The oral microbiome is critical to human health and disease, yet the role that host salivary proteins play in maintaining oral health is unclear. A highly expressed gene in human salivary glands encodes the lectin zymogen granule protein 16 homolog B (ZG16B). Despite the abundance of this protein, its interaction partners in the oral microbiome are unknown. ZG16B possesses a lectin fold, but whether it binds carbohydrates is unclear. We postulated that ZG16B would bind microbial glycans to mediate recognition of oral microbes. To this end, we developed a microbial glycan analysis probe (mGAP) strategy based on conjugating the recombinant protein to fluorescent or biotin reporter functionality. Applying the ZG16B-mGAP to dental plaque isolates revealed that ZG16B predominantly binds to a limited set of oral microbes, including Streptococcus mitis, Gemella haemolysans , and, most prominently, Streptococcus vestibularis. S. vestibularis is a commensal bacterium widely distributed in healthy individuals. ZG16B binds to S. vestibularis through the cell wall polysaccharides attached to the peptidoglycan, indicating that the protein is a lectin. ZG16B slows the growth of S. vestibularis with no cytotoxicity, suggesting that it regulates S. vestibularis abundance. The mGAP probes also revealed that ZG16B interacts with the salivary mucin MUC7. Analysis of S. vestibularis and MUC7 with ZG16B using super-resolution microscopy supports ternary complex formation that can promote microbe clustering. Together, our data suggest that ZG16B influences the compositional balance of the oral microbiome by capturing commensal microbes and regulating their growth using a mucin-assisted clearance mechanism.

High altitude acclimatization and disease have been the centerpiece of investigations concerning human health at high altitude. Almost all investigations have focused on either understanding and ameliorating high altitude disease or finding better methods of acclimatization/training at high altitude. The aspect of altitude de-induction/de-acclimatization has remained clouded despite the fact that it was documented since the first decade of twentieth century. A few recent studies, particularly in China, have stated unanimously that high altitude de-acclimatization involved multiple observable clinical symptoms ranging from headache to abdominal distention. These symptoms have been collectively referred to as “high altitude de-acclimatization syndrome” (HADAS). However, computational omics and network biology centric investigations concerning HADAS are nascent. In this study, we focus on the quantitative proteo-informatics, especially network biology, of human plasma proteome in individuals who successfully descended from high altitude areas after a stay of 120 days. In brief, the protein list was uploaded into STRING and IPA to compute z-score based cut-offs which were used to analyze the directionality and significance of various identified protein networks as well as the proteins within them. Relevant upstream regulators extracted using computational strategies were also validated. Time-points till the 180th day of de-induction have been investigated to comparatively assess the changes in the plasma proteome and protein pathways of such individuals since the 7th day of arrival at altitude. Our investigation revealed extensive effects of de-induction on lipid metabolism, inflammation and innate immune system as well as coagulation system. This novel study provides a conceptual framework for formulating therapeutic strategies to ease the symptoms of HADAS during de-acclimatization. Such strategies should focus on normalization of lipid metabolism, inflammatory signaling and coagulation systems.

Mammalian saliva plays essential roles in digestion, immunity, and host-microbiome interactions, yet its protein composition varies across species and sexes. The evolutionary mechanisms underlying this molecular diversity remain poorly understood. Here, we compared mouse and human salivary gland secretomes at genomic, transcriptomic, and proteomic levels to understand how saliva composition evolves. We performed RNA-seq analysis of the major mouse salivary glands (parotid, submandibular, and sublingual), liver and pancreas from both sexes, compared them with reanalyzed previously published human salivary gland transcriptomes, and integrated them with proteome data of mouse and human whole saliva. We found that evolution of gene expression in mouse salivary glands is driven by rapid gene turnover and sexual dimorphism. In the submandibular and sublingual glands, respectively, 68% and 73% of expression from genes encoding secreted proteins derives from lineage-specific genes that lack one-to-one human orthologs. Mouse submandibular gland shows striking sexual dimorphism, with 1537 tissue specific sex-biased genes, five times higher than in the liver, a classic model of sex-biased expression. These genes cluster in regions shaped by recent gene duplication, such as the kallikrein gene cluster, a mouse-specific expansion that accounts for ∼16.4% of male-biased submandibular expression. Our analyses suggest that this bias arises through regulatory changes that are expanded by gene duplication, including the spread of a testosterone-associated regulatory motif and the expansion of a shared chromatin domain that promotes coordinated gene regulation. Our results reveal how lineage-specific gene duplication and regulatory rewiring drive rapid, sex-specific evolution of the mammalian salivary gland secretome.