Biology subjects

Fields, S.

Publications and source records attributed to Fields, S..

At least 19 recordsLinked to original sources

bioRxiv2026

Chemokine-Dependent Natural Killer Cells Prevent Pulmonary Metastasis in a Newly Established Mouse Osteosarcoma Model

Rampant genomic instability of osteosarcoma (OS) and associated inter- and intratumoral heterogeneity convey a high risk of metastasis despite contemporary multimodal therapy. A mouse primary OS tumor model, originating from Myc-overexpressing Trp53-null mesenchymal progenitor cells, closely mimics cardinal genetic features and gene expression patterns of human OS samples. Subcutaneous injection of OS cells into immunocompromised NSG mice produced extensive metastases, whereas many fewer metastases occurred in T cell-deficient nude mice, suggesting a principal role for innate immunity in controlling OS dissemination. Depletion of natural killer (NK) cells in nude mice facilitated OS metastasis. OS cells released a suite of chemokines, with CCL2 the most prominent. A genome-wide CRISPR/Cas9 screen in OS cells identified 11 genes, including Ccl2, whose loss facilitated pulmonary metastasis in nude mice. Disruption of CCL2 in OS cells partially phenocopied the effects of antibody-dependent NK cell depletion, underscoring a plausible OS-NK signaling pathway that limits OS metastasis. SignificanceOsteosarcoma exhibits complex genomic instability and a propensity for pulmonary metastasis that limit chemotherapeutic response and patient survival. Despite the plethora of heterogeneous genetic alterations that connote poor prognosis, a novel preclinical in vivo model for studying metastasis highlights potentially targetable signaling between osteosarcoma cell-derived chemokines and pulmonary NK cells.

cancer biology↗

bioRxiv2026

Massively parallel characterization and deep learning of enhancers in plant genomes

Enhancers coordinate gene expression in response to developmental and environmental cues. Because plant enhancers lack the readily detectable molecular hallmarks of animal enhancers, their systematic functional characterization has yet to be accomplished. Here, we characterize the species- and condition-specific enhancer activity of over 350,000 sequences derived from accessible chromatin regions of the Arabidopsis, tomato, maize, and sorghum genomes. Enabled by the massive scale of the data, we developed plantGREP, a deep learning model that predicts enhancer strength and identifies the underlying functional sequence motifs. We apply plantGREP to evolve strong constitutive as well as species- and condition-specific enhancers, and to locate regions with enhancer activity upstream of developmental genes in crop genomes. These results should facilitate the targeted editing of enhancers in crop genomes and the design of cell-type-specific plant enhancers.

plant biology↗

bioRxiv2025

Dosa: A method to covalently barcode proteinsfor high throughput biochemistry

Deep mutational scanning couples a proteins activity to DNA sequencing for high throughput assessment of the effects of all single amino acid substitutions, but it largely uses indirect assays, like growth, as proxy for protein activity. Here, we covalently link variant proteins in vivo to an RNA barcode by fusing them to E. coli tRNA (m5U54) methyltransferase TrmA (E358Q), which forms a covalent bond with a tRNA stem-loop. Following cell lysis, variant proteins are separated in vitro according to their biochemical properties and identified by their barcodes. We use this method, Dosa, to analyze a large pool of FLAG epitope variants for binding to an anti-FLAG antibody, to profile the cleavage preferences of variants of enteropeptidase and human rhinovirus 3C protease, and to measure the solubility of several hundred A{beta}(1-42) variants. This method should be amenable to numerous biochemical assays with proteins produced in E. coli or mammalian cells.

genomics↗

bioRxiv2024

Small DNA elements that act as both insulators and silencers in plants

Insulators are cis-regulatory elements that separate transcriptional units, whereas silencers are elements that repress transcription regardless of their position. In plants, these elements remain largely uncharacterized. Here, we use the massively parallel reporter assay Plant STARR-seq with short fragments of eight large insulators to identify more than 100 fragments that block enhancer activity. The short fragments can be combined to generate more powerful insulators that abolish the capacity of the strong viral 35S enhancer to activate the 35S minimal promoter. Unexpectedly, when tested upstream of weak enhancers, these fragments act as silencers and repress transcription. Thus, these elements are capable of both insulating or repressing transcription dependent upon regulatory context. We validate our findings in stable transgenic Arabidopsis, maize, and rice plants. The short elements identified here should be useful building blocks for plant biotechnology efforts.

