199 Do the Microbiomes of Horses Process Nutrients Differently Based on Keeper Status?

2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 106-106
Author(s):  
Alexa C Johnson ◽  
Amy S Biddle
Keyword(s):  
Fixed Effects ◽  
High Performance ◽  
16S Rrna Gene Sequencing ◽  
Gas Production ◽  
Rrna Gene ◽  
Total N ◽  
Fermentation Products ◽  
Fecal Samples ◽  
Α Diversity ◽  
C 50

Abstract This study reports the differential response of the equine gut microbiome to protein and/or carbohydrate based on keeper status (easy keeper (EK), medium keeper (MK), hard keeper (HK)). Anaerobic equine fecal samples (n = 12 total, n = 3 / EK, MK, HK of four breeds) inoculated microcosms with three dietary conditions (C = Carb (cornmeal), P = Protein (soybean meal), and M = mix (50% C, 50% P)). Over 48 hours, fermentation products were measured using colorimetric assays and high-performance liquid chromatography. Microbial populations were surveyed using 16S rRNA gene sequencing analyzed by QIIME2. Linear mixed models were fit with fixed effects of Treatment and Keeper status and their interactions, with random effects of HorseID. Differences in fermentation products by keeper status included: MK had higher pH and greater gas production, EK produced higher hydrogen sulfide, and HK had greater total protein. Total SCFA was not different between keeper status (P = 0.89) but the acetate: propionate ratio was highest for HK (2.45mM) and lowest for EK (1.85mM) (P = 0.05). Isobutyrate production was highest in HK (2.34mM) compared to MK (0.85mM) and EK (0.17mM). Treatment had significant effects across all measurements; M and C treatment values were similar reflecting microbial preferences for carbohydrates before protein. P treated trials had increased fermentation outputs due to lower acidity effects. Keeper status had no effect on α-diversity (P > 0.05) however HK horses were least affected by treatments. P treated samples were more diverse than C and M (P < 0.001). Spearman correlation of Keeper x Treatment identified Oligosphaeria spp. in EK (r = 0.49) and Fusobacteria spp. in HK whole fecal samples (r = 0.37). These data suggest that while the compositions of the gut microbiomes of keeper groups were similar, they were functionally different in processing key nutrients.

scholarly journals A Combined Analysis of Gut and Skin Microbiota in Infants with Food Allergy and Atopic Dermatitis: A Pilot Study

Nutrients ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 1682
Author(s):  
Ewa Łoś-Rycharska ◽  
Marcin Gołębiewski ◽  
Marcin Sikora ◽  
Tomasz Grzybowski ◽  
Marta Gorzkiewicz ◽  
...  
Keyword(s):  
Atopic Dermatitis ◽  
Food Allergy ◽  
Gut Microbiota ◽  
Bacterial Species ◽  
Rrna Gene ◽  
Healthy Children ◽  
Skin Microbiota ◽  
Fecal Samples ◽  
Healthy Infants ◽  
Α Diversity

The gut microbiota in patients with food allergy, and the skin microbiota in atopic dermatitis patients differ from those of healthy people. We hypothesize that relationships may exist between gut and skin microbiota in patients with allergies. The aim of this study was to determine the possible relationship between gut and skin microbiota in patients with allergies, hence simultaneous analysis of the two compartments of microbiota was performed in infants with and without allergic symptoms. Fifty-nine infants with food allergy and/or atopic dermatitis and 28 healthy children were enrolled in the study. The skin and gut microbiota were evaluated using 16S rRNA gene amplicon sequencing. No significant differences in the α-diversity of dermal or fecal microbiota were observed between allergic and non-allergic infants; however, a significant relationship was found between bacterial community structure and allergy phenotypes, especially in the fecal samples. Certain clinical conditions were associated with characteristic bacterial taxa in the skin and gut microbiota. Positive correlations were found between skin and fecal samples in the abundance of Gemella among allergic infants, and Lactobacillus and Bacteroides among healthy infants. Although infants with allergies and healthy infants demonstrate microbiota with similar α-diversity, some differences in β-diversity and bacterial species abundance can be seen, which may depend on the phenotype of the allergy. For some organisms, their abundance in skin and feces samples may be correlated, and these correlations might serve as indicators of the host’s allergic state.

