Using PeptideAtlas, SRMAtlas, and PASSEL: Comprehensive Resources for Discovery and Targeted Proteomics

Kusebauch, Ulrike; Deutsch, Eric W.; Campbell, D. S.; Sun, Zhi; Farrah, Terry; Moritz, Robert L.

doi:10.1002/0471250953.bi1325s46

Cited by 59 publications

(48 citation statements)

References 32 publications

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“…The same set of criteria were then applied to filter recent datasets stored in three large proteomics data repositories: PRIDE [9], GPMDB [12], and PeptideAtlas [10]. In the case of PRIDE, datasets were accessed via the PRIDE BioMart if "complete" submissions were available, and via the pepXML format in case of selected "partial" submissions.…”

Section: Data Updatesmentioning

confidence: 99%

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Version 4.0 of PaxDb: Protein abundance data, integrated across model organisms, tissues, and cell‐lines

et al. 2015

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Protein quantification at proteome-wide scale is an important aim, enabling insights into fundamental cellular biology and serving to constrain experiments and theoretical models. While proteome-wide quantification is not yet fully routine, many datasets approaching proteomewide coverage are becoming available through biophysical and MS techniques. Data of this type can be accessed via a variety of sources, including publication supplements and online data repositories. However, access to the data is still fragmentary, and comparisons across experiments and organisms are not straightforward. Here, we describe recent updates to our database resource "PaxDb" (Protein Abundances Across Organisms). PaxDb focuses on protein abundance information at proteome-wide scope, irrespective of the underlying measurement technique. Quantification data is reprocessed, unified, and quality-scored, and then integrated to build a meta-resource. PaxDb also allows evolutionary comparisons through precomputed gene orthology relations. Recently, we have expanded the scope of the database to include cell-line samples, and more systematically scan the literature for suitable datasets. We report that a significant fraction of published experiments cannot readily be accessed and/or parsed for quantitative information, requiring additional steps and efforts. The current update brings PaxDb to 414 datasets in 53 organisms, with (semi-) quantitative abundance information covering more than 300 000 proteins.

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Section: Data Updatesmentioning

confidence: 99%

“…Of these, the largest repositories of primary, raw data are those that are organized in the ProteomeXchange consortium [8]: PRIDE [9], PeptideAtlas [10], MassIVE [11], and PASSEL [10]. Building on these raw data collections as well as on additional curation, submission, and/or reprocessing, a number of additional resources exist.…”

Section: Introductionmentioning

confidence: 99%

Version 4.0 of PaxDb: Protein abundance data, integrated across model organisms, tissues, and cell‐lines

et al. 2015

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“…SRMAtlas, an online resource designed to overcome this limitation, has MS spectra from natural and synthetic peptides collected on triple-quadrupole mass spectrometers, the most common instrument for SRM. A prepublication SRMAtlas preview covers 99.9% of the human proteome (19 ). A third approach, in silico prediction of proteotypic peptides based solely on a protein's amino acid sequence, provides an alternative to relying on previously acquired spectra that is especially useful for pioneering work on biological samples that have not been subjected to extensive proteomic analysis (20 ).…”

confidence: 99%

An Empirical Approach to Signature Peptide Choice for Selected Reaction Monitoring: Quantification of Uromodulin in Urine

Grote

Zhu

et al. 2016

Clinical Chemistry

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BACKGROUND: Many avenues have been proposed for a seamless transition between biomarker discovery data and selected reaction monitoring (SRM) assays for biomarker validation. Unfortunately, studies with the abundant urinary protein uromodulin have shown that these methods do not converge on a consistent set of surrogate peptides for targeted mass spectrometry. As an alternative, we present an empirical peptide selection work flow for robust protein quantification.

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“…A total of 1 ml supernatant was depleted from the 14 most abundant plasma proteins using the multiple affinity removal system (MARS Hu-14, 4.6 3 100 mm, Agilent Technologies) according to the manufacturer's protocol. Thirty-nine proteotypic peptides that are unique to the ten proteins studied and their respective SRM assays were obtained from SRMAtlas (www.srmatlas.org) 25 (Supplemental Table 2). For each peptide sequence the heavy isotopelabeled analog with the C-terminal arginine as R[13C6; 15N4] or lysine as K[13C6; 15N2] and carbamidomethylated cysteine residues were synthesized as crude product (Thermo Fisher Scientific) to allow for relative quantification.…”

Section: Srm Assaysmentioning

confidence: 99%

RNA Sequencing Identifies Novel Translational Biomarkers of Kidney Fibrosis

Craciun

Bijol

Ajay

et al. 2015

JASN

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CKD is the gradual, asymptomatic loss of kidney function, but current tests only identify CKD when significant loss has already happened. Several potential biomarkers of CKD have been reported, but none have been approved for preclinical or clinical use. Using RNA sequencing in a mouse model of folic acidinduced nephropathy, we identified ten genes that track kidney fibrosis development, the common pathologic finding in patients with CKD. The gene expression of all ten candidates was confirmed to be significantly higher (approximately ten-to 150-fold) in three well established, mechanistically distinct mouse models of kidney fibrosis than in models of nonfibrotic AKI. Protein expression of these genes was also high in the folic acid model and in patients with biopsy-proven kidney fibrosis. mRNA expression of the ten genes increased with increasing severity of kidney fibrosis, decreased in response to therapeutic intervention, and increased only modestly (approximately two-to five-fold) with liver fibrosis in mice and humans, demonstrating specificity for kidney fibrosis. Using targeted selected reaction monitoring mass spectrometry, we detected three of the ten candidates in human urine: cadherin 11 (CDH11), macrophage mannose receptor C1 (MRC1), and phospholipid transfer protein (PLTP). Furthermore, urinary levels of each of these three proteins distinguished patients with CKD (n=53) from healthy individuals (n=53; P,0.05). In summary, we report the identification of urinary CDH11, MRC1, and PLTP as novel noninvasive biomarkers of CKD.

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Using PeptideAtlas, SRMAtlas, and PASSEL: Comprehensive Resources for Discovery and Targeted Proteomics

Cited by 59 publications

References 32 publications

Version 4.0 of PaxDb: Protein abundance data, integrated across model organisms, tissues, and cell‐lines

Version 4.0 of PaxDb: Protein abundance data, integrated across model organisms, tissues, and cell‐lines

An Empirical Approach to Signature Peptide Choice for Selected Reaction Monitoring: Quantification of Uromodulin in Urine

RNA Sequencing Identifies Novel Translational Biomarkers of Kidney Fibrosis

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