Differences In Microbial Composition Research Articles

Differences in the Oral Microbiome in Patients With Early Rheumatoid Arthritis and Individuals at Risk of Rheumatoid Arthritis Compared to Healthy Individuals.

ObjectiveIt has been suggested that rheumatoid arthritis (RA) may originate at the oral mucosa. The aim of the present study was to assess the oral microbiome and periodontal condition in patients with early RA and individuals at risk of developing RA compared to healthy controls.MethodsThree groups were recruited (n = 50 participants per group): 1) patients with early RA (meeting the American College of Rheumatology/European Alliance of Associations for Rheumatology 2010 classification criteria), 2) individuals at risk of developing RA (those with arthralgia who were positive for RA‐associated autoantibodies), and 3) healthy controls. A periodontal examination was conducted to assess the presence of bleeding on probing (BOP), pocket probing depth (PPD), and periodontal inflamed surface area (PISA). The microbial composition of subgingival dental plaque, saliva, and tongue coating was assessed using 16S ribosomal DNA amplicon sequencing, and findings were compared between groups with permutational multivariate analysis of variance (PERMANOVA).ResultsThere were no significant differences in any of the 3 periodontal variables between patients with early RA, at‐risk individuals, and healthy controls (P = 0.70 for BOP, P = 0.30 for PPD, and P = 0.57 for PISA, by Kruskal‐Wallis test). PERMANOVA analyses comparing microbial composition between the groups showed significant differences in the microbial composition of saliva (F = 2.08, P = 0.0002) and tongue coating (F = 2.04, P = 0.008), but not subgingival dental plaque (F = 0.948, P = 0.51). However, in post hoc tests, no significant differences in microbial composition of the saliva or tongue coating were observed between the early RA group and the at‐risk group (F = 1.12, P = 0.28 for saliva; F = 0.834, P = 0.59 for tongue coating). In assessing microbial diversity based on the number of zero‐radius operational taxonomic units per sample, Prevotella in the saliva and Veillonella in the saliva and tongue coating were each found at a higher relative abundance in samples from patients with early RA and at‐risk individuals compared to healthy controls.ConclusionThe results show similarities in the oral microbiome between patients with early RA and at‐risk individuals, since in both groups, the oral microbiome was characterized by an increased relative abundance of potentially proinflammatory species when compared to that in healthy controls. These findings suggest a possible association between the oral microbiome and the onset of RA.

Cytotoxic T-Cell Trafficking Chemokine Profiles Correlate With Defined Mucosal Microbial Communities in Colorectal Cancer.

The involvement of gut microbiota in T-cell trafficking into tumor tissue of colorectal cancer (CRC) remains to be further elucidated. The current study aimed to evaluate the expression of major cytotoxic T-cell trafficking chemokines (CTTCs) and chemokine-associated microbiota profiles in both tumor and adjacent normal tissues during CRC progression. We analyzed the expression of chemokine C-X-C motif ligands 9, 10, and 11 (CXCL9, CXCL10, and CXCL11), and C-C motif ligand 5 (CCL5), characterized gut mucosa-associated microbiota (MAM), and investigated their correlations in CRC patients. Our results showed that the expression of CXCL9, CXCL10, and CXCL11 was significantly higher in tumor than in adjacent normal tissues in 136 CRC patients. Notably, the high expression of CXCL9 in tumor tissues was associated with enhanced CD8+ T-cell infiltration and improved survival. Moreover, the MAM in tumor tissues showed reduction of microbial diversity and increase of oral bacteria. Microbial network analysis identified differences in microbial composition and structure between tumor and adjacent normal tissues. In addition, stronger associations between oral bacteria and other gut microbes were observed. Furthermore, the correlation analysis between the defined MAM and individual CTTCs showed that the CTTCs’ correlated operational taxonomic units (OTUs) in tumor and adjacent normal tissues rarely overlap with each other. Notably, all the enriched OTUs were positively correlated with the CTTCs in either tumor or adjacent normal tissues. Our findings demonstrated stronger interactions between oral bacteria and gut microbes, and a shifted correlation pattern between MAM and major CTTCs in tumor tissues, underlining possible mechanisms of gut microbiota–host interaction in CRC.

Characterization of the gut microbiome in wild rocky mountainsnails (Oreohelix strigosa)

BackgroundThe Rocky Mountainsnail (Oreohelix strigosa) is a terrestrial gastropod of ecological importance in the Rocky Mountains of western United States and Canada. Across the animal kingdom, including in gastropods, gut microbiomes have profound effects on the health of the host. Current knowledge regarding snail gut microbiomes, particularly throughout various life history stages, is limited. Understanding snail gut microbiome composition and dynamics can provide an initial step toward better conservation and management of this species.ResultsIn this study, we employed 16S rRNA gene amplicon sequencing to examine gut bacteria communities in wild-caught O. strigosa populations from the Front Range of Colorado. These included three treatment groups: (1) adult and (2) fetal snails, as well as (3) sub-populations of adult snails that were starved prior to ethanol fixation. Overall, O. strigosa harbors a high diversity of bacteria. We sequenced the V4 region of the 16S rRNA gene on an Illumina MiSeq and obtained 2,714,330 total reads. We identified a total of 7056 unique operational taxonomic units (OTUs) belonging to 36 phyla. The core gut microbiome of four unique OTUs accounts for roughly half of all sequencing reads returned and may aid the snails’ digestive processes. Significant differences in microbial composition, as well as richness, evenness, and Shannon Indices were found across the three treatment groups.ConclusionsComparisons of gut microbiomes in O. strigosa adult, fetal, and starved samples provide evidence that the host internal environments influence bacterial community compositions, and that bacteria may be transmitted vertically from parent to offspring. This work provides the first comprehensive report on the structure and membership of bacterial populations in the gastropod family Oreohelicidae and reveals similarities and differences across varying life history metrics. Strong differentiation between these life history metrics demonstrates the need for wider sampling for studies of dynamics of the snail gut microbiome.

