Journal articles: 'Label-free quantitative proteomic'

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Ankney, J. Astor, Adil Muneer, and Xian Chen. "Relative and Absolute Quantitation in Mass Spectrometry–Based Proteomics." Annual Review of Analytical Chemistry 11, no. 1 (June 12, 2018): 49–77. http://dx.doi.org/10.1146/annurev-anchem-061516-045357.

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Mass spectrometry–based quantitative proteomics is a powerful tool for gaining insights into function and dynamics of biological systems. However, peptides with different sequences have different ionization efficiencies, and their intensities in a mass spectrum are not correlated with their abundances. Therefore, various label-free or stable isotope label–based quantitation methods have emerged to assist mass spectrometry to perform comparative proteomic experiments, thus enabling nonbiased identification of thousands of proteins differentially expressed in healthy versus diseased cells. Here, we discuss the most widely used label-free and metabolic-, enzymatic-, and chemical labeling–based proteomic strategies for relative and absolute quantitation. We summarize the specific strengths and weaknesses of each technique in terms of quantification accuracy, proteome coverage, multiplexing capability, and robustness. Applications of each strategy for solving specific biological complexities are also presented.

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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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Silva, Wanderson M., Cassiana S. Sousa, Leticia C. Oliveira, Siomar C. Soares, Gustavo F. M. H. Souza, Guilherme C. Tavares, Cristiana P. Resende, et al. "Comparative proteomic analysis of four biotechnological strainsLactococcus lactisthrough label-free quantitative proteomics." Microbial Biotechnology 12, no. 2 (October 19, 2018): 265–74. http://dx.doi.org/10.1111/1751-7915.13305.

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Zhang, Yan, and Ioannis P. Nezis. "Label-free quantitative proteomic analysis of adult Drosophila heads." STAR Protocols 3, no. 4 (December 2022): 101830. http://dx.doi.org/10.1016/j.xpro.2022.101830.

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Burch, Andrew R., Cody W. Yothers, Michelle R. Salemi, Brett S. Phinney, Pramod Pandey, and Annaliese K. Franz. "Quantitative label-free proteomics and biochemical analysis of Phaeodactylum tricornutum cultivation on dairy manure wastewater." Journal of Applied Phycology 33, no. 4 (May 27, 2021): 2105–21. http://dx.doi.org/10.1007/s10811-021-02483-3.

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AbstractMicroalgae cultivation on wastewater offers the dual benefit of lowering costs for feedstock production with simultaneous wastewater remediation. This study utilized biochemical and quantitative label-free proteomic approaches to evaluate the growth and proteomic response for diatom Phaeodactylum tricornutum cultivated on flushed dairy manure wastewater (DMW). Comparing several DMW dilutions (up to 60% DMW diluted in seawater) with a synthetic seawater medium indicates that biomass and lipid yields correlate with the starting nitrogen content of the DMW dilution. Phaeodactylum tricornutum cultivated on DMW exhibits elevated levels of polyunsaturated fatty acids (PUFAs), particularly docosapentaenoic acid (DPA, 22:5 n-3). Proteomic analysis revealed alterations in the regulations of proteins associated with protein metabolism, cellular signaling, transcription and translation, protein trafficking, and oxidative stress management pathways when comparing P. tricornutum cultivation on diluted DMW versus synthetic media, thus providing insights into how P. tricornutum reorganizes its proteome in response to a complex wastewater source. Graphical abstract

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Karpiński, Adam Aleksander, Julio Cesar Torres Elguera, Anne Sanner, Witold Konopka, Leszek Kaczmarek, Dominic Winter, Anna Konopka, and Ewa Bulska. "Study on Tissue Homogenization Buffer Composition for Brain Mass Spectrometry-Based Proteomics." Biomedicines 10, no. 10 (October 2, 2022): 2466. http://dx.doi.org/10.3390/biomedicines10102466.

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Mass spectrometry-based proteomics aims to study the proteome both qualitatively and quantitatively. A key step in proteomic analysis is sample preparation, which is crucial for reliable results. We investigated the effect of the composition of the homogenization buffer used to extract proteins from brain tissue on the yield of protein extraction and the number and type of extracted proteins. Three different types of buffers were compared—detergent-based buffer (DB), chaotropic agent-based buffer (CAB) and buffer without detergent and chaotropic agent (DFB). Based on label-free quantitative protein analysis, detergent buffer was identified as the most suitable for global proteomic profiling of brain tissue. It allows the most efficient extraction of membrane proteins, synaptic and synaptic membrane proteins along with ribosomal, mitochondrial and myelin sheath proteins, which are of particular interest in the field of neurodegenerative disorders research.

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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.

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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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Kohli, Priyanka, Malte P. Bartram, Sandra Habbig, Caroline Pahmeyer, Tobias Lamkemeyer, Thomas Benzing, Bernhard Schermer, and Markus M. Rinschen. "Label-free quantitative proteomic analysis of the YAP/TAZ interactome." American Journal of Physiology-Cell Physiology 306, no. 9 (May 1, 2014): C805—C818. http://dx.doi.org/10.1152/ajpcell.00339.2013.

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The function of an individual protein is typically defined by protein-protein interactions orchestrating the formation of large complexes critical for a wide variety of biological processes. Over the last decade the analysis of purified protein complexes by mass spectrometry became a key technique to identify protein-protein interactions. We present a fast and straightforward approach for analyses of interacting proteins combining a Flp-in single-copy cellular integration system and single-step affinity purification with single-shot mass spectrometry analysis. We applied this protocol to the analysis of the YAP and TAZ interactome. YAP and TAZ are the downstream effectors of the mammalian Hippo tumor suppressor pathway. Our study provides comprehensive interactomes for both YAP and TAZ and does not only confirm the majority of previously described interactors but, strikingly, revealed uncharacterized interaction partners that affect YAP/TAZ TEAD-dependent transcription. Among these newly identified candidates are Rassf8, thymopoetin, and the transcription factors CCAAT/enhancer-binding protein (C/EBP)β/δ and core-binding factor subunit β (Cbfb). In addition, our data allowed insights into complex stoichiometry and uncovered discrepancies between the YAP and TAZ interactomes. Taken together, the stringent approach presented here could help to significantly sharpen the understanding of protein-protein networks.

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Di Luca, Alessio, Andrea Ianni, Francesca Bennato, Michael Henry, Paula Meleady, and Giuseppe Martino. "A Label-Free Quantitative Analysis for the Search of Proteomic Differences between Goat Breeds." Animals 12, no. 23 (November 29, 2022): 3336. http://dx.doi.org/10.3390/ani12233336.

