Extreme mutation rates in microbes and cancer cells can result in error-induced extinction (EEX), where every descendant cell eventually acquires a lethal mutation. In this work, we investigate critical birth-death processes with n distinct types as a birth-death model of EEX in a growing population. Each type-i cell divides independently ( i ) → ( i ) + ( i ) or mutates ( i ) → ( i + 1 ) at the same rate. The total number of cells grows exponentially as a Yule process until a cell of type-n appears, which cell type can only divide or die at rate one. This makes the whole process critical and hence after the exponentially growing phase eventually all cells die with probability one. We present large-time asymptotic results for the general n-type critical birth-death process. We find that the mass function of the number of cells of type-k has algebraic and stationary tail ( size ) - 1 - χ k , with χ k = 2 1 - k , for k = 2 , ⋯ , n , in sharp contrast to the exponential tail of the first type. The same exponents describe the tail of the asymptotic survival probability ( time ) - ξ k . We present applications of the results for studying extinction due to intolerable mutation rates in biological populations.

Klebsiella pneumoniae strains that produce Klebsiella pneumoniae Carbapenemase (KPC) variants displaying resistance to ceftazidime-avibactam (CZA) often remain susceptible to meropenem (MEM), suggesting a potential therapeutic use of this carbapenem antibiotic. However, in vitro studies indicate that these sorts of strains can mutate becoming MEM-resistant, raising concerns about the effectiveness of carbapenems as treatment option. We have studied mutation rates occurring from the reversion of MEM-susceptible KPC-114 to MEM-resistant KPC-2, in CZA-resistant K. pneumoniae belonging to ST11. Two-step fluctuation assays (FAs) were conducted. In brief, initial cultures of KPC-114-producing K. pneumoniae showing 1 µg/mL MEM MIC were spread on Mueller-Hinton agar plates containing 2-8 µg/mL MEM. A second step of FA, at 4-16 µg/mL MEM was performed from a mutant colony obtained at 2 µg/mL MEM. Mutation rates were calculated using maximum likelihood estimation. Parental and mutant strains were sequenced by Illumina NextSeq, and mutations were predicted by variant-calling analysis. At 8 µg/mL MEM, mutants derived from parental CZA-resistant (MIC ≥ 64 µg/mL)/MEM-susceptible (MIC = 1 µg/mL) KPC-114-positive K. pneumoniae exhibited an accumulative mutation rate of 3.05 × 10-19 mutations/cell/generation, whereas at 16 µg/mL MEM an accumulative mutation rate of 1.33 × 10-19 mutations/cell/generation resulted in the reversion of KPC-114 (S181_P182 deletion) to KPC-2. These findings highlight that the reversion of MEM-susceptible KPC-114 to MEM-resistant KPC-2, in CZA-resistant K. pneumoniae ST11 is related to low mutation rates suggesting a low risk of therapeutic failure. In vivo investigations are necessary to confirm the clinical potential of MEM against CZA-resistant KPC variants.IMPORTANCEThe emergence of ceftazidime-avibactam (CZA) resistance among carbapenem-resistant Klebsiella pneumoniae is a major concern due to the limited therapeutic options. Strikingly, KPC mutations mediating CZA resistance are generally associated with meropenem susceptibility, suggesting a potential therapeutic use of this carbapenem antibiotic. However, the reversion of meropenem-susceptible to meropenem-resistant could be expected. Therefore, knowing the mutation rate related to this genetic event is essential to estimate the potential use of meropenem against CZA-resistant KPC-producing K. pneumoniae. In this study, we demonstrate, in vitro, that under high concentrations of meropenem, reversion of KPC-114 to KPC-2 in CZA-resistant/meropenem-susceptible K. pneumoniae belonging to the global high-risk ST11 is related to low mutation rates.

