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Miclotte G, Martens K, Fostier J. Computational assessment of the feasibility of protonation-based protein sequencing. PLoS One 2020; 15:e0238625. [PMID: 32915813 PMCID: PMC7485799 DOI: 10.1371/journal.pone.0238625] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2019] [Accepted: 08/20/2020] [Indexed: 02/05/2023] Open
Abstract
Recent advances in DNA sequencing methods revolutionized biology by providing highly accurate reads, with high throughput or high read length. These read data are being used in many biological and medical applications. Modern DNA sequencing methods have no equivalent in protein sequencing, severely limiting the widespread application of protein data. Recently, several optical protein sequencing methods have been proposed that rely on the fluorescent labeling of amino acids. Here, we introduce the reprotonation-deprotonation protein sequencing method. Unlike other methods, this proposed technique relies on the measurement of an electrical signal and requires no fluorescent labeling. In reprotonation-deprotonation protein sequencing, the terminal amino acid is identified through its unique protonation signal, and by repeatedly cleaving the terminal amino acids one-by-one, each amino acid in the peptide is measured. By means of simulations, we show that, given a reference database of known proteins, reprotonation-deprotonation sequencing has the potential to correctly identify proteins in a sample. Our simulations provide target values for the signal-to-noise ratios that sensor devices need to attain in order to detect reprotonation-deprotonation events, as well as suitable pH values and required measurement times per amino acid. For instance, an SNR of 10 is required for a 61.71% proteome recovery rate with 100 ms measurement time per amino acid.
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Affiliation(s)
| | | | - Jan Fostier
- IDLab, Ghent University-Imec, Ghent, Belgium
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2
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Kelly LE, Sinha Y, Barker CIS, Standing JF, Offringa M. Useful pharmacodynamic endpoints in children: selection, measurement, and next steps. Pediatr Res 2018; 83:1095-1103. [PMID: 29667952 PMCID: PMC6023695 DOI: 10.1038/pr.2018.38] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2017] [Accepted: 02/08/2018] [Indexed: 12/13/2022]
Abstract
Pharmacodynamic (PD) endpoints are essential for establishing the benefit-to-risk ratio for therapeutic interventions in children and neonates. This article discusses the selection of an appropriate measure of response, the PD endpoint, which is a critical methodological step in designing pediatric efficacy and safety studies. We provide an overview of existing guidance on the choice of PD endpoints in pediatric clinical research. We identified several considerations relevant to the selection and measurement of PD endpoints in pediatric clinical trials, including the use of biomarkers, modeling, compliance, scoring systems, and validated measurement tools. To be useful, PD endpoints in children need to be clinically relevant, responsive to both treatment and/or disease progression, reproducible, and reliable. In most pediatric disease areas, this requires significant validation efforts. We propose a minimal set of criteria for useful PD endpoint selection and measurement. We conclude that, given the current heterogeneity of pediatric PD endpoint definitions and measurements, both across and within defined disease areas, there is an acute need for internationally agreed, validated, and condition-specific pediatric PD endpoints that consider the needs of all stakeholders, including healthcare providers, policy makers, patients, and families.
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Affiliation(s)
- Lauren E Kelly
- Department of Pediatrics and Child Health, Max Rady College of Medicine, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Yashwant Sinha
- Therapeutic Goods Administration, Department of Health, Sydney, Australia
| | - Charlotte I S Barker
- Infection, Inflammation and Rheumatology Section, UCL Great Ormond Street Institute of Child Health, University College London, London, UK
| | - Joseph F Standing
- Infection, Inflammation and Rheumatology Section, UCL Great Ormond Street Institute of Child Health, University College London, London, UK
| | - Martin Offringa
- Child Health Evaluative Sciences, Research Institute, The Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada
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3
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Sigdel TK, Nicora CD, Qian WJ, Sarwal MM. Optimization for Peptide Sample Preparation for Urine Peptidomics. Methods Mol Biol 2018; 1788:63-72. [PMID: 29623538 DOI: 10.1007/7651_2017_90] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
Analysis of native or endogenous peptides in biofluids can provide valuable insight into disease mechanisms. Furthermore, the detected peptides may also have utility as potential biomarkers for noninvasive monitoring of human diseases. The noninvasive nature of urine collection and the abundance of peptides in the urine make analysis by high-throughput "peptidomics" methods an attractive approach for investigating the pathogenesis of renal disease. However, urine peptidomics methodologies can be problematic with regard to difficulties associated with sample preparation. The urine matrix can provide significant background interference in making the analytical measurements, in that it hampers both the identification of peptides and the depth of the peptidomics read when utilizing LC-MS-based peptidome analysis. We report on a novel adaptation of the standard solid-phase extraction (SPE) method to a modified SPE (mSPE) approach for improved peptide yield and analysis sensitivity with LC-MS-based peptidomics, in terms of time, cost, clogging of the LC-MS column, peptide yield, peptide quality, and number of peptides identified by each method. The mSPE method provides significantly improved efficiencies for the preparation of samples from urine. The mSPE method is found to be superior to the conventional, standard SPE method for urine peptide sample preparation when applying LC-MS peptidomics analysis, due to optimized sample cleanup that provides improved experimental inference from confidently identified peptides.
