Detection of genome-wide low-frequency mutations with Paired-End and Complementary Consensus Sequencing (PECC-Seq) revealed end-repair-derived artifacts as residual errors

Effect of sequencing platforms on the sensitivity of chemical mutation detection using Hawk-Seq™

BACKGROUND

Error-corrected next-generation sequencing (ecNGS) technologies have enabled the direct evaluation of genome-wide mutations after exposure to mutagens. Previously, we reported an ecNGS methodology, Hawk-Seq™, and demonstrated its utility in evaluating mutagenicity. The evaluation of technical transferability is essential to further evaluate the reliability of ecNGS-based assays. However, cutting-edge sequencing platforms are continually evolving, which can affect the sensitivity of ecNGS. Therefore, the effect of differences in sequencing instruments on mutation data quality should be evaluated.

RESULTS

We assessed the performance of four sequencing platforms (HiSeq2500, NovaSeq6000, NextSeq2000, and DNBSEQ-G400) with the Hawk-Seq™ protocol for mutagenicity evaluation using DNA samples from mouse bone marrow exposed to benzo[a]pyrene (BP). The overall mutation (OM) frequencies per 106 bp in vehicle-treated samples were 0.22, 0.36, 0.46, and 0.26 for HiSeq2500, NovaSeq6000, NextSeq2000, and DNBSEQ-G400, respectively. The OM frequency of NextSeq2000 was significantly higher than that of HiSeq2500, suggesting the difference to be based on the platform. The relatively higher value in NextSeq2000 was a consequence of the G:C to C:G mutations in NextSeq2000 data (0.67 per 106 G:C bp), which was higher than the mean of the four platforms by a ca. of 0.25 per 106 G:C bp. A clear dose-dependent increase in G:C to T:A mutation frequencies was observed in all four sequencing platforms after BP exposure. The cosine similarity values of the 96-dimensional trinucleotide mutation patterns between HiSeq and the three other platforms were 0.93, 0.95, and 0.92 for NovaSeq, NextSeq, and DNBSeq, respectively. These results suggest that all platforms can provide equivalent data that reflect the characteristics of the mutagens.

CONCLUSIONS

All platforms sensitively detected mutagen-induced mutations using the Hawk-Seq™ analysis. The substitution types and frequencies of the background errors differed depending on the platform. The effects of sequencing platforms on mutagenicity evaluation should be assessed before experimentation.

Chasing Sequencing Perfection: Marching Toward Higher Accuracy and Lower Costs

Next-generation sequencing (NGS), represented by Illumina platforms, has been an essential cornerstone of basic and applied research. However, the sequencing error rate of 1 per 1000 bp (10-3) represents a serious hurdle for research areas focusing on rare mutations, such as somatic mosaicism or microbe heterogeneity. By examining the high-fidelity sequencing methods developed in the past decade, we summarized three major factors underlying errors and the corresponding 12 strategies mitigating these errors. We then proposed a novel framework to classify 11 preexisting representative methods according to the corresponding combinatory strategies and identified three trends that emerged during methodological developments. We further extended this analysis to eight long-read sequencing methods, emphasizing error reduction strategies. Finally, we suggest two promising future directions that could achieve comparable or even higher accuracy with lower costs in both NGS and long-read sequencing.

Genome-wide direct quantification of in vivo mutagenesis using high-accuracy paired-end and complementary consensus sequencing

Error-corrected next-generation sequencing (ecNGS) is an emerging technology for accurately measuring somatic mutations. Here, we report paired-end and complementary consensus sequencing (PECC-Seq), a high-accuracy ecNGS approach for genome-wide somatic mutation detection. We characterize a novel 2-aminoimidazolone lesion besides 7,8-dihydro-8-oxoguanine and the resulting end-repair artifacts originating from NGS library preparation that obscure the sequencing accuracy of NGS. We modify library preparation protocol for the enzymatic removal of end-repair artifacts and improve the accuracy of our previously developed duplex consensus sequencing method. Optimized PECC-Seq shows an error rate of <5 × 10-8 with consensus bases compressed from approximately 25 Gb of raw sequencing data, enabling the accurate detection of low-abundance somatic mutations. We apply PECC-Seq to the quantification of in vivo mutagenesis. Compared with the classic gpt gene mutation assay using gpt delta transgenic mice, PECC-Seq exhibits high sensitivity in quantitatively measuring dose-dependent mutagenesis induced by Aristolochic acid I (AAI). Moreover, PECC-Seq specifically characterizes the distinct genome-wide mutational signatures of AAI, Benzo[a]pyrene, N-Nitroso-N-ethylurea and N-nitrosodiethylamine and reveals the mutational signature of Quinoline in common mouse models. Overall, our findings demonstrate that high-accuracy PECC-Seq is a promising tool for genome-wide somatic mutagenesis quantification and for in vivo mutagenicity testing.

