An official website of the United States government
Abstract The evolutionary transition to multicellularity requires shifting the primary unit of selection from cells to multicellular collectives. How this occurs in aggregative organisms remains poorly understood. Clonal development provides a direct path to multicellular adaptation through genetic identity between cells, but aggregative organisms face a constraint: selection on collective-level traits cannot drive adaptation without positive genetic assortment. We leveraged experimental evolution of flocculatingSaccharomyces cerevisiaeto examine the evolution and role of genetic assortment in multicellular adaptation. After 840 generations of selection for rapid settling, 13 of 19 lineages evolved increased positive assortment relative to their ancestor. However, assortment provided no competitive advantage during settling selection, suggesting it arose as an indirect effect of selection on cell-level traits rather than through direct selection on collective-level properties. Genetic reconstruction experiments and protein structure modeling revealed two distinct pathways to assortment: kin recognition mediated by mutations in theFLO1adhesion gene and generally enhanced cellular adhesion that improved flocculation efficiency independent of partner genotype. The evolution of assortment without immediate adaptive benefit suggests that key innovations enabling multicellular adaptation may arise indirectly through cell-level selection. Our results demonstrate fundamental constraints on aggregative multicellularity and help explain why aggregative lineages have remained simple.
more »
« less
This content will become publicly available on December 31, 2026
Surrogate selection oversamples expanded T cell clonotypes
Surrogate selection is an experimental design that without sequencing any DNA can restrict a sample of cells to those carrying certain genomic mutations. In immunological disease studies, this design may provide a relatively easy approach to enrich a lymphocyte sample with cells relevant to the disease response because the emergence of neutral mutations associates with the proliferation history of clonal subpopulations. A statistical analysis of clonotype sizes provides a structured, quantitative perspective on this useful property of surrogate selection. Our model specification couples within-clonotype birth-death processes with an exchangeable model across clonotypes. Beyond enrichment questions about the surrogate selection design, our framework enables a study of sampling properties of elementary sample diversity statistics; it also points to new statistics that may usefully measure the burden of somatic genomic alterations associated with clonal expansion. We examine statistical properties of immunological samples governed by the coupled model specification, and we illustrate calculations in surrogate selection studies of melanoma and in single-cell genomic studies of T cell repertoires.
more »
« less
- Award ID(s):
- 2023239
- PAR ID:
- 10625761
- Publisher / Repository:
- The Institute of Mathematical Statistics
- Date Published:
- Journal Name:
- The annals of applied statistics
- ISSN:
- 1932-6157
- Subject(s) / Keyword(s):
- Bayes’s rule clonal expansion diversity statistic enrichment exchangeable birth-death processes experimental design single cell sequencing size bias somatic mutation
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
When students think of evolution, they might imagine T. rex, or perhaps an abiotic scene of sizzling electrical storms and harsh reducing atmospheres, an Earth that looks like a lunar landscape. Natural selection automatically elicits responses that include “survival of the fittest,” and “descent with modification,” and with these historical biological catch phrases, one conjures up images of large animals battling it out on the Mesozoic plane. Rarely do teachers or students apply these same ideas to cancer and the evolution of somatic cells, which have accrued mutations and epigenetic imprinting and relentlessly survive and proliferate. Our questions in this paper include the following: Can cancer become an important teaching model for students to explore fundamental hypotheses about evolutionary process? Can the multi- step somatic cancer model encourage visualizations that enable students to revisit and reenter previous primary concepts in general biology such as the cell, mitosis, chromosomes, genetic diversity, ecological diversity, immune function, and of course evolution, continually integrating their biology knowledge into process and pattern knowledge? Can the somatic cancer model expose similar patterns and protagonists, linking Darwinian observations of the natural world to our body? And, can the cancer clone model excite critical thinking and student hypotheses about what cancer is as a biological process? Does this visually simple model assist students in recognizing patterns, connecting their biological curriculum dots into a more coherent learning experience? These biological dynamics and intercepting aptitudes of cells are amplified through the cancer model and can help shape the way biology students begin to appreciate the interrelatedness of all biological systems while they continue to explore pivotal points of biological fuzziness, such as the microbiome, limitations of models, and the complex coordination of genomic networks required for the function of even a single cell and the realization of phenotypes. In this paper we use clonal evolution of cancer as a model experience for students to recreate how a single, non-germline cell appears to shadow the classic pattern of natural selection in body cells that have gone awry. With authentic STEAM activities students can easily crossover and revisit previous biological topics and the ubiquitous nature of natural selection as seen in the example of somatic cells that result in a metastasizing tumor, giving students insight into natural selection’s accommodating and tractable patterns throughout the planet.more » « less