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Affiliation(s)
- Tara K Sigdel
- Department of Surgery, University of California San Francisco, San Francisco, CA, USA.
| | - Carrie D Nicora
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Wei-Jun Qian
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Minnie M Sarwal
- Department of Surgery, University of California San Francisco, San Francisco, CA, USA
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4
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Sigdel TK, Sarwal MM. Assessment of Circulating Protein Signatures for Kidney Transplantation in Pediatric Recipients. Front Med (Lausanne) 2017; 4:80. [PMID: 28670579 PMCID: PMC5472654 DOI: 10.3389/fmed.2017.00080] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2017] [Accepted: 05/31/2017] [Indexed: 11/17/2022] Open
Abstract
Identification and use of non-invasive biomarkers for kidney transplantation monitoring is an unmet need. A total of 121 biobanked sera collected from 111 unique kidney transplant (KT) patients (children and adolescent) and 10 age-matched healthy normal controls were used to profile serum proteins using semi-quantitative proteomics. The proteomics data were analyzed to identify panels of serum proteins that were specific to various transplant injuries, which included acute rejection (AR), BK virus nephropathy (BKVN), and chronic allograft nephropathy (CAN). Gene expression data from matching peripheral blood mononuclear cells were interrogated to investigate the association between soluble serum proteins and altered gene expression of corresponding genes in different injury phenotypes. Analysis of the proteomics data identified from different patient phenotypes, with criteria of false discovery rate <0.05 and at least twofold changes in either direction, resulted in a list of 10 proteins that distinguished KT injury from no injury. Similar analyses to identify proteins specific to chronic injury, acute injury, and AR after kidney transplantation identified 22, 6, and 10 proteins, respectively. Elastic-Net logistic regression method was applied on the 137 serum proteins to classify different transplant injuries. This algorithm has identified panels of 10 serum proteins specific for AR, BKVN, and CAN with classification rates 93, 93, and 95%, respectively. The identified proteins could prove to be potential surrogate biomarkers for routine monitoring of the injury status of pediatric KT patients.
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Affiliation(s)
- Tara K Sigdel
- University of California, San Francisco, San Francisco, CA, United States
| | - Minnie M Sarwal
- University of California, San Francisco, San Francisco, CA, United States
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5
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Abstract
Modern multianalyte "omics" technologies allow for the identification of molecular signatures that confer significantly more information than measurement of a single parameter as typically used in current medical diagnostics. Proteomics and metabolomics bioanalytical assays capture a large set of proteins and metabolites in body fluids, cells, or tissues and, complementing genomics, assess the phenome. Proteomics and metabolomics contribute to the development of novel predictive clinical biomarkers in transplantation in 2 ways: they can be used to generate a diagnostic fingerprint or they can be used to discover individual proteins and metabolites of diagnostic potential. Much fewer metabolomics than proteomics biomarker studies in transplant patients have been reported, and, in contrast to proteomics discovery studies, new lead metabolite markers have yet to emerge. Most clinical proteomics studies have been discovery studies. Several of these studies have assessed diagnostic sensitivity and specificity. Nevertheless, none of these newly discovered protein biomarkers have yet been implemented in clinical decision making in transplantation. The currently most advanced markers discovered in proteomics studies in transplant patients are the chemokines CXCL-9 and CXCL-10, which have successfully been validated in larger multicenter trials in kidney transplant patients. These chemokines can be measured using standard immunoassay platforms, which should facilitate clinical implementation. Based on the published evidence, it is reasonable to expect that these chemokine markers can help guiding and individualizing immunosuppressive regimens, may be able to predict acute and chronic T-cell-mediated and antibody-mediated rejection, and may be useful tools for risk stratification of kidney transplant patients.
