High-throughput sequencing in mutation detection: A new generation of genotoxicity tests?

An integrated in vitro carcinogenicity test that distinguishes between genotoxic carcinogens, non-genotoxic carcinogens, and non-carcinogens

Chemical safety testing plays a crucial role in product and pharmacological development, as well as chemoprevention; however, in vitro genotoxicity safety tests do not always accurately predict the chemicals that will be in vivo carcinogens. If chemicals test positive in vitro for genotoxicity but negative in vivo, this can contribute to unnecessary testing in animals used to confirm erroneous in vitro positive results. Current in vitro tests typically evaluate only genotoxicity endpoints, which limits their potential to detect non-genotoxic carcinogens. The frequency of misleading in vitro positive results can be high, leading to a requirement for more informative in vitro tests. It is now recognized that multiple-endpoint genotoxicity testing may aid more accurate detection of carcinogens and non-carcinogens. The objective of this review was to evaluate the utility of our novel, multiple-endpoint in vitro test, which uses multiple cancer-relevant endpoints to predict carcinogenic potential. The tool assessed micronucleus frequency, p53 expression, p21 expression, mitochondrial respiration, cell cycle abnormalities and, uniquely, cell morphology changes in human lymphoblastoid cell lines, TK6 and MCL-5. The endpoints were used to observe cellular responses to 18 chemicals within the following categories: genotoxic carcinogens, non-genotoxic carcinogens, toxic non-carcinogens, and misleading in vitro positive and negative agents. The number of endpoints significantly altered for each chemical was considered, alongside the holistic Integrated Signature of Carcinogenicity score, derived from the sum of fold changes for all endpoints. Following the calculation of an overall score from these measures, carcinogens exhibited greater potency than non-carcinogens. Genotoxic carcinogens were generally more potent than non-genotoxic carcinogens. This novel approach therefore demonstrated potential for correctly predicting whether chemicals with unknown mechanism may be considered carcinogens. Overall, while further validation is recommended, the test demonstrates potential for the identification of carcinogenic compounds. Adoption of the approach could enable reduced animal use in carcinogenicity testing.

Somatic mutation burden in relation to aging and functional life span: implications for cellular reprogramming and rejuvenation

The accrual of somatic mutations has been implicated as causal factors in aging since the 1950s. However, the quantitative analysis of somatic mutations has posed a major challenge due to the random nature of de novo mutations in normal tissues, which has limited analysis to tumors and other clonal lineages. Advances in single-cell and single-molecule next-generation sequencing now allow to obtain, for the first time, detailed insights into the landscape of somatic mutations in different human tissues and cell types as a function of age under various conditions. Here, we will briefly recapitulate progress in somatic mutation analysis and discuss the possible relationship between somatic mutation burden with functional life span, with a focus on differences between germ cells, stem cells, and differentiated cells.

Genotoxicity assessment: opportunities, challenges and perspectives for quantitative evaluations of dose-response data

Genotoxicity data are mainly interpreted in a qualitative way, which typically results in a binary classification of chemical entities. For more than a decade, there has been a discussion about the need for a paradigm shift in this regard. Here, we review current opportunities, challenges and perspectives for a more quantitative approach to genotoxicity assessment. Currently discussed opportunities mainly include the determination of a reference point (e.g., a benchmark dose) from genetic toxicity dose-response data, followed by calculation of a margin of exposure (MOE) or derivation of a health-based guidance value (HBGV). In addition to new opportunities, major challenges emerge with the quantitative interpretation of genotoxicity data. These are mainly rooted in the limited capability of standard in vivo genotoxicity testing methods to detect different types of genetic damage in multiple target tissues and the unknown quantitative relationships between measurable genotoxic effects and the probability of experiencing an adverse health outcome. In addition, with respect to DNA-reactive mutagens, the question arises whether the widely accepted assumption of a non-threshold dose-response relationship is at all compatible with the derivation of a HBGV. Therefore, at present, any quantitative genotoxicity assessment approach remains to be evaluated case-by-case. The quantitative interpretation of in vivo genotoxicity data for prioritization purposes, e.g., in connection with the MOE approach, could be seen as a promising opportunity for routine application. However, additional research is needed to assess whether it is possible to define a genotoxicity-derived MOE that can be considered indicative of a low level of concern. To further advance quantitative genotoxicity assessment, priority should be given to the development of new experimental methods to provide a deeper mechanistic understanding and a more comprehensive basis for the analysis of dose-response relationships.

