A recombinant plasmid containing the Rous sarcoma virus-long terminal repeat (RSV-LTR) promoter linked to rainbow trout (Salmo gairdneri) growth hormone (GH) cDNA was microinjected into fertilized carp eggs. Genomic DNA extracted from pectoral fin of individual presumptive transgenic fish was analyzed by dot blot and Southern blot hybridization, using the RSV-LTR and/or the GH cDNA sequences as probes. Out of 365 presumptive transgenic fish analyzed, 20 individuals were found to contain pRSV-rtGH-cDNA sequence in the genomic DNA. Expression of the trout GH polypeptide was detected by immunobinding assay in the red blood cells of nine transgenic fish tested. The level of expression, however, varied among the transgenics and could not be correlated with exogenous DNA copy number. Although there was considerable variation in the sizes of the transgenic fish, those microinjected during the one-cell stage were (P less than 0.05) 22% larger, on the average, than their sibling controls. A randomly selected fraction of the progeny derived from crosses between transgenic males and non-transgenic females inherited the foreign DNA. These transgenic progeny grew faster (P less than 0.05) than their non-transgenic siblings.

Summary Nuclear magnetic resonance (NMR)-based metabolomics is widely used to obtain metabolic fingerprints of biological systems. While targeted workflows require previous knowledge of metabolites, prior to statistical analysis, untargeted approaches remain a challenge. Computational tools dealing with fully untargeted NMR-based metabolomics are still scarce or not user-friendly. Therefore, we developed AlpsNMR (Automated spectraL Processing System for NMR), an R package that provides automated and efficient signal processing for untargeted NMR metabolomics. AlpsNMR includes spectra loading, metadata handling, automated outlier detection, spectra alignment and peak-picking, integration and normalization. The resulting output can be used for further statistical analysis. AlpsNMR proved effective in detecting metabolite changes in a test case. The tool allows less experienced users to easily implement this workflow from spectra to a ready-to-use dataset in their routines. Availability and implementation The AlpsNMR R package and tutorial is freely available to download from http://github.com/sipss/AlpsNMR under the MIT license. Supplementary information Supplementary data are available at Bioinformatics online.

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Bifidobacteria are saccharolytic bacteria that are able to metabolize a relatively large range of carbohydrates through their unique central carbon metabolism known as the “bifid-shunt”. Carbohydrates have been shown to modulate the growth rate of bifidobacteria, but unlike for other genera (e.g., E. coli or L. lactis), the impact it may have on the overall physiology of the bacteria has not been studied in detail to date. Using glucose and galactose as model substrates in Bifidobacterium longum NCC 2705, we established that the strain displayed fast and slow growth rates on those carbohydrates, respectively. We show that these differential growth conditions are accompanied by global transcriptional changes and adjustments of central carbon fluxes. In addition, when grown on galactose, NCC 2705 cells were significantly smaller, exhibited an expanded capacity to import and metabolized different sugars and displayed an increased acid-stress resistance, a phenotypic signature associated with generalized fitness. We predict that part of the observed adaptation is regulated by the previously described bifidobacterial global transcriptional regulator AraQ, which we propose to reflect a catabolite-repression-like response in B. longum. With this manuscript, we demonstrate that not only growth rate but also various physiological characteristics of B. longum NCC 2705 are responsive to the carbon source used for growth, which is relevant in the context of its lifestyle in the human infant gut where galactose-containing oligosaccharides are prominent.