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Abstract
INTRODUCTION Identification of allograft injury, including acute clinical and subclinical injury, is vital in increasing the longevity of the transplanted organ. Acute rejection, which occurs as a result of a variety of immune and non-immune factors including the infiltration of immune cells and antibodies to the donor specific epitopes, poses a significant risk to the organ. Recent years have marked an increase in the discovery of new genomic, transcriptomic, and proteomic biomarkers in molecular diagnostics, which offer better potential for personalized management of the transplanted organ by providing earlier detection of rejection episodes. Areas covered: This review was compiled from key word searches of full-text publications relevant to the field. Expert commentary: Many of the recent advancements in the molecular diagnostics of allograft injury show much promise, but before they can be fully realized further validation in larger sample sets must be conducted. Additionally, for better informed therapeutic decisions, more work must be completed to differentiate between different causes of injury. Moreover, the diagnostics field is looking at methodologies that allow for multiplexing, the ability to identify multiple targets simultaneously, in order to provide more robust biomarkers and better understanding.
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Affiliation(s)
- Michael Nasr
- Sarwal Lab, University of California, San Francisco
- University of California, San Francisco, Department of Bioengineering & Therapeutic Sciences
- University of California, Berkeley, Department of Bioengineering
| | - Tara Sigdel
- Sarwal Lab, University of California, San Francisco
- Unversity of California, San Francisco Department of Surgery
| | - Minnie Sarwal
- Sarwal Lab, University of California, San Francisco
- Unversity of California, San Francisco Department of Surgery
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7
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Epigenetics in Kidney Transplantation: Current Evidence, Predictions, and Future Research Directions. Transplantation 2016; 100:23-38. [PMID: 26356174 DOI: 10.1097/tp.0000000000000878] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Epigenetic modifications are changes to the genome that occur without any alteration in DNA sequence. These changes include cytosine methylation of DNA at cytosine-phosphate diester-guanine dinucleotides, histone modifications, microRNA interactions, and chromatin remodeling complexes. Epigenetic modifications may exert their effect independently or complementary to genetic variants and have the potential to modify gene expression. These modifications are dynamic, potentially heritable, and can be induced by environmental stimuli or drugs. There is emerging evidence that epigenetics play an important role in health and disease. However, the impact of epigenetic modifications on the outcomes of kidney transplantation is currently poorly understood and deserves further exploration. Kidney transplantation is the best treatment option for end-stage renal disease, but allograft loss remains a significant challenge that leads to increased morbidity and return to dialysis. Epigenetic modifications may influence the activation, proliferation, and differentiation of the immune cells, and therefore may have a critical role in the host immune response to the allograft and its outcome. The epigenome of the donor may also impact kidney graft survival, especially those epigenetic modifications associated with early transplant stressors (e.g., cold ischemia time) and donor aging. In the present review, we discuss evidence supporting the role of epigenetic modifications in ischemia-reperfusion injury, host immune response to the graft, and graft response to injury as potential new tools for the diagnosis and prediction of graft function, and new therapeutic targets for improving outcomes of kidney transplantation.
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Mining the human urine proteome for monitoring renal transplant injury. Kidney Int 2016; 89:1244-52. [PMID: 27165815 DOI: 10.1016/j.kint.2015.12.049] [Citation(s) in RCA: 68] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2015] [Revised: 12/09/2015] [Accepted: 12/30/2015] [Indexed: 12/13/2022]
Abstract
The human urinary proteome provides an assessment of kidney injury with specific biomarkers for different kidney injury phenotypes. In an effort to fully map and decipher changes in the urine proteome and peptidome after kidney transplantation, renal allograft biopsy matched urine samples were collected from 396 kidney transplant recipients. Centralized and blinded histology data from paired graft biopsies was used to classify urine samples into diagnostic categories of acute rejection, chronic allograft nephropathy, BK virus nephritis, and stable graft. A total of 245 urine samples were analyzed by liquid chromatography-mass spectrometry using isobaric Tags for Relative and Absolute Quantitation (iTRAQ) reagents. From a group of over 900 proteins identified in transplant injury, a set of 131 peptides were assessed by selected reaction monitoring for their significance in accurately segregating organ injury causation and pathology in an independent cohort of 151 urine samples. Ultimately, a minimal set of 35 proteins were identified for their ability to segregate the 3 major transplant injury clinical groups, comprising the final panel of 11 urinary peptides for acute rejection (93% area under the curve [AUC]), 12 urinary peptides for chronic allograft nephropathy (99% AUC), and 12 urinary peptides for BK virus nephritis (83% AUC). Thus, urinary proteome discovery and targeted validation can identify urine protein panels for rapid and noninvasive differentiation of different causes of kidney transplant injury, without the requirement of an invasive biopsy.
