Somatic mutations - Evolution within the individual

Simulation of Somatic Evolution Through the Introduction of Random Mutation to the Rules of Conway's Game of Life

Introduction

Conway's Game of Life (GOL), and related cellular automata (CA) models, have served as interesting simulations of complex behaviors resulting from simple rules of interactions between neighboring cells, that sometime resemble the growth and reproduction of living things. Thus, CA has been applied towards understanding the interaction and reproduction of single-cell organisms, and the growth of larger, disorganized tissues such as tumors. Surprisingly, however, there have been few attempts to adapt simple CA models to recreate the evolution of either new species, or subclones within a multicellular, tumor-like tissue.

Methods

In this article, I present a modified form of the classic Conway's GOL simulation, in which the three integer thresholds that define GOL (number of neighboring cells, below which a cell will "die of loneliness"; number of neighboring cells, above which a cell will die of overcrowding; and number of neighboring cells that will result in spontaneous birth of a new cell within an empty lattice location) are occasionally altered with a randomized mutation of fractional magnitude during new "cell birth" events. Newly born cells "inherit" the current mutation state of a neighboring parent cell, and over the course of 10,000 generations these mutations tend to accumulate until they impact the behaviors of individual cells, causing them to transition from the sparse, small patterns of live cells characteristic of GOL into a more dense, unregulated growth resembling a connected tumor tissue.

Results

The mutation rate and mutation magnitude were systematically varied in repeated randomized simulation runs, and it was determined that the most important mutated rule for the transition to unregulated, tumor-like growth was the overcrowding threshold, with the spontaneous birth and loneliness thresholds being of secondary importance. Spatial maps of the different "subclones" of cells that spontaneously develop during a typical simulation trial reveal that cells with greater fitness will overgrow the lattice and proliferate while the less fit, "wildtype" GOL cells die out and are replaced with mutant cells.

Conclusions

This simple modeling approach can be easily modified to add complexity and more realistic biological details, and may yield new understanding of cancer and somatic evolution.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12195-024-00828-9.

Chimerism and mosaicism shape our physical constitution and impact medical conditions

ABO blood group discrepancies in healthy individuals were caused by body-wide chimerism and mosaicism. They can be evaluated with new diagnostic options for disease-related cell clones that are typically associated with mosaicism. The observations raise the attention for sporadic mixed-field observations of any blood group antigen. Commentary on: Dauber et al. Body-wide chimerism and mosaicism are predominant causes of naturally occurring ABO discrepancies. Br J Haematol 2024; 205:1188-1196.

Asymmetric Contribution of Blastomere Lineages of First Division of the Zygote to Entire Human Body Using Post-Zygotic Variants

BACKGROUND

In humans, after fertilization, the zygote divides into two 2n diploid daughter blastomeres. During this division, DNA is replicated, and the remaining mutually exclusive genetic mutations in the genome of each cell are called post-zygotic variants. Using these somatic mutations, developmental lineages can be reconstructed. How these two blastomeres are contributing to the entire body is not yet identified. This study aims to evaluate the cellular contribution of two blastomeres of 2-cell embryos to the entire body in humans using post-zygotic variants based on whole genome sequencing.

METHODS

Tissues from different anatomical areas were obtained from five donated cadavers for use in single-cell clonal expansion and bulk target sequencing. After conducting whole genome sequencing, computational analysis was applied to find the early embryonic mutations of each clone. We developed our in-house bioinformatics pipeline, and filtered variants using strict criteria, composed of mapping quality, base quality scores, depth, soft-clipped reads, and manual inspection, resulting in the construction of embryological phylogenetic cellular trees.

RESULTS

Using our in-house pipeline for variant filtering, we could extract accurate true positive variants, and construct the embryological phylogenetic trees for each cadaver. We found that two daughter blastomeres, L1 and L2 (lineage 1 and 2, respectively), derived from the zygote, distribute unequally to the whole body at the clonal level. From bulk target sequencing data, we validated asymmetric contribution by means of the variant allele frequency of L1 and L2. The asymmetric contribution of L1 and L2 varied from person to person.

CONCLUSION

We confirmed that there is asymmetric contribution of two daughter blastomeres from the first division of the zygote across the whole human body.

MQuad enables clonal substructure discovery using single cell mitochondrial variants

Mitochondrial mutations are increasingly recognised as informative endogenous genetic markers that can be used to reconstruct cellular clonal structure using single-cell RNA or DNA sequencing data. However, identifying informative mtDNA variants in noisy and sparse single-cell sequencing data is still challenging with few computation methods available. Here we present an open source computational tool MQuad that accurately calls clonally informative mtDNA variants in a population of single cells, and an analysis suite for complete clonality inference, based on single cell RNA, DNA or ATAC sequencing data. Through a variety of simulated and experimental single cell sequencing data, we showed that MQuad can identify mitochondrial variants with both high sensitivity and specificity, outperforming existing methods by a large extent. Furthermore, we demonstrate its wide applicability in different single cell sequencing protocols, particularly in complementing single-nucleotide and copy-number variations to extract finer clonal resolution.

Mitochondrial variants are informative endogenous barcodes for clonal substructure. Here, the authors developed a computational method MQuad to effectively detect these clonal informed mtDNA variants from single-cell RNA, DNA or ATAC sequencing data.

Is cancer a disease set up by cellular stress responses?

For several decades, the somatic mutation theory (SMT) has been the dominant paradigm on cancer research, leading to the textbook notion that cancer is fundamentally a genetic disease. However, recent discoveries indicate that mutations, including "oncogenic" ones, are widespread in normal somatic cells, suggesting that mutations may be necessary but not sufficient for cancer to develop. Indeed, a fundamental but as yet unanswered question is whether or not the first step in oncogenesis corresponds to a mutational event. On the other hand, for some time, it has been acknowledged the important role in cancer progression of molecular processes that participate in buffering cellular stress. However, their role is considered secondary or complementary to that of putative oncogenic mutations. Here we present and discuss evidence that cancer may have its origin in epigenetic processes associated with cellular adaptation to stressful conditions, and so it could be a direct consequence of stress-buffering mechanisms that allow cells with aberrant phenotypes (not necessarily associated with genetic mutations) to survive and propagate within the organism. We put forward the hypothesis that there would be an inverse correlation between the activation threshold of the cellular stress responses (CSRs) and the risk of cancer, so that species or individuals with low-threshold CSRs will display a higher incidence or risk of cancer.