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The intensification and standardization of livestock farming are causing a decline in the number of animal breeds in many species, such as the goat. The availability of more studies on the potentiality of goat breeds could raise awareness of their importance, conservation and productive possibilities. Label-free quantitative analysis was applied in this study to investigate the proteomic differences between the autochthon Teramana and Saanen goats that could be useful for defining peculiar features of these breeds. A total of 2093 proteins were characterized in the muscle exudate proteome of the Teramana and Saanen breeds. A total of 41 proteins clearly separated the two breeds. Eukaryotic initiation factor proteins and aldehyde-dehydrogenase 7 family-member A1 were up-regulated in the autochthon breed and associated with its resilience, whereas catalase was down-regulated and associated with lower muscular mass. This study is the most detailed report of goat muscle proteome. Several differentially regulated proteins between the two breeds were identified, providing insights into functional pathways that define this organism and its biology.

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Mosley, Amber L., Laurence Florens, Zhihui Wen, and Michael P. Washburn. "A label free quantitative proteomic analysis of the Saccharomyces cerevisiae nucleus." Journal of Proteomics 72, no. 1 (February 2009): 110–20. http://dx.doi.org/10.1016/j.jprot.2008.10.008.

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Mosley, Amber L., Mihaela E. Sardiu, Samantha G. Pattenden, Jerry L. Workman, Laurence Florens, and Michael P. Washburn. "Highly Reproducible Label Free Quantitative Proteomic Analysis of RNA Polymerase Complexes." Molecular & Cellular Proteomics 10, no. 2 (November 3, 2010): M110.000687. http://dx.doi.org/10.1074/mcp.m110.000687.

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Castillejo, María-Ángeles, Rebeca Iglesias-García, Stefanie Wienkoop, and Diego Rubiales. "Label-free quantitative proteomic analysis of tolerance to drought inPisum sativum." PROTEOMICS 16, no. 21 (September 16, 2016): 2776–87. http://dx.doi.org/10.1002/pmic.201600156.

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Wang, Xu, Marlène Davanture, Michel Zivy, Christophe Bailly, Eiji Nambara, and Françoise Corbineau. "Label-Free Quantitative Proteomics Reveal the Involvement of PRT6 in Arabidopsis thaliana Seed Responsiveness to Ethylene." International Journal of Molecular Sciences 23, no. 16 (August 19, 2022): 9352. http://dx.doi.org/10.3390/ijms23169352.

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In Arabidopsis thaliana, the breaking of seed dormancy in wild type (Col-0) by ethylene at 100 μL L−1 required at least 30 h application. A mutant of the proteolytic N-degron pathway, lacking the E3 ligase PROTEOLYSIS 6 (PRT6), was investigated for its role in ethylene-triggered changes in proteomes during seed germination. Label-free quantitative proteomics was carried out on dormant wild type Col-0 and prt6 seeds treated with (+) or without (−) ethylene. After 16 h, 1737 proteins were identified, but none was significantly different in protein levels in response to ethylene. After longer ethylene treatment (30 h), 2552 proteins were identified, and 619 Differentially Expressed Proteins (DEPs) had significant differences in protein abundances between ethylene treatments and genotypes. In Col, 587 DEPs were enriched for those involved in signal perception and transduction, reserve mobilization and new material generation, which potentially contributed to seed germination. DEPs up-regulated by ethylene in Col included S-adenosylmethionine synthase 1, methionine adenosyltransferase 3 and ACC oxidase involved in ethylene synthesis and of Pyrabactin Resistance1 acting as an ABA receptor, while DEPs down-regulated by ethylene in Col included aldehyde oxidase 4 involved in ABA synthesis. In contrast, in prt6 seeds, ethylene did not result in strong proteomic changes with only 30 DEPs. Taken together, the present work demonstrates that the proteolytic N-degron pathway is essential for ethylene-mediated reprogramming of seed proteomes during germination.

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Wasinger, Valerie C., Ming Zeng, and Yunki Yau. "Current Status and Advances in Quantitative Proteomic Mass Spectrometry." International Journal of Proteomics 2013 (March 6, 2013): 1–12. http://dx.doi.org/10.1155/2013/180605.

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The accurate quantitation of proteins and peptides in complex biological systems is one of the most challenging areas of proteomics. Mass spectrometry-based approaches have forged significant in-roads allowing accurate and sensitive quantitation and the ability to multiplex vastly complex samples through the application of robust bioinformatic tools. These relative and absolute quantitative measures using label-free, tags, or stable isotope labelling have their own strengths and limitations. The continuous development of these methods is vital for increasing reproducibility in the rapidly expanding application of quantitative proteomics in biomarker discovery and validation. This paper provides a critical overview of the primary mass spectrometry-based quantitative approaches and the current status of quantitative proteomics in biomedical research.

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Yu, Xiaolan, Yongsheng Wang, Markus V. Kohnen, Mingxin Piao, Min Tu, Yubang Gao, Chentao Lin, Zecheng Zuo, and Lianfeng Gu. "Large Scale Profiling of Protein Isoforms Using Label-Free Quantitative Proteomics Revealed the Regulation of Nonsense-Mediated Decay in Moso Bamboo (Phyllostachys edulis)." Cells 8, no. 7 (July 19, 2019): 744. http://dx.doi.org/10.3390/cells8070744.

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Moso bamboo is an important forest species with a variety of ecological, economic, and cultural values. However, the gene annotation information of moso bamboo is only based on the transcriptome sequencing, lacking the evidence of proteome. The lignification and fiber in moso bamboo leads to a difficulty in the extraction of protein using conventional methods, which seriously hinders research on the proteomics of moso bamboo. The purpose of this study is to establish efficient methods for extracting the total proteins from moso bamboo for following mass spectrometry-based quantitative proteome identification. Here, we have successfully established a set of efficient methods for extracting total proteins of moso bamboo followed by mass spectrometry-based label-free quantitative proteome identification, which further improved the protein annotation of moso bamboo genes. In this study, 10,376 predicted coding genes were confirmed by quantitative proteomics, accounting for 35.8% of all annotated protein-coding genes. Proteome analysis also revealed the protein-coding potential of 1015 predicted long noncoding RNA (lncRNA), accounting for 51.03% of annotated lncRNAs. Thus, mass spectrometry-based proteomics provides a reliable method for gene annotation. Especially, quantitative proteomics revealed the translation patterns of proteins in moso bamboo. In addition, the 3284 transcript isoforms from 2663 genes identified by Pacific BioSciences (PacBio) single-molecule real-time long-read isoform sequencing (Iso-Seq) was confirmed on the protein level by mass spectrometry. Furthermore, domain analysis of mass spectrometry-identified proteins encoded in the same genomic locus revealed variations in domain composition pointing towards a functional diversification of protein isoform. Finally, we found that part transcripts targeted by nonsense-mediated mRNA decay (NMD) could also be translated into proteins. In summary, proteomic analysis in this study improves the proteomics-assisted genome annotation of moso bamboo and is valuable to the large-scale research of functional genomics in moso bamboo. In summary, this study provided a theoretical basis and technical support for directional gene function analysis at the proteomics level in moso bamboo.

