A versatile genetic tool for post-translational control of gene expression in Drosophila melanogaster

Sethi, Sachin; Wang, Jing W.

doi:10.7554/elife.30327

Cited by 25 publications

(34 citation statements)

References 48 publications

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“…In Drosophila , GAL4 and split GAL4 lines enable targeting of single cell types 3 , but selective manipulation of subsets of neurons of the same type remains challenging. For example, effector expression can be restricted by limiting the spatial and/or temporal expression of a recombinase, but this necessitates user-dependent heat shock or chemical induction, and in some cases, cannot be used in post-mitotic cells 4-6 . Therefore, a routine all-genetic method of expressing effectors in defined fractions of post-mitotic cells of the same type would provide a powerful means of dissecting cellular and genetic functions.…”

Section: Main Textmentioning

confidence: 99%

SPARC: a method to genetically manipulate precise proportions of cells

Isaacman-Beck

Cfr

et al. 2019

Preprint

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17Many experimental approaches rely on controlling gene expression in select subsets of 18 cells within an individual animal. However, reproducibly targeting transgene expression 19 to specific fractions of a genetically-defined cell-type is challenging. We developed 20Sparse Predictive Activity through Recombinase Competition (SPARC), a generalizable 21 toolkit that can express any effector in precise proportions of post-mitotic cells in 22Drosophila. Using this approach, we demonstrate targeted expression of many 23 S2) 7 . The core of this toolkit is a set of bistable UAS-driven constructs that can be 46 switched on or off in different relative proportions of cells, depending on their 47 expression of each SPARC construct in one of the largest genetically-defined 62 populations of neurons in the Drosophila optic lobe, T4 and T5 cells 11 , in animals that 63 express PhiC31 pan-neuronally. Across SPARC-GCaMP6f variants, we observed 64 progressively fewer labeled neurons (Fig. 1C-E). SPARC-attP60-GCaMP6f labeled 65 many overlapping neurons, SPARC-attP38-GCaMP6f labeled an intermediate number 66of neurons and SPARC-attP34-GCaMP6f labeled individual neurons whose dendrites 67 could be visualized (Fig 1E inset). We therefore named these variants SPARC-D individual T5 cells relied on laborious FlpOut approaches that required titrated and 108 temporally precise heat shocks of Drosophila larvae to restrict effector expression to a 109 subset of cells [16][17][18] . In contrast, the SPARC method consistently labeled fewer T5 110 neurons, and labeled them more sparsely, than the sparsest FlpOut labeling using brief 111 and developmentally late heat-shock ( Fig. 1E, 2A,B). More importantly, when we 112 imaged visually-evoked Ca 2+ responses in regions of interest (ROIs) representing T5 113 dendrites, we observed that the fluorescent signals from SPARC-labeled ROIs were depolarized ( Figure 2I, J). Indeed, tdTomato -R2 neurons were slightly hyperpolarized 130 by light ( Figure 2I, J), implying that these R2 neurons were postsynaptic to other R2 131 neurons that express CsChrimson. Thus, the SPARC system enables optogenetic 132 activation of sparse cell populations within a single cell type, allowing us to discover 133 evidence for mutual inhibitory interactions within a cell type. Although it was already 134 known that some R neuron types inhibit other R types 20 , it was not previously known 135 that there is mutual inhibition between R neurons of the same type.

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Section: Main Textmentioning

confidence: 99%

SPARC: a method to genetically manipulate precise proportions of cells

Isaacman-Beck

Cfr

et al. 2019

Preprint

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“…Because adult neurogenesis occurs in the visual and auditory/vestibular sensory systems, we hypothesized that the adult olfactory system also retains this capacity. To investigate this, we applied P-MARCM with the pan-neuronal line nsyb-GAL4 (P-MARCM nsyb), in order to maximize the number of new OSN detected in the antennae (Vosshall et al, 2000; Sethi and Wang, 2017). We activated P-MARCM nsyb on 3-5 days-old female flies by heat shock and quantified OSN neurogenesis from confocal images of antennae dissected weekly over the next 3 weeks (Figure 1D,E).…”

Section: Resultsmentioning

confidence: 99%

Olfactory neuron turnover in adultDrosophila

Fernández-Hernández

2020

Preprint

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Sustained neurogenesis occurs in the olfactory epithelium of several species, including humans, to support olfactory function throughout life. We recently developed a modified lineage tracing method to identify adult neurogenesis in Drosophila. By applying this technique, here we report on the continuous generation of Olfactory Sensory Neurons (OSN) in the antennae of adult Drosophila. New neurons develop sensory dendrites and project axons targeting diverse glomeruli of the antennal lobes in the brain. Furthermore, we identified sustained apoptosis of OSN in the antennae of adult flies, revealing unexpected turnover in the adult olfactory system. Our results substantiate Drosophila as a compelling platform to expedite research about mechanisms and compounds promoting neuronal regeneration, circuit remodeling and its contribution to behavior in the adult.

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“…Another key advantage Drosophila brings as a functional validation platform for big cancer data is the ability to genetically manipulate multiple genes at once. Some of the tools developed for this purpose include the use of multigenic vectors, multiple short hairpin and guide RNA sequences, multicistronic expression systems that use self-cleaving peptides or Internal Ribosome Entry Sites (IRES), parallel genome editing, and multiplexable orthogonal and intersectional expression systems [16,17,[60][61][62][63][64][65][66][67][68][69]. These tools can be used to build transgenic constructs that capture multiple gene expression changes observed in tumors, or those predicted as candidate biomarkers by computational approaches, and explore their roles in tumorigenesis.…”

Section: Functional Exploration Of Integrated Multi-omics Analyses Anmentioning

confidence: 99%

Strategies for Functional Interrogation of Big Cancer Data Using Drosophila Cancer Models

Bangi¹

2020

IJMS

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Rapid development of high throughput genome analysis technologies accompanied by significant reduction in costs has led to the accumulation of an incredible amount of data during the last decade. The emergence of big data has had a particularly significant impact in biomedical research by providing unprecedented, systems-level access to many disease states including cancer, and has created promising opportunities as well as new challenges. Arguably, the most significant challenge cancer research currently faces is finding effective ways to use big data to improve our understanding of molecular mechanisms underlying tumorigenesis and developing effective new therapies. Functional exploration of these datasets and testing predictions from computational approaches using experimental models to interrogate their biological relevance is a key step towards achieving this goal. Given the daunting scale and complexity of the big data available, experimental systems like Drosophila that allow large-scale functional studies and complex genetic manipulations in a rapid, cost-effective manner will be of particular importance for this purpose. Findings from these large-scale exploratory functional studies can then be used to formulate more specific hypotheses to be explored in mammalian models. Here, I will discuss several strategies for functional exploration of big cancer data using Drosophila cancer models.

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A versatile genetic tool for post-translational control of gene expression in Drosophila melanogaster

Cited by 25 publications

References 48 publications

SPARC: a method to genetically manipulate precise proportions of cells

SPARC: a method to genetically manipulate precise proportions of cells

Olfactory neuron turnover in adultDrosophila

Strategies for Functional Interrogation of Big Cancer Data Using Drosophila Cancer Models

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