scholarly journals Effect of temperature and time on the thanatomicrobiome of the cecum, ileum, kidney, and lung of domestic rabbits

2019 ◽  
Vol 31 (2) ◽  
pp. 155-163 ◽  
Author(s):  
Kelsey E. Lawrence ◽  
Khiem C. Lam ◽  
Andrey Morgun ◽  
Natalia Shulzhenko ◽  
Christiane V. Löhr
Keyword(s):  
16S Rrna Gene Sequencing ◽  
Effect Of Temperature ◽  
Postmortem Changes ◽  
Rrna Gene ◽  
Limited Information ◽  
Microbiome Composition ◽  
Microbiome Diversity ◽  
Domestic Rabbits ◽  
High Concentrations ◽  
Rrna Gene Sequencing

Knowledge of changes in the composition of microbial communities (microbiota) in tissues after death, over time, is critical to correctly interpret results of microbiologic testing from postmortem examinations. Limited information is available about postmortem changes of the microbiota and the associated microbial genes (microbiome) of internal organs in any species. We examined the effect of time and ambient temperature on the postmortem microbiome (thanatomicrobiome) of tissues typically sampled for microbiologic testing during autopsies. Twenty rabbits were euthanized and their bodies stored at 4°C or 20°C for 6 or 48 h. Ileum, cecum, kidney, and lung tissue were sampled. Bacterial DNA abundance was determined by RT-qPCR. Microbiome diversity was determined by 16S rRNA gene sequencing. By relative abundance of the microbiome composition, intestinal tissues were clearly separated from lungs and kidneys, which were similar to each other, over all times and temperatures. Only cecal thanatomicrobiomes had consistently high concentrations and consistent composition in all conditions. In lungs and kidneys, but not intestine, proteobacteria were highly abundant at specific times and temperatures. Thanatomicrobiome variation was not explained by minor subclinical lesions identified upon microscopic examination of tissues. Bacterial communities typically found in the intestine were not identified at extra-intestinal sites in the first 48 h at 4°C and only in small amounts at 20°C. However, changes in tissue-specific microbiomes during the postmortem interval should be considered when interpreting results of microbiologic testing.

scholarly journals Effects of Giardia lamblia Colonization and Fenbendazole Treatment on Canine Fecal Microbiota

2020 ◽  
Author(s):  
Naomi N Lee ◽  
Willie A Bidot ◽  
Aaron C Ericsson ◽  
Craig L Franklin
Keyword(s):  
Giardia Lamblia ◽  
16S Rrna Gene Sequencing ◽  
Fecal Microbiota ◽  
Rrna Gene ◽  
Limited Information ◽  
Sample Collection ◽  
Minimal Impact ◽  
Clinically Normal ◽  
Significant Difference ◽  
Rrna Gene Sequencing

The gut microbiota (GM) is the sum of hundreds of distinct microbial species that can equal or outnumber their host’ssomatic cells. The GM influences a multitude of physiologic and immunologic processes in the host, and changes in the GM have been shown to alter the phenotypes of animal models. Previous studies using rodents have also shown that the composition of the GM is affected by many factors, including diet, husbandry, housing, and the genetic background of the animals. However, limited information exists about factors that may modulate GM in other laboratory species, such as dogs. We sought to eliminate sporadic Giardia colonization of dogs using fenbendazole (FBZ), an antiprotozoal widely used in biomedical research dog colonies. Concerns that FBZ could have inadvertent effects on the canine GM led us to assess GM over the course of treatment. FBZ (50 mg/kg) was given orally to all dogs in 3 different facilities (n = 19 to 25) for 10 consecutive days. Fecal samples were obtained 2 d before the initiation of treatment, on the last day of treatment, and 2 wk after the completion of treatment. Targeted 16S rRNA gene sequencing was used to analyze fecal microbiota. All dogs were clinically normal throughout the sample collection period. Statistical analyses of data showed significant differences between dogs housed in the 3 different facilities, further emphasizing the effect of housing and husbandry factors on the GM. However,negligible differences were seen between time points, indicating that FBZ did not significantly alter the canine GM. Comparison of the GM of Giardia lamblia positive and negative dogs revealed no significant difference between the 2 groups. These findings suggest that FBZ can be used therapeutically in dogs with minimal impact on the GM. Furthermore, the presence ofG. lamblia in clinically normal animals may not be sufficient to influence the normal canine microbiota.