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Chen, Cunkun, Xiaojun Zhang, Huijie Zhang, Zhaojun Ban, Li Li, Chenghu Dong, Haipeng Ji, and Wentong Xue. "Label-free quantitative proteomics to investigate the response of strawberry fruit after controlled ozone treatment." RSC Advances 9, no. 2 (2019): 676–89. http://dx.doi.org/10.1039/c8ra08405j.

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Bakku, Ranjith Kumar, Ravi Gupta, Cheol-Woo Min, Sun-Tae Kim, Genboku Takahashi, Junko Shibato, Seiji Shioda, Fumiko Takenoya, Ganesh Kumar Agrawal, and Randeep Rakwal. "Unravelling the Helianthus tuberosus L. (Jerusalem Artichoke, Kiku-Imo) Tuber Proteome by Label-Free Quantitative Proteomics." Molecules 27, no. 3 (February 7, 2022): 1111. http://dx.doi.org/10.3390/molecules27031111.

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The present research investigates the tuber proteome of the ‘medicinal’ plant Jerusalem artichoke (abbreviated as JA) (Helianthus tuberosus L.) using a high-throughput proteomics technique. Although JA has been historically known to the Native Americans, it was introduced to Europe in the late 19th century and later spread to Japan (referred to as ‘kiku-imo’) as a folk remedy for diabetes. Genboku Takahashi research group has been working on the cultivation and utilization of kiku-imo tuber as a traditional/alternative medicine in daily life and researched on the lowering of blood sugar level, HbA1c, etc., in human subjects (unpublished data). Understanding the protein components of the tuber may shed light on its healing properties, especially related to diabetes. Using three commercially processed JA tuber products (dried powder and dried chips) we performed total protein extraction on the powdered samples using a label-free quantitate proteomic approach (mass spectrometry) and catalogued for the first time a comprehensive protein list for the JA tuber. A total of 2967 protein groups were identified, statistically analyzed, and further categorized into different protein classes using bioinformatics techniques. We discussed the association of these proteins to health and disease regulatory metabolism. Data are available via ProteomeXchange with identifier PXD030744.

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Piragasam, Ramanaguru S., S. Faraz Hussain, Steven G. Chaulk, Zaeem A. Siddiqi, and Richard P. Fahlman. "Label-free proteomic analysis reveals large dynamic changes to the cellular proteome upon expression of the miRNA-23a-27a-24-2 microRNA cluster." Biochemistry and Cell Biology 98, no. 1 (February 2020): 61–69. http://dx.doi.org/10.1139/bcb-2019-0014.

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In deciphering the regulatory networks of gene expression controlled by the small non-coding RNAs known as microRNAs (miRNAs), a major challenge has been with the identification of the true mRNA targets by these RNAs within the context of the enormous numbers of predicted targets for each of these small RNAs. To facilitate the system-wide identification of miRNA targets, a variety of system wide methods, such as proteomics, have been implemented. Here we describe the utilization of quantitative label-free proteomics and bioinformatics to identify the most significant changes to the proteome upon expression of the miR-23a-27a-24-2 miRNA cluster. In light of recent work leading to the hypothesis that only the most pronounced regulatory events by miRNAs may be physiologically relevant, our data reveal that label-free analysis circumvents the limitations of proteomic labeling techniques that limit the maximum differences that can be quantified. The result of our analysis identifies a series of novel candidate targets that are reduced in abundance by more than an order of magnitude upon the expression of the miR-23a-27a-24-2 cluster.

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Ryu, Soyoung, Byron Gallis, Young Ah Goo, Scott A. Shaffer, Dragan Radulovic, and David R. Goodlett. "Comparison of a Label-Free Quantitative Proteomic Method Based on Peptide Ion Current Area to the Isotope Coded Affinity Tag Method." Cancer Informatics 6 (January 2008): CIN.S385. http://dx.doi.org/10.4137/cin.s385.

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Recently, several research groups have published methods for the determination of proteomic expression profiling by mass spectrometry without the use of exogenously added stable isotopes or stable isotope dilution theory. These so-called label-free, methods have the advantage of allowing data on each sample to be acquired independently from all other samples to which they can later be compared in silico for the purpose of measuring changes in protein expression between various biological states. We developed label free software based on direct measurement of peptide ion current area (PICA) and compared it to two other methods, a simpler label free method known as spectral counting and the isotope coded affinity tag (ICAT) method. Data analysis by these methods of a standard mixture containing proteins of known, but varying, concentrations showed that they performed similarly with a mean squared error of 0.09. Additionally, complex bacterial protein mixtures spiked with known concentrations of standard proteins were analyzed using the PICA label-free method. These results indicated that the PICA method detected all levels of standard spiked proteins at the 90% confidence level in this complex biological sample. This finding confirms that label-free methods, based on direct measurement of the area under a single ion current trace, performed as well as the standard ICAT method. Given the fact that the label-free methods provide ease in experimental design well beyond pair-wise comparison, label-free methods such as our PICA method are well suited for proteomic expression profiling of large numbers of samples as is needed in clinical analysis.

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Van Nguyen, Truong, So-Wun Kim, Cheol-Woo Min, Ravi Gupta, Gi-Hyun Lee, Jeong-Woo Jang, Divya Rathi, et al. "Optimization of Protein Isolation and Label-Free Quantitative Proteomic Analysis in Four Different Tissues of Korean Ginseng." Plants 10, no. 7 (July 9, 2021): 1409. http://dx.doi.org/10.3390/plants10071409.

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Korean ginseng is one of the most valuable medicinal plants worldwide. However, our understanding of ginseng proteomics is largely limited due to difficulties in the extraction and resolution of ginseng proteins because of the presence of natural contaminants such as polysaccharides, phenols, and glycosides. Here, we compared four different protein extraction methods, namely, TCA/acetone, TCA/acetone–MeOH/chloroform, phenol–TCA/acetone, and phenol–MeOH/chloroform methods. The TCA/acetone–MeOH/chloroform method displayed the highest extraction efficiency, and thus it was used for the comparative proteome profiling of leaf, root, shoot, and fruit by a label-free quantitative proteomics approach. This approach led to the identification of 2604 significantly modulated proteins among four tissues. We could pinpoint differential pathways and proteins associated with ginsenoside biosynthesis, including the methylerythritol 4–phosphate (MEP) pathway, the mevalonate (MVA) pathway, UDP-glycosyltransferases (UGTs), and oxidoreductases (CYP450s). The current study reports an efficient and reproducible method for the isolation of proteins from a wide range of ginseng tissues and provides a detailed organ-based proteome map and a more comprehensive view of enzymatic alterations in ginsenoside biosynthesis.

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Clermont, Kristen, Charles J. Graham, Steven W. Lloyd, Casey C. Grimm, Jennifer J. Randall, and Christopher P. Mattison. "Proteomic Analysis of Pecan (Carya illinoinensis) Nut Development." Foods 12, no. 4 (February 17, 2023): 866. http://dx.doi.org/10.3390/foods12040866.

