11 research outputs found
Pulsed Azidohomoalanine Labeling in Mammals (PALM) Detects Changes in Liver-Specific LKB1 Knockout Mice
Quantification
of proteomes by mass spectrometry has proven to
be useful to study human pathology recapitulated in cellular or animal
models of disease. Enriching and quantifying newly synthesized proteins
(NSPs) at set time points by mass spectrometry has the potential to
identify important early regulatory or expression changes associated
with disease states or perturbations. NSP can be enriched from proteomes
by employing pulsed introduction of the noncanonical amino acid, azidohomoalanine
(AHA). We demonstrate that pulsed introduction of AHA in the feed
of mice can label and identify NSP from multiple tissues. Furthermore,
we quantitate differences in new protein expression resulting from
CRE-LOX initiated knockout of LKB1 in mouse livers. Overall, the PALM
strategy allows for the first time in vivo labeling of mouse tissues
to differentiate protein synthesis rates at discrete time points
PACOM: A Versatile Tool for Integrating, Filtering, Visualizing, and Comparing Multiple Large Mass Spectrometry Proteomics Data Sets
Mass-spectrometry-based
proteomics has evolved into a high-throughput
technology in which numerous large-scale data sets are generated from
diverse analytical platforms. Furthermore, several scientific journals
and funding agencies have emphasized the storage of proteomics data
in public repositories to facilitate its evaluation, inspection, and
reanalysis. As a consequence, public proteomics
data repositories are growing rapidly. However, tools are needed to
integrate multiple proteomics data sets to compare different experimental
features or to perform quality control analysis. Here, we present
a new Java stand-alone tool, Proteomics Assay COMparator (PACOM),
that is able to import, combine, and simultaneously compare numerous
proteomics experiments to check the integrity of the proteomic data
as well as verify data quality. With PACOM, the user can detect source
of errors that may have been introduced in any step of a proteomics
workflow and that influence the final results. Data sets can be easily
compared and integrated, and data quality and reproducibility can
be visually assessed through a rich set of graphical representations
of proteomics data features as well as a wide variety of data filters.
Its flexibility and easy-to-use interface make PACOM a unique tool
for daily use in a proteomics laboratory. PACOM is available at https://github.com/smdb21/pacom
Surfing Transcriptomic Landscapes. A Step beyond the Annotation of Chromosome 16 Proteome
The
Spanish team of the Human Proteome Project (SpHPP) marked the
annotation of Chr16 and data analysis as one of its priorities. Precise
annotation of Chromosome 16 proteins according to C-HPP criteria is
presented. Moreover, Human Body Map 2.0 RNA-Seq and Encyclopedia of
DNA Elements (ENCODE) data sets were used to obtain further information
relative to cell/tissue specific chromosome 16 coding gene expression
patterns and to infer the presence of missing proteins. Twenty-four
shotgun 2D-LC–MS/MS and gel/LC–MS/MS MIAPE compliant
experiments, representing 41% coverage of chromosome 16 proteins,
were performed. Furthermore, mapping of large-scale multicenter mass
spectrometry data sets from CCD18, MCF7, Jurkat, and Ramos cell lines
into RNA-Seq data allowed further insights relative to correlation
of chromosome 16 transcripts and proteins. Detection and quantification
of chromosome 16 proteins in biological matrices by SRM procedures
are also primary goals of the SpHPP. Two strategies were undertaken:
one focused on known proteins, taking advantage of MS data already
available, and the second, aimed at the detection of the missing proteins,
is based on the expression of recombinant proteins to gather MS information
and optimize SRM methods that will be used in real biological samples.
SRM methods for 49 known proteins and for recombinant forms of 24
missing proteins are reported in this study
Surfing Transcriptomic Landscapes. A Step beyond the Annotation of Chromosome 16 Proteome
The
Spanish team of the Human Proteome Project (SpHPP) marked the
annotation of Chr16 and data analysis as one of its priorities. Precise
annotation of Chromosome 16 proteins according to C-HPP criteria is
presented. Moreover, Human Body Map 2.0 RNA-Seq and Encyclopedia of
DNA Elements (ENCODE) data sets were used to obtain further information
relative to cell/tissue specific chromosome 16 coding gene expression
patterns and to infer the presence of missing proteins. Twenty-four
shotgun 2D-LC–MS/MS and gel/LC–MS/MS MIAPE compliant
experiments, representing 41% coverage of chromosome 16 proteins,
were performed. Furthermore, mapping of large-scale multicenter mass
spectrometry data sets from CCD18, MCF7, Jurkat, and Ramos cell lines
into RNA-Seq data allowed further insights relative to correlation
of chromosome 16 transcripts and proteins. Detection and quantification
of chromosome 16 proteins in biological matrices by SRM procedures
are also primary goals of the SpHPP. Two strategies were undertaken:
one focused on known proteins, taking advantage of MS data already
available, and the second, aimed at the detection of the missing proteins,
is based on the expression of recombinant proteins to gather MS information
and optimize SRM methods that will be used in real biological samples.
