Quantitative analysis of ruminal bacterial populations involved in lipid metabolism in dairy cows fed different vegetable oils

Vegetable oils are used to increase energy density of dairy cow diets, although they can provoke changes in rumen bacteria populations and have repercussions on the biohydrogenation process. The aim of this study was to evaluate the effect of two sources of dietary lipids: soybean oil (SO, an unsaturated source) and hydrogenated palm oil (HPO, a saturated source) on bacterial populations and the fatty acid profile of ruminal digesta. Three non-lactating Holstein cows fitted with ruminal cannulae were used in a 3x3 Latin square design with three periods consisting of 21 days. Dietary treatments consisted of a basal diet (Control, no fat supplement) and the basal diet supplemented with SO (2.7% of dry matter (DM)) or HPO (2.7% of DM). Ruminal digesta pH, NH3-N and volatile fatty acids were not affected by dietary treatments. Compared with control and HPO, total bacteria measured as copies of 16S ribosomal DNA/ml by quantitative PCR was decreased (P < 0.05) by SO. Fibrobacter succinogenes, Butyrivibrio proteoclasticus and Anaerovibrio lipolytica loads were not affected by dietary treatments. In contrast, compared with control, load of Prevotella bryantii was increased (P < 0.05) with HPO diet. Compared with control and SO, HPO decreased (P < 0.05) C18:2 cis n-6 in ruminal digesta. Contents of C15:0 iso, C18:11 trans-11 and C18:2 cis-9, trans-11 were increased (P < 0.05) in ruminal digesta by SO compared with control and HPO. In conclusion, supplementation of SO or HPO do not affect ruminal fermentation parameters, whereas HPO can increase load of ruminal P. bryantii. Also, results observed in our targeted bacteria may have depended on the saturation degree of dietary oils

Prediction of Susceptibility to First-Line Tuberculosis Drugs by DNA Sequencing

Background: The World Health Organization recommends drug-susceptibility testing of Mycobacterium tuberculosis complex for all patients with tuberculosis to guide treatment decisions and improve outcomes. Whether DNA sequencing can be used to accurately predict profiles of susceptibility to first-line antituberculosis drugs has not been clear. Methods: We obtained whole-genome sequences and associated phenotypes of resistance or susceptibility to the first-line antituberculosis drugs isoniazid, rifampin, ethambutol, and pyrazinamide for isolates from 16 countries across six continents. For each isolate, mutations associated with drug resistance and drug susceptibility were identified across nine genes, and individual phenotypes were predicted unless mutations of unknown association were also present. To identify how whole-genome sequencing might direct first-line drug therapy, complete susceptibility profiles were predicted. These profiles were predicted to be susceptible to all four drugs (i.e., pansusceptible) if they were predicted to be susceptible to isoniazid and to the other drugs or if they contained mutations of unknown association in genes that affect susceptibility to the other drugs. We simulated the way in which the negative predictive value changed with the prevalence of drug resistance. Results: A total of 10,209 isolates were analyzed. The largest proportion of phenotypes was predicted for rifampin (9660 [95.4%] of 10,130) and the smallest was predicted for ethambutol (8794 [89.8%] of 9794). Resistance to isoniazid, rifampin, ethambutol, and pyrazinamide was correctly predicted with 97.1%, 97.5%, 94.6%, and 91.3% sensitivity, respectively, and susceptibility to these drugs was correctly predicted with 99.0%, 98.8%, 93.6%, and 96.8% specificity. Of the 7516 isolates with complete phenotypic drug-susceptibility profiles, 5865 (78.0%) had complete genotypic predictions, among which 5250 profiles (89.5%) were correctly predicted. Among the 4037 phenotypic profiles that were predicted to be pansusceptible, 3952 (97.9%) were correctly predicted. Conclusions: Genotypic predictions of the susceptibility of M. tuberculosis to first-line drugs were found to be correlated with phenotypic susceptibility to these drugs. (Funded by the Bill and Melinda Gates Foundation and others.

Technical note: Use of internal transcribed spacer for ruminal yeast identification in dairy cows

Molecular techniques are important tools for microbiological studies in different habitats, and the internal transcribed spacer (ITS) has been proved to be useful for analyzing fungal diversity. The aim of this study was to use the ITS region to generate ruminal yeast profile and to identify ruminal yeast. DNA from ruminal digesta was extracted to amplify the ribosomal ITS region. The profile from the PCR products was visualized and the excised bands from the profile were identified as the genera Millerozyma, Pichia, Rhizomucor and Hyphopichia. Overall, the ITS resulted to be a simple, fast and sensitive approach that allowed profiling and identification of ruminal yeast that have not been previously described (Millerozyma and Hyphopichia) in the rumen microbial community

Prediction of susceptibility to first-line tuberculosis drugs by DNA sequencing

BACKGROUND The World Health Organization recommends drug-susceptibility testing of Mycobacterium tuberculosis complex for all patients with tuberculosis to guide treatment decisions and improve outcomes. Whether DNA sequencing can be used to accurately predict profiles of susceptibility to first-line antituberculosis drugs has not been clear. METHODS We obtained whole-genome sequences and associated phenotypes of resistance or susceptibility to the first-line antituberculosis drugs isoniazid, rifampin, ethambutol, and pyrazinamide for isolates from 16 countries across six continents. For each isolate, mutations associated with drug resistance and drug susceptibility were identified across nine genes, and individual phenotypes were predicted unless mutations of unknown association were also present. To identify how whole-genome sequencing might direct first-line drug therapy, complete susceptibility profiles were predicted. These profiles were predicted to be susceptible to all four drugs (i.e., pansusceptible) if they were predicted to be susceptible to isoniazid and to the other drugs or if they contained mutations of unknown association in genes that affect susceptibility to the other drugs. We simulated the way in which the negative predictive value changed with the prevalence of drug resistance. RESULTS A total of 10,209 isolates were analyzed. The largest proportion of phenotypes was predicted for rifampin (9660 [95.4%] of 10,130) and the smallest was predicted for ethambutol (8794 [89.8%] of 9794). Resistance to isoniazid, rifampin, ethambutol, and pyrazinamide was correctly predicted with 97.1%, 97.5%, 94.6%, and 91.3% sensitivity, respectively, and susceptibility to these drugs was correctly predicted with 99.0%, 98.8%, 93.6%, and 96.8% specificity. Of the 7516 isolates with complete phenotypic drug-susceptibility profiles, 5865 (78.0%) had complete genotypic predictions, among which 5250 profiles (89.5%) were correctly predicted. Among the 4037 phenotypic profiles that were predicted to be pansusceptible, 3952 (97.9%) were correctly predicted. CONCLUSIONS Genotypic predictions of the susceptibility of M. tuberculosis to first-line drugs were found to be correlated with phenotypic susceptibility to these drugs. (Funded by the Bill and Melinda Gates Foundation and others.