Maintenance of neuronal fate and transcriptional identity

The processes that drive naive multipotent stem cells towards fully differentiated fates are increasingly well understood. However, once differentiated, the mechanisms and molecular factors involved in maintaining differentiated states and associated transcriptomes are less well studied. Neurons are a post-mitotic cell-type with highly specialised functions that largely lack the capacity for renewal. Therefore, neuronal cell identities and the transcriptional states that underpin them are locked into place by active mechanisms that prevent lineage reversion/dedifferentiation and repress cell cycling. Furthermore, individual neurons may be very long-lived, so these mechanisms must be sufficient to ensure the fidelity of neuronal transcriptomes over long time periods. This Review aims to provide an overview of recent progress in understanding how neuronal cell fate and associated gene expression are maintained and the transcriptional regulators that are involved. Maintenance of neuronal fate and subtype specification are discussed, as well as the activating and repressive mechanisms involved. The relevance of these processes to disease states, such as brain cancers and neurodegeneration is outlined. Finally, outstanding questions and hypotheses in this field are proposed

Bi-allelic genetic variants in the translational GTPases GTPBP1 and GTPBP2 cause a distinct identical neurodevelopmental syndrome

: The homologous genes GTPBP1 and GTPBP2 encode GTP-binding proteins 1 and 2, which are involved in ribosomal homeostasis. Pathogenic variants in GTPBP2 were recently shown to be an ultra-rare cause of neurodegenerative or neurodevelopmental disorders (NDDs). Until now, no human phenotype has been linked to GTPBP1. Here, we describe individuals carrying bi-allelic GTPBP1 variants that display an identical phenotype with GTPBP2 and characterize the overall spectrum of GTP-binding protein (1/2)-related disorders. In this study, 20 individuals from 16 families with distinct NDDs and syndromic facial features were investigated by whole-exome (WES) or whole-genome (WGS) sequencing. To assess the functional impact of the identified genetic variants, semi-quantitative PCR, western blot, and ribosome profiling assays were performed in fibroblasts from affected individuals. We also investigated the effect of reducing expression of CG2017, an ortholog of human GTPBP1/2, in the fruit fly Drosophila melanogaster. Individuals with bi-allelic GTPBP1 or GTPBP2 variants presented with microcephaly, profound neurodevelopmental impairment, pathognomonic craniofacial features, and ectodermal defects. Abnormal vision and/or hearing, progressive spasticity, choreoathetoid movements, refractory epilepsy, and brain atrophy were part of the core phenotype of this syndrome. Cell line studies identified a loss-of-function (LoF) impact of the disease-associated variants but no significant abnormalities on ribosome profiling. Reduced expression of CG2017 isoforms was associated with locomotor impairment in Drosophila. In conclusion, bi-allelic GTPBP1 and GTPBP2 LoF variants cause an identical, distinct neurodevelopmental syndrome. Mutant CG2017 knockout flies display motor impairment, highlighting the conserved role for GTP-binding proteins in CNS development across species

Investigation into the mechanisms of cytoophidia assembly in drosophila melanogaster

Subcellular sequestration of proteins within membrane bound compartments is widely acknowledged to be an important mode of enzymatic regulation. Recently a novel paradigm for metabolic enzyme compartmentalisation has become apparent with the identification of several proteins which are able to form filamentous structures in vivo. Multiple studies independently identified the essential de novo pyrimidine biosynthesis enzyme CTP synthetase as a major constituent of a novel filamentous structure which has been termed “the cytoophidium”. Cytoophidia have been observed to form in multiple organisms including bacteria (C. crescentus), yeast (S. cerevisiae) and fruit fly (D. melanogaster) as well as in human cultured cells.In this thesis I describe the development and results of a high throughput genomescale screen to identify factors involved in cytoophidia biogenesis. Observations of tissue specific CTPS distribution lead to the identification of the well-conserved growth regulator dm/dMyc as an essential factor for CTPS regulation in vivo. These results provide new insights into the coordination of cellular growth and metabolic regulation during normal development and indicate the potential of CTPS/cytoophidia as a future therapeutic target.This thesis is not currently available via ORA

Dynamic adult tracheal plasticity drives stem cell adaptation to changes in intestinal homeostasis

Data that was previously stored at this DOI can now be accessed from: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE163570 To download the raw data (260GB approx.) that underpins this paper please request a link to it using the 'Request Data' button above. Details of what is included in the raw data can be seen in the readme file attached

<i>Myc</i> overexpression promotes cytoophidium formation in follicle cells.

<p>(<b>A-D</b>) In stage-8 egg chambers, <i>UAS</i>-<i>Myc</i> overexpression clones marked with GFP (<b>B</b>, outlined in yellow in <b>A-D</b>) have longer cytoophidia, as indicated by CTPsyn staining (<b>C</b>), than non-GFP cells. DNA staining shows that the nuclei in clones (green cells in <b>D</b>) are larger than those of neighbouring cells (non-green cells in <b>D</b>). (<b>E</b>) Cytoophidia in <i>Myc</i> overexpression (<i>UAS-Myc</i>) cells increase significantly in length, compared with those in neighbouring cells. ***P<0.001. Error bars show SEM.</p

<i>Myc</i> overexpression increases cytoophidia length in <i>Drosophila</i> follicle cells.

