Dynamic ADP-Ribosylome, Phosphoproteome, and Interactome in LPS-Activated Macrophages.

We have used mass spectrometry (MS) to characterize protein signaling in lipopolysaccharide (LPS)-stimulated macrophages from human blood, human THP1 cells, mouse bone marrow, and mouse Raw264.7 cells. Protein ADP-ribosylation was truncated down to phosphoribose, allowing for enrichment and identification of the resulting phosphoribosylated peptides alongside phosphopeptides. Size exclusion chromatography-MS (SEC-MS) was used to separate proteoforms by size; protein complexes were then identified by weighted correlation network analysis (WGCNA) based on their correlated movement into or out of SEC fractions following stimulation, presenting an analysis method for SEC-MS that does not rely on established databases. We highlight two modules of interest: one linked to the apoptosis signal-regulating kinase (ASK) signalosome and the other containing poly(ADP-ribose) polymerase 9 (PARP9). Finally, PARP inhibition was used to perturb the characterized systems, demonstrating the importance of ADP-ribosylation for the global interactome. All post-translational modification (PTM) and interactome data have been aggregated into a meta-database of 6729 proteins, with ADP-ribosylation characterized on 2905 proteins and phosphorylation characterized on 2669 proteins. This database-titled MAPCD, for Macrophage ADP-ribosylation, Phosphorylation, and Complex Dynamics-serves as an invaluable resource for studying crosstalk between the ADP-ribosylome, phosphoproteome, and interactome.

Multi-omics Comparative Analysis Reveals Multiple Layers of Host Signaling Pathway Regulation by the Gut Microbiota.

The bodies of mammals are hosts to vast microbial communities composed of trillions of bacteria from thousands of species, whose effects on health and development have begun to be appreciated only recently. In this investigation, an integrated analysis combining proteomics and transcriptomics was used to quantitatively compare the terminal ilia from conventional and germfree mice. Female and male mice responded similarly to the microbiota, but C57BL/10A mice responded more strongly than BALB/c mice at both the transcriptome and proteome levels. The microbiota primarily caused upregulation of immunological pathways and downregulation of metabolic pathways in the conventional mice. Many of the affected pathways were altered only at either the transcriptome or proteome level. Of the pathways that were affected at both levels, most were affected concordantly. The discordant pathways were not principally involved in the immune system but instead were related to metabolism, oxidative phosphorylation, protein translation, transport, and turnover. To broaden the discovery of affected host pathways, a meta-analysis was performed using intestinal transcriptomics data from previously published studies of germfree versus conventional mice with diverse microbiota populations. Similar transcript-level responses to the microbiota were found, and many additional affected host pathways were discovered. IMPORTANCE Multiple host pathways were affected by its adaptation to the microbiota. We have found significant transcriptome-proteome discordance caused by the microbiota. This discovery leads to the definite conclusion that transcript-level analysis is not sufficient to predict protein levels and their influence on the function of many specific cellular pathways, so only analysis of combinations of the quantitative data determined at different levels will lead to a complete understanding of the complex relationships between the host and the microbiota. Therefore, our results demonstrate the importance of using an integrative approach to study host-microbiota interaction at the molecular level.