2DE. Dithiothreitol (DTT), tributylphosphine (TBP), and 2-hydroxyethyldisulfide (HED), combined and alone, were tested in one-dimensional SDS-PAGE (1DE), prior to implementation into a full 2DE protocol. Prior to sample rehydration, reduction with 100 mM DTT + 5 mM TBP yielded increased spot counts, total signal, and spot circularity (i.e., decreased streaking) compared to other conditions and reduction protocols reported in the literature. The data indicate that many widely implemented reduction protocols are significantly ‘under-powered’ in terms of proteoform reduction and thus, limit the quality and depth of routine top–down proteomic analyses.
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Serambeque, Beatriz, Catarina Mestre, Kristina Hundarova, Carlos Miguel Marto, Bárbara Oliveiros, Ana Rita Gomes, Ricardo Teixo, et al. "Proteomic Profile of Endometrial Cancer: A Scoping Review." Biology 13, no. 8 (August 1, 2024): 584. http://dx.doi.org/10.3390/biology13080584.
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Proteomics can be a robust tool in protein identification and regulation, allowing the discovery of potential biomarkers. In clinical practice, the management of endometrial cancer can be challenging. Thus, identifying promising markers could be beneficial, helping both in diagnosis and prognostic stratification, even predicting the response to therapy. Therefore, this manuscript systematically reviews the existing evidence of the proteomic profile of human endometrial cancer. The literature search was conducted via Medline (through PubMed) and the Web of Science. The inclusion criteria were clinical, in vitro, and in vivo original studies reporting proteomic analysis using all types of samples to map the human endometrial cancer proteome. A total of 55 publications were included in this review. Most of the articles carried out a proteomic analysis on endometrial tissue, serum and plasma samples, which enabled the identification of several potential diagnostic and prognostic biomarkers. In addition, eight articles were analyzed regarding the identified proteins, where three studies showed a strong correlation, sharing forty-five proteins. This analysis also allowed the identification of the 10 most frequently reported proteins in these studies: EGFR, PGRMC1, CSE1L, MYDGF, STMN1, CASP3 ANXA2, YBX1, ANXA1, and MYH11. Proteomics-based approaches pointed out potential diagnostic and prognostic candidates for endometrial cancer. However, there is a lack of studies exploring novel therapeutic targets.
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Panner Selvam, Manesh, Ashok Agarwal, Tânia Dias, Ana Martins, and Luna Samanta. "Presence of Round Cells Proteins do not Interfere with Identification of Human Sperm Proteins from Frozen Semen Samples by LC-MS/MS." International Journal of Molecular Sciences 20, no. 2 (January 14, 2019): 314. http://dx.doi.org/10.3390/ijms20020314.
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In sperm proteomic experiments round cells and leukocyte proteins are profiled along with sperm proteome. The influence of round cell and leukocyte proteins on the sperm proteome has not been investigated. The objective of this study was to identify if the proteins from round cells, including leukocytes, interfere with the proteomic analysis of spermatozoa in frozen semen samples. Proteomic profiling of sperm was performed using liquid chromatography-tandem mass spectrometry in four groups: Group 1 contained neat semen with round cells and leukocytes ≥ 1 × 106/mL, group 2 contained neat semen with round cells ≥ 1 × 106/mL that was processed by 65% density gradient to remove the round cells and leukocytes, group 3 contained neat semen with round cells < 1 × 106/mL, and group 4 contained neat semen with round cells < 1 × 106/mL that was processed by 65% density gradient to remove the round cells. Pure leukocyte culture was used as control group. A total of 1638, 1393, 1755, and 1404 proteins were identified in groups 1, 2, 3, and 4, respectively. Comparative analysis of group 1 vs. 3 revealed 26 (1.18%) differentially expressed proteins (DEPs). On the other hand, only 6 (0.31%) DEPs were observed with group 2 vs. 4. Expression of these DEPs were either absent or very low in the control group. The results of our proteomics analysis failed to show any influence of non-spermatogenic round cell proteins on sperm proteome identification. These results validate the use of neat semen samples for sperm proteomic studies.
