The aminopeptidase from Streptomyces griseus (SGAP) has been cloned and expressed in Escherichia coli. By growing the cells in the presence of 1 M sorbitol at 18°C, the protein was obtained in a soluble and active form. The amino acid sequence of the recombinant SGAP contained four amino acids differing from the previously published sequence. Resequencing of the native protein indicated that asparagines 70 and 184 are in fact aspartic acids as in the recombinant protein.Based on the crystal structure of SGAP, Glu131 and Tyr246 were proposed to be the catalytic residues. Replacements of Glu131 resulted in loss of activity of 4-5 orders of magnitude, consistent with Glu131 acting as the general base residue. Mutations in Tyr246 resulted in about 100-fold reduction of activity, suggesting that this residue is involved in the stabilization of the transition state intermediate.

Background The use of remote data capture for monitoring blood glucose and supporting digital apps is becoming the norm in diabetes care. One common goal of such apps is to increase user awareness and engagement with their day-to-day health-related behaviors (digital engagement) in order to improve diabetes outcomes. However, we lack a deep understanding of the complicated association between digital engagement and diabetes outcomes. Objective This study investigated the association between digital engagement (operationalized as tagging of behaviors alongside glucose measurements) and the monthly average blood glucose level in persons with type 2 diabetes during the first year of managing their diabetes with a digital chronic disease management platform. We hypothesize that during the first 6 months, blood glucose levels will drop faster and further in patients with increased digital engagement and that difference in outcomes will persist for the remainder of the year. Finally, we hypothesize that disaggregated between- and within-person variabilities in digital engagement will predict individual-level changes in blood glucose levels. Methods This retrospective real-world analysis followed 998 people with type 2 diabetes who regularly tracked their blood glucose levels with the Dario digital therapeutics platform for chronic diseases. Subjects included “nontaggers” (users who rarely or never used app features to notice and track mealtime, food, exercise, mood, and location, n=585) and “taggers” (users who used these features, n=413) representing increased digital engagement. Within- and between-person variabilities in tagging behavior were disaggregated to reveal the association between tagging behavior and blood glucose levels. The associations between an individual’s tagging behavior in a given month and the monthly average blood glucose level in the following month were analyzed for quasicausal effects. A generalized mixed piecewise statistical framework was applied throughout. Results Analysis revealed significant improvement in the monthly average blood glucose level during the first 6 months (t=−10.01, P<.001), which was maintained during the following 6 months (t=−1.54, P=.12). Moreover, taggers demonstrated a significantly steeper improvement in the initial period relative to nontaggers (t=2.15, P=.03). Additional findings included a within-user quasicausal nonlinear link between tagging behavior and glucose control improvement with a 1-month lag. More specifically, increased tagging behavior in any given month resulted in a 43% improvement in glucose levels in the next month up to a person-specific average in tagging intensity (t=−11.02, P<.001). Above that within-person mean level of digital engagement, glucose levels remained stable but did not show additional improvement with increased tagging (t=0.82, P=.41). When assessed alongside within-person effects, between-person changes in tagging behavior were not associated with changes in monthly average glucose levels (t=1.30, P=.20). Conclusions This study sheds light on the source of the association between user engagement with a diabetes tracking app and the clinical condition, highlighting the importance of within-person changes versus between-person differences. Our findings underscore the need for and provide a basis for a personalized approach to digital health.

The yet uncharacterized ywad gene from Bacillus subtilis has been cloned and overexpressed in Escherichia coli. The gene product (BSAP) was purified and shown to be an aminopeptidase. The activity of BSAP was optimal at pH 8.4, the enzyme was stable for 20 min at 80 degrees C and its activity was not affected by serine protease and aspartic protease inhibitors, but was completely diminished by the Zn-chelator 1,10-phenanthroline. ZnCl2 was able to restore activity, and the binding stoichiometry of zinc to apo-BSAP indicated two Zn ions per protein molecule. BSAP exhibited high preference toward p-nitroanilide derived Arg, Lys, and Leu synthetic substrates resulting in kcat/Km values of 1-5 x 10(1) s(-1) mM(-1).

