Frequency of HBsAg variants in occult hepatitis B virus infected patients and detection by ARCHITECT HBsAg quantitative.

Objective: To analyze the amino acid substitution caused by mutations in the major hydrophilic region (MHR) of the S-region genes in the serum samples of occult hepatitis B virus infection (OBI), and to explore the reasons for the missed detection of HBsAg. Method: The full-length gene of the S-region in hepatitis B virus(HBV) in the chronic hepatitis B virus(CHB)(10 samples) and OBI groups(42 samples) was amplified using a lab-developed, two-round PCR amplification technology. The PCR amplification products were sequenced/clone sequenced, and the nucleotide sequences of the S-region gene in HBV were compared to the respective genotype consensus sequence. Results: Only 20 of the 42 samples in the OBI group had the S-region genes successfully amplified, with the lowest HBV DNA load of 20.1IU/ml. As S-region genes in HBV, 68 cloned strains were sequenced. In the OBI and CHB groups MHR region, with a mutation rate of 3.21% (155/4828) and 0.70% (5/710). The genetic mutation rate was significantly higher in the OBI group than in the CHB group (P<0.05). The common mutation types in the MHR region were: I126T, L162R, K122E, C124R, and C147Y.Mutations at s122, s126, and s162 were associated with subgenotypes, most of which being C genotypes. The high-frequency mutation sites L162R and K122E found in this study have not been reported in previous literature. Conclusion: The results of this study confirmed that MHR mutations can cause the missed detection of HBsAg, giving rise to OBI.

Human epidermal growth factor receptor-2 expression and subsequent dynamic changes in patients with ovarian cancer.

Human epidermal growth factor receptor-2 (HER2)-targeting drugs are increasingly being incorporated into therapeutic paradigms for non-breast cancers, yet studies on HER2 expression in ovarian cancer (OC) are inadequate. Here, we studied the HER2 status and dynamic changes in OC by reviewing the records of patients who underwent HER2 testing at a single institution. Clinical parameters, including histology, BRCA status, and immunohistochemistry (IHC), were evaluated alongside HER2 expression, timing, and anatomical location. Among 200 patients, 28% and 6% exhibited expression scores of 2+ and 3+, respectively. HER2 3+ scores were observed in 23%, 11%, 9%, and 5% of mucinous, endometrioid, clear cell, and high-grade serous tumors, respectively, and were exclusively identified in BRCA-wildtype, mismatch repair-proficient, or PD-L1-low-expressing tumors. The TP53 mutation rate was low, whereas ARID1A, KRAS, and PIK3CA mutations were relatively more prevalent with HER2 scores of 2+ or 3+ than with 0 or 1+. Four of the five tumors with an HER2 3+ score exhibited ERBB2 amplification. Among 19 patients who underwent multiple time-lagged biopsies, 11 showed increased HER2 expression in subsequent biopsies. Patients with HER2-overexpressing OC exhibited distinct histological, IHC, and genomic profiles. HER2-targeting agents are potential options for BRCA-wildtype patients, particularly as later lines of treatment.

Environmental and genetic influence on the rate and spectrum of spontaneous mutations in Escherichia coli.

Spontaneous mutations are the ultimate source of novel genetic variation on which evolution operates. Although mutation rate is often discussed as a single parameter in evolution, it comprises multiple distinct types of changes at the level of DNA. Moreover, the rates of these distinct changes can be independently influenced by genomic background and environmental conditions. Using fluctuation tests, we characterized the spectrum of spontaneous mutations in Escherichia coli grown in low and high glucose environments. These conditions are known to affect the rate of spontaneous mutation in wild-type MG1655, but not in a ΔluxS deletant strain - a gene with roles in both quorum sensing and the recycling of methylation products used in E. coli's DNA repair process. We find an increase in AT>GC transitions in the low glucose environment, suggesting that processes relating to the production or repair of this mutation could drive the response of overall mutation rate to glucose concentration. Interestingly, this increase in AT>GC transitions is maintained by the glucose non-responsive ΔluxS deletant. Instead, an elevated rate of GC>TA transversions, more common in a high glucose environment, leads to a net non-responsiveness of overall mutation rate for this strain. Our results show how relatively subtle changes, such as the concentration of a carbon substrate or loss of a regulatory gene, can substantially influence the amount and nature of genetic variation available to selection.