Association between bacteria other than Helicobacter pylori and the risk of gastric cancer.

The gastric microbiota, including Helicobacter pylori (HP), has a remarkable role in gastric cancer (GC) occurrence. Evidence for the role of non-HP bacteria in GC risk is limited. We aimed to observe the association between bacteria other than HP and risk of GC in a Korean population. In this study, 268 GC cases and 288healthy controls were included. Demographic data and total energy intake data were collected using a general questionnaire and a semiquantitative food frequency questionnaire, respectively. 16S rRNA gene sequencing was performed using DNA extracted from gastric biopsy samples. Actinobacteria, Bacteroidetes, Firmicutes, Fusobacteria, and non-HP Proteobacteria were the five main phyla in the gastric environment. The five phyla were negatively related to the relative abundance of Helicobacter species (all p<0.001). The Shannon index, richness, and Pilou-evenness were negatively correlated with Helicobacter species (all p<0.001), while the microbial dysbiosis index was positively correlated with Helicobacter species (p<0.001). Participants with a higher relative abundance of Actinobacteria species showed a significantly increased risk of GC (OR: 3.16, 95% CI=1.92-5.19, p-trend<0.001). The non-HP microbiota composition among the four groups (HP+cases, HP- cases, HP+controls, and HP- controls) was significantly different (ANOSIM R=0.10, p=0.001). Other than HP, several bacterial species might be associated with GC risk. HP status and GC status could determine the differences in microbial compositions. Further large prospective studies are warranted to confirm our findings.

Abstract 1780: Associations between gut microbiota and PD-L1 immunotherapy/JAK1/2 inhibition in mouse Pten-deficient prostate cancer

Abstract The gut microbiome is now known to influence host immune function, malignancies, and response to therapy. We previously showed that sequencing PD-L1/JAK1/2 blockade prior to androgen deprivation therapy (ADT) could promote immune activity to potentiate antitumor responses in mouse Pten-deficient prostate cancer. Here, we investigate the associations between the treatment pairings of PD-L1 antibody (aPD-L1, clone D265A, mouse/IgG1 kappa) blockade and the JAK1/2 inhibitor AZD1480 with ADT in mouse Pten-deficient prostate cancer and fecal gut microbiomes. We used 16S rRNA amplicon sequencing to survey fecal samples of tumor bearing conditional Pten-knockout (KO) mice treated for four weeks with aPD-L1 and AZD14870 alone and as combination therapy in intact mice, and as concurrent (Conc) therapy with ADT (via surgical castration), or sequenced as adjuvant (Adj) or neoadjuvant (NeoAdj) therapy. In this model, PD-L1 blockade was ineffective as monotherapy in all treatment settings and as combination therapy in intact and Conc combination settings and hyperprogression was observed in some mice treated with aPD-L1 monotherapy in intact and Adj settings. In the NeoAdj setting, aPDL1/AZD1480 therapy demonstrated superiority over monotherapy. Significant differences in microbial composition were observed between groups (P&amp;lt;0.001), drugs (P&amp;lt;0.001), castration status (P&amp;lt;0.001) and treatment responses (P&amp;lt;0.001). AZD1480 as monotherapy or in combination with aPD-L1 was associated with the greatest changes in microbial composition followed by surgical castration. In the neoadjuvant setting Allobaculum, Lactobacillus, Sutturella, Turcibacter and Prevotella were associated with responders whereas Hellicobacter, Oscillospora, and Ruminococcus gnavus were associated with hyperprogression. Functionally, enrichments in fatty acid biosynthesis/metabolism, tetracycline biosynthesis, phenylalanine, tyrosine and tryptophan biosynthesis, and glycolysis/gluconeogenesis were revealed in responders whereas lipopolysaccharide biosynthesis, glycosaminoglycan degradation, fructose and mannose metabolism, histidine metabolism, glyoxylate and dicarboxylate metabolism, and the citrate cycle (TCA) were enriched in low responders. This study provides insight into the complex interactions between gut microbiota and cancer-burdened hosts, and reveals associations between gut microbial composition and treatment responses to androgen deprivation, immune modulation via JAK1/2 inhibition and PD-L1 blockade in a mouse model of Pten-deficient prostate cancer. Citation Format: Marco A. De Velasco, Kazuko Sakai, Yurie Kura, Naomi Ando, Noriko Sako, Kazutoshi Fujita, Masahiro Nozawa, Kazuhiro Yoshimura, Kazuto Nishio, Hirotsugu Uemura. Associations between gut microbiota and PD-L1 immunotherapy/JAK1/2 inhibition in mouse Pten-deficient prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1780.

Genomic adaptations enabling Acidithiobacillus distribution across wide-ranging hot spring temperatures and pHs