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Dourdouna, Maria-Myrto, Elizabeth-Barbara Tatsi, Vasiliki Syriopoulou, and Athanasios Michos. "Proteomic Signatures of Multisystem Inflammatory Syndrome in Children (MIS-C) Associated with COVID-19: A Narrative Review." Children 11, no. 10 (September 26, 2024): 1174. http://dx.doi.org/10.3390/children11101174.
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Background/Objectives: Multisystem Inflammatory Syndrome in Children (MIS-C) is a post-infectious complication of COVID-19. MIS-C has overlapping features with other pediatric inflammatory disorders including Kawasaki Disease (KD), Macrophage Activation Syndrome (MAS), Toxic Shock Syndrome and sepsis. The exact mechanisms responsible for the clinical overlap between MIS-C and these conditions remain unclear, and biomarkers that could distinguish MIS-C from its clinical mimics are lacking. This study aimed to provide an overview of how proteomic methods, like Mass Spectrometry (MS) and affinity-based proteomics, can offer a detailed understanding of pathophysiology and aid in the diagnosis and prognosis of MIS-C. Methods: A narrative review of relevant studies published up to July 2024 was conducted. Results: We identified 15 studies and summarized their key proteomic findings. These studies investigated the serum or plasma proteome of MIS-C patients using MS, Proximity Extension, or Aptamer-based assays. The studies associated the proteomic profile of MIS-C with laboratory and clinical parameters and/or compared it with that of other diseases including acute COVID-19, KD, MAS, pediatric rheumatic diseases, sepsis and myocarditis or pericarditis following COVID-19 mRNA immunization. Depending on the method and the control group, different proteins were increased or decreased in the MIS-C group. The limitations and challenges in MIS-C proteomic research are also discussed, and future research recommendations are provided. Conclusions: Although proteomics appear to be a promising approach for understanding the pathogenesis and uncovering candidate biomarkers in MIS-C, proteomic studies are still needed to recognize and validate biomarkers that could accurately discriminate MIS-C from its clinical mimics.
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Dowling, Paul, Dieter Swandulla, and Kay Ohlendieck. "Mass Spectrometry-Based Proteomic Technology and Its Application to Study Skeletal Muscle Cell Biology." Cells 12, no. 21 (November 1, 2023): 2560. http://dx.doi.org/10.3390/cells12212560.
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Voluntary striated muscles are characterized by a highly complex and dynamic proteome that efficiently adapts to changed physiological demands or alters considerably during pathophysiological dysfunction. The skeletal muscle proteome has been extensively studied in relation to myogenesis, fiber type specification, muscle transitions, the effects of physical exercise, disuse atrophy, neuromuscular disorders, muscle co-morbidities and sarcopenia of old age. Since muscle tissue accounts for approximately 40% of body mass in humans, alterations in the skeletal muscle proteome have considerable influence on whole-body physiology. This review outlines the main bioanalytical avenues taken in the proteomic characterization of skeletal muscle tissues, including top-down proteomics focusing on the characterization of intact proteoforms and their post-translational modifications, bottom-up proteomics, which is a peptide-centric method concerned with the large-scale detection of proteins in complex mixtures, and subproteomics that examines the protein composition of distinct subcellular fractions. Mass spectrometric studies over the last two decades have decisively improved our general cell biological understanding of protein diversity and the heterogeneous composition of individual myofibers in skeletal muscles. This detailed proteomic knowledge can now be integrated with findings from other omics-type methodologies to establish a systems biological view of skeletal muscle function.
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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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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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Annunziata, C. M., N. Azad, A. S. Dhamoon, G. Whiteley, and E. C. Kohn. "Ovarian cancer in the proteomics era." International Journal of Gynecologic Cancer 18, Suppl 1 (2008): 1–6. http://dx.doi.org/10.1111/j.1525-1438.2007.01096.x.
