Recent advances in molecular biological techniques and their relevance to pulmonary research

Impact of experiential learning among medical undergraduates: A randomized controlled trial

BACKGROUND

Experiential learning sessions as a teaching aid have been applied early in the medical undergraduate curriculum to improve the knowledge and inculcate research interest. We compared the ability of 1st-year medical undergraduates to answer the molecular biology questions among those who had attended the experiential learning sessions of molecular biology techniques versus those who did not attend.

SUBJECTS AND METHODS

A randomized controlled trial was carried out with 200 1st-year medical undergraduates, among whom 69 students were selected by simple random sampling for the demonstration of the molecular biology techniques, such as isolation of genomic DNA, polymerase chain reaction, cell culture techniques, western blotting, and high-performance liquid chromatography for 1-week duration. Student's feedback was collected on a five-point Likert sc ale at the end of the session to understand how they agree or disagree with a particular statement. The content validity rate (CVR) and content validity index (CVI) of the questionnaire were determined, and its internal consistency was examined by Cronbach's alpha. The internal assessment marks of these students, valued by faculty who were blinded to their training sessions, were compared with the rest of the 131 students by independent t-test to know the outcome of these experiential learning sessions.

RESULTS

On CVR and CVI assessment, all the questions scored more than 0.70 and 0.85, respectively. Cronbach's alpha for the whole questionnaire was 0.85. Student's feedback indicated that these sessions did complement the cognitive skills acquired for these techniques. We also found a statistically significant improvement (P = 0.006) in the examination performance between the students who attended versus those who did not attend the experiential learning sessions.

CONCLUSION

Experiential learning, through demonstration and hands-on experience, enhance d the learning of molecular biology techniques among 1st-year medical undergraduates.

A multiscale road map of cancer spheroids – incorporating experimental and mathematical modelling to understand cancer progression

Computational models represent a highly suitable framework, not only for testing biological hypotheses and generating new ones but also for optimising experimental strategies. As one surveys the literature devoted to cancer modelling, it is obvious that immense progress has been made in applying simulation techniques to the study of cancer biology, although the full impact has yet to be realised. For example, there are excellent models to describe cancer incidence rates or factors for early disease detection, but these predictions are unable to explain the functional and molecular changes that are associated with tumour progression. In addition, it is crucial that interactions between mechanical effects, and intracellular and intercellular signalling are incorporated in order to understand cancer growth, its interaction with the extracellular microenvironment and invasion of secondary sites. There is a compelling need to tailor new, physiologically relevant in silico models that are specialised for particular types of cancer, such as ovarian cancer owing to its unique route of metastasis, which are capable of investigating anti-cancer therapies, and generating both qualitative and quantitative predictions. This Commentary will focus on how computational simulation approaches can advance our understanding of ovarian cancer progression and treatment, in particular, with the help of multicellular cancer spheroids, and thus, can inform biological hypothesis and experimental design.

In vitro reporter gene transfection via plasmid DNA delivered by metered dose inhaler

Aerosolised DNA administration could potentially advance the treatment of inheritable lung diseases, lung malignancies and provide genetic immunisation against infection. Jet nebulisation, the current standard for introducing DNA formulations into the lung, is inherently inefficient. Pressurised metered dose inhalers (pMDIs) offer a potentially more efficacious and convenient alternative, especially for repeat administration. We aim to modify a novel low-energy nanotechnology process to prepare surfactant-coated pDNA nanoparticles for pulmonary gene delivery via a pMDI. Water-in-oil microemulsions containing green fluorescent protein reporter plasmid were snap-frozen and lyophilised. Lyophilised pDNA, in some cases following a surfactant wash, was incorporated into pMDIs with hydrofluoroalkane 134a (HFA134a) propellant and ethanol as cosolvent. To assess biological functionality, A549 human lung epithelial cells were exposed to aerosolised pDNA particles in the presence of dioleoyl-trimethylammonium propane (DOTAP). Transfection studies demonstrated that pDNA biological functionality was maintained following aerosolisation. In vitro toxicity assays (MTT) showed no significant cell viability loss following aerosolised pDNA treatment. We have demonstrated that pDNA particles can be incorporated into an HFA134a formulation and aerosolised using a standard valve and actuator. Particles prepared by this novel process have potential for stable and efficient delivery of pDNA to the lower respiratory tract via standard pMDI technology.

