ABSTRACT
Drugs that block DNA replication prevent cell proliferation, which may result in anticancer activity. The latter is dependent on the drug's mode of action as well as on cell type-dependent responses to treatment. The inhibition of Cell division cycle 7-related protein kinase (CDC7), a key regulator of DNA replication, decreases the efficiency of origin firing and hampers the restarting of paused replication forks. Here, we show that upon prolonged CDC7 inhibition, breast-derived MCF10A cells progressively withdraw from the cell cycle and enter a reversible senescent-like state. This is characterised by the rewiring of the transcriptional programme with the induction of cytokine and chemokine expression and correlates with the accumulation of Cyclic GMP-AMP synthase (cGAS)-positive micronuclei. Importantly, cell fate depends on Cellular tumour antigen p53 (p53) function as cells no longer enter senescence but are funnelled into apoptosis upon p53 knockout. This work uncovers key features of the secondary response to CDC7 inhibitors, which could aid the development of these compounds as anticancer drugs.
ABSTRACT
Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a newly emerging virus well known as the major cause of the worldwide pandemic due to Coronavirus Disease 2019 (COVID-19). Major breakthroughs in the Next Generation Sequencing (NGS) field were elucidated following the first release of a full-length SARS-CoV-2 genome on the 10 January 2020, with the hope of turning the table against the worsening pandemic situation. Previous studies in respiratory virus characterization require mapping of raw sequences to the human genome in the downstream bioinformatics pipeline as part of metagenomic principles. Illumina, as the major player in the NGS arena, took action by releasing guidelines for improved enrichment kits called the Respiratory Virus Oligo Panel (RVOP) based on a hybridization capture method capable of capturing targeted respiratory viruses, including SARS-CoV-2; therefore, allowing a direct map of raw sequences data to SARS-CoV-2 genome in downstream bioinformatics pipeline. Consequently, two bioinformatics pipelines emerged with no previous studies benchmarking the pipelines. This study focuses on gaining insight and understanding of target enrichment workflow by Illumina through the utilization of different bioinformatics pipelines named as 'Fast Pipeline' and 'Normal Pipeline' to SARS-CoV-2 strains isolated from Yogyakarta and Central Java, Indonesia. Overall, both pipelines work well in the characterization of SARS-CoV-2 samples, including in the identification of major studied nucleotide substitutions and amino acid mutations. A higher number of reads mapped to the SARS-CoV-2 genome in Fast Pipeline and merely were discovered as a contributing factor in a higher number of coverage depth and identified variations (SNPs, insertion, and deletion). Fast Pipeline ultimately works well in a situation where time is a critical factor. On the other hand, Normal Pipeline would require a longer time as it mapped reads to the human genome. Certain limitations were identified in terms of pipeline algorithm, whereas it is highly recommended in future studies to design a pipeline in an integrated framework, for instance, by using NextFlow, a workflow framework to combine all scripts into one fully integrated pipeline.
