Biomedical subjects

Pramod P Wangikar

Publications and source records attributed to Pramod P Wangikar.

14 recordsLinked to original sources

PubMed2006

Hierarchical amino acid utilization and its influence on fermentation dynamics: rifamycin B fermentation using Amycolatopsis mediterranei S699, a case study.

BACKGROUND: Industrial fermentation typically uses complex nitrogen substrates which consist of mixture of amino acids. The uptake of amino acids is known to be mediated by several amino acid transporters with certain preferences. However, models to predict this preferential uptake are not available. We present the stoichiometry for the utilization of amino acids as a sole carbon and nitrogen substrate or along with glucose as an additional carbon source. In the former case, the excess nitrogen provided by the amino acids is excreted by the organism in the form of ammonia. We have developed a cybernetic model to predict the sequence and kinetics of uptake of amino acids. The model is based on the assumption that the growth on a specific substrate is dependent on key enzyme(s) responsible for the uptake and assimilation of the substrates. These enzymes may be regulated by mechanisms of nitrogen catabolite repression. The model hypothesizes that the organism is an optimal strategist and invests resources for the uptake of a substrate that are proportional to the returns. RESULTS: Stoichiometric coefficients and kinetic parameters of the model were estimated experimentally for Amycolatopsis mediterranei S699, a rifamycin B overproducer. The model was then used to predict the uptake kinetics in a medium containing cas amino acids. In contrast to the other amino acids, the uptake of proline was not affected by the carbon or nitrogen catabolite repression in this strain. The model accurately predicted simultaneous uptake of amino acids at low cas concentrations and sequential uptake at high cas concentrations. The simulated profile of the key enzymes implies the presence of specific transporters for small groups of amino acids. CONCLUSION: The work demonstrates utility of the cybernetic model in predicting the sequence and kinetics of amino acid uptake in a case study involving Amycolatopsis mediterranei, an industrially important organism. This work also throws some light on amino acid transporters and their regulation in A. mediterranei. Further, cybernetic model based experimental strategy unravels formation and utilization of ammonia as well as its inhibitory role during amino acid uptake. Our results have implications for model based optimization and monitoring of other industrial fermentation processes involving complex nitrogen substrate.

Journal Article↗

PubMed2006

Phase shifts in the stoichiometry of rifamycin B fermentation and correlation with the trends in the parameters measured online.

Antibiotic fermentation processes are raw material cost intensive and the profitability is greatly dependent on the product yield per unit substrate consumed. In order to reduce costs, industrial processes use organic nitrogen substrates (ONS) such as corn steep liquor and yeast extract. Thus, although the stoichiometric analysis is the first logical step in process development, it is often difficult to achieve due to the ill-defined nature of the medium. Here, we present a black-box stoichiometric model for rifamycin B production via Amycolatopsis mediterranei S699 fermentation in complex multi-substrate medium. The stoichiometric coefficients have been experimentally evaluated for nine different media compositions. The ONS was quantified in terms of the amino acid content that it provides. Note that the black box stoichiometric model is an overall result of the metabolic reactions that occur during growth. Hence, the observed stoichiometric coefficients are liable to change during the batch cycle. To capture the shifts in stoichiometry, we carried out the stoichiometric analysis over short intervals of 8-16 h in a batch cycle of 100-200 h. An error analysis shows that there are no systematic errors in the measurements and that there are no unaccounted products in the process. The growth stoichiometry shows a shift from one substrate combination to another during the batch cycle. The shifts were observed to correlate well with the shifts in the trends of pH and exit carbon dioxide profiles. To exemplify, the ammonia uptake and nitrate uptake phases were marked by a decreasing pH trend and an increasing pH trend, respectively. Further, we find the product yield per unit carbon substrate to be greatly dependent on the nature of the nitrogen substrate. The analysis presented here can be readily applied to other fermentation systems that employ multi-substrate complex media.

Actinomycetales↗

PubMed2006

Substrate specificity of lipases in alkoxycarbonylation reaction: QSAR model development and experimental validation.