scholarly journals Pre-digest of unprotected DNA by Benzonase improves the representation of living skin bacteria and efficiently depletes host DNA

Microbiome ◽  
2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Yacine Amar ◽  
Ilias Lagkouvardos ◽  
Rafaela L. Silva ◽  
Oluwaseun Ayodeji Ishola ◽  
Bärbel U. Foesel ◽  
...  
Keyword(s):  
Defense Mechanisms ◽  
Bacterial Load ◽  
16S Rrna Gene Sequencing ◽  
Rrna Gene ◽  
Skin Microbiome ◽  
Mock Community ◽  
Skin Bacteria ◽  
Α Diversity ◽  
Microbial Turnover ◽  
Microbial Dna

Abstract Background The identification of microbiota based on next-generation sequencing (NGS) of extracted DNA has drastically improved our understanding of the role of microbial communities in health and disease. However, DNA-based microbiome analysis cannot per se differentiate between living and dead microorganisms. In environments such as the skin, host defense mechanisms including antimicrobial peptides and low cutaneous pH result in a high microbial turnover, likely resulting in high numbers of dead cells present and releasing substantial amounts of microbial DNA. NGS analyses may thus lead to inaccurate estimations of microbiome structures and consequently functional capacities. Results We investigated in this study the feasibility of a Benzonase-based approach (BDA) to pre-digest unprotected DNA, i.e., of dead microbial cells, as a method to overcome these limitations, thus offering a more accurate assessment of the living microbiome. A skin mock community as well as skin microbiome samples were analyzed using 16S rRNA gene sequencing and metagenomics sequencing after DNA extraction with and without a Benzonase digest to assess bacterial diversity patterns. The BDA method resulted in less reads from dead bacteria both in the skin mock community and skin swabs spiked with either heat-inactivated bacteria or bacterial-free DNA. This approach also efficiently depleted host DNA reads in samples with high human-to-microbial DNA ratios, with no obvious impact on the microbiome profile. We further observed that low biomass samples generate an α-diversity bias when the bacterial load is lower than 105 CFU and that Benzonase digest is not sufficient to overcome this bias. Conclusions The BDA approach enables both a better assessment of the living microbiota and depletion of host DNA reads. Graphical abstract

scholarly journals Refinement of metabolite detection in cystic fibrosis sputum reveals heme negatively correlates with lung function

2018 ◽  
Author(s):  
Nathaniel R. Glasser ◽  
Ryan C. Hunter ◽  
Theodore G. Liou ◽  
Dianne K. Newman ◽  
Keyword(s):  
Mass Spectrometry ◽  
Cystic Fibrosis ◽  
Lung Function ◽  
High Performance ◽  
16S Rrna Gene Sequencing ◽  
Initial Study ◽  
Rrna Gene ◽  
Sequencing Data ◽  
Unknown Compound ◽  
Mountain West

SummaryPseudomonas aeruginosalung infections are a leading cause of morbidity and mortality in cystic fibrosis (CF) patients (1, 2). Our laboratory has studied a class of small molecules produced byP. aeruginosaknown as phenazines, including pyocyanin and its biogenic precursor phenazine-1-carboxylic acid (PCA). As phenazines are known virulence factors (3), we and others have explored the possibility of using phenazine concentrations as a marker for disease progression (4–6). Previously, we reported that sputum concentrations of pyocyanin and PCA negatively correlate with lung function in cystic fibrosis patients (6). Our study used high performance liquid chromatography (HPLC) to quantify phenazines by UV–vis absorbance after extraction from lung sputum. Since our initial study, methods for metabolite analysis have advanced considerably, aided in large part by usage of mass spectrometry (LC-MS) and tandem mass spectrometry (LC-MS/MS). Because a more recent study employing LC-MS/MS revealed a surprising decoupling ofP. aeruginosametabolites in sputum and the detection ofP. aeruginosathrough culturing or microbiome profiles (4), we decided to check whether we could reproduce our previous findings by analyzing sputum samples from a different patient cohort with a new LC-MS instrument in our laboratory. Our new samples were provided by the Mountain West CF Consortium Sputum Biomarker study (7). In the course of performing our new analyses, comparison of our old HPLC data to our new LC-MS data led us to realize that the peak previously assigned to PCA instead originates from heme, and the peak assigned to pyocyanin originates from an as-yet unknown compound. This correction only affects the measurements of phenazines in sputum, and we are confident in the phenazine measurements from isolated cultures and the 16S rRNA gene sequencing data from that study (6). Here we outline the basis for our correction and present additional data showing that heme concentration negatively correlates with lung function in cystic fibrosis patients.

