15 research outputs found
Metabolic Labeling of Human Bone Marrow Mesenchymal Stem Cells for the Quantitative Analysis of their Chondrogenic Differentiation
Human mesenchymal stem cells (hMSCs), residing in bone
marrow as well as in the synovial lining of joints, can be triggered
to differentiate toward chondrocytes. Thus, hMSCs harbor great therapeutic
potential for the repair of cartilage defects in osteoarthritis (OA)
and other articular diseases. However, the molecular mechanisms underlying
the chondrogenesis process are still in part unknown. In this work,
we applied for the first time the stable isotope labeling by amino
acids in cell culture (SILAC) technique for the quantitative analysis
of protein modulation during the chondrogenic differentiation process
of hMSCs. First, we have standardized the metabolic labeling procedure
on MSCs isolated from bone marrow (hBMSCs), and we have assessed the
quality of chondrogenesis taking place in these conditions. Then,
chondrogenic differentiation was induced on these labeled cells, and
a quantitative proteomics approach has been followed to evaluate protein
changes between two differentiation days. With this strategy, we could
identify 622 different proteins by LCāMALDI-TOF/TOF analysis
and find 65 proteins whose abundance was significantly modulated between
day 2 and day 14 of chondrogenesis. Immunohistochemistry analyses
were performed to verify the changes on a panel of six proteins that
play different biological roles in the cell: fibronectin, gelsolin,
vimentin, alpha-ATPase, mitochondrial superoxide dismutase, and cyclophilin
A. All of these proteins were increased at day 14 compared to day
2 of chondrogenic induction, thus being markers of the enhanced extracellular
matrix synthesis, cell adhesion, metabolism, and response to stress
processes that take place in the early steps of chondrogenesis. Our
strategy has allowed an additional insight into both specific protein
function and the mechanisms of chondrogenesis and has provided a panel
of protein markers of this differentiation process in hBMSCs
Pierre Marie Auguste Broussonet, Paris, [France], to James Edward Smith
Has edited works of [Pierre Richer de] Belleval
Quantitative Proteomic Profiling of Human Articular Cartilage Degradation in Osteoarthritis
Osteoarthritis
(OA) is the most common rheumatic pathology and is characterized primarily
by articular cartilage degradation. Despite its high prevalence, there
is no effective therapy to slow disease progression or regenerate
the damaged tissue. Therefore, new diagnostic and monitoring tests
for OA are urgently needed, which would also promote the development
of alternative therapeutic strategies. In the present study, we have
performed an iTRAQ-based quantitative proteomic analysis of secretomes
from healthy human articular cartilage explants, comparing their protein
profile to those from unwounded (early disease) and wounded (advanced
disease) zones of osteoarthritic tissue. This strategy allowed us
to identify a panel of 76 proteins that are distinctively released
by the diseased tissue. Clustering analysis allowed the classification
of proteins according to their different profile of release from cartilage.
Among these proteins, the altered release of osteoprotegerin (decreased
in OA) and periostin (increased in OA), both involved in bone remodelling
processes, was verified in further analyses. Moreover, periostin was
also increased in the synovial fluid of OA patients. Altogether, the
present work provides a novel insight into the mechanisms of human
cartilage degradation and a number of new cartilage-characteristic
proteins with possible biomarker value for early diagnosis and prognosis
of OA
Cryoconservation of Peptide Extracts from Trypsin Digestion of Proteins for Proteomic Analysis in a Hospital Biobank Facility
We
tested a semiautomated protocol for the proper storage and conservation
in a hospital biobank of tryptic peptide extracts coming from samples
with low and high protein complexity for subsequent mass spectrometry
analysis. Low-complexity samples (serum albumin, serotransferrin.
and alpha-S1-casein) were loaded in replicates in SDS-PAGE and subjected
to standard in-gel trypsin digestion. For LCāMALDIāTOF/TOF
analysis, purified Ī²-galactosidase and human serum samples were
in-solution digested following standard procedures and desalted with
C18 stage-tips. In both cases, peptides extracts were aliquoted in
individually 2D coded tubes, vacuum-dried, barcode-read, and stored
in an automated ā20 Ā°C freezer in the Biobank facility.