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.

Advances in Single-Cell Toxicogenomics in Environmental Toxicology

The toxicity evaluation system of environmental pollutants has undergone numerous changes due to the application of new technologies. Single-cell toxicogenomics is rapidly changing our view on environmental toxicology by increasing the resolution of our analysis to the level of a single cell. Applications of this technology in environmental toxicology have begun to emerge and are rapidly expanding the portfolio of existing technologies and applications. Here, we first summarized different methods involved in single-cell isolation and amplification in single-cell sequencing process, compared the advantages and disadvantages of different methods, and analyzed their development trends. Then, we reviewed the main advances of single-cell toxicogenomics in environmental toxicology, emphatically analyzed the application prospects of this technology in identifying the target cells of pollutants in early embryos, clarifying the heterogeneous response of cell subtypes to pollutants, and finding pathogenic bacteria in unknown microbes, and highlighted the unique characteristics of this approach with high resolution, high throughput, and high specificity by examples. We also offered a prediction of the further application of this technology and the revolution it brings in environmental toxicology. Overall, these advances will provide practical solutions for controlling or mitigating exogenous toxicological effects that threaten human and ecosystem health, contribute to improving our understanding of the physiological processes affected by pollutants, and lead to the emergence of new methods of pollution control.

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.

Clinical implementation of an oncology-specific family health history risk assessment tool

BACKGROUND

The presence of hereditary cancer syndromes in cancer patients can have an impact on current clinical care and post-treatment prevention and surveillance measures. Several barriers inhibit identification of hereditary cancer syndromes in routine practice. This paper describes the impact of using a patient-facing family health history risk assessment platform on the identification and referral of breast cancer patients to genetic counselling services.

METHODS

This was a hybrid implementation-effectiveness study completed in breast cancer clinics. English-literate patients not previously referred for genetic counselling and/or gone through genetic testing were offered enrollment. Consented participants were provided educational materials on family health history collection, entered their family health history into the platform and completed a satisfaction survey. Upon completion, participants and their clinicians were given personalized risk reports. Chart abstraction was done to identify actions taken by patients, providers and genetic counsellors.

RESULTS

Of 195 patients approached, 102 consented and completed the study (mean age 55.7, 100 % women). Sixty-six (65 %) met guideline criteria for genetic counseling of which 24 (36 %) were referred for genetic counseling. Of those referred, 13 (54 %) participants attended and eight (33 %) completed genetic testing. On multivariate logistic regression, referral was not associated with age, cancer stage, or race but was associated with clinical provider (p = 0.041). Most providers (71 %) had higher referral rates during the study compared to prior. The majority of participants found the experience useful (84 %), were more aware of their health risks (83 %), and were likely to recommend using a patient-facing platform to others (69 %).

CONCLUSIONS

65 % of patients attending breast cancer clinics in this study are at-risk for hereditary conditions based on current guidelines. Using a patient-facing risk assessment platform enhances the ability to identify these patients systematically and with widespread acceptability and recognized value by patients. As only a third of at-risk participants received referrals for genetic counseling, further understanding barriers to referral is needed to optimize hereditary risk assessment in oncology practices.

TRIAL REGISTRATION

NIH Clinical Trials registry, NCT04639934 . Registered Nov 23, 2020 -- Retrospectively registered.

Effects of physicochemical properties of polyacrylamide (PAA) and (polydimethylsiloxane) PDMS on cardiac cell behavior

In vitro cell culture is commonly applied in laboratories around the world. Cultured cells are either of primary origin or established cell lines. Such transformed cell lines are increasingly replaced by pluripotent stem cell derived organotypic cells with more physiological properties. The quality of the culture conditions and matrix environment is of considerable importance in this regard. In fact, mechanical cues of the extracellular matrix have substantial effects on the cellular physiology. This is especially true if contractile cells such as cardiomyocytes are cultured. Therefore, elastic biomaterials have been introduced as scaffolds in 2D and 3D culture models for different cell types, cardiac cells among them. In this review, key aspects of cell-matrix interaction are highlighted with focus on cardiomyocytes and chemical properties as well as strengths and potential pitfalls in using two commonly applied polymers for soft matrix engineering, polyacrylamide (PAA) and polydimethylsiloxane (PDMS) are discussed.

