Proximate and Mineral Composition of the Pulp of Chrysophyllum albidum Fruit

The proximate composition of Chrysophyllum albidum fruit pulp was determined. Mineral elements were determined using a tri-acid digestion method. The result of the proximate composition of the fruit pulp showed moisture content (64.00 ± 0.02%), ash (3.00 ± 0.02%), lipids (8.50 ± 0.02%), crude fibre (4.00 ± 0.02%), crude protein (0.24 ± 0.03%) and soluble carbohydrate (20.26±0.03%). The energy value of the fruit was found to be (663.12±0.60%kJ/100g) in the fruit pulp. Similarly, mineral analysis revealed potassium with (256.57± 5.77mg/100g), sodium (40.00 ± 0.00mg/100g), phosphorus (2.21 ± 0.03mg/100g), calcium (61.67±5.77mg/100g), magnesium (33.33 ± 20.21mg/100g), copper (0.94 ± 0.20mg/100g), zinc (0.26 + 0.10mg/100g), and iron (3.46+ 0.06). Others include heavy metal such as lead (0.09 ±0.08mg/100g), chromium (6.83± 6.26/100g) and cadmium was not detected. The pulp also contained appreciable amount of vitamin C (3.70 ± 0.17mg/100g). The results showed that the fruit pulp of Chrysophyllum albidum contained essential nutrients and mineral elements.Keywords: Chrysophyllum albidum, minerals, proximat

75 Years of India's Independence and 80 Years of CSIR

38-44The 75th year of Indian independence is even more special to CSIR because CSIR enters its 80 years of gloriously serving the Indian society through S&T interventions

Understanding Communication Signals during Mycobacterial Latency through Predicted Genome-Wide Protein Interactions and Boolean Modeling

About 90% of the people infected with Mycobacterium tuberculosis carry latent bacteria that are believed to get activated upon immune suppression. One of the fundamental challenges in the control of tuberculosis is therefore to understand molecular mechanisms involved in the onset of latency and/or reactivation. We have attempted to address this problem at the systems level by a combination of predicted functional protein∶protein interactions, integration of functional interactions with large scale gene expression studies, predicted transcription regulatory network and finally simulations with a Boolean model of the network. Initially a prediction for genome-wide protein functional linkages was obtained based on genome-context methods using a Support Vector Machine. This set of protein functional linkages along with gene expression data of the available models of latency was employed to identify proteins involved in mediating switch signals during dormancy. We show that genes that are up and down regulated during dormancy are not only coordinately regulated under dormancy-like conditions but also under a variety of other experimental conditions. Their synchronized regulation indicates that they form a tightly regulated gene cluster and might form a latency-regulon. Conservation of these genes across bacterial species suggests a unique evolutionary history that might be associated with M. tuberculosis dormancy. Finally, simulations with a Boolean model based on the regulatory network with logical relationships derived from gene expression data reveals a bistable switch suggesting alternating latent and actively growing states. Our analysis based on the interaction network therefore reveals a potential model of M. tuberculosis latency

Dynamic Changes in Protein Functional Linkage Networks Revealed by Integration with Gene Expression Data

Response of cells to changing environmental conditions is governed by the dynamics of intricate biomolecular interactions. It may be reasonable to assume, proteins being the dominant macromolecules that carry out routine cellular functions, that understanding the dynamics of protein∶protein interactions might yield useful insights into the cellular responses. The large-scale protein interaction data sets are, however, unable to capture the changes in the profile of protein∶protein interactions. In order to understand how these interactions change dynamically, we have constructed conditional protein linkages for Escherichia coli by integrating functional linkages and gene expression information. As a case study, we have chosen to analyze UV exposure in wild-type and SOS deficient E. coli at 20 minutes post irradiation. The conditional networks exhibit similar topological properties. Although the global topological properties of the networks are similar, many subtle local changes are observed, which are suggestive of the cellular response to the perturbations. Some such changes correspond to differences in the path lengths among the nodes of carbohydrate metabolism correlating with its loss in efficiency in the UV treated cells. Similarly, expression of hubs under unique conditions reflects the importance of these genes. Various centrality measures applied to the networks indicate increased importance for replication, repair, and other stress proteins for the cells under UV treatment, as anticipated. We thus propose a novel approach for studying an organism at the systems level by integrating genome-wide functional linkages and the gene expression data