Association of Intelectin Gene Polymorphism with Type 2 Diabetes Risk in the North Indian Population

Background: Intelectin 1 is an anti-inflammatory adipocytokine involved in the regulation of insulin secretion. Genetic variations in the coding region of Intelectin can cause hyperglycemia due to impaired glucose levels, increasing the susceptibility to Type 2 Diabetes Mellitus (T2DM). Objective: This study examines the genetic variations in the Intelectin 1 coding region, specifically rs2274907 and rs2274908. Materials and Methods: A case-control study was conducted with 300 participants: 150 individuals with Type 2 Diabetes Mellitus (fasting glucose >125 mg/dL) and 150 healthy controls (fasting glucose <125 mg/dL). The frequencies of rs2274907 and rs2274908 polymorphisms were analyzed using the Tetra Amplification refractory Mutation system and allele-specific PCR, respectively. Results: The study identified a significant association between specific gene variations and increased risk of Type 2 Diabetes mellitus. The TT genotype of rs2274907 showed a higher frequency in the diabetes group (15.33%) compared to the control group (3.33%), with a model of TT vs. AT+AA: X²=12.76, P=0.0004, OR=5.25, and 95% CI=1.93-14.21. Similarly, the AA genotype of rs2274908 was more frequent in the diabetes group (26.66%) compared to the control group (7.33%), with a model of AA vs. AG+GG: X²=18.52, P=0.0001, OR=4.59, and 95% CI=2.25-9.3. Conclusion: This is the first study of the North Indian population suggesting that specific Intelectin 1 gene variations (TT genotype of rs2274907 and AA genotype of rs2274908) are associated with an increased risk of Type 2 Diabetes Mellitus. Variations in Intelectin 1 may impact protein function and stability, serving as potential biomarkers for Type 2 Diabetes Mellitus and targets for personalized medicine. Keywords: ITLN1, Case-control, Genetic variation, Type 2 Diabetes Mellitu

RAPD-PCR and 16S rDNA phylogenetic analysis of alkaline protease producing bacteria isolated from soil of India: Identification and detection of genetic variability

Abstract178 bacterial strains were isolated from the soil samples collected from different regions of India out of which, 20 bacterial isolates were selected for alkaline protease production. The alkaline protease production efficiency of organisms was monitored at regular intervals (24h) upto 7days at 37°C, pH 10. The 16S rDNA sequencing and RAPD-PCR based technique were used to identify the genetic variability among the 20 isolates of alkaline protease producing bacteria. The phylogenetic analysis indicated that the isolates can be separated into two clusters which could be further subdivided into five groups. Group 1 and 5 represented the family Bacillaceae, Groups 2 represented the Micrococcaceae family while Group 3 included the Arthrobacter bacterial group (family Micrococcaceae) from different geographical locations, respectively. Group 4 was identified as Pseudomonadaceae which was gram (−) bacteria. 21 different oligonucleotide primers were used to amplify approximately 261 fragments from each DNA sample. The bands were scored on the basis of their presence and absence and similarity between DNA samples was checked using Jaccard’s coefficient. Isolates were distinguished into distinct groups based on RAPD profiles from different geographical locations, morphological features and enzyme production efficiency. For cluster analysis the dendrogram was constructed using the unweighted pair group method with arithmetic averages (UPGMA). The results indicated that 16S rDNA and RAPD-PCR are suitable methods for rapid identification and differentiation of alkaline protease producing bacteria