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Thermo Scienti c Poster Note
•
PN HUPO13_POS-02-041_APrakash
_E 09/13S
multiple PTMs and partially cleaved peptides in a single run.
Methods
Comprehensive Workflow Development
We developed a comprehensive MS/MS searching workflow in
Proteome Discoverer software using a combination of multiple
search engines (Figure 1) in an iterative fashion to maximize
protein/peptide identifications by considering the most
frequently found PTMs1, artefacts (Table 1) and partially
cleaved peptides. The combination of PTMs were judiciously
chosen based on relative abundances (UniProtKB) of each
PTM found experimentally and putatively as described in, from
high-quality, manually curated, proteome-wide data1. The
workflows were tested on plasma and urine samples analyzed
on a hybrid Orbitrap mass spectrometer.
Sample Preparation
In order to evaluate the performance of the comprehensive
workflow we took four human samples from two different
sources (a) urine and (b) plasma (three samples). Human urine
and plasma samples were collected with full consent and
approval. The samples were subjected to reduction and
alkylation followed by digestion with trypsin.
Liquid Chromatography and Mass Spectrometry
The digested samples were separated with a 5-45%
acetonitrile gradient in 0.1% formic acid using a C18 nano-LC
column. The urine sample (sample no. 1) and a plasma sample
(sample no. 2) were run for 140 minutes and 90 minutes,
respectively and the data were acquired with a Thermo
Scientific™ LTQ Orbitrap
Velos
™ MS with Top 11 and Top 10
data-dependent MS/MS respectively, using CID fragmentation.
Another two plasma samples (sample nos. 3 and 4) were run
for 240 minutes and the data were acquired with the Thermo
Scientific™ Q Exactive™
benchtop mass spectrometer, with
Top 15 data-dependent MS/MS using HCD fragmentation.
Data Analysis
The acquired data was searched with Proteome Discoverer 1.4
against Uniprot human complete proteome database using the
comprehensive workflow (Figure 1, Table1) and compared with
the SEQUEST workflow with standard modifications (oxidation
at methionine as dynamic modification and alkylation as static
modification) coupled with percolator validation (Standard
Search).
FIGURE 1. Structure of the comprehensive workflow
The comprehensiv
number of high-
co
by 90% and the hi
respect to the stan
comprehensive wo
proteins (with at le
protein in the grou
The comprehensiv
peptides with multi
particular combinat
FIGURE 2. Comp
peptide identifica
plasma)
FIGURE 3. The co
number of identifi
peptide hits per p