Although lipases are known to catalyze alkoxycarbonylation reactions in organic solvents, the existing knowledge base on their substrate specificity in alkoxycarbonylation reaction is sparse. Moreover, models to predict substrate specificity have not been reported. Here, we report the experimentally measured rate constants for 180 acyl donor-alcohol pairs and demonstrate the two-step synthesis of over 70 disubstituted carbonate products from simple precursors such as diphenyl carbonate and alcohols. The efficiency of synthesis was found to be dependent on the order of alcohol addition. This motivated the need to develop a model to predict lipase specificity in alkoxycarbonylation reactions. A partial least square model has been developed to correlate the reaction rate with (i) descriptors of alcohol for a fixed acyl donor, (ii) descriptors of acyl donor for a fixed alcohol, (iii) descriptors of both the acyl donor and the alcohol. The number of descriptors being far greater than the number of observations was a potential limitation in the model development. This was addressed by selecting a subset of descriptors using a systematic procedure based on (a) correlation among the descriptors and step-wise regression methodology, and (b) variable influence on projection methodology. The model was able to accurately predict the reaction rate and the optimal order of addition of alcohols in the two-step synthesis of disubstituted carbonates using the enzyme mixture. The descriptor subset and the relevant model would benefit the users of lipases in synthetic applications while the modeling strategy presented here can have applications in predicting specificity of other enzymes.

Alcohols↗

PubMed2006

A cybernetic model to predict the effect of freely available nitrogen substrate on rifamycin B production in complex media.

It is well-known that secondary metabolite production is repressed by excess nitrogen substrate available in the fermentation media. Although the nitrogen catabolite repression has been known, quantitative process models have not been reported to represent this phenomenon in complex medium. In this paper, we present a cybernetic model for rifamycin B production via Amycolatopsis mediterranei S699 in complex medium, which is typically used in industry. Nitrogen substrate is assumed to be present in two forms in the medium; available nitrogen (S(ANS)) such as free amino acids and unavailable nitrogen (S(UNS)) such as peptides and proteins. The model assumes that an inducible enzyme catalyzes the conversion of S(UNS) to S(ANS). Although S(ANS) is required for growth and product formation, high concentrations were found to inhibit rifamycin production. To experimentally validate the model, five different organic nitrogen sources were used that differ in the ratio of S(ANS)/S (UNS). The model successfully predicts higher rifamycin B productivity for nitrogen sources that contain lower initial S(ANS). The higher productivity is attributed to the sustained availability of S(ANS) at low concentration via conversion of S(UNS) to S(ANS), thereby minimizing the effects of nitrogen catabolite repression on rifamycin production. The model can have applications in model-based optimization of substrate feeding recipe and in monitoring and control of fed batch processes.

Actinomycetales↗

PubMed2006

Structured kinetic model to represent the utilization of multiple substrates in complex media during rifamycin B fermentation.

Industrial fermentations typically use media that are balanced with multiple substitutable substrates including complex carbon and nitrogen source. Yet, much of the modeling effort to date has mainly focused on defined media. Here, we present a structured model that accounts for growth and product formation kinetics of rifamycin B fermentation in a multi-substrate complex medium. The phenomenological model considers the organism to be an optimal strategist with an in-built mechanism that regulates the sequential and simultaneous uptake of the substrate combinations. This regulatory process is modeled by assuming that the uptake of a substrate depends on the level of a key enzyme or a set of enzymes, which may be inducible. Further, the fraction of flux through a given metabolic branch is estimated using a simple multi-variable constrained optimization. The model has the typical form of Monod equation with terms incorporating multiple limiting substrates and substrate inhibition. Several batch runs were set up with varying initial substrate concentrations to estimate the kinetic parameters for the rifamycin overproducer strain Amycolatopsis mediterranei S699. Glucose and ammonium sulfate (AMS) demonstrated significant substrate inhibition toward growth as well as product formation. The model correctly predicts the experimentally observed regulated simultaneous uptake of the substitutable substrate combinations under different fermentation conditions. The modeling results may have applications in the optimization and control of rifamycin B fermentation while the modeling strategy presented here would be applicable to other industrially important fermentations.

Actinomycetales↗

PubMed2006

Gaussian mixture modeling of alpha-helix subclasses: structure and sequence variations.

Classification of helical structures and identification of class specific sequence features is of interest for protein structure modeling. We use geometric invariant based method to first select helix-like local conformations. These conformations are mapped in a principal component space and subjected to Gaussian mixture modeling. The largest Gaussian corresponds to the regular alpha-helix. Kinked helix and curved helix appear as a separate gaussians. Class conditional, position specific amino acid propensity analysis reveals striking difference among the three classes. In regular helix, proline propensity is significant only in the beginning and low in the rest of the region regardless of length of the helix. In kinked helix, the proline propensity has a sharp peak at the helix center, while in the curved helix, the proline propensity has a broad peak in the middle region.

