Advantageous Mutations Research Articles

Accumulation of Oncogenic Mutations During Progression from Healthy Tissue to Cancer

Cancers are typically fueled by sequential accumulation of driver mutations in a previously healthy cell. Some of these mutations, such as inactivation of the first copy of a tumor suppressor gene, can be neutral, and some, like those resulting in activation of oncogenes, may provide cells with a selective growth advantage. We study a multi-type branching process that starts with healthy tissue in homeostasis and models accumulation of neutral and advantageous mutations on the way to cancer. We provide results regarding the sizes of premalignant populations and the waiting times to the first cell with a particular combination of mutations, including the waiting time to malignancy. Finally, we apply our results to two specific biological settings: initiation of colorectal cancer and age incidence of chronic myeloid leukemia. Our model allows for any order of neutral and advantageous mutations and can be applied to other evolutionary settings.

Pervasive findings of directional selection realize the promise of ancient DNA to elucidate human adaptation.

We present a method for detecting evidence of natural selection in ancient DNA time-series data that leverages an opportunity not utilized in previous scans: testing for a consistent trend in allele frequency change over time. By applying this to 8433 West Eurasians who lived over the past 14000 years and 6510 contemporary people, we find an order of magnitude more genome-wide significant signals than previous studies: 347 independent loci with >99% probability of selection. Previous work showed that classic hard sweeps driving advantageous mutations to fixation have been rare over the broad span of human evolution, but in the last ten millennia, many hundreds of alleles have been affected by strong directional selection. Discoveries include an increase from ∼0% to ∼20% in 4000 years for the major risk factor for celiac disease at HLA-DQB1 ; a rise from ∼0% to ∼8% in 6000 years of blood type B; and fluctuating selection at the TYK2 tuberculosis risk allele rising from ∼2% to ∼9% from ∼5500 to ∼3000 years ago before dropping to ∼3%. We identify instances of coordinated selection on alleles affecting the same trait, with the polygenic score today predictive of body fat percentage decreasing by around a standard deviation over ten millennia, consistent with the "Thrifty Gene" hypothesis that a genetic predisposition to store energy during food scarcity became disadvantageous after farming. We also identify selection for combinations of alleles that are today associated with lighter skin color, lower risk for schizophrenia and bipolar disease, slower health decline, and increased measures related to cognitive performance (scores on intelligence tests, household income, and years of schooling). These traits are measured in modern industrialized societies, so what phenotypes were adaptive in the past is unclear. We estimate selection coefficients at 9.9 million variants, enabling study of how Darwinian forces couple to allelic effects and shape the genetic architecture of complex traits.

Gene Duplication and Functional Diversification of MADS-Box Genes in Malus × domestica following WGD: Implications for Fruit Type and Floral Organ Evolution.

The evolution of the MADS-box gene family is essential for the rapid differentiation of floral organs and fruit types in angiosperms. Two key processes drive the evolution of gene families: gene duplication and functional differentiation. Duplicated copies provide the material for variation, while advantageous mutations can confer new functions on gene copies. In this study, we selected the Rosaceae family, which includes a variety of fruit types and flower organs, as well as species that existed before and after whole-genome duplication (WGD). The results indicate that different fruit types are associated with different copies of MADS-box gene family duplications and WGD events. While most gene copies derived from WGD have been lost, MADS-box genes not only retain copies derived from WGD but also undergo further gene duplication. The sequences, protein structures, and expression patterns of these gene copies have undergone significant differentiation. This work provides a clear example of MADS-box genes in the context of gene duplication and functional differentiation, offering new insights into the evolution of fruit types and floral organs.