plant biology↗

bioRxiv2023

Cooperativity and additivity in plant enhancers

Enhancers are cis-regulatory elements that shape gene expression in response to numerous developmental and environmental cues. In animals, several models have been proposed to explain how enhancers integrate the activity of multiple transcription factors. However, it remains largely unknown how plant enhancers integrate transcription factor activity. Here, we use Plant STARR-seq to characterize three light-responsive plant enhancers--AB80, Cab-1, and rbcS-E9--derived from genes active in photosynthesis. Saturation mutagenesis reveals mutations, many of which cluster in short regions, that strongly reduce enhancer activity in the light, in the dark or in both conditions. When tested in the light, these mutation-sensitive regions do not function on their own; rather, cooperative interactions with other such regions are required for full activity. Epistatic interactions occur between mutations in adjacent mutation-sensitive regions, and the spacing and order of mutation-sensitive regions in synthetic enhancers affects enhancer activity. In contrast, when tested in the dark, mutation-sensitive regions act independently and additively in conferring enhancer activity. Taken together, this work demonstrates that plant enhancers show evidence for both cooperative and additive interactions among their functional elements. This knowledge can be harnessed to design strong, condition-specific synthetic enhancers.

plant biology↗

bioRxiv2023

Impact of random 50-base sequences inserted into an intron on splicing in Saccharomyces cerevisiae

Intron splicing is a key regulatory step in gene expression in eukaryotes. Three sequence elements required for splicing - 5 and 3 splice sites and a branch point - are especially well- characterized in Saccharomyces cerevisiae, but our understanding of additional intron features that impact splicing in this organism is incomplete, due largely to its small number of introns. To overcome this limitation, we constructed a library in S. cerevisiae of random 50-nucleotide elements (N50) individually inserted into the intron of a reporter gene and quantified canonical splicing and the use of cryptic splice sites by sequencing analysis. More than 70% of approximately 140,000 N50 elements reduced splicing by at least 20% compared to the intron control. N50 features, including higher GC content, presence of GU repeats and stronger predicted secondary structure of its pre-mRNA, correlated with reduced splicing efficiency. A likely basis for the reduced splicing of such a large proportion of variants is the formation of RNA structures that pair N50 bases - such as the GU repeats - with other bases specifically within the reporter pre-mRNA analyzed. However, neither convolutional neural network nor linear models were able to explain more than a small fraction of the variance in splicing efficiency across the library, suggesting that complex non-linear interactions in RNA structures are not accurately captured by RNA structure prediction methods given the limited number of variants. Our results imply that the specific context of a pre-mRNA may determine the bases allowable in an intron to prevent secondary structures that reduce splicing.

synthetic biology↗

bioRxiv2023

Features that Govern Terminator Strength in Plants

The 3 end of a gene, often called a terminator, modulates mRNA stability, localization, translation, and polyadenylation. Here, we adapted Plant STARR-seq, a massively parallel reporter assay, to measure the activity of over 50,000 terminators from the plants Arabidopsis thaliana and Zea mays. We characterize thousands of plant terminators, including many that outperform bacterial terminators commonly used in plants. Terminator activity is species-specific, differing in tobacco leaf and maize protoplast assays. While recapitulating known biology, our results reveal the relative contributions of polyadenylation motifs to terminator strength. We built a computational model to predict terminator strength and used it to conduct in silico evolution that generated optimized synthetic terminators. Additionally, we discover alternative polyadenylation sites across tens of thousands of terminators; however, the strongest terminators tend to have a dominant cleavage site. Our results establish features of plant terminator function and identify strong naturally occurring and synthetic terminators.

plant biology↗

bioRxiv2022

Proteome-wide identification of amino acid substitutions deleterious for protein function

