11 research outputs found
Identification of the Missing Protein Hyaluronan Synthase 1 in Human Mesenchymal Stem Cells Derived from Adipose Tissue or Umbilical Cord
Currently, 14% of the human proteome
is made up of proteins whose
existence is not confirmed by mass spectrometry. We performed a proteomic
profiling of human mesenchymal stem cells derived from adipose tissue
or umbilical cord (PRIDE accession number: PXD009893) and identified
peptides derived from 13 of such missing proteins. Remarkably, we
found compelling evidence of the expression of hyaluronan synthase
1 (NX_Q92839-1) and confirmed its identification by the fragmentation
of four heavy-labeled peptides that coeluted with their endogenous
light counterparts. Our data also suggest that mesenchymal stem cells
constitute a promising source for the detection of missing proteins
General Statistical Framework for Quantitative Proteomics by Stable Isotope Labeling
The combination of stable isotope
labeling (SIL) with mass spectrometry
(MS) allows comparison of the abundance of thousands of proteins in
complex mixtures. However, interpretation of the large data sets generated
by these techniques remains a challenge because appropriate statistical
standards are lacking. Here, we present a generally applicable model
that accurately explains the behavior of data obtained using current
SIL approaches, including <sup>18</sup>O, iTRAQ, and SILAC labeling,
and different MS instruments. The model decomposes the total technical
variance into the spectral, peptide, and protein variance components,
and its general validity was demonstrated by confronting 48 experimental
distributions against 18 different null hypotheses. In addition to
its general applicability, the performance of the algorithm was at
least similar than that of other existing methods. The model also
provides a general framework to integrate quantitative and error information
fully, allowing a comparative analysis of the results obtained from
different SIL experiments. The model was applied to the global analysis
of protein alterations induced by low H<sub>2</sub>O<sub>2</sub> concentrations
in yeast, demonstrating the increased statistical power that may be
achieved by rigorous data integration. Our results highlight the importance
of establishing an adequate and validated statistical framework for
the analysis of high-throughput data
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