-
Affinity maturation (AM) of B cells through somatic hypermutations (SHMs) enables the immune system to evolve to recognize diverse pathogens. The accumulation of SHMs leads to the formation of clonal lineages of antibody-secreting b cells that have evolved from a common naïve B cell. Advances in high-throughput sequencing have enabled deep scans of B cell receptor repertoires, paving the way for reconstructing clonal trees. However, it is not clear if clonal trees, which capture microevolutionary time scales, can be reconstructed using traditional phylogenetic reconstruction methods with adequate accuracy. In fact, several clonal tree reconstruction methods have been developed to fix supposed shortcomings of phylogenetic methods. Nevertheless, no consensus has been reached regarding the relative accuracy of these methods, partially because evaluation is challenging. Benchmarking the performance of existing methods and developing better methods would both benefit from realistic models of clonal lineage evolution specifically designed for emulating B cell evolution. In this paper, we propose a model for modeling B cell clonal lineage evolution and use this model to benchmark several existing clonal tree reconstruction methods. Our model, designed to be extensible, has several features: by evolving the clonal tree and sequences simultaneously, it allows modeling selective pressure due to changes in affinity binding; it enables scalable simulations of large numbers of cells; it enables several rounds of infection by an evolving pathogen; and, it models building of memory. In addition, we also suggest a set of metrics for comparing clonal trees and measuring their properties. Our results show that while maximum likelihood phylogenetic reconstruction methods can fail to capture key features of clonal tree expansion if applied naively, a simple post-processing of their results, where short branches are contracted, leads to inferences that are better than alternative methods.more » « less
-
Chronic myeloid leukemia (CML) is a blood cancer characterized by dysregulated production of maturing myeloid cells driven by the product of the Philadelphia chromosome, the BCR-ABL1 tyrosine kinase. Tyrosine kinase inhibitors (TKIs) have proved effective in treating CML, but there is still a cohort of patients who do not respond to TKI therapy even in the absence of mutations in the BCR-ABL1 kinase domain that mediate drug resistance. To discover novel strategies to improve TKI therapy in CML, we developed a nonlinear mathematical model of CML hematopoiesis that incorporates feedback control and lineage branching. Cell–cell interactions were constrained using an automated model selection method together with previous observations and new in vivo data from a chimericBCR-ABL1transgenic mouse model of CML. The resulting quantitative model captures the dynamics of normal and CML cells at various stages of the disease and exhibits variable responses to TKI treatment, consistent with those of CML patients. The model predicts that an increase in the proportion of CML stem cells in the bone marrow would decrease the tendency of the disease to respond to TKI therapy, in concordance with clinical data and confirmed experimentally in mice. The model further suggests that, under our assumed similarities between normal and leukemic cells, a key predictor of refractory response to TKI treatment is an increased maximum probability of self-renewal of normal hematopoietic stem cells. We use these insights to develop a clinical prognostic criterion to predict the efficacy of TKI treatment and design strategies to improve treatment response. The model predicts that stimulating the differentiation of leukemic stem cells while applying TKI therapy can significantly improve treatment outcomes.more » « less
-
Abstract Adaptation dynamics on fitness landscapes is often studied theoretically in the strong-selection, weak-mutation regime. However, in a large population, multiple beneficial mutants can emerge before any of them fixes in the population. Competition between mutants is known as clonal interference, and while it is known to slow down the rate of adaptation (when compared to the strong-selection, weak-mutation model with the same parameters), how it affects the shape of long-term fitness trajectories in the presence of epistasis is an open question. Here, by considering how changes in fixation probabilities arising from weak clonal interference affect the dynamics of adaptation on fitness-parameterized landscapes, we find that the change in the shape of fitness trajectory arises only through changes in the supply of beneficial mutations (or equivalently, the beneficial mutation rate). Furthermore, a depletion of beneficial mutations as a population climbs up the fitness landscape can speed up the rescaled fitness trajectory (where adaptation speed is measured relative to its value at the start of the experiment), while an enhancement of the beneficial mutation rate does the opposite of slowing it down. Our findings suggest that by carrying out evolution experiments in both regimes (with and without clonal interference), one could potentially distinguish the different sources of macroscopic epistasis (fitness effect of mutations vs change in fraction of beneficial mutations).more » « less