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Pecan (Carya illinoinensis) nuts are an economically valuable crop native to the United States and Mexico. A proteomic summary from two pecan cultivars at multiple time points was used to compare protein accumulation during pecan kernel development. Patterns of soluble protein accumulation were elucidated using qualitative gel-free and label-free mass-spectrometric proteomic analyses and quantitative (label-free) 2-D gel electrophoresis. Two-dimensional (2-D) gel electrophoresis distinguished a total of 1267 protein spots and shotgun proteomics identified 556 proteins. Rapid overall protein accumulation occurred in mid-September during the transition to the dough stage as the cotyledons enlarge within the kernel. Pecan allergens Car i 1 and Car i 2 were first observed to accumulate during the dough stage in late September. While overall protein accumulation increased, the presence of histones diminished during development. Twelve protein spots accumulated differentially based on 2-D gel analysis in the weeklong interval between the dough stage and the transition into a mature kernel, while eleven protein spots were differentially accumulated between the two cultivars. These results provide a foundation for more focused proteomic analyses of pecans that may be used in the future to identify proteins that are important for desirable traits, such as reduced allergen content, improved polyphenol or lipid content, increased tolerance to salinity, biotic stress, seed hardiness, and seed viability.

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Foratori-Junior, Gerson Aparecido, Talita Mendes Oliveira Ventura, Larissa Tercilia Grizzo, Guy Howard Carpenter, Marília Afonso Rabelo Buzalaf, and Silvia Helena de Carvalho Sales-Peres. "Label-Free Quantitative Proteomic Analysis Reveals Inflammatory Pattern Associated with Obesity and Periodontitis in Pregnant Women." Metabolites 12, no. 11 (November 10, 2022): 1091. http://dx.doi.org/10.3390/metabo12111091.

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Obesity and pregnancy may have synergistic effects on periodontal condition, and proteomics could be an ideal approach to highlight the pathophysiological mechanisms associated with these outcomes. This study analyzed the salivary proteomics related to obesity and periodontitis in women during pregnancy (T1) and after delivery (T2). Initially, 126 women were recruited and forty were allocated into groups: with obesity and periodontitis (OP); with obesity, but without periodontitis (OWP); with normal BMI, but with periodontitis (NP); with normal BMI and without periodontitis (NWP). Whole-mouth saliva was collected in T1 and T2, and proteins were extracted and individually processed by label-free proteomics (nLC-ESI-MS/MS). The up-regulations of Heat shock 70 kDa protein 1A, 1B, and 1-like were related to both obesity and periodontitis, separately. Albumin and Thioredoxin were up-regulated in periodontitis cases, while Cystatins (mainly S, SA, SN) and Lactotransferrin were down-regulated. The high abundances of Submaxillary gland androgen-regulated protein 3B, Protein S100-A8, Matrix metalloproteinase-9, Heat shock 70 kDa protein 2 and 6, Putative Heat shock 70 kDa protein 7, Heat shock 71 kDa protein, Haptoglobin and Plastin-1 were significant in the combination of obesity and periodontitis. Obesity and periodontitis remarkably altered the proteome of the saliva during pregnancy with substantial alterations after delivery.

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Mitsa, Georgia, Qianyu Guo, Christophe Goncalves, Samuel E. J. Preston, Vincent Lacasse, Adriana Aguilar-Mahecha, Naciba Benlimame, et al. "A Non-Hazardous Deparaffinization Protocol Enables Quantitative Proteomics of Core Needle Biopsy-Sized Formalin-Fixed and Paraffin-Embedded (FFPE) Tissue Specimens." International Journal of Molecular Sciences 23, no. 8 (April 18, 2022): 4443. http://dx.doi.org/10.3390/ijms23084443.

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Most human tumor tissues that are obtained for pathology and diagnostic purposes are formalin-fixed and paraffin-embedded (FFPE). To perform quantitative proteomics of FFPE samples, paraffin has to be removed and formalin-induced crosslinks have to be reversed prior to proteolytic digestion. A central component of almost all deparaffinization protocols is xylene, a toxic and highly flammable solvent that has been reported to negatively affect protein extraction and quantitative proteome analysis. Here, we present a ‘green’ xylene-free protocol for accelerated sample preparation of FFPE tissues based on paraffin-removal with hot water. Combined with tissue homogenization using disposable micropestles and a modified protein aggregation capture (PAC) digestion protocol, our workflow enables streamlined and reproducible quantitative proteomic profiling of FFPE tissue. Label-free quantitation of FFPE cores from human ductal breast carcinoma in situ (DCIS) xenografts with a volume of only 0.79 mm3 showed a high correlation between replicates (r2 = 0.992) with a median %CV of 16.9%. Importantly, this small volume is already compatible with tissue micro array (TMA) cores and core needle biopsies, while our results and its ease-of-use indicate that further downsizing is feasible. Finally, our FFPE workflow does not require costly equipment and can be established in every standard clinical laboratory.

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Held, Jason M., Birgit Schilling, Alexandria K. D'Souza, Tara Srinivasan, Jessica B. Behring, Dylan J. Sorensen, Christopher C. Benz, and Bradford W. Gibson. "Label-Free Quantitation and Mapping of the ErbB2 Tumor Receptor by Multiple Protease Digestion with Data-Dependent (MS1) and Data-Independent (MS2) Acquisitions." International Journal of Proteomics 2013 (April 4, 2013): 1–11. http://dx.doi.org/10.1155/2013/791985.

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The receptor tyrosine kinase ErbB2 is a breast cancer biomarker whose posttranslational modifications (PTMs) are a key indicator of its activation. Quantifying the expression and PTMs of biomarkers such as ErbB2 by selected reaction monitoring (SRM) mass spectrometry has several limitations, including minimal coverage and extensive assay development time. Therefore, we assessed the utility of two high resolution, full scan mass spectrometry approaches, MS1 Filtering and SWATH MS2, for targeted ErbB2 proteomics. Endogenous ErbB2 immunoprecipitated from SK-BR-3 cells was in-gel digested with trypsin, chymotrypsin, Asp-N, or trypsin plus Asp-N in triplicate. Data-dependent acquisition with an AB SCIEX TripleTOF 5600 and MS1 Filtering data processing was used to assess peptide and PTM coverage as well as the reproducibility of enzyme digestion. Data-independent acquisition (SWATH) was also performed for MS2 quantitation. MS1 Filtering and SWATH MS2 allow quantitation of all detected analytes after acquisition, enabling the use of multiple proteases for quantitative assessment of target proteins. Combining high resolution proteomics with multiprotease digestion enabled quantitative mapping of ErbB2 with excellent reproducibility, improved amino acid sequence and PTM coverage, and decreased assay development time compared to typical SRM assays. These results demonstrate that high resolution quantitative proteomic approaches are an effective tool for targeted biomarker quantitation.