Detection of in vivo mutagenicity in rat liver samples using error-corrected sequencing techniques

BACKGROUND

Mutagenicity, the ability of chemical agents to cause mutations and potentially lead to cancer, is a critical aspect of substance safety assessment for protecting human health and the environment. Metabolic enzymes activate multiple mutagens in living organisms, thus in vivo animal models provide highly important information for evaluating mutagenicity in human. Rats are considered suitable models as they share a similar metabolic pathway with humans for processing toxic chemical and exhibit higher responsiveness to chemical carcinogens than mice. To assess mutagenicity in rats, transgenic rodents (TGRs) are widely used for in vivo gene mutation assays. However, such assays are labor-intensive and could only detect transgene mutations inserted into the genome. Therefore, introducing a technology to directly detect in vivo mutagenicity in rats would be necessary. The next-generation sequencing (NGS) based error-corrected sequencing technique is a promising approach for such purposes.

RESULTS

We investigated the applicability of paired-end and complementary consensus sequencing (PECC-Seq), an error-corrected sequencing technique, for detecting in vivo mutagenicity in the rat liver samples. PECC-Seq allows for the direct detection of ultra-rare somatic mutations in the genomic DNA without being constrained by the genomic locus, tissue, or organism. We tested PECC-Seq feasibility in rats treated with diethylnitrosamine (DEN), a mutagenic compound. Interestingly, the mutation and mutant frequencies between PECC-Seq and the TGR assay displayed a promising correlation. Our results also demonstrated that PECC-Seq could successfully detect the A:T > T:A mutation in rat liver samples, consistent with the TGR assay. Furthermore, we calculated the trinucleotide mutation frequency and proved that PECC-Seq accurately identified the DEN treatment-induced mutational signatures.

CONCLUSIONS

Our study provides the first evidence of using PECC-Seq for in vivo mutagenicity detection in rat liver samples. This approach could provide a valuable alternative to conventional TGR assays as it is labor- and time-efficient and eliminates the need for transgenic rodents. Error-corrected sequencing techniques, such as PECC-Seq, represent promising approaches for enhancing mutagenicity assessment and advancing regulatory science.

Error-corrected next generation sequencing - Promises and challenges for genotoxicity and cancer risk assessment

Error-corrected Next Generation Sequencing (ecNGS) is rapidly emerging as a valuable, highly sensitive and accurate method for detecting and characterizing mutations in any cell type, tissue or organism from which DNA can be isolated. Recent mutagenicity and carcinogenicity studies have used ecNGS to quantify drug-/chemical-induced mutations and mutational spectra associated with cancer risk. ecNGS has potential applications in genotoxicity assessment as a new readout for traditional models, for mutagenesis studies in 3D organotypic cultures, and for detecting off-target effects of gene editing tools. Additionally, early data suggest that ecNGS can measure clonal expansion of mutations as a mechanism-agnostic early marker of carcinogenic potential and can evaluate mutational load directly in human biomonitoring studies. In this review, we discuss promising applications, challenges, limitations, and key data initiatives needed to enable regulatory testing and adoption of ecNGS - including for advancing safety assessment, augmenting weight-of-evidence for mutagenicity and carcinogenicity mechanisms, identifying early biomarkers of cancer risk, and managing human health risk from chemical exposures.

