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The glpK genes of Enterococcus casseliflavus and Enterococcus faecalis, encoding glycerol kinase, the key enzyme of glycerol uptake and metabolism in bacteria, have been cloned and sequenced. The translated amino acid sequences exhibit strong homology to the amino acid sequences of other bacterial glycerol kinases. After expression of the enterococcal glpK genes in Escherichia coli, both glycerol kinases were purified and were found to be phosphorylated by enzyme I and the histidine-containing protein of the phosphoenolpyruvate:glycose phosphotransferase system. Phosphoenolpyruvate-dependent phosphorylation caused a 9-fold increase in enzyme activity. The site of phosphorylation in glycerol kinase of E. casseliflavus was determined as His-232. Site-specific mutagenesis was used to replace His-232 in glycerol kinase of E. casseliflavus with an alanyl, glutamate, or arginyl residue. The mutant proteins could no longer be phosphorylated confirming that His-232 of E. casseliflavus glycerol kinase represents the site of phosphorylation. The His232 --> Arg glycerol kinase exhibited an about 3-fold elevated activity compared with wild-type glycerol kinase. Fructose 1,6-bisphosphate was found to inhibit E. casseliflavus glycerol kinase activity. However, neither EIIAGlc from E. coli nor the EIIAGlc domain of Bacillus subtilis had an inhibitory effect on glycerol kinase of E. casseliflavus.

Objective: Mobility assessment is critical in the clinical management of people with Multiple Sclerosis (pwMS). Instrumented gait analysis provides a plethora of metrics for quantifying concurrent factors contributing to gait deterioration. However, a gait model discriminating underlying features contributing to this deterioration is lacking in pwMS. This study aimed at developing and validating such a model. Methods: The gait of 24 healthy controls and 114 pwMS with mild, moderate, or severe disability was measured with inertial sensors on the shanks and lower trunk while walking for 6 minutes along a hospital corridor. Twenty out of thirty-six initially explored metrics computed from the sensor data met the quality criteria for exploratory factor analysis. This analysis provided the sought model, which underwent a confirmatory factor analysis before being used to characterize gait impairment across the three disability groups. Results: A gait model consisting of five domains (rhythm/variability, pace, asymmetry, and forward and lateral dynamic balance) was revealed by the factor analysis, which was able to highlight gait abnormalities across the disability groups: significant alterations in rhythm/variability-, asymmetry-, and pace-based features were present in the mild group, but these were more profound in the moderate and severe groups. Deterioration in dynamic balance-based features was only noted in pwMS with a moderate and severe disability. Conclusion: A conceptual model of gait for disease-specific mobility assessment in pwMS was successfully developed and tested. Significance: The new model, built with metrics that represent gait impairment in pwMS, highlighted clinically relevant changes across different disability levels, including those with no clinically observable walking disability. This shows the clear potential as a monitoring biomarker in pwMS. This work was supported by the Mobilise-D project, that has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No. 820820. This Joint Undertaking receives support from the European Union's Horizon 2020 research and innovation program and the European Federation of Pharmaceutical Industries and Associations (EFPIA). Content in this publication reflects the authors’ view and neither IMI nor the European Union, EFPIA, or any Associated Partners are responsible for any use that may be made of the information contained herein.