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Dytfeld, Dominik, Malathi Kandarpa, John R. Strahler, Dattatreya Mellacheruvu, Suchitra Subramani, Stephanie J. Kraftson, Lambert Ngoka, Alexey Nesvizhskii, Arun Sreekumar, and Andrzej J. Jakubowiak. "Proteomic Signature Predicting Achievement of Very Good Partial Response In Patients with Multiple Myeloma Based On Complementary Label-Free and iTRAQ Quantitative Proteome Analysis." Blood 116, no. 21 (November 19, 2010): 1902. http://dx.doi.org/10.1182/blood.v116.21.1902.1902.

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Abstract Abstract 1902 Introduction: Multiple myeloma (MM) remains mostly incurable. Novel therapies have improved response rates, which are now reaching 100%. More importantly, number of recent studies showed that the depth of response, e.g. achievement of at least 90% reduction of the disease (≥VGPR) is associated with longer disease control. Therefore, improving VGPR rates and establishing predictors of VGPR to a given regimen may be an important clinical goal. High throughput quantitative proteomics may offer greater insight into the actual biology of the malignant cell than genome analysis and therefore, may be more useful in the development of personalized therapy. The objective of this study is to establish a proteomic signature predicting achievement of at least VGPR to initial treatment with bortezomib (Velcade®), pegylated liposomal doxorubicin, and dexamethasone (VDD). We previously reported preliminary proteomic profile of malignant plasma cells (PCs) obtained from a set of naïve MM pts enrolled in the VDD trial (Dytfeld et al., ASH 2009). Here we present the results of differential proteomic analysis of MM PCs of all available samples from the frontline VDD study (≥VGPR vs. <VGPR) using two independent and complementary quantitative proteomic platforms. We also compared the proteomic profile with gene expression data. Preliminary validation of the biomarkers of response prediction is presented. Methods: PCs were acquired from pre-treatment bone marrow specimens after obtaining informed consent from patients (pts), and were thereafter enriched with a RosetteSep® negative selection kit. Quantitative proteomic analysis of PCs from 17 naïve pts with MM from the VDD study was performed using iTRAQ approach in 8-plex variant. To increase confidence of analysis, label-free quantitative proteomics (LF) based on spectra counting was conducted on PCs from 12 pts. In iTRAQ experiments, proteins were processed with reagents according to the manufacturer's protocol followed by SCX fractionation and LC-MS/MS analysis (4800 Plus MALDI TOF/TOF). Peptides from the MM1S cell line were used as a reference. The data were analyzed using ProteinPilot™. For LF analysis, proteins were fractionated before trypsin digestion on Bis-Tris-Gel and subsequently run on LC-ESI-MS/MS on a linear trap mass spectrometer (LTQ Orbitrap). A database search was carried out using X!Tandem followed by Trans-proteomic Pipeline. At least 1.5-fold difference in expression in both platforms was used as a cut-off value. To correlate proteomics with gene expression of dysregulated proteins of interest, mRNA levels were analyzed by quantitative real time PCR (RT-PCR). Validation of proteomic findings on proteins of interest was performed using Western Blot. Results: We identified a total of 894 proteins in 3 iTRAQ experiments with high confidence (FDR<1%) and 1058 proteins by LF approach. Based on iTRAQ analysis, 20 proteins were found up-regulated in samples from pts with ≥VGPR (8 out of 17 pts) while 14 were down- regulated. Using LF approach, 284 proteins were elevated in the ≥VGPR group (6 out of 12 pts) while 315 proteins were down-regulated. Both iTRAQ and LF methods showed 15 differentially expressed proteins in common and 14 of them showed identical up or down trends. Interestingly, among differentially expressed proteins, there were proteins involved in proteasome activation (PSME1 and TXNL1), protection against oxidative stress (TXN and TXNDC5), glucose and cholesterol metabolism (TP1, APOA1 and ACAT1) and apoptosis (MX1). RT-PCR performed on a subset of genes confirmed the trend in differential expression between pts with ≥VGPR and <VGPR for TXNDC5 and PSME1. No change in mRNA expression levels was observed in TXN, APOA1, TPI1 and MX1while the trend in expression was reversed for ACAT1. Western blot analysis performed to date validated differential expression of PSME1. Conclusions: We present patient-derived proteomic characteristics of MM cells using two independent proteomic platforms. As a proof of concept, analysis of PCs obtained from pts enrolled in the frontline VDD study shows differential expression of 34 proteins in pts who achieved ≥VGPR vs. pts with <VGPR. Correlation with gene expression and further validation and functional analysis are in progress. This study was supported by a grant from the Multiple Myeloma Research Foundation. Disclosures: Jakubowiak: Millennium, Celgene, Bristol-Myers Squibb, Johnson & Johnson Ortho-Centocor: Honoraria; Millennium, Bristol-Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Millennium, Celgene, Centocor-Ortho Biotech: Speakers Bureau.

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Marques, Isabel, Duarte Gouveia, Jean-Charles Gaillard, Sónia Martins, Magda C. Semedo, Fernando C. Lidon, Fábio M. DaMatta, Ana I. Ribeiro-Barros, Jean Armengaud, and José C. Ramalho. "Next-Generation Proteomics Reveals a Greater Antioxidative Response to Drought in Coffea arabica Than in Coffea canephora." Agronomy 12, no. 1 (January 8, 2022): 148. http://dx.doi.org/10.3390/agronomy12010148.

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Drought is a major threat to coffee, compromising the quality and quantity of its production. We have analyzed the core proteome of 18 Coffea canephora cv. Conilon Clone 153 and C. arabica cv. Icatu plants and assessed their responses to moderate (MWD) and severe (SWD) water deficits. Label-free quantitative shotgun proteomics identified 3000 proteins in both genotypes, but less than 0.8% contributed to ca. 20% of proteome biomass. Proteomic changes were dependent on the severity of drought, being stronger under SWD and with an enrolment of different proteins, functions, and pathways than under MWD. The two genotypes displayed stress-responsive proteins under SWD, but only C. arabica showed a higher abundance of proteins involved in antioxidant detoxification activities. Overall, the impact of MWD was minor in the two genotypes, contrary to previous studies. In contrast, an extensive proteomic response was found under SWD, with C. arabica having a greater potential for acclimation/resilience than C. canephora. This is likely supported by a wider antioxidative response and an ability to repair photosynthetic structures, being crucial to develop new elite genotypes that assure coffee supply under water scarcity levels.

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Moura, Hercules, Rebecca R. Terilli, Adrian R. Woolfitt, Yulanda M. Williamson, Glauber Wagner, Thomas A. Blake, Maria I. Solano, and John R. Barr. "Proteomic Analysis and Label-Free Quantification of the Large Clostridium difficile Toxins." International Journal of Proteomics 2013 (August 27, 2013): 1–10. http://dx.doi.org/10.1155/2013/293782.

