Ng, E. W. L. | bioRxiv Science

bioRxiv2024

Gut microbiota-derived GlcNAc-MurNAc is a TLR4 agonist that protects the host gut

Gut microbiota-derived peptidoglycan fragments (PGNs) are key signaling molecules that regulate multiple aspects of the hosts health. Yet the exact structures of natural PGNs in hosts have not been fully elucidated. Herein, we developed an LC-HRMS/MS analytical platform for global quantification and profiling of natural PGN subtypes in host gut and sera, unexpectedly revealing the abundance of PGN-derived saccharide moieties that do not resemble canonical ligands of mammalian NOD1/2 receptors. Focusing on the disaccharide GlcNAc-MurNAc (GM), a natural gut PGN that does not activate NOD1/2 yet still exhibits robust immunostimulatory effects in host immune cells, we unambiguously established GM as a TLR4 agonist, adding to the growing knowledge of NOD-independent mechanisms of PGN sensing in hosts. Importantly, the administration of GM effectively mitigates colonic inflammation in the DSS-induced colitis model in mice via TLR4-dependent mechanisms, highlighting the in vivo significance of natural gut microbiota-derived PGNs in maintaining host intestinal homeostasis.

biochemistry↗

bioRxiv2023

In silico MS/MS prediction for peptidoglycan profiling uncovers novel anti-inflammatory peptidoglycan fragments of the gut microbiota

Peptidoglycan is an essential exoskeletal polymer present across all bacteria. The gut microbiota-derived peptidoglycan fragments (PGNs) are increasingly recognized as key effector molecules that impact host biology, offering attractive yet untapped potential to combat microbiome-associated diseases in humans. Unfortunately, comprehensive peptidoglycan profiling of gut bacteria has been hampered by the lack of a robust and automated analysis workflow. Currently, PGN identification still relies on manual deconvolutions of acquired tandem mass spectrometry (MS/MS) data, which are highly laborious and inconsistent. Recognizing the unique sugar and amino acid makeup of bacterial peptidoglycan and guided by the experimental MS/MS fragmentation patterns of known PGNs, we developed a computational tool PGN_MS2 that reliably simulates MS/MS spectra of PGNs. Integrating PGN_MS2 into the customizable in silico PGN database, we built an open-access PGN MS library of predicted MS/MS spectra for all molecules in the user-defined in silico PGN search space. With this library, automated searching and spectral matching can be used to identify PGN. We then performed comprehensive peptidoglycan profiling for several gut bacteria species, revealing distinct PGN structural features that may be implicated in microbiota-host crosstalk. Strikingly, the probiotic Bifidobacterium spp. has an exceedingly high proportion of anhydro-PGNs, which exhibit anti-inflammatory effects in vitro. We further identified MltG and RfpB homologs in Bifidobacterium as lytic transglycosylases (LTs), which demonstrate distinct substrate preferences to produce anhydro-PGNs. Overall, our novel PGN_MS2 prediction tool contributes to the robust and automated peptidoglycan analysis workflow, advancing efforts to elucidate the structures and functions of gut microbiota-derived PGNs in the host.

microbiology↗