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A catalog of transcription factor (TF) binding sites in the genome is critical for deciphering regulatory relationships. Here we present the culmination of the efforts of the Model Organism ENCyclopedia Of DNA Elements (modENCODE) and the model organism Encyclopedia of Regulatory Networks (modERN) consortia to systematically assay TF binding events in vivo in two major model organisms, Drosophila melanogaster (fly) and Caenorhabditis elegans (worm). These datasets comprise 605 TFs identifying 3.6M sites in the fly and 356 TFs identifying 0.9 M sites in the worm and represent the majority of the regulatory space in each genome. We demonstrate that TFs associate with chromatin in clusters termed "metapeaks", that larger metapeaks have characteristics of high occupancy target (HOT) regions, and that the importance of consensus sequence motifs bound by TFs depends on metapeak size and complexity. Combining ChIP-seq data with single cell RNA-seq data in a machine learning model identifies TFs with a prominent role in promoting target gene expression in specific cell types, even differentiating between parent-daughter cells during embryogenesis. These data are a rich resource for the community that should fuel and guide future investigations into TF function. To facilitate data accessibility and utility, all strains expressing GFP-tagged TFs are available at the stock centers for each organism. The chromatin immunoprecipitation sequencing data are available through the ENCODE Data Coordinating Center, GEO, and through a direct interface that provides rapid access to processed data sets and summary analyses, as well as widgets to probe the cell type-specific TF-target relationships., (Published by Cold Spring Harbor Laboratory Press.)

Endocytosis and lysosomal trafficking of cell surface receptors can be triggered by endogenous ligands. Therapeutic approaches such as lysosome-targeting chimaeras 1,2 (LYTACs) and cytokine receptor-targeting chimeras 3 (KineTACs) have used this to target specific proteins for degradation by fusing modified native ligands to target binding proteins. Although powerful, these approaches can be limited by competition with native ligands and requirements for chemical modification that limit genetic encodability and can complicate manufacturing, and, more generally, there may be no native ligands that stimulate endocytosis through a given receptor. Here we describe computational design approaches for endocytosis-triggering binding proteins (EndoTags) that overcome these challenges. We present EndoTags for insulin-like growth factor 2 receptor (IGF2R) and asialoglycoprotein receptor (ASGPR), sortilin and transferrin receptors, and show that fusing these tags to soluble or transmembrane target protein binders leads to lysosomal trafficking and target degradation. As these receptors have different tissue distributions, the different EndoTags could enable targeting of degradation to different tissues. EndoTag fusion to a PD-L1 antibody considerably increases efficacy in a mouse tumour model compared to antibody alone. The modularity and genetic encodability of EndoTags enables AND gate control for higher-specificity targeted degradation, and the localized secretion of degraders from engineered cells. By promoting endocytosis, EndoTag fusion increases signalling through an engineered ligand-receptor system by nearly 100-fold. EndoTags have considerable therapeutic potential as targeted degradation inducers, signalling activators for endocytosis-dependent pathways, and cellular uptake inducers for targeted antibody-drug and antibody-RNA conjugates., (© 2024. The Author(s).)

Deep-learning methods have revolutionized protein structure prediction and design but are presently limited to protein-only systems. We describe RoseTTAFold All-Atom (RFAA), which combines a residue-based representation of amino acids and DNA bases with an atomic representation of all other groups to model assemblies that contain proteins, nucleic acids, small molecules, metals, and covalent modifications, given their sequences and chemical structures. By fine-tuning on denoising tasks, we developed RFdiffusion All-Atom (RFdiffusionAA), which builds protein structures around small molecules. Starting from random distributions of amino acid residues surrounding target small molecules, we designed and experimentally validated, through crystallography and binding measurements, proteins that bind the cardiac disease therapeutic digoxigenin, the enzymatic cofactor heme, and the light-harvesting molecule bilin.

Recently it has become possible to de novo design high affinity protein binding proteins from target structural information alone. There is, however, considerable room for improvement as the overall design success rate is low. Here, we explore the augmentation of energy-based protein binder design using deep learning. We find that using AlphaFold2 or RoseTTAFold to assess the probability that a designed sequence adopts the designed monomer structure, and the probability that this structure binds the target as designed, increases design success rates nearly 10-fold. We find further that sequence design using ProteinMPNN rather than Rosetta considerably increases computational efficiency., (© 2023. The Author(s).)