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Clostridium difficile is the leading cause of antibiotic-associated diarrhea in hospitals worldwide, due to hypervirulent epidemic strains with the ability to produce increased quantities of the large toxins TcdA and TcdB. Unfortunately, accurate quantification of TcdA and TcdB from different toxinotypes using small samples has not yet been reported. In the present study, we quantify C. difficile toxins in <0.1 mL of culture filtrate by quantitative label-free mass spectrometry (MS) using data-independent analysis (MSE). In addition, analyses of both purified TcdA and TcdB as well as a standard culture filtrate were performed using gel-based and gel-independent proteomic platforms. Gel-based proteomic analysis was then used to generate basic information on toxin integrity and provided sequence confirmation. Gel-independent in-solution digestion of both toxins using five different proteolytic enzymes with MS analysis generated broad amino acid sequence coverage (91% for TcdA and 95% for TcdB). Proteomic analysis of a culture filtrate identified a total of 101 proteins, among them TcdA, TcdB, and S-layer proteins.

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Jung, Ju Young, Cheol Woo Min, Hye Won Shin, Truong Van Nguyen, Ji hyun Kim, Eui Jung Kim, Ick Hyun Jo, Yu Jin Kim, and Sun Tae Kim. "Label-free Quantitative Proteomic Analysis of Drought-Responsive Proteins in Panax ginseng Meyer." Korean Journal of Medicinal Crop Science 29, no. 6 (December 31, 2021): 369–79. http://dx.doi.org/10.7783/kjmcs.2021.29.6.369.

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Soares, Eduardo de A., Emily G. Werth, Leidy J. Madroñero, José A. Ventura, Silas P. Rodrigues, Leslie M. Hicks, and Patricia M. B. Fernandes. "Label-free quantitative proteomic analysis of pre-flowering PMeV-infected Carica papaya L." Journal of Proteomics 151 (January 2017): 275–83. http://dx.doi.org/10.1016/j.jprot.2016.06.025.

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Zhang, Ying, Bo Xu, Naohiko Kinoshita, Yutaka Yoshida, Masayuki Tasaki, Hidehiko Fujinaka, Sameh Magdeldin, Eishin Yaoita, and Tadashi Yamamoto. "Datasets from label-free quantitative proteomic analysis of human glomeruli with sclerotic lesions." Data in Brief 4 (September 2015): 180–85. http://dx.doi.org/10.1016/j.dib.2015.05.013.

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Ramus, Claire, Agnès Hovasse, Marlène Marcellin, Anne-Marie Hesse, Emmanuelle Mouton-Barbosa, David Bouyssié, Sebastian Vaca, et al. "Spiked proteomic standard dataset for testing label-free quantitative software and statistical methods." Data in Brief 6 (March 2016): 286–94. http://dx.doi.org/10.1016/j.dib.2015.11.063.

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Tang, Jing, Yunxia Wang, Yi Li, Yang Zhang, Runyuan Zhang, Ziyu Xiao, Yongchao Luo, et al. "Recent Technological Advances in the Mass Spectrometry-based Nanomedicine Studies: An Insight from Nanoproteomics." Current Pharmaceutical Design 25, no. 13 (August 16, 2019): 1536–53. http://dx.doi.org/10.2174/1381612825666190618123306.

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Nanoscience becomes one of the most cutting-edge research directions in recent years since it is gradually matured from basic to applied science. Nanoparticles (NPs) and nanomaterials (NMs) play important roles in various aspects of biomedicine science, and their influences on the environment have caused a whole range of uncertainties which require extensive attention. Due to the quantitative and dynamic information provided for human proteome, mass spectrometry (MS)-based quantitative proteomic technique has been a powerful tool for nanomedicine study. In this article, recent trends of progress and development in the nanomedicine of proteomics were discussed from quantification techniques and publicly available resources or tools. First, a variety of popular protein quantification techniques including labeling and label-free strategies applied to nanomedicine studies are overviewed and systematically discussed. Then, numerous protein profiling tools for data processing and postbiological statistical analysis and publicly available data repositories for providing enrichment MS raw data information sources are also discussed.

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Xie, Yazhen, and Qibin Lu. "Proteomic Analysis of Differentially Expressed Proteins in the Placenta of Anticardiolipin Antibody- (ACA-) Positive Pregnant Mice after Anzi Heji Treatment." Evidence-Based Complementary and Alternative Medicine 2020 (December 14, 2020): 1–11. http://dx.doi.org/10.1155/2020/1967698.

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Anzi Heji (AZHJ) has been used to treat anticardiolipin antibody- (ACA-) positive pregnant women at risk of spontaneous abortion for many years. The aim of this study was to investigate the protective mechanism of AZHJ in a mouse model of ACA-positive pregnancy at risk of spontaneous abortion using label-free quantitative proteomics. Mice were divided into three groups: normal pregnant mice (control group), ACA-positive pregnant mice administered normal saline (model group), and ACA-positive pregnant mice administered AZHJ (AZHJ group). The model was established by injecting β 2 -glycoprotein I (GPI) into mice for 18 days. The DEPs and their functions were analyzed by label-free quantitative proteomic and bioinformatic analyses. The levels of IL-6, IL-10, ACA, and TNF- α in the serum and placentas of the mice were measured by enzyme-linked immunosorbent assays (ELISAs). Proteomic data were validated by western blot analysis. The abnormal serum and placental levels of IL-6, ACA, and TNF- α in the model group were reversed by AZHJ. There were 39 upregulated and 10 downregulated DEPs in the AZHJ group relative to the model group. Bioinformatic analysis revealed that the DEPs were mainly involved in nucleic acid binding, signal conduction, and posttranslational modification. The placental levels of T-cell immunoglobulin mucin 3 (Tim-3) and Toll-like receptor 4 (TLR4) expression and AKT phosphorylation in the three groups were consistent with the proteomic findings. Tim-3/AKT signaling is involved in maternal-fetal immune tolerance, while TLR4 is associated with inflammatory responses. Collectively, these results indicate that AZHJ may exert its protective effect in ACA-positive pregnant mice by regulating the maternal-fetal immune tolerance and inflammatory response.

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Jurado-Flores, Ana, Luis C. Romero, and Cecilia Gotor. "Label-Free Quantitative Proteomic Analysis of Nitrogen Starvation in Arabidopsis Root Reveals New Aspects of H2S Signaling by Protein Persulfidation." Antioxidants 10, no. 4 (March 24, 2021): 508. http://dx.doi.org/10.3390/antiox10040508.