Samples were kept dried at ā20 Ā°C until the corresponding
time-point of analysis, then reconstituted in the proper buffer and
analyzed by either MALDI-TOF/TOF (peptide fingerprinting and MS/MS)
or LCāMALDI-TOF/TOF following a highly reproducible pattern
to ensure the reproducibility of the results. Protein identification
was done with either Mascot or Protein Pilot as search engines using
constant parameters. Over a period of 1 year we checked six different
time points at days 0, 7, 30, 90, 180, and 365. We compared MS and
MS/MS protein score, number of identified peptides, and coverage of
the identified proteins. In the low complexity samples, the number
of peptides detected gradually decreased over time, especially affecting
the MS score. However, two of the three proteins ā serum albumin
and serotransferrin ā were identified by both PMF and MS/MS
at day 90. By day 180, only MS/MS identification in some replicates
was possible. By LCāMS/MS, Ī²-galactosidase and the most
abundant serum proteins were identified with good scores at all time
points even by day 365, with no detectable peptide loss or decrease
in the fragmentation efficiency, although a progressive decrease in
peptide intensity indicates that detection of low abundant proteins
could not be optimal after very long periods of time. Our results
encourage us to use the biobank facility in the future for long-term
storage ā up to 3 months ā of dried peptide extracts
Cryoconservation of Peptide Extracts from Trypsin Digestion of Proteins for Proteomic Analysis in a Hospital Biobank Facility
We
tested a semiautomated protocol for the proper storage and conservation
in a hospital biobank of tryptic peptide extracts coming from samples
with low and high protein complexity for subsequent mass spectrometry
analysis. Low-complexity samples (serum albumin, serotransferrin.
and alpha-S1-casein) were loaded in replicates in SDS-PAGE and subjected
to standard in-gel trypsin digestion. For LCāMALDIāTOF/TOF
analysis, purified Ī²-galactosidase and human serum samples were
in-solution digested following standard procedures and desalted with
C18 stage-tips. In both cases, peptides extracts were aliquoted in
individually 2D coded tubes, vacuum-dried, barcode-read, and stored
in an automated ā20 Ā°C freezer in the Biobank facility.
Samples were kept dried at ā20 Ā°C until the corresponding
time-point of analysis, then reconstituted in the proper buffer and
analyzed by either MALDI-TOF/TOF (peptide fingerprinting and MS/MS)
or LCāMALDI-TOF/TOF following a highly reproducible pattern
to ensure the reproducibility of the results. Protein identification
was done with either Mascot or Protein Pilot as search engines using
constant parameters. Over a period of 1 year we checked six different
time points at days 0, 7, 30, 90, 180, and 365. We compared MS and
MS/MS protein score, number of identified peptides, and coverage of
the identified proteins. In the low complexity samples, the number
of peptides detected gradually decreased over time, especially affecting
the MS score. However, two of the three proteins ā serum albumin
and serotransferrin ā were identified by both PMF and MS/MS
at day 90. By day 180, only MS/MS identification in some replicates
was possible. By LCāMS/MS, Ī²-galactosidase and the most
abundant serum proteins were identified with good scores at all time
points even by day 365, with no detectable peptide loss or decrease
in the fragmentation efficiency, although a progressive decrease in
peptide intensity indicates that detection of low abundant proteins
could not be optimal after very long periods of time. Our results
encourage us to use the biobank facility in the future for long-term
storage ā up to 3 months ā of dried peptide extracts
Analysis of Autoantibody Profiles in Osteoarthritis Using Comprehensive Protein Array Concepts
Osteoarthritis
(OA) is the most common rheumatic disease and one
of the most disabling pathologies worldwide. To date, the diagnostic
methods of OA are very limited, and there are no available medications
capable of halting its characteristic cartilage degeneration. Therefore,
there is a significant interest in new biomarkers useful for the early
diagnosis, prognosis, and therapeutic monitoring. In the recent years,
protein microarrays have emerged as a powerful proteomic tool to search
for new biomarkers. In this study, we have used two concepts for generating
protein arrays, antigen microarrays, and NAPPA (nucleic acid programmable
protein arrays), to characterize differential autoantibody profiles
in a set of 62 samples from OA, rheumatoid arthritis (RA), and healthy
controls. An untargeted screen was performed on 3840 protein fragments
spotted on planar antigen arrays, and 373 antigens were selected for
validation on bead-based arrays. In the NAPPA approach, a targeted
screening was performed on 80 preselected proteins. The autoantibody
targeting CHST14 was validated by ELISA in the same set of patients.
Altogether, nine and seven disease related autoantibody target candidates
were identified, and this work demonstrates a combination of these
two array concepts for biomarker discovery and their usefulness for
characterizing disease-specific autoantibody profiles
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-LCāMS/MS and gel/LCāMS/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-LCāMS/MS and gel/LCāMS/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-LCāMS/MS and gel/LCāMS/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-LCāMS/MS and gel/LCāMS/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