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.

A gradient-layer calorimeter for measurement of energy expenditure of infants.

We have developed and validated a gradient-layer calorimeter for direct measurement of energy expenditure of preterm infants. Infant calorimeters must be operated and tested differently from adult calorimeters, because the calorimeter must be warmed during operation to limit heat loss from the infant, the calorimeter wall temperature (which is selected on the basis of the infant's maturity) must be precisely controlled, and energy expenditure (heat output) is typically < 10 W. We calibrated our calorimeter by varying the heat produced by a dry source (manikin or light bulb) with airflow (n = 42) and without airflow (n = 8) at various water jacket temperatures (n = 7) and by a wet source (combustion of ethyl alcohol) with airflow (n = 9). With no air moving, qc = 0.740 Vc + 0.029 Twj-0.697, where qc (W) is the estimated output of the heat source measured by the calorimeter, Vc (mV) is the gradient-layer voltage of the calorimeter, and Twj (degree C) is the temperature of the water jacket surrounding the walls of the device. From this equation and enthalpy calculations, the slope and intercept of the regression line relating the estimated heat production to the actual heat produced from alcohol combustion are 1.029 +/- 0.046 and -0.549 +/- 0.484 (SE), respectively. The slope is not significantly different from unity, and the intercept is not significantly different from zero. Thus we can accurately estimate the energy expenditure of preterm infants from the equations describing our calorimeter, and we can accurately resolve the total heat output into a dry (nonevaporative) component and a wet (evaporative) component.