Molecular modelling of the links between growth, environment and metabolism using Grb10 knockdown in Zebrafish.
Lead Research Organisation:
University of Manchester
Department Name: School of Medical Sciences
Abstract
The co-ordinated control of growth and metabolism in relation to the environment is an essential feature of living organisms. Characterisation of the interactions between the networks of genes that control these processes allows possible manipulation of these pathways to facilitate both better growth profiles, important for agriculture, and the characterisation of healthy ageing, important for medicine.
We have recently identified GRB10 as an important gene linking growth and metabolism in response to latitude as measured by exposure to summer daylight1. Grb10 is an adaptor protein modulating insulin and IGF-I receptor signalling. We have shown that transient Grb10 knockdown in Zebrafish generates an increase in growth rate with a reduced weight-to-length ratio and that oxygen consumption is increased, implying a "leaner" more metabolically active phenotype. This project will identify the mechanisms through which Grb10 knockdown produces this phenotype and modifies metabolic rate in relation to exposure to light.
This project links in vivo whole animal metabolic respirometry and measurements of growth phenotype with the computational and mathematical analysis of transcriptomic data to understand how periods of growth are co-ordinated with metabolic rate and affected by environmental determinants. The candidate will learn how to use traditional bench skills in molecular biology, in combination with animal handling, to make accurate phenotypic measurements of growth and metabolism using both control and CRISPR modified animals. These observations will then be linked with transcriptomic data using machine learning approaches. Comparisons will be made to available data deposited in databases such as Zfin, Gene Expression Omnibus and ArrayExpress. This project will, therefore, teach the student to "routinely apply computational and mathematical techniques to high-quality quantitative biological data" and how to access and utilise "comprehensive, integrated and interoperable data resources" as required by the BBSRC.
We have recently identified GRB10 as an important gene linking growth and metabolism in response to latitude as measured by exposure to summer daylight1. Grb10 is an adaptor protein modulating insulin and IGF-I receptor signalling. We have shown that transient Grb10 knockdown in Zebrafish generates an increase in growth rate with a reduced weight-to-length ratio and that oxygen consumption is increased, implying a "leaner" more metabolically active phenotype. This project will identify the mechanisms through which Grb10 knockdown produces this phenotype and modifies metabolic rate in relation to exposure to light.
This project links in vivo whole animal metabolic respirometry and measurements of growth phenotype with the computational and mathematical analysis of transcriptomic data to understand how periods of growth are co-ordinated with metabolic rate and affected by environmental determinants. The candidate will learn how to use traditional bench skills in molecular biology, in combination with animal handling, to make accurate phenotypic measurements of growth and metabolism using both control and CRISPR modified animals. These observations will then be linked with transcriptomic data using machine learning approaches. Comparisons will be made to available data deposited in databases such as Zfin, Gene Expression Omnibus and ArrayExpress. This project will, therefore, teach the student to "routinely apply computational and mathematical techniques to high-quality quantitative biological data" and how to access and utilise "comprehensive, integrated and interoperable data resources" as required by the BBSRC.
Organisations
People |
ORCID iD |
| Adam Stevens (Primary Supervisor) |