As a natural environment for human-microbiota interactions, healthy mucus houses a remarkably stable and diverse microbial community. Maintaining this microbiota is essential to human health, both to support the commensal bacteria that perform a wide array of beneficial functions and to prevent the outgrowth of pathogens. However, how the host selects and maintains a specialized microbiota remains largely unknown. In this viewpoint, we propose several strategies by which mucus may regulate the composition and function of the human microbiota and discuss how compromised mucus barriers in disease can give rise to microbial dysbiosis.

Simulating native mucus with model systems such as gels made from reconstituted mucin or commercially available polymers presents experimental advantages including greater sample availability and reduced inter- and intradonor heterogeneity. Understanding whether these gels reproduce the complex physical and biochemical properties of native mucus at multiple length scales is critical to building relevant experimental models, but few systematic comparisons have been reported. Here, we compared bulk mechanical properties, microstructure, and biochemical responses of mucus from different niches, reconstituted mucin gels (with similar pH and polymer concentrations as native tissues), and commonly used commercially available polymers. To evaluate gel properties across these length scales, we used small-amplitude oscillatory shear, single-particle tracking, and microaffinity chromatography with small analytes. With the exception of human saliva, the mechanical response of mucin gels was qualitatively similar to that of native mucus. The transport behavior of charged peptides through native mucus gels was qualitatively reproduced in gels composed of corresponding isolated mucins. Compared to native mucus, we observed substantial differences in the physicochemical properties of gels reconstituted from commercially available mucins and the substitute carboxymethylcellulose, which is currently used in artificial tear and saliva treatments. Our study highlights the importance of selecting a mucus model system guided by the length scale relevant to the scientific investigation or disease application.

SARS‐CoV‐2 mortality has been extensively studied in relation to host susceptibility. How sequence variations in the SARS‐CoV‐2 genome affect pathogenicity is poorly understood. Starting in October 2020, using the methodology of genome‐wide association studies (GWAS), we looked at the association between whole‐genome sequencing (WGS) data of the virus and COVID‐19 mortality as a potential method of early identification of highly pathogenic strains to target for containment. Although continuously updating our analysis, in December 2020, we analyzed 7548 single‐stranded SARS‐CoV‐2 genomes of COVID‐19 patients in the GISAID database and associated variants with mortality using a logistic regression. In total, evaluating 29,891 sequenced loci of the viral genome for association with patient/host mortality, two loci, at 12,053 and 25,088 bp, achieved genome‐wide significance (p values of 4.09e−09 and 4.41e−23, respectively), though only 25,088 bp remained significant in follow‐up analyses. Our association findings were exclusively driven by the samples that were submitted from Brazil (p value of 4.90e−13 for 25,088 bp). The mutation frequency of 25,088 bp in the Brazilian samples on GISAID has rapidly increased from about 0.4 in October/December 2020 to 0.77 in March 2021. Although GWAS methodology is suitable for samples in which mutation frequencies varies between geographical regions, it cannot account for mutation frequencies that change rapidly overtime, rendering a GWAS follow‐up analysis of the GISAID samples that have been submitted after December 2020 as invalid. The locus at 25,088 bp is located in the P.1 strain, which later (April 2021) became one of the distinguishing loci (precisely, substitution V1176F) of the Brazilian strain as defined by the Centers for Disease Control. Specifically, the mutations at 25,088 bp occur in the S2 subunit of the SARS‐CoV‐2 spike protein, which plays a key role in viral entry of target host cells. Since the mutations alter amino acid coding sequences, they potentially imposing structural changes that could enhance viral infectivity and symptom severity. Our analysis suggests that GWAS methodology can provide suitable analysis tools for the real‐time detection of new more transmissible and pathogenic viral strains in databases such as GISAID, though new approaches are needed to accommodate rapidly changing mutation frequencies over time, in the presence of simultaneously changing case/control ratios. Improvements of the associated metadata/patient information in terms of quality and availability will also be important to fully utilize the potential of GWAS methodology in this field.

Human microbiome composition is closely tied to health, but how the host manages its microbial inhabitants remains unclear. One important, but understudied, factor is the natural host environment: mucus, which contains gel-forming glycoproteins (mucins) that display hundreds of glycan structures with potential regulatory function. Leveraging a tractable culture-based system to study how mucins influence oral microbial communities, we found that mucin glycans enable the coexistence of diverse microbes, while resisting disease-associated compositional shifts. Mucins from tissues with unique glycosylation differentially tuned microbial composition, as did isolated mucin glycan libraries, uncovering the importance of specific glycan patterns in microbiome modulation. We found that mucins shape microbial communities in several ways: serving as nutrients to support metabolic diversity, organizing spatial structure through reduced aggregation, and possibly limiting antagonism between competing taxa. Overall, this work identifies mucin glycans as a natural host mechanism and potential therapeutic intervention to maintain healthy microbial communities.

Modulation of mucus production by the human ecto- and endo-cervical epithelium by steroid hormones and associated interactions with commensal microbiome play a central role in the physiology and pathophysiology of the female reproductive tract. However, most of our knowledge about these interactions is based on results from animal studies or in vitro models that fail to faithfully mimic the mucosal environment of the human cervix. Here we describe microfluidic organ-on-a-chip (Organ Chip) models of the human cervical mucosa that recreate the cervical epithelial-stromal interface with a functional epithelial barrier and produce abundant mucus that has compositional, biophysical, and hormone-responsive properties similar to the living cervix. Use of continuous fluid flow promoted ecto-cervical differentiation, whereas use of periodic flow including periods of stasis stimulated endo-cervical specialization. Similar results with minor differences were obtained using epithelial cells isolated from three donors each from a different ethnic background (African American, Hispanic, and Caucasian). When the endo-Cervix Chips were co-cultured with living Lactobacillus crispatus and Gardnerella vaginalis bacterial communities to respectively mimic the effects of human host interactions with optimal (healthy) or non-optimal (dysbiotic) microbiome, significant differences in tissue innate immune responses, barrier function, cell viability, and mucus composition were detected reminiscent of those observed in vivo. Thus, human Cervix Chips provide a physiologically relevant experimental in vitro model to study cervical mucus physiology and its role in human host-microbiome interactions as well as a potential preclinical testbed for development of therapeutic interventions to enhance women's health.