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9
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Baron D, Giral M, Brouard S. Reconsidering the detection of tolerance to individualize immunosuppression minimization and to improve long-term kidney graft outcomes. Transpl Int 2015; 28:938-59. [DOI: 10.1111/tri.12578] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2015] [Revised: 02/03/2015] [Accepted: 04/02/2015] [Indexed: 01/03/2023]
Affiliation(s)
- Daniel Baron
- INSERM; UMR 1064; Nantes France
- CHU de Nantes; ITUN; Nantes France
- Faculté de Médecine; Université de Nantes; Nantes France
| | - Magali Giral
- INSERM; UMR 1064; Nantes France
- CHU de Nantes; ITUN; Nantes France
- Faculté de Médecine; Université de Nantes; Nantes France
| | - Sophie Brouard
- INSERM; UMR 1064; Nantes France
- CHU de Nantes; ITUN; Nantes France
- Faculté de Médecine; Université de Nantes; Nantes France
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10
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Roedder S, Sigdel T, Salomonis N, Hsieh S, Dai H, Bestard O, Metes D, Zeevi A, Gritsch A, Cheeseman J, Macedo C, Peddy R, Medeiros M, Vincenti F, Asher N, Salvatierra O, Shapiro R, Kirk A, Reed E, Sarwal MM. The kSORT assay to detect renal transplant patients at high risk for acute rejection: results of the multicenter AART study. PLoS Med 2014; 11:e1001759. [PMID: 25386950 PMCID: PMC4227654 DOI: 10.1371/journal.pmed.1001759] [Citation(s) in RCA: 134] [Impact Index Per Article: 13.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/28/2014] [Accepted: 10/10/2014] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Development of noninvasive molecular assays to improve disease diagnosis and patient monitoring is a critical need. In renal transplantation, acute rejection (AR) increases the risk for chronic graft injury and failure. Noninvasive diagnostic assays to improve current late and nonspecific diagnosis of rejection are needed. We sought to develop a test using a simple blood gene expression assay to detect patients at high risk for AR. METHODS AND FINDINGS We developed a novel correlation-based algorithm by step-wise analysis of gene expression data in 558 blood samples from 436 renal transplant patients collected across eight transplant centers in the US, Mexico, and Spain between 5 February 2005 and 15 December 2012 in the Assessment of Acute Rejection in Renal Transplantation (AART) study. Gene expression was assessed by quantitative real-time PCR (QPCR) in one center. A 17-gene set--the Kidney Solid Organ Response Test (kSORT)--was selected in 143 samples for AR classification using discriminant analysis (area under the receiver operating characteristic curve [AUC] = 0.94; 95% CI 0.91-0.98), validated in 124 independent samples (AUC = 0.95; 95% CI 0.88-1.0) and evaluated for AR prediction in 191 serial samples, where it predicted AR up to 3 mo prior to detection by the current gold standard (biopsy). A novel reference-based algorithm (using 13 12-gene models) was developed in 100 independent samples to provide a numerical AR risk score, to classify patients as high risk versus low risk for AR. kSORT was able to detect AR in blood independent of age, time post-transplantation, and sample source without additional data normalization; AUC = 0.93 (95% CI 0.86-0.99). Further validation of kSORT is planned in prospective clinical observational and interventional trials. CONCLUSIONS The kSORT blood QPCR assay is a noninvasive tool to detect high risk of AR of renal transplants. Please see later in the article for the Editors' Summary.
