5 research outputs found
Native Proteomics in Discovery Mode Using Size-Exclusion Chromatography–Capillary Zone Electrophoresis–Tandem Mass Spectrometry
Native proteomics aims to characterize complex proteomes under native conditions and
ultimately produces a full picture of endogenous protein complexes in cells. It requires
novel analytical platforms for high-resolution and liquid-phase separation of protein
complexes prior to native mass spectrometry (MS) and MS/MS. In this work, size
exclusion chromatography (SEC)-capillary zone electrophoresis (CZE)-MS/MS was
developed for native proteomics in discovery mode, resulting in the identification of 144
proteins, 672 proteoforms, and 23 protein complexes from the Escherichia coli
proteome. The protein complexes include four protein homodimers, 16 protein-metal
complexes, two protein-[2Fe-2S] complexes, and one protein-glutamine complex. Half
of them have not been reported in the literature. This work represents the first example
of online liquid-phase separation-MS/MS for characterization of a complex proteome
under the native condition, offering the proteomics community an efficient and simple
platform for native proteomics
A Markov Chain Monte Carlo Method for Estimating the Statistical Significance of Proteoform Identifications by Top-Down Mass Spectrometry
Top-down
mass spectrometry is capable of identifying whole proteoform
sequences with multiple post-translational modifications because it
generates tandem mass spectra directly from intact proteoforms. Many
software tools, such as ProSightPC, MSPathFinder, and TopMG, have
been proposed for identifying proteoforms with modifications. In these
tools, various methods are employed to estimate the statistical significance
of identifications. However, most existing methods are designed for
proteoform identifications without modifications, and the challenge
remains for accurately estimating the statistical significance of
proteoform identifications with modifications. Here we propose TopMCMC,
a method that combines a Markov chain random walk algorithm and a
greedy algorithm for assigning statistical significance to matches
between spectra and protein sequences with variable modifications.
Experimental results showed that TopMCMC achieved high accuracy in
estimating <i>E</i>-values and false discovery rates of
identifications in top-down mass spectrometry. Coupled with TopMG,
TopMCMC identified more spectra than the generating function method
from an MCF-7 top-down mass spectrometry data set
Deep Top-Down Proteomics Using Capillary Zone Electrophoresis-Tandem Mass Spectrometry: Identification of 5700 Proteoforms from the <i>Escherichia coli</i> Proteome
Capillary
zone electrophoresis (CZE)-tandem mass spectrometry (MS/MS)
has been recognized as a useful tool for top-down proteomics. However,
its performance for deep top-down proteomics is still dramatically
lower than widely used reversed-phase liquid chromatography (RPLC)-MS/MS.
We present an orthogonal multidimensional separation platform that
couples size exclusion chromatography (SEC) and RPLC based protein
prefractionation to CZE-MS/MS for deep top-down proteomics of <i>Escherichia coli</i>. The platform generated high peak capacity
(∼4000) for separation of intact proteins, leading to the identification
of 5700 proteoforms from the <i>Escherichia coli</i> proteome.
The data represents a 10-fold improvement in the number of proteoform
identifications compared with previous CZE-MS/MS studies and represents
the largest bacterial top-down proteomics data set reported to date.
The performance of the CZE-MS/MS based platform is comparable to the
state-of-the-art RPLC-MS/MS based systems in terms of the number of
proteoform identifications and the instrument time
Deep Top-Down Proteomics Using Capillary Zone Electrophoresis-Tandem Mass Spectrometry: Identification of 5700 Proteoforms from the <i>Escherichia coli</i> Proteome
Capillary
zone electrophoresis (CZE)-tandem mass spectrometry (MS/MS)
has been recognized as a useful tool for top-down proteomics. However,
its performance for deep top-down proteomics is still dramatically
lower than widely used reversed-phase liquid chromatography (RPLC)-MS/MS.
We present an orthogonal multidimensional separation platform that
couples size exclusion chromatography (SEC) and RPLC based protein
prefractionation to CZE-MS/MS for deep top-down proteomics of <i>Escherichia coli</i>. The platform generated high peak capacity
(∼4000) for separation of intact proteins, leading to the identification
of 5700 proteoforms from the <i>Escherichia coli</i> proteome.
The data represents a 10-fold improvement in the number of proteoform
identifications compared with previous CZE-MS/MS studies and represents
the largest bacterial top-down proteomics data set reported to date.
The performance of the CZE-MS/MS based platform is comparable to the
state-of-the-art RPLC-MS/MS based systems in terms of the number of
proteoform identifications and the instrument time
<i>De Novo</i> Protein Sequencing by Combining Top-Down and Bottom-Up Tandem Mass Spectra
There
are two approaches for <i>de novo</i> protein sequencing:
Edman degradation and mass spectrometry (MS). Existing MS-based methods
characterize a novel protein by assembling tandem mass spectra of
overlapping peptides generated from multiple proteolytic digestions
of the protein. Because each tandem mass spectrum covers only a short
peptide of the target protein, the key to high coverage protein sequencing
is to find spectral pairs from overlapping peptides in order to assemble
tandem mass spectra to long ones. However, overlapping regions of
peptides may be too short to be confidently identified. High-resolution
mass spectrometers have become accessible to many laboratories. These
mass spectrometers are capable of analyzing molecules of large mass
values, boosting the development of top-down MS. Top-down tandem mass
spectra cover whole proteins. However, top-down tandem mass spectra,
even combined, rarely provide full ion fragmentation coverage of a
protein. We propose an algorithm, TBNovo, for <i>de novo</i> protein sequencing by combining top-down and bottom-up MS. In TBNovo,
a top-down tandem mass spectrum is utilized as a scaffold, and bottom-up
tandem mass spectra are aligned to the scaffold to increase sequence
coverage. Experiments on data sets of two proteins showed that TBNovo
achieved high sequence coverage and high sequence accuracy