Targeted accurate RNA consensus sequencing (tARC-seq) reveals mechanisms of replication error affecting SARS-CoV-2 divergence.

RNA viruses, like SARS-CoV-2, depend on their RNA-dependent RNA polymerases (RdRp) for replication, which is error prone. Monitoring replication errors is crucial for understanding the virus's evolution. Current methods lack the precision to detect rare de novo RNA mutations, particularly in low-input samples such as those from patients. Here we introduce a targeted accurate RNA consensus sequencing method (tARC-seq) to accurately determine the mutation frequency and types in SARS-CoV-2, both in cell culture and clinical samples. Our findings show an average of 2.68 × 10-5 de novo errors per cycle with a C > T bias that cannot be solely attributed to APOBEC editing. We identified hotspots and cold spots throughout the genome, correlating with high or low GC content, and pinpointed transcription regulatory sites as regions more susceptible to errors. tARC-seq captured template switching events including insertions, deletions and complex mutations. These insights shed light on the genetic diversity generation and evolutionary dynamics of SARS-CoV-2.

Mutation rate heterogeneity at the sub-gene scale due to local DNA hypomethylation.

Local mutation rates in human are highly heterogeneous, with known variability at the scale of megabase-sized chromosomal domains, and, on the other extreme, at the scale of oligonucleotides. The intermediate, kilobase-scale heterogeneity in mutation risk is less well characterized. Here, by analyzing thousands of somatic genomes, we studied mutation risk gradients along gene bodies, representing a genomic scale spanning roughly 1-10 kb, hypothesizing that different mutational mechanisms are differently distributed across gene segments. The main heterogeneity concerns several kilobases at the transcription start site and further downstream into 5' ends of gene bodies; these are commonly hypomutated with several mutational signatures, most prominently the ubiquitous C > T changes at CpG dinucleotides. The width and shape of this mutational coldspot at 5' gene ends is variable across genes, and corresponds to variable interval of lowered DNA methylation depending on gene activity level and regulation. Such hypomutated loci, at 5' gene ends or elsewhere, correspond to DNA hypomethylation that can associate with various landmarks, including intragenic enhancers, Polycomb-marked regions, or chromatin loop anchor points. Tissue-specific DNA hypomethylation begets tissue-specific local hypomutation. Of note, direction of mutation risk is inverted for AID/APOBEC3 cytosine deaminase activity, whose signatures are enriched in hypomethylated regions.

Role of SARS-CoV-2 mutations in the evolution of the COVID-19 pandemic.

OBJECTIVES: The SARS-CoV-2 pandemic and large-scale genomic surveillance provided an exceptional opportunity to analyze mutations that appeared over three years in viral genomes. Here we studied mutations and their epidemic consequences for SARS-CoV-2 genomes from our center. METHODS: We analyzed 61,397 SARS-CoV-2 genomes we sequenced from respiratory samples for genomic surveillance. Mutations frequencies were calculated using Nextclade, Microsoft Excel, and an in-house Python script. RESULTS: A total of 22,225 nucleotide mutations were identified, 220 (1.0%) being each at the root of ≥836 genomes, classifying mutations as 'hyperfertile'. Two seeded the European pandemic: P323L in RNA polymerase, associated with an increased mutation rate, and D614G in spike that improved fitness. Most 'hyperfertile' mutations occurred in areas not predicted with increased virulence. Their mean number was 8±6 (0-22) per 1000 nucleotides per gene. They were 3.7-times more frequent in accessory than informational genes (13.8 versus 3.7/1000 nucleotides). Particularly, they were 4.1-times more frequent in ORF8 than in the RNA polymerase gene. Interestingly, stop codons were present in 97 positions, almost only in accessory genes, including ORF8 (21/100 codons). CONCLUSIONS: most 'hyperfertile' mutations did not predict emergence of a new epidemic, and some were stop codons indicating the existence of so-named 'non-virulence' genes.

Evolutionary graph theory beyond pairwise interactions: Higher-order network motifs shape times to fixation in structured populations.

