Abhijeet Kate, Arpana G Panicker, Diana Writer, Giridharan P, Keshav K V Ramamoorthy, Saji George, Shailendra K Sonawane
Protoplast fusion and transformation: A tool for activation of latent gene clusters
In the quest to discover new bioactive leads for unmet medical needs, actinomycetes present a treasure trove of undiscovered molecules. The ability of actinomycetes to produce antibiotics and other bioactive secondary metabolites has been underestimated due to sparse studies of cryptic gene clusters. These gene clusters can be tapped to explore scaffolds hidden in them. The up-regulation of the dormant genes is one of the most important areas of interest in the bioactive compounds discovery from microbial resources. Genome shuffling is a powerful tool for the activation of such gene clusters. Lei Yu, et al.1, reported enhancement of the lactic acid production in Lactobacillus rhamnosus through genome shuffling brought about by protoplast fusion. D. A. Hopwood et al.2 suggested that an interspecific recombination between strains producing different secondary metabolites, generate producers of â€˜hybridâ€™ antibiotics. They also mentioned that an intraspecific fusion of actinomycetes protoplast bring about random and high frequency recombination. Protoplasts can also be used as recipients for isolated DNA, again in the presence of polyethylene glycol (PEG). In our study we had undertaken random genome shuffling by protoplast fusion of two, rather poorly expressed actinomycetes strains A (Figure 1) & B (Figure 2), mediated by PEG; and also by naked DNA transformation of Strain A protoplast with the DNA of Strain B. We generated eight protoplast fusants and seven transformants from parents considering their morphological difference from the two parent strains. These 15 recombinants were checked for their same colony morphologies for five generations to ensure phenotypic stability. Antibiotic resistance pattern was established by using antibiotic octodisc to generate a marker profile of the recombinants and the parent strains. Eight fusants (AP-18, AP-25, AP-2, AP-11, AP-14, AP-19, AP-11 and AP-27) and four transformants (TAP-30, TAP-31, TAP-32 and TAP-33) (Table 1) have shown a different antibiotic sensitivity pattern as compared to the parent strains. We envisage that these recombinants harbor shuffled gene clusters. To support array of conditions to express such shuffled/cryptic genes the recombinants were fermented in 11 different nutrient stress variants. The extracts generated were subjected to metabolite profiling by HPLC-ELSD, bioactivity screening for cytotoxicity and anti-infective capabilities. Two fusants AP-11 (Figure 3) and AP-25; one transformant TAP-32 (in growth media MBA-5 and MBA-7) displayed antifungal activity unlike parent strains (Table 2) Fusant AP-11 (Table 5) exhibited significant cell growth inhibition of five different cancer cell lines. The parents Strain A and Strain B did not exhibit any cell growth inhibition of these cell lines (Table 5). The metabolite profiling of fusant AP-11 and transformant TAP-32 was done by HPLC-ELSD. AP-11 showed the presence of five additional peaks (Figure 5 & Figure 6); TAP-32 extract from medium MBA-5 (Figure 7 & Figure 8) showed the presence of four additional peaks and TAP-32 extract from MBA-7 (Figure 9 & Figure 10) showed 14 additional peaks as compared to parent strains in similar medium and media controls. The study indicated that protoplast fusion and transformation have not only caused morphological changes but also shuffled genes responsible for synthesis of bioactive molecules. Further characterization of these new peaks is warranted.
Lalitha Subramanian, Ph.D.
Chief Scientific Officer & VP, Services at Scienomics, USA
Nanoscale Simulations – Tackling Form and Formulation Challenges in Drug Development and Drug Delivery
Lalitha Subramanian, Dora Spyriouni, Andreas Bick, Sabine Schweizer, and Xenophon Krokidis Scienomics
The discovery of a compound which is potent in activity against a target is a major milestone in Pharmaceutical and Biotech industry. However, a potent compound is only effective as a therapeutic agent when it can be administered such that the optimal quantity is transported to the site of action at an optimal rate. The active pharmaceutical ingredient (API) has to be tested for its physicochemical properties before the appropriate dosage form and formulation can be designed. Some of the commonly evaluated parameters are crystal forms and polymorphs, solubility, dissolution behavior, stability, partition coefficient, water sorption behavior, surface properties, particle size and shape, etc. Pharmaceutical development teams face the challenge of quickly and efficiently determining a number of properties with small quantities of the expensive candidate compounds. Recently the trend has been to screen these properties as early as possible and often the candidate compounds are not available in sufficient quantities. Increasingly, these teams are leveraging nanoscale simulations similar to those employed by drug discovery teams for several decades. Nanoscale simulations are used to predict the behavior using very little experimental data and only if this is promising further experiments are done. Another aspect where nanoscale simulations are being used in drug development and drug delivery is to get insights into the behavior of the system so that process failures can be remediated and formulation performance can be improved. Thus, the predictive screening and the in-depth understanding leads to experimental efficiency resulting in far-reaching business impacts.
With specific examples, this talk will focus on the different types of nanoscale simulations used to predict properties of the API in excipients and also provide insight into system behavior as a function of shelf life, temperature, mechanical stress, etc.