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Hydrogen sulfide (H2S)-mediated signaling pathways regulate many physiological and pathophysiological processes in mammalian and plant systems. The molecular mechanism by which hydrogen sulfide exerts its action involves the posttranslational modification of cysteine residues to form a persulfidated thiol motif. We developed a comparative and label-free quantitative proteomic analysis approach for the detection of endogenous persulfidated proteins in N-starved Arabidopsis thaliana roots by using the tag-switch method. In this work, we identified 5214 unique proteins from root tissue that were persulfidated, 1674 of which were quantitatively analyzed and found to show altered persulfidation levels in vivo under N deprivation. These proteins represented almost 13% of the entire annotated proteome in Arabidopsis. Bioinformatic analysis revealed that persulfidated proteins were involved in a wide range of biological functions, regulating important processes such as primary metabolism, plant responses to stresses, growth and development, RNA translation and protein degradation. Quantitative mass spectrometry analysis allowed us to obtain a comprehensive view of hydrogen sulfide signaling via changes in the persulfidation levels of key protein targets involved in ubiquitin-dependent protein degradation and autophagy, among others.

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Montoya, Andrés, Manuel Carlos López, Ivan D. Vélez, and Sara M. Robledo. "Label-free quantitative proteomic analysis reveals potential biomarkers for early healing in cutaneous leishmaniasis." PeerJ 6 (January 11, 2019): e6228. http://dx.doi.org/10.7717/peerj.6228.

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Background Leishmaniasis is a parasitic disease caused by more than 20 species of the Leishmania genus. The disease is globally distributed and is endemic in 97 countries and three territories in the tropical and subtropical regions. The efficacy of the current treatments is becoming increasingly low either due to incomplete treatment or resistant parasites. Failure of treatment is frequent, and therefore, the search for early biomarkers of therapeutic response in cutaneous leishmaniasis (CL) is urgently needed. Objective The aim of this study was to compare the proteomic profiles in patients with CL before and after 7 days of treatment and identify early biomarkers of curative response. Methods Four patients with a parasitological diagnosis of leishmaniasis with confirmation of species by PCR-RFLP were recruited. All patients had a single lesion, and a protein from the middle of the ulcer was quantified by liquid chromatography and mass spectrometry. Results A total of 12 proteins showed differential expression in the comparative LC-electrospray ionization MS/MS (LC-ESI-MS/MS) triplicate analysis. Seven of them were up-regulated and five of them were down-regulated. Calcium binding proteins A2, A8, and A9 and hemoglobin subunits alpha-2 and delta showed high correlation with epidermis development and immune response. Conclusion We identified changes in the profiles of proteins that had a positive therapeutic response to the treatment. The proteins identified with differential expression are related to the reduction of inflammation and increased tissue repair. These proteins can be useful as biomarkers for early monitoring of therapeutic response in CL.

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Kaur, Gurjeet, Syed Azmal Ali, Sudarshan Kumar, Ashok Kumar Mohanty, and Pradip Behare. "Label-free quantitative proteomic analysis of Lactobacillus fermentum NCDC 400 during bile salt exposure." Journal of Proteomics 167 (September 2017): 36–45. http://dx.doi.org/10.1016/j.jprot.2017.08.008.

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Adav, Sunil S., Esther Sok Hwee Cheow, Anita Ravindran, Bamaprasad Dutta, and Siu Kwan Sze. "Label free quantitative proteomic analysis of secretome by Thermobifida fusca on different lignocellulosic biomass." Journal of Proteomics 75, no. 12 (June 2012): 3694–706. http://dx.doi.org/10.1016/j.jprot.2012.04.031.

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Zhao, Zuohui, Fei Wu, Sentai Ding, Liang Sun, Zhao Liu, Kejia Ding, and Jiaju Lu. "Label-free quantitative proteomic analysis reveals potential biomarkers and pathways in renal cell carcinoma." Tumor Biology 36, no. 2 (October 15, 2014): 939–51. http://dx.doi.org/10.1007/s13277-014-2694-2.

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Zhang, Wentao, Xihong Li, Li Li, Yao Tang, Wei Qi, Xia Liu, Liping Qiao, Wei Wang, and Xiaoyu Jia. "A label-free quantitative proteomic investigation reveals stage-responsive ripening genes in apricot fruits." Journal of Horticultural Science and Biotechnology 92, no. 3 (January 9, 2017): 261–69. http://dx.doi.org/10.1080/14620316.2016.1265469.

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Kim, So Wun, Ravi Gupta, Cheol Woo Min, Seo Hyun Lee, Ye Eun Cheon, Qing Feng Meng, Jeong Woo Jang, et al. "Label-free quantitative proteomic analysis of Panax ginseng leaves upon exposure to heat stress." Journal of Ginseng Research 43, no. 1 (January 2019): 143–53. http://dx.doi.org/10.1016/j.jgr.2018.09.005.

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Hofsteen, Peter, Aaron M. Robitaille, Daniel Patrick Chapman, Randall T. Moon, and Charles E. Murry. "Quantitative proteomics identify DAB2 as a cardiac developmental regulator that inhibits WNT/β-catenin signaling." Proceedings of the National Academy of Sciences 113, no. 4 (January 11, 2016): 1002–7. http://dx.doi.org/10.1073/pnas.1523930113.

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To reveal the molecular mechanisms involved in cardiac lineage determination and differentiation, we quantified the proteome of human embryonic stem cells (hESCs), cardiac progenitor cells (CPCs), and cardiomyocytes during a time course of directed differentiation by label-free quantitative proteomics. This approach correctly identified known stage-specific markers of cardiomyocyte differentiation, including SRY-box2 (SOX2), GATA binding protein 4 (GATA4), and myosin heavy chain 6 (MYH6). This led us to determine whether our proteomic screen could reveal previously unidentified mediators of heart development. We identified Disabled 2 (DAB2) as one of the most dynamically expressed proteins in hESCs, CPCs, and cardiomyocytes. We used clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) mutagenesis in zebrafish to assess whether DAB2 plays a functional role during cardiomyocyte differentiation. We found that deletion of Dab2 in zebrafish embryos led to a significant reduction in cardiomyocyte number and increased endogenous WNT/β-catenin signaling. Furthermore, the Dab2-deficient defects in cardiomyocyte number could be suppressed by overexpression of dickkopf 1 (DKK1), an inhibitor of WNT/β-catenin signaling. Thus, inhibition of WNT/β-catenin signaling by DAB2 is essential for establishing the correct number of cardiomyocytes in the developing heart. Our work demonstrates that quantifying the proteome of human stem cells can identify previously unknown developmental regulators.

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Murugaiyan, Jayaseelan, Murat Eravci, Christoph Weise, and Uwe Roesler. "Label-Free Quantitative Proteomic Analysis of Harmless and Pathogenic Strains of Infectious Microalgae, Prototheca spp." International Journal of Molecular Sciences 18, no. 1 (December 29, 2016): 59. http://dx.doi.org/10.3390/ijms18010059.

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Latosinska, Agnieszka, Konstantinos Vougas, Manousos Makridakis, Julie Klein, William Mullen, Mahmoud Abbas, Konstantinos Stravodimos, et al. "Comparative Analysis of Label-Free and 8-Plex iTRAQ Approach for Quantitative Tissue Proteomic Analysis." PLOS ONE 10, no. 9 (September 2, 2015): e0137048. http://dx.doi.org/10.1371/journal.pone.0137048.