To design population topologies that can accelerate rates of solution discovery in directed evolution problems or for evolutionary optimization applications, we must first systematically understand how population structure shapes evolutionary outcome. Using the mathematical formalism of evolutionary graph theory, recent studies have shown how to topologically build networks of population interaction that increase probabilities of fixation of beneficial mutations, at the expense, however, of longer fixation times, which can slow down rates of evolution, under elevated mutation rate. Here we find that moving beyond dyadic interactions in population graphs is fundamental to explain the trade-offs between probabilities and times to fixation of new mutants in the population. We show that higher-order motifs, and in particular three-node structures, allow the tuning of times to fixation, without changes in probabilities of fixation. This gives a near-continuous control over achieving solutions that allow for a wide range of times to fixation. We apply our algorithms and analytic results to two evolutionary optimization problems and show that the rate of solution discovery can be tuned near continuously by adjusting the higher-order topology of the population. We show that the effects of population structure on the rate of evolution critically depend on the optimization landscape and find that decelerators, with longer times to fixation of new mutants, are able to reach the optimal solutions faster than accelerators in complex solution spaces. Our results highlight that no one population topology fits all optimization applications, and we provide analytic and computational tools that allow for the design of networks suitable for each specific task.

Self-replicating artificial neural networks give rise to universal evolutionary dynamics.

In evolutionary models, mutations are exogenously introduced by the modeler, rather than endogenously introduced by the replicator itself. We present a new deep-learning based computational model, the self-replicating artificial neural network (SeRANN). We train it to (i) copy its own genotype, like a biological organism, which introduces endogenous spontaneous mutations; and (ii) simultaneously perform a classification task that determines its fertility. Evolving 1,000 SeRANNs for 6,000 generations, we observed various evolutionary phenomena such as adaptation, clonal interference, epistasis, and evolution of both the mutation rate and the distribution of fitness effects of new mutations. Our results demonstrate that universal evolutionary phenomena can naturally emerge in a self-replicator model when both selection and mutation are implicit and endogenous. We therefore suggest that SeRANN can be applied to explore and test various evolutionary dynamics and hypotheses.

Correction of non-random mutational biases along a linear bacterial chromosome by the mismatch repair endonuclease NucS.

The linear chromosome of Streptomyces exhibits a highly compartmentalized structure with a conserved central region flanked by variable arms. As double strand break (DSB) repair mechanisms play a crucial role in shaping the genome plasticity of Streptomyces, we investigated the role of EndoMS/NucS, a recently characterized endonuclease involved in a non-canonical mismatch repair (MMR) mechanism in archaea and actinobacteria, that singularly corrects mismatches by creating a DSB. We showed that Streptomyces mutants lacking NucS display a marked colonial phenotype and a drastic increase in spontaneous mutation rate. In vitro biochemical assays revealed that NucS cooperates with the replication clamp to efficiently cleave G/T, G/G and T/T mismatched DNA by producing DSBs. These findings are consistent with the transition-shifted mutational spectrum observed in the mutant strains and reveal that NucS-dependent MMR specific task is to eliminate G/T mismatches generated by the DNA polymerase during replication. Interestingly, our data unveil a crescent-shaped distribution of the transition frequency from the replication origin towards the chromosomal ends, shedding light on a possible link between NucS-mediated DSBs and Streptomyces genome evolution.

Mutation Rate and Effective Population Size of the Model Cooperative Bacterium Myxococcus xanthus.

Intrinsic rates of genetic mutation have diverged greatly across taxa and exhibit statistical associations with several other parameters and features. These include effective population size (Ne), genome size, and gametic multicellularity, with the latter being associated with both increased mutation rates and decreased effective population sizes. However, data sufficient to test for possible relationships between microbial multicellularity and mutation rate (µ) are lacking. Here, we report estimates of two key population-genetic parameters, Ne and µ, for Myxococcus xanthus, a bacterial model organism for the study of aggregative multicellular development, predation, and social swarming. To estimate µ, we conducted an ∼400-day mutation accumulation experiment with 46 lineages subjected to regular single colony bottlenecks prior to clonal regrowth. Upon conclusion, we sequenced one clonal-isolate genome per lineage. Given collective evolution for 85,323 generations across all lines, we calculate a per base-pair mutation rate of ∼5.5 × 10-10 per site per generation, one of the highest mutation rates among free-living eubacteria. Given our estimate of µ, we derived Ne at ∼107 from neutral diversity at four-fold degenerate sites across two dozen M. xanthus natural isolates. This estimate is below average for eubacteria and strengthens an already clear negative correlation between µ and Ne in prokaryotes. The higher and lower than average mutation rate and Ne for M. xanthus, respectively, amplify the question of whether any features of its multicellular life cycle-such as group-size reduction during fruiting-body development-or its highly structured spatial distribution have significantly influenced how these parameters have evolved.

