Biology subjects

Box, A.

Publications and source records attributed to Box, A..

5 recordsLinked to original sources

bioRxiv2025

Post-Domestication selection of MKK3 Shaped Seed Dormancy and End-Use Traits in Barley

Anthropogenic selection of grain traits such as dormancy has shaped the developmental trajectories of crop plants (1). In cereals, shortening dormancy provides rapid and even post-harvest germination, but increases the risk of weather-induced pre-harvest sprouting (PHS) with harvest losses estimated at beyond 1 billion USD a year (2, 3, 4). Our understanding of how, why, when and where diversification of cereal dormancy arose is fragmentary. Here, we show in the founder cereal crop barley (Hordeum vulgare) that the Mitogen-Activated Protein Kinase (MAPK) pathway regulates dormancy primarily through a mosaic of locus haplotypes comprising copy-number variation and inherent kinase activity of Mitogen-activated protein kinase kinase 3 (MKK3). We provide evidence supporting the historical selection of specific MKK3 haplotypes that shape dormancy levels according to changing climatic pressures. Understanding the regulatory landscape of MKK3 provides a genetic framework to balance short grain dormancy and PHS-avoidance during a period of rapid climate change.

plant biology↗

bioRxiv2021

The polyglutamine amyloid nucleus in living cells is monomeric and has competing dimensions of order

A long-standing goal of the study of amyloids has been to characterize the structural basis of the rate-determining nucleating event. However, the ephemeral nature of that event has made it inaccessible to classical biochemistry, structural biology, and computational approaches. Here, we addressed that limitation by measuring the dependence of amyloid formation on concentration and conformational templates in living cells, whose volumes are sufficiently small to resolve the outcomes of independent nucleation events. We characterized numerous rationally designed sequence variants of polyglutamine (polyQ), a polypeptide that precipitates Huntingtons and other amyloid-associated neurodegenerative diseases when its length exceeds a characteristic threshold. This effort uncovered a pattern of approximately twelve Qs, only for polypeptides exceeding the clinical length threshold, that allow for amyloid nucleation to occur spontaneously within single polypeptides. Nucleation was inhibited by intermolecular phase separation. Using atomistic molecular dynamics simulations, we found that the pattern encodes a minimal steric zipper of interdigitated side chains. Lateral growth of the steric zipper competed with axial growth to produce "pre-amyloid" oligomers. By illuminating the structural mechanism of polyQ amyloid formation in cells, our findings reveal a potential molecular etiology for polyQ diseases, and may provide a roadmap for the design of new therapies.

biophysics↗

bioRxiv2020

Identification of Stem Cells from Large Cell Populations with Topological Scoring

Machine learning and topological analysis methods are becoming increasingly used on various large-scale omics datasets. Modern high dimensional flow cytometry data sets share many features with other omics datasets like genomics and proteomics. For example, genomics or proteomics datasets can be sparse and have high dimensionality, and flow cytometry datasets can also share these features. This makes flow cytometry data potentially a suitable candidate for employing machine learning and topological scoring strategies, for example, to gain novel insights into patterns within the data. We have previously developed the Topological Score (TopS) and implemented it for the analysis of quantitative protein interaction network datasets. Here we show that the TopS approach for large scale data analysis is applicable to the analysis of a previously described flow cytometry sorted human hematopoietic stem cell dataset. We demonstrate that TopS is capable of effectively sorting this dataset into cell populations and identify rare cell populations. We demonstrate the utility of TopS when coupled with multiple approaches including topological data analysis, X-shift clustering, and t-Distributed Stochastic Neighbor Embedding (t-SNE). Our results suggest that TopS could be effectively used to analyze large scale flow cytometry datasets to find rare cell populations.

systems biology↗

bioRxiv2017

Quinary structure kinetically controls protein function and dysfunction

Protein self-assemblies modulate protein activities over biological time scales that can exceed the lifetimes of the proteins or even the cells that harbor them. We hypothesized that these time scales relate to kinetic barriers inherent to the nucleation of ordered phases. To investigate nucleation barriers in living cells, we developed Distributed Amphifluoric FRET (DAmFRET). DAmFRET exploits a photoconvertible fluorophore, heterogeneous expression, and large cell numbers to quantify via flow cytometry the extent of a proteins self-assembly as a function of cellular concentration. We show that kinetic barriers limit the nucleation of ordered self-assemblies, and that the persistence of the barriers with respect to concentration relates to structure. Supersaturation resulting from sequence-encoded nucleation barriers gave rise to prion behavior, and enabled a prion-forming protein, Sup35 PrD, to partition into dynamic intracellular condensates or to form toxic aggregates. Our results suggest that nucleation barriers govern cytoplasmic inheritance, subcellular organization, and proteotoxicity.\n\nHighlightsO_LIDistributed Amphifluoric FRET (DAmFRET) quantifies nucleation in living cells\nC_LIO_LIDAmFRET rapidly distinguishes prion-like from non-prion phase transitions\nC_LIO_LINucleation barriers allow switch-like temporal control of protein activity\nC_LIO_LISequence-intrinsic features determine the concentration-dependence of nucleation barriers\nC_LI

biophysics↗

bioRxiv2017

Insulin resistance in cavefish as an adaptation to a nutrient-limited environment

Periodic food shortage is one of the biggest challenges organisms face in natural habitats. How animals cope with nutrient limited conditions is an active area of study, of particular relevance in the context of the current increasing destabilization of global climate. Caves represent an extreme setting where animals have adapted to nutrient-limited conditions, as most cave environments lack a primary energy source. Here we show that cave-adapted populations of the Mexican Tetra, Astyanax mexicanus, have dysregulated blood glucose homeostasis and are insulin resistant compared to the river-adapted population. We found that multiple cave populations carry a mutation in the insulin receptor that leads to decreased insulin binding in vitro. Surface/cave hybrid fish carrying the allele weigh more than non-carriers, and zebrafish genetically engineered to carry the mutation similarly have increased body weight and insulin resistance. Higher bodyweight may be advantageous in the cave as a strategy to cope with infrequent food. In humans, the identical mutation in the insulin receptor leads to a severe form of insulin resistance and dramatically reduced life-span. However, cavefish have a similar lifespan to surface fish (of greater than fourteen years) and do not accumulate advanced glycated end products (AGEs) in the blood that are typically associated with progression of diabetes-associated pathologies. Our findings raise the intriguing hypothesis that cavefish have acquired compensatory mechanisms that allow them to circumvent the typical negative effects associated with failure to regulate blood glucose.

evolutionary biology↗