Growth stimulation of Brevibacterium sp. by siderophores

To assess which types of siderophores are typically produced by Brevibacterium and how siderophore production and utilization traits are distributed within this genus. Methods and Results: During co-cultivation experiments it was found that growth of B. linens Br5 was stimulated by B. linens NIZO B1410 by two orders of magnitude. The stimulation was caused by the production of hydroxamate siderophores by B. linens NIZO B1410 that enabled the siderophore-auxotrophic strain Br5 to grow faster under the applied iron-limited growth conditions. Different patterns of siderophore production and utilization were observed within the genus Brevibacterium. These patterns did not reflect the phylogenetic relations within the group as determined by partial 16S rDNA sequencing. Most Brevibacterium strains were found to utilize hydroxamate siderophores. Conclusions: Brevibacteria can produce and utilize siderophores although certain strains within this genus are siderophore-auxotrophic. Significance and Impact of the Study: It is reported for the first time that brevibacteria produce and utilize siderophores. This knowledge can be utilized to stimulate growth of auxotrophic strains under certain conditions. Enhancing the growth rate of Brevibacterium is of importance for the application of this species, for example, for cheese manufacturing or for industrial production of enzymes or metabolites

Predicting enteric methane emission of dairy cows with milk Fourier-transform infrared spectra and gas chromatography–based milk fatty acid profiles

The objective of the present study was to compare the prediction potential of milk Fourier-transform infrared spectroscopy (FTIR) for CH4 emissions of dairy cows with that of gas chromatography (GC)–based milk fatty acids (MFA). Data from 9 experiments with lactating Holstein-Friesian cows, with a total of 30 dietary treatments and 218 observations, were used. Methane emissions were measured for 3 consecutive days in climate respiration chambers and expressed as production (g/d), yield (g/kg of dry matter intake; DMI), and intensity (g/kg of fat- and protein-corrected milk; FPCM). Dry matter intake was 16.3 ± 2.18 kg/d (mean ± standard deviation), FPCM yield was 25.9 ± 5.06 kg/d, CH4 production was 366 ± 53.9 g/d, CH4 yield was 22.5 ± 2.10 g/kg of DMI, and CH4 intensity was 14.4 ± 2.58 g/kg of FPCM. Milk was sampled during the same days and analyzed by GC and by FTIR. Multivariate GC-determined MFA–based and FTIR-based CH4 prediction models were developed, and subsequently, the final CH4 prediction models were evaluated with root mean squared error of prediction and concordance correlation coefficient analysis. Further, we performed a random 10-fold cross validation to calculate the performance parameters of the models (e.g., the coefficient of determination of cross validation). The final GC-determined MFA–based CH4 prediction models estimate CH4 production, yield, and intensity with a root mean squared error of prediction of 35.7 g/d, 1.6 g/kg of DMI, and 1.6 g/kg of FPCM and with a concordance correlation coefficient of 0.72, 0.59, and 0.77, respectively. The final FTIR-based CH4 prediction models estimate CH4 production, yield, and intensity with a root mean squared error of prediction of 43.2 g/d, 1.9 g/kg of DMI, and 1.7 g/kg of FPCM and with a concordance correlation coefficient of 0.52, 0.40, and 0.72, respectively. The GC-determined MFA–based prediction models described a greater part of the observed variation in CH4 emission than did the FTIR-based models. The cross validation results indicate that all CH4 prediction models (both GC-determined MFA–based and FTIR-based models) are robust; the difference between the coefficient of determination and the coefficient of determination of cross validation ranged from 0.01 to 0.07. The results indicate that GC-determined MFA have a greater potential than FTIR spectra to estimate CH4 production, yield, and intensity. Both techniques hold potential but may not yet be ready to predict CH4 emission of dairy cows in practice. Additional CH4 measurements are needed to improve the accuracy and robustness of GC-determined MFA and FTIR spectra for CH4 prediction

Application of rpoB sequence similarity analysis, REP-PCR and BOX-PCR for the differentiation of species within the genus Geobacillus

Aim: To investigate the applicability of rpoB gene, which encodes the beta subunit of RNA polymerase, to be used as an alternative to 16S rRNA for sequence similarity analysis in the thermophilic genus Geobacillus. Rapid and reproducible repetitive extragenic palindromic fingerprinting techniques (REP- and BOX-polymerase chain reaction) were also used. Methods and Results: rpoB DNA (458 bp) were amplified from 21 Geobacillus- and Bacillus type strains, producing different BOX- and REP-PCR profiles, in addition to 11 thermophilic isolates of Geobacillus and Bacillus species from a Santorini volcano habitat. The sequences and the phylogenetic tree of rpoB were compared with those obtained from 16S rRNA gene analysis. The results demonstrated between 90-100% (16S rRNA) and 74-100% (rpoB) similarity among examined bacteria. Conclusion: BOX- and REP-PCR can be applied for molecular typing within Geobacillus genus. rpoB sequence similarity analysis permits a more accurate discrimination of the species within the Geobacillus genus than the more commonly used 16S rRNA. Significance and Impact of the Study: The obtained results suggested that rpoB sequence similarity analysis is a powerful tool for discrimination between species within the ecologically and industrially important strains of Geobacillus genus