scholarly journals The Diversity of the Intestinal Flora Disturbed After Feeding Intolerance Recovery in Preterm Twins

2021 ◽  
Vol 9 ◽  
Author(s):  
Ying Li ◽  
Chunhong Jia ◽  
Xiaojun Lin ◽  
Lili Lin ◽  
Lizhen Li ◽  
...  
Keyword(s):  
Acid Metabolism ◽  
Intestinal Flora ◽  
16S Rrna Gene Sequencing ◽  
Rrna Gene ◽  
Feeding Intolerance ◽  
Fecal Samples ◽  
Kegg Pathways ◽  
Intestinal Bacterial Community ◽  
Β Diversity ◽  
Significant Difference

Background: Feeding intolerance (FI) is a common condition in premature infants that results in growth retardation and even necrotizing enterocolitis. The gut microbiome is linked to FI occurrence; however, the outcome after FI recovery is unclear.Methods: Fecal samples were collected from 11 pairs of premature twins/triplets for 16S rRNA gene sequencing. Initial fecal samples were collected shortly after admission, and then every other week until 7 weeks or discharge.Results: After FI recovery, there was no significant difference in the β-diversity of the intestinal flora between the FI group and the feeding tolerance (FT) group. By contrast, there was a significant difference in the β-diversity. Proteobacteria was the predominant phylum in the microbiome of the FI group, whereas Firmicutes was the predominant phylum in the microbiome of the FT group. The predominant bacteria with LDA >4 between the two groups at 13–15 days after birth, 19–28 days after birth, and at discharge were different, with the proportions of Bacillus, Clostridium butyricum, and Clostridium being highest in the FT group and Firmicutes, unidentified_Clostridiales, and Proteobacteria being highest in the FI group. Similarly, there were significant differences in the relative abundances of KEGG pathways, such as fatty acid metabolism, DNA repair and recombination proteins, energy metabolism, and amino acid metabolism, between the two groups (P < 0.01).Conclusions: There was a significant difference in diversity of the intestinal flora after feeding intolerance recovery. Feeding intolerance may disturb the succession of the intestinal bacterial community.

scholarly journals The Effect of White Rice and White Bread as Staple Foods on Gut Microbiota and Host Metabolism

Nutrients ◽  
2018 ◽  
Vol 10 (9) ◽  
pp. 1323 ◽  
Author(s):  
Fumika Mano ◽  
Kaori Ikeda ◽  
Erina Joo ◽  
Yoshihito Fujita ◽  
Shunsuke Yamane ◽  
...  
Keyword(s):  
Gut Microbiota ◽  
Dietary Intervention ◽  
16S Rrna Gene Sequencing ◽  
Rrna Gene ◽  
White Bread ◽  
Fecal Samples ◽  
White Rice ◽  
Staple Foods ◽  
Glucagon Like Peptide 1 ◽  
Side Dishes

The purpose of this study was to examine the influence of two kinds of major Japanese staple foods, white rice and white bread, on gut microbiota against the background in which participants eat common side dishes. Seven healthy subjects completed the dietary intervention with two 1-week test periods with a 1-week wash-out period in cross-over design (UMIN registration UMIN000023142). White bread or white rice and 21 frozen prepared side dishes were consumed during the test periods. At baseline and at the end of each period, fasting blood samples, breath samples, and fecal samples were collected. For fecal samples, 16S rRNA gene sequencing was used to analyze the gut microbiota. After the bread period, the abundance of fecal Bifidobacterium genus (19.2 ± 14.5 vs. 6.2 ± 6.6 (%), p = 0.03), fasting glucagon-like peptide 1 (GLP-1) (13.6 ± 2.0 vs. 10.5 ± 2.9 (pg/mL), p = 0.03), and breath hydrogen (23.4 ± 9.9 vs. 8.2 ± 5.5 (ppm), p = 0.02) were significantly higher than those of after the rice period. Plasma SCFAs also tended to be higher after the bread period. White bread contains more dietary fiber than refined short grain rice. These findings suggest that indigestible carbohydrate intake from short grain rice as a staple food may be smaller than that of white bread.