Amino Acids↗

PubMed2005

A geometric invariant-based framework for the analysis of protein conformational space.

MOTIVATION: Characterization of the restricted nature of the protein local conformational space has remained a challenge, thereby necessitating a computationally expensive conformational search in protein modeling. Moreover, owing to the lack of unilateral structural descriptors, conventional data mining techniques, such as clustering and classification, have not been applied in protein structure analysis. RESULTS: We first map the local conformations in a fixed dimensional space by using a carefully selected suite of geometric invariants (GIs) and then reduce the number of dimensions via principal component analysis (PCA). Distribution of the conformations in the space spanned by the first four PCs is visualized as a set of conditional bivariate probability distribution plots, where the peaks correspond to the preferred conformations. The locations of the different canonical structures in the PC-space have been interpreted in the context of the weights of the GIs to the first four PCs. Clustering of the available conformations reveals that the number of preferred local conformations is several orders of magnitude smaller than that suggested previously. SUPPLEMENTARY INFORMATION: www.it.iitb.ac.in/~ashish/bioinfo2005/.

Algorithms↗

PubMed2004

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.

Algorithms↗

PubMed2004

Optimization of rifamycin B fermentation in shake flasks via a machine-learning-based approach.

Rifamycin B is an important polyketide antibiotic used in the treatment of tuberculosis and leprosy. We present results on medium optimization for Rifamycin B production via a barbital insensitive mutant strain of Amycolatopsis mediterranei S699. Machine-learning approaches such as Genetic algorithm (GA), Neighborhood analysis (NA) and Decision Tree technique (DT) were explored for optimizing the medium composition. Genetic algorithm was applied as a global search algorithm while NA was used for a guided local search and to develop medium predictors. The fermentation medium for Rifamycin B consisted of nine components. A large number of distinct medium compositions are possible by variation of concentration of each component. This presents a large combinatorial search space. Optimization was achieved within five generations via GA as well as NA. These five generations consisted of 178 shake-flask experiments, which is a small fraction of the search space. We detected multiple optima in the form of 11 distinct medium combinations. These medium combinations provided over 600% improvement in Rifamycin B productivity. Genetic algorithm performed better in optimizing fermentation medium as compared to NA. The Decision Tree technique revealed the media-media interactions qualitatively in the form of sets of rules for medium composition that give high as well as low productivity.

Actinomycetales↗

PubMed2003

Parameterization and classification of the protein universe via geometric techniques.

We present a scheme for the classification of 3487 non-redundant protein structures into 1207 non-hierarchical clusters by using recurring structural patterns of three to six amino acids as keys of classification. This results in several signature patterns, which seem to decide membership of a protein in a functional category. The patterns provide clues to the key residues involved in functional sites as well as in protein-protein interaction. The discovered patterns include a "glutamate double bridge" of superoxide dismutase, the functional interface of the serine protease and inhibitor, interface of homo/hetero dimers, and functional sites of several enzyme families. We use geometric invariants to decide superimposability of structural patterns. This allows the parameterization of patterns and discovery of recurring patterns via clustering. The geometric invariant-based approach eliminates the computationally explosive step of pair-wise comparison of structures. The results provide a vast resource for the biologists for experimental validation of the proposed functional sites, and for the design of synthetic enzymes, inhibitors and drugs.

Algorithms↗

PubMed2003

Combined sequence and structure analysis of the fungal laccase family.

Plant and fungal laccases belong to the family of multi-copper oxidases and show much broader substrate specificity than other members of the family. Laccases have consequently been of interest for potential industrial applications. We have analyzed the essential sequence features of fungal laccases based on multiple sequence alignments of more than 100 laccases. This has resulted in identification of a set of four ungapped sequence regions, L1-L4, as the overall signature sequences that can be used to identify the laccases, distinguishing them within the broader class of multi-copper oxidases. The 12 amino acid residues in the enzymes serving as the copper ligands are housed within these four identified conserved regions, of which L2 and L4 conform to the earlier reported copper signature sequences of multi-copper oxidases while L1 and L3 are distinctive to the laccases. The mapping of regions L1-L4 on to the three-dimensional structure of the Coprinus cinerius laccase indicates that many of the non-copper-ligating residues of the conserved regions could be critical in maintaining a specific, more or less C-2 symmetric, protein conformational motif characterizing the active site apparatus of the enzymes. The observed intraprotein homologies between L1 and L3 and between L2 and L4 at both the structure and the sequence levels suggest that the quasi C-2 symmetric active site conformational motif may have arisen from a structural duplication event that neither the sequence homology analysis nor the structure homology analysis alone would have unraveled. Although the sequence and structure homology is not detectable in the rest of the protein, the relative orientation of region L1 with L2 is similar to that of L3 with L4. The structure duplication of first-shell and second-shell residues has become cryptic because the intraprotein sequence homology noticeable for a given laccase becomes significant only after comparing the conservation pattern in several fungal laccases. The identified motifs, L1-L4, can be useful in searching the newly sequenced genomes for putative laccase enzymes.