Error-corrected duplex sequencing enables direct detection and quantification of mutations in human TK6 cells with strong inter-laboratory consistency

Error-corrected duplex sequencing (DS) enables direct quantification of low-frequency mutations and offers tremendous potential for chemical mutagenicity assessment. We investigated the utility of DS to quantify induced mutation frequency (MF) and spectrum in human lymphoblastoid TK6 cells exposed to a prototypical DNA alkylating agent, N-ethyl-N-nitrosourea (ENU). Furthermore, we explored appropriate experimental parameters for this application, and assessed inter-laboratory reproducibility. In two independent experiments in two laboratories, TK6 cells were exposed to ENU (25-200 µM) and DNA was sequenced 48, 72, and 96 h post-exposure. A DS mutagenicity panel targeting twenty 2.4-kb regions distributed across the genome was used to sample diverse, genome-representative sequence contexts. A significant increase in MF that was unaffected by time was observed in both laboratories. Concentration-response in the MF from the two laboratories was strongly positively correlated (r = 0.97). C:G>T:A, T:A>C:G, T:A>A:T, and T:A>G:C mutations increased in consistent, concentration-dependent manners in both laboratories, with high proportions of C:G>T:A at all time points. The consistent results across the three time points suggest that 48 h may be sufficient for mutation analysis post-exposure. The target sites responded similarly between the two laboratories and revealed a higher average MF in intergenic regions. These results, demonstrating remarkable reproducibility across time and laboratory for both MF and spectrum, support the high value of DS for characterizing chemical mutagenicity in both research and regulatory evaluation.

Preparation of Duplex Sequencing Libraries for Archival Paraffin-Embedded Tissue Samples Using Single-Strand-Specific Nuclease P1

DNA from formalin-fixed paraffin-embedded (FFPE) tissues, which are frequently utilized in cancer research, is significantly affected by chemical degradation. It was suggested that approaches that are based on duplex sequencing can significantly improve the accuracy of mutation detection in FFPE-derived DNA. However, the original duplex sequencing method cannot be utilized for the analysis of formalin-fixed paraffin-embedded (FFPE) tissues, as FFPE DNA contains an excessive number of damaged bases, and these lesions are converted to false double-strand nucleotide substitutions during polymerase-driven DNA end repair process. To resolve this drawback, we replaced DNA polymerase by a single strand-specific nuclease P1. Nuclease P1 was shown to efficiently remove RNA from DNA preparations, to fragment the FFPE-derived DNA and to remove 5'/3'-overhangs. To assess the performance of duplex sequencing-based methods in FFPE-derived DNA, we constructed the Bottleneck Sequencing System (BotSeqS) libraries from five colorectal carcinomas (CRCs) using either DNA polymerase or nuclease P1. As expected, the number of identified mutations was approximately an order of magnitude higher in libraries prepared with DNA polymerase vs. nuclease P1 (626 ± 167/Mb vs. 75 ± 37/Mb, paired t-test p-value 0.003). Furthermore, the use of nuclease P1 but not polymerase-driven DNA end repair allowed a reliable discrimination between CRC tumors with and without hypermutator phenotypes. The utility of newly developed modification was validated in the collection of 17 CRCs and 5 adjacent normal tissues. Nuclease P1 can be recommended for the use in duplex sequencing library preparation from FFPE-derived DNA.

Subclonal landscape of cancer drives resistance to immune therapy

Tumor mutation burden (TMB) is often used as a biomarker for immunogenicity and prerequisite for immune checkpoint inhibitor (ICI) therapy. However, it is becoming increasingly evident that not all tumors with high TMB respond to ICIs as expected. It has been shown that the ability of T-cells to infiltrate the tumor microenvironment and elicit a specific immune response is dependent not only on the TMB, but also on intra-tumor heterogeneity and the fraction of low-frequency subclonal mutations that make up the tumor. High intra-tumor heterogeneity leads to inefficient recognition of tumor neoantigens by T-cells due to their diluted frequency and spatial heterogeneity. Clinical studies have shown that tumors with a high degree of intra-tumor heterogeneity respond poorly to ICI therapy, and previous cytotoxic treatment may increase the intra-tumor heterogeneity and render second-line ICI therapy less effective. This paper reviews the role of ICI therapy when following chemotherapy or radiation to determine if they may be better suited as first-line therapy in patients with high TMB, low intra-tumor heterogeneity, and high PD-1, PD-L1, or CTLA-4 expression.

