LMdist: Local Manifold distance accurately measures beta diversity in ecological gradients.

MOTIVATION: Differentiating ecosystems poses a complex, high-dimensional problem constrained by capturing relevant variation across species profiles. Researchers use pairwise distances and subsequent dimensionality reduction to highlight variation in a few dimensions. Despite popularity in analysis of ecological data, these low-dimensional visualizations can contain geometric abnormalities such as "arch" and "horseshoe" effects, potentially obscuring the impact of environmental gradients. These abnormalities appear in ordination but are in fact a product of oversaturated large pairwise distances. RESULTS: We present Local Manifold distance (LMdist), an unsupervised algorithm which adjusts pairwise beta diversity measures to better represent true ecological distances between samples. Beta diversity measures can have a bounded dynamic range in depicting long environmental gradients with high species turnover. Using a graph structure, LMdist projects pairwise distances onto a manifold and traverses the manifold surface to adjust pairwise distances at the upper end of the beta diversity measure's dynamic range. This allows for values beyond the range of the original measure. Not all datasets will have oversaturated pairwise distances, nor will capture variation that resembles a manifold, so LMdist adjusts only those pairwise values which may be undervalued in the presence of a sampled gradient. The adjusted distances serve as input for ordination and statistical testing. We demonstrate on real and simulated data that LMdist effectively recovers distances along known gradients and along complex manifolds such as the Swiss roll dataset. LMdist enables more powerful statistical tests for gradient effects and reveals variation orthogonal to the gradient. AVAILABILITY AND IMPLEMENTATION: Available on GitHub at https://github.com/knights-lab/LMdist.

Industrialized human gut microbiota increases CD8+ T cells and mucus thickness in humanized mouse gut.

Immigration to a highly industrialized nation has been associated with metabolic disease and simultaneous shifts in microbiota composition, but the underlying mechanisms are challenging to test in human studies. Here, we conducted a pilot study to assess the differential effects of human gut microbiota collected from the United States (US) and rural Thailand on the murine gut mucosa and immune system. Colonization of germ-free mice with microbiota from US individuals resulted in an increased accumulation of innate-like CD8 T cells in the small intestine lamina propria and intra-epithelial compartments when compared to colonization with microbiota from Thai individuals. Both TCRγδ and CD8αα T cells showed a marked increase in mice receiving Western microbiota and, interestingly, this phenotype was also associated with an increase in intestinal mucus thickness. Serendipitously, an accidentally infected group of mice corroborated this association between elevated inflammatory response and increased mucus thickness. These results suggest that Western-associated human gut microbes contribute to a pro-inflammatory immune response.

A Guide to Dietary Pattern-Microbiome Data Integration.

The human gut microbiome is linked to metabolic and cardiovascular disease risk. Dietary modulation of the human gut microbiome offers an attractive pathway to manipulate the microbiome to prevent microbiome-related disease. However, this promise has not been realized. The complex system of diet and microbiome interactions is poorly understood. Integrating observational human diet and microbiome data can help researchers and clinicians untangle the complex systems of interactions that predict how the microbiome will change in response to foods. The use of dietary patterns to assess diet-microbiome relations holds promise to identify interesting associations and result in findings that can directly translate into actionable dietary intake recommendations and eating plans. In this article, we first highlight the complexity inherent in both dietary and microbiome data and introduce the approaches generally used to explore diet and microbiome simultaneously in observational studies. Second, we review the food group and dietary pattern-microbiome literature focusing on dietary complexity-moving beyond nutrients. Our review identified a substantial and growing body of literature that explores links between the microbiome and dietary patterns. However, there was very little standardization of dietary collection and assessment methods across studies. The 54 studies identified in this review used ≥7 different methods to assess diet. Coupled with the variation in final dietary parameters calculated from dietary data (e.g., dietary indices, dietary patterns, food groups, etc.), few studies with shared methods and assessment techniques were available for comparison. Third, we highlight the similarities between dietary and microbiome data structures and present the possibility that multivariate and compositional methods, developed initially for microbiome data, could have utility when applied to dietary data. Finally, we summarize the current state of the art for diet-microbiome data integration and highlight ways dietary data could be paired with microbiome data in future studies to improve the detection of diet-microbiome signals.

Saliva Testing Is Accurate for Early-Stage and Presymptomatic COVID-19.

Although nasopharyngeal samples have been considered the gold standard for COVID-19 testing, variability in viral load across different anatomical sites could cause nasopharyngeal samples to be less sensitive than saliva or nasal samples in certain cases. Self-collected samples have logistical advantages over nasopharyngeal samples, making them amenable to population-scale screening. To evaluate sampling alternatives for population screening, we collected nasopharyngeal, saliva, and nasal samples from two cohorts with varied levels and types of symptoms. In a mixed cohort of 60 symptomatic and asymptomatic participants, we found that saliva had 88% concordance with nasopharyngeal samples when tested in the same testing lab (n = 41) and 68% concordance when tested in different testing labs (n = 19). In a second cohort of 20 participants hospitalized for COVID-19, saliva had 74% concordance with nasopharyngeal samples tested in the same testing lab but detected virus in two participants that tested negative with nasopharyngeal samples on the same day. Medical record review showed that the saliva-based testing sensitivity was related to the timing of symptom onset and disease stage. We find that no sample site will be perfectly sensitive for COVID-19 testing in all situations, and the significance of negative results will always need to be determined in the context of clinical signs and symptoms. Saliva retained high clinical sensitivity for early-stage and presymptomatic COVID-19 while allowing easier collection, minimizing the exposure of health care workers, and need for personal protective equipment and making it a viable option for population-scale testing. IMPORTANCE Methods for COVID-19 detection are necessary for public health efforts to monitor the spread of disease. Nasopharyngeal samples have been considered the best approach for COVID-19 testing. However, alternative samples like self-collected saliva offer advantages for population-scale screening. Meta-analyses of recent studies suggest that saliva is useful for detecting SARS-CoV-2; however, differences in disease prevalence, sample collection, and analysis methods still confound strong conclusions on the utility of saliva compared to nasopharyngeal samples. Here, we find that the sensitivity of saliva testing is related to both the timing of the sample collection relative to symptom onset and the disease stage. Importantly, several clinical vignettes in our cohorts highlight the challenges of medical decision making with limited knowledge of the associations between laboratory test data and the natural biology of infection.