SRM methods for 49 known proteins and for recombinant forms of 24
missing proteins are reported in this study
Surfing Transcriptomic Landscapes. A Step beyond the Annotation of Chromosome 16 Proteome
The
Spanish team of the Human Proteome Project (SpHPP) marked the
annotation of Chr16 and data analysis as one of its priorities. Precise
annotation of Chromosome 16 proteins according to C-HPP criteria is
presented. Moreover, Human Body Map 2.0 RNA-Seq and Encyclopedia of
DNA Elements (ENCODE) data sets were used to obtain further information
relative to cell/tissue specific chromosome 16 coding gene expression
patterns and to infer the presence of missing proteins. Twenty-four
shotgun 2D-LC–MS/MS and gel/LC–MS/MS MIAPE compliant
experiments, representing 41% coverage of chromosome 16 proteins,
were performed. Furthermore, mapping of large-scale multicenter mass
spectrometry data sets from CCD18, MCF7, Jurkat, and Ramos cell lines
into RNA-Seq data allowed further insights relative to correlation
of chromosome 16 transcripts and proteins. Detection and quantification
of chromosome 16 proteins in biological matrices by SRM procedures
are also primary goals of the SpHPP. Two strategies were undertaken:
one focused on known proteins, taking advantage of MS data already
available, and the second, aimed at the detection of the missing proteins,
is based on the expression of recombinant proteins to gather MS information
and optimize SRM methods that will be used in real biological samples.
SRM methods for 49 known proteins and for recombinant forms of 24
missing proteins are reported in this study
Surfing Transcriptomic Landscapes. A Step beyond the Annotation of Chromosome 16 Proteome
The
Spanish team of the Human Proteome Project (SpHPP) marked the
annotation of Chr16 and data analysis as one of its priorities. Precise
annotation of Chromosome 16 proteins according to C-HPP criteria is
presented. Moreover, Human Body Map 2.0 RNA-Seq and Encyclopedia of
DNA Elements (ENCODE) data sets were used to obtain further information
relative to cell/tissue specific chromosome 16 coding gene expression
patterns and to infer the presence of missing proteins. Twenty-four
shotgun 2D-LC–MS/MS and gel/LC–MS/MS MIAPE compliant
experiments, representing 41% coverage of chromosome 16 proteins,
were performed. Furthermore, mapping of large-scale multicenter mass
spectrometry data sets from CCD18, MCF7, Jurkat, and Ramos cell lines
into RNA-Seq data allowed further insights relative to correlation
of chromosome 16 transcripts and proteins. Detection and quantification
of chromosome 16 proteins in biological matrices by SRM procedures
are also primary goals of the SpHPP. Two strategies were undertaken:
one focused on known proteins, taking advantage of MS data already
available, and the second, aimed at the detection of the missing proteins,
is based on the expression of recombinant proteins to gather MS information
and optimize SRM methods that will be used in real biological samples.
SRM methods for 49 known proteins and for recombinant forms of 24
missing proteins are reported in this study
Surfing Transcriptomic Landscapes. A Step beyond the Annotation of Chromosome 16 Proteome
The
Spanish team of the Human Proteome Project (SpHPP) marked the
annotation of Chr16 and data analysis as one of its priorities. Precise
annotation of Chromosome 16 proteins according to C-HPP criteria is
presented. Moreover, Human Body Map 2.0 RNA-Seq and Encyclopedia of
DNA Elements (ENCODE) data sets were used to obtain further information
relative to cell/tissue specific chromosome 16 coding gene expression
patterns and to infer the presence of missing proteins. Twenty-four
shotgun 2D-LC–MS/MS and gel/LC–MS/MS MIAPE compliant
experiments, representing 41% coverage of chromosome 16 proteins,
were performed. Furthermore, mapping of large-scale multicenter mass
spectrometry data sets from CCD18, MCF7, Jurkat, and Ramos cell lines
into RNA-Seq data allowed further insights relative to correlation
of chromosome 16 transcripts and proteins. Detection and quantification
of chromosome 16 proteins in biological matrices by SRM procedures
are also primary goals of the SpHPP. Two strategies were undertaken:
one focused on known proteins, taking advantage of MS data already
available, and the second, aimed at the detection of the missing proteins,
is based on the expression of recombinant proteins to gather MS information
and optimize SRM methods that will be used in real biological samples.
