The safety of drinking water is essential to our health. In this context, the mutagenicity of water needs to be checked strictly. However, from the methodological limit, the lower concentration (less than parts per million) of mutagenicity could not be detected, though there have been of interest in the effect of less concentration mutagens. Here, we describe a highly sensitive mutation assay that detects mutagens at the ppb level, termed genome profiling-based mutation assay (GPMA). This consists of two steps; (i) Escherichia coli culture in the medium with/without mutagens and (ii) Genome profiling (GP) method (an integrated method of random PCR, temperature gradient gel electrophoresis and computer-aided normalization). Owing to high sensitivity of this method, very low concentration of mutagens in tap water could be directly detected without introducing burdensome concentration processes, enabling rapid measurement of low concentration samples. Less expectedly, all of the tap waters tested (22 samples) were shown to be significantly mutagenic while mineral waters were not. Resultantly, this article informs two facts that the GPMA method is competent to measure the mutagenicity of waters directly and the experimental results supported the former reports that the city tap waters contain very low level of mutagenicity reagent trihalomethanes.

The application of signal processing techniques for identification of exons in Deoxyribonucleic acid (DNA) sequence is a challenging task. The objective of this paper is to introduce a combinational window approach for locating exons in DNA sequence. In contrast to the traditional single window function for evaluation of short time Fourier transform (STFT), this work proposes a novel method for evaluating STFT coefficients using a combinational window function comprising of Gaussian, Lanczos and Chebyshev (GLC) windows. The chosen combinational window GLC has the highest relative side lobe attenuation values compared to other window functions introduced by various researchers. The proposed algorithm incorporates GLC window function for evaluating STFT coefficients and in the design of FIR bandpass filter. Simulation results revealed its effectiveness in improving the evaluation parameters like Sensitivity, Specificity, Accuracy, Area under curve (AUC), Discrimination Measure (DM). Furthermore, the proposed algorithm has been applied successfully to some universal benchmark datasets like C. elegans, Homosapiens, etc., The proposed method has shown to be an efficient approach for the prediction of protein coding regions compared to other existing methods. All the simulations are done using the MATLAB 2016a.

Familial clustering without any prerequisite knowledge becomes often necessary in Behavioral Science, and forensic studies in case of great disasters like Tsunami and earthquake requiring body-identification without any usable information. However, there has been no well-established method for this purpose although conventional ones such as short tandem repeats (STR) and single nucleotide polymorphism (SNP), which might be applied with toil and moil to some extent. In this situation, we could find that the universal genome distance-measuring method genome profiling (GP), which is made up of three elemental techniques; random PCR, micro-temperature gradient gel electrophoresis (μTGGE), and computer processing for normalization, can do this purpose with ease when applied to mouse families. We also confirmed that the sequencing approach based on the ccgf (commonly conserved genetic fragment appearing in the genome profile) was not completely discriminative in this case. This is the first demonstration that the familial clustering can be attained without a priori sequence information to the level of discriminating strains and sibling relationships. This method can complement the conventional approaches in preliminary familial clustering.

Genome profiling-based mutation assay (GPMA) is, to date, the only DNA sequence-based mutation assay that directly measures DNA alterations induced by mutagens. Here, the all-important congruence of mutagen assignment between DNA-based GPMA and the phenotype-based Ames test (the gold standard of mutagen assays) was confirmed qualitatively and semi-quantitatively by means of 94 chemical species (including previously examined 64). The high sensitivity (on the order of 10 ppb) and reproducibility of GPMA were also corroborated by the match between virtually independent experiments conducted in the distant past (10 years ago) and recently. Meanwhile, a standard experimental framework was established: the conditions of 100 parts per billion (ppb) concentration of a chemical and 15-generation culture of Escherichia coli. Moreover, a mammalian cell line (NIH 3T3) was shown to be suitable as a tester organism for the GPMA approach. Preliminary experimental results suggested that this approach can provide a qualitatively equivalent and quantitatively different mutagen assay results relative to the bacteria-based GPMA (renamed as bGPMA). This finding confirmed the effectiveness of the GPMA approach and indicates that mGPMA is a promising way to detect mammalian-cell mutagens.