Stress has profound effects on health, yet how it damages tissues remains poorly understood. Here, we show that acute stress triggers rapid hair loss and initiates autoimmunity. Under stress, hyperactivated sympathetic nerves release excessive norepinephrine, causing necrosis in rapidly dividing hair follicle transit-amplifying cells (HF-TACs) while sparing most hair follicle stem cells (HFSCs). This differential sensitivity stems from differences in cell death pathways, metabolic strategies, and calcium homeostasis, which render HF-TACs more susceptible to norepinephrine-induced calcium surges. HF-TAC necrosis releases cellular debris that triggers macrophage-mediated clearance and dendritic cell activation, ultimately leading to the activation and amplification of autoreactive T cells that can attack the hair follicle under inflammatory insults. Our findings reveal mechanistically how stress causes immediate tissue damage in highly proliferative HF-TACs via sympathetic nerve-induced necrosis, which in turn fuels the activation of autoreactive T cells capable of mounting future attacks against the same tissue.

The molecular details governing transcription factor (TF) binding and the formation of accessible chromatin are not yet quantitatively understood-including how sequence context modulates affinity, how TFs search DNA, the kinetics of TF occupancy, and how motif grammars coordinate binding. To resolve these questions for a human TF, erythroid Krüppel-like factor (eKLF/KLF1), we quantitatively compare, in high throughput, in vitro TF binding rates and affinities with in vivo single-molecule TF and nucleosome occupancies and in vivo-derived deep learning models. We find that 40-fold flanking sequence effects on affinity are consistent with distal flanks tuning TF search parameters and captured by a linear energy model. Motif recognition probability, rather than time in the bound state, drives affinity changes, and in vitro and in nuclei measurements exhibit consistent, minutes-long TF residence times. Finally, in vitro biophysical parameters predict in vivo sequence preferences and single-molecule chromatin states for unseen motif grammars.

Genome-wide assessment of genetic variation is becoming routine in genetics, yet functional interpretation of non-coding single nucleotide variants in both common and rare diseases remains a major challenge. Here, we used chromatin immunoprecipitation coupled to self-transcribing active regulatory region sequencing (ChIP-STARR-seq) to functionally annotate non-coding regulatory elements (NCREs) in cellular models of human brain development. This provides gene regulatory insights into neural stem cells and evidence of NCRE priming already in embryonic stem cells for later neural activity. Based on this functional genomics atlas, we developed BRAIN-MAGNET (brain-focused artificial intelligence method to analyze genomes for non-coding regulatory element mutation targets), a functionally validated convolutional neural network that predicts NCRE activity from DNA sequence composition and identifies nucleotides required for NCRE function. BRAIN-MAGNET allows fine-mapping of genome-wide association study (GWAS) loci for common neurological traits and prioritizing candidate disease-causing rare non-coding variants in genetically unexplained individuals with neurogenetic disorders. Together, this NCRE atlas and BRAIN-MAGNET represent a powerful resource for the interpretation of non-coding genetic variation, possibly aiding the identification of previously unrecognized enhanceropathies.

The ubiquitous metabolite heme has diverse enzymatic and signaling functions in most mammalian cells. Through integrated analyses of mouse models, human cell lines, and primary patient samples, we identify de novo heme biosynthesis as a selective dependency in acute myeloid leukemia (AML). The dependency is underpinned by a propensity of AML cells, and especially leukemic stem cells (LSCs), to downregulate heme biosynthesis enzymes (HBEs), which promotes their self-renewal. Inhibition of HBEs causes the collapse of mitochondrial Complex IV and dysregulates the copper-chaperone system, inducing cuproptosis, a form of programmed cell death brought about by the oligomerization of lipoylated proteins by copper. Moreover, we identify pathways that are synthetic lethal with heme biosynthesis, including glycolysis, which can be leveraged for combination strategies. Altogether, our work uncovers a heme rheostat that is connected to gene expression and drug sensitivity in AML and implicates HBE inhibition as a trigger of cuproptosis.

Ancient DNA has revolutionized the study of extinct and extant organisms that lived up to 2 million years ago, enabling the reconstruction of genomes from multiple extinct species, as well as the ecosystems where they once thrived. However, current DNA sequencing techniques alone cannot directly provide insights into tissue identity, gene expression dynamics, or transcriptional regulation, as these are encoded in the RNA fraction. Here, we report transcriptional profiles from 10 Late Pleistocene woolly mammoths. One of these, dated to be ∼39,000 years old, yielded sufficient detail to recover tissue-specific regulatory mechanisms and biological functions essential for skeletal muscle metabolism, representing the oldest ancient RNA sequences recorded to date. We showcase the potential to study ancient RNA molecules beyond preconceived limitations, providing an analytical framework for validating and decoding preserved transcriptomes through time. With our findings, we anticipate the emergence of integrative paleo-studies combining genomics, proteomics, and transcriptomics.