Chemical mutagenesis-driven forward genetic screens are pivotal in unveiling gene functions, yet identifying causal mutations behind phenotypes remains laborious, hindering their high-throughput application. Here, we reveal a non-uniform mutation rate caused by Ethyl Methane Sulfonate (EMS) mutagenesis in the C. elegans genome, indicating that mutation frequency is influenced by proximate sequence context and chromatin status. Leveraging these factors, we developed a machine learning enhanced pipeline to create a comprehensive EMS mutagenesis probability map for the C. elegans genome. This map operates on the principle that causative mutations are enriched in genetic screens targeting specific phenotypes among random mutations. Applying this map to Whole Genome Sequencing (WGS) data of genetic suppressors that rescue a C. elegans ciliary kinesin mutant, we successfully pinpointed causal mutations without generating recombinant inbred lines. This method can be adapted in other species, offering a scalable approach for identifying causal genes and revitalizing the effectiveness of forward genetic screens.

AbstractMutation rates vary widely along genomes and across inheritance systems. This suggests that complex traits-resulting from the contributions of multiple determinants-might be composite in terms of the underlying mutation rates. Here we investigate through mathematical modeling whether such a heterogeneity may drive changes in a trait\'s architecture, especially in fluctuating environments, where phenotypic instability can be beneficial. We first identify a convexity principle related to the shape of the trait\'s fitness function, setting conditions under which composite architectures should be adaptive or, conversely and more commonly, should be selected against. Simulations reveal, however, that applying this principle to realistic evolving populations requires taking into account pervasive epistatic interactions that take place in the system. Indeed, the fate of a mutation affecting the architecture depends on the (epi)genetic background, which itself depends on the current architecture in the population. We tackle this problem by borrowing the adaptive dynamics framework from evolutionary ecology-where it is routinely used to deal with such resident/mutant dependencies-and find that the principle excluding composite architectures generally prevails. Yet the predicted evolutionary trajectories will typically depend on the initial architecture, possibly resulting in historical contingencies. Finally, by relaxing the large population size assumption, we unexpectedly find that not only the strength of selection on a trait\'s architecture but also its direction depend on population size, revealing a new occurrence of the recently identified phenomenon coined \"sign inversion.\"

How does social complexity depend on population size and cultural transmission? Kinship structures in traditional societies provide a fundamental illustration, where cultural rules between clans determine people\'s marriage possibilities. Here, we propose a simple model of kinship interactions that considers kin and in-law cooperation and sexual rivalry. In this model, multiple societies compete. Societies consist of multiple families with different cultural traits and mating preferences. These values determine interactions and hence the growth rate of families and are transmitted to offspring with mutations. Through a multilevel evolutionary simulation, family traits and preferences are grouped into multiple clans with interclan mating preferences. It illustrates the emergence of kinship structures as the spontaneous formation of interdependent cultural associations. Emergent kinship structures are characterized by the cycle length of marriage exchange and the number of cycles in society. We numerically and analytically clarify their parameter dependence. The relative importance of cooperation versus rivalry determines whether attraction or repulsion exists between families. Different structures evolve as locally stable attractors. The probabilities of formation and collapse of complex structures depend on the number of families and the mutation rate, showing characteristic scaling relationships. It is now possible to explore macroscopic kinship structures based on microscopic interactions, together with their environmental dependence and the historical causality of their evolution. We propose the basic causal mechanism of the formation of typical human social structures by referring to ethnographic observations and concepts from statistical physics and multilevel evolution. Such interdisciplinary collaboration will unveil universal features in human societies.

The mouse serves as a mammalian model for understanding the nature of variation from new mutations, a question that has both evolutionary and medical significance. Previous studies suggest that the rate of single-nucleotide mutations (SNMs) in mice is ∼50% of that in humans. However, information largely comes from studies involving the C57BL/6 strain, and there is little information from other mouse strains. Here, we study the mutations that accumulated in 59 mouse lines derived from four inbred strains that are commonly used in genetics and clinical research (BALB/cAnNRj, C57BL/6JRj, C3H/HeNRj, and FVB/NRj), maintained for eight to nine generations by brother-sister mating. By analyzing Illumina whole-genome sequencing data, we estimate that the average rate of new SNMs in mice is ∼μ = 6.7 × 10-9. However, there is substantial variation in the spectrum of SNMs among strains, so the burden from new mutations also varies among strains. For example, the FVB strain has a spectrum that is markedly skewed toward C→A transversions and is likely to experience a higher deleterious load than other strains, due to an increased frequency of nonsense mutations in glutamic acid codons. Finally, we observe substantial variation in the rate of new SNMs among DNA sequence contexts, CpG sites, and their adjacent nucleotides playing an important role.

