scholarly journals Identification, characterization and use of novel thermogenetic tools in drosophilia melanogaster

2019 ◽  
Author(s):  
◽  
Aditi Mishra
Keyword(s):  
Drosophila Melanogaster ◽  
Learning And Memory ◽  
Avoidance Behavior ◽  
Dopaminergic Neurons ◽  
Temperature Response ◽  
Place Learning ◽  
Temperature Sensitive ◽  
Gustatory Receptors ◽  
Response Properties ◽  
Different Temperatures

Extrinsic control of neural activity is necessary to decipher the neural mechanisms underlying behavior. Molecular tools that employ light (optogenetics) or temperature (thermogenetics) are primarily used for extrinsic manipulation of neurons. While the available tools offer precise temporal and spatial resolution, their caveats lie in the limited number of tools that can be used simultaneously to alter neuronal activity. The overlapping spectrum of activation of optogenetic tools prevents their simultaneous use in preparations. Similarly, the lack of thermogenetic tools that can function in the physiological range of organisms has restricted their use. The use of thermogenetic tools is limited to two members from the Transient receptor family of proteins, TrpA1 and TrpM8 to activate neurons, and one protein that reduces synaptic output, Shibirets. A major drawback to the Trp channels is their response to both temperature and voltage changes. Hence, the discovery of a new temperature sensitive Gustatory Receptor protein provided an opportunity to mine for other temperature sensitive proteins and develop novel thermogenetic tools. In this thesis we report the identification of several thermosensitive proteins, their characterization, and use in studying the learning and memory of freely moving flies. In the first chapter, we probed several Gustatory receptors for their temperature sensitivity using the heat box. The heat box is a high throughput system that enables us to test and track the behavior of single flies in response to temperature. The top and bottom of heat box chamber has Peltier elements that allow for control of temperature with a resolution of 1[degrees]C. We overexpressed several Gustatory receptors one at a time pan neuronally in Drosophila melanogaster and exposed them to various assays. Our initials results imply that at least 2 Drosophila melanogaster Gustatory receptors other than Gr28bD are temperature sensitive. To increase the repertoire of thermosensitive proteins, we assayed for temperature response properties of Gr28bD orthologs from 5 other Drosophila species that occupy different habitats in the world. We rationalized that flies in different habitats will have Gr28bD orthologs with unique temperature response properties designed to sustain in that habitat. Of the 5 proteins we tested, we found that 4 proteins are temperature sensitive at different temperatures. While pan-neuronal overexpression is a robust method to determine the temperature responsiveness of a protein, it does not recapitulate the natural environment the protein is present in. In D. melanogaster, Gr28bD is present in specialized heat sensing cells in the antenna, called Hot Cells. There are 3 Hot cells on each of the two antennae. There is however no physiological information on the where the orthologs are expressed. Since Gr28bD is used for rapid heat avoidance in flies, we rationalized that its orthologs too sever a similar function in their host species and are expressed in the peripheral regions. Hence, in the second chapter, we tested for the avoidance behavior of flies using two choice assays. We made mutant flies that lacked Gr28b proteins, including Gr28bD in the antennae. We then examined the ability of the orthologs to rescue the heat avoidance behavior in these mutants. We found that all the orthologs respond to temperature differences albeit, at different temperatures. Above a threshold temperature, flies rescued with some orthologs could not differentiate between small temperature differences, suggesting that the activity of the orthologs might saturate beyond certain temperatures. Some homologs responded to temperature only when expressed in Hot Cells, thus leading us to examine the presence of accessory proteins it the hot cells that might be enhancing the thermosensitive properties of these homologs. We found several candidate proteins that can studied further to determine their role in the temperature sensing in the hot cells. When used as thermogenetic tools, thermosensitive proteins are in localized environments in small cluster of cells. In the third chapter, we expressed Gr28bD in small clusters of dopaminergic neurons in the fly brain with an aim to understand the role of activation of dopaminergic neurons in operant place learning and memory paradigm. In addition to examining their learning scores at different temperatures, we investigated other behaviors of the flies during the training. Contrary to previous results from our lab that showed that dopaminergic neurons are not important for place learning and memory, we found that activation of a specific subset of dopaminergic neurons does alter place learning and memory. Our findings new laid the groundwork for more experiments to investigate dopaminergic modulation of place learning and memory.

scholarly journals Multiple genetic loci affect place learning and memory performance in Drosophila melanogaster