SRM methods for 49 known proteins and for recombinant forms of 24
missing proteins are reported in this study
Surfing Transcriptomic Landscapes. A Step beyond the Annotation of Chromosome 16 Proteome
The
Spanish team of the Human Proteome Project (SpHPP) marked the
annotation of Chr16 and data analysis as one of its priorities. Precise
annotation of Chromosome 16 proteins according to C-HPP criteria is
presented. Moreover, Human Body Map 2.0 RNA-Seq and Encyclopedia of
DNA Elements (ENCODE) data sets were used to obtain further information
relative to cell/tissue specific chromosome 16 coding gene expression
patterns and to infer the presence of missing proteins. Twenty-four
shotgun 2D-LC–MS/MS and gel/LC–MS/MS MIAPE compliant
experiments, representing 41% coverage of chromosome 16 proteins,
were performed. Furthermore, mapping of large-scale multicenter mass
spectrometry data sets from CCD18, MCF7, Jurkat, and Ramos cell lines
into RNA-Seq data allowed further insights relative to correlation
of chromosome 16 transcripts and proteins. Detection and quantification
of chromosome 16 proteins in biological matrices by SRM procedures
are also primary goals of the SpHPP. Two strategies were undertaken:
one focused on known proteins, taking advantage of MS data already
available, and the second, aimed at the detection of the missing proteins,
is based on the expression of recombinant proteins to gather MS information
and optimize SRM methods that will be used in real biological samples.
SRM methods for 49 known proteins and for recombinant forms of 24
missing proteins are reported in this study
Surfing Transcriptomic Landscapes. A Step beyond the Annotation of Chromosome 16 Proteome
The
Spanish team of the Human Proteome Project (SpHPP) marked the
annotation of Chr16 and data analysis as one of its priorities. Precise
annotation of Chromosome 16 proteins according to C-HPP criteria is
presented. Moreover, Human Body Map 2.0 RNA-Seq and Encyclopedia of
DNA Elements (ENCODE) data sets were used to obtain further information
relative to cell/tissue specific chromosome 16 coding gene expression
patterns and to infer the presence of missing proteins. Twenty-four
shotgun 2D-LC–MS/MS and gel/LC–MS/MS MIAPE compliant
experiments, representing 41% coverage of chromosome 16 proteins,
were performed. Furthermore, mapping of large-scale multicenter mass
spectrometry data sets from CCD18, MCF7, Jurkat, and Ramos cell lines
into RNA-Seq data allowed further insights relative to correlation
of chromosome 16 transcripts and proteins. Detection and quantification
of chromosome 16 proteins in biological matrices by SRM procedures
are also primary goals of the SpHPP. Two strategies were undertaken:
one focused on known proteins, taking advantage of MS data already
available, and the second, aimed at the detection of the missing proteins,
is based on the expression of recombinant proteins to gather MS information
and optimize SRM methods that will be used in real biological samples.
SRM methods for 49 known proteins and for recombinant forms of 24
missing proteins are reported in this study
Surfing Transcriptomic Landscapes. A Step beyond the Annotation of Chromosome 16 Proteome
The
Spanish team of the Human Proteome Project (SpHPP) marked the
annotation of Chr16 and data analysis as one of its priorities. Precise
annotation of Chromosome 16 proteins according to C-HPP criteria is
presented. Moreover, Human Body Map 2.0 RNA-Seq and Encyclopedia of
DNA Elements (ENCODE) data sets were used to obtain further information
relative to cell/tissue specific chromosome 16 coding gene expression
patterns and to infer the presence of missing proteins. Twenty-four
shotgun 2D-LC–MS/MS and gel/LC–MS/MS MIAPE compliant
experiments, representing 41% coverage of chromosome 16 proteins,
were performed. Furthermore, mapping of large-scale multicenter mass
spectrometry data sets from CCD18, MCF7, Jurkat, and Ramos cell lines
into RNA-Seq data allowed further insights relative to correlation
of chromosome 16 transcripts and proteins. Detection and quantification
of chromosome 16 proteins in biological matrices by SRM procedures
are also primary goals of the SpHPP. Two strategies were undertaken:
one focused on known proteins, taking advantage of MS data already
available, and the second, aimed at the detection of the missing proteins,
is based on the expression of recombinant proteins to gather MS information
and optimize SRM methods that will be used in real biological samples.
SRM methods for 49 known proteins and for recombinant forms of 24
missing proteins are reported in this study