scholarly journals Dietary sphinganine is selectively assimilated by members of the gut microbiome

2020 ◽  
Author(s):  
Min-Ting Lee ◽  
Henry H. Le ◽  
Elizabeth L. Johnson
Keyword(s):  
Gut Microbiome ◽  
16S Rrna Gene Sequencing ◽  
Dietary Lipids ◽  
Rrna Gene ◽  
Bioactive Components ◽  
Microbiome Composition ◽  
Metabolic Products ◽  
Comparative Metabolomics ◽  
Rrna Gene Sequencing ◽  
Gut Microbial Community

AbstractFunctions of the gut microbiome have a growing number of implications for host metabolic health, with diet being one of the most significant influences on microbiome composition. Compelling links between diet and the gut microbiome suggest key roles for various macronutrients, including lipids, yet how individual classes of dietary lipids interact with the microbiome remain largely unknown. A class of lipids known as sphingolipids are bioactive components of most foods and are produced by prominent gut microbes. This makes sphingolipids intriguing candidates for shaping diet-microbiome interactions. Here, we use a click-chemistry based approach to track the incorporation of bioorthogonal dietary omega-alkynyl sphinganine (sphinganine alkyne – SAA) into the gut microbial community (Click). Identification of microbe and SAA-specific metabolic products was achieved by fluorescence-based sorting of SAA containing microbes (Sort), 16S rRNA gene sequencing to identify the sphingolipid-interacting microbes (Seq), and comparative metabolomics to identify products of SAA assimilation by the microbiome (Spec). Together this approach, Click-Sort-Seq-Spec (ClickSSS), revealed that SAA-assimilation was nearly exclusively performed by gut Bacteroides, indicating that sphingolipid-producing bacteria play a major role in processing dietary sphinganine. Comparative metabolomics of cecal microbiota from SAA-treated mice showed conversion of SAA to a suite of dihydroceramides, consistent with metabolic activity via Bacteroides and Bifidobacterium. Additionally, other sphingolipid-interacting microbes were identified with a focus on an uncharacterized ability of Bacteroides and Bifidobacterium to metabolize dietary sphingolipids. Therefore, ClickSSS provides a platform to study the flux of virtually any alkyne-labeled metabolite in diet-microbiome interactions.

scholarly journals Characterizing the fecal bacteria and archaea community of heifers and lactating cows through 16S rRNA next-generation sequencing

2020 ◽  
Vol 61 (4) ◽  
pp. 593-605
Author(s):  
Filippo Cendron ◽  
Giovanni Niero ◽  
Gabriele Carlino ◽  
Mauro Penasa ◽  
Martino Cassandro
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene Sequencing ◽  
Rrna Gene ◽  
Fecal Bacteria ◽  
Fecal Microbiome ◽  
Alpha And Beta Diversity ◽  
Microbiome Composition ◽  
Lactating Cows ◽  
Holstein Friesian ◽  
Rrna Gene Sequencing

AbstractThe aim of this study was to describe the fecal bacteria and archaea composition of Holstein-Friesian and Simmental heifers and lactating cows, using 16S rRNA gene sequencing. Bacteria and archaea communities were characterized and compared between heifers and cows of the same breed. Two breeds from different farms were considered, just to speculate about the conservation of the microbiome differences between cows and heifers that undergo different management conditions. The two breeds were from two different herds. Firmicutes, Bacteroidetes, Actinobacteria, and Proteobacteria were the most abundant phyla in all experimental groups. Alpha- and beta-diversity metrics showed significant differences between heifers and cows within the same breed, supported by principal coordinate analysis. The analysis of Holstein-Friesian fecal microbiome composition revealed 3 different bacteria families, 2 genera, and 2 species that differed between heifers and cows; on the other hand, Simmental heifers and cows differed only for one bacteria family, one archaeal genus, and one bacteria species. Results of the present study suggest that fecal communities of heifers and cows are different, and that fecal microbiome is maintained across experimental groups.

