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1.
Integr Comp Biol ; 62(2): 237-251, 2022 08 25.
Article in English | MEDLINE | ID: mdl-35587374

ABSTRACT

The gut microbial communities of mammals provide numerous benefits to their hosts. However, given the recent development of the microbiome field, we still lack a thorough understanding of the variety of ecological and evolutionary factors that structure these communities across species. Metabarcoding is a powerful technique that allows for multiple microbial ecology questions to be investigated simultaneously. Here, we employed DNA metabarcoding techniques, predictive metagenomics, and culture-dependent techniques to inventory the gut microbial communities of several species of rodent collected from the same environment that employ different natural feeding strategies [granivorous pocket mice (Chaetodipus penicillatus); granivorous kangaroo rats (Dipodomys merriami); herbivorous woodrats (Neotoma albigula); omnivorous cactus mice (Peromyscus eremicus); and insectivorous grasshopper mice (Onychomys torridus)]. Of particular interest were shifts in gut microbial communities in rodent species with herbivorous and insectivorous diets, given the high amounts of indigestible fibers and chitinous exoskeleton in these diets, respectively. We found that herbivorous woodrats harbored the greatest microbial diversity. Granivorous pocket mice and kangaroo rats had the highest abundances of the genus Ruminococcus and highest predicted abundances of genes related to the digestion of fiber, representing potential adaptations in these species to the fiber content of seeds and the limitations to digestion given their small body size. Insectivorous grasshopper mice exhibited the greatest inter-individual variation in the membership of their microbiomes, and also exhibited the highest predicted abundances of chitin-degrading genes. Culture-based approaches identified 178 microbial isolates (primarily Bacillus and Enterococcus), with some capable of degrading cellulose and chitin. We observed several instances of strain-level diversity in these metabolic capabilities across isolates, somewhat highlighting the limitations and hidden diversity underlying DNA metabarcoding techniques. However, these methods offer power in allowing the investigation of several questions concurrently, thus enhancing our understanding of gut microbial ecology.


Subject(s)
Gastrointestinal Microbiome , Microbiota , Animals , Chitin , Dipodomys , Herbivory , Peromyscus , Rodentia
2.
J Nanobiotechnology ; 14: 34, 2016 Apr 22.
Article in English | MEDLINE | ID: mdl-27102228

ABSTRACT

BACKGROUND: Titanium dioxide (TiO2) is one of the most common nanoparticles found in industry ranging from food additives to energy generation. Approximately four million tons of TiO2 particles are produced worldwide each year with approximately 3000 tons being produced in nanoparticulate form, hence exposure to these particles is almost certain. RESULTS: Even though TiO2 is also used as an anti-bacterial agent in combination with UV, we have found that, in the absence of UV, exposure of HeLa cells to TiO2 nanoparticles significantly increased their risk of bacterial invasion. HeLa cells cultured with 0.1 mg/ml rutile and anatase TiO2 nanoparticles for 24 h prior to exposure to bacteria had 350 and 250 % respectively more bacteria per cell. The increase was attributed to bacterial polysaccharides absorption on TiO2 NPs, increased extracellular LDH, and changes in the mechanical response of the cell membrane. On the other hand, macrophages exposed to TiO2 particles ingested 40 % fewer bacteria, further increasing the risk of infection. CONCLUSIONS: In combination, these two factors raise serious concerns regarding the impact of exposure to TiO2 nanoparticles on the ability of organisms to resist bacterial infection.


Subject(s)
Metal Nanoparticles/adverse effects , Staphylococcal Infections/chemically induced , Staphylococcus aureus/drug effects , Titanium/adverse effects , Anti-Bacterial Agents/adverse effects , Cell Line, Tumor , Cell Survival/drug effects , HeLa Cells , Humans , Particle Size
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