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Dive into the research topics where Lorenzo Vega-Montoto is active.

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Featured researches published by Lorenzo Vega-Montoto.


Nature Biotechnology | 2009

Multi-site assessment of the precision and reproducibility of multiple reaction monitoring-based measurements of proteins in plasma.

Terri Addona; Susan E. Abbatiello; Birgit Schilling; Steven J. Skates; D. R. Mani; David M. Bunk; Clifford H. Spiegelman; Lisa J. Zimmerman; Amy-Joan L. Ham; Hasmik Keshishian; Steven C. Hall; Simon Allen; Ronald K. Blackman; Christoph H. Borchers; Charles Buck; Michael P. Cusack; Nathan G. Dodder; Bradford W. Gibson; Jason M. Held; Tara Hiltke; Angela M. Jackson; Eric B. Johansen; Christopher R. Kinsinger; Jing Li; Mehdi Mesri; Thomas A. Neubert; Richard K. Niles; Trenton Pulsipher; David F. Ransohoff; Henry Rodriguez

Verification of candidate biomarkers relies upon specific, quantitative assays optimized for selective detection of target proteins, and is increasingly viewed as a critical step in the discovery pipeline that bridges unbiased biomarker discovery to preclinical validation. Although individual laboratories have demonstrated that multiple reaction monitoring (MRM) coupled with isotope dilution mass spectrometry can quantify candidate protein biomarkers in plasma, reproducibility and transferability of these assays between laboratories have not been demonstrated. We describe a multilaboratory study to assess reproducibility, recovery, linear dynamic range and limits of detection and quantification of multiplexed, MRM-based assays, conducted by NCI-CPTAC. Using common materials and standardized protocols, we demonstrate that these assays can be highly reproducible within and across laboratories and instrument platforms, and are sensitive to low μg/ml protein concentrations in unfractionated plasma. We provide data and benchmarks against which individual laboratories can compare their performance and evaluate new technologies for biomarker verification in plasma.


Journal of Proteome Research | 2010

Repeatability and Reproducibility in Proteomic Identifications by Liquid Chromatography−Tandem Mass Spectrometry

David L. Tabb; Lorenzo Vega-Montoto; Paul A. Rudnick; Asokan Mulayath Variyath; Amy-Joan L. Ham; David M. Bunk; Lisa E. Kilpatrick; Dean Billheimer; Ronald K. Blackman; Steven A. Carr; Karl R. Clauser; Jacob D. Jaffe; Kevin A. Kowalski; Thomas A. Neubert; Fred E. Regnier; Birgit Schilling; Tony Tegeler; Mu Wang; Pei Wang; Jeffrey R. Whiteaker; Lisa J. Zimmerman; Susan J. Fisher; Bradford W. Gibson; Christopher R. Kinsinger; Mehdi Mesri; Henry Rodriguez; Stephen E. Stein; Paul Tempst; Amanda G. Paulovich; Daniel C. Liebler

The complexity of proteomic instrumentation for LC-MS/MS introduces many possible sources of variability. Data-dependent sampling of peptides constitutes a stochastic element at the heart of discovery proteomics. Although this variation impacts the identification of peptides, proteomic identifications are far from completely random. In this study, we analyzed interlaboratory data sets from the NCI Clinical Proteomic Technology Assessment for Cancer to examine repeatability and reproducibility in peptide and protein identifications. Included data spanned 144 LC-MS/MS experiments on four Thermo LTQ and four Orbitrap instruments. Samples included yeast lysate, the NCI-20 defined dynamic range protein mix, and the Sigma UPS 1 defined equimolar protein mix. Some of our findings reinforced conventional wisdom, such as repeatability and reproducibility being higher for proteins than for peptides. Most lessons from the data, however, were more subtle. Orbitraps proved capable of higher repeatability and reproducibility, but aberrant performance occasionally erased these gains. Even the simplest protein digestions yielded more peptide ions than LC-MS/MS could identify during a single experiment. We observed that peptide lists from pairs of technical replicates overlapped by 35-60%, giving a range for peptide-level repeatability in these experiments. Sample complexity did not appear to affect peptide identification repeatability, even as numbers of identified spectra changed by an order of magnitude. Statistical analysis of protein spectral counts revealed greater stability across technical replicates for Orbitraps, making them superior to LTQ instruments for biomarker candidate discovery. The most repeatable peptides were those corresponding to conventional tryptic cleavage sites, those that produced intense MS signals, and those that resulted from proteins generating many distinct peptides. Reproducibility among different instruments of the same type lagged behind repeatability of technical replicates on a single instrument by several percent. These findings reinforce the importance of evaluating repeatability as a fundamental characteristic of analytical technologies.