DNA sequencing has led to the discovery of millions of mutations that change the encoded protein sequences, but the impact of nearly all of these mutations on protein function is unknown. We addressed this scarcity of functional data by developing Miro, a proteomic technology that uses mistranslation to introduce amino acid substitutions and biochemical assays to quantify functional differences of thousands of protein variants by mass spectrometry. We apply this technology to the proteome of yeast to reveal amino acid substitutions that impact protein structure, ligand binding, protein-protein interactions, protein post-translational modifications, and protein thermal stability. Adapting Miro to human cells will provide a means to efficiently accelerate our mechanistic interpretation of genomic mutations to predict disease risk.

genomics↗

bioRxiv2022

Mapping functional regions of essential bacterial proteins with dominant-negative protein fragments

Massively-parallel measurements of dominant negative inhibition by protein fragments have been used to map protein interaction sites and discover peptide inhibitors. However, the underlying principles governing fragment-based inhibition have thus far remained unclear. Here, we adapt a high-throughput inhibitory fragment assay for use in Escherichia coli, applying it to a set of ten essential proteins. This approach yielded single amino acid-resolution maps of inhibitory activity, with peaks localized to functionally important interaction sites, including oligomerization interfaces and folding contacts. Leveraging these data, we perform a systematic analysis to uncover principles of fragment-based inhibition. We determine a robust negative correlation between susceptibility to inhibition and cellular protein concentration, demonstrating that inhibitory fragments likely act primarily by titrating native protein interactions. We also characterize a series of trade-offs related to fragment length, showing that shorter peptides allow higher-resolution mapping but suffer from lower inhibitory activity. We employ an unsupervised statistical analysis to show that the inhibitory activities of protein fragments are largely driven not by generic properties such as charge, hydrophobicity, and secondary structure, but by the more specific characteristics of their bespoke macromolecular interactions. AlphaFold computational modeling of peptide complexes with one protein shows that the inhibitory activity of peptides is associated with their predicted ability to form native-like interactions. Overall, this work demonstrates fundamental characteristics of inhibitory protein fragment function and provides a foundation for understanding and controlling protein interactions in vivo. Significance StatementPeptide fragments derived from protein sequences can inhibit interactions of their parental proteins, providing a promising avenue for drug development. Here we employ a massively-parallel assay to measure in vivo inhibition by fragments that tile the full sequences of ten essential bacterial proteins. We leverage these data to decipher principles of fragment-based inhibition, showing how parental protein concentration drives activity and how protein fragment length interplays with activity and specificity. We employ statistical analysis to parse the roles of biophysical properties in fragment-to-fragment variation, and AlphaFold modeling to determine the relationship between measured inhibitory activity and predicted native-like binding. These results provide a path towards rational design of peptide inhibitors and broader principles of protein-protein interactions in living cells.

microbiology↗

bioRxiv2021

Effects of sequence motifs in the yeast 3' untranslated region determined from massively-parallel assays of random sequences

The 3' untranslated region (UTR) plays critical roles in determining the level of gene expression, through effects on activities such as mRNA stability and translation. The underlying functional elements within this region have largely been identified through analyses of the limited number of native genes. To explore the effects of sequence elements when not present in biologically evolved sequence backgrounds, we analyzed hundreds of thousands of random 50-mers inserted into the 3' UTR of a reporter gene in the yeast Saccharomyces cerevisiae. We determined relative protein expression levels from the fitness of a library of transformants in a growth selection. We find that the consensus 3' UTR efficiency element significantly boosts expression, independent of sequence context; on the other hand, the consensus positioning element has only a small effect on expression. Some sequence motifs that are binding sites for Puf proteins substantially increase expression in this random library, despite these proteins generally being associated with post-transcriptional downregulation when bound to native mRNAs. Thus, the regulatory effects of 3' UTR sequence features like the positioning element and Puf binding sites appear to be strongly dependent on their context within native genes, where they exist alongside co-evolved sequence features. Our measurements also allowed a systematic examination of the effects of point mutations within efficiency element motifs across diverse sequence backgrounds. These mutational scans reveal the relative in vivo importance of individual bases in the efficiency element, which likely reflects their roles in binding the Hrp1 protein involved in cleavage and polyadenylation.

genomics↗

bioRxiv2021

Synthetic Promoter Designs Enabled by a Comprehensive Analysis of Plant Core Promoters