BackgroundTerrestrial hot spring settings span a broad spectrum of physicochemistries. Physicochemical parameters, such as pH and temperature, are key factors influencing differences in microbial composition across diverse geothermal areas. Nonetheless, analysis of hot spring pools from the Taupo Volcanic Zone (TVZ), New Zealand, revealed that some members of the bacterial genus, Acidithiobacillus, are prevalent across wide ranges of hot spring pHs and temperatures. To determine the genomic attributes of Acidithiobacillus that inhabit such diverse conditions, we assembled the genomes of 19 uncultivated hot spring Acidithiobacillus strains from six geothermal areas and compared these to 37 publicly available Acidithiobacillus genomes from various habitats.ResultsAnalysis of 16S rRNA gene amplicons from 138 samples revealed that Acidithiobacillus comprised on average 11.4 ± 16.8% of hot spring prokaryotic communities, with three Acidithiobacillus amplicon sequence variants (ASVs) (TVZ_G1, TVZ_G2, TVZ_G3) accounting for > 90% of Acidithiobacillus in terms of relative abundance, and occurring in 126 out of 138 samples across wide ranges of temperature (17.5–92.9 °C) and pH (1.0–7.5). We recovered 19 environmental genomes belonging to each of these three ASVs, as well as a fourth related group (TVZ_G4). Based on genome average nucleotide identities, the four groups (TVZ_G1-TVZ_G4) constitute distinct species (ANI < 96.5%) of which three are novel Acidithiobacillus species (TVZ_G2-TVZ_G4) and one belongs to Acidithiobacillus caldus (TVZ_G1). All four TVZ Acidithiobacillus groups were found in hot springs with temperatures above the previously known limit for the genus (up to 40 °C higher), likely due to significantly higher proline and GC contents than other Acidithiobacillus species, which are known to increase thermostability. Results also indicate hot spring-associated Acidithiobacillus have undergone genome streamlining, likely due to thermal adaptation. Moreover, our data suggest that Acidithiobacillus prevalence across varied hot spring pHs is supported by distinct strategies, whereby TVZ_G2-TVZ_G4 regulate pH homeostasis mostly through Na+/H+ antiporters and proton-efflux ATPases, whereas TVZ_G1 mainly relies on amino acid decarboxylases.ConclusionsThis study provides insights into the distribution of Acidithiobacillus species across diverse hot spring physichochemistries and determines genomic features and adaptations that potentially enable Acidithiobacillus species to colonize a broad range of temperatures and pHs in geothermal environments.BoTSrZ5f8ypScVzkmXt8zFVideo

Characterizing the Effects of Calcium and Prebiotic Fiber on Human Gut Microbiota Composition and Function Using a Randomized Crossover Design-A Feasibility Study.

Consumption of prebiotic inulin has been found to increase calcium absorption, which may protect against gut diseases such as colorectal cancer. This dietary relation may be modulated by compositional changes in the gut microbiota; however, no human study has addressed this hypothesis. We determined the feasibility of a randomized crossover trial to evaluate the effect of three interventions (combined calcium and inulin supplementation, calcium supplementation alone, and inulin supplementation alone) on the intestinal microbiota composition and function. We conducted a 16-week pilot study in 12 healthy adults who consumed the three interventions in a random sequence. Participants provided fecal and blood samples before and after each intervention. Each intervention period lasted four weeks and was flanked by one-week washout periods. 16S ribosomal RNA sequencing and quantification of short chain fatty acids (SCFA) was determined in fecal samples. Systemic lipopolysaccharide binding protein (LBP) was quantified in serum. Of the 12 individuals assigned to an intervention sequence, seven completed the study. Reasons for dropout included time (n = 3), gastrointestinal discomfort (n = 1), and moving (n = 1). Overall, participants reported positive attitudes towards the protocol (n = 9) but were unsatisfied by the practicalities of supplement consumption (44%) and experienced digestive discomfort (56%). We found no appreciable differences in microbial composition, SCFA concentration, nor LBP concentrations when comparing intervention periods. In conclusion, an intervention study using a randomized crossover design with calcium and a prebiotic fiber is feasible. Improvements of our study design include using a lower dose prebiotic fiber supplement and a larger sample size.

MO137DIFFERENCES IN GUT MICROBIOTA PROFILES AND FUNCTIONS BETWEEN END-STAGE KIDNEY DISEASE AND HEALTHY POPULATIONS

Abstract Background and Aims Patients with end-stage kidney disease (ESKD) are characterized by altered gut microbiota, impaired intestinal barrier function, and experienced gut microbiota-derived metabolites related to systemic complications. However, limited studies evaluated the microbial diversity and function in ESKD patients previously. Method Compared to age- and gender-matched subjects without kidney disease, 82 ESKD patients in the discovery cohort and 58 ESKD patients in the validation cohort were investigated for the microbial richness, biodiversity, gut dysbiosis, microbial composition differences, and the functional changes by gut metabolic module analysis. Bacterial derived free form protein-bound uremic toxins were analyzed by mass spectrometry and their association with microbial richness in ESKD patients was determined. Results Compared to controls, an increased α-diversity and distinct β-diversity were found in ESKD (Figure). The increase in α-diversity was correlated with protein-bound uremic toxins, particularly hippuric acid. A higher microbial dysbiosis index (MDI) was found in ESKD patients with the following enriched genera: Facealibacterium, Ruminococcus, Fusobacterium, Dorea, Anaerovorax, Sarcina, Akkermansia, Streptococcus, and Dysgonomonas. MDI at the genus level successfully differentiated between ESKD and controls in the discovery cohort (area under the curve [AUC] of 81.9%) and the validation cohort (AUC of 83.2%). Regarding functional enrichment analysis with gut metabolic modules, ESKD subjects presented with gut microbial function of increased saccharide and amino acid metabolism compared with matched controls. Conclusion An enriched but dysbiotic gut microbiota was presented in ESKD patients, in which the bacteria that were present increase amino acid metabolism linked to the production of protein-bound uremic toxins.

Characterisation of the bacterial microbiota of a landfill-contaminated confined aquifer undergoing intrinsic remediation

Literature on microbiomes of landfill leachate-contaminated aquifers is scarce despite groundwater contaminations from landfills being common globally. In this study, a combination of microbiological techniques was applied to groundwater samples from an aquifer contaminated by a municipal landfill and undergoing intrinsic remediation. Groundwater samples were obtained from three multilevel sampling wells placed along the groundwater flow path in the contaminated aquifer, and additionally from a background well located in a nearby uncontaminated aquifer. The samples were subjected to chemical analysis, microbial culturing and characterisation, cell counting by fluorescence microscopy, and 16S rRNA metabarcoding. Good concordance was realised with the results from the different microbiological techniques. Samples from the uncontaminated aquifer had both lower cell density and lower microbial diversity compared to samples from the contaminated aquifer. Among the wells located in the contaminated aquifer, microbial diversity increased between the well closest to the landfill and the intermediate well but was lower at the most distant well. The majority of the cultured microbes represent taxa frequently recovered from contaminated environments, with 47% belonging to taxa with previously documented bioremediation potential. Multivariate redundancy analysis showed that the microbial composition was most similar in wells located closer to the landfill, although beta diversity analysis indicated a significant difference in microbial composition across the wells. Taken together with the results of cell counting, culture, and metabarcoding, these findings illustrate the effect of landfill leachates on microbial communities.

