The role and regulation of folate metabolism during bacterial infection of Drosophila melanogaster

Immunity and metabolism are closely interlinked processes. Mounting an immune response is costly, and therefore metabolism is altered upon infection to provide the necessary energy and raw materials. In serious or prolonged infection, these immune-induced metabolic changes can be a driver of pathology. Drosophila melanogaster has been a widely used model for the study of interplay between immunity and metabolism. However, many of the signalling mechanisms linking immune detection with metabolic regulation, and their specific consequences for infection course and outcome, remain to be explored. In this work, I used Targeted DamID to generate a transcriptional profile of the fat body during infection. The fat body is the predominant site of energy storage and intermediary metabolism but also coordinates humoral immunity, and is thus a critical tissue for immune-metabolic interaction in Drosophila. I determined that the fly responds to many bacteria by altering expression of genes of the folate cycle and associated enzymes of amino acid metabolism. These transcriptional changes occur in a manner that would increase flow of carbon from glycolysis into serine and glycine synthesis and increase folate cycle flux through the mitochondrion. I determined that the two most highly induced enzymes, astray and Nmdmc, are repressed in healthy flies by the transcription factor MEF2. This repression is overcome upon infection by the coordinated action of major immune and metabolic transcription factors Dif and FOXO. The transcriptional regulation of these serine-folate metabolic unit enzymes has functional consequence for immunity, as knockdowns and mutants present altered resistance and tolerance phenotypes, in a pathogen-specific manner. This work has thus uncovered the immune-induced signalling that regulates a novel metabolic unit of functional importance during infection.Open Acces

TECPR1 conjugates LC3 to damaged endomembranes upon detection of sphingomyelin exposure

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

An Environmental Science and Engineering Framework for Combating Antimicrobial Resistance

On June 20, 2017, members of the environmental engineering and science (EES) community convened at the Association of Environmental Engineering and Science Professors (AEESP) Biennial Conference for a workshop on antimicrobial resistance. With over 80 registered participants, discussion groups focused on the following topics: risk assessment, monitoring, wastewater treatment, agricultural systems, and synergies. In this study, we summarize the consensus among the workshop participants regarding the role of the EES community in understanding and mitigating the spread of antibiotic resistance via environmental pathways. Environmental scientists and engineers offer a unique and interdisciplinary perspective and expertise needed for engaging with other disciplines such as medicine, agriculture, and public health to effectively address important knowledge gaps with respect to the linkages between human activities, impacts to the environment, and human health risks. Recommendations that propose priorities for research within the EES community, as well as areas where interdisciplinary perspectives are needed, are highlighted. In particular, risk modeling and assessment, monitoring, and mass balance modeling can aid in the identification of “hot spots” for antibiotic resistance evolution and dissemination, and can help identify effective targets for mitigation. Such information will be essential for the development of an informed and effective policy aimed at preserving and protecting the efficacy of antibiotics for future generations

An Environmental Science and Engineering Framework for Combating Antimicrobial Resistance

On June 20, 2017, members of the environmental engineering and science (EES) community convened at the Association of Environmental Engineering and Science Professors (AEESP) Biennial Conference for a workshop on antimicrobial resistance. With over 80 registered participants, discussion groups focused on the following topics: risk assessment, monitoring, wastewater treatment, agricultural systems, and synergies. In this study, we summarize the consensus among the workshop participants regarding the role of the EES community in understanding and mitigating the spread of antibiotic resistance via environmental pathways. Environmental scientists and engineers offer a unique and interdisciplinary perspective and expertise needed for engaging with other disciplines such as medicine, agriculture, and public health to effectively address important knowledge gaps with respect to the linkages between human activities, impacts to the environment, and human health risks. Recommendations that propose priorities for research within the EES community, as well as areas where interdisciplinary perspectives are needed, are highlighted. In particular, risk modeling and assessment, monitoring, and mass balance modeling can aid in the identification of 'hot spots' for antibiotic resistance evolution and dissemination, and can help identify effective targets for mitigation. Such information will be essential for the development of an informed and effective policy aimed at preserving and protecting the efficacy of antibiotics for future generations

Kudzu Bug Preference Across Four Soybean Varieties

The kudzu bug,Megacopta cribraria,was first discovered in Georgia in 2009. Soybeans are a profitable agricultural crop and a host plant for kudzu bugs. The purpose of this experiment was to determine if kudzu bugs would exhibit a preference between rhizobia-inoculated and un-inoculated treatments across four different soybean varieties (Butterbean, Viking, Black jet, and Tohya). Rhizobia bacteria allow nodulation and nitrogen fixation in soybeans. Kudzu bug preference was determined by placing 6-10 kudzu bugs into a bug dorm with one inoculated and one uninoculated plant. Soybean varieties were examined separately. For two days, the number of kudzu bugs present on each plant was counted and recorded twice a day. There was no significant difference in preference between inoculated and control treatments for tohya. Kudzu bugs significantly preferred inoculated black jet and viking and uninoculated butterbean soybean varieties. It was expected that kudzu bugs would have preferred inoculated soybeans across all varieties; however, the varied preferences in the experiment was unexpected because soybeans with nodules are assumed to have a higher nutritional content than those without

Micro-scale Testing of Fiber Reinforced Polymer Resin and Additive to Evaluate Kinetic Parameters for Pyrolysis Modeling

The testing of Fiber Reinforced Polymers (FRP) is an essential building block to understanding the chemical and physical properties involved in their decomposition. The goal of this project was to evaluate the kinetic parameters of a specific resin and additive via testing and model their decomposition using the fire pyrolysis program, Gpyro. Samples of different resin-additive ratios were evaluated using Thermogravimetric Analysis (TGA) and Differential Scanning Calorimetry (DSC). These data were used to determine kinetic parameters of the resin and additive based on optimization of standard 0D models. To check the validity of these 0D models thermal lag analysis was conducted and the model Gpyro was used to conduct 1D simulation of TGA specimens

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

TECPR1 conjugates LC3 to damaged endomembranes upon detection of sphingomyelin exposure

Acknowledgements: We thank the LMB mass spectrometry facility for analysing samples (Farida Begum, Sew Peak Chew and Mark Skehel). This work was supported by the Medical Research Council as part of United Kingdom Research and Innovation [U105170648] and was funded in whole, or in part, by the Wellcome Trust [222503/Z/21/Z]. For the purpose of open access, the MRC Laboratory of Molecular Biology has applied a CC BY public copyright license to any Author Accepted Manuscript version arising from this submission.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

TECPR1 conjugates LC3 to damaged endomembranes upon detection of sphingomyelin exposure.

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

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