Molecular & Cellular Proteomics | 2010

Performance Metrics for Liquid Chromatography-Tandem Mass Spectrometry Systems in Proteomics Analyses

Paul A. Rudnick; Karl R. Clauser; Lisa E. Kilpatrick; Dmitrii V. Tchekhovskoi; P. Neta; Nikša Blonder; Dean Billheimer; Ronald K. Blackman; David M. Bunk; Amy-Joan L. Ham; Jacob D. Jaffe; Christopher R. Kinsinger; Mehdi Mesri; Thomas A. Neubert; Birgit Schilling; David L. Tabb; Tony Tegeler; Lorenzo Vega-Montoto; Asokan Mulayath Variyath; Mu Wang; Pei Wang; Jeffrey R. Whiteaker; Lisa J. Zimmerman; Steven A. Carr; Susan J. Fisher; Bradford W. Gibson; Amanda G. Paulovich; Fred E. Regnier; Henry Rodriguez; Cliff Spiegelman

A major unmet need in LC-MS/MS-based proteomics analyses is a set of tools for quantitative assessment of system performance and evaluation of technical variability. Here we describe 46 system performance metrics for monitoring chromatographic performance, electrospray source stability, MS1 and MS2 signals, dynamic sampling of ions for MS/MS, and peptide identification. Applied to data sets from replicate LC-MS/MS analyses, these metrics displayed consistent, reasonable responses to controlled perturbations. The metrics typically displayed variations less than 10% and thus can reveal even subtle differences in performance of system components. Analyses of data from interlaboratory studies conducted under a common standard operating procedure identified outlier data and provided clues to specific causes. Moreover, interlaboratory variation reflected by the metrics indicates which system components vary the most between laboratories. Application of these metrics enables rational, quantitative quality assessment for proteomics and other LC-MS/MS analytical applications.


Molecular & Cellular Proteomics | 2010

Interlaboratory Study Characterizing a Yeast Performance Standard for Benchmarking LC-MS Platform Performance

Amanda G. Paulovich; Dean Billheimer; Amy-Joan L. Ham; Lorenzo Vega-Montoto; Paul A. Rudnick; David L. Tabb; Pei Wang; Ronald K. Blackman; David M. Bunk; Karl R. Clauser; Christopher R. Kinsinger; Birgit Schilling; Tony Tegeler; Asokan Mulayath Variyath; Mu Wang; Jeffrey R. Whiteaker; Lisa J. Zimmerman; David Fenyö; Steven A. Carr; Susan J. Fisher; Bradford W. Gibson; Mehdi Mesri; Thomas A. Neubert; Fred E. Regnier; Henry Rodriguez; Cliff Spiegelman; Stephen E. Stein; Paul Tempst; Daniel C. Liebler

Optimal performance of LC-MS/MS platforms is critical to generating high quality proteomics data. Although individual laboratories have developed quality control samples, there is no widely available performance standard of biological complexity (and associated reference data sets) for benchmarking of platform performance for analysis of complex biological proteomes across different laboratories in the community. Individual preparations of the yeast Saccharomyces cerevisiae proteome have been used extensively by laboratories in the proteomics community to characterize LC-MS platform performance. The yeast proteome is uniquely attractive as a performance standard because it is the most extensively characterized complex biological proteome and the only one associated with several large scale studies estimating the abundance of all detectable proteins. In this study, we describe a standard operating protocol for large scale production of the yeast performance standard and offer aliquots to the community through the National Institute of Standards and Technology where the yeast proteome is under development as a certified reference material to meet the long term needs of the community. Using a series of metrics that characterize LC-MS performance, we provide a reference data set demonstrating typical performance of commonly used ion trap instrument platforms in expert laboratories; the results provide a basis for laboratories to benchmark their own performance, to improve upon current methods, and to evaluate new technologies. Additionally, we demonstrate how the yeast reference, spiked with human proteins, can be used to benchmark the power of proteomics platforms for detection of differentially expressed proteins at different levels of concentration in a complex matrix, thereby providing a metric to evaluate and minimize preanalytical and analytical variation in comparative proteomics experiments.