2019 ◽  
Vol 18 (7) ◽  
Author(s):  
Patricka A. Williams‐Simon ◽  
Christopher Posey ◽  
Samuel Mitchell ◽  
Enoch Ng'oma ◽  
James A. Mrkvicka ◽  
...  
Keyword(s):  
Drosophila Melanogaster ◽  
Learning And Memory ◽  
Memory Performance ◽  
Place Learning ◽  
Genetic Loci

scholarly journals Multiple genetic loci affect place learning and memory performance in Drosophila melanogaster

2019 ◽  
Author(s):  
P.A. Williams-Simon ◽  
C. Posey ◽  
S. Mitchell ◽  
E. Ng’oma ◽  
J.A. Mrkvicka ◽  
...  
Keyword(s):  
Drosophila Melanogaster ◽  
Learning And Memory ◽  
Recombinant Inbred Lines ◽  
Memory Performance ◽  
Place Learning ◽  
Learning Ability ◽  
Large Set ◽  
High Performing ◽  
Place Memory ◽  
Mapping Resource

AbstractLearning and memory are critical functions for all animals, giving individuals the ability to respond to changes in their environment. Within populations, individuals vary, however the mechanisms underlying this variation in performance are largely unknown. Thus, it remains to be determined what genetic factors cause an individual to have high learning ability, and what factors determine how well an individual will remember what they have learned. To genetically dissect learning and memory performance, we used the DSPR, a multiparent mapping resource in the model system Drosophila melanogaster, consisting of a large set of recombinant inbred lines (RILs) that naturally vary in these and other traits. Fruit flies can be trained in a “heat box” to learn to remain on one side of a chamber (place learning), and can remember this (place memory) over short timescales. Using this paradigm, we measured place learning and memory for ∼49,000 individual flies from over 700 DSPR RILs. We identified 16 different loci across the genome that significantly affect place learning and/or memory performance, with 5 of these loci affecting both traits. To identify transcriptomic differences associated with performance, we performed RNA-Seq on pooled samples of 7 high performing and 7 low performing RILs for both learning and memory and identified hundreds of genes with differences in expression in the two sets. Integrating our transcriptomic results with the mapping results allowed us to identify nine promising candidate genes, advancing our understanding of the genetic basis underlying natural variation in learning and memory performance.

scholarly journals Dissecting the genetic basis of learning, memory, and thermal tolerance in a multi-parental population of fruit flies

2021 ◽  
Author(s):  
◽  
Patricka Williams-Simon
Keyword(s):  
Drosophila Melanogaster ◽  
Candidate Genes ◽  
Learning And Memory ◽  
Thermal Tolerance ◽  
Genetic Basis ◽  
Memory Performance ◽  
Place Learning ◽  
Large Set ◽  
Physiological Mechanisms ◽  
Causal Genes