scholarly journals Alterations to the Gastrointestinal Microbiome Associated with Methamphetamine Use among Young Men who have Sex with Men

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Ryan R. Cook ◽  
Jennifer A. Fulcher ◽  
Nicole H. Tobin ◽  
Fan Li ◽  
David J. Lee ◽  
...  
Keyword(s):  
Public Health Problem ◽  
16S Rrna Gene Sequencing ◽  
The United States ◽  
Rrna Gene ◽  
People Living With Hiv ◽  
Major Public Health Problem ◽  
Microbiome Composition ◽  
Rrna Gene Sequencing ◽  
Sex With Men ◽  
Living With Hiv

Abstract Methamphetamine (MA) use is a major public health problem in the United States, especially among people living with HIV (PLWH). Many MA-induced neurotoxic effects are mediated by inflammation and gut microbiota may play a role in this process, yet the effects of MA on the microbiome have not been adequately explored. Therefore, we performed 16S rRNA gene sequencing on rectal swab samples from 381 men who have sex with men, 48% of whom were PLWH and 41% of whom used MA. We compared microbiome composition between MA users and non-users while testing for potential interactions with HIV and controlling for numerous confounders using inverse probability of treatment weighting. We found that MA use explained significant variation in overall composition (R2 = 0.005, p = 0.008) and was associated with elevated Finegoldia, Parvimonas, Peptoniphilus, and Porphyromonas and reduced Butyricicoccus and Faecalibacterium, among others. Genera including Actinomyces and Streptobacillus interacted with HIV status, such that they were increased in HIV+ MA users. Finegoldia and Peptoniphilus increased with increasing frequency of MA use, among others. In summary, MA use was associated with a microbial imbalance favoring pro-inflammatory bacteria, including some with neuroactive potential and others that have previously been associated with poor HIV outcomes.

scholarly journals Dietary sphinganine is selectively assimilated by members of the mammalian gut microbiome

2020 ◽  
pp. jlr.RA120000950 ◽  
Author(s):  
Min-Ting Lee ◽  
Henry H Le ◽  
Elizabeth L Johnson
Keyword(s):  
Gut Microbiome ◽  
16S Rrna Gene Sequencing ◽  
Dietary Lipids ◽  
Rrna Gene ◽  
Microbiome Composition ◽  
Bioorthogonal Labeling ◽  
Comparative Metabolomics ◽  
Metabolic Activities ◽  
Rrna Gene Sequencing ◽  
Gut Microbial Community

Functions of the gut microbiome have a growing number of implications for host metabolic health, with diet being one of the most significant influences on microbiome composition. Compelling links between diet and the gut microbiome suggest key roles for various macronutrients, including lipids, yet how individual classes of dietary lipids interact with the microbiome remains largely unknown. Sphingolipids are bioactive components of most foods and are also produced by prominent gut microbes. This makes sphingolipids intriguing candidates for shaping diet–microbiome interactions. Here, we used a click chemistry–based approach to track the incorporation of bioorthogonal dietary omega-alkynyl sphinganine (sphinganine alkyne [SAA]) into the murine gut microbial community (Bioorthogonal labeling). We identified microbial and SAA-specific metabolic products through fluorescence-based sorting of SAA-containing microbes (Sort), 16S rRNA gene sequencing to identify the sphingolipid-interacting microbes (Seq), and comparative metabolomics to identify products of SAA assimilation by the microbiome (Spec). Together, this approach, termed Bioorthogonal labeling-Sort-Seq-Spec (BOSSS), revealed that SAA assimilation is nearly exclusively performed by gut Bacteroides, indicating that sphingolipid-producing bacteria play a major role in processing dietary sphinganine. Comparative metabolomics of cecal microbiota from SAA-treated mice revealed conversion of SAA to a suite of dihydroceramides, consistent with metabolic activities of Bacteroides and Bifidobacterium. Additionally, other sphingolipid-interacting microbes were identified with a focus on an uncharacterized ability of Bacteroides and Bifidobacterium to metabolize dietary sphingolipids. We conclude that BOSSS provides a platform to study the flux of virtually any alkyne-labeled metabolite in diet–microbiome interactions.

scholarly journals Megasphaera in the stool microbiota is negatively associated with diarrheal cryptosporidiosis

