A Mycobacterial Systems Resource for the Research Community.

Functional characterization of bacterial proteins lags far behind the identification of new protein families. This is especially true for bacterial species that are more difficult to grow and genetically manipulate than model systems such as Escherichia coli and Bacillus subtilis To facilitate functional characterization of mycobacterial proteins, we have established a Mycobacterial Systems Resource (MSR) using the model organism Mycobacterium smegmatis This resource focuses specifically on 1,153 highly conserved core genes that are common to many mycobacterial species, including Mycobacterium tuberculosis, in order to provide the most relevant information and resources for the mycobacterial research community. The MSR includes both biological and bioinformatic resources. The biological resource includes (i) an expression plasmid library of 1,116 genes fused to a fluorescent protein for determining protein localization; (ii) a library of 569 precise deletions of nonessential genes; and (iii) a set of 843 CRISPR-interference (CRISPRi) plasmids specifically targeted to silence expression of essential core genes and genes for which a precise deletion was not obtained. The bioinformatic resource includes information about individual genes and a detailed assessment of protein localization. We anticipate that integration of these initial functional analyses and the availability of the biological resource will facilitate studies of these core proteins in many Mycobacterium species, including the less experimentally tractable pathogens M. abscessus, M. avium, M. kansasii, M. leprae, M. marinum, M. tuberculosis, and M. ulceransIMPORTANCE Diseases caused by mycobacterial species result in millions of deaths per year globally, and present a substantial health and economic burden, especially in immunocompromised patients. Difficulties inherent in working with mycobacterial pathogens have hampered the development and application of high-throughput genetics that can inform genome annotations and subsequent functional assays. To facilitate mycobacterial research, we have created a biological and bioinformatic resource (https://msrdb.org/) using Mycobacterium smegmatis as a model organism. The resource focuses specifically on 1,153 proteins that are highly conserved across the mycobacterial genus and, therefore, likely perform conserved mycobacterial core functions. Thus, functional insights from the MSR will apply to all mycobacterial species. We believe that the availability of this mycobacterial systems resource will accelerate research throughout the mycobacterial research community.

Quantitative trait loci influencing hepatic copper in rats.

Significant differences in liver copper content have been observed between rat inbred strains. To define loci controlling this trait, the offspring (n = 190) from an (LEW/OlaHsd x BC/CpbU) F(2)-intercross was genetically analyzed. From each F(2) animal, liver copper content was determined and genomic DNA was screened with polymorphic DNA markers. We found a major quantitative trait locus (QTL) for liver copper content in females on chromosome 2 and in males on chromosome 10. Both QTLs accounted for approximately 20% of the genetic variance. In addition, suggestive linkage for liver copper content was found on rat chromosomes 1, 8, 10, 12, 14, and 19. The regions on these chromosomes contain genes that are responsible for 9.0-15.5% of the genetic variance of liver copper content.

Genetic and correlation analysis of hepatic copper content in the rat.

Thirty recombinant inbred (RI) strains derived from the spontaneous hypertensive rat (SHR/OlaIpcv) and the Brown Norway (BN-Lx/Cub) progenitors were used to search for quantitative trait loci (QTLs) that are responsible for differences in liver copper between these two strains. The heritability of liver copper concentration (expressed as microg/g liver wet wt and microg/g liver dry wt) and liver copper store (microg/whole liver) was estimated to be 57, 57, and 46%, respectively. In a total genome scan of the RI strains, involving over 600 genetic markers, suggestive association was found between liver copper store (microg/whole liver) and the D16Wox9 marker on chromosome 16 (lod score = 2.8), and between liver copper concentration (microg/g dry wt) and the D10Cebrp1016s2 marker on chromosome 10 (lod score = 3.0). These putative QTLs are responsible for nearly 34 and 40% of the additive genetic variability for liver copper store and concentration, respectively.