Somatic cells accumulate genomic alterations with age; however, our understanding of mitochondrial DNA (mtDNA) mosaicism remains limited. Here we investigated the genomes of 2,096 clones derived from three cell types across 31 donors, identifying 6,451 mtDNA variants with heteroplasmy levels of ≳0.3%. While the majority of these variants were unique to individual clones, suggesting stochastic acquisition with age, 409 variants (6%) were shared across multiple embryonic lineages, indicating their origin from heteroplasmy in fertilized eggs. The mutational spectrum exhibited replication-strand bias, implicating mtDNA replication as a major mutational process. We evaluated the mtDNA mutation rate (5.0 × 10-8 per base pair) and a turnover frequency of 10-20 per year, which are fundamental components shaping the landscape of mtDNA mosaicism over a lifetime. The expansion of mtDNA-truncating mutations toward homoplasmy was substantially suppressed. Our findings provide comprehensive insights into the origins, dynamics and functional consequences of mtDNA mosaicism in human somatic cells.

During each cell cycle, the process of DNA replication timing is tightly regulated to ensure the accurate duplication of the genome. The extent and significance of alterations in this process during malignant transformation have not been extensively explored. Here, we assess the impact of altered replication timing (ART) on cancer evolution by analysing replication-timing sequencing of cancer and normal cell lines and 952 whole-genome sequenced lung and breast tumours. We find that 6%-18% of the cancer genome exhibits ART, with regions with a change from early to late replication displaying an increased mutation rate and distinct mutational signatures. Whereas regions changing from late to early replication contain genes with increased expression and present a preponderance of APOBEC3-mediated mutation clusters and associated driver mutations. We demonstrate that ART occurs relatively early during cancer evolution and that ART may have a stronger correlation with mutation acquisition than alterations in chromatin structure.

The endonuclease activity of Pms1 directs mismatch repair by generating a nick in the newly replicated DNA strand. Inactivating Pms2, the human homologue of yeast Pms1, increases the chances of colorectal and uterine cancers. Here we use whole genome sequencing to show that loss of this endonuclease activity, via the pms1-DE variant, results in strong mutator effects throughout the Saccharomyces cerevisiae genome. Mutation rates are strongly increased for mutations resulting from all types of single-base substitutions and for a wide variety of single- and multi-base indel mutations. Rates for these events are further increased in strains combining pms1-DE with mutator variants of each of the three major leading and lagging strand replicases. In all cases, mutation rates, spectra, biases, and context preferences are statistically indistinguishable from strains with equivalent polymerases but lacking initial mismatch recognition due to deletion of MSH2. This implies that, across the nuclear genome, strand discrimination via the Pms1 endonuclease is as important for MMR as is initial mismatch recognition by Msh2 heterodimers.

The best predictive marker for the expected efficacy of PARP inhibitor therapy is mutations in BRCA1/2 or other homologous recombination repair genes. These tests are part of routine molecular pathology diagnostics. Among 281 patients with prostate adenocarcinoma, somatic pathogenic mutations in one of these genes were identified in 21.4% of patients. In 28.5% of the patients, the test was unsuccessful; the main limitation of successful testing was the age of the paraffin blocks and low DNA concentration. In the case of BRCA1/2 testing, the success rate was significantly reduced for samples older than 5 years, while in tests involving a broader set of homologous recombination repair genes, the success rate was significantly reduced for samples older than 2 years. Therefore, it is very important to test high-risk prostate cancers at the time of primary diagnosis, and probably also liquid biopsy testing of circulating tumor DNA will play an important role in safe diagnosis in the near future.