Temporal differences in microbial composition of Époisses cheese rinds during ripening and storage

Époisses is a protected designation of origin smear-ripened cheese from the Burgundy region in France. It has an orange color and a strong flavor, both of which are generated by surface microorganisms. The objective of the present study was to investigate the microbial dynamics at the surface of Époisses cheese during ripening and postmanufacturing storage at low temperatures. Rind samples were analyzed by enumeration on agar plates and by 16S rRNA gene and internal transcribed spacer amplicon sequencing. During most of the ripening process, the counts of yeasts, which corresponded to the species Debaryomyces hansenii and Geotrichum candidum, were higher than those of the aerobic acid-sensitive bacteria. Debaryomyces hansenii reached a level of about 3 × 108 cfu/cm2, and its viability strongly decreased in the late stage of ripening and during storage at 4°C. Two of the inoculated bacterial species, Brevibacterium aurantiacum and Staphylococcus xylosus, did not establish themselves at the cheese surface. At the end of ripening, among the 18 most abundant bacterial species detected by amplicon sequencing, 14 were gram-negative, mainly from genera Psychrobacter, Vibrio, Halomonas, and Mesonia. It was hypothesized that the high moisture level of the Époisses rinds, due the humid atmosphere of the ripening rooms and to the frequent washings of the curds, favored growth of these gram-negative species. These species may be of interest for the development of efficient ripening cultures. In addition, because the orange color of Époisses cheeses could not be attributed to the growth of Brevibacterium, it would be interesting to investigate the type and origin of the pigments that confer color to this cheese.

Microbial and Antimicrobial Resistance Profiles of Microbiota in Common Carps (Cyprinus carpio) from Aquacultured and Wild Fish Populations.

Simple SummaryThis study was focused on differences in microbial varieties in common carp living in two different environments: open fish ponds and in nature. The results demonstrated that wild fish carry more than 2.5 times the bacterial species in their gut compared with aquacultured fish. More than 400 species of bacteria were identified, the majority of which are considered beneficial microbiota. Besides bacterial variety, it was determined that aquacultured fish harbored more bacteria that are treated as pathogens in animals and humans. The frequency of antimicrobial resistance in bacterial indicators was more common in aquacultured fish compared with bacteria from a wild population, therefore fish farming can be treated as a potential source of environmental contamination with antimicrobial resistant bacteria.In this study we analyzed differences in microbial composition and antimicrobial resistance profiles in common carp living in two different environments: fish ponds, where carp have been kept under the same growing conditions over the last 50 years, and from the wild. The results demonstrated that wild fish carry a great variety of bacterial species (448 species with a prevalence of at least 0.01% from the total number of reads). Aquacultured individuals harbored 2.56 times fewer species in their gut. Significant microbial differences were observed in all taxonomic ranks, including bacterial classes and phyla. Besides bacterial variety, it was determined that aquacultured fish harbored more bacteria that are considered pathogens or opportunistic pathogens, such as Moraxellaceae, Flavobacteriaceae, and Staphylococcaceae. The frequency of antimicrobial resistance in bacterial indicators was more common in aquacultured fish than in wild fish, therefore fish farming may be a potential source of environmental contamination with antimicrobial resistant bacteria.

Mucosa\u2010associated cultivable aerobic gut bacterial microbiota among colorectal cancer patients attending at the referral hospitals of Amhara Regional State, Ethiopia

BackgroundColorectal cancer (CRC) is one of the top ten causes of cancer deaths in the world. Despite an increased prevalence of colorectal cancer has been documented from developing countries, there is no any report regarding gut microbiota among colorectal cancer patients in Ethiopia. Therefore, the current study evaluated cultivable aerobic gut bacterial distributions among malignant and its adjacent normal biopsies of CRC patients.MethodsCRC patients who were under colorectal cancer resection surgery during April 2017 to February 2018 at Felege Hiwot Referral and University of Gondar Teaching Hospitals enrolled in the study. Biopsy specimens were taken from malignant and its adjacent normal-appearing tissues. Bacterial cultivation, quantification and characterization of saline washed biopsies were performed under aerobic and candle jar conditions. Differences in bacterial microbiota compositions between malignant and normal tissue biopsies were evaluated and analyzed using Microsoft excel 2010 and GraphPad Prism5 statistical software.Results Fifteen CRC patients were participated with a mean age of 53.8 ± 10.8 years old and majorities (73.3 %) of patients were in between the age groups of 40 and 60 years old. The mean ± SD bacterial microbiota of malignant biopsies (3.2 × 105 ± 1.6 × 105 CFU/ml) was significantly fewer than that of adjacent normal tissue biopsies (4.0 × 105 ± 2.2 × 105 CFU/ml). This dysbacteriosis is positively correlated with the occurrence of CRC (p = 0.019). Proteobacteria (55.6 %), Firmicutes (33.3 %) and Fusobacteria (11.1 %) were the most frequently isolated phyla from non-malignant biopsies while only Proteobacteria (58.8 %) and Firmicutes (41.2 %) were from malignant ones. Family level differences were observed among phyla (Firmicutes and Proteobacteria) isolated from the study participants. For instance, the relative abundance of family Bacillaceae from malignant (26 %) was lower than the normal biopsies (39 %). On other hand, family Enterobacteriaceae was twice more abundant in malignant tissues (45 %) than in its matched normal tissues (23 %). Furthermore, the family Enterococcaceae (14 %) of phylum Firmicutes was solely isolated from malignant tissue biopsies.ConclusionsThe overall microbial composition of normal and malignant tissues was considerably different among the study participants. Further culture independent analysis of mucosal microbiota will provide detail pictures of microbial composition differences and pathogenesis of CRC in Ethiopian settings.