Rational modification of Neisseria meningitidis β1,3-N-acetylglucosaminyltransferase for lacto-N-neotetraose synthesis with reduced long-chain derivatives

Lacto-N-neotetraose (LNnT), as a neutral core structure within human milk oligosaccharides (HMOs), has garnered widespread attention due to its exceptional physiological functions. In the process of LNnT synthesis using cellular factory approaches, substrate promiscuity of glycosyltransferases leads to the production of longer oligosaccharide derivatives. Here, rational modification of β1,3-N-acetylglucosaminyltransferase from Neisseria meningitidis (LgtA) effectively decreased the concentration of long-chain LNnT derivatives. Specifically, the optimal β1,4-galactosyltransferase (β1,4-GalT) was selected from seven known candidates, enabling the efficient synthesis of LNnT in Escherichia coli BL21(DE3). Furthermore, the influence of lactose concentration on the distribution patterns of LNnT and its longer derivatives was investigated. The modification of LgtA was conducted with computational assistance, involving alanine scanning based on molecular docking to identify the substrate binding pocket and implementing large steric hindrance on crucial amino acids to obstruct LNnT entry. The implementation of saturation mutagenesis at positions 223 and 228 of LgtA yielded advantageous mutant variants that did not affect LNnT synthesis while significantly reducing the production of longer oligosaccharide derivatives. The most effective mutant, N223I, reduced the molar ratio of long derivatives by nearly 70%, showcasing promising prospects for LNnT production with diminished byproducts.

Fixation times on directed graphs.

Computing the rate of evolution in spatially structured populations is difficult. A key quantity is the fixation time of a single mutant with relative reproduction rate r which invades a population of residents. We say that the fixation time is "fast" if it is at most a polynomial function in terms of the population size N. Here we study fixation times of advantageous mutants (r > 1) and neutral mutants (r = 1) on directed graphs, which are those graphs that have at least some one-way connections. We obtain three main results. First, we prove that for any directed graph the fixation time is fast, provided that r is sufficiently large. Second, we construct an efficient algorithm that gives an upper bound for the fixation time for any graph and any r ≥ 1. Third, we identify a broad class of directed graphs with fast fixation times for any r ≥ 1. This class includes previously studied amplifiers of selection, such as Superstars and Metafunnels. We also show that on some graphs the fixation time is not a monotonically declining function of r; in particular, neutral fixation can occur faster than fixation for small selective advantages.

Through virtual saturation mutagenesis and rational design for superior substrate conversion in engineered d-amino acid oxidase.

The d-amino acid oxidase (DAAO) is pivotal in obtaining optically pure l-glufosinate (l-PPT) by converting d-glufosinate (d-PPT) to its deamination product. We screened and designed a Rasamsonia emersonii DAAO (ReDAAO), making it more suitable for oxidizing d-PPT. Using Caver 3.0, we delineated three substrate binding pockets and, via alanine scanning, identified nearby key residues. Pinpointing key residues influencing activity, we applied virtual saturation mutagenesis (VSM), and experimentally validated mutants which reduced substrate binding energy. Analysis of positive mutants revealed elongated side-chain prevalence in substrate binding pocket periphery. Although computer-aided approaches can rapidly identify advantageous mutants and guide further design, the mutations obtained in the first round may not be suitable for combination with other advantageous mutations. Therefore, each round of combination requires reasonable iteration. Employing VSM-assisted screening multiple times and after four rounds of combining mutations, we ultimately obtained a mutant, N53V/F57Q/V94R/V242R, resulting in a mutant with a 5097% increase in enzyme activity compared to the wild type. It provides valuable insights into the structural determinants of enzyme activity and introduces a novel rational design procedure.

Distal mutations enhance efficiency of free and immobilized NOV1 dioxygenase for vanillin synthesis

Protein engineering is crucial to improve enzymes’ efficiency and robustness for industrial biocatalysis. NOV1 is a bacterial dioxygenase that holds biotechnological potential by catalyzing the one-step oxidation of the lignin-derived isoeugenol into vanillin, a popular flavoring agent used in food, cleaning products, cosmetics and pharmaceuticals. This study aims to enhance NOV1 activity and operational stability through the identification of distal hotspots, located at more than 9 Å from the active site using Zymspot, a tool that predicts advantageous distant mutations, streamlining protein engineering. A total of 41 variants were constructed using site-directed mutagenesis and the six most active enzyme variants were then recombined. Two variants, with two and three mutations, showed nearly a 10-fold increase in activity and up to 40-fold higher operational stability than the wild-type. Furthermore, these variants show 90–100 % immobilization efficiency in metal affinity resins, compared to approximately 60 % for the wild-type. In bioconversions where 50 mM of isoeugenol was added stepwise over 24-h cycles, the 1D2 variant produced approximately 144 mM of vanillin after six reaction cycles, corresponding to around 22 mg, indicating a 35 % molar conversion yield. This output was around 2.5 times higher than that obtained using the wild-type. Our findings highlight the efficacy of distal protein engineering in enhancing enzyme functions like activity, stability, and metal binding selectivity, thereby fulfilling the criteria for industrial biocatalysts. This study provides a novel approach to enzyme optimization that could have significant implications for various biotechnological applications.