scholarly journals Identification of a Shared Microbiomic and Metabolomic Profile in Systemic Autoimmune Diseases

2019 ◽  
Vol 8 (9) ◽  
pp. 1291 ◽  
Author(s):  
Bellocchi ◽  
Fernández-Ochoa ◽  
Montanelli ◽  
Vigone ◽  
Santaniello ◽  
...  
Keyword(s):  
Autoimmune Diseases ◽  
Lupus Erythematosus ◽  
High Performance ◽  
16S Rrna Gene Sequencing ◽  
Study Groups ◽  
Mass Spectrometry Analysis ◽  
Rrna Gene ◽  
Operating Characteristics ◽  
Systemic Autoimmune Diseases ◽  
Spectrometry Analysis

Dysbiosis has been described in systemic autoimmune diseases (SADs), including systemic lupus erythematosus (SLE), Sjögren’s syndrome (SjS), and primary anti-phosholipid syndrome (PAPS), however the biological implications of these associations are often elusive. Stool and plasma samples from 114 subjects, including in SLE (n = 27), SjS (n = 23), PAPs (n = 11) and undifferentiated connective tissue (UCTD, n = 26) patients, and geographically-matched healthy controls (HCs, n = 27), were collected for microbiome (16s rRNA gene sequencing) and metabolome (high-performance liquid chromatography coupled to mass spectrometry) analysis to identify shared characteristics across diseases. Out of 130 identified microbial genera, a subset of 29 bacteria was able to differentiate study groups (area under receiver operating characteristics (AUROC) = 0.730 ± 0.025). A fair classification was obtained with a subset of 41 metabolic peaks out of 254 (AUROC = 0.748 ± 0.021). In both models, HCs were well separated from SADs, while UCTD largely overlapped with the other diseases. In all of the SADs pro-tolerogenic bacteria were reduced, while pathobiont genera were increased. Metabolic alterations included two clusters comprised of: (a) members of the acylcarnitine family, positively correlating with a Prevotella-enriched cluster and negatively correlating with a butyrate-producing bacteria-enriched cluster; and (b) phospholipids, negatively correlating with butyrate-producing bacteria. These findings demonstrate a strong interaction between intestinal microbiota and metabolic function in patients with SADs.

scholarly journals Age-Related Colonic Mucosal Microbiome Community Shifts in Monkeys

2020 ◽  
Author(s):  
Ravichandra Vemuri ◽  
Chrissy Sherrill ◽  
Matthew A Davis ◽  
Kylie Kavanagh
Keyword(s):  
Microbial Community ◽  
Systemic Inflammation ◽  
16S Rrna Gene Sequencing ◽  
Microbial Interactions ◽  
Rrna Gene ◽  
Vervet Monkeys ◽  
Fecal Samples ◽  
Age Related ◽  
Rrna Gene Sequencing ◽  
The Stability

Abstract Age-related changes in gut microbiome impact host health. The interactive relationship between the microbiome and physiological systems in an aged body system remains to be clearly defined, particularly in the context of inflammation. Therefore, we aimed to evaluate systemic inflammation, microbial translocation (MT), and differences between fecal and mucosal microbiomes. Ascending colon mucosal biopsies, fecal samples, and blood samples from healthy young and old female vervet monkeys were collected for 16S rRNA gene sequencing, MT, and cytokine analyses, respectively. To demonstrate microbial co-occurrence patterns, we used Kendall’s tau correlation measure of interactions between microbes. We found elevated levels of plasma LBP-1, MCP-1, and CRP in old monkeys, indicative of higher MT and systemic inflammation. Microbiome analysis revealed significant differences specific to age. At the phylum level, abundances of pathobionts such as Proteobacteria were increased in the mucosa of old monkeys. At the family level, Helicobacteriaceae was highly abundant in mucosal samples (old); in contrast, Ruminococcaceae were higher in the fecal samples of old monkeys. We found significantly lower Firmicutes:Bacteroidetes ratio and lower abundance of butyrate-producing microbes in old monkeys, consistent with less healthy profiles. Microbial community co-occurrence analysis on mucosal samples revealed 13 nodes and 41 associations in the young monkeys, but only 12 nodes and 21 associations in the old monkeys. Our findings provide novel insights into systemic inflammation and gut microbial interactions, highlight the importance of the mucosal niche, and facilitate further understanding of the decline in the stability of the microbial community with aging.

