Natural sequence variation as a tool to dissect gene expression regulation in Drosophila melanogaster

Genetic variation is a major cause of differences between individuals and it represents a powerful tool to study gene regulation. By interfering with cis- Regulatory Modules (CRMs), variants can unravel CRM function. On the other hand, predicting the effect of variants on phenotype by the DNA sequence has proven to be challenging. In this thesis, I use Drosophila embryonic development as a model system to study diversity in gene regulation at the transcriptional level. CRMs can be characterized using multiple genome-wide techniques such as DNase hypersensitivity. However, despite having comprehensive CRM maps, it is still difficult to predict what are the genes regulated by each CRM. Functional methods, such as mutagenesis, are effective but poorly scalable. To address this issue, I developed an eQTL method (called DHS-eQTL) that makes use of naturally occurring genetic variation, to associate CRMs with the genes they regulate. The results reveal 2,967 DHS-eQTLs and indicate a high extent of CRM sharing between genes. We validated the results with in silico and in vitro approaches and I discuss upcoming in vivo experiments. We observed long-range enhancer regulation suggesting that commonly used methods to associate genes and enhancers underestimate their distance. Also, the DHS-eQTLs show that promoter-proximal CRMs have widespread distal activity. The separation between populations causes an increase in genetic differences by drift and adaptation to different environments. We investigated gene expression differences between Drosophila populations from five continents by performing RNA-Seq on 80 inbred fly lines. We performed multiple quality-control tests to ensure that the gene expression dataset is of high quality. Gene expression profiles show detectable diversity among the fly lines from different continents and confirm what has been observed at the genetic level. In particular, the African population is the most separated, while the American, European and Australian ones show less diversity. In addition, we identified 903 gene and 2,021 exon eQTLs. Genetic variants can interfere with Transcription Factor Binding Sites (TFBS) and this might, in turn, lead to changes in chromatin accessibility. We applied LS-GKM (an SVM method that uses gapped k-mers) to learn sequence features of tissue-specific accessible chromatin and predict the impact of natural sequence variation on accessibility. We train LS-GKM on six tissue-specific training sets: neuroectodermal, mesodermal and double negative CRMs divided in promoter-proximal and promoter-distal. The method unbiasedly recovers tissue-specific TFBS and shows good performance despite the small training sets. Finally, we score variants from groups of inbred Drosophila lines. Interestingly, rare variants have a higher impact on accessibility

Non-coding RNA Expression, Function, and Variation during Drosophila Embryogenesis

Long non-coding RNAs (lncRNAs) can often function in the regulation of gene expression during development; however, their generality as essential regulators in developmental processes and organismal phenotypes remains unclear. Here, we performed a tailored investigation of lncRNA expression and function during Drosophila embryogenesis, interrogating multiple stages, tissue specificity, nuclear localization, and genetic backgrounds. Our results almost double the number of annotated lncRNAs expressed at these embryonic stages. lncRNA levels are generally positively correlated with those of their neighboring genes, with little evidence of transcriptional interference. Using fluorescent in situ hybridization, we report the spatiotemporal expression of 15 new lncRNAs, revealing very dynamic tissue-specific patterns. Despite this, deletion of selected lncRNA genes had no obvious developmental defects or effects on viability under standard and stressed conditions. However, two lncRNA deletions resulted in modest expression changes of a small number of genes, suggesting that they fine-tune expression of non-essential genes. Several lncRNAs have strain-specific expression, indicating that they are not fixed within the population. This intra-species variation across genetic backgrounds may thereby be a useful tool to distinguish rapidly evolving lncRNAs with as yet non-essential roles.Fil: Schor, Ignacio Esteban. 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; Argentina. European Molecular Biology Laboratory; AlemaniaFil: Bussotti, Giovanni. European Bioinformatics Institute; Reino UnidoFil: Maleš, Matilda. European Molecular Biology Laboratory; AlemaniaFil: Forneris, Mattia. European Molecular Biology Laboratory; AlemaniaFil: Viales, Rebecca R.. European Molecular Biology Laboratory; AlemaniaFil: Enright, Anton J.. European Bioinformatics Institute; Reino UnidoFil: Furlong, Eileen E. M.. European Molecular Biology Laboratory; Alemani

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Predictive features of gene expression variation reveal a mechanistic link between expression variation and differential expression

AbstractFor most biological processes, organisms must respond to extrinsic cues, while maintaining essential gene expression programs. Although studied extensively in single cells, it is still unclear how variation is controlled in multicellular organisms. Here, we used a machine-learning approach to identify genomic features that are predictive of genes with high versus low variation in their expression across individuals, using bulk data to remove stochastic cell-to-cell variation. Using embryonic gene expression across 75 Drosophila isogenic lines, we identify features predictive of expression variation, while controlling for expression level. Genes with low variation fall into two classes, indicating they employ different mechanisms to maintain a robust expression. In contrast, genes with high variation seem to lack both types of stabilizing mechanisms. Applying the framework to human tissues from GTEx revealed similar predictive features, indicating that promoter architecture is an ancient mechanism to control expression variation. Remarkably, expression variation features could also predict differential expression upon stress in both Drosophila and human. Differential gene expression signatures may therefore be partially explained by genetically encoded gene-specific features, unrelated to the studied treatment.</jats:p