Targeted engineering of plant gene expression holds great promise for ensuring food security and for producing biopharmaceuticals in plants. However, this engineering requires thorough knowledge of cis-regulatory elements in order to precisely control either endogenous or introduced genes. To generate this knowledge, we used a massively parallel reporter assay to measure the activity of nearly complete sets of promoters from Arabidopsis, maize and sorghum. We demonstrate that core promoter elements - notably the TATA-box - as well as promoter GC content and promoter-proximal transcription factor binding sites influence promoter strength. By performing the experiments in two assay systems, leaves of the dicot tobacco and protoplasts of the monocot maize, we detect species-specific differences in the contributions of GC content and transcription factors to promoter strength. Using these observations, we built computational models to predict promoter strength in both assay systems, allowing us to design highly active promoters comparable in activity to the viral 35S minimal promoter. Our results establish a promising experimental approach to optimize native promoter elements and generate synthetic ones with desirable features.

plant biology↗

bioRxiv2020

MaveRegistry: a collaboration platform for multiplexed assays of variant effect

SummaryMultiplexed assays of variant effect (MAVEs) are capable of experimentally testing all possible single nucleotide or amino acid variants in selected genomic regions, generating variant effect maps, which provide biochemical insight and functional evidence to enable more rapid and accurate clinical interpretation of human variation. Because the international community applying MAVE approaches is growing rapidly, we developed the online MaveRegistry platform to catalyze collaboration, reduce redundant efforts, allow stakeholders to nominate targets, and enable tracking and sharing of progress on ongoing MAVE projects. Availability and implementationhttps://registry.varianteffect.org Contactfritz.roth@utoronto.ca

bioinformatics↗

bioRxiv2020

The regulatory landscape of Arabidopsis thaliana roots at single-cell resolution

In plants, chromatin accessibility - the primary mark of regulatory DNA - is relatively static across tissues and conditions. This scarcity of accessible sites that are dynamic or tissue-specific may be due in part to tissue heterogeneity in previous bulk studies. To assess the effects of tissue heterogeneity, we apply single-cell ATAC-seq to A. thaliana roots and identify thousands of differentially accessible sites, sufficient to resolve all major cell types of the root. However, even this vast increase relative to bulk studies in the number of dynamic sites does not resolve the poor correlation at individual loci between accessibility and expression. Instead, we find that the entirety of a cells regulatory landscape and its transcriptome each capture cell type identity independently. We leverage this shared information on cell identity to integrate accessibility and transcriptome data in order to characterize developmental progression, endoreduplication and cell division in the root. We further use the combined data to characterize cell type-specific motif enrichments of large transcription factor families and to link the expression of individual family members to changing accessibility at specific loci, taking the first steps toward resolving the direct and indirect effects that shape gene expression. Our approach provides an analytical framework to infer the gene regulatory networks that execute plant development.

genomics↗

bioRxiv2020

Balance between promiscuity and specificity in phage {lambda} host range

As hosts acquire resistance to viruses, viruses must overcome that resistance to re-establish infectivity, or go extinct. Despite the significant hurdles associated with adapting to a resistant host, viruses are evolutionarily successful and maintain stable coevolutionary relationships with their hosts. To investigate the factors underlying how pathogens adapt to their hosts, we performed a deep mutational scan of the region of the λ tail fiber tip protein that mediates contact with the λ host, E. coli. Phages harboring amino acid substitutions were subjected to selection for infectivity on wild type E. coli, revealing a highly restrictive fitness landscape, in which most substitutions completely abrogate function. By comparing this lack of mutational tolerance to evolutionary diversity, we highlight a set of mutationally intolerant and diverse positions associated with host range expansion. Imposing selection for infectivity on three λ-resistant hosts, each harboring a different missense mutation in the λ receptor, reveals hundreds of adaptive variants in λ. We distinguish λ variants that confer promiscuity, a general ability to overcome host resistance, from those that drive host-specific infectivity. Both processes may be important in driving adaptation to a novel host.Competing Interest StatementThe authors have declared no competing interest.View Full Text

