Browsing by Subject "proteomics"
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Item Cancer and Chemotherapy Contribute to Muscle Loss by Activating Common Signaling Pathways(Frontiers, 2016) Barreto, Rafael; Mandili, Giorgia; Witzmann, Frank A.; Novelli, Francesco; Zimmers, Teresa A.; Bonetto, Andrea; Department of Surgery, IU School of MedicineCachexia represents one of the primary complications of colorectal cancer due to its effects on depletion of muscle and fat. Evidence suggests that chemotherapeutic regimens, such as Folfiri, contribute to cachexia-related symptoms. The purpose of the present study was to investigate the cachexia signature in different conditions associated with severe muscle wasting, namely Colon-26 (C26) and Folfiri-associated cachexia. Using a quantitative LC-MS/MS approach, we identified significant changes in 386 proteins in the quadriceps muscle of Folfiri-treated mice, and 269 proteins differentially expressed in the C26 hosts (p < 0.05; -1.5 ≥ fold change ≥ +1.5). Comparative analysis isolated 240 proteins that were modulated in common, with a large majority (218) that were down-regulated in both experimental settings. Interestingly, metabolic (47.08%) and structural (21.25%) proteins were the most represented. Pathway analysis revealed mitochondrial dysfunctions in both experimental conditions, also consistent with reduced expression of mediators of mitochondrial fusion (OPA-1, mitofusin-2), fission (DRP-1) and biogenesis (Cytochrome C, PGC-1α). Alterations of oxidative phosphorylation within the TCA cycle, fatty acid metabolism, and Ca(2+) signaling were also detected. Overall, the proteomic signature in the presence of both chemotherapy and cancer suggests the activation of mechanisms associated with movement disorders, necrosis, muscle cell death, muscle weakness and muscle damage. Conversely, this is consistent with the inhibition of pathways that regulate nucleotide and fatty acid metabolism, synthesis of ATP, muscle and heart function, as well as ROS scavenging. Interestingly, strong up-regulation of pro-inflammatory acute-phase proteins and a more coordinated modulation of mitochondrial and lipidic metabolisms were observed in the muscle of the C26 hosts that were different from the Folfiri-treated animals. In conclusion, our results suggest that both cancer and chemotherapy contribute to muscle loss by activating common signaling pathways. These data support the undertaking of combination strategies that aim to both counteract tumor growth and reduce chemotherapy side effects.Item classCleaner: A Quantitative Method for Validating Peptide Identification in LC-MS/MS Workflows(2020-05) Key, Melissa Chester; Boukai, Benzion; Ragg, Susanne; Katz, Barry; Mosley, AmberBecause label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS) shotgun proteomics infers the peptide sequence of each measurement, there is inherent uncertainty in the identity of each peptide and its originating protein. Removing misidentified peptides can improve the accuracy and power of downstream analyses when differences between proteins are of primary interest. In this dissertation I present classCleaner, a novel algorithm designed to identify misidentified peptides from each protein using the available quantitative data. The algorithm is based on the idea that distances between peptides belonging to the same protein are stochastically smaller than those between peptides in different proteins. The method first determines a threshold based on the estimated distribution of these two groups of distances. This is used to create a decision rule for each peptide based on counting the number of within-protein distances smaller than the threshold. Using simulated data, I show that classCleaner always reduces the proportion of misidentified peptides, with better results for larger proteins (by number of constituent peptides), smaller inherent misidentification rates, and larger sample sizes. ClassCleaner is also applied to a LC-MS/MS proteomics data set and the Congressional Voting Records data set from the UCI machine learning repository. The later is used to demonstrate that the algorithm is not specific to proteomics.Item Comprehensive Proteomics Analysis of Stressed Human Islets Identifies GDF15 as a Target for Type 1 Diabetes Intervention(Elsevier, 2020-02-04) Nakayasu, Ernesto S.; Syed, Farooq; Tersey, Sarah A.; Gritsenko, Marina A.; Mitchell, Hugh D.; Chan, Chi Yuet; Dirice, Ercument; Turatsinze, Jean-Valery; Cui, Yi; Kulkarni, Rohit N.; Eizirik, Decio L.; Qian, Wei-Jun; Webb-Robertson, Bobbie-Jo M.; Evans-Molina, Carmella; Mirmira., Raghavendra G.; Metz, Thomas O.; Pediatrics, School of MedicineType 1 diabetes (T1D) results from the progressive loss of β cells, a process propagated by pro-inflammatory cytokine signaling that disrupts the balance between pro- and anti-apoptotic proteins. To identify proteins involved in this process, we performed comprehensive proteomics of human pancreatic islets treated with interleukin-1β and interferon-γ, leading to the identification of 11,324 proteins, of which 387 were significantly regulated by treatment. We then tested the function of growth/differentiation factor 15 (GDF15), which was repressed by the treatment. We found that GDF15 translation was blocked during inflammation, and it was depleted in islets from individuals with T1D. The addition of exogenous GDF15 inhibited interleukin-1β+interferon-γ-induced apoptosis of human islets. Administration of GDF15 reduced by 53% the incidence of diabetes in NOD mice. Our approach provides a unique resource for the identification of the human islet proteins regulated by cytokines and was effective in discovering a potential target for T1D therapy.Item A