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ABSTRACT Intrinsically disordered protein regions (IDRs) are ubiquitous across all kingdoms of life and play a variety of essential cellular roles. IDRs exist in a collection of structurally distinct conformers known as an ensemble. An IDR’s amino acid sequence determines its ensemble, which in turn can play an important role in dictating molecular function. Yet a clear link connecting IDR sequence, its ensemble properties, and its molecular function in living cells has not been directly established. Here, we set out to test this sequence-ensemble-function paradigm using a novel computational method (GOOSE) that enables the rational design of libraries of IDRs by systematically varying specific sequence properties. Using ensemble FRET, we measured the ensemble dimensions of a library of rationally designed IDRs in human-derived cell lines, revealing how IDR sequence influences ensemble dimensionsin situ.Furthermore, we show that the interplay between sequence and ensemble can tune an IDR’s ability to sense changes in cell volume - ade novomolecular function for these synthetic sequences. Our results establish biophysical rules for intracellular sequence-ensemble relationships, enable a new route for understanding how IDR sequences map to function in live cells, and set the ground for the design of synthetic IDRs withde novofunction. 

Proteins must be hydrated to function. Desiccation, a common event in an increasing number of ecosystems, can drive proteome-wide unfolding and aggregation. For cells to survive, proteins must disaggregate and retain their function upon rehydration. The molecular determinants that underlie protein desiccation resistance remain unknown. Here, we use mass spectrometry to show that some proteins possess an innate ability to survive dehydration and subsequent rehydration. Structural analysis correlates the ability of proteins to resist desiccation with their surface area chemistry. Remarkably, highly resistant proteins are responsible for the production of the cell's building blocks - amino acids, metabolites, and sugars. Conversely, those proteins that are desiccation-sensitive are responsible for ribosome biogenesis. As a result, the rehydrated proteome is preferentially enriched with metabolite and small molecule producers and depleted of ribosomes - the cell's heaviest consumers. We propose this functional bias allows cells to kickstart their metabolism and promote cell survival upon rehydration. 

Gene expression in Arabidopsis is regulated by more than 1,900 transcription factors (TFs), which have been identified genome-wide by the presence of well-conserved DNA-binding domains. Activator TFs contain activation domains (ADs) that recruit coactivator complexes; however, for nearly all Arabidopsis TFs, we lack knowledge about the presence, location and transcriptional strength of their ADs1. To address this gap, here we use a yeast library approach to experimentally identify Arabidopsis ADs on a proteome-wide scale, and find that more than half of the Arabidopsis TFs contain an AD. We annotate 1,553 ADs, the vast majority of which are, to our knowledge, previously unknown. Using the dataset generated, we develop a neural network to accurately predict ADs and to identify sequence features that are necessary to recruit coactivator complexes. We uncover six distinct combinations of sequence features that result in activation activity, providing a framework to interrogate the subfunctionalization of ADs. Furthermore, we identify ADs in the ancient AUXIN RESPONSE FACTOR family of TFs, revealing that AD positioning is conserved in distinct clades. Our findings provide a deep resource for understanding transcriptional activation, a framework for examining function in intrinsically disordered regions and a predictive model of ADs. 

Abstract Auxin critically regulates plant growth and development. Auxin-driven transcriptional responses are mediated through the AUXIN RESPONSE FACTOR (ARF) family of transcription factors. ARF protein condensation attenuates ARF activity, resulting in dramatic shifts in the auxin transcriptional landscape. Here, we perform a forward genetics screen for ARF hypercondensation, identifying an F-box protein, which we named AUXIN RESPONSE FACTOR F-BOX1 (AFF1). Functional characterization of SCF^AFF1revealed that this E3 ubiquitin ligase directly interacts with ARF19 and ARF7 to regulate their accumulation, condensation, and nucleo-cytoplasmic partitioning. Mutants defective inAFF1display attenuated auxin responsiveness, and developmental defects, suggesting that SCF^AFF1-mediated regulation of ARF protein drives aspects of auxin response and plant development. 

Abstract Duckweeds are a monophyletic group of rapidly reproducing aquatic monocots in the Lemnaceae family. Given their clonal, exponentially fast reproduction, a key question is whether genome structure is conserved across the species in the absence of meiotic recombination. Here, we studied the genome and proteome of Spirodela polyrhiza, or greater duckweed, which has the largest body plan yet the smallest genome size in the family (1C=150 Mb). Using Oxford Nanopore sequencing combined with Hi-C scaffolding, we generated a highly contiguous, chromosome-scale assembly of S. polyrhiza line Sp7498 (Sp7498_HiC). Both the Sp7498_HiC and Sp9509 genome assemblies reveal large chromosomal misorientations relative to a recent PacBio assembly of Sp7498, highlighting the need for orthogonal long-range scaffolding techniques such as Hi-C and BioNano optical mapping. Shotgun proteomics of Sp7498 verified the expression of ~2250 proteins and revealed a high abundance of proteins involved in photosynthesis and carbohydrate metabolism among other functions. In addition, a strong increase in chloroplast proteins was observed that correlated to chloroplast density. This Sp7498_HiC genome was generated cheaply and quickly with a single Oxford Nanopore MinION flow cell and one Hi-C library in a classroom setting. Combining these data with a mass spectrometry-generated proteome illustrates the utility of duckweed as a model for genomics- and proteomics-based education.