CHIPing away at immunity: the role of clonal hematopoiesis of indeterminate potential in bacterial pneumonia.

The occurrence of clonal hematopoiesis of indeterminate potential (CHIP), in which advantageous somatic mutations result in the clonal expansion of blood cells, increases with age, as do an increased risk of mortality and detrimental outcomes associated with CHIP. However, the role of CHIP in susceptibility to pulmonary infections, which also increase with age, is unclear. In this issue of the JCI, Quin and colleagues explored the role of CHIP in bacterial pneumonia. Using characterization of immune cells from human donors and mice lacking tet methylcytosine dioxygenase 2 (Tet2), the authors mechanistically link myeloid immune cell dysfunction to CHIP-mediated risk of bacterial pneumonia. The findings suggest that CHIP drives inflammaging and immune senescence, and provide Tet2 status in older adults as a potential prognostic tool for informing treatment options related to immune modulation.

Dynamic analysis of SARS-CoV-2 evolution based on different countries

Since late 2019, COVID-19 has significantly impacted the world. Understanding the evolution of SARS-CoV-2 is crucial for protecting against future infectious pathogens. In this study, we conducted a comprehensive chronological analysis of SARS-CoV-2 evolution by examining mutation prevalence from the source countries of VOCs: United Kingdom, India, Brazil, South Africa, plus two countries: United States, Russia, utilizing genomic sequences from GISAID. Our methodological approach involved large-scale genomic sequence alignment using MAFFT, Python-based data processing on a high-performance computing platform, and advanced statistical methods the Maximal Information Coefficient (MIC), and also Long Short-Term Memory (LSTM) models for correlation analysis.Our findings elucidate the dynamics of SARS-CoV-2 evolution, highlighting the virus's changing behaviour over various pandemic stages. Key results include the discovery of three temporal mutation patterns—lineage distinct, long-span, and competitive mutations—with varying levels of impact on the virus. Notably, we observed a convergence of advantageous mutations in the spike protein, especially in the later stages of the pandemic, indicating a substantial evolutionary pressure on the virus.One of the most significant revelations is the predominant role of natural immunity over vaccination-induced immunity in driving these evolutionary changes. This emphasizes the critical need for regular vaccine updates to maintain efficacy against evolving strains.In conclusion, our study not only sheds light on the evolutionary trajectory of SARS-CoV-2 but also underscores the urgency for robust, continuous global data collection and sharing. It highlights the necessity for rapid adaptations in medical countermeasures, including vaccine development, to stay ahead of pathogen evolution. This research provides valuable insights for future pandemic preparedness and response strategies.

Amplifiers of selection for the Moran process with both Birth-death and death-Birth updating.

Populations evolve by accumulating advantageous mutations. Every population has some spatial structure that can be modeled by an underlying network. The network then influences the probability that new advantageous mutations fixate. Amplifiers of selection are networks that increase the fixation probability of advantageous mutants, as compared to the unstructured fully-connected network. Whether or not a network is an amplifier depends on the choice of the random process that governs the evolutionary dynamics. Two popular choices are Moran process with Birth-death updating and Moran process with death-Birth updating. Interestingly, while some networks are amplifiers under Birth-death updating and other networks are amplifiers under death-Birth updating, so far no spatial structures have been found that function as an amplifier under both types of updating simultaneously. In this work, we identify networks that act as amplifiers of selection under both versions of the Moran process. The amplifiers are robust, modular, and increase fixation probability for any mutant fitness advantage in a range r ∈ (1, 1.2). To complement this positive result, we also prove that for certain quantities closely related to fixation probability, it is impossible to improve them simultaneously for both versions of the Moran process. Together, our results highlight how the two versions of the Moran process differ and what they have in common.

