Evolutionary Capacitance Emerges Spontaneously during Adaptation to Environmental Changes

Eco-evolutionary trade-offs in the dynamics of prion strain competition

Prion and prion-like molecules are a type of self-replicating aggregate protein that have been implicated in a variety of neurodegenerative diseases. Over recent decades, the molecular dynamics of prions have been characterized both empirically and through mathematical models, providing insights into the epidemiology of prion diseases and the impact of prions on the evolution of cellular processes. At the same time, a variety of evidence indicates that prions are themselves capable of a form of evolution, in which changes to their structure that impact their rate of growth or fragmentation are replicated, making such changes subject to natural selection. Here we study the role of such selection in shaping the characteristics of prions under the nucleated polymerization model (NPM). We show that fragmentation rates evolve to an evolutionary stable value which balances rapid reproduction of PrPSc aggregates with the need to produce stable polymers. We further show that this evolved fragmentation rate differs in general from the rate that optimizes transmission between cells. We find that under the NPM, prions that are both evolutionary stable and optimized for transmission have a characteristic length of three times the critical length below which they become unstable. Finally, we study the dynamics of inter-cellular competition between strains, and show that the eco-evolutionary trade-off between intra- and inter-cellular competition favours coexistence.

The effect of prions on cellular metabolism: The metabolic impact of the [RNQ+] prion and potential role of native Rnq1p

Within the field of amyloid and prion disease there is a need for a more comprehensive understanding of the fundamentals of disease biology. In order to facilitate the progression treatment and underpin comprehension of toxicity, fundamental understanding of the disruption to normal cellular biochemistry and trafficking is needed. Here, by removing the complex biochemistry of the brain, we have utilised known prion forming strains of Saccharomyces cerevisiae carrying different conformational variants of the Rnq1p to obtain Liquid Chromatography-Mass Spectrometry (LC-MS) metabolic profiles and identify key perturbations of prion presence. These studies reveal that prion containing [RNQ+] cells display a significant reduction in amino acid biosynthesis and distinct perturbations in sphingolipid metabolism, with significant downregulation in metabolites within these pathways. Moreover, that native Rnq1p appears to downregulate ubiquinone biosynthesis pathways within cells, suggesting that Rnq1p may play a lipid/mevalonate-based cytoprotective role as a regulator of ubiquinone production. These findings contribute to the understanding of how prion proteins interact in vivo in both their prion and non-prion confirmations and indicate potential targets for the mitigation of these effects. We demonstrate specific sphingolipid centred metabolic disruptions due to prion presence and give insight into a potential cytoprotective role of the native Rnq1 protein. This provides evidence of metabolic similarities between yeast and mammalian cells as a consequence of prion presence and establishes the application of metabolomics as a tool to investigate prion/amyloid-based phenomena.

Phenotypic mutations contribute to protein diversity and shape protein evolution

Errors in DNA replication generate genetic mutations, while errors in transcription and translation lead to phenotypic mutations. Phenotypic mutations are orders of magnitude more frequent than genetic ones, yet they are less understood. Here, we review the types of phenotypic mutations, their quantifications, and their role in protein evolution and disease. The diversity generated by phenotypic mutation can facilitate adaptive evolution. Indeed, phenotypic mutations, such as ribosomal frameshift and stop codon readthrough, sometimes serve to regulate protein expression and function. Phenotypic mutations have often been linked to fitness decrease and diseases. Thus, understanding the protein heterogeneity and phenotypic diversity caused by phenotypic mutations will advance our understanding of protein evolution and have implications on human health and diseases.

Fluctuating Environments Maintain Genetic Diversity through Neutral Fitness Effects and Balancing Selection

Genetic variation is the raw material upon which selection acts. The majority of environmental conditions change over time and therefore may result in variable selective effects. How temporally fluctuating environments impact the distribution of fitness effects and in turn population diversity is an unresolved question in evolutionary biology. Here, we employed continuous culturing using chemostats to establish environments that switch periodically between different nutrient limitations and compared the dynamics of selection to static conditions. We used the pooled Saccharomyces cerevisiae haploid gene deletion collection as a synthetic model for populations comprising thousands of unique genotypes. Using barcode sequencing, we find that static environments are uniquely characterized by a small number of high-fitness genotypes that rapidly dominate the population leading to dramatic decreases in genetic diversity. By contrast, fluctuating environments are enriched in genotypes with neutral fitness effects and an absence of extreme fitness genotypes contributing to the maintenance of genetic diversity. We also identified a unique class of genotypes whose frequencies oscillate sinusoidally with a period matching the environmental fluctuation. Oscillatory behavior corresponds to large differences in short-term fitness that are not observed across long timescales pointing to the importance of balancing selection in maintaining genetic diversity in fluctuating environments. Our results are consistent with a high degree of environmental specificity in the distribution of fitness effects and the combined effects of reduced and balancing selection in maintaining genetic diversity in the presence of variable selection.

Prevention of dsRNA-induced interferon signaling by AGO1x is linked to breast cancer cell proliferation

Translational readthrough, i.e., elongation of polypeptide chains beyond the stop codon, was initially reported for viral RNA, but later found also on eukaryotic transcripts, resulting in proteome diversification and protein‐level modulation. Here, we report that AGO1x, an evolutionarily conserved translational readthrough isoform of Argonaute 1, is generated in highly proliferative breast cancer cells, where it curbs accumulation of double‐stranded RNAs (dsRNAs) and consequent induction of interferon responses and apoptosis. In contrast to other mammalian Argonaute protein family members with primarily cytoplasmic functions, AGO1x exhibits nuclear localization in the vicinity of nucleoli. We identify AGO1x interaction with the polyribonucleotide nucleotidyltransferase 1 (PNPT1) and show that the depletion of this protein further augments dsRNA accumulation. Our study thus uncovers a novel function of an Argonaute protein in buffering the endogenous dsRNA‐induced interferon responses, different than the canonical function of AGO proteins in the miRNA effector pathway. As AGO1x expression is tightly linked to breast cancer cell proliferation, our study thus suggests a new direction for limiting tumor growth.

Structural instability and divergence from conserved residues underlie intracellular retention of mammalian odorant receptors

Mammalian odorant receptors are a diverse and rapidly evolving set of G protein-coupled receptors expressed in olfactory cilia membranes. Most odorant receptors show little to no cell surface expression in nonolfactory cells due to endoplasmic reticulum retention, which has slowed down biochemical studies. Here we provide evidence that structural instability and divergence from conserved residues of individual odorant receptors underlie intracellular retention using a combination of large-scale screening of odorant receptors cell surface expression in heterologous cells, point mutations, structural modeling, and machine learning techniques. We demonstrate the importance of conserved residues by synthesizing consensus odorant receptors that show high levels of cell surface expression similar to conventional G protein-coupled receptors. Furthermore, we associate in silico structural instability with poor cell surface expression using molecular dynamics simulations. We propose an enhanced evolutionary capacitance of olfactory sensory neurons that enable the functional expression of odorant receptors with cryptic mutations.