Methods: We performed whole-genome sequencing on 121 H. pylori clinical strains, among which 73 were metronidazole-resistant. Sequence-alignment analysis of core protein clusters derived from clinical strains containing full-length RdxA was performed. Variable sites in each alignment were statistically compared between the resistant and susceptible groups to determine candidate genes along with their respective amino-acid changes that may account for the development of metronidazole resistance in H. pylori.
Results: Resistance due to RdxA truncation was identified in 34% of metronidazole-resistant strains. Analysis of core protein clusters derived from the remaining 48 metronidazole-resistant strains and 48 metronidazole-susceptible identified four variable sites significantly associated with metronidazole resistance. These sites included R16H/C in RdxA, D85N in the inner-membrane protein RclC (HP0565), V265I in a biotin carboxylase protein (HP0370) and A51V/T in a putative threonylcarbamoyl-AMP synthase (HP0918).
Conclusions: Our approach identified new potential mechanisms for metronidazole resistance in H. pylori that merit further investigation.
METHODS: In the present study, 3D model of transketolase was constructed and its atomic characteristics revealed. Besides, molecular dynamic simulation of the protein at 310 K and 368 K deciphered transketolase may be a thermophilic protein as the structure does not distort even at elevated temperature. This study also used the protein at 310 K and 368 K resimulated back at 310 K environment.
RESULTS: The results revealed that the protein is stable at all condition which suggest that it has high capacity to adapt at different environment not only at high temperature but also from high temperature condition to low temperature where the structure remains unchanged while retaining protein function.
CONCLUSION: The thermostability properties of transketolase is beneficial for pharmaceutical industries as most of the drug making processes are at high temperature condition.
RESULTS: In this study we generated Whole Exome Sequencing (WES), Reduced Representation Bisulfite Sequencing (RRBS) and RNA sequencing (RNA-seq) data from samples with known mixtures of mouse and human DNA or RNA and from a cohort of human breast cancers and their derived PDTXs. We show that using an In silico Combined human-mouse Reference Genome (ICRG) for alignment discriminates between human and mouse reads with up to 99.9% accuracy and decreases the number of false positive somatic mutations caused by misalignment by >99.9%. We also derived a model to estimate the human DNA content in independent PDTX samples. For RNA-seq and RRBS data analysis, the use of the ICRG allows dissecting computationally the transcriptome and methylome of human tumour cells and mouse stroma. In a direct comparison with previously reported approaches, our method showed similar or higher accuracy while requiring significantly less computing time.
CONCLUSIONS: The computational pipeline we describe here is a valuable tool for the molecular analysis of PDTXs as well as any other mixture of DNA or RNA species.