Calprotectin (S100A8/A9) Is an Innate Immune Effector in Experimental Periodontitis.

Upregulated in inflammation, calprotectin (complexed S100A8 and S100A9; S100A8/A9) functions as an innate immune effector molecule, promoting inflammation, and also as an antimicrobial protein. We hypothesized that antimicrobial S100A8/A9 would mitigate change to the local microbial community and promote resistance to experimental periodontitis in vivo. To test this hypothesis, S100A9-/- and wild-type (WT; S100A9+/+) C57BL/6 mice were compared using a model of ligature-induced periodontitis. On day 2, WT mice showed fewer infiltrating innate immune cells than S100A9-/- mice; by day 5, the immune cell numbers were similar. At 5 days post ligature placement, oral microbial communities sampled with swabs differed significantly in beta diversity between the mouse genotypes. Ligatures recovered from molar teeth of S100A9-/- and WT mice contained significantly dissimilar microbial genera from each other and the overall oral communities from swabs. Concomitantly, the S100A9-/- mice had significantly greater alveolar bone loss than WT mice around molar teeth in ligated sites. When the oral microflora was ablated by antibiotic pretreatment, differences disappeared between WT and S100A9-/- mice in their immune cell infiltrates and alveolar bone loss. Calprotectin, therefore, suppresses emergence of a dysbiotic, proinflammatory oral microbial community, which reduces innate immune effector activity, including early recruitment of innate immune cells, mitigating subsequent alveolar bone loss and protecting against experimental periodontitis.

Alteration of the Gut Microbiome in Normal and Overweight School Children from Selangor with Lactobacillus Fermented Milk Administration.

Childhood obesity is a serious public health problem worldwide. Perturbations in the gut microbiota composition have been associated with the development of obesity in both children and adults. Probiotics, on the other hand, are proven to restore the composition of the gut microbiome which helps reduce the development of obesity. However, data on the effect of probiotics on gut microbiota and its association with childhood obesity is limited. This study aims to determine the effect of probiotics supplement intervention on gut microbiota profiles in obese and normal-weight children. A total of 37 children, 17 normal weight, and 20 overweight school children from a government school in Selangor were selected to participate in this study. Participants were further divided into intervention and control groups. The intervention groups received daily probiotic drinks while the control groups continued eating their typical diet. Fecal samples were collected from the participants for DNA extraction. The hypervariable V3 and V4 regions of 16S rRNA gene were amplified and sequenced using the Illumina MiSeq platform. No significant differences in alpha diversity were observed between normal weight and obese children in terms of the Shannon Index for evenness or species richness. However, a higher intervention effect on alpha diversity was observed among normal-weight participants compared to obese. The participants' microbiome was found to fluctuate throughout the study. Analysis of the taxa at species level showed an increase in Bacteroides ovatus among the normal weight cohort. Genus-level comparison revealed a rise in genus Lachnospira and Ruminococcus in the overweight participants after intervention, compared to the normal-weight participants. The probiotics intervention causes an alteration in gut microbiota composition in both normal and overweight children. Though the association could not be defined statistically, this study has provided an improved understanding of the intervention effect of probiotics on gut microbiome dysbiosis in an underrepresented population.

Bacterial community structure and function distinguish gut sites in captive red-shanked doucs (Pygathrix nemaeus).

The mammalian order primates contains wide species diversity. Members of the subfamily Colobinae are unique amongst extant primates in that their gastrointestinal systems more closely resemble those of ruminants than other members of the primate order. In the growing literature surrounding nonhuman primate microbiomes, analysis of microbial communities has been limited to the hindgut, since few studies have captured data on other gut sites, including the foregut of colobine primates. In this study, we used the red-shanked douc (Pygathrix nemaeus) as a model for colobine primates to study the relationship between gastrointestinal bacterial community structure and gut site within and between subjects. We analyzed fecal and pregastric stomach content samples, representative of the hindgut and foregut respectively, using 16S recombinant DNA (rDNA) sequencing and identified microbiota using closed-reference operational taxonomic unit (OTU) picking against the GreenGenes database. Our results show divergent bacterial communities clearly distinguish the foregut and hindgut microbiomes. We found higher bacterial biodiversity and a higher Firmicutes:Bacteroides ratio in the hindgut as opposed to the foregut. These gut sites showed strong associations with bacterial function. Specifically, energy metabolism was upregulated in the hindgut, whereas detoxification was increased in the foregut. Our results suggest a red-shanked douc's foregut microbiome is no more concordant with its own hindgut than it is with any other red-shanked douc's hindgut microbiome, thus reinforcing the notion that the bacterial communities of the foregut and hindgut are distinctly unique. OPEN PRACTICES: This article has been awarded Open Materials and Open Data badges. All materials and data are publicly accessible via the IRIS Repository at https://www.iris-database.org/iris/app/home/detail?id=york:934328. Learn more about the Open Practices badges from the Center for Open Science: https://osf.io/tvyxz/wiki.