7 research outputs found
Quantitative Metaproteomics and Activity-Based Probe Enrichment Reveals Significant Alterations in Protein Expression from a Mouse Model of Inflammatory Bowel Disease
Tandem
mass spectrometry based shotgun proteomics of distal gut
microbiomes is exceedingly difficult due to the inherent complexity
and taxonomic diversity of the samples. We introduce two new methodologies
to improve metaproteomic studies of microbiome samples. These methods
include the stable isotope labeling in mammals to permit protein quantitation
across two mouse cohorts as well as the application of activity-based
probes to enrich and analyze both host and microbial proteins with
specific functionalities. We used these technologies to study the
microbiota from the adoptive T cell transfer mouse model of inflammatory
bowel disease (IBD) and compare these samples to an isogenic control,
thereby limiting genetic and environmental variables that influence
microbiome composition. The data generated highlight quantitative
alterations in both host and microbial proteins due to intestinal
inflammation and corroborates the observed phylogenetic changes in
bacteria that accompany IBD in humans and mouse models. The combination
of isotope labeling with shotgun proteomics resulted in the total
identification of 4434 protein clusters expressed in the microbial
proteomic environment, 276 of which demonstrated differential abundance
between control and IBD mice. Notably, application of a novel cysteine-reactive
probe uncovered several microbial proteases and hydrolases overrepresented
in the IBD mice. Implementation of these methods demonstrated that
substantial insights into the identity and dysregulation of host and
microbial proteins altered in IBD can be accomplished and can be used
in the interrogation of other microbiome-related diseases
Quantitative Metaproteomics and Activity-Based Probe Enrichment Reveals Significant Alterations in Protein Expression from a Mouse Model of Inflammatory Bowel Disease
Tandem
mass spectrometry based shotgun proteomics of distal gut
microbiomes is exceedingly difficult due to the inherent complexity
and taxonomic diversity of the samples. We introduce two new methodologies
to improve metaproteomic studies of microbiome samples. These methods
include the stable isotope labeling in mammals to permit protein quantitation
across two mouse cohorts as well as the application of activity-based
probes to enrich and analyze both host and microbial proteins with
specific functionalities. We used these technologies to study the
microbiota from the adoptive T cell transfer mouse model of inflammatory
bowel disease (IBD) and compare these samples to an isogenic control,
thereby limiting genetic and environmental variables that influence
microbiome composition. The data generated highlight quantitative
alterations in both host and microbial proteins due to intestinal
inflammation and corroborates the observed phylogenetic changes in
bacteria that accompany IBD in humans and mouse models. The combination
of isotope labeling with shotgun proteomics resulted in the total
identification of 4434 protein clusters expressed in the microbial
proteomic environment, 276 of which demonstrated differential abundance
between control and IBD mice. Notably, application of a novel cysteine-reactive
probe uncovered several microbial proteases and hydrolases overrepresented
in the IBD mice. Implementation of these methods demonstrated that
substantial insights into the identity and dysregulation of host and
microbial proteins altered in IBD can be accomplished and can be used
in the interrogation of other microbiome-related diseases
Quantitative Metaproteomics and Activity-Based Probe Enrichment Reveals Significant Alterations in Protein Expression from a Mouse Model of Inflammatory Bowel Disease
Tandem
mass spectrometry based shotgun proteomics of distal gut
microbiomes is exceedingly difficult due to the inherent complexity
and taxonomic diversity of the samples. We introduce two new methodologies
to improve metaproteomic studies of microbiome samples. These methods
include the stable isotope labeling in mammals to permit protein quantitation
across two mouse cohorts as well as the application of activity-based
probes to enrich and analyze both host and microbial proteins with
specific functionalities. We used these technologies to study the
microbiota from the adoptive T cell transfer mouse model of inflammatory
bowel disease (IBD) and compare these samples to an isogenic control,
thereby limiting genetic and environmental variables that influence