The human microbiota is a beneficial reservoir for SARS-CoV-2 mutations.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mutations are rapidly emerging, in particular advantageous mutations in the spike (S) protein, which either increase transmissibility or lead to immune escape and are posing a major challenge to pandemic prevention and treatment. However, how the virus acquires a high number of advantageous mutations in a short time remains a mystery. Here, we provide evidence that the human microbiota is a reservoir of advantageous mutations and aids mutational evolution and host adaptation of SARS-CoV-2. Our findings demonstrate a conceptual breakthrough on the mutational evolution mechanisms of SARS-CoV-2 for human adaptation. SARS-CoV-2 may grab advantageous mutations from the widely existing microorganisms in the host, which is undoubtedly an "efficient" manner. Our study might open a new perspective to understand the evolution of virus mutation, which has enormous implications for comprehending the trajectory of the COVID-19 pandemic.

On the feasibility of malaria hypothesis

In 1954, Allison proposed that hemoglobin S (HbS) gene causes protection against fatal malaria. This would explain the high HbS gene frequency observed in certain regions hyperendemic for malaria, so-called “malaria hypothesis”. This in silico study was conducted to examine the feasibility of the hypothesis under more realistic initial conditions, where a mutant gene with heterozygous advantage against malaria (e.g., HbS) was introduced in a group of Neolithic hunter-gatherers who decided to start agriculture nearby water where malaria killed a proportion of population. The tribe population size, number of children born to each woman in each generation, mortality from malaria and sickle cell disease, the protection factor provided by the gene carriers against malaria, the probability of mating between the members of the parent and offspring populations, population growth, and increased fertility in women heterozygous for HbS, were also considered. For effectively confer protection against malaria within the shortest possible period, the mutation needs to be happened in a small population. For a large population, the process would take around 100 generations (~ 2500 years) or more to provide an effective protection. Even then, the probability that the new gene could survive and propagate to future generations is about 35%. Conventional population genetics equations with differential or difference equations, give totally incorrect estimates of the gene frequency in small populations; discrete mathematics should be used, instead. After introduction of the advantageous mutation, the gene frequency increased until a steady state value. This value is far less than the gene frequency reported in certain tribes of Africa. It seems that the malaria hypothesis, per se, could not explain such a high observed gene frequency, unless HbS is associated with lower mortality from other causes too.

Physico-Chemical Investigation and Antimicrobial Efficacy of Ozonated Oils: The Case Study of Commercial Ozonated Olive and Sunflower Seed Refined Oils.

Drug resistance represents one of the great plagues of our time worldwide. This largely limits the treatment of common infections and requires the development of new antibiotics or other alternative approaches. Noteworthy, the indiscriminate use of antibiotics is mostly responsible for the selection of mutations that confer drug resistance to microbes. In this regard, recently, ozone has been raising interest for its unique biological properties when dissolved in natural oils. Ozonated oils have been reported to act in a non-specific way on microorganisms hindering the acquisition of advantageous mutations that result in resistance. Here, we focused on the antimicrobial effect of two commercial olive (OOO) and sunflower seeds (OSO) oils. Nuclear magnetic resonance spectroscopy and thermal analysis showed the change in the chemical composition of the oils after ozonation treatment. Different ozonated oil concentrations were then used to evaluate their antimicrobial profile against Candida albicans, Enterococcus faecalis, Staphylococcus aureus, Klebsiella pneumoniae, Pseudomonas aeruginosa, and Escherichia coli by agar diffusion and broth dilution methods. Cytotoxicity was also evaluated in keratinocytes and epithelial cells. Overall, our results revealed that both OOO and OSO showed a potent microbicidal effect, especially against C. albicans (IC50 = OOO: 0.3 mg/mL and OSO: 0.2 mg/mL) and E. faecalis (IC50 = OOO: 0.4 mg/mL and OSO: 2.8 mg/mL) albeit exerting a certain effect also against S. aureus and E. coli. Moreover, both OOO and OSO do not yield any relevant cytotoxic effect at the active concentrations in both cell lines. This indicates that the ozonated oils studied are not toxic for mammalian cells despite exerting a potent antimicrobial effect on specific microorganisms. Therefore, OOO and OSO may be considered to integrate standard therapies in the treatment of common infections, likely overcoming drug resistance issues.