<p><b>(A-E)</b> The nuclei of cells overexpressing <i>Myc</i> (<i>UAS-Myc</i>) are marked by GFP (<b>B</b>, outlined by yellow lines in A-E). <i>Myc</i> overexpression is verified by immunostaining with an antibody against Myc (<b>C</b>). Note that cytoophidia in the clone cells are not only detectable but also longer than those in wild-type cells (comparing those in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005867#pgen.1005867.g005" target="_blank">Fig 5</a>).</p

<i>CTPsyn</i> knockdown supresses <i>Myc</i>-induced overgrowth phenotype in <i>Drosophila</i> follicle cells.

<p><b>(A-E)</b> The nuclei of cells both overexpressing <i>Myc</i> and knocking down <i>CTPsyn</i> (<i>UAS-Myc</i>, <i>CTPsyn</i>^<i>RNAi</i>) are marked by GFP (<b>B</b>, outlined by yellow lines in <b>A-E</b>). <i>Myc</i> overexpression is verified by immunostaining with an antibody against Myc (<b>D</b>). <i>CTPsyn</i> knockdown is verified by immunostaining with an antibody against CTPsyn (<b>C</b>). Note that no cytoophidia are detectable in the clonal cells even when <i>Myc</i> is overexpressed. (<b>F</b>) Quantification of mid-stage follicle cells shows that <i>Myc</i> overexpression (<i>UAS-Myc</i>) alone increases nuclear size significantly. Follicle cells in <i>UAS-Myc</i>, <i>CTPsyn</i>^<i>RNAi</i> cells have similar nuclear size compared to non-clonal (nc) cells. <i>CTPsyn</i>^<i>RNAi</i> or <i>CTPsyn</i> overexpression show no significant difference in nuclear area (see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005867#pgen.1005867.s010" target="_blank">S10</a> and <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005867#pgen.1005867.s011" target="_blank">S11</a> Figs for representative images). Quantification represents the mean nuclear areas from > 50 cells in > 3 egg chambers per genotype. ***P<0.001. n.s. = not significant. Error bars show SEM.</p

<i>Myc</i> knockdown reduces cytoophidium formation in follicle cells.

<p><i>UAS-Myc-RNAi</i>^{<i>JF01761</i>} clones (i.e. <i>Myc</i> RNAi) marked with GFP (<b>B</b>, outlined in yellow in <b>A-H</b>) have decreased levels of Myc (<b>C</b>) and have no detectable cytoophidia as indicated by an antibody against CTP synthase (CTPsyn). DNA staining shows that nuclei of clonal cells (green cells in <b>E-F</b>) are smaller than those of neighbouring cells (non-green cells in <b>E-F</b>). (<b>I</b>) Quantification of nuclear area shows that <i>Myc</i> RNAi decreases nuclear size significantly. (<b>J</b>) <i>Myc</i> RNAi decreases cytoophidium length significantly. ***P<0.001. Error bars show SEM.</p

A serine-folate metabolic unit controls resistance and tolerance of infection

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.Fil: Grimes, Krista. Imperial College Of Science And Technology; Reino Unido. Imperial College London; Reino UnidoFil: Beckwith, Esteban Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Fisiología, Biología Molecular y Neurociencias. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Fisiología, Biología Molecular y Neurociencias; ArgentinaFil: Pearson, William H.. Imperial College Of Science And Technology; Reino Unido. Imperial College London; Reino UnidoFil: Jacobson, Jake. Imperial College Of Science And Technology; Reino Unido. Imperial College London; Reino UnidoFil: Chaudhari, Surabhi. Imperial College London; Reino Unido. Imperial College Of Science And Technology; Reino UnidoFil: Aughey, Gabriel N.. University College London; Estados Unidos. Imperial College London; Reino UnidoFil: Larrouy Maumus, Gerald. Imperial College Of Science And Technology; Reino Unido. Imperial College London; Reino UnidoFil: Southall, Tony D.. Imperial College Of Science And Technology; Reino Unido. Imperial College London; Reino UnidoFil: Dionne, Marc S.. Imperial College Of Science And Technology; Reino Unido. Imperial College London; Reino Unid

Decoding gene regulation in the fly brain

The Drosophila brain is a frequently used model in neuroscience. Single-cell transcriptome analysis1-6, three-dimensional morphological classification7 and electron microscopy mapping of the connectome8,9 have revealed an immense diversity of neuronal and glial cell types that underlie an array of functional and behavioural traits in the fly. The identities of these cell types are controlled by gene regulatory networks (GRNs), involving combinations of transcription factors that bind to genomic enhancers to regulate their target genes. Here, to characterize GRNs at the cell-type level in the fly brain, we profiled the chromatin accessibility of 240,919 single cells spanning 9 developmental timepoints and integrated these data with single-cell transcriptomes. We identify more than 95,000 regulatory regions that are used in different neuronal cell types, of which 70,000 are linked to developmental trajectories involving neurogenesis, reprogramming and maturation. For 40 cell types, uniquely accessible regions were associated with their expressed transcription factors and downstream target genes through a combination of motif discovery, network inference and deep learning, creating enhancer GRNs. The enhancer architectures revealed by DeepFlyBrain lead to a better understanding of neuronal regulatory diversity and can be used to design genetic driver lines for cell types at specific timepoints, facilitating their characterization and manipulation