The position of the epistatic S locus in the halothane linkage group in pigs

The linkage of the Phi, Pgd, Po2, S, H and halothane sensitivity loci was followed in a Belgian Landrace family, heterozygous for these systems over 6 generations. Recombination next to the S locus occurred mainly in pigs belonging to this particular family. From this investigation the position of the S locus is proved to be outwith the Phi-Pgd region, next to Phi . Therefore the gene sequence S - Phi - Hal -H- Po2 -Pgd is proposed. Higher recombination rates were observed in the female parental line of the multiheterozygous family when compared to the male parental line. Additional data from animals, unrelated to this strain, confirm the evidence of close linkage of the S system to the nearest marker loci.     

Molecular Mechanisms of Translation Initiation in Mammals Studied by in vitroReconstruction of Initiation Complexes

Papers on the mechanisms of translation initiation in mammals studied by reconstruction of initiation complexes from individual components are reviewed. The author points to the constraints of this approach and to the pitfalls ignoring which one might come to erroneous conclusions and even artifacts. In addition, some methods employed in the field as well as some technical problems are discussed in the paper, together with the means of obviating them. The review could be a guidebook for newcomers into this quite labor-consuming field.     

Cloning of aroG, the gene coding for phospho-2-keto-3-deoxy-heptonate aldolase(phe), in Escherichia coli K-12, and subcloning of the aroG promoter and operator in a promoter-detecting plasmid

Defective transducing phages carrying aroG, the structural gene for phenylalanine (phe)-inhibitable phospho-2-keto-heptonate aldolase (EC 4.1.2.15; previously known as 3-deoxy-D-arabinoheptulosonate-7-phosphate synthetase[phe]), have been isolated, and DNA from two of these phages has been used to construct a restriction map of the region from att lambda to aroG. A 7.6-kb PstI-HindIII fragment from one of these phages was cloned into pBR322 and shown to contain aroG. The location of aroG within the 7.6 kb was established by subcloning and Tn3 transpositional mutagenesis. A fragment carrying the aroG promoter and operator has been cloned into a high copy number promoter-cloning vector (pMC489), and the resulting aroGpo-LacZ' (alpha) fusion subcloned in a low copy number vector. Strains with this fusion on the low copy number vector exhibit negative regulation of beta-galactosidase expression by both phenylalanine and tryptophan and positive regulation by tyrosine in a tyrR+ background.     

Carotenoid synthesis in Streptomyces setonii ISP5395 is induced by the gene crtS, whose product is similar to a sigma factor

In many species of actinomycetes, carotenogenesis can be photoinduced. The capacity to respond to photoinduction is, however unstable and, in various strains of Streptomyces, is lost at a relatively high frequency. In Streptomyces setonii ISP5395, which normally produces no carotenoids, carotenoid-producing mutants can be obtained following protoplast regeneration. We report here the characterization of a gene, crtS, which was isolated from one such mutant and can confer on wild-type S. setonii ISP5395 cells the capacity to synthesize carotenoids. Sequence analysis of crtS reveals an open reading frame, which shows homology to genes that encode alternative sigma factors in Bacillus subtilis. We propose that crtS encodes a sigma factor which is necessary for the expression of a cryptic gene(s) for carotenoid biosynthesis in S. setonii ISP5395.     

Prediction of the halothane (Hal) genotypes of pigs by deducing Hal, Phi, Po2, Pgd haplotypes of parents and offspring: results from a large-scale practice in Swedish breeds

Results from a large-scale study, comprising 75 different breeding herds, are reported on predicting the halothane ( Hal ) genotypes of individual pigs by making use of the known close linkage between Hal and three C blood marker loci ( Phi, Po2, Pgd ). The parents haplotypes (involving Hal and marker loci) were determined from the HAL phenotypes (halothane test results) and marker loci phenotypes of their offspring in the first one or two litters studied. In subsequent litters of the Hal -marker loci haplotyped parents, the offspring's expected Hal genotypes could be predicted on the basis of the marker loci haplotypes inherited by them. By comparing the expected and observed HAL phenotypes of offspring in subsequent litters, the predicted Hal genotype was found to be correct in 90–95 % of the 4000 offspring (from Nn × Nn and Nn × nn matings) of Swedish Landrace and Yorkshire breeds studied.
The order of the three marker loci was confirmed as Phi-Po2-Pgd but the position of Hal with regards to Phi could not be resolved. The recombination frequencies between the most distant loci in this region, viz. Hal-Pgd and Phi-Pgd , were estimated to be 3–4.5 % and 4–6 % , respectively. The easy and rapid electrophoretic techniques described in the study to phenotype PHI, PO2, PGD, also allowed phe-notyping of six other polymorphic protein systems on the same gels. Thus Hal genotyping and effective parentage control can be conducted simultaneously.     

Multiomic Metabolic Enrichment Network Analysis Reveals Metabolite–Protein Physical Interaction Subnetworks Altered in Cancer

Metabolism is recognized as an important driver of cancer progression and other complex diseases, but global metabolite profiling remains a challenge. Protein expression profiling is often a poor proxy since existing pathway enrichment models provide an incomplete mapping between the proteome and metabolism. To overcome these gaps, we introduce multiomic metabolic enrichment network analysis (MOMENTA), an integrative multiomic data analysis framework for more accurately deducing metabolic pathway changes from proteomics data alone in a gene set analysis context by leveraging protein interaction networks to extend annotated metabolic models. We apply MOMENTA to proteomic data from diverse cancer cell lines and human tumors to demonstrate its utility at revealing variation in metabolic pathway activity across cancer types, which we verify using independent metabolomics measurements. The novel metabolic networks we uncover in breast cancer and other tumors are linked to clinical outcomes, underscoring the pathophysiological relevance of the findings.     

Structure-based protein design with deep learning

Since the first revelation of proteins functioning as macromolecular machines through their three dimensional structures, researchers have been intrigued by the marvelous ways the biochemical processes are carried out by proteins. The aspiration to understand protein structures has fueled extensive efforts across different scientific disciplines. In recent years, it has been demonstrated that proteins with new functionality or shapes can be designed via structure-based modeling methods, and the design strategies have combined all available information — but largely piece-by-piece — from sequence derived statistics to the detailed atomic-level modeling of chemical interactions. Despite the significant progress, incorporating data-derived approaches through the use of deep learning methods can be a game changer. In this review, we summarize current progress, compare the arc of developing the deep learning approaches with the conventional methods, and describe the motivation and concepts behind current strategies that may lead to potential future opportunities.