Increased genomic instability and reshaping of tissue microenvironment underlie oncogenic properties of Arid1a mutations.

Oncogenic mutations accumulating in many chromatin-associated proteins have been identified in different tumor types. With a mutation rate from 10 to 57%, ARID1A has been widely considered a tumor suppressor gene. However, whether this role is mainly due to its transcriptional-related activities or its ability to preserve genome integrity is still a matter of intense debate. Here, we show that ARID1A is largely dispensable for preserving enhancer-dependent transcriptional regulation, being ARID1B sufficient and required to compensate for ARID1A loss. We provide in vivo evidence that ARID1A is mainly required to preserve genomic integrity in adult tissues. ARID1A loss primarily results in DNA damage accumulation, interferon type I response activation, and chronic inflammation leading to tumor formation. Our data suggest that in healthy tissues, the increased genomic instability that follows ARID1A mutations and the selective pressure imposed by the microenvironment might result in the emergence of aggressive, possibly immune-resistant, tumors.

Unravelling the link between SARS-CoV-2 mutation frequencies, patient comorbidities, and structural dynamics.

Genomic surveillance is crucial for tracking emergence and spread of novel variants of pathogens, such as SARS-CoV-2, to inform public health interventions and to enforce control measures. However, in some settings especially in low- and middle- income counties, where sequencing platforms are limited, only certain patients get to be selected for sequencing surveillance. Here, we show that patients with multiple comorbidities potentially harbour SARS-CoV-2 with higher mutation rates and thus deserve more attention for genomic surveillance. The relationship between the patient comorbidities, and type of amino acid mutations was assessed. Correlation analysis showed that there was a significant tendency for mutations to occur within the ORF1a region for patients with higher number of comorbidities. Frequency analysis of the amino acid substitution within ORF1a showed that nsp3 P822L of the PLpro protease was one of the highest occurring mutations. Using molecular dynamics, we simulated that the P822L mutation in PLpro represents a system with lower Root Mean Square Deviation (RMSD) fluctuations, and consistent Radius of gyration (Rg), Solvent Accessible Surface Area (SASA) values-indicate a much stabler protein than the wildtype. The outcome of this study will help determine the relationship between the clinical status of a patient and the mutations of the infecting SARS-CoV-2 virus.

The evolutionary safety of mutagenic drugs should be assessed before drug approval.

Some drugs increase the mutation rate of their target pathogen, a potentially concerning mechanism as the pathogen might evolve faster toward an undesired phenotype. We suggest a four-step assessment of evolutionary safety for the approval of such treatments.

Effects of parental age and polymer composition on short tandem repeat de novo mutation rates.

Short tandem repeats (STRs) are hotspots of genomic variability in the human germline because of their high mutation rates, which have long been attributed largely to polymerase slippage during DNA replication. This model suggests that STR mutation rates should scale linearly with a father's age, as progenitor cells continually divide after puberty. In contrast, it suggests that STR mutation rates should not scale with a mother's age at her child's conception, since oocytes spend a mother's reproductive years arrested in meiosis II and undergo a fixed number of cell divisions that are independent of the age at ovulation. Yet, mirroring recent findings, we find that STR mutation rates covary with paternal and maternal age, implying that some STR mutations are caused by DNA damage in quiescent cells rather than polymerase slippage in replicating progenitor cells. These results echo the recent finding that DNA damage in oocytes is a significant source of de novo single nucleotide variants and corroborate evidence of STR expansion in postmitotic cells. However, we find that the maternal age effect is not confined to known hotspots of oocyte mutagenesis, nor are postzygotic mutations likely to contribute significantly. STR nucleotide composition demonstrates divergent effects on de novo mutation (DNM) rates between sexes. Unlike the paternal lineage, maternally derived DNMs at A/T STRs display a significantly greater association with maternal age than DNMs at G/C-containing STRs. These observations may suggest the mechanism and developmental timing of certain STR mutations and contradict prior attribution of replication slippage as the primary mechanism of STR mutagenesis.