Biocultural Drivers of Salivary Microbiota in Australian Aboriginal and Torres Strait Islander Children.

Australian Aboriginal and Torres Strait Islander children experience unacceptably high rates of dental caries compared to their non-Indigenous Australian counterparts. Dental caries significantly impacts the quality of life of children and their families, particularly in remote communities. While many socioeconomic and lifestyle factors impact caries risk, the central role of the oral microbiota in mediating dental caries has not been extensively investigated in these communities. Here, we examine factors that shape diversity and composition of the salivary microbiota in Aboriginal and Torres Strait Islander children and adolescents living in the remote Northern Peninsula Area (NPA) of Far North Queensland. We employed 16S ribosomal RNA amplicon sequencing to profile bacteria present in saliva collected from 205 individuals aged 4–17 years from the NPA. Higher average microbial diversity was generally linked to increased age and salivary pH, less frequent toothbrushing, and proxies for lower socioeconomic status (SES). Differences in microbial composition were significantly related to age, salivary pH, SES proxies, and active dental caries. Notably, a feature classified as Streptococcus sobrinus increased in abundance in children who reported less frequent tooth brushing. A specific Veillonella feature was associated with caries presence, while features classified as Actinobacillus/Haemophilus and Leptotrichia were associated with absence of caries; a Lactobacillus gasseri feature increased in abundance in severe caries. Finally, we statistically assessed the interplay between dental caries and caries risk factors in shaping the oral microbiota. These data provide a detailed understanding of biological, behavioral, and socioeconomic factors that shape the oral microbiota and may underpin caries development in this group. This information can be used in the future to improve tailored caries prevention and management options for Australian Aboriginal and Torres Strait Islander children and communities.

Microbiome Markers of Pancreatic Cancer Based on Bacteria-Derived Extracellular Vesicles Acquired from Blood Samples: A Retrospective Propensity Score Matching Analysis.

Simple SummaryAlthough tremendous advances in diagnosis and treatment, pancreatic cancer still remains one of the lethal diseases with an overall survival rate of 10~15%. Early detection and diagnosis of pancreatic cancer is very important in improving the prognosis of patients. The aim of our study was to find new biomarkers, using microbiomes based on bacteria-derived extracellular vesicles, extracted from blood serum. With 38 patients with pancreatic cancer and 52 healthy controls with no history of pancreatic disease, we identified several compositional differences of microbiome between them. Using various combinations of the metagenomic markers which made the compositional differences, we also built a pancreatic cancer prediction model with high area under the receiver operating characteristic curve (0.966 at the phylum level and 1.000 at the genus level). These microbiome markers, based on bacteria-derived extracellular vesicles acquired from blood, show demonstrate the potential of candidate biomarkers for early diagnosis of pancreatic cancer.Novel biomarkers for early diagnosis of pancreatic cancer (PC) are necessary to improve prognosis. We aimed to discover candidate biomarkers by identifying compositional differences of microbiome between patients with PC (n = 38) and healthy controls (n = 52), using microbial extracellular vesicles (EVs) acquired from blood samples. Composition analysis was performed using 16S rRNA gene analysis and bacteria-derived EVs. Statistically significant differences in microbial compositions were used to construct PC prediction models after propensity score matching analysis to reduce other possible biases. Between-group differences in microbial compositions were identified at the phylum and genus levels. At the phylum level, three species (Verrucomicrobia, Deferribacteres, and Bacteroidetes) were more abundant and one species (Actinobacteria) was less abundant in PC patients. At the genus level, four species (Stenotrophomonas, Sphingomonas, Propionibacterium, and Corynebacterium) were less abundant and six species (Ruminococcaceae UCG-014, Lachnospiraceae NK4A136 group, Akkermansia, Turicibacter, Ruminiclostridium, and Lachnospiraceae UCG-001) were more abundant in PC patients. Using the best combination of these microbiome markers, we constructed a PC prediction model that yielded a high area under the receiver operating characteristic curve (0.966 and 1.000, at the phylum and genus level, respectively). These microbiome markers, which altered microbial compositions, are therefore candidate biomarkers for early diagnosis of PC.

Differences in the Microbial Composition of Hemodialysis Patients Treated with and without β-Blockers

β-blockers are commonly prescribed to treat cardiovascular disease in hemodialysis patients. Beyond the pharmacological effects, β-blockers have potential impacts on gut microbiota, but no study has investigated the effect in hemodialysis patients. Hence, we aim to investigate the gut microbiota composition difference between β-blocker users and nonusers in hemodialysis patients. Fecal samples collected from hemodialysis patients (83 β-blocker users and 110 nonusers) were determined by 16S ribosomal RNA amplification sequencing. Propensity score (PS) matching was performed to control confounders. The microbial composition differences were analyzed by the linear discriminant analysis effect size, random forest, and zero-inflated Gaussian fit model. The α-diversity (Simpson index) was greater in β-blocker users with a distinct β-diversity (Bray–Curtis Index) compared to nonusers in both full and PS-matched cohorts. There was a significant enrichment in the genus Flavonifractor in β-blocker users compared to nonusers in full and PS-matched cohorts. A similar finding was demonstrated in random forest analysis. In conclusion, hemodialysis patients using β-blockers had a different gut microbiota composition compared to nonusers. In particular, the Flavonifractor genus was increased with β-blocker treatment. Our findings highlight the impact of β-blockers on the gut microbiota in hemodialysis patients.