Analytical Chemistry | 2012

QuaMeter: Multivendor Performance Metrics for LC–MS/MS Proteomics Instrumentation

Ze Qiang Ma; Kenneth O. Polzin; Surendra Dasari; Matthew C. Chambers; Birgit Schilling; Bradford W. Gibson; Bao Q. Tran; Lorenzo Vega-Montoto; Daniel C. Liebler; David L. Tabb

LC-MS/MS-based proteomics studies rely on stable analytical system performance that can be evaluated by objective criteria. The National Institute of Standards and Technology (NIST) introduced the MSQC software to compute diverse metrics from experimental LC-MS/MS data, enabling quality analysis and quality control (QA/QC) of proteomics instrumentation. In practice, however, several attributes of the MSQC software prevent its use for routine instrument monitoring. Here, we present QuaMeter, an open-source tool that improves MSQC in several aspects. QuaMeter can directly read raw data from instruments manufactured by different vendors. The software can work with a wide variety of peptide identification software for improved reliability and flexibility. Finally, QC metrics implemented in QuaMeter are rigorously defined and tested. The source code and binary versions of QuaMeter are available under Apache 2.0 License at http://fenchurch.mc.vanderbilt.edu.


Journal of Proteome Research | 2012

Pepitome: evaluating improved spectral library search for identification complementarity and quality assessment.

Surendra Dasari; Matthew C. Chambers; Misti A. Martinez; Kristin L. Carpenter; Amy-Joan L. Ham; Lorenzo Vega-Montoto; David L. Tabb

Spectral libraries have emerged as a viable alternative to protein sequence databases for peptide identification. These libraries contain previously detected peptide sequences and their corresponding tandem mass spectra (MS/MS). Search engines can then identify peptides by comparing experimental MS/MS scans to those in the library. Many of these algorithms employ the dot product score for measuring the quality of a spectrum-spectrum match (SSM). This scoring system does not offer a clear statistical interpretation and ignores fragment ion m/z discrepancies in the scoring. We developed a new spectral library search engine, Pepitome, which employs statistical systems for scoring SSMs. Pepitome outperformed the leading library search tool, SpectraST, when analyzing data sets acquired on three different mass spectrometry platforms. We characterized the reliability of spectral library searches by confirming shotgun proteomics identifications through RNA-Seq data. Applying spectral library and database searches on the same sample revealed their complementary nature. Pepitome identifications enabled the automation of quality analysis and quality control (QA/QC) for shotgun proteomics data acquisition pipelines.


Journal of Clinical Investigation | 2014

Integrin-mediated type II TGF-β receptor tyrosine dephosphorylation controls SMAD-dependent profibrotic signaling

Xiwu Chen; Hongtao Wang; Hong Jun Liao; Wen Hu; Leslie Gewin; Glenda Mernaugh; Sheng Zhang; Zhong Yin Zhang; Lorenzo Vega-Montoto; Roberto M. Vanacore; Reinhard Fässler; Roy Zent; Ambra Pozzi

Tubulointerstitial fibrosis underlies all forms of end-stage kidney disease. TGF-β mediates both the development and the progression of kidney fibrosis through binding and activation of the serine/threonine kinase type II TGF-β receptor (TβRII), which in turn promotes a TβRI-mediated SMAD-dependent fibrotic signaling cascade. Autophosphorylation of serine residues within TβRII is considered the principal regulatory mechanism of TβRII-induced signaling; however, there are 5 tyrosine residues within the cytoplasmic tail that could potentially mediate TβRII-dependent SMAD activation. Here, we determined that phosphorylation of tyrosines within the TβRII tail was essential for SMAD-dependent fibrotic signaling within cells of the kidney collecting duct. Conversely, the T cell protein tyrosine phosphatase (TCPTP) dephosphorylated TβRII tail tyrosine residues, resulting in inhibition of TβR-dependent fibrotic signaling. The collagen-binding receptor integrin α1β1 was required for recruitment of TCPTP to the TβRII tail, as mice lacking this integrin exhibited impaired TCPTP-mediated tyrosine dephosphorylation of TβRII that led to severe fibrosis in a unilateral ureteral obstruction model of renal fibrosis. Together, these findings uncover a crosstalk between integrin α1β1 and TβRII that is essential for TβRII-mediated SMAD activation and fibrotic signaling pathways.


