Interleukin 15 (IL-15) is an essential cytokine for the survival and proliferation of natural killer (NK) cells. IL-15 activates signaling by the β and common γ (γ) chain heterodimer of the IL-2 receptor through -presentation by cells expressing IL-15 bound to the α chain of the IL-15 receptor (IL-15Rα). We show here that membrane-associated IL-15Rα-IL-15 complexes are transferred from presenting cells to NK cells through -endocytosis and contribute to the phosphorylation of ribosomal protein S6 and NK cell proliferation. NK cell interaction with soluble or surface-bound IL-15Rα-IL-15 complex resulted in Stat5 phosphorylation and NK cell survival at a concentration or density of the complex much lower than required to stimulate S6 phosphorylation. Despite this efficient response, Stat5 phosphorylation was reduced after inhibition of metalloprotease-induced IL-15Rα-IL-15 shedding from -presenting cells, whereas S6 phosphorylation was unaffected. Conversely, inhibition of -endocytosis by silencing of the small GTPase TC21 or expression of a dominant-negative TC21 reduced S6 phosphorylation but not Stat5 phosphorylation. Thus, -endocytosis of membrane-associated IL-15Rα-IL-15 provides a mode of regulating NK cells that is not afforded to IL-2 and is distinct from activation by soluble IL-15. These results may explain the strict IL-15 dependence of NK cells and illustrate how the cellular compartment in which receptor-ligand interaction occurs can influence functional outcome.

Transcription is a stochastic process occurring mostly in episodic bursts. Although the local chromatin environment is known to influence the bursting behavior on long timescales, the impact of transcription factors (TFs)-especially in rapidly inducible systems-is largely unknown. Using fluorescence in situ hybridization and computational models, we quantified the transcriptional activity of the proto-oncogene c-Fos with single mRNA accuracy at individual endogenous alleles. We showed that, during MAPK induction, the TF concentration modulates the burst frequency of c-Fos, whereas other bursting parameters remain mostly unchanged. By using synthetic TFs with TALE DNA-binding domains, we systematically altered different aspects of these bursts. Specifically, we linked the polymerase initiation frequency to the strength of the transactivation domain and the burst duration to the TF lifetime on the promoter. Our results show how TFs and promoter binding domains collectively act to regulate different bursting parameters, offering a vast, evolutionarily tunable regulatory range for individual genes.

Transcription factors that can convert adult cells of one type to another are usually discovered empirically by testing factors with a known developmental role in the target cell. Here we show that standard genomic methods (RNA-seq and ChIP-seq) can help identify these factors, as most are more strongly Polycomb repressed in the source cell and more highly expressed in the target cell. This criterion is an effective genome-wide screen that significantly enriches for factors that can transdifferentiate several mammalian cell types including neural stem cells, neurons, pancreatic islets, and hepatocytes. These results suggest that barriers between adult cell types, as depicted in Waddington’s "epigenetic landscape", consist in part of differentially Polycomb-repressed transcription factors. This genomic model of cell identity helps rationalize a growing number of transdifferentiation protocols and may help facilitate the engineering of cell identity for regenerative medicine.

Forty years of classical biochemical analysis have identified the molecular players involved in initiation of transcription by eukaryotic RNA polymerase II (Pol II) and largely assigned their functions. However, a dynamic picture of Pol II transcription initiation and an understanding of the mechanisms of its regulation have remained elusive due in part to inherent limitations of conventional ensemble biochemistry. Here we have begun to dissect promoter-specific transcription initiation directed by a reconstituted human Pol II system at single-molecule resolution using fluorescence video-microscopy. We detected several stochastic rounds of human Pol II transcription from individual DNA templates, observed attenuation of transcription by promoter mutations, observed enhancement of transcription by activator Sp1, and correlated the transcription signals with real-time interactions of holo-TFIID molecules at individual DNA templates. This integrated single-molecule methodology should be applicable to studying other complex biological processes.

Long-term memory depends on the control of activity-dependent neuronal gene expression, which is regulated by epigenetic modifications. The epigenetic modification of histones is orchestrated by the opposing activities of two classes of regulatory complexes: permissive co-activators and silencing co-repressors. Much work has focused on co-activator complexes, but little is known about the co-repressor complexes that suppress the expression of plasticity-related genes. Here, we define a critical role for the co-repressor SIN3A in memory and synaptic plasticity, showing that postnatal neuronal deletion of Sin3a enhances hippocampal long-term potentiation and long-term contextual fear memory. SIN3A regulates the expression of genes encoding proteins in the post-synaptic density. Loss of SIN3A increases expression of the synaptic scaffold Homer1, alters the mGluR1α- and mGluR5-dependence of long-term potentiation, and increases activation of extracellular signal regulated kinase (ERK) in the hippocampus after learning. Our studies define a critical role for co-repressors in modulating neural plasticity and memory consolidation and reveal that Homer1/mGluR signaling pathways may be central molecular mechanisms for memory enhancement.

A brain consists of numerous distinct neurons arising from a limited number of progenitors, called neuroblasts in Drosophila. Each neuroblast produces a specific neuronal lineage. To unravel the transcriptional networks that underlie the development of distinct neuroblast lineages, we marked and isolated lineage-specific neuroblasts for RNA sequencing. We labeled particular neuroblasts throughout neurogenesis by activating a conditional neuroblast driver in specific lineages using various intersection strategies. The targeted neuroblasts were efficiently recovered using a custom-built device for robotic single-cell picking. Transcriptome analysis of mushroom body, antennal lobe and type II neuroblasts compared with non-selective neuroblasts, neurons and glia revealed a rich repertoire of transcription factors expressed among neuroblasts in diverse patterns. Besides transcription factors that are likely to be pan-neuroblast, many transcription factors exist that are selectively enriched or repressed in certain neuroblasts. The unique combinations of transcription factors present in different neuroblasts may govern the diverse lineage-specific neuron fates.

Object recognition depends on the ability to extract stable representations across changes in how they are viewed, yet it remains unclear how this capacity depends on visual acuity and cortical hierarchy. We combined behavioral testing and computational modeling to determine whether tree shrews, close relatives of primates with lower spatial acuity, can perform transformation-tolerant object recognition. Front-end modeling incorporating species-specific optics and photoreceptor sampling showed that, when scaled for acuity, tree shrew retinal filtering preserves the similarity structure of natural image categories relevant for object recognition. Behaviorally, tree shrews reliably discriminated complex objects across variations in position, scale, and viewpoint, including when embedded within natural scenes, and generalized to novel exemplars. Their recognition behavior was best explained by visual features emphasizing differences in global shape and size between objects and by representations from intermediate and deep layers of hierarchical neural network models. These results demonstrate that visual processing supporting object-level generalization can arise within visual systems lacking high-acuity front-end optics and establish the tree shrew as a key model for understanding the computational and evolutionary origins of high-level vision.

In a recent publication, Ma et al [1] claim that a transformer-based cellular segmentation method called Mediar [2] — which won a Neurips challenge — outperforms Cellpose [3] (0.897 vs 0.543 median F1 score). Here we show that this result was obtained by artificially impairing Cellpose in multiple ways. When we removed these impairments, Cellpose outperformed Mediar (0.861 vs 0.826 median F1 score on the updated test set). To further investigate the performance of transformers for cellular segmentation, we replaced the Cellpose backbone with a transformer. The transformer-Cellpose model also did not outperform the standard Cellpose (0.848 median F1 test score). Our results suggest that transformers do not advance the state-of-the-art in cellular segmentation.