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Affiliation(s)
- Silke Roedder
- Department of Surgery, University of California San Francisco, San Francisco, California, United States of America
| | - Tara Sigdel
- Department of Surgery, University of California San Francisco, San Francisco, California, United States of America
| | - Nathan Salomonis
- Biomedical Informatics, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, United States of America
| | - Sue Hsieh
- Department of Surgery, University of California San Francisco, San Francisco, California, United States of America
| | - Hong Dai
- California Pacific Medical Center, San Francisco, California, United States of America
| | - Oriol Bestard
- Renal Transplant Unit, Bellvitge University Hospital, Barcelona, Spain
| | - Diana Metes
- Thomas E. Starzl Transplantation Institute, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Andrea Zeevi
- Thomas E. Starzl Transplantation Institute, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Albin Gritsch
- Immunogenetics Center, University of California Los Angeles, Los Angeles, California, United States of America
| | - Jennifer Cheeseman
- Department of Surgery, Emory University, Atlanta, Georgia, United States of America
| | - Camila Macedo
- Thomas E. Starzl Transplantation Institute, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Ram Peddy
- California Pacific Medical Center, San Francisco, California, United States of America
| | - Mara Medeiros
- Laboratorio de Investigacion en Nefrologia, Hospital Infantil de México Federico Gómez, Mexico City, Mexico
| | - Flavio Vincenti
- Department of Surgery, University of California San Francisco, San Francisco, California, United States of America
| | - Nancy Asher
- Department of Surgery, University of California San Francisco, San Francisco, California, United States of America
| | | | - Ron Shapiro
- Thomas E. Starzl Transplantation Institute, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Allan Kirk
- Department of Surgery, Emory University, Atlanta, Georgia, United States of America
| | - Elaine Reed
- Immunogenetics Center, University of California Los Angeles, Los Angeles, California, United States of America
| | - Minnie M. Sarwal
- Department of Surgery, University of California San Francisco, San Francisco, California, United States of America
- * E-mail:
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Samuel N, Remke M, Rutka JT, Raught B, Malkin D. Proteomic analyses of CSF aimed at biomarker development for pediatric brain tumors. J Neurooncol 2014; 118:225-238. [PMID: 24771250 DOI: 10.1007/s11060-014-1432-3] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2013] [Accepted: 03/31/2014] [Indexed: 11/29/2022]
Abstract
Primary brain tumors cumulatively represent the most common solid tumors of childhood and are the leading cause of cancer related death in this age group. Traditionally, molecular findings and histological analyses from biopsies of resected tumor tissue have been used for diagnosis and classification of these diseases. However, there is a dearth of useful biomarkers that have been validated and clinically implemented for pediatric brain tumors. Notably, diseases of the central nervous system (CNS) can be assayed through analysis of cerebrospinal fluid (CSF) and as such, CSF represents an appropriate medium to obtain liquid biopsies that can be informative for diagnosis, disease classification and risk stratification. Proteomic profiling of pediatric CNS malignancies has identified putative protein markers of disease, yet few effective biomarkers have been clinically validated or implemented. Advances in protein quantification techniques have made it possible to conduct such investigations rapidly and accurately through proteome-wide analyses. This review summarizes the current literature on proteomics in pediatric neuro-oncology and discusses the implications for clinical applications of proteomics research. We also outline strategies for translating effective CSF proteomic studies into clinical applications to optimize the care of this patient population.
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Affiliation(s)
- Nardin Samuel
- MD/PhD Program, Faculty of Medicine, University of Toronto, Toronto, ON, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada.,The Hospital for Sick Children, Toronto, ON, Canada
| | - Marc Remke
- The Hospital for Sick Children, Toronto, ON, Canada
| | - James T Rutka
- The Hospital for Sick Children, Toronto, ON, Canada.,Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada
| | - Brian Raught
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - David Malkin
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada. .,The Hospital for Sick Children, Toronto, ON, Canada. .,Department of Pediatrics, University of Toronto, Toronto, ON, Canada.