Direct quantification of in vivo mutagenesis and carcinogenesis using duplex sequencing

Error-corrected next-generation sequencing (ecNGS) can be used to rapidly detect and quantify the in vivo mutagenic impact of environmental exposures or endogenous processes in any tissue, from any species, at any genomic location. The greater speed, higher scalability, richer data outputs, and cross-species and cross-locus applicability of ecNGS compared to existing methods make it a powerful new tool for mutational research, regulatory safety testing, and emerging clinical applications.

The ability to accurately measure mutations is critical for basic research and identifying potential drug and chemical carcinogens. Current methods for in vivo quantification of mutagenesis are limited because they rely on transgenic rodent systems that are low-throughput, expensive, prolonged, and do not fully represent other species such as humans. Next-generation sequencing (NGS) is a conceptually attractive alternative for detecting mutations in the DNA of any organism; however, the limit of resolution for standard NGS is poor. Technical error rates (∼1 × 10⁻³) of NGS obscure the true abundance of somatic mutations, which can exist at per-nucleotide frequencies ≤1 × 10⁻⁷. Using duplex sequencing, an extremely accurate error-corrected NGS (ecNGS) technology, we were able to detect mutations induced by three carcinogens in five tissues of two strains of mice within 31 d following exposure. We observed a strong correlation between mutation induction measured by duplex sequencing and the gold-standard transgenic rodent mutation assay. We identified exposure-specific mutation spectra of each compound through trinucleotide patterns of base substitution. We observed variation in mutation susceptibility by genomic region, as well as by DNA strand. We also identified a primordial marker of carcinogenesis in a cancer-predisposed strain of mice, as evidenced by clonal expansions of cells carrying an activated oncogene, less than a month after carcinogen exposure. These findings demonstrate that ecNGS is a powerful method for sensitively detecting and characterizing mutagenesis and the early clonal evolutionary hallmarks of carcinogenesis. Duplex sequencing can be broadly applied to basic mutational research, regulatory safety testing, and emerging clinical applications.

Mutagenicity monitoring in humans: Global versus specific origin of mutations

An underappreciated aspect of human mutagenicity biomonitoring is tissue specificity reflected in different assays, especially those that measure events that can only occur in developing bone marrow (BM) cells. Reviewed here are 9 currently-employed human mutagenicity biomonitoring assays. Several assays measure chromosome-level events in circulating T-lymphocytes (T-cells), i.e., traditional analyses of aberrations, translocation studies involving chromosome painting and fluorescence in situ hybridization (FISH) and determinations of micronuclei (MN). Other T-cell assays measure gene mutations. i.e., hypoxanthine-guanine phosphoriboslytransferase (HPRT) and phosphoribosylinositol glycan class A (PIGA). In addition to the T-cell assays, also reviewed are those assays that measure events in peripheral blood cells that necessarily arose in BM cells, i.e., MN in reticulocytes; glycophorin A (GPA) gene mutations in red blood cells (RBCs), and PIGA gene mutations in RBC or granulocytes. This review considers only cell culture- or cytometry-based assays to describe endpoints measured, methods, optimal sampling times, and sample summaries of typical quantitative and qualitative results. However, to achieve its intended focus on the target cells where events occur, kinetics of the cells of peripheral blood that derive at some point from precursor cells are reviewed to identify body sites and tissues where the genotoxic events originate. Kinetics indicate that in normal adults, measured events in T-cells afford global assessments of in vivo mutagenicity but are not specific for BM effects. Therefore, an agent's capacity for inducing mutations in BM cells cannot be reliably inferred from T-cell assays as the magnitude of effect in BM, if any, is unknown. By contrast, chromosome or gene level mutations measured in RBCs/reticulocytes or granulocytes must originate in BM cells, i.e. in RBC or granulocyte precursors, thereby making them specific indicators for effects in BM. Assays of mutations arising directly in BM cells may quantitatively reflect the mutagenicity of potential leukemogenic agents.

