Hawk-Seq™ differentiates between various mutations in Salmonella typhimurium TA100 strain caused by exposure to Ames test-positive mutagens

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.

Application of luminescent Photobacterium Phosphoreum T3 for the detection of zearalenone and estimating the efficiency of their enzymatic degradation

Zearalenone (ZEN), a nonsteroidal estrogenic mycotoxin, causes enormous economic losses in the food and feed industries. Simple, rapid, low-cost, and quantitative analysis of ZEN is particularly urgent in the fields of food safety and animal husbandry. Using the bioluminescent bacterium Photobacterium phosphoreum T3, we propose a bioluminescence inhibition assay to evaluate ZEN levels quickly. The limit of detection (LOD), limit of quantification (LOQ), and quantitative working range of this bioluminescence inhibition assay were 0.1 µg/mL, 5 µg/mL, and 5-100 µg/mL, respectively. The concentration-response curve of the bioluminescence inhibition rate and ZEN concentration was plotted within the range 5 to 100 μg/mL, as follows: y = 0.0069x2 - 0.0190x + 7.9907 (R2 = 0.9943, y is luminescence inhibition rate, x is ZEN concentration). First, we used the bioluminescence inhibition assay to detect the remaining ZEN in samples treated with purified lactonohydrolase ZHD101. The bioluminescence inhibition assay results showed a strong correlation with the HPLC analysis. Furthermore, we successfully evaluated the overall toxicity of samples treated with purified peroxidase Prx and H2O2 using the P. phosphoreum T3 bioluminescence inhibition assay. The results indicate that the degradation products of ZEN created by purified peroxidase Prx and H2O2 showed little toxicity to P. phosphoreum T3. In this study, a simple, rapid, and low-cost assay method of zearalenone by bioluminescent P. phosphoreum T3 was developed. The bioluminescence inhibition assay could be used to estimate the efficiency of enzymatic degradation of ZEN.

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.

Next-generation sequencing methodologies to detect low-frequency mutations: "Catch me if you can"

Mutations, the irreversible changes in an organism's DNA sequence, are present in tissues at a variant allele frequency (VAF) ranging from ∼10-8 per bp for a founder mutation to ∼10-3 for a histologically normal tissue sample containing several independent clones - compared to 1%- 50% for a heterozygous tumor mutation or a polymorphism. The rarity of these events poses a challenge for accurate clinical diagnosis and prognosis, toxicology, and discovering new disease etiologies. Standard Next-Generation Sequencing (NGS) technologies report VAFs as low as 0.5% per nt, but reliably observing rarer precursor events requires additional sophistication to measure ultralow-frequency mutations. We detail the challenge; define terms used to characterize the results, which vary between laboratories and sometimes conflict between biologists and bioinformaticists; and describe recent innovations to improve standard NGS methodologies including: single-strand consensus sequence methods such as Safe-SeqS and SiMSen-Seq; tandem-strand consensus sequence methods such as o2n-Seq and SMM-Seq; and ultrasensitive parent-strand consensus sequence methods such as DuplexSeq, PacBio HiFi, SinoDuplex, OPUSeq, EcoSeq, BotSeqS, Hawk-Seq, NanoSeq, SaferSeq, and CODEC. Practical applications are also noted. Several methods quantify VAF down to 10-5 at a nt and mutation frequency (MF) in a target region down to 10-7 per nt. By expanding to > 1 Mb of sites never observed twice, thus forgoing VAF, other methods quantify MF < 10-9 per nt or < 15 errors per haploid genome. Clonal expansion cannot be directly distinguished from independent mutations by sequencing, so it is essential for a paper to report whether its MF counted only different mutations - the minimum independent-mutation frequency MFminI - or all mutations observed including recurrences - the larger maximum independent-mutation frequency MFmaxI which may reflect clonal expansion. Ultrasensitive methods reveal that, without their use, even mutations with VAF 0.5-1% are usually spurious.

Genome-wide detection of ultralow-frequency substitution mutations in cultures of mouse lymphoma L5178Y cells and Caenorhabditis elegans worms by PacBio sequencing

Many conventional genetic toxicology assays require specialized cell cultures or animals and can only detect mutations that inactivate the function of a reporter gene. These limitations make such assays incompatible with many toxicological models but could be overcome by the development of techniques capable of directly detecting genome-wide somatic mutations through DNA sequencing. PacBio sequencing can generate almost error-free consensus reads by repeatedly inspecting both DNA strands from circularized molecules (a method known as PacBio HiFi). In this study, we show that PacBio HiFi can detect genome-wide ultralow-frequency substitution mutations in cultures of mouse lymphoma L5178Y cells and Caenorhabditis elegans worms. The mutation frequencies (MFs) of unexposed samples in both models were ~1 × 10^-7 mutations per base pair. Compared to these controls, PacBio HiFi detected MF increases of 23-fold in cultures of L5178Y cells exposed to 5 mM ethyl methanosulfonate (EMS) for 4 h, and 5-, 12-, and 29-fold in cultures of C. elegans worms exposed to 12.5, 25, and 50 mM EMS for 4 h, respectively. In both models, the mutation spectra of controls were diverse, while those derived from EMS-exposed samples were dominated by C:G → T:A transitions. To validate these results, clone sequencing analyses were performed on the same cultures of L5178Y cells. The results obtained by clone sequencing and PacBio HiFi were almost identical. Our results suggest that PacBio sequencing could be used for the detection, quantitation, and characterization of mutations in any DNA-containing sample, including those that are not compatible with conventional mutation detection approaches.

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.