Emergence of a multilocus mutator genotype in mutator Escherichia coli experimental populations under repeated lethal selection.

Mutator alleles, which confer increased mutation rates, are known to spontaneously emerge and "hitchhike" to fixation in evolving asexual populations. Theory predicts that in an evolving asexual mutator population, a second mutator allele may spontaneously arise and hitchhike to fixation. Here, we describe an empirical test of the hypothesis of repeated hitchhiking. The starting population was a clonal strain of mutL-Escherichia coli whose mutation rate was 100-fold higher than wild type. We exposed the mutL- strain to a series of three antibiotics in increasing order of selective strength: fosfomycin, rifampicin, and streptomycin. Two independent replicates of the experiment were performed. As predicted, elevated mutation rates and enrichment for multilocus mutators (which bear more than one mutator allele) were observed in the end point populations of both experiments. DNA sequencing revealed an identical spontaneous 1-bp insertion in the mutator gene mutT in both end point populations. In the multilocus mutators, the causal relationship between the mutT- mutations and the increase in mutation rate was supported with mutT+ plasmid complementation tests. Surprisingly, when the experiment was repeated with the antibiotics deployed in decreasing order of selective strength, enrichment for multilocus mutators was not observed. Our data support the likelihood that the mutT- mutations rose to fixation in both populations, consistent with the hypothesis of repeated mutator hitchhiking. The escalation of mutation rates in asexual populations is relevant to multiple biological scenarios, including antibiotic resistance, host-pathogen interactions, and carcinogenesis.

High germline mutation rates, but not extreme population outbreaks, influence genetic diversity in a keystone coral predator.

Lewontin's paradox, the observation that levels of genetic diversity (π) do not scale linearly with census population size (Nc) variation, is an evolutionary conundrum. The most extreme mismatches between π and Nc are found for highly abundant marine invertebrates. Yet, the influences of new mutations on π relative to extrinsic processes such as Nc fluctuations are unknown. Here, we provide the first germline mutation rate (µ) estimate for a marine invertebrate in corallivorous crown-of-thorns sea stars (Acanthaster cf. solaris). We use high-coverage whole-genome sequencing of 14 parent-offspring trios alongside empirical estimates of Nc in Australia's Great Barrier Reef to jointly examine the determinants of π in populations undergoing extreme Nc fluctuations. The A. cf. solaris mean µ was 9.13 x 10-09 mutations per-site per-generation (95% CI: 6.51 x 10-09 to 1.18 x 10-08), exceeding estimates for other invertebrates and showing greater concordance with vertebrate mutation rates. Lower-than-expected Ne (~70,000-180,000) and low Ne/Nc values (0.0047-0.048) indicated weak influences of population outbreaks on long-term π. Our findings are consistent with elevated µ evolving in response to reduced Ne and generation time length, with important implications for explaining high mutational loads and the determinants of genetic diversity in marine invertebrate taxa.

Application of next-generation sequencing in the detection of low-abundance mutations.

Mutation accumulation in somatic cells contributes to cancer development, aging and many non-malignant diseases. The true mutation frequency in normal cells is extremely low, which presents a challenge in detecting these mutations at such low frequencies. The emergence of next-generation sequencing (NGS) technology enables direct detection of rare mutations across the entire genome of any species. This breakthrough overcomes numerous limitations of traditional mutation detection techniques that rely on specific detection models and sites. However, conventional NGS is limited in its application for detecting low-frequency mutations due to its high sequencing error rate. To address this challenge, high-accuracy NGS sequencing techniques based on molecular consensus sequencing strategies have been developed. These techniques have the ability to correct sequencing errors, resulting in error rates lower than 10-7, are expected to serve as effective tools for low-frequency mutation detection. Error-corrected NGS (ecNGS) techniques hold great potential in various areas, including safety evaluation and research on environmental mutagens, risk assessment of cell and gene therapy drugs, population health risk monitoring, and fundamental research in life sciences. This review highlights a comprehensive review of the research progress in low-frequency mutation detection techniques based on NGS, and provides a glimpse into their potential applications. It also offers an outlook on the potential applications of these techniques, thereby providing valuable insights for further development, research, and application of this technology in relevant fields.