Recent studies at molecular and genomic scales have enriched our understanding of life's most fundamental building block: the cell. However, bridging the gap between single-cell phenotypes and the emergent functions of tissues and organs remains a formidable challenge. Here, we suggest that the conceptual span from cells to tissues and organs is so large as to warrant intermediate stepping stones. Drawing inspiration from "network motifs"-discrete units of cell-level function that emerge from the interactions of a handful of genes or enzymes-we argue that similarly identifiable units of tissue-level function, which we term "mesoscale modules," emerge from coordinated "interactions" among relatively small numbers of cells and their extracellular milieu. We outline several such modules and propose that a concerted effort to study them will deepen our foundational understanding of tissue and organ functions. By developing these mesoscale insights, we anticipate a more tractable and mechanistic approach to complex human conditions rooted in tissue- and organ-scale dysregulation, including developmental defects, cancer, cardiovascular disease, immune-related disorders, infectious disease, and aging.

Intrinsically disordered regions (IDRs) of proteins are defined by molecular grammars. This refers to IDR-specific non-random amino acid compositions and non-random patterning of distinct pairs of amino acid types. Here, we introduce grammars inferred using NARDINI+ (GIN) as a resource that uncovers IDR-specific and IDRome-spanning grammars. Using GIN-enabled analyses, we find that specific IDR features and GIN clusters are associated with distinct biological processes, intra-cellular localization preferences, specialized molecular functions, and functionalization as assessed by cellular fitness correlations. IDRs with exceptional grammars, defined as sequences with high-scoring non-random features, are harbored in proteins and complexes that enable spatial and temporal sorting of biochemical activities within the nucleus. Overall, GIN can be used to extract sequence-function relationships of individual IDRs or clusters of IDRs, to redesign extant IDRs or design de novo IDRs, to perform evolutionary analyses through the lens of molecular grammars and GIN clusters, and to make sense of IDR-specific disease-associated mutations.

CRISPR screens have become standard gene discovery platforms in various contexts, including cancer. Yet commonly available CRISPR-Cas9 tools are increasingly recognized as unfit for in vivo investigations in immunocompetent contexts, due to broad immunogenicity of bacterial nucleases and reporters. Here, we show how conventional CRISPR screens in tumor grafts are systematically jeopardized by immunoediting in syngeneic and humanized immunocompetent hosts, resulting in iatrogenic clonal dropouts and ultimately compromising target identification. To resolve this, we present StealTHY, an immunogen-free CRISPR platform compatible with virtually all immunocompetent designs, enabling preservation of clonal architecture and exposing previously concealed cancer vulnerabilities. Among these, we identify the AMH-AMHR2 axis as a formerly unappreciated metastasis target. Thus, with StealTHY, we provide a new resource to expand the applicability of CRISPR screens to immunocompetent models, including humanized tumor grafts, revealing metastasis regulators of therapeutic relevance.

Biomarkers accurately informing prognostic assessment and therapeutic strategy are critical for improving patient outcome in oncology. Here, we apply a whole-genome, tumor-informed circulating tumor DNA (ctDNA) detection approach to address this challenge, leveraging 1,800 variants across 2,994 plasma samples from 431 patients with non-small cell lung cancer (NSCLC) from the TRACERx study. We show that ultrasensitive ctDNA detection below 80 parts per million both pre- and postoperatively is highly prognostic, and combinatorial analysis of the pre- and postoperative ctDNA status identifies an intermediate risk group, improving disease stratification. ctDNA kinetics demonstrate clinical utility during adjuvant therapy, where patients that "clear" ctDNA during adjuvant therapy experience improved outcomes. Moreover, characterization of patterns in postoperative ctDNA kinetics reveals insights into the timing, risk, and anatomical pattern of relapses. By incorporating longitudinal ultrasensitive ctDNA detection, we propose a refined schema for guiding the stratification and treatment recommendations in early stage NSCLC.

Chromatin structure is a key determinant of gene expression in eukaryotes, but it has not been possible to define the structure of cis-regulatory elements at the scale of the proteins that bind them. Here, we generate multidimensional chromosome conformation capture (3C) maps at base-pair resolution using Micro Capture-C ultra (MCCu). This can resolve contacts between individual transcription factor motifs within cis-regulatory elements. Using degron systems, we show that removal of Mediator complex components alters fine-scale promoter structure and that nucleosome depletion plays a key role in transcription factor-driven enhancer-promoter contacts. We observe that chromatin is partitioned into nanoscale domains by nucleosome-depleted regions. This structural conformation is reproduced by chemically specific coarse-grained molecular dynamics simulations of the physicochemical properties of chromatin. Combining MCCu with molecular dynamics simulations and super-resolution microscopy allows us to propose a unified model in which the biophysical properties of chromatin orchestrate contacts between cis-regulatory elements.