microbiome composition. The data generated highlight quantitative
alterations in both host and microbial proteins due to intestinal
inflammation and corroborates the observed phylogenetic changes in
bacteria that accompany IBD in humans and mouse models. The combination
of isotope labeling with shotgun proteomics resulted in the total
identification of 4434 protein clusters expressed in the microbial
proteomic environment, 276 of which demonstrated differential abundance
between control and IBD mice. Notably, application of a novel cysteine-reactive
probe uncovered several microbial proteases and hydrolases overrepresented
in the IBD mice. Implementation of these methods demonstrated that
substantial insights into the identity and dysregulation of host and
microbial proteins altered in IBD can be accomplished and can be used
in the interrogation of other microbiome-related diseases
Triflic Acid Treatment Enables LC-MS/MS Analysis of Insoluble Bacterial Biomass
The
lysis and extraction of soluble bacterial proteins from cells is a
common practice for proteomics analyses, but insoluble bacterial biomasses
are often left behind. Here, we show that with triflic acid treatment,
the insoluble bacterial biomass of Gram<sup>–</sup> and Gram<sup>+</sup> bacteria can be rendered soluble. We use LC-MS/MS shotgun
proteomics to show that bacterial proteins in the soluble and insoluble
postlysis fractions differ significantly. Additionally, in the case
of Gram<sup>–</sup> Pseudomonas aeruginosa, triflic acid treatment enables the enrichment of cell-envelope-associated
proteins. Finally, we apply triflic acid to a human microbiome sample
to show that this treatment is robust and enables the identification
of a new, complementary subset of proteins from a complex microbial
mixture
Triflic Acid Treatment Enables LC-MS/MS Analysis of Insoluble Bacterial Biomass
The
lysis and extraction of soluble bacterial proteins from cells is a
common practice for proteomics analyses, but insoluble bacterial biomasses
are often left behind. Here, we show that with triflic acid treatment,
the insoluble bacterial biomass of Gram<sup>–</sup> and Gram<sup>+</sup> bacteria can be rendered soluble. We use LC-MS/MS shotgun
proteomics to show that bacterial proteins in the soluble and insoluble
postlysis fractions differ significantly. Additionally, in the case
of Gram<sup>–</sup> Pseudomonas aeruginosa, triflic acid treatment enables the enrichment of cell-envelope-associated
proteins. Finally, we apply triflic acid to a human microbiome sample
to show that this treatment is robust and enables the identification
of a new, complementary subset of proteins from a complex microbial
mixture
<sup>13</sup>C NMR Metabolomics: Applications at Natural Abundance
<sup>13</sup>C NMR has many advantages for a metabolomics study,
including a large spectral dispersion, narrow singlets at natural
abundance, and a direct measure of the backbone structures of metabolites.
However, it has not had widespread use because of its relatively low
sensitivity compounded by low natural abundance. Here we demonstrate
the utility of high-quality <sup>13</sup>C NMR spectra obtained using
a custom <sup>13</sup>C-optimized probe on metabolomic mixtures. A
workflow was developed to use statistical correlations between replicate
1D <sup>13</sup>C and <sup>1</sup>H spectra, leading to composite
spin systems that can be used to search publicly available databases
for compound identification. This was developed using synthetic mixtures
and then applied to two biological samples, <i>Drosophila melanogaster</i> extracts and mouse serum. Using the synthetic mixtures we were able
to obtain useful <sup>13</sup>C–<sup>13</sup>C statistical
correlations from metabolites with as little as 60 nmol of material.
The lower limit of <sup>13</sup>C NMR detection under our experimental
conditions is approximately 40 nmol, slightly lower than the requirement
for statistical analysis. The <sup>13</sup>C and <sup>1</sup>H data
together led to 15 matches in the database compared to just 7 using <sup>1</sup>H alone, and the <sup>13</sup>C correlated peak lists had
far fewer false positives than the <sup>1</sup>H generated lists.
In addition, the <sup>13</sup>C 1D data provided improved metabolite
identification and separation of biologically distinct groups using
multivariate statistical analysis in the <i>D. melanogaster</i> extracts and mouse serum
WikiGenomes: an open Web application for community consumption and curation of gene annotation data in Wikidata.
Slideshow of the Wikidata backed web application WikiGenomes.org, presented at the Biocuration 2017 conference at Stanford University