Human embryonic stem cell differentiation into insulin secreting β‐cells for diabetes

hESC (human embryonic stem cells), when differentiated into pancreatic β ILC (islet‐like clusters), have enormous potential for the cell transplantation therapy for Type 1 diabetes. We have developed a five‐step protocol in which the EBs (embryoid bodies) were first differentiated into definitive endoderm and subsequently into pancreatic lineage followed by formation of functional endocrine β islets, which were finally matured efficiently under 3D conditions. The conventional cytokines activin A and RA (retinoic acid) were used initially to obtain definitive endoderm. In the last step, ILC were further matured under 3D conditions using amino acid rich media (CMRL media) supplemented with anti‐hyperglycaemic hormone‐Glp1 (glucagon‐like peptide 1) analogue Liraglutide with prolonged t_½ and Exendin 4. The differentiated islet‐like 3D clusters expressed bonafide mature and functional β‐cell markers‐PDX1 (pancreatic and duodenal homoeobox‐1), C‐peptide, insulin and MafA. Insulin synthesis de novo was confirmed by C‐peptide ELISA of culture supernatant in response to varying concentrations of glucose as well as agonist and antagonist of functional 3D β islet cells in vitro. Our results indicate the presence of almost 65% of insulin producing cells in 3D clusters. The cells were also found to ameliorate hyperglycaemia in STZ (streptozotocin) induced diabetic NOD/SCID (non‐obese diabetic/severe combined immunodeficiency) mouse up to 96 days of transplantation. This protocol provides a basis for 3D in vitro generation of long‐term in vivo functionally viable islets from hESC.     

Sequential utilization of substrates by Pseudomonas putida CSV86: signatures of intermediate metabolites and online measurements

Pseudomonas putida CSV86 preferentially utilizes aromatics over glucose and co-metabolizes them with organic acids. On aromatics plus glucose, CSV86 utilized aromatics first with concomitant appearance of transient metabolites such as salicylate, benzaldehyde and benzoate. Citrate was the main extracellular metabolite observed during glucose uptake. The strain showed simultaneous utilization of organic acids and aromatic compounds. Based on the metabolite analysis and growth profiles, we hypothesize that the repression of glucose utilization could be due to organic acid intermediates generated from aromatic compound metabolism. The online measurements indicate the instantaneous metabolic state of the culture. For example, the CO₂ evolution and agitation speed show peak values during the two growth phases in the diauxic growth while dissolved oxygen values show decrease at the corresponding durations. These measurements correlated well with the offline measurements but provided a better time resolution of the process.     

Horseradish peroxidase catalyzed degradation of industrially important dyes.

Horseradish peroxidase (HRP) is known to degrade certain recalcitrant organic compounds such as phenol and substituted phenols. Here, for the first time we have shown HRP to be effective in degrading and precipitating industrially important azo dyes. For Remazol blue, the enzyme activity was found to be far better at pH 2.5 than at neutral pH. In addition, Remazol blue acts as a strong competitive inhibitor of HRP at neutral pH. Horseradish peroxidase shows broad substrate specificity toward a variety of azo dyes. Kinetic constants (K(m)(app) and V(max)(app)) for two different dyes have been determined. In addition to providing a systematic analysis of the potential of HRP in degradation of dyes, this study opens up a new area on exploration of commercial dyes as inhibitors of enzymes. 2001 John Wiley & Sons, Inc.     

Clustering of protein structural fragments reveals modular building block approach of nature

Structures of peptide fragments drawn from a protein can potentially occupy a vast conformational continuum. We co-ordinatize this conformational space with the help of geometric invariants and demonstrate that the peptide conformations of the currently available protein structures are heavily biased in favor of a finite number of conformational types or structural building blocks. This is achieved by representing a peptides' backbone structure with geometric invariants and then clustering peptides based on closeness of the geometric invariants. This results in 12,903 clusters, of which 2207 are made up of peptides drawn from functionally and/or structurally related proteins. These are termed "functional" clusters and provide clues about potential functional sites. The rest of the clusters, including the largest few, are made up of peptides drawn from unrelated proteins and are termed "structural" clusters. The largest clusters are of regular secondary structures such as helices and beta strands as well as of beta hairpins. Several categories of helices and strands are discovered based on geometric differences. In addition to the known classes of loops, we discover several new classes, which will be useful in protein structure modeling. Our algorithm does not require assignment of secondary structure and, therefore, overcomes the limitations in loop classification due to ambiguity in secondary structure assignment at loop boundaries.     