The extracellular aminopeptidase from Bacillus subtilis (BSAP) has recently been cloned, overexpressed and purified from Escherichia coli. It is a monomer with a molecular weight of 46 425 Da, consisting of 425 amino-acid residues and a double-zinc catalytic centre. The recombinant enzyme was found to be stable for 20 min at 353 K, to function optimally in the pH range 8-9 and to prefer basic and large hydrophobic N-terminal amino acids in peptide and protein substrates. As such, this enzyme can be used as a representative model for structural, functional and mechanistic studies of monomeric double-zinc aminopeptidases, many of which have been found to be involved in medically important biological activities. In this report, the crystallization and preliminary crystallographic characterization of wild-type BSAP are described. Two different crystal forms are reported, of which the hexagonal form H2 is the more suitable for structural study, with average unit-cell dimensions a = b = 226.5, c = 42.8 A. A full diffraction data set has been collected from such a crystal of the native enzyme (2.2 A resolution, 91.2% completeness, R(merge) = 7.1%). A multiwavelength anomalous diffraction (MAD) data set was collected on native (zinc-containing) BSAP at three wavelengths around the zinc absorption edge (peak data set at 2.5 A resolution, 98.8% completeness, R(merge) = 5.3%). These diffraction data were collected at 95-100 K using a synchrotron X-ray source and a CCD area detector. The data are currently being used to obtain crystallographic phasing and to determine the detailed three-dimensional structure of the enzyme.

Background Remote data capture for blood glucose (BG) or blood pressure (BP) monitoring and the use of a supportive digital app are becoming the model in diabetes and hypertension chronic care. One of the goals in chronic condition management is to increase awareness and generate behavioral change in order to improve outcomes in diabetes and related comorbidities, such as hypertension. In addition, there is a lack of understanding of the association between BG and BP levels when using digital health tools. Objective By applying a rigorous study framework to digital health data, this study investigated the relationship between BP monitoring and BG and BP levels, as well as a lagged association between BP and BG. We hypothesized that during the first 6 months of BP monitoring, BG and BP levels would decrease. Finally, we suggested a positive association between BP levels and the following month’s BG levels. Methods In this retrospective, real-world case-control study, we extracted the data of 269 people with type 2 diabetes (T2D) who tracked their BG levels using the Dario digital platform for a chronic condition. We analyzed the digital data of the users who, in addition to BG, monitored their BP using the same app (BP-monitoring [BPM] group, n=137) 6 months before and after starting their BP monitoring. Propensity score matching established a control group, no blood pressure monitoring (NBPM, n=132), matched on demographic and baseline clinical measures to the BPM group. A piecewise mixed model was used for analyzing the time trajectories of BG, BP, and their lagged association. Results Analysis revealed a significant difference in BG time trajectories associated with BP monitoring in BPM and NBPM groups (t=–2.12, P=.03). The BPM group demonstrated BG reduction improvement in the monthly average BG levels during the first 6 months (t=–3.57, P<.001), while BG did not change for the NBPM group (t=0.39, P=.70). Both groups showed similarly stable BG time trajectories (B=0.98, t=1.16, P=.25) before starting the use of the BP-monitoring system. In addition, the BPM group showed a significant reduction in systolic (t=–6.42, P<.001) and diastolic (t=–4.80, P<.001) BP during the first 6 months of BP monitoring. Finally, BG levels were positively associated with systolic (B=0.24, t=2.77, P=.001) and diastolic (B=0.30, t=2.41, P=.02) BP. Conclusions The results of this study shed light on the association between BG and BP levels and on the role of BP self-monitoring in diabetes management. Our findings also underscore the need and provide a basis for a comprehensive approach to understanding the mechanism of BP regulation associated with BG.