scholarly journals Leuconostoc durionis sp. nov., a heterofermenter with no detectable gas production from glucose

2005 ◽  
Vol 55 (3) ◽  
pp. 1267-1270 ◽  
Author(s):  
J. J. Leisner ◽  
M. Vancanneyt ◽  
R. Van der Meulen ◽  
K. Lefebvre ◽  
K. Engelbeen ◽  
...  
Keyword(s):  
Dna Hybridization ◽  
Type Strain ◽  
Sequence Similarity ◽  
Gene Sequencing ◽  
16S Rrna Gene Sequencing ◽  
Gas Production ◽  
Rrna Gene ◽  
Nearest Neighbour ◽  
Sds Page ◽  
Rrna Gene Sequencing

Three lactic acid bacterial (LAB) strains obtained from a Malaysian acid-fermented condiment, tempoyak (made from pulp of the durian fruit), showed analogous but distinct patterns after screening by SDS-PAGE of whole-cell proteins and comparison with profiles of all recognized LAB species. 16S rRNA gene sequencing of one representative strain showed that the taxon belongs phylogenetically to the genus Leuconostoc, with its nearest neighbour being Leuconostoc fructosum (98 % sequence similarity). Biochemical characteristics and DNA–DNA hybridization experiments demonstrated that the strains differ from Leuconostoc fructosum and represent a single, novel Leuconostoc species for which the name Leuconostoc durionis sp. nov. is proposed. The type strain is LMG 22556T (=LAB 1679T=D-24T=CCUG 49949T).

scholarly journals Analysis of the Gull Fecal Microbial Community Reveals the Dominance of Catellicoccus marimammalium in Relation to Culturable Enterococci

2013 ◽  
Vol 80 (2) ◽  
pp. 757-765 ◽  
Author(s):  
Amber M. Koskey ◽  
Jenny C. Fisher ◽  
Mary F. Traudt ◽  
Ryan J. Newton ◽  
Sandra L. McLellan
Keyword(s):  
Microbial Community ◽  
16S Rrna ◽  
16S Rrna Gene ◽  
16S Rrna Gene Sequencing ◽  
Illumina Miseq ◽  
Rrna Gene ◽  
Sequence Comparisons ◽  
Fecal Indicator ◽  
Fecal Samples ◽  
Content Type

ABSTRACTGulls are prevalent in beach environments and can be a major source of fecal contamination. Gulls have been shown to harbor a high abundance of fecal indicator bacteria (FIB), such asEscherichia coliand enterococci, which can be readily detected as part of routine beach monitoring. Despite the ubiquitous presence of gull fecal material in beach environments, the associated microbial community is relatively poorly characterized. We generated comprehensive microbial community profiles of gull fecal samples using Roche 454 and Illumina MiSeq platforms to investigate the composition and variability of the gull fecal microbial community and to measure the proportion of FIB.EnterococcaceaeandEnterobacteriaceaewere the two most abundant families in our gull samples. Sequence comparisons between short-read data and nearly full-length 16S rRNA gene clones generated from the same samples revealedCatellicoccus marimammaliumas the most numerous taxon among all samples. The identification of bacteria from gull fecal pellets cultured on membrane-Enterococcusindoxyl-β-d-glucoside (mEI) plates showed that the dominant sequences recovered in our sequence libraries did not represent organisms culturable on mEI. Based on 16S rRNA gene sequencing of gull fecal isolates cultured on mEI plates, 98.8% were identified asEnterococcusspp., 1.2% were identified asStreptococcusspp., and none were identified asC. marimammalium. Illumina deep sequencing indicated that gull fecal samples harbor significantly higher proportions ofC. marimammalium16S rRNA gene sequences (>50-fold) relative to typical mEI culturableEnterococcusspp.C. marimammaliumtherefore can be confidently utilized as a genetic marker to identify gull fecal pollution in the beach environment.

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