Metabolic modeling for multi-objective optimization of ethanol production in a Synechocystis mutant

Cyanobacteria have potential to produce drop-in bio-fuels such as ethanol via photoautotrophic metabolism. Although model cyanobacterial strains have been engineered to produce such products, systematic metabolic engineering studies to identify optimal strains for the same have not been performed. In this work, we identify optimal ethanol producing mutants corresponding to appropriate gene deletions that result in a suitable redirection in the carbon flux. In particular, we systematically simulate exhaustive single and double gene deletions considering a genome scale metabolic model of a mutant strain of the unicellular cyanobacterium Synechocystis species strain PCC 6803. Various optimization based metabolic modeling techniques, such as flux balance analysis (FBA), method of minimization of metabolic adjustment (MOMA) and regulatory on/off minimization (ROOM) were used for this analysis. For single gene deletion MOMA simulations, the Pareto front with biomass and ethanol fluxes as the two objectives to be maximized was obtained and analyzed. Points on the Pareto front represent maximal utilization of resources constrained by substrate uptake thereby representing an optimal trade-off between the two fluxes. Pareto analysis was also performed for double gene deletion MOMA and single and double gene deletion ROOM simulations. Based on these analyses, two mutants, with combined gene deletions in ethanol and purine metabolism pathways, were identified as promising candidates for ethanol production. The relevant genes were adk, pta and ackA. An ethanol productivity of approximately 0.15 mmol/(gDW h) was predicted for these mutants which appears to be reasonable based on experimentally reported values in literature for other strains.     

Distribution of live and dead cells in pellets of an actinomycete Amycolatopsis balhimycina and its correlation with balhimycin productivity

Secondary metabolites such as antibiotics are typically produced by actinomycetes as a response to growth limiting stress conditions. Several studies have shown that secondary metabolite production is correlated with changes observed in actinomycete pellet morphology. Therefore, we investigated the correlation between the production of balhimycin and the spatio-temporal distribution of live and dead cells in pellets of Amycolatopsis balhimycina in submerged cultures. To this end, we used laser scanning confocal microscopy to analyze pellets from balhimycin producing and nonproducing media containing 0.2 and 1.0 g l^?1 of potassium di-hydrogen phosphate, respectively. We observed a substantially higher fraction of live cells in pellets from cultures yielding larger amounts of balhimycin. Moreover, in media that resulted in no balhimycin production, the pellets exhibit an initial death phase which commences from the centre of the pellet and extends in the radial direction. A second growth phase was observed in these pellets, where live mycelia are seen to appear in the dead core of the pellets. This secondary growth was absent in pellets from media producing higher amounts of balhimycin. These results suggest that distribution of live and dead cells and its correlation with antibiotic production in the non-sporulating A. balhimycina differs markedly than that observed in Streptomycetes.     

Protein local conformations arise from a mixture of Gaussian distributions

The classical approaches for protein structure prediction rely either on homology of the protein sequence with a template structure or on ab initio calculations for energy minimization. These methods suffer from disadvantages such as the lack of availability of homologous template structures or intractably large conformational search space, respectively. The recently proposed fragment library based approaches first predict the local structures,which can be used in conjunction with the classical approaches of protein structure prediction. The accuracy of the predictions is dependent on the quality of the fragment library. In this work, we have constructed a library of local conformation classes purely based on geometric similarity. The local conformations are represented using Geometric Invariants, properties that remain unchanged under transformations such as translation and rotation, followed by dimension reduction via principal component analysis. The local conformations are then modeled as a mixture of Gaussian probability distribution functions (PDF). Each one of the Gaussian PDF's corresponds to a conformational class with the centroid representing the average structure of that class. We find 46 classes when we use an octapeptide as a unit of local conformation. The protein 3-D structure can now be described as a sequence of local conformational classes. Further, it was of interest to see whether the local conformations can be predicted from the amino acid sequences. To that end,we have analyzed the correlation between sequence features and the conformational classes.