Studies on aerosol delivery of plasmid DNA using a mesh nebulizer

Aerosol delivery of plasmid DNA therapeutic solutions is promising for the treatment of respiratory diseases. However, it poses challenges, most significantly the need to protect the delicate supercoiled (sc) structure of plasmid during aerosolization. Nebulizers for liquid aerosolization using meshes appear a better method for delivery than conventional jet and ultrasonic nebulizers. This paper explores their application to the delivery of plasmid DNA. A computational fluid dynamics model of the dynamics of fluid flow through the nozzle of the MicroAIR mesh nebulizer indicated high strain rates (>10(5) s(-1)) near the nozzle exit capable of causing damage to the shear-sensitive plasmid DNA. Knowledge of the strain rates predicted using CFD and molecule size determined using atomic force microscopy (AFM) enabled estimation of the hydrodynamic force and whether damage of shear-sensitive therapeutics was likely. Plasmids of size 5.7 and 20 kb were aerosolized in the mesh nebulizer. The sc structure of the 5.7-kb plasmid was successfully delivered without damage, while aerosolization of the 20-kb plasmid led to disintegration of the pDNA sc structure as observed in AFM. Subsequent formulation of the sc 20-kb plasmid with PEI resulted in successful aerosol delivery. The maximum hydrodynamic forces computed for the aerosolization of structures of the size of 5.7-kb and PEI formulated 20-kb plasmids were less than the forces reported to damage the structure of double-stranded DNA. A combination of CFD analysis and structure analysis may be used to predict successful aerosol delivery in such a mesh nebulizer.

Glucocorticoid regulation of human eosinophil gene expression

Molecular analysis of steroid-regulated gene expression in freshly isolated human eosinophils is difficult due to the inherent high rate of spontaneous apoptosis and elevated levels of endogenous ribonucleases. To circumvent these limitations, we determined if the human eosinophilic cell line EoL-1 could serve as an in vitro model of glucocorticoid signaling. We found by optimizing growth conditions in low serum-containing media that dexamethasone (Dex) treatment of EoL-1 cells induced an apoptotic pathway that was inhibited by interleukin-5 (IL-5). Moreover, gene expression profiling using RNA from untreated EoL-1 cells and from freshly isolated human eosinophils identified 380 commonly expressed genes, including the eosinophil markers granule major basic protein, prostaglandin-endoperoxide synthase 1 and arachidonate 15-lipoxygenase. Expression profiling was performed using EoL-1 cells that had been treated with dexamethasone for 0, 4, 12, 24 and 48h identifying 162 genes as differentially expressed. Two of the most highly upregulated genes based on expression profiling were the transcription factor Ets-2 and the MHC Class II genes (Q, R, and P). Expression of these genes in EoL-1 cells was shown to be dexamethasone-induced at the RNA and protein levels which is consistent with the known function of Ets-2 in controlling cell cycle progression and the role of MHC Class II antigens in mediating eosinophil functions.

Genomics and proteomics: the new millennium of drug discovery and development

One of the most pressing issues facing the pharmaceutical and biotechnology industry is the tremendous dropout rate of lead drug candidates. Over the last two decades, several new genomic technologies have been developed in hopes of addressing the issues of target identification and lead candidate optimization. Gene expression microarray is one of these technologies and this review describes the four main formats, which are currently available: (a) cDNA; (b) oligonucleotide; (c) electrokinetic; and (d) fiberoptic. Many of these formats have been developed with the goal of screening large numbers of genes. Recently, a high-throughput array format has been developed where a large number of samples can be assayed using arrays in parallel. In addition, focusing on gene expression may be only one avenue in preventing lead candidate failure. Proteomics or the study of protein expression may also play a role. Two-dimensional polyacrylamide gel electrophoresis (2-DE) coupled with mass spectroscopy has been the most widely accepted format to study protein expression. However, protein microarrays are now being developed and modified to a high-throughput screening format. Examples of several gene and protein expression studies as they apply to drug discovery and development are reviewed. These studies often result in large data sets. Examples of how several statistical methods (principal components analysis [PCA], clustering methods, Shannon entropy, etc.) have been applied to these data sets are also described. These newer genomic and proteomic technologies and their analysis and visualization methods have the potential to make the drug discovery and development process less costly and more efficient by aiding to select better target and lead candidates.