The Drosophila brain is a work horse in neuroscience. Single-cell transcriptome analysis 1-5 , 3D morphological classification 6 , and detailed EM mapping of the connectome 7-10 have revealed an immense diversity of neuronal and glial cell types that underlie the wide array of functional and behavioral traits in the fruit fly. The identities of these cell types are controlled by -still unknowngene regulatory networks (GRNs), involving combinations of transcription factors that bind to genomic enhancers to regulate their target genes. To characterize the GRN for each cell type in the Drosophila brain, we profiled chromatin accessibility of 240,919 single cells spanning nine developmental timepoints, and integrated this data with single-cell transcriptomes. We identify more than 95,000 regulatory regions that are used in different neuronal cell types, of which around 70,000 are linked to specific developmental trajectories, involving neurogenesis, reprogramming and maturation. For 40 cell types, their uniquely accessible regions could be associated with their expressed transcription factors and downstream target genes, through a combination of motif discovery, network inference techniques, and deep learning. We illustrate how these "enhancer-GRNs" can be used to reveal enhancer architectures leading to a better understanding of neuronal regulatory diversity. Finally, our atlas of regulatory elements can be used to design genetic driver lines for specific cell types at specific timepoints, facilitating the characterization of brain cell types and the manipulation of brain function. MainThe brain consists of a myriad of different neuronal and glial types, each unique in their morphology and function. The Drosophila brain, which contains around 100,000 cells, is uniquely positioned as a model in which the diversity of brain cell types can be investigated. Recent advances in electron microscopy have allowed the creation of connectome maps of the different regions in the Drosophila brain 7-10 , while the availability of genetic driver lines 11 provides genetic access to many cell types for understanding neuronal function 12 . Furthermore, this diversity of cell types has been bolstered by single-cell transcriptomics on the adult brain 1-5 , the larval brain [13][14][15] , and the ventral nerve cord 16 . The recent development of single-cell assay for transposase accessible chromatin by sequencing (scATAC-seq), makes it possible to measure chromatin accessibility of single cells in high throughput 17,18 , providing an additional crucial layer of information underlying neuronal identity: which genomic regions encode the regulatory information to create and maintain each cell type. The integrated analysis of transcriptomics and chromatin accessibility makes it then possible to jointly study enhancers and gene expression to discover precise regulatory programs across cell types [19][20][21] .Cell type identity is defined by the activity of GRNs in which combinations of transcription factors activate or repress target genes....

Invasive bacteria enter the cytosol of host cells through initial uptake into bacteria-containing vacuoles (BCVs) and subsequent rupture of the BCV membrane, thereby exposing to the cytosol intraluminal, otherwise shielded danger signals such as glycans and sphingomyelin. The detection of glycans by galectin-8 triggers anti-bacterial autophagy, but how cells sense and respond to cytosolically exposed sphingomyelin remains unknown. Here, we identify TECPR1 (tectonin beta-propeller repeat containing 1) as a receptor for cytosolically exposed sphingomyelin, which recruits ATG5 into an E3 ligase complex that mediates lipid conjugation of LC3 independently of ATG16L1. TECPR1 binds sphingomyelin through its N-terminal DysF domain (N'DysF), a feature not shared by other mammalian DysF domains. Solving the crystal structure of N'DysF, we identified key residues required for the interaction, including a solvent-exposed tryptophan (W154) essential for binding to sphingomyelin-positive membranes and the conjugation of LC3 to lipids. Specificity of the ATG5/ATG12-E3 ligase responsible for the conjugation of LC3 is therefore conferred by interchangeable receptor subunits, that is, the canonical ATG16L1 and the sphingomyelin-specific TECPR1, in an arrangement reminiscent of certain multi-subunit ubiquitin E3 ligases.

During neuronal development, extensive changes to chromatin states occur to regulate lineage‐specific gene expression. The molecular factors underlying the repression of non‐neuronal genes in differentiated neurons are poorly characterised. The Mi2/NuRD complex is a multiprotein complex with nucleosome remodelling and histone deacetylase activity. Whilst NuRD has previously been implicated in the development of nervous system tissues, the precise nature of the gene expression programmes that it coordinates is ill‐defined. Furthermore, evidence from several species suggests that Mi‐2 may be incorporated into multiple complexes that may not possess histone deacetylase activity. We show that Mi‐2 activity is required for suppressing ectopic expression of germline genes in neurons independently of HDAC1/NuRD, whilst components of NuRD, including Mi‐2, regulate neural gene expression to ensure proper development of the larval nervous system. We find that Mi‐2 binding in the genome is dynamic during neuronal maturation, and Mi‐2‐mediated repression of ectopic gene expression is restricted to the early stages of neuronal development, indicating that Mi‐2/NuRD is required for establishing stable neuronal transcriptomes during the early stages of neuronal differentiation.

During neuronal development, extensive changes to chromatin states occur to regulate lineage-specific gene expression. The molecular factors underlying the repression of non-neuronal genes in differentiated neurons are poorly characterised. The Mi2/NuRD complex is a multiprotein complex with nucleosome remodelling and histone deacetylase activity. Whilst NuRD has previously been implicated in the development of nervous system tissues the precise nature of the gene expression programmes that it coordinates are ill-defined. Furthermore, evidence from several species suggests that Mi-2 may be incorporated into multiple complexes that may not possess histone deacetylase activity. Here, we show that Mi-2 activity is required for suppressing the ectopic expression of germline genes in neurons independently of HDAC1/NuRD, whilst components of the NuRD complex including Mi-2 regulate neural gene expression to ensure proper development of the larval nervous system. We find that Mi-2 binding in the genome is dynamic during neuronal maturation and Mi-2 mediated repression of ectopic gene expression is restricted to the early stages of neuronal development, indicating that Mi-2/NuRD is required for establishing stable neuronal transcriptomes during the early stages of neuronal differentiation.

Immune activation drives metabolic change in most animals. Immune-induced metabolic change is most conspicuous as a driver of pathology in serious or prolonged infection, but it is normally expected to be important to support immune function and recovery. Many of the signalling mechanisms linking immune detection with metabolic regulation, and their specific consequences, are unknown. Here, we show that Drosophila melanogaster respond to many bacterial infections by altering expression of genes of the folate cycle and associated enzymes of amino acid metabolism. The net result of these changes is increased flow of carbon from glycolysis into serine and glycine synthesis and a shift of folate cycle activity from the cytosol into the mitochondrion. Immune-induced transcriptional induction of astray and Nmdmc, the two most-induced of these enzymes, depends on Dif and foxo. Loss of astray or Nmdmc results in infection-specific immune defects. Our work thus shows a key mechanism that connects immune-induced changes in metabolic signalling with the serine-folate metabolic unit to result in changed immune function.