Engineering Bacillus subtilis J46 for efficient utilization of galactose through adaptive laboratory evolution

Efficient utilization of galactose by microorganisms can lead to the production of valuable bio-products and improved metabolic processes. While Bacillus subtilis has inherent pathways for galactose metabolism, there is potential for enhancement via evolutionary strategies. This study aimed to boost galactose utilization in B. subtilis using adaptive laboratory evolution (ALE) and to elucidate the genetic and metabolic changes underlying the observed enhancements. The strains of B. subtilis underwent multiple rounds of adaptive laboratory evolution (approximately 5000 generations) in an environment that favored the use of galactose. This process resulted in an enhanced specific growth rate of 0.319 ± 0.005 h−1, a significant increase from the 0.03 ± 0.008 h−1 observed in the wild-type strains. Upon selecting the evolved strain BSGA14, a comprehensive whole-genome sequencing revealed the presence of 63 single nucleotide polymorphisms (SNPs). Two of them, located in the coding sequences of the genes araR and glcR, were found to be the advantageous mutations after reverse engineering. The strain with these two accumulated mutations, BSGALE4, exhibited similar specific growth rate on galactose to the evolved strain BSGA14 (0.296 ± 0.01 h−1). Furthermore, evolved strain showed higher productivity of protease and β-galactosidase in mock soybean biomass medium. ALE proved to be a potent tool for enhancing galactose metabolism in B. subtilis. The findings offer valuable insights into the potential of evolutionary strategies in microbial engineering and pave the way for industrial applications harnessing enhanced galactose conversion.

A Countable-Type Branching Process Model for the Tug-of-War Cancer Cell Dynamics.

We consider a time-continuous Markov branching process of proliferating cells with a countable collection of types. Among-type transitions are inspired by the Tug-of-War process introduced by McFarland et al. (Proc Natl Acad Sci 111(42):15138-15143, 2014) as a mathematical model for competition of advantageous driver mutations and deleterious passenger mutations in cancer cells. We introduce a version of the model in which a driver mutation pushes the type of the cell L-units up, while a passenger mutation pulls it 1-unit down. The distribution of time to divisions depends on the type (fitness) of cell, which is an integer. The extinction probability given any initial cell type is strictly less than 1, which allows us to investigate the transition between types (type transition) in an infinitely long cell lineage of cells. The analysis leads to the result that under driver dominance, the type transition process escapes to infinity, while under passenger dominance, it leads to a limit distribution. Implications in cancer cell dynamics and population genetics are discussed.

Signification and Application of Mutator and Antimutator Phenotype-Induced Genetic Variations in Evolutionary Adaptation and Cancer Therapeutics.

Mutations present a dichotomy in their implications for cellular processes. They primarily arise from DNA replication errors or damage repair processes induced by environmental challenges. Cumulative mutations underlie genetic variations and drive evolution, yet also contribute to degenerative diseases such as cancer and aging. The mutator phenotype elucidates the heightened mutation rates observed in malignant tumors. Evolutionary adaptation, analogous to bacterial and eukaryotic systems, manifests through mutator phenotypes during changing environmental conditions, highlighting the delicate balance between advantageous mutations and their potentially detrimental consequences. Leveraging the genetic tractability of Saccharomyces cerevisiae offers unique insights into mutator phenotypes and genome instability akin to human cancers. Innovative reporter assays in yeast model organisms enable the detection of diverse genome alterations, aiding a comprehensive analysis of mutator phenotypes. Despite significant advancements, our understanding of the intricate mechanisms governing spontaneous mutation rates and preserving genetic integrity remains incomplete. This review outlines various cellular pathways affecting mutation rates and explores the role of mutator genes and mutation-derived phenotypes, particularly prevalent in malignant tumor cells. An in-depth comprehension of mutator and antimutator activities in yeast and higher eukaryotes holds promise for effective cancer control strategies.