Amino Acid Sequence↗

PubMed2003

Functional sites in protein families uncovered via an objective and automated graph theoretic approach.

We report a method for detection of recurring side-chain patterns (DRESPAT) using an unbiased and automated graph theoretic approach. We first list all structural patterns as sub-graphs where the protein is represented as a graph. The patterns from proteins are compared pair-wise to detect patterns common to a protein pair based on content and geometry criteria. The recurring pattern is then detected using an automated search algorithm from the all-against-all pair-wise comparison data of proteins. Intra-protein pattern comparison data are used to enable detection of patterns recurring within a protein. A method has been proposed for empirical calculation of statistical significance of recurring pattern. The method was tested on 17 protein sets of varying size, composed of non-redundant representatives from SCOP superfamilies. Recurring patterns in serine proteases, cysteine proteases, lipases, cupredoxin, ferredoxin, ferritin, cytochrome c, aspartoyl proteases, peroxidases, phospholipase A2, endonuclease, SH3 domain, EF-hand and lectins show additional residues conserved in the vicinity of the known functional sites. On the basis of the recurring patterns in ferritin, EF-hand and lectins, we could separate proteins or domains that are structurally similar yet different in metal ion-binding characteristics. In addition, novel recurring patterns were observed in glutathione-S-transferase, phospholipase A2 and ferredoxin with potential structural/functional roles. The results are discussed in relation to the known functional sites in each family. Between 2000 and 50,000 patterns were enumerated from each protein with between ten and 500 patterns detected as common to an evolutionarily related protein pair. Our results show that unbiased extraction of functional site pattern is not feasible from an evolutionarily related protein pair but is feasible from protein sets comprising five or more proteins. The DRESPAT method does not require a user-defined pattern, size or location of the pattern and therefore, has the potential to uncover new functional sites in protein families.

Algorithms↗

PubMedDate not supplied

Method for lipase-catalyzed carbonate synthesis via one- and two-step alkoxycarbonylation reactions.

Lipase-catalyzed alkoxycarbonylation methods offer potential advantages over the currently practiced industrial scale chemical synthesis of carbonates. We report a method for synthesis of organic carbonates via lipase-catalyzed alkoxycarbonylation between diphenyl carbonate and various alcohols in hexane. This method utilizes precursors that are readily available and does not involve extensive purification of the intermediate. In a two-step process, the two phenyl groups of diphenyl carbonate were substituted by two alcohol nucleophiles. The approach was demonstrated for two-step synthesis of 14 different disubstituted carbonate products. The rates of reaction for the two steps were much slower if the order of nucleophile addition was reversed. Under optimal conditions, complete conversion of diphenyl carbonate occurred within 8-15 h at 50 degrees C, which is a significant improvement from 50-90 h at 24 degrees C. A kinetic model for the alkoxycarbonylation reaction was derived based on the Michaelis-Menten equation, which simplified to first-order kinetics at low and equimolar concentration of substrates.

Alcohols↗

PubMedDate not supplied

An optimized method for Aspergillus niger spore production on natural carrier substrates.

Aspergillus niger spores have wide ranging applications in the fermentation industry as well as in wastewater treatment. We present an optimized method for production of A. niger spores on natural substrates such as rice, split pea, and millet. The specific productivity (number of spores per gram of dry substrate) was 31-fold greater and volumetric productivity was 750-fold greater compared to agar slopes. The important process variables were incubation temperature, moisture content, and inoculum quantity. We find that the optimal condition for total spore count is different from the viable spore count for millet. The optimum lies in a narrow region defined by the process parameters. Of the three substrates tested split pea gave the highest specific spore productivity of 3.1 x 10(10) spores per gram of dry substrate. This is the first report of systematic study on the effect of process parameters on spore viability. The method of A. niger spore production on natural substrate appears advantageous as compared to the currently practiced method in terms of scale-up, cost, and ease of operation.

Aspergillus niger↗