large, consistent plasma proteomics data set from prospectively collected breast cancer patient and healthy volunteer samples(BMC, 2011-05-27) Riley, Catherine P; Zhang, Xiang; Nakshatri, Harikrishna; Schneider, Bryan; Regnier, Fred E; Adamec, Jiri; Buck, CharlesBackground Variability of plasma sample collection and of proteomics technology platforms has been detrimental to generation of large proteomic profile datasets from human biospecimens. Methods We carried out a clinical trial-like protocol to standardize collection of plasma from 204 healthy and 216 breast cancer patient volunteers. The breast cancer patients provided follow up samples at 3 month intervals. We generated proteomics profiles from these samples with a stable and reproducible platform for differential proteomics that employs a highly consistent nanofabricated ChipCube™ chromatography system for peptide detection and quantification with fast, single dimension mass spectrometry (LC-MS). Protein identification is achieved with subsequent LC-MS/MS analysis employing the same ChipCube™ chromatography system. Results With this consistent platform, over 800 LC-MS plasma proteomic profiles from prospectively collected samples of 420 individuals were obtained. Using a web-based data analysis pipeline for LC-MS profiling data, analyses of all peptide peaks from these plasma LC-MS profiles reveals an average coefficient of variability of less than 15%. Protein identification of peptide peaks of interest has been achieved with subsequent LC-MS/MS analyses and by referring to a spectral library created from about 150 discrete LC-MS/MS runs. Verification of peptide quantity and identity is demonstrated with several Multiple Reaction Monitoring analyses. These plasma proteomic profiles are publicly available through ProteomeCommons. Conclusion From a large prospective cohort of healthy and breast cancer patient volunteers and using a nano-fabricated chromatography system, a consistent LC-MS proteomics dataset has been generated that includes more than 800 discrete human plasma profiles. This large proteomics dataset provides an important resource in support of breast cancer biomarker discovery and validation efforts.Item Mass graphs and their applications in top-down proteomics(2015) Kou, Qiang; Wu, Si; Tolić, Nikola; Pasa-Tolić, Ljiljana; Liu, Xiaowen; Department of Biohealth Informatics, School of Informatics and ComputingAlthough proteomics has made rapid progress in the past decade, researchers are still in the early stage of exploring the world of complex proteoforms, which are protein products with various primary structure alterations resulting from gene mutations, alternative splicing, post-translational modifications, and other biological processes. Proteoform identification is essential to mapping proteoforms to their biological functions as well as discovering novel proteoforms and new protein functions. Top-down mass spectrometry is the method of choice for identifying complex proteoforms because it provides a "bird view" of intact proteoforms. The combinatorial explosion of possible proteoforms, which may result in billions of possible proteoforms for one protein, makes proteoform identification a challenging computational problem. Here we propose a new data structure, called the mass graph, for efficiently representing proteoforms. In addition, we design mass graph alignment algorithms for proteoform identification by top-down mass spectrometry. Experiments on a histone H4 mass spectrometry data set showed that the proposed methods outperformed MS-Align-E in identifying complex proteoforms.Item Molecular targets of alcohol action: translational research for pharmacotherapy development and screening.(Elsevier, 2011) Gorini, Giorgio; Bell, Richard L.; Mayfield, R. Dayne; Department of Psychology, School of ScienceAlcohol abuse and dependence are multifaceted disorders with neurobiological, psychological, and environmental components. Research on other complex neuropsychiatric diseases suggests that genetically influenced intermediate characteristics affect the risk for heavy alcohol consumption and its consequences. Diverse therapeutic interventions can be developed through identification of reliable biomarkers for this disorder and new pharmacological targets for its treatment. Advances in the fields of genomics and proteomics offer a number of possible targets for the development of new therapeutic approaches. This brain-focused review highlights studies identifying neurobiological systems associated with these targets and possible pharmacotherapies, summarizing evidence from clinically relevant animal and human studies, as well as sketching improvements and challenges facing the fields of proteomics and genomics. Concluding thoughts on using results from these profiling technologies for medication development are also presented.Item Plasma-Derived Extracellular Vesicle Phosphoproteomics through Chemical Affinity Purification(ACS, 2020-05) liuk, Anton; Wu, Xiaofeng; Li, Li; Sun, Jie; Hadisurya, Marco; Boris, Ronald S.; Tao, W. Andy; Urology, School of MedicineThe invasive nature and the pain caused to patients inhibit the routine use of tissue biopsy-based procedures for cancer diagnosis and surveillance. The analysis of extracellular vesicles (EVs) from biofluids has recently gained significant traction in the liquid biopsy field. EVs offer an essential “snapshot” of their precursor cells in real time and contain an information-rich collection of nucleic acids, proteins, lipids, and so on. The analysis of protein phosphorylation, as a direct marker of cellular signaling and disease progression could be an important stepping stone to successful liquid biopsy applications. Here we introduce a rapid EV