Single-strand specific nuclease enhances accuracy of error-corrected sequencing and improves rare mutation-detection sensitivity

Error-corrected sequences (ECSs) that utilize double-stranded DNA sequences are useful in detecting mutagen-induced mutations. However, relatively higher frequencies of G:C > T:A (1 × 10⁻⁷ bp) and G:C > C:G (2 × 10⁻⁷ bp) errors decrease the accuracy of detection of rare G:C mutations (approximately 10⁻⁷ bp). Oxidized guanines in single-strand (SS) overhangs generated after shearing could serve as the source of these errors. To remove these errors, we first computationally discarded up to 20 read bases corresponding to the ends of the DNA fragments. Error frequencies decreased proportionately with trimming length; however, the results indicated that they were not sufficiently removed. To efficiently remove SS overhangs, we evaluated three mechanistically distinct SS-specific nucleases (S1 Nuclease, mung bean nuclease, and RecJf exonuclease) and found that they were more efficient than computational trimming. Consequently, we established Jade-Seq™, an ECS protocol with S1 Nuclease treatment, which reduced G:C > T:A and G:C > C:G errors to 0.50 × 10⁻⁷ bp and 0.12 × 10⁻⁷ bp, respectively. This was probably because S1 Nuclease removed SS regions, such as gaps and nicks, depending on its wide substrate specificity. Subsequently, we evaluated the mutation-detection sensitivity of Jade-Seq™ using DNA samples from TA100 cells exposed to 3-methylcholanthrene and 7,12-dimethylbenz[a]anthracene, which contained the rare G:C > T:A mutation (i.e., 2 × 10⁻⁷ bp). Fold changes of G:C > T:A compared to the vehicle control were 1.2- and 1.3-times higher than those of samples without S1 Nuclease treatment, respectively. These findings indicate the potential of Jade-Seq™ for detecting rare mutations and determining the mutagenicity of environmental mutagens.

Significance and limitations of the use of next-generation sequencing technologies for detecting mutational signatures

Next generation sequencing technologies (NGS) have been critical in characterizing the genomic landscape and untangling the genetic heterogeneity of human cancer. Since its advent, NGS has played a pivotal role in identifying the patterns of somatic mutations imprinted on cancer genomes and in deciphering the signatures of the mutational processes that have generated these patterns. Mutational signatures serve as phenotypic molecular footprints of exposures to environmental factors as well as deficiency and infidelity of DNA replication and repair pathways. Since the first roadmap of mutational signatures in human cancer was generated from whole-genome and whole-exome sequencing data, there has been a growing interest to extract mutational signatures from other NGS technologies such as targeted panel sequencing, RNA sequencing, single-cell sequencing, duplex sequencing, reduced representation sequencing, and long-read sequencing. Many of these technologies have their inherent sequencing biases and produce technical artifacts that can confound the extraction of reliable and interpretable mutational signatures. In this review, we highlight the relevance, limitations, and prospects of using different NGS technologies for examining mutational patterns and for deciphering mutational signatures.

Somatic mutation landscapes at single-molecule resolution

Somatic mutations drive the development of cancer and may contribute to ageing and other diseases1,2. Despite their importance, the difficulty of detecting mutations that are only present in single cells or small clones has limited our knowledge of somatic mutagenesis to a minority of tissues. Here, to overcome these limitations, we developed nanorate sequencing (NanoSeq), a duplex sequencing protocol with error rates of less than five errors per billion base pairs in single DNA molecules from cell populations. This rate is two orders of magnitude lower than typical somatic mutation loads, enabling the study of somatic mutations in any tissue independently of clonality. We used this single-molecule sensitivity to study somatic mutations in non-dividing cells across several tissues, comparing stem cells to differentiated cells and studying mutagenesis in the absence of cell division. Differentiated cells in blood and colon displayed remarkably similar mutation loads and signatures to their corresponding stem cells, despite mature blood cells having undergone considerably more divisions. We then characterized the mutational landscape of post-mitotic neurons and polyclonal smooth muscle, confirming that neurons accumulate somatic mutations at a constant rate throughout life without cell division, with similar rates to mitotically active tissues. Together, our results suggest that mutational processes that are independent of cell division are important contributors to somatic mutagenesis. We anticipate that the ability to reliably detect mutations in single DNA molecules could transform our understanding of somatic mutagenesis and enable non-invasive studies on large-scale cohorts.