2020 ◽  
Author(s):  
Maureen A. Carey ◽  
Gregory L. Medlock ◽  
Masud Alam ◽  
Mamun Kabir ◽  
Md Jashim Uddin ◽  
...  
Keyword(s):  
Diarrheal Disease ◽  
16S Rrna Gene Sequencing ◽  
Fold Change ◽  
Rrna Gene ◽  
Fecal Microbiome ◽  
Microbiome Composition ◽  
Random Forest Classification ◽  
Forest Classification ◽  
Microbiome Profile ◽  
Rrna Gene Sequencing

ABSTRACTBackgroundThe protozoan parasites in the Cryptosporidium genus cause both acute diarrheal disease and subclinical (i.e. non-diarrheal) disease. It is unclear if the microbiota can influence the manifestation of diarrhea during a Cryptosporidium infection.MethodsTo characterize the role of the gut microbiota in diarrheal cryptosporidiosis, the microbiome composition of both diarrheal and surveillance Cryptosporidium-positive fecal samples was evaluated using 16S rRNA gene sequencing. Additionally, the microbiome composition prior to infection was examined to test whether a preexisting microbiome profile could influence the Cryptosporidium infection phenotype.ResultsFecal microbiome composition was associated with diarrheal symptoms at two timepoints. Megasphaera was significantly less abundant in diarrheal samples when compared to subclinical samples at the time of Cryptosporidium detection (log2(fold change) = -4.3, p=10−10) and prior to infection (log2(fold change) = -2.0, p=10−4). Random forest classification also identified Megasphaera abundance in the pre- and post-exposure microbiota.as predictive of a subclinical infection.ConclusionsMicrobiome composition broadly, and specifically low Megasphaera abundance, was associated with diarrheal symptoms prior to and at the time of Cryptosporidium detection. This observation suggests that the gut microenvironment may play a role in determining the severity of a Cryptosporidium infection.SummaryMegasphaera abundance in the stool of Bangladeshi infants is associated with the development of diarrhea upon infection with the Cryptosporidium parasite.

scholarly journals Low Diversity in Nasal Microbiome Associated with Staphylococcus aureus Colonization and Bloodstream Infections in Hospitalized Neonates

2021 ◽  
Author(s):  
Ni Zhao ◽  
Dina F Khamash ◽  
Hyunwook Koh ◽  
Annie Voskertchian ◽  
Emily Egbert ◽  
...  
Keyword(s):  
Staphylococcus Aureus ◽  
Alpha Diversity ◽  
Bloodstream Infections ◽  
16S Rrna Gene Sequencing ◽  
Rrna Gene ◽  
Case Control Studies ◽  
Wilcoxon Rank Sum Test ◽  
Microbiome Diversity ◽  
Matched Case ◽  
Rrna Gene Sequencing

Abstract Background Staphylococcus aureus is a leading cause of infectious morbidity and mortality in neonates. Little data exist on the association of the nasal microbiome and susceptibility to neonatal S. aureus colonization and infection. Methods We performed two matched case-control studies (colonization cohort – neonates who did and did not acquire S. aureus colonization; bacteremia cohort - neonates who did [colonized neonates] and did not [controls] acquire S. aureus colonization and neonates with S. aureus bacteremia [bacteremic neonantes]). Neonates in two intensive care units were enrolled and matched on week of life at time of colonization or infection. Nasal samples were collected weekly until discharge, cultured for S. aureus, and the nasal microbiome characterized using 16S rRNA gene sequencing. Results In the colonization cohort, 43 S. aureus colonized neonates were matched to 82 controls. At first week of life, neonates who acquired S. aureus colonization had lower alpha diversity (Wilcoxon rank sum test p<0.05) and differed in beta diversity (omnibus MiRKAT p=0.002) even after adjusting for birth weight (p=0.01). The bacteremia cohort included 10 neonates of which 80% developed bacteremia within 4 weeks of birth and 70% had positive S. aureus cultures within a few days of bacteremia. Neonates with bacteremia had an increased relative abundance of S. aureus sequences and lower alpha diversity measures compared to colonized neonates and controls. Conclusions The association of increased S. aureus abundance and decrease of microbiome diversity suggests the need for interventions targeting the nasal microbiome to prevent S. aureus disease in vulnerable neonates.