The promise of toxicogenomics for genetic toxicology: past, present and future

Toxicogenomics, the application of genomics to toxicology, was described as 'a new era' for toxicology. Standard toxicity tests typically involve a number of short-term bioassays that are costly, time consuming, require large numbers of animals and generally focus on a single end point. Toxicogenomics was heralded as a way to improve the efficiency of toxicity testing by assessing gene regulation across the genome, allowing rapid classification of compounds based on characteristic expression profiles. Gene expression microarrays could measure and characterise genome-wide gene expression changes in a single study and while transcriptomic profiles that can discriminate between genotoxic and non-genotoxic carcinogens have been identified, challenges with the approach limited its application. As such, toxicogenomics did not transform the field of genetic toxicology in the way it was predicted. More recently, next generation sequencing (NGS) technologies have revolutionised genomics owing to the fact that hundreds of billions of base pairs can be sequenced simultaneously cheaper and quicker than traditional Sanger methods. In relation to genetic toxicology, and thousands of cancer genomes have been sequenced with single-base substitution mutational signatures identified, and mutation signatures have been identified following treatment of cells with known or suspected environmental carcinogens. RNAseq has been applied to detect transcriptional changes following treatment with genotoxins; modified RNAseq protocols have been developed to identify adducts in the genome and Duplex sequencing is an example of a technique that has recently been developed to accurately detect mutation. Machine learning, including MutationSeq and SomaticSeq, has also been applied to somatic mutation detection and improvements in automation and/or the application of machine learning algorithms may allow high-throughput mutation sequencing in the future. This review will discuss the initial promise of transcriptomics for genetic toxicology, and how the development of NGS technologies and new machine learning algorithms may finally realise that promise.

Next generation sequencing data for use in risk assessment

Next generation sequencing (NGS) represents several powerful platforms that have revolutionized RNA and DNA analysis. The parallel sequencing of millions of DNA molecules can provide mechanistic insights into toxicology and provide new avenues for biomarker discovery with growing relevance for risk assessment. The evolution of NGS technologies has improved over the last decade with increased sensitivity and accuracy to foster new biomarker assays from tissue, blood and other biofluids. NGS sequencing technologies can identify transcriptional changes and genomic targets with base pair precision in response to chemical exposure. Further, there are several exciting movements within the toxicology community that incorporate NGS platforms into new strategies for more rapid toxicological characterizations. These include the Tox21 in vitro high throughput transcriptomic screening program, development of organotypic spheroids, alternative animal models, mining archival tissues, liquid biopsy and epigenomics. This review will describe NGS-based technologies, demonstrate how they can be used as tools for target discovery in tissue and blood, and suggest how they might be applied for risk assessment.

The State-of-the Art of Environmental Toxicogenomics: Challenges and Perspectives of "Omics" Approaches Directed to Toxicant Mixtures

The last decade witnessed extraordinary advances in “omics” methods, particularly transcriptomics, proteomics and metabolomics, enabling toxicologists to integrate toxicokinetics and toxicodynamics with mechanistic insights on the mode-of-action of noxious chemicals, single or combined. The toxicology of mixtures is, nonetheless, a most challenging enterprise, especially for environmental toxicologists and ecotoxicologists, who invariably deal with chemical mixtures, many of which contain unknowns. Despite costs and demanding computations, the systems toxicology framework, of which “omics” is a major component, endeavors extracting adverse outcome pathways for complex mixtures. Still, the interplay between the multiple components of gene expression and cell metabolism tends to be overlooked. As an example, the proteome allocates DNA methyltransferases whose altered transcription or loss of function by action of chemicals can have a global impact on gene expression in the cell. On the other hand, chemical insult can produce reactive metabolites and radicals that can intercalate or bind to DNA as well as to enzymes and structural proteins, compromising their activity. These examples illustrate the importance of exploring multiple “omes” and the purpose of “omics” and multi-“omics” for building truly predictive models of hazard and risk. Here we will review the state-of-the-art of toxicogenomics highlighting successes, shortcomings and perspectives for next-generation environmental toxicologists.

