Subchronic inhalation exposure to ultrafine particulate matter alters the intestinal microbiome in various mouse models.

Exposure to ultrafine particles (UFPs) has been associated with multiple adverse health effects. Inhaled UFPs could reach the gastrointestinal tract and influence the composition of the gut microbiome. We have previously shown that oral ingestion of UFPs alters the gut microbiome and promotes intestinal inflammation in hyperlipidemic Ldlr-/- mice. Particulate matter (PM)2.5 inhalation studies have also demonstrated microbiome shifts in normolipidemic C57BL/6 mice. However, it is not known whether changes in microbiome precede or follow inflammatory effects in the intestinal mucosa. We hypothesized that inhaled UFPs modulate the gut microbiome prior to the development of intestinal inflammation. We studied the effects of UFP inhalation on the gut microbiome and intestinal mucosa in two hyperlipidemic mouse models (ApoE-/- mice and Ldlr-/- mice) and normolipidemic C57BL/6 mice. Mice were exposed to PM in the ultrafine-size range by inhalation for 6 h a day, 3 times a week for 10 weeks at a concentration of 300-350 µg/m3.16S rRNA gene sequencing was performed to characterize sequential changes in the fecal microbiome during exposures, and changes in the intestinal microbiome at the end. PM exposure led to progressive differentiation of the microbiota over time, associated with increased fecal microbial richness and evenness, altered microbial composition, and differentially abundant microbes by week 10 depending on the mouse model. Cross-sectional analysis of the small intestinal microbiome at week 10 showed significant changes in α-diversity, ß-diversity, and abundances of individual microbial taxa in the two hyperlipidemic models. These alterations of the intestinal microbiome were not accompanied, and therefore could not be caused, by increased intestinal inflammation as determined by histological analysis of small and large intestine, cytokine gene expression, and levels of fecal lipocalin. In conclusion, 10-week inhalation exposures to UFPs induced taxonomic changes in the microbiome of various animal models in the absence of intestinal inflammation.

Hierarchical organization and assembly of the archaeal cell sheath from an amyloid-like protein.

Certain archaeal cells possess external proteinaceous sheath, whose structure and organization are both unknown. By cellular cryogenic electron tomography (cryoET), here we have determined sheath organization of the prototypical archaeon, Methanospirillum hungatei. Fitting of Alphafold-predicted model of the sheath protein (SH) monomer into the 7.9 Å-resolution structure reveals that the sheath cylinder consists of axially stacked ß-hoops, each of which is comprised of two to six 400 nm-diameter rings of ß-strand arches (ß-rings). With both similarities to and differences from amyloid cross-ß fibril architecture, each ß-ring contains two giant ß-sheets contributed by ~ 450 SH monomers that entirely encircle the outer circumference of the cell. Tomograms of immature cells suggest models of sheath biogenesis: oligomerization of SH monomers into ß-ring precursors after their membrane-proximal cytoplasmic synthesis, followed by translocation through the unplugged end of a dividing cell, and insertion of nascent ß-hoops into the immature sheath cylinder at the junction of two daughter cells.

Fecal and Tissue Microbiota Are Associated with Tumor T-Cell Infiltration and Mesenteric Lymph Node Involvement in Colorectal Cancer.

Colorectal cancer (CRC) is associated with alterations of the fecal and tissue-associated microbiome. Preclinical models support a pathogenic role of the microbiome in CRC, including in promoting metastasis and modulating antitumor immune responses. To investigate whether the microbiome is associated with lymph node metastasis and T cell infiltration in human CRC, we performed 16S rRNA gene sequencing of feces, tumor core, tumor surface, and healthy adjacent tissue collected from 34 CRC patients undergoing surgery (28 fecal samples and 39 tissue samples). Tissue microbiome profiles-including increased Fusobacterium-were significantly associated with mesenteric lymph node (MLN) involvement. Fecal microbes were also associated with MLN involvement and accurately classified CRC patients into those with or without MLN involvement. Tumor T cell infiltration was assessed by immunohistochemical staining of CD3 and CD8 in tumor tissue sections. Tumor core microbiota, including members of the Blautia and Faecalibacterium genera, were significantly associated with tumor T cell infiltration. Abundance of specific fecal microbes including a member of the Roseburia genus predicted high vs. low total and cytotoxic T cell infiltration in random forests classifiers. These findings support a link between the microbiome and antitumor immune responses that may influence prognosis of locally advanced CRC.

The Ocular Microbiome Is Altered by Sampling Modality and Age.

Background: Studies of the ocular microbiome have used a variety of sampling techniques, but no study has directly compared different sampling methods applied to the same eyes to one another or to a reference standard of corneal epithelial biopsy. We addressed this lack by comparing the microbiome from three conjunctival swabs with those of corneal epithelial biopsy. Methods: Twelve eyes (11 patients) were swabbed by calcium alginate swab, cotton-tipped applicator, and Weck-Cel cellulose sponge before a corneal epithelial biopsy (48 samples). We then performed 16S rRNA gene sequencing and universal 16S rRNA gene real-time polymerase chain reaction. Negative/blank controls were used to eliminate contaminants. An analysis was performed to examine the concordance of the three swab types to corneal epithelial biopsy. The effect of patient age on the ocular microbiome as determined by epithelial biopsy was also examined. Results: The ocular microbiome from corneal epithelial biopsies consisted of 31 genera with a relative abundance of 1% or more, including Weisella, Corynebacterium, and Pseudomonas. Of the three swab types, Weck-Cel differed the most from corneal biopsies based on beta-diversity analysis. Cotton swabs were unable to capture the Bacteroides population seen on epithelial biopsy. Therefore, calcium alginate swabs seemed to be the closest to epithelial biopsies. Older patients (≥65 years old) had higher alpha diversity (P < 0.05) than younger patients. Differential abundance testing showed that there were 18 genera that were differentially abundant between the two age groups, including Streptococcus and eight members of the Proteobacteria phylum. Conclusions: We demonstrate that ocular sampling method and patient age can greatly affect the outcome of sequencing-based analysis of the ocular microbiome. Translational Relevance: By understanding the impact of different sampling methods on the results obtained from the ocular surface microbiome, future research on the topic will be more reproducible, leading to a better understanding of ocular surface microbiome in health and disease.