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Komatsu, Setsuko, Chao Han, Yohei Nanjo, Most Altaf-Un-Nahar, Kun Wang, Dongli He, and Pingfang Yang. "Label-Free Quantitative Proteomic Analysis of Abscisic Acid Effect in Early-Stage Soybean under Flooding." Journal of Proteome Research 12, no. 11 (July 23, 2013): 4769–84. http://dx.doi.org/10.1021/pr4001898.

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Poleti, Mirele D., Luciana C. A. Regitano, Gustavo H. M. F. Souza, Aline S. M. Cesar, Rosineide C. Simas, Bárbara Silva-Vignato, Gabriella B. Oliveira, Sónia C. S. Andrade, Luiz C. Cameron, and Luiz L. Coutinho. "Longissimus dorsi muscle label-free quantitative proteomic reveals biological mechanisms associated with intramuscular fat deposition." Journal of Proteomics 179 (May 2018): 30–41. http://dx.doi.org/10.1016/j.jprot.2018.02.028.

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Xia, Yu, Haifa Hong, Lincai Ye, Yanlin Wang, Huiwen Chen, and Jinfen Liu. "Label-free quantitative proteomic analysis of right ventricular remodeling in infant Tetralogy of Fallot patients." Journal of Proteomics 84 (June 2013): 78–91. http://dx.doi.org/10.1016/j.jprot.2013.03.032.

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Li, Yingying, Wenying Zhang, Yu Zuo, Ting Zhu, Yue Pang, Tiesong Li, and Qingwei Li. "Label-Free Quantitative Proteomic Reveals Differentially Expressed Proteins in Aeromonas-Immunostimulated Leukocytes of Lampetra japonica." Current Microbiology 75, no. 7 (March 14, 2018): 934–41. http://dx.doi.org/10.1007/s00284-018-1468-2.

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Deng, Qianwen, Liangfang Dai, Yaling Chen, Decai Wu, Yu Shen, Jiankun Xie, and Xiangdong Luo. "Identification of Phosphorus Stress Related Proteins in the Seedlings of Dongxiang Wild Rice (Oryza Rufipogon Griff.) Using Label-Free Quantitative Proteomic Analysis." Genes 13, no. 1 (January 4, 2022): 108. http://dx.doi.org/10.3390/genes13010108.

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Phosphorus (P) deficiency tolerance in rice is a complex character controlled by polygenes. Through proteomics analysis, we could find more low P tolerance related proteins in unique P-deficiency tolerance germplasm Dongxiang wild rice (Oryza Rufipogon, DXWR), which will provide the basis for the research of its regulation mechanism. In this study, a proteomic approach as well as joint analysis with transcriptome data were conducted to identify potential unique low P response genes in DXWR during seedlings. The results showed that 3589 significant differential accumulation proteins were identified between the low P and the normal P treated root samples of DXWR. The degree of change was more than 1.5 times, including 60 up-regulated and 15 downregulated proteins, 24 of which also detected expression changes of more than 1.5-fold in the transcriptome data. Through quantitative trait locus (QTLs) matching analysis, seven genes corresponding to the significantly different expression proteins identified in this study were found to be uncharacterized and distributed in the QTLs interval related to low P tolerance, two of which (LOC_Os12g09620 and LOC_Os03g40670) were detected at both transcriptome and proteome levels. Based on the comprehensive analysis, it was found that DXWR could increase the expression of purple acid phosphatases (PAPs), membrane location of P transporters (PTs), rhizosphere area, and alternative splicing, and it could decrease reactive oxygen species (ROS) activity to deal with low P stress. This study would provide some useful insights in cloning the P-deficiency tolerance genes from wild rice, as well as elucidating the molecular mechanism of low P resistance in DXWR.

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De Pasquale, Valeria, Michele Costanzo, Rosa Siciliano, Maria Mazzeo, Valeria Pistorio, Laura Bianchi, Emanuela Marchese, Margherita Ruoppolo, Luigi Pavone, and Marianna Caterino. "Proteomic Analysis of Mucopolysaccharidosis IIIB Mouse Brain." Biomolecules 10, no. 3 (February 26, 2020): 355. http://dx.doi.org/10.3390/biom10030355.

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Mucopolysaccharidosis IIIB (MPS IIIB) is an inherited metabolic disease due to deficiency of α-N-Acetylglucosaminidase (NAGLU) enzyme with subsequent storage of undegraded heparan sulfate (HS). The main clinical manifestations of the disease are profound intellectual disability and neurodegeneration. A label-free quantitative proteomic approach was applied to compare the proteome profile of brains from MPS IIIB and control mice to identify altered neuropathological pathways of MPS IIIB. Proteins were identified through a bottom up analysis and 130 were significantly under-represented and 74 over-represented in MPS IIIB mouse brains compared to wild type (WT). Multiple bioinformatic analyses allowed to identify three major clusters of the differentially abundant proteins: proteins involved in cytoskeletal regulation, synaptic vesicle trafficking, and energy metabolism. The proteome profile of NAGLU−/− mouse brain could pave the way for further studies aimed at identifying novel therapeutic targets for the MPS IIIB. Data are available via ProteomeXchange with the identifier PXD017363.

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Costanzo, Michele, Marco Fiocchetti, Paolo Ascenzi, Maria Marino, Marianna Caterino, and Margherita Ruoppolo. "Proteomic and Bioinformatic Investigation of Altered Pathways in Neuroglobin-Deficient Breast Cancer Cells." Molecules 26, no. 8 (April 20, 2021): 2397. http://dx.doi.org/10.3390/molecules26082397.

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Neuroglobin (NGB) is a myoglobin-like monomeric globin that is involved in several processes, displaying a pivotal redox-dependent protective role in neuronal and extra-neuronal cells. NGB remarkably exerts its function upon upregulation by NGB inducers, such as 17β-estradiol (E2) and H2O2. However, the molecular bases of NGB’s functions remain undefined, mainly in non-neuronal cancer cells. Human MCF-7 breast cancer cells with a knocked-out (KO) NGB gene obtained using CRISPR/Cas9 technology were analyzed using shotgun label-free quantitative proteomics in comparison with control cells. The differential proteomics experiments were also performed after treatment with E2, H2O2, and E2 + H2O2. All the runs acquired using liquid chromatography–tandem mass spectrometry were elaborated within the same MaxQuant analysis, leading to the quantification of 1872 proteins in the global proteomic dataset. Then, a differentially regulated protein dataset was obtained for each specific treatment. After the proteomic study, multiple bioinformatics analyses were performed to highlight unbalanced pathways and processes. Here, we report the proteomic and bioinformatic investigations concerning the effects on cellular processes of NGB deficiency and cell treatments. Globally, the main processes that were affected were related to the response to stress, cytoskeleton dynamics, apoptosis, and mitochondria-driven pathways.

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Journal articles on the topic 'Label-free quantitative proteomic'

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