Insulin resistance in Fibrocalculous (tropical) pancreatic diabetes

Insulin resistance was assessed by Insulin Tolerance Test (ITT) in 12 patients with FCPD, 10 with NIDDM and 12 age and sex matched control subjects. The mean BMI of the FCPD was lower than the NIDDM and control groups (P less than 0.001). There was no significant difference between the mean fasting plasma glucose or HbA1 between the FCPD and NIDDM patients. The mean fasting C-peptide of the FCPD group was significantly lower than the NIDDM and control groups (P less than 0.001). The mean glucose disposal rate (KITT) was 5.57 +/- 2.28 in the control group, 2.15 +/- 2.00 in the FCPD and 1.77 +/- 0.91 in the NiDDM group (P less than 0.001, control vs FCPD and NIDDM). The difference in KITT between FCPD and NIDDM groups was not significant statistically. The data suggests that patients with FCPD have evidence of insulin resistance and this is similar to that seen in NIDDM patients.     

Biochemical characterization and molecular modeling of a unique lipase from Staphylococcus arlettae JPBW‐1

A three‐step purification of a unique lipase with halo‐, solvent‐, detergent‐, and thermo‐tolerance from Staphylococcus arlettae JPBW‐1 gave raise to a 27‐fold purification with a specific activity of 32.5 U/mg. The molecular weight of the purified lipase was estimated to be 45 kDa using SDS–PAGE, and its amino acid sequence was characterized using MALDI‐TOF‐MS analysis. The sequence obtained from MALDI‐TOF‐MS showed significant similarity with the capsular polysaccharide biosynthesis protein (CapD) of Staphylococcus aureus through comparative modeling approach using ROBETTA server. Identification of responsible fragments for homodimer formation was performed using comparative modeling and substrate binding domain through C‐terminus matching of this new lipase with the CapD of Staphylococcus aureus was executed. Thus, the experimental coupled molecular modeling postulated a structure–activity relationship of lipase from S. arlettae JPBW‐1, a potential candidate for detergent, leather, pulp, and paper industries.     

An Integrated Metabolomic and Microbiome Analysis Identified Specific Gut Microbiota Associated with Fecal Cholesterol and Coprostanol in Clostridium difficile Infection

Clostridium difficile infection (CDI) is characterized by dysbiosis of the intestinal microbiota and a profound derangement in the fecal metabolome. However, the contribution of specific gut microbes to fecal metabolites in C. difficile-associated gut microbiome remains poorly understood. Using gas-chromatography mass spectrometry (GC-MS) and 16S rRNA deep sequencing, we analyzed the metabolome and microbiome of fecal samples obtained longitudinally from subjects with Clostridium difficile infection (n = 7) and healthy controls (n = 6). From 155 fecal metabolites, we identified two sterol metabolites at >95% match to cholesterol and coprostanol that significantly discriminated C. difficile-associated gut microbiome from healthy microbiota. By correlating the levels of cholesterol and coprostanol in fecal extracts with 2,395 bacterial operational taxonomic units (OTUs) determined by 16S rRNA sequencing, we identified 63 OTUs associated with high levels of coprostanol and 2 OTUs correlated with low coprostanol levels. Using indicator species analysis (ISA), 31 of the 63 coprostanol-associated bacteria correlated with health, and two Veillonella species were associated with low coprostanol levels that correlated strongly with CDI. These 65 bacterial taxa could be clustered into 12 sub-communities, with each community containing a consortium of organisms that co-occurred with one another. Our studies identified 63 human gut microbes associated with cholesterol-reducing activities. Given the importance of gut bacteria in reducing and eliminating cholesterol from the GI tract, these results support the recent finding that gut microbiome may play an important role in host lipid metabolism.     

Discovery of Metabolic Biomarkers for Duchenne Muscular Dystrophy within a Natural History Study

Serum metabolite profiling in Duchenne muscular dystrophy (DMD) may enable discovery of valuable molecular markers for disease progression and treatment response. Serum samples from 51 DMD patients from a natural history study and 22 age-matched healthy volunteers were profiled using liquid chromatography coupled to mass spectrometry (LC-MS) for discovery of novel circulating serum metabolites associated with DMD. Fourteen metabolites were found significantly altered (1% false discovery rate) in their levels between DMD patients and healthy controls while adjusting for age and study site and allowing for an interaction between disease status and age. Increased metabolites included arginine, creatine and unknown compounds at m/z of 357 and 312 while decreased metabolites included creatinine, androgen derivatives and other unknown yet to be identified compounds. Furthermore, the creatine to creatinine ratio is significantly associated with disease progression in DMD patients. This ratio sharply increased with age in DMD patients while it decreased with age in healthy controls. Overall, this study yielded promising metabolic signatures that could prove useful to monitor DMD disease progression and response to therapies in the future.     

Structural vaccinology approach to investigate the virulent and secretory proteins of Bacillus anthracis for devising anthrax next-generation vaccine

Abstract

Communicated by Ramaswamy H. Sarma     

Handwriting Analysis Indicates Spontaneous Dyskinesias in Neuroleptic Na?ve Adolescents at High Risk for Psychosis

Growing evidence suggests that movement abnormalities are a core feature of psychosis. One marker of movement abnormality, dyskinesia, is a result of impaired neuromodulation of dopamine in fronto-striatal pathways. The traditional methods for identifying movement abnormalities include observer-based reports and force stability gauges. The drawbacks of these methods are long training times for raters, experimenter bias, large site differences in instrumental apparatus, and suboptimal reliability. Taking these drawbacks into account has guided the development of better standardized and more efficient procedures to examine movement abnormalities through handwriting analysis software and tablet. Individuals at risk for psychosis showed significantly more dysfluent pen movements (a proximal measure for dyskinesia) in a handwriting task. Handwriting kinematics offers a great advance over previous methods of assessing dyskinesia, which could clearly be beneficial for understanding the etiology of psychosis.