To develop a catalog of regulatory sites in two major model organisms, Drosophila melanogaster and Caenorhabditis elegans , the modERN (model organism Encyclopedia of Regulatory Networks) consortium has systematically assayed the binding sites of transcription factors (TFs). Combined with data produced by our predecessor, modENCODE (Model Organism ENCyclopedia Of DNA Elements), we now have data for 262 TFs identifying 1.23 M sites in the fly genome and 217 TFs identifying 0.67 M sites in the worm genome. Because sites from different TFs are often overlapping and tightly clustered, they fall into 91,011 and 59,150 regions in the fly and worm, respectively, and these binding sites span as little as 8.7 and 5.8 Mb in the two organisms. Clusters with large numbers of sites (so-called high occupancy target, or HOT regions) predominantly associate with broadly expressed genes, whereas clusters containing sites from just a few factors are associated with genes expressed in tissue-specific patterns. All of the strains expressing GFP-tagged TFs are available at the stock centers, and the chromatin immunoprecipitation sequencing data are available through the ENCODE Data Coordinating Center and also through a simple interface (http://epic.gs.washington.edu/modERN/) that facilitates rapid accessibility of processed data sets. These data will facilitate a vast number of scientific inquiries into the function of individual TFs in key developmental, metabolic, and defense and homeostatic regulatory pathways, as well as provide a broader perspective on how individual TFs work together in local networks and globally across the life spans of these two key model organisms., (Copyright © 2018 by the Genetics Society of America.)

Despite the large evolutionary distances between metazoan species, they can show remarkable commonalities in their biology, and this has helped to establish fly and worm as model organisms for human biology. Although studies of individual elements and factors have explored similarities in gene regulation, a large-scale comparative analysis of basic principles of transcriptional regulatory features is lacking. Here we map the genome-wide binding locations of 165 human, 93 worm and 52 fly transcription regulatory factors, generating a total of 1,019 data sets from diverse cell types, developmental stages, or conditions in the three species, of which 498 (48.9%) are presented here for the first time. We find that structural properties of regulatory networks are remarkably conserved and that orthologous regulatory factor families recognize similar binding motifs in vivo and show some similar co-associations. Our results suggest that gene-regulatory properties previously observed for individual factors are general principles of metazoan regulation that are remarkably well-preserved despite extensive functional divergence of individual network connections. The comparative maps of regulatory circuitry provided here will drive an improved understanding of the regulatory underpinnings of model organism biology and how these relate to human biology, development and disease.

Discovering the structure and dynamics of transcriptional regulatory events in the genome with cellular and temporal resolution is crucial to understanding the regulatory underpinnings of development and disease. We determined the genomic distribution of binding sites for 92 transcription factors and regulatory proteins across multiple stages of Caenorhabditis elegans development by performing 241 ChIP-seq (chromatin immunoprecipitation followed by sequencing) experiments. Integration of regulatory binding and cellular-resolution expression data produced a spatiotemporally resolved metazoan transcription factor binding map. Using this map, we explore developmental regulatory circuits that encode combinatorial logic at the levels of co-binding and co-expression of transcription factors, characterizing the genomic coverage and clustering of regulatory binding, the binding preferences of, and biological processes regulated by, transcription factors, the global transcription factor co-associations and genomic subdomains that suggest shared patterns of regulation, and identifying key transcription factors and transcription factor co-associations for fate specification of individual lineages and cell types.

How cells adopt different expression patterns is a fundamental question of developmental biology. We quantitatively measured reporter expression of 127 genes, primarily transcription factors, in every cell and with high temporal resolution in C. elegans embryos. Embryonic cells are highly distinct in their gene expression; expression of the 127 genes studied here can distinguish nearly all pairs of cells, even between cells of the same tissue type. We observed recurrent lineage-regulated expression patterns for many genes in diverse contexts. These patterns are regulated in part by the TCF-LEF transcription factor POP-1. Other genes' reporters exhibited patterns correlated with tissue, position, and left-right asymmetry. Sequential patterns both within tissues and series of sublineages suggest regulatory pathways. Expression patterns often differ between embryonic and larval stages for the same genes, emphasizing the importance of profiling expression in different stages. This work greatly expands the number of genes in each of these categories and provides the first large-scale, digitally based, cellular resolution compendium of gene expression dynamics in live animals. The resulting data sets will be a useful resource for future research.