Extracellular vesicle-derived microbiome obtained from exhaled breath condensate in patients with asthma

The bronchial microbiome of patients with asthma differs from that of the healthy controls. Metagenomic analysis has been conducted using 16S recombinant DNA sequencing from extracellular vesicles (EVs) to identify microbiomes and provide culture-independent estimation of microbial diversity.1Lee J.H. Choi J.P. Yang J. et al.Metagenome analysis using serum extracellular vesicles identified distinct microbiota in asthmatics.Sci Rep. 2020; 10: 15125Crossref PubMed Scopus (5) Google Scholar Despite the construction of the metagenome of the asthmatic lung, limitations persist in sampling the bronchial airway. Exhaled breath condensate (EBC) contains aerosol and volatile compounds that can be analyzed to noninvasively understand the physiological and pathologic processes in the lung.2Hunt J. Exhaled breath condensate: an evolving tool for noninvasive evaluation of lung disease.J Allergy Clin Immunol. 2002; 110: 28-34Abstract Full Text Full Text PDF PubMed Scopus (270) Google Scholar This study performed metagenomic analysis using EBC-derived EVs to determine the characteristics of the microbiome in patients with asthma compared with those in healthy controls. Moreover, we suggested a diagnostic tool for asthma using artificial intelligence (AI) modeling based on the results of the microbiota composition in patients with asthma. The EBC was obtained from 58 healthy controls and 251 individuals with asthma at the Asan Medical Center between September 2014 and December 2019. Healthy controls were screened for respiratory diseases and recruited during regular wellness examinations. The eligibility criteria for patients with asthma were as follows: (1) patients older than 18 years; (2) symptoms such as dyspnea, wheezing, or cough for more than 3 months; and (3) airway hyperresponsiveness on a provocation test or airway reversibility after inhalation of a short-acting beta-agonist. Patients with severe lung damage, bronchiectasis, or a history of lung resection were excluded. Informed consent was obtained from all participants, and the study protocol was approved by the Institutional Review Board of Asan Medical Center (IRB No. 2006-0388). The EBC samples were collected using RTube (Respiratory Research, Austin, Texas). EVs were isolated from the EBC and analyzed. The extracted 16S recombinant DNA was subjected to next-generation sequencing as described previously.3Yang J. McDowell A. Kim E.K. et al.Consumption of a Leuconostoc holzapfelii-enriched synbiotic beverage alters the composition of the microbiota and microbial extracellular vesicles.Exp Mol Med. 2019; 51: 1-11Crossref Scopus (19) Google Scholar Taxonomic profiling was conducted for all samples at the genus level.4Yang J. Moon H.E. Park H.W. et al.Brain tumor diagnostic model and dietary effect based on extracellular vesicle microbiome data in serum.Exp Mol Med. 2020; 52: 1602-1613Crossref PubMed Scopus (3) Google Scholar Two algorithms of AI modeling including artificial neural network (ANN) and gradient boosting (GBM) were applied to selective EBC biomarkers.5Abadi M, Agarwal A, Barham P, et al. Tensorflow: large-scale machine learning on heterogeneous distributed systems. arXiv preprint arXiv:1603.04467. Available at: https://arxiv.org/abs/1603.04467. Accessed March 16, 2016.Google Scholar,6Pedregosa F. Varoquaux G. Gramfort A. et al.Scikit-learn: machine learning in Python.J Mach Learn Res. 2011; 12: 2825-2830Google Scholar The data were split into testing and training sets 10 times before training to validate the performance of the models. Alpha diversity was ascertained using the phyloseq R package to calculate the observed species richness and Chao1 for the estimated species richness and the Shannon and Simpson indices for species evenness and richness with the rarefaction set at 1091. Beta diversity testing was performed using principal coordinate analysis for multidimensional scaling of the EBC samples. In addition, t tests were performed to evaluate the statistical difference between the control and asthma groups, in which P < .05 was considered statistically significant. The asthma group had significantly higher alpha diversity (P < .05) for all 4 measurements (Fig 1). The observed operational taxonomic units and Chao1 estimates revealed greater species richness in the asthma EBC samples. The Shannon and Simpson diversity indices both revealed higher alpha diversity measures in the individuals with asthma than those in the healthy controls. In the plot of principal coordinates analysis (based on Bray-Curtis distance of all samples of control and patients with asthma), 2 groups were clustered separately even though there were several patients with asthma in the same cluster of the control group. There was no difference in the airway microbiota related to airway inflammation according to the proportions of induced sputum eosinophils and neutrophils, severity and duration of asthma, obesity, smoking status, or use of inhaled corticosteroids. At the genus level, Sphingomonas, Akkermansia, Methylophaga, Acidocella, and Marinobacter were significantly more abundant in patients with asthma (P < .05). Based on the result of the microbiome-based differences between patients with asthma and controls, the diagnostic AI model for asthma using GBM and ANN revealed good performance with respective areas under the curve of 0.832 and 0.769. Firmicutes and Proteobacteria at the phylum level were common important features between the GBM and ANN asthma models. The change in microorganisms in the respiratory tract has been found to play an important role in mediating the pathogenesis of asthma.7Shukla S.D. Shastri M.D. Chong W.C. et al.Microbiome-focused asthma management strategies.Curr Opin Pharmacol. 2019; 46: 143-149Crossref PubMed Scopus (5) Google Scholar Our study identified bacterial compositional differences between patients with asthma and healthy controls using EBC-derived EVs, which is consistent with previous studies using induced sputum and bronchial washing.8Marri P.R. Stern D.A. Wright A.L. Billheimer D. Martinez F.D. Asthma-associated differences in microbial composition of induced sputum.J Allergy Clin Immunol. 2013; 131 (346-352.e1-3)Abstract Full Text Full Text PDF PubMed Scopus (243) Google Scholar,9Huang Y.J. Nelson C.E. Brodie E.L. et al.Airway microbiota and bronchial hyperresponsiveness in patients with suboptimally controlled asthma.J Allergy Clin Immunol. 2011; 127 (372-381.e1-3)Abstract Full Text Full Text PDF Scopus (465) Google Scholar Furthermore, EBC is a simple and less invasive method for obtaining samples from the lung. This sample collection allows for more readily available analysis of the lung microbiome. Our model using AI techniques revealed that Firmicutes and Proteobacteria were common important features of asthma at the phylum level. It also revealed the best performance for differentiating patients with asthma from healthy controls. However, this technique is more complex and costly compared than the usual criteria for diagnosing asthma. Therefore, this method may have limited helpfulness when conventional methods, such as spirometry and the bronchial provocation test, are not available for diagnosing asthma. The ability of this tool should be further verified to differentiate asthma from chronic obstructive pulmonary disease and nonasthmatic bronchitis. Despite these challenges, modulating the lung microbiome in patients with asthma has the capacity to act as a new treatment strategy.7Shukla S.D. Shastri M.D. Chong W.C. et al.Microbiome-focused asthma management strategies.Curr Opin Pharmacol. 2019; 46: 143-149Crossref PubMed Scopus (5) Google Scholar Our model may be used as an indicator of screening subjects with the potential of developing asthma because dysbiosis of the microbiome early in life is related to the development of asthma later in life. Several studies have mentioned the potential role of the microbiome in shaping phenotypes, endotypes, and disease severity of asthma with respect to patient-specific therapy.10Loverdos K. Bellos G. Kokolatou L. et al.Lung microbiome in asthma: current perspectives.J Clin Med. 2019; 8: 1967Crossref Scopus (17) Google Scholar However, our further subgroup analyses did not reveal significant differences according to neutrophil airway inflammation, severity and duration of asthma, or use of inhaled corticosteroids. This may be due to the small sample size with heterogeneous clinical characteristics. Providing the clinical use of microbiome-based diagnosis and management may require a longitudinal prospective study of sufficient size. Our study was limited in that dietary patterns, use of antibiotics, and recent lower respiratory infections were not evaluated as confounding factors. In addition, we did not present the specific mechanisms or functional activity underlying microbial influences on immunomodulatory effects. In conclusion, we have revealed differences between the lung microbiome of individuals with asthma and controls by analyzing EVs derived from EBC. We also proposed an asthma diagnostic model using AI. Although the clinical application of microbiota-targeting management is controversial, our findings may support a microbiome-based approach for diagnosing and managing asthma.