A decision tree-based integrated testing strategy for tailor-made carcinogenicity evaluation of test substances using genotoxicity test results and chemical spaces

Genotoxicity evaluation has been widely used to estimate the carcinogenicity of test substances during safety evaluation. However, the latest strategies using genotoxicity tests give more weight to sensitivity; therefore, their accuracy has been very low. For precise carcinogenicity evaluation, we attempted to establish an integrated testing strategy for the tailor-made carcinogenicity evaluation of test materials, considering the relationships among genotoxicity test results (Ames, in vitro mammalian genotoxicity and in vivo micronucleus), carcinogenicity test results and chemical properties (molecular weight, logKow and 179 organic functional groups). By analyzing the toxicological information and chemical properties of 230 chemicals, including 184 carcinogens in the Carcinogenicity Genotoxicity eXperience database, a decision tree for carcinogenicity evaluation was optimised statistically. A decision forest model was generated using a machine-learning method-random forest-which comprises thousands of decision trees. As a result, balanced accuracies in cross-validation of the optimised decision tree and decision forest model, considering chemical space (71.5% and 75.5%, respectively), were higher than balanced accuracy of an example regulatory decision tree (54.1%). Moreover, the statistical optimisation of tree-based models revealed significant organic functional groups that would cause false prediction in standard genotoxicity tests and non-genotoxic carcinogenicity (e.g., organic amide and thioamide, saturated heterocyclic fragment and aryl halide). In vitro genotoxicity tests were the most important parameters in all models, even when in silico parameters were integrated. Although external validation is required, the findings of the integrated testing strategies established herein will contribute to precise carcinogenicity evaluation and to determine new mechanistic hypotheses of carcinogenicity.

Bleomycin-induced genome structural variations in normal, non-tumor cells

Many anticancer drugs are genotoxic agents inducing DNA breaks in actively proliferating cancer cells. However, these same drugs also induce mutations, mostly genome structural variations (GSVs). The detection of GSVs in normal cells and tissues is a major challenge due to the very low abundance of these mutations, which are essentially only detectable in clonal outgrowths, such as tumors. Previously we developed Structural Variant Search (SVS) – an NGS-based assay for the quantitative detection of somatic GSVs in normal cells. Using an improved version of SVS we now demonstrate that the same dose of the anti-cancer drug bleomycin induces about 5 times more somatic GSVs in quiescent primary human fibroblasts than in proliferating cells. GVS induction in non-dividing, normal cells was subsequently confirmed in vivo by demonstrating that a single dose of bleomycin leads to a significant increase of GSV frequency in mouse liver and heart, two postmitotic tissues. Our findings suggest that normal non-cycling differentiated cells may serve as a reservoir of iatrogenically induced mutations. These results provide more insight into the possible molecular mechanisms that underlie late-life morbidities in cancer survivors exposed to chemotherapy.

Somatic Mutagenesis in Mammals and Its Implications for Human Disease and Aging

DNA mutations as a consequence of errors during DNA damage repair, replication, or mitosis are the substrate for evolution. In multicellular organisms, mutations can occur in the germline and also in somatic tissues, where they are associated with cancer and other chronic diseases and possibly with aging. Recent advances in high-throughput sequencing have made it relatively easy to study germline de novo mutations, but in somatic cells, the vast majority of mutations are low-abundant and can be detected only in clonal lineages, such as tumors, or single cells. Here we review recent results on somatic mutations in normal human and animal tissues with a focus on their possible functional consequences.

Next-generation sequencing approaches for the study of genome and epigenome toxicity induced by sulfur mustard

Sulfur mustard (SM) is an extensive nucleophilic and alkylating agent that targets different tissues. The genotoxic property of SM is the most threatening effect, because it is associated with detrimental inflammations and susceptibility to several kinds of cancer. Moreover, SM causes a wide variety of adverse effects on DNA which result in accumulation of DNA adducts, multiple mutations, aneuploidies, and epigenetic aberrations in the genome. However, these adverse effects are still not known well, possibly because no valid biomarkers have been developed for detecting them. The advent of next-generation sequencing (NGS) has provided opportunities for the characterization of these alterations with a higher level of molecular detail and cost-effectivity. The present review introduces NGS approaches for the detection of SM-induced DNA adducts, mutations, chromosomal structural variation, and epigenetic aberrations, and also comparing and contrasting them with regard to which might be most advantageous.