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Ovarian cancer presents a diagnostic challenge because of its subtle clinical presentation and elusive cell of origin. Two new technologies of proteomics have advanced the dissection of the underlying molecular signaling events and the proteomic characterization of ovarian cancer: mass spectrometry and protein array analysis. Mass spectrometry can provide a snapshot of a proteome in time and space, with sensitivity and resolution that may allow identification of the elusive “needle in the haystack” heralding ovarian cancer. Proteomic profiling of tumor tissue samples can survey molecular targets during treatment and quantify changes using reverse phase protein arrays generated from tumor samples captured by microdissection, lysed and spotted in serial dilutions for high-throughput analysis. This approach can be applied to identify the optimal biological dose of a targeted agent and to validate target to outcome link. The evolution of proteomic technologies has the capacity to advance rapidly our understanding of ovarian cancer at a molecular level and thus elucidate new directions for the treatment of this disease
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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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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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Hill, Jennifer J., Arsalan S. Haqqani, and Danica B. Stanimirovic. "Proteome of the Luminal Surface of the Blood–Brain Barrier." Proteomes 9, no. 4 (November 10, 2021): 45. http://dx.doi.org/10.3390/proteomes9040045.
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Interrogation of the molecular makeup of the blood–brain barrier (BBB) using proteomic techniques has contributed to the cataloguing and functional understanding of the proteins uniquely organized at this specialized interface. The majority of proteomic studies have focused on cellular components of the BBB, including cultured brain endothelial cells (BEC). Detailed proteome mapping of polarized BEC membranes and their intracellular endosomal compartments has led to an improved understanding of the processes leading to internalization and transport of various classes of molecules across the BBB. Quantitative proteomic methods have further enabled absolute and comparative quantification of key BBB transporters and receptors in isolated BEC and microvessels from various species. However, translational studies further require in vivo/in situ analyses of the proteins exposed on the luminal surface of BEC in vessels under various disease and treatment conditions. In vivo proteomics approaches, both profiling and quantitative, usually rely on ‘capturing’ luminally-exposed proteins after perfusion with chemical labeling reagents, followed by analysis with various mass spectrometry-based approaches. This manuscript reviews recent advances in proteomic analyses of luminal membranes of BEC in vitro and in vivo and their applications in translational studies focused on developing novel delivery methods across the BBB.
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Arnold, Georg J., and T. Frohlich. "Dynamic proteome signatures in gametes, embryos and their maternal environment." Reproduction, Fertility and Development 23, no. 1 (2011): 81. http://dx.doi.org/10.1071/rd10223.
Full textAbstract:
Comprehensive molecular analysis at the level of proteins represents a technically demanding, but indispensable, task since several post-transcriptional regulation mechanisms disable a valid prediction of quantitative protein expression profiles from transcriptome analysis. In crucial steps of gamete and early embryo development, de novo transcription is silenced, meaning that almost all macromolecular events take place at the level of proteins. In this review, we describe selected examples of dynamic proteome signatures addressing capacitation of spermatozoa, in vitro maturation of oocytes, effect of oestrous cycle on oviduct epithelial cells and embryo-induced alterations to the maternal environment. We also present details of the experimental strategies applied and the experiments performed to verify quantitative proteomic data. Far from being comprehensive, examples were selected to cover several mammalian species as well as the most powerful proteomic techniques currently applied. To enable non-experts in the field of proteomics to appraise published proteomic data, our examples are preceded by a customised description of quantitative proteomic methods, covering 2D difference gel electrophoresis (2D-DIGE), nano-liquid chromatography combined with tandem mass spectrometry, and label-free as well as stable-isotope labelling strategies for mass spectrometry-based quantifications.
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Kline, Rachel A., Lena Lößlein, Dominic Kurian, Judit Aguilar Martí, Samantha L. Eaton, Felipe A. Court, Thomas H. Gillingwater, and Thomas M. Wishart. "An Optimized Comparative Proteomic Approach as a Tool in Neurodegenerative Disease Research." Cells 11, no. 17 (August 26, 2022): 2653. http://dx.doi.org/10.3390/cells11172653.