A51 ENTERIC PARASITE INFECTION-INDUCED ALTERATION OF THE GUT MICROBIOTA REGULATES INTESTINAL GOBLET CELL BIOLOGY AND MUCIN PRODUCTION VIA TLR2 SIGNALING

Abstract Background Goblet cells (GCs) are the major source of mucin which are the main components of the mucus layer that represents the front line of innate defense in the gastrointestinal (GI) tract. Hyperplasia of GCs and increased mucin production are observed in many enteric nematode infections such as Trichuris muris infection. Increased mucin production contributes to parasite clearance by trapping in mucus and inhibiting motility. The GI tract contains trillions of commensal microbes, and these microbes control mucin production from GCs by activating different signaling cascades. During nematode parasite infection due to the coexistence of parasites and microbiota in close proximity of GCs in gut, it is likely that this nematode-microbiota interaction plays an important role in mucin production. Toll-like receptors (TLRs), components of the innate immune system, sense gut microbiota stimuli. The human GC-like cell line, LS174T, expresses TLR2 mRNA which was enhanced by stimulation with synthetic TLR2 ligands. We hypothesize T. muris-induced altered microbiota modulates GC response and mucin production via TLR2 signaling. Aims To elucidate the role of T. muris-induced altered gut microbiota in the regulation of intestinal GC response and mucin production via host TLR2 signaling. Methods C57BL/6 mice were infected by gavage with ~300 T. muris eggs and infectivity was confirmed by worm burden. Microbiota was analyzed by 16s rRNA sequencing. Colonic GCs response, mucins and TLR2 expression and cytokines production were assessed in germ-free (GF) mice receiving non-infected and T. muris-infected microbiota (collected on day 36 post-infection to exclude worms). Muc2 and Muc5ac expression were assessed in wild-type (WT) and TLR2 deficient (TLR2-/-) mice transplanted with T. muris-infected microbiota following antibiotic treatment. Results We observed a difference in microbial composition between non-infected and T. muris infected mice. Transfer of T. muris-infected microbiota into GF mice significantly increased GC numbers and TLR2 expression as well as up-regulated Muc2 and Muc5ac expression and IL-4, IL-13 production compared to GF mice with non-infected microbiota. Antibiotic-treated TLR2-/- mice after receiving microbiota from T. muris-infected mice showed significantly decreased expression of Muc2 and Muc5ac compared to antibiotic-treated WT mice receiving the same microbiota. Conclusions T. muris-induced altered microbiota influences intestinal GC response and mucin production via TLR2. In addition to enhancing our understanding on the interaction of parasite with resident microbiota in host defense, this study provides new information on TLR2 based innate signaling in the regulation of GC biology and mucin production. Funding Agencies NSERC

Alterations of Gastric Microbiota in Gastric Cancer and Precancerous Stages.