A genome-wide mutation analysis method enabling high-throughput identification of chemical mutagen signatures

Trinucleotide mutational signatures extracted from cancer genomes provide clues useful in understanding the roles of mutagens and mutagenic mechanisms in cancer development. The lack of a simple method for genome-wide analysis of alterations induced by mutagens hampers the identification of trinucleotide signatures of mutagen exposure and evaluation of their relationships with human cancers. Here, we describe a novel approach to facilitate analysis of chemically induced mutations in bacterial cells by detection of increased frequencies of base substitutions after mutagen exposure, using paired-end overlapping next-generation sequencing. DNA samples from Salmonella typhimurium strain TA100, exposed to three alkylating agents, ethylnitrosourea (ENU), methylnitrosourea (MNU), and ethyl methansulphonate (EMS), were analysed. The G:C > A:T mutation frequency was increased in all samples, whereas A:T base pair substitution frequencies were increased specifically in samples exposed to ENU, consistent with previous reports. Mutation patterns in the context of 96 possible trinucleotide formats in these samples exhibited a sharp peak corresponding to an NpCpY consensus sequence, which is similar to the mutational signature of alkylating agents in human cancer. These results indicate that our approach can be useful in facilitating the understanding of mechanisms underlying chemical mutagenicity and for identification of unknown causal mutagens in human cancer.

Enhancing the accuracy of next-generation sequencing for detecting rare and subclonal mutations

Mutations, the fuel of evolution, are first manifested as rare DNA changes within a population of cells. Although next-generation sequencing (NGS) technologies have revolutionized the study of genomic variation between species and individual organisms, most have limited ability to accurately detect and quantify rare variants among the different genome copies in heterogeneous mixtures of cells or molecules. We describe the technical challenges in characterizing subclonal variants using conventional NGS protocols and the recent development of error correction strategies, both computational and experimental, including consensus sequencing of single DNA molecules. We also highlight major applications for low-frequency mutation detection in science and medicine, describe emerging methodologies and provide our vision for the future of DNA sequencing.

Genome-wide mutation detection by interclonal genetic variation

Genetic toxicology assays estimate mutation frequencies by phenotypically screening for the activation or inactivation of endogenous or exogenous reporter genes. These reporters can only detect mutations in narrow areas of the genome and their use is often restricted to certain in vitro and in vivo models. Here, we show that Interclonal Genetic Variation (ICGV) can directly identify mutations genome-wide by comparing sequencing data of single-cell clones derived from the same source or organism. Upon ethyl methanesulfonate (EMS) exposure, ICGV detected greater levels of mutation in a dose- and time-dependent manner in E. coli. In addition, ICGV was also able to identify a ∼20-fold increase in somatic mutations in T-cell clones derived from an N-ethyl-N-nitrosourea (ENU)-treated rat vs. a vehicle-treated rat. These results demonstrate that the genetic differences of single-cell clones can be used for genome-wide mutation detection.

Analysis of BRCA1/2 mutation spectrum and prevalence in unselected Chinese breast cancer patients by next-generation sequencing

PURPOSE

BRCA1 and BRCA2 (BRCA1/2) are two major high-penetrance breast cancer predisposition genes, mutations in which can lead to high risks and early onset of breast cancer. This study was performed to comprehensively investigate the spectrum and prevalence of BRCA1/2 mutations in unselected Chinese breast cancer patients and evaluate the associations of BRCA1/2 mutations with related clinicopathological characteristics of the tumors.

METHODS

By integrating microfluidic PCR-based target enrichment and next-generation sequencing, paired tumor and normal tissues from 313 unselected breast cancer patients were analyzed for both germline and somatic mutations of BRCA1/2 genes in Chinese Han population.

RESULTS

Total 5 BRCA1 and 8 BRCA2 deleterious germline mutations were detected in 5 (1.60%) and 12 (3.83%) of the 313 patients, respectively. The entire frequency of deleterious germline mutations of BRCA1/2 was 5.43%. Among them, c.1069A > T and c.3418_3419insTGACTACT in BRCA1, c.8474_8487delCATACCCTATACAG and c.6547delG in BRCA2 were novel. In addition, 32 germline variants of unknown significance in 31 (9.90%) of the 313 patients were identified. We also detected 13 somatic mutations in ten patients (3.19%), including 4 (1.28%) deleterious mutations (c.1575delT, c.2677C > T, c.7024C > T, and c.7672G > T in BRCA2) and 5 novel mutations (c.4728A > G and c.4820T > C in BRCA1; c.2527G > A, c.4069C > G and c.7672G > T in BRCA2). Notably, BRCA1 mutation carriers were significantly younger, and more likely to be ER negative and basal-like breast cancers.