Predictive features of gene expression variation reveal mechanistic link with differential expression

Abstract For most biological processes, organisms must respond to extrinsic cues, while maintaining essential gene expression programmes. Although studied extensively in single cells, it is still unclear how variation is controlled in multicellular organisms. Here, we used a machine‐learning approach to identify genomic features that are predictive of genes with high versus low variation in their expression across individuals, using bulk data to remove stochastic cell‐to‐cell variation. Using embryonic gene expression across 75 Drosophila isogenic lines, we identify features predictive of expression variation (controlling for expression level), many of which are promoter‐related. Genes with low variation fall into two classes reflecting different mechanisms to maintain robust expression, while genes with high variation seem to lack both types of stabilizing mechanisms. Applying this framework to humans revealed similar predictive features, indicating that promoter architecture is an ancient mechanism to control expression variation. Remarkably, expression variation features could also partially predict differential expression after diverse perturbations in both Drosophila and humans. Differential gene expression signatures may therefore be partially explained by genetically encoded gene‐specific features, unrelated to the studied treatment

The Vitamin D Receptor Inhibits the Respiratory Chain, Contributing to the Metabolic Switch that Is Essential for Cancer Cell Proliferation

<div><p>We recently described the mitochondrial localization and import of the vitamin D receptor (VDR) in actively proliferating HaCaT cells for the first time, but its role in the organelle remains unknown. Many metabolic intermediates that support cell growth are provided by the mitochondria; consequently, the identification of proteins that regulate mitochondrial metabolic pathways is of great interest, and we sought to understand whether VDR may modulate these pathways. We genetically silenced VDR in HaCaT cells and studied the effects on cell growth, mitochondrial metabolism and biosynthetic pathways. VDR knockdown resulted in robust growth inhibition, with accumulation in the G0G1 phase of the cell cycle and decreased accumulation in the M phase. The effects of VDR silencing on proliferation were confirmed in several human cancer cell lines. Decreased VDR expression was consistently observed in two different models of cell differentiation. The impairment of silenced HaCaT cell growth was accompanied by sharp increases in the mitochondrial membrane potential, which sensitized the cells to oxidative stress. We found that transcription of the subunits II and IV of cytochrome c oxidase was significantly increased upon VDR silencing. Accordingly, treatment of HaCaT cells with vitamin D downregulated both subunits, suggesting that VDR may inhibit the respiratory chain and redirect TCA intermediates toward biosynthesis, thus contributing to the metabolic switch that is typical of cancer cells. In order to explore this hypothesis, we examined various acetyl-CoA-dependent biosynthetic pathways, such as the mevalonate pathway (measured as cholesterol biosynthesis and prenylation of small GTPases), and histone acetylation levels; all of these pathways were inhibited by VDR silencing. These data provide evidence of the role of VDR as a gatekeeper of mitochondrial respiratory chain activity and a facilitator of the diversion of acetyl-CoA from the energy-producing TCA cycle toward biosynthetic pathways that are essential for cellular proliferation.</p></div

VDR knock down cells display an impaired acetyl-coA-dependent biosynthetic rate.

<p>HaCaT cells were infected with shRNA control or VDR shRNA 3 and biosynthetic pathways were examined seven days post-infection. The mevalonate pathway was evaluated as the <i>de novo</i> synthesis of cholesterol (<b>A</b>) and ubiquinone (<b>B</b>). The values represent the means ±SD of three independent experiments. (<b>C</b>) Isoprenoid units produced by the same pathway were analyzed as prenyl moiety incorporation in the small GTPases RhoA and Ras. Control and silenced cells were harvested and the lysates were subjected to TX-114 phase-extraction in order to separate the prenylated forms. Total and prenylated proteins were analyzed using western blotting. VDAC and actin expression demonstrated equivalent protein loading of the hydrophobic phase and total extracts, respectively. (<b>D</b>) Histone acetylation levels were evaluated by western blotting analysis using an anti-acetyl H4 antibody and tubulin as a loading control. The blots are representative of a set of three independent experiments.</p

SARS-CoV-2 Spike Affinity and Dynamics Exclude the Strict Requirement of an Intermediate Host

AbstractSARS-CoV-2 proximal origin is still unclear, limiting the possibility of foreseeing other spillover events with pandemic potential. Here we propose an evolutionary model based on the thorough dissection of SARS-CoV-2 and RaTG13 – the closest bat relative – spike dynamics, kinetics and binding to ACE2. Our results indicate that both spikes share nearly identical, high affinities for Rhinolophus affinis bat and human ACE2, pointing out to negligible species barriers directly related to receptor binding. Also, SARS-CoV-2 spike shows a higher degree of dynamics and kinetics optimization that favors ACE2 engagement. Therefore, we devise an affinity-independent evolutionary process that likely took place in R. affinis bats and limits the eventual involvement of other animal species in initiating the pandemic to the role of vector.</jats:p