ObjectiveMicrobial infections have been shown to contribute to gastric carcinogenesis, the knowledge of gastric microbiota alteration in this process may provide help in early diagnosis of gastric cancer. The aim of this study was to characterize the microbial changes and identify taxonomic biomarkers across stages of gastric carcinogenesis.MethodsThe gastric microbiota was investigated by 16S rRNA gene analysis in gastric mucosal specimens from 47 patients including superficial gastritis (SG), atrophic gastritis (AG), gastric intraepithelial neoplasia (GIN), and gastric cancer (GC). Differences in microbial composition across the disease stages, especially in GIN and GC were assessed using linear discriminant analysis effect size.ResultsThere was no gradual changing trend in the richness or diversity of the gastric microbiota across stages of gastric carcinogenesis. The relative abundance of dominant taxa at phylum and genus levels didn’t show a gradual shift pattern, and the only four taxa that continuously enriched from SG to GC were Slackia, Selenomonas, Bergeyella, and Capnocytophaga, all of which were oral bacteria. The most representative taxa which were enriched in GC patients were oral bacteria including Parvimonas, Eikenella and Prevotella-2, and environmental bacteria including Kroppenstedtia, Lentibacillus, and Oceanobacillus. The gastric microbiota in GIN patients were characterized by enrichment of intestinal commensals including Romboutsia, Fusicatenibacter, Prevotellaceae-Ga6A1-group, and Intestinimonas. Gastric cardia cancer and non-cardia cancer patients had significantly different microbiota profiles characterized by a higher abundance of Helicobacter in the cardia cancer patients.ConclusionsOur results provide insights on potential taxonomic biomarkers for gastric cancer and precancerous stages, and suggest that gastric microbiota might play different roles in the carcinogenesis of cardia cancer and non-cardia cancer.

Effects of Xylo-Oligosaccharides on Growth and Gut Microbiota as Potential Replacements for Antibiotic in Weaning Piglets.

Xylo-oligosaccharides (XOS) is a well-known kind of oligosaccharide and extensively applied as a prebiotic. The objective of this study was to investigate the effect of XOS supplementation substituting chlortetracycline (CTC) on growth, gut morphology, gut microbiota, and hindgut short chain fatty acid (SCFA) contents of weaning piglets. A total of 180 weaned piglets were randomly allocated to three treatments for 28 days, as follows: control group (basal diet, CON), basal diet with 500 mg/kg (XOS500) XOS, and positive control (basal diet with 100 mg/kg CTC). Compared with the CON group, the piglets in the XOS500 group improved body weight (BW) on days 28, average daily gain (ADG) and reduced feed: gain ratio during days 1–28 (P < 0.05). The XOS500 supplementation increased Villus height and Villus height: Crypt depth ratio in the ileum (P < 0.05). Villus Height: Crypt Depth of the ileum was also increased in the CTC treatment group (P < 0.05). Meanwhile, the XOS500 supplementation increased significantly the numbers of goblet cells in the crypt of the cecum. High-throughput 16S rRNA gene sequencing revealed distinct differences in microbial compositions between the ileum and cecum. XOS500 supplementation significantly increased the bacterial diversity. However, CTC treatment markedly reduced the microbial diversity (P < 0.05). Meanwhile, XOS500 supplementation in the diet significantly increased the abundance of Lactobacillus genus compared to the CON and CTC group in the ileum and cecum (P < 0.01), whereas the level of Clostridium_sensu_stricto_1, Escherichia-Shigella, and Terrisporobacter genus in the XOS500 group were markedly lower than the CON and CTC group (P < 0.05). In addition, dietary supplementation with XOS500 significantly increased the total short-chain fatty acids, propionate and butyrate concentrations and decreased the acetate concentration compared to the CON group in the cecum (P < 0.05). In summary, dietary supplemented with XOS500 could enhance specific beneficial microbiota abundance and decrease harmful microbiota abundance to maintain the structure of the intestinal morphology and improve growth performance of weaned piglets. Thus, XOS may potentially function as an alternative to in-feed antibiotics in weaned piglets in modern husbandry.

Clinical Study of Correlation for the Intestinal and Pharyngeal Microbiota in the Premature Neonates.

Objective: There are mutual influences between intestine and lung, that propose a concept of the gut-lung axis, but the mechanism is still unclear. Microbial colonization in early life plays an important role in regulating intestinal and lung function. In order to explore the characteristics of early microbiota on the gut-lung axis, we studied the correlation between intestinal and pharyngeal microbiota on day 1 and day 28 after birth in premature neonates.Methods: Thirteen neonates born at 26–32 weeks gestational age (GA) hospitalized at the neonatal intensive care unit (NICU) of the West China Second Hospital of Sichuan University were enrolled in this study. Stool samples and pharyngeal swabs samples were collected from each neonate on the first day (T1) and the 28th day (T28) after birth. Total bacterial DNA was extracted and sequenced using the Illumina MiSeq Sequencing System based on the V3–V4 hyper-variable regions of the 16S rRNA gene. Based on the sequencing results, the composition of the intestinal and pharyngeal microbiota was compared and analyzed.Results: At T1, the difference in microbial composition between intestine and pharynx was not statistically significant. The intestinal microbiota was mainly composed of Unidentified Enterobacteriaceae, Ralstonia, Streptococcus, Fusobacterium, Ureaplasma, etc. The pharyngeal microbiota was mainly composed of Ureaplasma, Bacteroides, Fusobacterium, etc. Ureaplasma and Fusobacterium were detected in both intestine and pharynx. At T28, there was a significant difference in microbial composition between intestine and pharynx (p < 0.001). The intestinal microbiota was mainly composed of Unidentified Clostridiales, Klebsiella, Unidentified Enterobacteriaceae, Enterobacter, Streptococcus, etc. Pharyngeal microbiota was mainly composed of Streptococcus, Rothia, etc. Streptococcus was detected in both intestine and pharynx.Conclusions: The intestine and pharynx of premature neonates have a unique microbial composition, and share some common microbiota. Whether these microbiotas play a role in the mechanism of gut-lung crosstalk needs further study.