CONCLUSIONS

Our study provided a reliable and effective platform for BRCA1/2 genetic testing, and suggested that there was a relatively high prevalence and special spectrum of BRCA1/2 mutations in unselected Chinese breast cancer patients.

The various aspects of genetic and epigenetic toxicology: testing methods and clinical applications

Genotoxicity refers to the ability of harmful substances to damage genetic information in cells. Being exposed to chemical and biological agents can result in genomic instabilities and/or epigenetic alterations, which translate into a variety of diseases, cancer included. This concise review discusses, from both a genetic and epigenetic point of view, the current detection methods of different agents’ genotoxicity, along with their basic and clinical relation to human cancer, chemotherapy, germ cells and stem cells.

Genome resequencing analysis of Salmonella typhimurium LT-2 strains TA98 and TA100 for the establishment of a next-generation sequencing-based mutagenicity assay

Next-generation sequencing (NGS) is a potentially useful technology to achieve a more precise evaluation of chemical mutagenicity. To establish NGS-based mutagenicity assays, which enable the direct detection of chemically induced mutations in a whole genome manner, the selection of appropriate biological resources and their precise genome sequences are essential. Here, we performed genome re-sequencing analyses of Salmonella typhimurium LT-2 strains TA98 and TA100, which have been frequently used in mutagenicity assays. We identified several strain-specific mutations including those that were relevant to their known phenotypes (his, ΔuvrB and rfa). The details of rfa mutations were first clarified in this study, which was a frameshift variant in rfaF and a missense variant in rfaC in TA98 and TA100, respectively. The uvrB deletion in TA98 was larger than that in TA100, which suggested differences in defects of lipopolysaccharide synthesis between these strains. The re-sequenced genome data of TA98 and TA100 will help us establish NGS-based bacterial mutagenicity assays and understand the biological events seen in them. Copyright © 2017 John Wiley & Sons, Ltd.

Tandem Oligonucleotide Probe Annealing and Elongation To Discriminate Viral Sequence

New approaches for genomic DNA/RNA detection are in high demand in order to provide controls for existing enzymatic technologies and to create alternatives for emerging applications. In particular, there is an unmet need in rapid, reliable detection of short RNA regions which could open up new opportunities in transcriptome analysis, virology, and other fields. Herein, we report for the first time a "click" chemistry approach to oligonucleotide probe elongation as a novel approach to specifically detect a viral sequence. We hybridized a library of short, terminally labeled probes to Ebola virus RNA followed by click assembly and analysis of the read sequence by various techniques. As we demonstrate in this paper, using our new approach, a viral RNA sequence can be detected in less than 2 h without the need for cDNA synthesis or any other enzymatic reactions and with a sensitivity of <10 pM target RNA.

Do DNA Double-Strand Breaks Drive Aging?

DNA double-strand breaks (DSBs) are rare, but highly toxic, lesions requiring orchestrated and conserved machinery to prevent adverse consequences, such as cell death and cancer-causing genome structural mutations. DSBs trigger the DNA damage response (DDR) that directs a cell to repair the break, undergo apoptosis, or become senescent. There is increasing evidence that the various endpoints of DSB processing by different cells and tissues are part of the aging phenotype, with each stage of the DDR associated with specific aging pathologies. In this Perspective, we discuss the possibility that DSBs are major drivers of intrinsic aging, highlighting the dynamics of spontaneous DSBs in relation to aging, the distinct age-related pathologies induced by DSBs, and the segmental progeroid phenotypes in humans and mice with genetic defects in DSB repair. A model is presented as to how DSBs could drive some of the basic mechanisms underlying age-related functional decline and death.