scholarly journals 16S rRNA Gene Sequencing as a Clinical Diagnostic Aid for Gastrointestinal-related Conditions

2016 ◽  
Author(s):  
Daniel E. Almonacid ◽  
Laurens Kraal ◽  
Francisco J. Ossandon ◽  
Yelena V. Budovskaya ◽  
Juan Pablo Cardenas ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
16S Rrna Gene Sequencing ◽  
Epidemiological Studies ◽  
Clinical Test ◽  
Rrna Gene ◽  
Bioinformatics Pipeline ◽  
Microbiome Composition ◽  
Rrna Gene Sequencing ◽  
Gut Microorganisms

AbstractAccurate detection of the microorganisms underlying gut dysbiosis in the patient is critical to initiate the appropriate treatment. However, most clinical microbiology techniques used to detect gut bacteria were developed over a century ago and rely on culture-based approaches that are often laborious, unreliable, and subjective. Further, culturing does not scale well for multiple targets and detects only a minority of the microorganisms in the human gastrointestinal tract. Here we present a clinical test for gut microorganisms based on targeted sequencing of the prokaryotic 16S rRNA gene. We tested 46 clinical prokaryotic targets in the human gut, 28 of which can be identified by a bioinformatics pipeline that includes sequence analysis and taxonomic annotation. Using microbiome samples from a cohort of 897 healthy individuals, we established a reference range defining clinically relevant relative levels for each of the 28 targets. Our assay accurately quantified all 28 targets and correctly reflected 38/38 verification samples of real and synthetic stool material containing known pathogens. Thus, we have established a new test to interrogate microbiome composition and diversity, which will improve patient diagnosis, treatment and monitoring. More broadly, our test will facilitate epidemiological studies of the microbiome as it relates to overall human health and disease.

scholarly journals Effect of Commonly Used Pediatric Antibiotics on Gut Microbial Diversity in Preschool Children in Burkina Faso: A Randomized Clinical Trial

2018 ◽  
Vol 5 (11) ◽  
Author(s):  
Catherine E Oldenburg ◽  
Ali Sié ◽  
Boubacar Coulibaly ◽  
Lucienne Ouermi ◽  
Clarisse Dah ◽  
...  
Keyword(s):  
Preschool Children ◽  
Diversity Index ◽  
Controlled Trial ◽  
16S Rrna Gene Sequencing ◽  
Intestinal Microbiome ◽  
Rrna Gene ◽  
Once Daily ◽  
Microbiome Composition ◽  
Α Diversity ◽  
Rrna Gene Sequencing

Abstract Background Exposure to antibiotics may result in alterations to the composition of intestinal microbiota. However, few trials have been conducted, and observational studies are subject to confounding by indication. We conducted a randomized controlled trial to determine the effect of 3 commonly used pediatric antibiotics on the intestinal microbiome in healthy preschool children. Methods Children aged 6–59 months were randomized (1:1:1:1) to a 5-day course of 1 of 3 antibiotics, including amoxicillin (25 mg/kg/d twice-daily doses), azithromycin (10 mg/kg dose on day 1 and then 5 mg/kg once daily for 4 days), cotrimoxazole (240 mg once daily), or placebo. Rectal swabs were obtained at baseline and 5 days after the last dose and were processed using 16S rRNA gene sequencing. The prespecified primary outcome was inverse Simpson’s α-diversity index. Results Post-treatment Simpson’s diversity was significantly different across the 4 arms (P = .003). The mean Simpson’s α-diversity among azithromycin-treated children was significantly lower than in placebo-treated children (6.6; 95% confidence interval [CI], 5.5–7.8; vs 9.8; 95% CI, 8.7–10.9; P = .0001). Diversity in children treated with amoxicillin (8.3; 95% CI, 7.0–9.6; P = .09) or cotrimoxazole (8.3; 95% CI, 8.2–9.7; P = .08) was not significantly different than placebo. Conclusions Azithromycin affects the composition of the pediatric intestinal microbiome. The effect of amoxicillin and cotrimoxazole on microbiome composition was less clear. Clinical Trials Registration clinicaltrials.gov NCT03187834.

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