Full textAbstract:
Recent advances in proteomic technologies now allow unparalleled assessment of the molecular composition of a wide range of sample types. However, the application of such technologies and techniques should not be undertaken lightly. Here, we describe why the design of a proteomics experiment itself is only the first step in yielding high-quality, translatable results. Indeed, the effectiveness and/or impact of the majority of contemporary proteomics screens are hindered not by commonly considered technical limitations such as low proteome coverage but rather by insufficient analyses. Proteomic experimentation requires a careful methodological selection to account for variables from sample collection, through to database searches for peptide identification to standardised post-mass spectrometry options directed analysis workflow, which should be adjusted for each study, from determining when and how to filter proteomic data to choosing holistic versus trend-wise analyses for biologically relevant patterns. Finally, we highlight and discuss the difficulties inherent in the modelling and study of the majority of progressive neurodegenerative conditions. We provide evidence (in the context of neurodegenerative research) for the benefit of undertaking a comparative approach through the application of the above considerations in the alignment of publicly available pre-existing data sets to identify potential novel regulators of neuronal stability.
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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.
Full textAbstract:
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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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.
Full textAbstract:
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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Meng, Zhaoyang, Ran You, Arif Mahmood, Fancheng Yan, and Yanling Wang. "Application of Proteomics Analysis and Animal Models in Optic Nerve Injury Diseases." Brain Sciences 13, no. 3 (February 26, 2023): 404. http://dx.doi.org/10.3390/brainsci13030404.
Full textAbstract:
Optic nerve damage is a common cause of blindness. Optic nerve injury is often accompanied by fundus vascular disease, retinal ganglion cell apoptosis, and changes in retinal thickness. These changes can cause alterations in protein expression within neurons in the retina. Proteomics analysis offers conclusive evidence to decode a biological system. Furthermore, animal models of optic nerve injury made it possible to gain insight into pathological mechanisms, therapeutic targets, and effective treatment of such injuries. Proteomics takes the proteome as the research object and studies protein changes in cells and tissues. At present, a variety of proteomic analysis methods have been widely used in the research of optic nerve injury diseases. This review summarizes the application of proteomic research in optic nerve injury diseases and animal models of optic nerve injury. Additionally, differentially expressed proteins are summarized and analyzed. Various optic nerve injuries, including those associated with different etiologies, are discussed along with their potential therapeutic targets and future directions.
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Glazyrin, Yury E., Dmitry V. Veprintsev, Irina A. Ler, Maria L. Rossovskaya, Svetlana A. Varygina, Sofia L. Glizer, Tatiana N. Zamay, et al. "Proteomics-Based Machine Learning Approach as an Alternative to Conventional Biomarkers for Differential Diagnosis of Chronic Kidney Diseases." International Journal of Molecular Sciences 21, no. 13 (July 7, 2020): 4802. http://dx.doi.org/10.3390/ijms21134802.
Full textAbstract:
Diabetic nephropathy, hypertension, and glomerulonephritis are the most common causes of chronic kidney diseases (CKD). Since CKD of various origins may not become apparent until kidney function is significantly impaired, a differential diagnosis and an appropriate treatment are needed at the very early stages. Conventional biomarkers may not have sufficient separation capabilities, while a full-proteomic approach may be used for these purposes. In the current study, several machine learning algorithms were examined for the differential diagnosis of CKD of three origins. The tested dataset was based on whole proteomic data obtained after the mass spectrometric analysis of plasma and urine samples of 34 CKD patients and the use of label-free quantification approach. The k-nearest-neighbors algorithm showed the possibility of separation of a healthy group from renal patients in general by proteomics data of plasma with high confidence (97.8%). This algorithm has also be proven to be the best of the three tested for distinguishing the groups of patients with diabetic nephropathy and glomerulonephritis according to proteomics data of plasma (96.3% of correct decisions). The group of hypertensive nephropathy could not be reliably separated according to plasma data, whereas analysis of entire proteomics data of urine did not allow differentiating the three diseases. Nevertheless, the group of hypertensive nephropathy was reliably separated from all other renal patients using the k-nearest-neighbors classifier “one against all” with 100% of accuracy by urine proteome data. The tested algorithms show good abilities to differentiate the various groups across proteomic data sets, which may help to avoid invasive intervention for the verification of the glomerulonephritis subtypes, as well as to differentiate hypertensive and diabetic nephropathy in the early stages based not on individual biomarkers, but on the whole proteomic composition of urine and blood.