Analytical Chemistry | 2014

QC Metrics from CPTAC Raw LC-MS/MS Data Interpreted through Multivariate Statistics

Xia Wang; Matthew C. Chambers; Lorenzo Vega-Montoto; David M. Bunk; Stephen E. Stein; David L. Tabb

Shotgun proteomics experiments integrate a complex sequence of processes, any of which can introduce variability. Quality metrics computed from LC-MS/MS data have relied upon identifying MS/MS scans, but a new mode for the QuaMeter software produces metrics that are independent of identifications. Rather than evaluating each metric independently, we have created a robust multivariate statistical toolkit that accommodates the correlation structure of these metrics and allows for hierarchical relationships among data sets. The framework enables visualization and structural assessment of variability. Study 1 for the Clinical Proteomics Technology Assessment for Cancer (CPTAC), which analyzed three replicates of two common samples at each of two time points among 23 mass spectrometers in nine laboratories, provided the data to demonstrate this framework, and CPTAC Study 5 provided data from complex lysates under Standard Operating Procedures (SOPs) to complement these findings. Identification-independent quality metrics enabled the differentiation of sites and run-times through robust principal components analysis and subsequent factor analysis. Dissimilarity metrics revealed outliers in performance, and a nested ANOVA model revealed the extent to which all metrics or individual metrics were impacted by mass spectrometer and run time. Study 5 data revealed that even when SOPs have been applied, instrument-dependent variability remains prominent, although it may be reduced, while within-site variability is reduced significantly. Finally, identification-independent quality metrics were shown to be predictive of identification sensitivity in these data sets. QuaMeter and the associated multivariate framework are available from http://fenchurch.mc.vanderbilt.edu and http://homepages.uc.edu/~wang2x7/, respectively.


Journal of Biological Chemistry | 2016

Lysyl Oxidase-like-2 Cross-links Collagen IV of Glomerular Basement Membrane.

Carolina Añazco; Alberto J. López-Jiménez; Mohamed Rafi; Lorenzo Vega-Montoto; Ming-Zhi Zhang; Billy G. Hudson; Roberto M. Vanacore

The 7S dodecamer is recognized as an important structural cross-linking domain of collagen IV networks that provide mechanical stability to basement membranes, a specialized form of extracellular matrix essential for the development and maintenance of tissue architecture. Although the 7S dodecamer is stabilized by covalent cross-linking, the molecular mechanism by which such cross-links are formed has not been revealed. Here, we aimed to identify the enzyme(s) that cross-links the 7S dodecamer and characterize its expression in the kidney glomerulus. Pharmacological inhibition of candidate extracellular matrix enzymes revealed that lysyl oxidase activity is required for cross-linking of 7S polypeptides. Among all lysyl oxidase family members, lysyl oxidase-like-2 (LOXL2) was identified as the isoform cross-linking collagen IV in mouse embryonal PFHR-9 cells. Biochemical analyses revealed that LOXL2 readily promoted the formation of lysyl-derived cross-links in the 7S dodecamer but not in the NC1 domain. We also established that LOXL2 is the main lysyl oxidase family member present in the glomerular extracellular matrix. Altogether, we demonstrate that LOXL2 is a novel component of the molecular machinery that forms cross-linked collagen IV networks, which are essential for glomerular basement membrane stability and molecular ultrafiltration function.


Journal of Proteome Research | 2016

Comprehensive Characterization of Glycosylation and Hydroxylation of Basement Membrane Collagen IV by High-Resolution Mass Spectrometry

Trayambak Basak; Lorenzo Vega-Montoto; Lisa J. Zimmerman; David L. Tabb; Billy G. Hudson; Roberto M. Vanacore

Collagen IV is the main structural protein that provides a scaffold for assembly of basement membrane proteins. Posttranslational modifications such as hydroxylation of proline and lysine and glycosylation of lysine are essential for the functioning of collagen IV triple-helical molecules. These modifications are highly abundant posing a difficult challenge for in-depth characterization of collagen IV using conventional proteomics approaches. Herein, we implemented an integrated pipeline combining high-resolution mass spectrometry with different fragmentation techniques and an optimized bioinformatics workflow to study posttranslational modifications in mouse collagen IV. We achieved 82% sequence coverage for the α1 chain, mapping 39 glycosylated hydroxylysine, 148 4-hydroxyproline, and seven 3-hydroxyproline residues. Further, we employed our pipeline to map the modifications on human collagen IV and achieved 85% sequence coverage for the α1 chain, mapping 35 glycosylated hydroxylysine, 163 4-hydroxyproline, and 14 3-hydroxyproline residues. Although lysine glycosylation heterogeneity was observed in both mouse and human, 21 conserved sites were identified. Likewise, five 3-hydroxyproline residues were conserved between mouse and human, suggesting that these modification sites are important for collagen IV function. Collectively, these are the first comprehensive maps of hydroxylation and glycosylation sites in collagen IV, which lay the foundation for dissecting the key role of these modifications in health and disease.

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David M. Bunk

National Institute of Standards and Technology

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Birgit Schilling

Buck Institute for Research on Aging

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Bradford W. Gibson

Buck Institute for Research on Aging

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Henry Rodriguez

National Institutes of Health

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Mehdi Mesri

National Institutes of Health

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