molecular biology↗

bioRxiv2020

Transcriptional re-wiring by mutation of the yeast Hsf1 oligomerization domain

Response to heat stress is mediated by heat shock transcription factors (HSFs), which possess conserved DNA-binding and oligomerization domains. The oligomerization domain is required for HSF1 to transition under heat stress from a monomer to a homotrimer, which alters DNA-binding specificity and affinity. Sequence variation in the oligomerization domain affects HSF1 activity, although this link is poorly understood. We performed a deep mutational scan of >400,000 variants of the oligomerization domain of Saccharomyces cerevisiae Hsf1 and measured fitness under stress and non-stress conditions. We identify mutations that confer temperature-specific phenotypes; some exceptional Hsf1variants lead to enhanced growth under heat stress and changes to in vivo DNA-binding and transcriptional programs. The link between Hsf1 oligomerization and DNA-binding domain is evolutionarily conserved, with co-evolving residues between these domains found among fungi. Mutation of transcription factor oligomerization domains may represent a path toward re-wiring transcriptional programs without mutation of DNA-binding domains.

genomics↗

bioRxiv2020

Identification of plant enhancers and their constituent elements by STARR-seq in tobacco leaves

Genetic engineering of cis-regulatory elements in crop plants is a promising strategy to ensure food security. However, such engineering is currently hindered by our limited knowledge of plant cis-regulatory elements. Here, we adapted STARR-seq -- a technology for the high-throughput identification of enhancers -- for its use in transiently transformed tobacco leaves. We demonstrate that the optimal placement in the reporter construct of enhancer sequences from a plant virus, pea and wheat was just upstream of a minimal promoter, and that none of these four known enhancers was active in the 3'-UTR of the reporter gene. The optimized assay sensitively identified small DNA regions containing each of the four enhancers, including two whose activity was stimulated by light. Furthermore, we coupled the assay to saturation mutagenesis to pinpoint functional regions within an enhancer, which we recombined to create synthetic enhancers. Our results describe an approach to define enhancer properties that can be performed in potentially any plant species or tissue transformable by Agrobacterium and that can use regulatory DNA derived from any plant genome. One-sentence summaryWe developed a high-throughput assay in transiently transformed tobacco leaves that can identify enhancers, characterize their functional elements and detect condition-specific enhancer activity.

plant biology↗

bioRxiv2019

Dimensionality reduction by UMAP to visualize physical and genetic interactions

Dimensionality reduction is often used to visualize complex expression profiling data. Here, we use the Uniform Manifold Approximation and Projection (UMAP) method on published transcript profiles of 1484 single gene deletions of Saccharomyces cerevisiae. Proximity in low-dimensional UMAP space identifies clusters of genes that correspond to protein complexes and pathways, and finds novel protein interactions even within well-characterized complexes. This approach is more sensitive than previous methods and should be broadly useful as additional transcriptome datasets become available for other organisms.

genomics↗

bioRxiv2018

Developmental and conditional dynamics of gene expression in single root cells of A. thaliana

Single-cell RNA-seq can yield high-resolution cell-type-specific expression signatures that reveal new cell types and the developmental trajectories of cell lineages. Here, we apply this approach to A. thaliana root cells to capture gene expression in 3,121 root cells. We analyze these data with Monocle 3, which orders single cell transcriptomes in an unsupervised manner and uses machine learning to reconstruct single-cell developmental trajectories along pseudotime. We identify hundreds of genes with cell-type-specific expression, with pseudotime analysis of several cell lineages revealing both known and novel genes that are expressed along a developmental trajectory. We identify transcription factor motifs that are enriched in early and late cells, together with the corresponding candidate transcription factors that likely drive the observed expression patterns. We assess and interpret changes in total RNA expression along developmental trajectories and show that trajectory branch points mark developmental decisions. Finally, by applying heat stress to whole seedlings, we address the longstanding question of possible heterogeneity among cell types in the response to an abiotic stress. Although the response of canonical heat shock genes dominates expression across cell types, subtle but significant differences in other genes can be detected among cell types. Taken together, our results demonstrate that single-cell transcriptomics holds promise for studying plant development and plant physiology with unprecedented resolution.

genetics↗