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12
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Sigdel TK, Nicora CD, Hsieh SC, Dai H, Qian WJ, Camp DG, Sarwal MM. Optimization for peptide sample preparation for urine peptidomics. Clin Proteomics 2014; 11:7. [PMID: 24568099 PMCID: PMC3944950 DOI: 10.1186/1559-0275-11-7] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2013] [Accepted: 12/10/2013] [Indexed: 11/10/2022] Open
Abstract
Analysis of native or endogenous peptides in biofluids can provide valuable insights into disease mechanisms. Furthermore, the detected peptides may also have utility as potential biomarkers for non-invasive monitoring of human diseases. The non-invasive nature of urine collection and the abundance of peptides in the urine makes analysis by high-throughput ‘peptidomics’ methods , an attractive approach for investigating the pathogenesis of renal disease. However, urine peptidomics methodologies can be problematic with regards to difficulties associated with sample preparation. The urine matrix can provide significant background interference in making the analytical measurements that it hampers both the identification of peptides and the depth of the peptidomics read when utilizing LC-MS based peptidome analysis. We report on a novel adaptation of the standard solid phase extraction (SPE) method to a modified SPE (mSPE) approach for improved peptide yield and analysis sensitivity with LC-MS based peptidomics in terms of time, cost, clogging of the LC-MS column, peptide yield, peptide quality, and number of peptides identified by each method. Expense and time requirements were comparable for both SPE and mSPE, but more interfering contaminants from the urine matrix were evident in the SPE preparations (e.g., clogging of the LC-MS columns, yellowish background coloration of prepared samples due to retained urobilin, lower peptide yields) when compared to the mSPE method. When we compared data from technical replicates of 4 runs, the mSPE method provided significantly improved efficiencies for the preparation of samples from urine (e.g., mSPE peptide identification 82% versus 18% with SPE; p = 8.92E-05). Additionally, peptide identifications, when applying the mSPE method, highlighted the biology of differential activation of urine peptidases during acute renal transplant rejection with distinct laddering of specific peptides, which was obscured for most proteins when utilizing the conventional SPE method. In conclusion, the mSPE method was found to be superior to the conventional, standard SPE method for urine peptide sample preparation when applying LC-MS peptidomics analysis due to the optimized sample clean up that provided improved experimental inference from the confidently identified peptides.
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Affiliation(s)
| | | | | | | | | | - David G Camp
- California Pacific Medical Center Research Institute, 475 Brannan St,, Ste 220, San Francisco, CA 9410, USA.
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13
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Sigdel TK, Salomonis N, Nicora CD, Ryu S, He J, Dinh V, Orton DJ, Moore RJ, Hsieh SC, Dai H, Thien-Vu M, Xiao W, Smith RD, Qian WJ, Camp DG, Sarwal MM. The identification of novel potential injury mechanisms and candidate biomarkers in renal allograft rejection by quantitative proteomics. Mol Cell Proteomics 2013; 13:621-31. [PMID: 24335474 DOI: 10.1074/mcp.m113.030577] [Citation(s) in RCA: 60] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Early transplant dysfunction and failure because of immunological and nonimmunological factors still presents a significant clinical problem for transplant recipients. A critical unmet need is the noninvasive detection and prediction of immune injury such that acute injury can be reversed by proactive immunosuppression titration. In this study, we used iTRAQ -based proteomic discovery and targeted ELISA validation to discover and validate candidate urine protein biomarkers from 262 renal allograft recipients with biopsy-confirmed allograft injury. Urine samples were randomly split into a training set of 108 patients and an independent validation set of 154 patients, which comprised the clinical biopsy-confirmed phenotypes of acute rejection (AR) (n = 74), stable graft (STA) (n = 74), chronic allograft injury (CAI) (n = 58), BK virus nephritis (BKVN) (n = 38), nephrotic syndrome (NS) (n = 8), and healthy, normal control (HC) (n = 10). A total of 389 proteins were measured that displayed differential abundances across urine specimens of the injury types (p < 0.05) with a significant finding that SUMO2 (small ubiquitin-related modifier 2) was identified as a "hub" protein for graft injury irrespective of causation. Sixty-nine urine proteins had differences in abundance (p < 0.01) in AR compared with stable graft, of which 12 proteins were up-regulated in AR with a mean fold increase of 2.8. Nine urine proteins were highly specific for AR because of their significant differences (p < 0.01; fold increase >1.5) from all other transplant categories (HLA class II protein HLA-DRB1, KRT14, HIST1H4B, FGG, ACTB, FGB, FGA, KRT7, DPP4). Increased levels of three of these proteins, fibrinogen beta (FGB; p = 0.04), fibrinogen gamma (FGG; p = 0.03), and HLA DRB1 (p = 0.003) were validated by ELISA in AR using an independent sample set. The fibrinogen proteins further segregated AR from BK virus nephritis (FGB p = 0.03, FGG p = 0.02), a finding that supports the utility of monitoring these urinary proteins for the specific and sensitive noninvasive diagnosis of acute renal allograft rejection.
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Affiliation(s)
- Tara K Sigdel
- California Pacific Medical Center Research Institute, 475 Brannan St., Ste 220, San Francisco, California 9410
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14
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Lake F. Pediatric-specific biomarkers: an important but challenging field. Biomark Med 2012; 6:237-8. [PMID: 22731897 DOI: 10.2217/bmm.12.32] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
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