Cell and Molecular Biology Symposia 2010

1. Evaluation of the Agilent Q-TOF 6520 LC/MS platform for Proteomic Analysis of
Brush Border Membranes from Rat Kidney Proximal Tubules
Scott Walmsley*1, Brian Cranmer2, Norman Curthoys1
1Cell and Molecular Biology Interdisciplinary Program, Department of Biochemistry and Molecular Biology, 2RMRCE Genomic and Proteomic Core
Colorado State University, Fort Collins, CO
I. Background II. Experimental III. Resulting methodologies:
A. Preliminary: C18-NSI-MS2 (Thermo LTQ)
In a previous study, two methods to prepare apical membranes
The proteomic analysis utilized 4 samples that were trypsin treated, reduced and alkylated. To Using two parallell workflows, we plan to develop a feature finding strategy that utilized
were compared. Using Mg2+/EGTA precipitation (Biber, et al. obtain enough peptide and spectral counts per protein the peptides were fractionated by SCX arrays of identified features from our LC-MS analysis on the Q-TOF. Correlation of retention
2007), brush border membrane vesicles were isolated from into 7 fractions. 7 ul / fraction was triply injected and then eluted into the Thermo finigan LTQ
times across runs as well as the mass accuracy of the instrument (~5ppm) together with our
kidney cortex (BBMVCTX) or Percoll gradient purified proximal
mass spectrometer (15-60% acetonitrile, 42 minutes) and the spectra collected in a data Sample Sample small protein lists as identified with the LTQ will enable feature matching to peptides in the
dependent manner. The resultant spectra were analyzed by SEQUEST and X!Tandem and the
results combined by Scaffold. The exported data were then analyzed using R and significance for protein list based on the mass and NET model alone.
convoluted tubules (BBMVPCT). The subsequent preparations relative abundance was tested using Fisher’s Exact Test and a BY corrected p value distribution (q
were analyzed using a shotgun proteomics approach with <0.001). The analysis was limited by the significant amount of starting material (30ug) and
subsequent analysis encompassing 21 injections per biological sample. These prevented the use
spectral counting as a quantitative measure to assess differences of technical replicates.
between the resultant membranes isolated from the different
cell types. BBMVCTX
Proximal Tubule BSA and Lysozyme was triply injected across 5
PCT
(S1/S2) Data
Data
Data
concentrations. Using msInspect software,
the feature sets were aligned using an AMT
BBMVPCT
Data
SCX Fractions strategy. The evaluative results indicated low
ppm error of the identified peptides by MS2
using X!Tandem .
Brush Border (lumenal side)
LC-MS2 LC-MS
LC-MS NET and mass mapping of the features
B. Preliminary: C18 (HPLC Chip) NSI-MS2 (Agilent Q-TOF 6520) (LTQ) (Q-TOF)
(Q-TOF) indicated strong correlation across all 15
PST Image: www.uptodate.com Since the LC HPLC chip coupled to the Q-TOF mass spectrometer has a significant lower dead arrays for the identified peptides. Validating
(S3) space between the enrichment and analytical columns when compared to the LTQ, we MS2 identifications back to the features will
analyzed our BBMV samples using a similar approach as to our previous study, with the increase the correlation of the “true”
Basolateral exception of SCX fractionation. The Z=2+ monoisotopic peaks when sorted by intensity identifications.
indicated greater signal to noise ratios when compared to the LTQ for the similarly prepared
samples. Peptide counts were significantly higher for the data acquired on the Q-TOF (not
shown).
Thermo LTQ Agilent Q-TOF 6520
The Results indicated significant differences between the two
preparations. From this analysis, it was concluded that
BBMV BBMV BBMV 7 Day Acidotic LC-MS2
Feature List (Q-TOF)
BBMVCTX were derived primarily from the S3 segment and NET, Mass,
BBMVPCT were derived from the S1/S2 segment of the
Protein IDs Intensities
Feature validation NET
proximal tubule. Enriched in the S1/S2 segment, were 150 47 70 26
NET and mass error of the features indicate
proteins involved in glycolysis/gluconeogenesis (KEGG). This alignment to the features developed for the
AMT database. Continued work is necessary
indicates the putative localization of a glycolytic complex at 1.SLC5A2 Cntrl to further optimize LC parameters to help to
the apical region of the S1/S2 segment, in concordance with 2.ENO1
3.FBP1
Acidotic
Acidotic obtain the best results from samples of a
4.Aldob Cntrl complex nature.
current dogma for PCT cell function. Statistical Validation
Validation ppm
C. Q-TOF with HPLC chip performance, quantitation
Our results had indicated that the LC front end significantly improved the ability to resolve
peaks with fewer separation steps because of the dimensions of the C18 enrichment
column and the analytical column, dead space, and the mass accuracy of the TOF MS
Cortex Cortex (when compared to the LTQ.
PCT
IV. Conclusion
Our results indicated that a combined approach
BBMV BBMV
utilizing both MS platforms may streamline
identification and matching of features that
represent differences in the abundance of peptides.
Due to the mass accuracy of the Q-TOF together
with the previously produced data from the LTQ,
and the small size of the database representing our
subset of the proteome, the features whose
abundances are altered from one sample to the
next can be statistically verified.