Low-frequency somatic mutations are heritable in tropical trees Dicorynia guianensis and Sextonia rubra.

Somatic mutations potentially play a role in plant evolution, but common expectations pertaining to plant somatic mutations remain insufficiently tested. Unlike in most animals, the plant germline is assumed to be set aside late in development, leading to the expectation that plants accumulate somatic mutations along growth. Therefore, several predictions were made on the fate of somatic mutations: mutations have generally low frequency in plant tissues; mutations at high frequency have a higher chance of intergenerational transmission; branching topology of the tree dictates mutation distribution; and exposure to UV (ultraviolet) radiation increases mutagenesis. To provide insights into mutation accumulation and transmission in plants, we produced two high-quality reference genomes and a unique dataset of 60 high-coverage whole-genome sequences of two tropical tree species, Dicorynia guianensis (Fabaceae) and Sextonia rubra (Lauraceae). We identified 15,066 de novo somatic mutations in D. guianensis and 3,208 in S. rubra, surprisingly almost all found at low frequency. We demonstrate that 1) low-frequency mutations can be transmitted to the next generation; 2) mutation phylogenies deviate from the branching topology of the tree; and 3) mutation rates and mutation spectra are not demonstrably affected by differences in UV exposure. Altogether, our results suggest far more complex links between plant growth, aging, UV exposure, and mutation rates than commonly thought.

N-Acetylcysteine Alters Disease Progression and Increases Janus Kinase Mutation Frequency in a Mouse Model of Precursor B-Cell Acute Lymphoblastic Leukemia.

B-cell acute lymphoblastic leukemia (B-ALL) is the most prevalent type of cancer in young children and is associated with high levels of reactive oxygen species (ROS). The antioxidant N-acetylcysteine (NAC) was tested for its ability to alter disease progression in a mouse model of B-ALL. Mb1-CreΔPB mice have deletions in genes encoding PU.1 and Spi-B in B cells and develop B-ALL at 100% incidence. Treatment of Mb1-CreΔPB mice with NAC in drinking water significantly reduced the frequency of CD19+ pre-B-ALL cells infiltrating the thymus at 11 weeks of age. However, treatment with NAC did not reduce leukemia progression or increase survival by a median 16 weeks of age. NAC significantly altered gene expression in leukemias in treated mice. Mice treated with NAC had increased frequencies of activating mutations in genes encoding Janus kinases 1 and 3. In particular, frequencies of Jak3 R653H mutations were increased in mice treated with NAC compared with control drinking water. NAC opposed oxidization of PTEN protein ROS in cultured leukemia cells. These results show that NAC alters leukemia progression in this mouse model, ultimately selecting for leukemias with high Jak3 R653H mutation frequencies. SIGNIFICANCE STATEMENT: In a mouse model of precursor B-cell acute lymphoblastic leukemia associated with high levels of reactive oxygen species, treatment with N-acetylcysteine did not delay disease progression but instead selected for leukemic clones with activating R653H mutations in Janus kinase 3.

Geometric analysis of SARS-CoV-2 variants.

SARS-CoV-2 as a severe respiratory disease has been prevalent around the world since its first discovery in 2019.As a single-stranded RNA virus, its high mutation rate makes its variants manifold and enables some of them to have high pathogenicity, such as Omicron variant, the most prevalent virus now. Research on the relationship of these SARS-CoV-2 variants, especially exploring their difference is a hot issue. In this study, we constructed a geometric space to represent all SARS-CoV-2 sequences of different variants. An alignment-free method: natural vector method was utilized to establish genome space. The genome space of SARS-CoV-2 was constructed based on the 24-dimensional natural vector and the appropriate metric was determined through performing phylogenetic analysises. Phylogenetic trees of different lineages constructed under the selected natural vector and metric coincided with the lineage naming standards, which means lineages with same alphabetical prefix cluster in phylogenetic trees. Furthermore, the relationships between the various GISAID clades as depicted by the natural graph primarily matched the description provided in the GISAID clade naming.The validity of our geometric space was demonstrated by these phylogenetic analysis results. So in this research, we constructed a geometry space for the genomes of the novel coronavirus SARS-CoV-2, which allows us to compare the different variants. Our geometric space is valuable for resolving the issues insides the virus.