Collaborative studies in toxicogenomics in rodent liver in JEMS·MMS; a useful application of principal component analysis on toxicogenomics

Toxicogenomics is a rapidly developing discipline focused on the elucidation of the molecular and cellular effects of chemicals on biological systems. As a collaborative study group of Toxicogenomics/JEMS·MMS, we conducted studies on hepatocarcinogens in rodent liver in which 100 candidate marker genes were selected to discriminate genotoxic hepatocarcinogens from non-genotoxic hepatocarcinogens. Differential gene expression induced by 13 chemicals were examined using DNA microarray and quantitative real-time PCR (qPCR), including eight genotoxic hepatocarcinogens [o-aminoazotoluene, chrysene, dibenzo[a,l]pyrene, diethylnitrosamine (DEN), 7,12-dimethylbenz[a]anthracene, dimethylnitrosamine, dipropylnitrosamine and ethylnitrosourea (ENU)], four non-genotoxic hepatocarcinogens [carbon tetrachloride, di(2-ethylhexyl)phthalate (DEHP), phenobarbital and trichloroethylene] and a non-genotoxic non-hepatocarcinogen [ethanol]. Using qPCR, 30 key genes were extracted from mouse livers at 4 h and 28 days following dose-dependent gene expression alteration induced by DEN and ENU: the most significant changes in gene expression were observed at 4 h. Next, we selected key point times at 4 and 48 h from changes in time-dependent gene expression during the acute phase following administration of chrysene by qPCR. We successfully showed discrimination of eight genotoxic hepatocarcinogens [2-acetylaminofluorene, 2,4-diaminotoluene, diisopropanolnitrosamine, 4-dimethylaminoazobenzene, 4-(methylnitsosamino)-1-(3-pyridyl)-1-butanone, N-nitrosomorpholine, quinoline and urethane] from four non-genotoxic hepatocarcinogens [1,4-dichlorobenzene, dichlorodiphenyltrichloroethane, DEHP and furan] using qPCR and principal component analysis. Additionally, we successfully identified two rat genotoxic hepatocarcinogens [DEN and 2,6-dinitrotoluene] from a nongenotoxic-hepatocarcinogen [DEHP] and a non-genotoxic non-hepatocarcinogen [phenacetin] at 4 and 48 h. The subsequent gene pathway analysis by Ingenuity Pathway Analysis extracted the DNA damage response, resulting from the signal transduction of a p53-class mediator leading to the induction of apoptosis. The present review of these studies suggests that application of principal component analysis on the gene expression profile in rodent liver during the acute phase is useful to predict genotoxic hepatocarcinogens in comparison to non-genotoxic hepatocarcinogens and/or non-carcinogenic hepatotoxins.

Quantitative detection of low-abundance somatic structural variants in normal cells by high-throughput sequencing

The detection and quantification of low-abundance somatic DNA mutations by high throughput sequencing is challenging because of the difficulty in distinguishing errors from true mutations. While there are several approaches available for analyzing somatic point mutations and small indels, an accurate genome-wide assessment of somatic structural variants (somSVs) in bulk DNA is still not possible. Here we present Structural Variant Search (SVS), a method to accurately detect rare somSVs by low-coverage sequencing. We demonstrate direct quantitative assessment of elevated somSV frequencies induced by known clastogenic compounds in human primary cells.

Base changes in tumour DNA have the power to reveal the causes and evolution of cancer

Next-generation sequencing (NGS) technology has demonstrated that the cancer genomes are peppered with mutations. Although most somatic tumour mutations are unlikely to have any role in the cancer process per se, the spectra of DNA sequence changes in tumour mutation catalogues have the potential to identify the mutagens, and to reveal the mutagenic processes responsible for human cancer. Very recently, a novel approach for data mining of the vast compilations of tumour NGS data succeeded in separating and precisely defining at least 30 distinct patterns of sequence change hidden in mutation databases. At least half of these mutational signatures can be readily assigned to known human carcinogenic exposures or endogenous mechanisms of mutagenesis. A quantum leap in our knowledge of mutagenesis in human cancers has resulted, stimulating a flurry of research activity. We trace here the major findings leading first to the hypothesis that carcinogenic insults leave characteristic imprints on the DNA sequence of tumours, and culminating in empirical evidence from NGS data that well-defined carcinogen mutational signatures are indeed present in tumour genomic DNA from a variety of cancer types. The notion that tumour DNAs can divulge environmental sources of mutation is now a well-accepted fact. This approach to cancer aetiology has also incriminated various endogenous, enzyme-driven processes that increase the somatic mutation load in sporadic cancers. The tasks now confronting the field of molecular epidemiology are to assign mutagenic processes to orphan and newly discovered tumour mutation patterns, and to determine whether avoidable cancer risk factors influence signatures produced by endogenous enzymatic mechanisms. Innovative research with experimental models and exploitation of the geographical heterogeneity in cancer incidence can address these challenges.