We systematically generated large-scale data sets to improve genome annotation for the nematode Caenorhabditis elegans, a key model organism. These data sets include transcriptome profiling across a developmental time course, genome-wide identification of transcription factor-binding sites, and maps of chromatin organization. From this, we created more complete and accurate gene models, including alternative splice forms and candidate noncoding RNAs. We constructed hierarchical networks of transcription factor-binding and microRNA interactions and discovered chromosomal locations bound by an unusually large number of transcription factors. Different patterns of chromatin composition and histone modification were revealed between chromosome arms and centers, with similarly prominent differences between autosomes and the X chromosome. Integrating data types, we built statistical models relating chromatin, transcription factor binding, and gene expression. Overall, our analyses ascribed putative functions to most of the conserved genome.

Brassinosteroids (BRs) signal through a plasma membrane-localized receptor kinase to regulate plant growth and development. We showed previously that a novel protein, BES1, accumulates in the nucleus in response to BRs, where it plays a role in BR-regulated gene expression; however, the mechanism by which BES1 regulates gene expression is unknown. In this study, we dissect BES1 subdomains and establish that BES1 is a transcription factor that binds to and activates BR target gene promoters both in vitro and in vivo. BES1 interacts with a basic helix-loop-helix protein, BIM1, to synergistically bind to E box (CANNTG) sequences present in many BR-induced promoters. Loss-of-function and gain-of-function mutants of BIM1 and its close family members display BR response phenotypes. Thus, BES1 defines a new class of plant-specific transcription factors that cooperate with transcription factors such as BIM1 to regulate BR-induced genes.

Plant steroid hormones, brassinosteroids (BRs), are perceived by the plasma membrane-localized leucine-rich-repeat-receptor kinase BRI1. Based on sequence similarity, we have identified three members of the BRI1 family, named BRL1, BRL2 and BRL3. BRL1 and BRL3, but not BRL2, encode functional BR receptors that bind brassinolide, the most active BR, with high affinity. In agreement, only BRL1 and BRL3 can rescue bri1 mutants when expressed under the control of the BRI1 promoter. While BRI1 is ubiquitously expressed in growing cells, the expression of BRL1 and BRL3 is restricted to non-overlapping subsets of vascular cells. Loss-of-function of brl1 causes abnormal phloem:xylem differentiation ratios and enhances the vascular defects of a weak bri1 mutant. bri1 brl1 brl3 triple mutants enhance bri1 dwarfism and also exhibit abnormal vascular differentiation. Thus, Arabidopsis contains a small number of BR receptors that have specific functions in cell growth and vascular differentiation.

Plant steroid hormones, brassinosteroids (BRs), are perceived by a cell surface receptor kinase, BRI1, but how BR binding leads to regulation of gene expression in the nucleus is unknown. Here we describe the identification of BZR1 as a nuclear component of the BR signal transduction pathway. A dominant mutation bzr1-1D suppresses BR-deficient and BR-insensitive (bri1) phenotypes and enhances feedback inhibition of BR biosynthesis. BZR1 protein accumulates in the nucleus of elongating cells of dark-grown hypocotyls and is stabilized by BR signaling and the bzr1-1D mutation. Our results demonstrate that BZR1 is a positive regulator of the BR signaling pathway that mediates both downstream BR responses and feedback regulation of BR biosynthesis.

Cytosolic calcium oscillations control signaling in animal cells, whereas in plants their importance remains largely unknown. In wild-type Arabidopsis guard cells abscisic acid, oxidative stress, cold, and external calcium elicited cytosolic calcium oscillations of differing amplitudes and frequencies and induced stomatal closure. In guard cells of the V-ATPase mutant det3, external calcium and oxidative stress elicited prolonged calcium increases, which did not oscillate, and stomatal closure was abolished. Conversely, cold and abscisic acid elicited calcium oscillations in det3, and stomatal closure occurred normally. Moreover, in det3 guard cells, experimentally imposing external calcium-induced oscillations rescued stomatal closure. These data provide genetic evidence that stimulus-specific calcium oscillations are necessary for stomatal closure.