Pollution of various environmental matrices by antibiotic resistance genes (ARGs) has become a growing threat to human health. For the quantitative analysis of the presence of ARGs, there is a need for sensitive and robust qPCR assays which can detect various genes from different types of DNA extracts. Fourteen ARGs were selected as target genes in this study including: blaTEM, blaOXA-1 and blaCTX-M coded for resistance to β-lactams; ermB coded for macrolides; tetA, tetG, tetM, tetQ, tetW and tetX coded for tetracyclines; sul I and sul II coded for sulfonamides; drfA1 and drfA12 coded for trimethoprim; integron gene intI 1 and intI 2. Chemically synthesized double-stranded gene fragments were modified using molecular biology methods and used as real-time PCR standards as well as to establish in-house qPCR assays. The ermB gene from a naturally occurring plasmid was used to compare the performance of qPCR assay with the chemically synthesized ermB. Additionally, environmental water, soil and faeces samples were used to validate the established qPCR assays. Importantly, the study proves the usefulness of rapidly synthesized oligonucleotides serving as qPCR standards for ARG analysis and provides comparable sensitivity and reliability to a traditional amplicon standard.
BackgroundThe entire collection of genetic information resides within the chromosomes, which themselves reside within almost every cell nucleus of eukaryotic organisms. Each individual chromosome is found to have its own preferred three-dimensional (3D) structure independent of the other chromosomes. The structure of each chromosome plays vital roles in controlling certain genome operations, including gene interaction and gene regulation. As a result, knowing the structure of chromosomes assists in the understanding of how the genome functions. Fortunately, the 3D structure of chromosomes proves possible to construct through computational methods via contact data recorded from the chromosome. We developed a unique computational approach based on optimization procedures known as adaptation, simulated annealing, and genetic algorithm to construct 3D models of human chromosomes, using chromosomal contact data.ResultsOur models were evaluated using a percentage-based scoring function. Analysis of the scores of the final 3D models demonstrated their effective construction from our computational approach. Specifically, the models resulting from our approach yielded an average score of 80.41 %, with a high of 91 %, across models for all chromosomes of a normal human B-cell. Comparisons made with other methods affirmed the effectiveness of our strategy. Particularly, juxtaposition with models generated through the publicly available method Markov chain Monte Carlo 5C (MCMC5C) illustrated the outperformance of our approach, as seen through a higher average score for all chromosomes. Our methodology was further validated using two consistency checking techniques known as convergence testing and robustness checking, which both proved successful.ConclusionsThe pursuit of constructing accurate 3D chromosomal structures is fueled by the benefits revealed by the findings as well as any possible future areas of study that arise. This motivation has led to the development of our computational methodology. The implementation of our approach proved effective in constructing 3D chromosome models and proved consistent with, and more effective than, some other methods thereby achieving our goal of creating a tool to help advance certain research efforts. The source code, test data, test results, and documentation of our method, Gen3D, are available at our sourceforge site at: http://sourceforge.net/projects/gen3d/.
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