Traditional epitranscriptomics relies on capturing a single RNA modification by antibody or chemical treatment, combined with short-read sequencing to identify its transcriptomic location. This approach is labor-intensive and may introduce experimental artifacts. Direct sequencing of native RNA using Oxford Nanopore Technologies (ONT) can allow for directly detecting the RNA base modifications, although these modifications might appear as sequencing errors. The percent Error of Specific Bases (%ESB) was higher for native RNA than unmodified RNA, which enabled the detection of ribonucleotide modification sites. Based on the %ESB differences, we developed a bioinformatic tool, epitranscriptional landscape inferring from glitches of ONT signals (ELIGOS), that is based on various types of synthetic modified RNA and applied to rRNA and mRNA. ELIGOS is able to accurately predict known classes of RNA methylation sites (AUC > 0.93) in rRNAs from Escherichiacoli, yeast, and human cells, using either unmodified in vitro transcription RNA or a background error model, which mimics the systematic error of direct RNA sequencing as the reference. The well-known DRACH/RRACH motif was localized and identified, consistent with previous studies, using differential analysis of ELIGOS to study the impact of RNA m6A methyltransferase by comparing wild type and knockouts in yeast and mouse cells. Lastly, the DRACH motif could also be identified in the mRNA of three human cell lines. The mRNA modification identified by ELIGOS is at the level of individual base resolution. In summary, we have developed a bioinformatic software package to uncover native RNA modifications.

DNA alkylation or adduct formation occurs at nucleophilic sites in DNA, mainly the N7-position of guanine. Ever since identification of the first N7-guanine adduct, several hundred studies on DNA adducts have been reported. Major issues addressed include the relationships between N7-guanine adducts and exposure, mutagenesis, and other biological endpoints. It became quickly apparent that N7-guanine adducts are frequently formed, but may have minimal biological relevance, since they are chemically unstable and do not participate in Watson Crick base pairing. However, N7-guanine adducts have been shown to be excellent biomarkers for internal exposure to direct acting and metabolically activated carcinogens. Questions arise, however, regarding the biological significance for N7-guanine adducts that are readily formed, do not persist, and are not likely to be mutagenic. Thus, we set out to review the current literature to evaluate their formation and the mechanistic evidence for the involvement of N7-guanine adducts in mutagenesis or other biological processes. It was concluded that there is insufficient evidence that N7-guanine adducts can be used beyond confirmation of exposure to the target tissue and demonstration of the molecular dose. There is little to no evidence that N7-guanine adducts or their depurination product, apurinic sites, are the cause of mutations in cells and tissues, since increases in AP sites have not been shown unless toxicity is extant. However, more research is needed to define the extent of chemical depurination versus removal by DNA repair proteins. Interestingly, N7-guanine adducts are clearly present as endogenous background adducts and the endogenous background amounts appear to increase with age. Furthermore, the N7-guanine adducts have been shown to convert to ring opened lesions (FAPy), which are much more persistent and have higher mutagenic potency. Studies in humans are limited in sample size and differences between controls and study groups are small. Future investigations should involve human studies with larger numbers of individuals and analysis should include the corresponding ring opened FAPy derivatives.

Tremendous advances have been made in the study of biomarkers related to carcinogenesis during the past 20 years. This perspective will briefly review improvements in methodology and instrumentation that have increased our abilities to measure the formation, repair, and consequences of DNA adducts. These biomarkers of exposure, along with surrogates such as protein adducts, have greatly improved our understanding of species differences in metabolism and effects of chemical stability and DNA repair on tissue differences in molecular dose. During this same time frame, improvements in assays for biomarkers of effect have provided better data and an improved understanding of the dose responses for both gene and chromosomal mutations. A framework analysis approach was used to examine the mode of action of genotoxic chemicals and the default assumption that cancer can be expected to be linear at very low doses. This analysis showed that biomarkers of exposure are usually linear at low doses, with the exception being when identical adducts are formed endogenously. Whereas biomarkers of exposure extrapolate down to zero, biomarkers of effect can only be interpolated back to the spontaneous or background number of mutations. The likely explanation for this major difference is that at high exposures, the biology that results in mutagenesis is driven by DNA damage resulting from the chemical exposure. In contrast, at very low exposures, the biology that results in mutagenesis is driven by endogenous DNA damage. The shapes of the dose-response curves for biomarkers of exposure and effect can be very different, with biomarkers of effect better informing quantitative estimates of risk for cancer, a disease that results from multiple mutations. It is also clear, however, that low dose data on mutagenesis are needed for many more chemicals.