isolation method based on chemical affinity called EVtrap (extracellular vesicle total recovery and purification) for the EV phosphoproteomics analysis of human plasma. By incorporating EVtrap with high-performance mass spectrometry (MS), we were able to identify over 16 000 unique peptides representing 2238 unique EV proteins from just 5 μL of plasma sample, including most known EV markers, with substantially higher recovery levels compared with ultracentrifugation. Most importantly, more than 5500 unique phosphopeptides representing almost 1600 phosphoproteins in EVs were identified using only 1 mL of plasma. Finally, we carried out a quantitative EV phosphoproteomics analysis of plasma samples from patients diagnosed with chronic kidney disease or kidney cancer, identifying dozens of phosphoproteins capable of distinguishing disease states from healthy controls. The study demonstrates the potential feasibility of our robust analytical pipeline for cancer signaling monitoring by tracking plasma EV phosphorylation.Item Proteomic profiling of halloysite clay nanotube exposure in intestinal cell co-culture(Wiley, 2013-11) Lai, Xianyin; Agarwal, Mangilal; Lvov, Yuri M.; Pachpande, Chetan; Varahramyan, Kody; Witzmann, Frank A.; Department of Cellular & Integrative Physiology, Indiana University School of MedicineHalloysite is aluminosilicate clay with a hollow tubular structure with nanoscale internal and external diameters. Assessment of halloysite biocompatibility has gained importance in view of its potential application in oral drug delivery. To investigate the effect of halloysite nanotubes on an in vitro model of the large intestine, Caco-2/HT29-MTX cells in monolayer co-culture were exposed to nanotubes for toxicity tests and proteomic analysis. Results indicate that halloysite exhibits a high degree of biocompatibility characterized by an absence of cytotoxicity, in spite of elevated pro-inflammatory cytokine release. Exposure-specific changes in expression were observed among 4081 proteins analyzed. Bioinformatic analysis of differentially expressed protein profiles suggest that halloysite stimulates processes related to cell growth and proliferation, subtle responses to cell infection, irritation and injury, enhanced antioxidant capability, and an overall adaptive response to exposure. These potentially relevant functional effects warrant further investigation in in vivo models and suggest that chronic or bolus occupational exposure to halloysite nanotubes may have unintended outcomes.Item The role of charge in the toxicity of polymer-coated cerium oxide nanomaterials to Caenorhabditis elegans(Elsevier, 2017-10) Arndt, Devrah A.; Oostveen, Emily K.; Triplett, Judy; Butterfield, D. Allan; Tsyusko, Olga V.; Collin, Blanche E.; Starnes, Daniel L.; Cai, Jian; Klein, Jon B.; Nass, Richard; Unrine, Jason M.; Department of Pharmacology and Toxicology, School of MedicineThis study examined the impact of surface functionalization and charge on ceria nanomaterial toxicity to Caenorhabditis elegans. The examined endpoints included mortality, reproduction, protein expression, and protein oxidation profiles. Caenorhabditis elegans were exposed to identical 2–5 nm ceria nanomaterial cores which were coated with cationic (diethylaminoethyl dextran; DEAE), anionic (carboxymethyl dextran; CM), and non-ionic (dextran; DEX) polymers. Mortality and reproductive toxicity of DEAE-CeO2 was approximately two orders of magnitude higher than for CM-CeO2 or DEX-CeO2. Two-dimensional gel electrophoresis with orbitrap mass spectrometry identification revealed changes in the expression profiles of several mitochondrial-related proteins and proteins that are expressed in the C. elegans intestine. However, each type of CeO2 material exhibited a distinct protein expression profile. Increases in protein carbonyls and protein-bound 3-nitrotyrosine were also observed for some proteins, indicating oxidative and nitrosative damage. Taken together the results indicate that the magnitude of toxicity and toxicity pathways vary greatly due to surface functionalization of CeO2 nanomaterials.Item The role of proteomics in assessing beta-cell dysfunction and death in type 1 diabetes(Taylor & Francis, 2019-06-24) Nakayasu, Ernesto S.; Qian, Wei-Jun; Evans-Molina, Carmella; Mirmira, Raghavendra G.; Eizirik, Decio L.; Metz, Thomas O.; Pediatrics, School of MedicineIntroduction: Type 1 diabetes (T1D) is characterized by autoimmune-induced dysfunction and destruction of the pancreatic beta cells. Unfortunately, this process is poorly understood, and the current best treatment for type 1 diabetes is administration of exogenous insulin. To better understand these mechanisms and to develop new therapies, there is an urgent need for biomarkers that can reliably predict disease stage. Areas covered: Mass spectrometry (MS)-based proteomics and complementary techniques play an important role in understanding the autoimmune response, inflammation and beta-cell death. MS is also a leading technology for the identification of biomarkers. This, and the technical difficulties and new technologies that provide opportunities to characterize small amounts of sample in great depth and to analyze large sample cohorts will be discussed in this review. Expert opinion: Understanding disease mechanisms and the discovery of disease-associated biomarkers are highly interconnected goals. Ideal biomarkers would be molecules specific to the different stages of the disease process that are released from beta cells to the bloodstream. However, such molecules are likely present in trace amounts in the blood due to the small number of pancreatic beta cells in the human body and the heterogeneity of the target organ and disease process.