Genetic contribution of an advantaged mutant in the biparental Moran model

UDC 519.21 We consider a large population of haploid sexually reproducing individuals. It is assumed that one individual initially carries a very strongly advantageous mutation at a single locus. We study the long-term contribution of this initial individual to the genome of the population.

120 Using Simulated Data to Evaluate the Accuracy of Selection Signature Detection Methods in Varying Scenarios

Abstract The identification of molecular signatures of selection has become increasingly important in recent years. The detection of selection signatures can aid in both population characterization as well as the detection and identification of genes and advantageous mutations within populations. Various statistical methodologies have been developed to detect directional selection signatures based on different demographic or selection models. The detection of definite evidence of selection on genomes remains a challenge, as other events in the demographic history of a population under investigation may imitate the effects of selection on the genetic variation in the genome. To accurately detect selection signatures, researchers need to consider the large number of methodologies available as well as the factors influencing the detection of selection signatures. Using simulated data, it is possible to evaluate several methods and factors on a larger number of genotypes without the expense of genotyping several animals. The objective of this study was to simulate several sheep populations that have undergone different selection pressures, with varying parameters that may possibly influence the accuracy of detecting selection signatures and testing multiple methods of selection signature detection to find the most reliable method for each scenario. Sheep populations were simulated with varying numbers of QTL (5, 100, 2000) and h2 (0.15, 0.4). The populations were then expanded through either selection for high, low, or random genetic values. Thereafter the populations were selected for sample sizes of 20, 200 and 1000 individuals, resulting in a total of 54 populations for analysis. The populations were then subjected to ROH, iHS, Fst and XP-EHH analysis. After the most effective method for detection of selection signatures for each scenario was identified, the influence of effective population size, generations of animals included in the sample, relatedness, and sex of individuals on the accuracy of each method was tested. Preliminary results indicated that the accuracy of XP-EHH as well as ROH increased with larger population sizes, as well as greater numbers of QTL. Further results of this study will be presented at the conference.

Mutant fixation in the presence of a natural enemy

The literature about mutant invasion and fixation typically assumes populations to exist in isolation from their ecosystem. Yet, populations are part of ecological communities, and enemy-victim (e.g. predator-prey or pathogen-host) interactions are particularly common. We use spatially explicit, computational pathogen-host models (with wild-type and mutant hosts) to re-visit the established theory about mutant fixation, where the pathogen equally attacks both wild-type and mutant individuals. Mutant fitness is assumed to be unrelated to infection. We find that pathogen presence substantially weakens selection, increasing the fixation probability of disadvantageous mutants and decreasing it for advantageous mutants. The magnitude of the effect rises with the infection rate. This occurs because infection induces spatial structures, where mutant and wild-type individuals are mostly spatially separated. Thus, instead of mutant and wild-type individuals competing with each other, it is mutant and wild-type “patches” that compete, resulting in smaller fitness differences and weakened selection. This implies that the deleterious mutant burden in natural populations might be higher than expected from traditional theory.

Coevolution between marine Aeromonas and phages reveals temporal trade-off patterns of phage resistance and host population fitness.

Coevolution of bacteria and phages is an important host and parasite dynamic in marine ecosystems, contributing to the understanding of bacterial community diversity. On the time scale, questions remain concerning what is the difference between phage resistance patterns in marine bacteria and how advantageous mutations gradually accumulate during coevolution. In this study, marine Aeromonas was co-cultured with its phage for 180 days and their genetic and phenotypic dynamics were measured every 30 days. We identified 11 phage resistance genes and classified them into three categories: lipopolysaccharide (LPS), outer membrane protein (OMP), and two-component system (TCS). LPS shortening and OMP mutations are two distinct modes of complete phage resistance, while TCS mutants mediate incomplete resistance by repressing the transcription of phage genes. The co-mutation of LPS and OMP was a major mode for bacterial resistance at a low cost. The mutations led to significant reductions in the growth and virulence of bacterial populations during the first 60 days of coevolution, with subsequent leveling off. Our findings reveal the marine bacterial community dynamics and evolutionary trade-offs of phage resistance during coevolution, thus granting further understanding of the interaction of marine microbes.