Engineering industrial microorganisms for ambitious applications, for example, the production of second-generation biofuels such as butanol, is impeded by a lack of knowledge of primary metabolism and its regulation. A quantitative system-scale analysis was applied to the biofuel-producing bacterium Clostridium acetobutylicum, a microorganism used for the industrial production of solvent. An improved genome-scale model, iCac967, was first developed based on thorough biochemical characterizations of 15 key metabolic enzymes and on extensive literature analysis to acquire accurate fluxomic data. In parallel, quantitative transcriptomic and proteomic analyses were performed to assess the number of mRNA molecules per cell for all genes under acidogenic, solventogenic, and alcohologenic steady-state conditions as well as the number of cytosolic protein molecules per cell for approximately 700 genes under at least one of the three steady-state conditions. A complete fluxomic, transcriptomic, and proteomic analysis applied to different metabolic states allowed us to better understand the regulation of primary metabolism. Moreover, this analysis enabled the functional characterization of numerous enzymes involved in primary metabolism, including (i) the enzymes involved in the two different butanol pathways and their cofactor specificities, (ii) the primary hydrogenase and its redox partner, (iii) the major butyryl coenzyme A (butyryl-CoA) dehydrogenase, and (iv) the major glyceraldehyde-3-phosphate dehydrogenase. This study provides important information for further metabolic engineering of C. acetobutylicum to develop a commercial process for the production of n-butanol.

BackgroundCardiac output (CO) monitoring is a valuable tool for the diagnosis and management of critically ill patients. In the critical care setting, few studies have evaluated the level of agreement between CO estimated by transthoracic echocardiography (CO-TTE) and that measured by the reference method, pulmonary artery catheter (CO-PAC). The objective of the present study was to evaluate the precision and accuracy of CO-TTE relative to CO-PAC and the ability of transthoracic echocardiography to track variations in CO, in critically ill mechanically ventilated patients.MethodsThirty-eight mechanically ventilated patients fitted with a PAC were included in a prospective observational study performed in a 16-bed university hospital ICU. CO-PAC was measured via intermittent thermodilution. Simultaneously, a second investigator used standard-view TTE to estimate CO-TTE as the product of stroke volume and the heart rate obtained during the measurement of the subaortic velocity time integral.ResultsSixty-four pairs of CO-PAC and CO-TTE measurements were compared. The two measurements were significantly correlated (r = 0.95; p < 0.0001). The median bias was 0.2 L/min, the limits of agreement (LOAs) were –1.3 and 1.8 L/min, and the percentage error was 25%. The precision was 8% for CO-PAC and 9% for CO-TTE. Twenty-six pairs of ΔCO measurements were compared. There was a significant correlation between ΔCO-PAC and ΔCO-TTE (r = 0.92; p < 0.0001). The median bias was –0.1 L/min and the LOAs were –1.3 and +1.2 L/min. With a 15% exclusion zone, the four-quadrant plot had a concordance rate of 94%. With a 0.5 L/min exclusion zone, the polar plot had a mean polar angle of 1.0° and a percentage error LOAs of –26.8 to 28.8°. The concordance rate was 100% between 30 and –30°. When using CO-TTE to detect an increase in ΔCO-PAC of more than 10%, the area under the receiving operating characteristic curve (95% CI) was 0.82 (0.62–0.94) (p < 0.001). A ΔCO-TTE of more than 8% yielded a sensitivity of 88% and specificity of 66% for detecting a ΔCO-PAC of more than 10%.ConclusionIn critically ill mechanically ventilated patients, CO-TTE is an accurate and precise method for estimating CO. Furthermore, CO-TTE can accurately track variations in CO.