Dietary needs are dynamic, with optimal ranges for nutrients varying over time and across physiological states. How optimal nutrient set points are established and why they are adjusted remains largely unknown. In our efforts to understand the physiology of recovery, we made the surprising observation that mice restrict protein intake at the expense of caloric supply. We identified three amino acids-glutamine (Q), lysine (K), and threonine (T)-within dietary protein, which are necessary and sufficient for protein aversion during recovery from catabolic states. The anorexigenic effects of QKT are driven by ammoniagenesis in the gut, sensed by enterochromaffin cells in a TRPA1-dependent fashion and transduced to brainstem neurons via serotonin signaling, inducing anorexia. We propose that this mechanism serves as a first-line defense against ammonia toxicity. In summary, we identified a set of adaptive food preferences during recovery ("recovery behavior"), with implications for understanding diseases of pathologic recovery and the development of therapeutic interventions deployed to enhance recovery.

During cancer development, mutations promote changes in gene expression that cause transformation. Leukemia associated with aberrant HOXA expression is driven by translocations of nucleoporin genes or KMT2A as well as mutations in NPM1. The mechanistic convergence of these disparate mutations remains elusive. Here, we demonstrate that mutant nucleophosmin 1 (NPM1c) forms nuclear condensates in human cell lines, mouse models, and primary patient samples. We show NPM1c phase separation is necessary and sufficient to recruit NUP98 and KMT2A to condensates. Through extensive mutagenesis and pharmacological destabilization of phase separation, we find that NPM1c condensates are necessary for regulating gene expression, promoting in vivo leukemic expansion, and maintaining the undifferentiated leukemic state. Finally, we show that nucleoporin and KMT2A fusion proteins form condensates that are biophysically indistinguishable from NPM1c condensates. Together, these data define a new condensate that we term the coordinating body (C-body) and establish C-bodies as a therapeutic vulnerability in leukemia.

The traditional process of antibody discovery is limited by inefficiency, high costs, and low success rates. Recent approaches employing artificial intelligence (AI) have been developed to optimize existing antibodies and generate antibody sequences in a target-agnostic manner. In this work, we present MAGE (monoclonal antibody generator), a sequence-based protein language model (PLM) fine-tuned for the task of generating paired human variable heavy- and light-chain antibody sequences against targets of interest. We show that MAGE can generate novel and diverse antibody sequences with experimentally validated binding specificity against SARS-CoV-2, an emerging avian influenza H5N1, and respiratory syncytial virus A (RSV-A). MAGE represents a first-in-class model capable of designing human antibodies against multiple targets with no starting template.

Vision first evolved in the water, where the spectral content of light informs about viewing distance. However, whether and how aquatic visual systems exploit this "fact of physics" remains unknown. Here, we show that zebrafish use "color" information to suppress responses to the visual background. For this, zebrafish divide their intact ancestral cone complement into two opposing systems: PR1/4 ("red/UV cones") versus PR2/3 ("green/blue cones"). Of these, the achromatic PR1 and PR4, which are retained in mammals, are necessary and sufficient for vision. By contrast, the color-opponent PR2 and PR3, which are lost in mammals, are neither necessary nor sufficient for vision. Instead, they form an "auxiliary" system that spectrally suppresses the "core" drive from PR1 and PR4. Our insights challenge the long-held notion that vertebrate cone diversity primarily serves color vision and further hint at terrestrialization, not nocturnalization, as the leading driver for visual circuit reorganization in mammals.

Microbial eukaryotes remain understudied despite their critical ecological importance, with the exception of a few established models. They are often small, difficult to culture, and resistant to standard labeling and imaging techniques. Here, we use ultrastructure expansion microscopy (U-ExM) to carry out high-resolution volumetric imaging of over 200 cultured planktonic eukaryotes across major lineages. By combining U-ExM with pan- and specific immuno-labeling, we reveal microtubule and centrin-containing elements and assign molecular identities to enigmatic cytoskeletal structures observed previously only by electron microscopy. This comprehensive resource provides a basis for understanding cytoskeletal diversity, phenotypic plasticity, and evolutionary dynamics. Moreover, our approach extends to mixed environmental samples, paving the way for environmental cell biology at ultrastructural resolution-a crucial step toward understanding and protecting ecosystems in the face of accelerating biodiversity loss.