RESEARCH
Our lab has two overlapping areas of research:
1) To understand the roles that RNA (in particular microRNA) play in neurodegeneration and movement disorders;
2) To exploit RNA biology to develop translational technologies based on novel functional RNA molecules, for disease diagnosis and therapeutics.
To do this, we take a cross-disciplinary approach, combining genetics, biochemistry and chemistry, behavioural assays, high-speed imaging and computational analysis, collaborating closely with computer scientists, chemists and engineers.
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We are currently hiring Postdoctoral Research Fellows and Research Officers to work on funded projects related to RNA regulation, neurodegeneration and therapeutics. If you have a passion for RNA and neurodegeneration and are interested in joining our team, please email Sherry.
RNA IN DISEASE
MiRNA, a class of short, non-coding RNA involved in gene regulation, carry out important functions in many biological systems and are implicated in disease. Through functional screens of miRNA mutants using quantitative phenotyping, and molecular and biochemical characterization of conserved miRNA regulatory pathways, we aim to understand how defects in miRNA biology can lead to diseases like neurodegeneration, tremor and movement disorder.
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I) Tremor
Essential Tremor (ET) is the most common movement disorder, with a high familial risk. The rare risk variants that have been identified account for a small fraction of disease risk, indicating that key causative genes remain to be discovered. We have identified a neuronal population whose function is required to prevent tremor in the fly, and are working to understand their normal function and dysregulation in disease.
II) MicroRNAs and movement disorders
One class of genes that we are interested in are microRNAs, and the targets that they regulate to protect against movement disorder.
Reference:
Aw, S. *#, Lim, KH, Tang, XM, Cohen, SM* (2017)
A glio-protective role of mir-263a by tuning sensitivity to glutamate.
Cell Reports 19(9): 1783–93
*Corresponding authors #Lead contact
RNA TECHNOLOGIES FOR DIAGNOSTICS AND THERAPEUTICS
Besides functioning in gene regulation and disease pathways, miRNA also have emerging roles as clinical biomarkers useful in disease diagnosis. Innovations in techniques to sense and quantify miRNAs may aid research into novel aspects of miRNA biology and contribute to the development of RNA-based diagnostics. By introducing an additional stem loop into the fluorescent RNA Spinach and altering its 3’ and 5’ ends, we generated a new RNA, Pandan, that functions as the basis for a miRNA sensor (Aw et. al., Nucleic Acids Research 2016, PCT/SG2017/050086 2017).
While Pandan exhibits large fluorescent fold changes and is specific for its target miRNA, it was not sensitive enough for detection of miRNA at endogenous levels, as the RNA is not amplified (as is normally carried out in RT-qPCR). Hence, we are developing other RNAs that will work in concert with Pandan to increase detection sensitivity.
We are further developing these molecules for clinical diagnostics for diseases in which RNA serve as useful biomarkers, including COVID-19. We also aim to genetically encode novel RNA sensors in vivo, for drug screening and therapeutic applications.
References:
Aw, S.*#, Tang, XM., Teo, YN*, Cohen, SM. (2016) A conformation-induced fluorescence method for microRNA detection. *Corresponding #Lead contact
Nucleic Acids Research 44 (10): e92, doi: 10.1093/nar/gkw108
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Sherry Aw, Melissa Tang, Teo Yin Nah and Stephen Cohen. A simple one-step real-time molecular sensor for microRNA detection PCT patent application 2018 (US and Singapore) - PCT/SG2017/050086; Singapore provisional patent 2014 #10201601384T - IMC/P/08599/01/SG
MACHINE LEARNING FOR STUDY OF MOVEMENT DISORDER
Movement defects often accompany neurodegenerative diseases, and are used as a basis for diagnosis. Fly models of neurodegeneration also exhibit locomotor dysfunction. To enable detailed behavioural phenotyping in fly disease models, we developed a machine-learning leg tracking method, Feature Learning-based Leg SegmentatIon and Tracking (FLLIT). Using FLLIT to analyse movement signatures of fly models of Parkinson's Disease (PD) and Spinocerebellar ataxia 3 (SCA3), we found that these models exhibit distinct gait signatures that resemble the respective human diseases. We are now using the system to link cellular dysfunction to behavioral outputs, in order to understand the molecular and circuit dysfunctions that underlie disease, including in miRNA pathways.
Reference:
Shuang Wu, Kah Junn Tan, Lakshmi Narasimhan Govindarajan, James Charles Stewart, Lin Gu, Joses Wei Hao Ho, Malvika Katarya, Boon Hui Wong, Eng King Tan, Daiqin Li, Adam Claridge-Chang, Camilo Libedinsky, Li Cheng* and Sherry Shiying Aw*#
Fully automated leg tracking of Drosophila neurodegeneration models reveals distinct conserved movement signatures.
PLOS Biology (2019) 17(6) (View)
*Corresponding authors #Lead contact