Learning, memory, and thermal tolerance are complex traits that are fundamental survival skills in many species. For example, small poikilotherms " like Drosophila melanogaster, have evolved physiological mechanisms to learn from and adapt to rapidly warming temperatures because their body temperature reflects that of their surroundings. Along with physiological mechanisms, these animals have also adapted cognitive practices, such as learning and memory, which help them escape extreme temperatures. Although scientific evidence shows that learning, memory, and thermal tolerance have been subjected to natural selection as a means of adapting to warmer temperatures, studies examining both traits (i.e., learning, and thermal tolerance) and how they relate genetically have not been done. Investigating the natural variation of the genes that control these traits is essential if we want to understand better how these traits arise within species. With recent advances in genomic technology, it is now feasible apart - down to a single gene - regions of the genome that influence complex phenotypes. For my Ph.D., I took a quantitative genetics and genomics approach to dissect the genetic basis of learning, memory, and thermal tolerance in Drosophila melanogaster. I hypothesized that there will be a shared and independent genetic locus controlling learning and memory and that there will be a trade-off between learning and thermal tolerance. To genetically dissect learning and memory performance, I used the Drosophila Synthetic Population Resource (DSPR), a multiparent mapping resource, consisting of a large set of recombinant inbred lines (RILs), which allows for high-resolution genome-wide scans, and the identification of loci contributing to naturally occurring genetic variation. Using a highly sensitive apparatus known as the "heat box", I trained flies with temperatures (24 [degrees] C and 41 [degrees] C, which is aversive) to learn to remain on one side of a chamber (place learning) and to remember thiory). An indl that spent most of the time on the side of the chamber associated with 24 [degrees] C will be considered to have high learning and memory. Immediately after, I assayed the flies for thermal tolerance, which is measured as the time to incapacitation at a constant high 41 [degrees] C temperature for 9.5 mins. I identified 16 different loci across the genome that significantly affect place learning and or memory performance, with 5 of these loci affecting both traits and eight loci that influence thermal tolerance. To identify transcriptomic differences associated with learning, memory, and thermal tolerance, I performed RNA-Sequencing (RNA-seq) on pooled samples of seven high-performing and seven low-performing RILs for all three traits and identified hundreds of genes with differences in expression. Integrating our transcriptomic results with the mapping results allowed us to identify nine promising candidate genes that control learning and twenty-one genes that fall between the most significant QTL that is possibly influenci thermal tolerance. I then used a few different methods to identify and validate genetic variants from the list of candidate genes within the most significant QTL (Q6) that influences thermal tolerance. First, I performed a structural variance analysis and found a few structural variants (SV; eg: inserts, deletions, or P-elements) located within candidate genes. Genes that contain SVs are known to influence phenotypic variation, and thus identifying any SV within candidate genes will provide a greater understanding of the genetic basis of a specific complex trait. Second, I functionally validated the candidate genes to identify causal genes using the UAS-GAL4/RNAi system. In this classical genetic system, a specific gene is disrupted through mutagenesis, which allows for the investigation of that gene on a specific phenotype. I then phenotyped lines to determine the phenotypic effect of each gene on thermal tolerance. We screened 20 UAS-RNAi lines (~1900 individuals) that were crossed with both pan neuronal and ubiquitously expressed Gal4 promoters and found 3 lines that were significant. Collectively, these results suggest that learning, memory, and thermal tolerance are highly polygenic and that multiple genes with both large and small effects influence these traits. Future work will aim to validate the function of candidate genes that influence learning and memory and identify the molecular pathways that the causal genes that influence thermal tolerance are associated with.

scholarly journals THE MECHANISM OF A BROODING EFFECT ASSOCIATED WITH SEGREGATION DISTORTION IN DROSOPHILA MELANOGASTER

Genetics ◽  
1973 ◽  
Vol 74 (4) ◽  
pp. 619-631
Author(s):  
D L Hartl
Keyword(s):  
Drosophila Melanogaster ◽  
Segregation Distortion ◽  
Mature Sperm ◽  
Temperature Sensitive ◽  
Short Time

ABSTRACT The recovery of the SD chromosome from a heterozygous SD male increases with brood. This is independent of the age of the female, occurs during the time the sperm are stored in the females, disappears when the segregation distortion is suppressed, and is temperature-sensitive-temperature shocks above or below 25°C applied to the mature sperm both tend to accelerate the increase in the recovery of SD. All this suggests the existence of a class of sperm affected by SD in which the sperm are able to fertilize eggs for a short time following ejaculation but become dysfunctional thereafter.

A Model of Wheat Grain Growth and Its Applications to Different Temperature and Carbon Dioxide Levels

1995 ◽  
Vol 22 (5) ◽  
pp. 843 ◽  
Author(s):  
YP Wang ◽  
RM Gifford
Keyword(s):  
Growth Rate ◽  
Grain Growth ◽  
Temperature Response ◽  
Rate Sensitivity ◽  
Temperature Sensitive ◽  
Potential Growth ◽  
Carbon Supply ◽  
The Difference ◽  
Carbon Dioxide Levels ◽  
Kernel Growth

Kernel growth after anthesis is simulated as a function of the potential kernel growth rate, current photosynthate production and mobilisation of stored reserves. The potential growth rate of the kernel is simulated as two temperature-sensitive processes, cell production and cell growth. The difference between the potential and actual growth rates of the kernel depends on the carbon supply to the free space of the kernel endosperm, while the carbon supply is itself affected by the actual kernel growth rate. Sensitivity analysis showed that the growth rate of the grain per plant is most sensitive to the potential growth rate of the kernel and number of kernels per plant. This model is able to simulate the observed rates of grain growth and leaf senescence from anthesis to physiological maturity for wheat plants grown in two CO2 concentrations. The simulated temperature response of grain growth agrees well with the experimenal observations.

Sign in / Sign up

Export Citation Format

Share Document