The Intestinal Microbiome Predicts Weight Loss on a Calorie-Restricted Diet and Is Associated With Improved Hepatic Steatosis.

Background: The microbiome has been shown in pre-clinical and epidemiological studies to be important in both the development and treatment of obesity and metabolic associated fatty liver disease (MAFLD). However, few studies have examined the role of the microbiome in the clinical response to calorie restriction. To explore this area, we performed a prospective study examining the association of the intestinal microbiome with weight loss and change in hepatic steatosis on a calorie-restricted diet. Methods: A prospective dietary intervention study of 80 overweight and obese participants was performed at the Greater West Los Angeles Veterans Affair Hospital. Patients were placed on a macronutrient standardized diet for 16 weeks, including 14 weeks of calorie restriction (500 calorie deficit). Body composition analysis by impedance, plasma lipid measurements, and ultrasound elastography to measure hepatic steatosis were performed at baseline and week 16. Intestinal microbiome composition was assessed using 16S rRNA gene sequencing. A per protocol analysis was performed on all subjects completing the trial (n = 46). Results: Study completers showed significant reduction in weight, body mass index, total cholesterol, low density lipoprotein, and triglyceride. Subjects who lost at least 5% of their body weight had significantly greater reduction in serum triglyceride and hepatic steatosis than those with <5% body weight loss. Enterococcus and Klebsiella were reduced at the end of the trial while Coprococcus and Collinsella were increased. There were also significant baseline microbiome differences between patients who had at least 5% weight loss as compared to those that did not. Lachnoclostridium was positively associated with hepatic steatosis and Actinomyces was positively associated with hepatic steatosis and weight. Baseline microbiome profiles were able to predict which patients lost at least 5% of their body weight with an AUROC of 0.80. Conclusion: Calorie restriction alters the intestinal microbiome and improves hepatic steatosis in those who experience significant weight loss. Baseline microbiome differences predict weight loss on a calorie-restricted diet and are associated with improvement in hepatic steatosis, suggesting a role of the gut microbiome in mediating the clinical response to calorie restriction.

Gut microbiome profiles associated with steatosis severity in metabolic associated fatty liver disease.

Aim: The microbiome has been shown to be pivotal in the development of metabolic associated fatty liver disease (MAFLD). Few have examined the relationship of the microbiome specifically with steatosis grade. Therefore, our aim was to characterize the association of the microbiome with MAFLD steatosis severity while adjusting for metabolic comorbidities including diabetes. Methods: We enrolled patients with MAFLD at the West Los Angeles Veterans Affair Hospital. All patients underwent ultrasound elastography, fasting serum collection, and fecal sampling for 16S sequencing. We examined the associations of microbial diversity and composition with advanced steatosis, defined as a CAP score of ≥ 300 dB/m, with or without the presence of metabolic comorbidities. Results: Seventy-five patients were enrolled. African American were less likely to have advanced steatosis than either Hispanics or Whites (P = 0.001). Patients with more advanced steatosis had higher fasting serum triglyceride (192.6 ± 157.1 mg/dL vs. 122.5 ± 57.4 mg/dL), HbA1c (6.7% ± 1.4% vs. 6.1% ± 0.8%), transaminases, and were more likely to have metabolic syndrome (52.4% vs. 24.2%, P = 0.02). Advanced steatosis and diabetes were associated with altered microbial composition. Bacteroides was negatively associated with advanced steatosis while Megasphaera was positively associated with steatosis. Akkermansia was negatively associated with diabetes, while Anaerostipes and Parabacteroides were positively associated with diabetes. Conclusion: Diabetes and metabolic syndrome are associated with hepatic steatosis severity in MAFLD patients and both advanced steatosis and comorbid diabetes are independently associated with microbiome changes. These results provide insight into the role of the gut microbiome in MAFLD associated with metabolic syndrome.

A High Protein Calorie Restriction Diet Alters the Gut Microbiome in Obesity.

BACKGROUND: High protein calorie restriction diets have shown clinical efficacy for obesity, but the mechanisms are not fully known. The intestinal microbiome is a mediator of obesity and preclinical data support an effect of high protein diet (HPD) on the gut microbiome of obesity, but there are few studies in humans. METHODS: To address this, we conducted a dietary intervention trial of 80 overweight and obese subjects who were randomized to a calorie-restricted high protein diet (HPD) (30% calorie intake) or calorie-restricted normal protein diet (NPD) (15%) for 8 weeks. Baseline dietary intake patterns were assessed by the Diet History Questionnaire III. Longitudinal fecal sampling was performed at baseline, week 1, week 2, week 4, week 6, and week 8, for a total of 365 samples. Intestinal microbiome composition was assessed by 16S rRNA gene sequencing. RESULTS: At baseline, microbial composition was associated with fiber and protein intake. Subjects on the HPD showed a significant increase in microbial diversity as measured by the Shannon index compared to those on the NPD. The HPD was also associated with significant differences in microbial composition after treatment compared to the NPD. Both diets induced taxonomic shifts compared to baseline, including enrichment of Akkermansia spp. and Bifidobacterium spp. and depletion of Prevotella spp. Conclusion: These findings provide evidence that weight loss diets alter the gut microbiome in obesity and suggest differential effects of HPDs compared to NPDs which may influence the clinical response to HPD.