UQ RNA research members

Our lab uses genetically modified mice, and in vitro motor neuron culture systems to investigate these issues.  Details of our recent work and future direction are given below.  

We have shown that TDP-43, a protein involved RNA metabolism and transport, is capable of binding to mRNAs that encode for proteins needed for synaptic transmission such as Syntaxin, Synaptophysin, and voltage gated Ca2+Channels (Narayanan et al, 2012 ALS). Recently, we have shown when this protein is mutated in motor neurons that have been subjected to stress, mutated TDP-43 but not normal TDP-43 is translocated to stress granules.  This translocation stalls mRNA translation (Ding et al., 2021 Front in Cell & Dev Biol. 9:611601).  

 We have recently established human motor neuron muscle – 2D microfluidic system and are intending on using this system to look at activity dependant transport and translation of pre-synaptic mRNAs.  Induction of motor neuron activity in these systems will be via optogenetic and or chemogenetic activation of transfected human stem cells that will be induced into upper and lower motor neurons. We also intend to develop mouse models whereby we can module motor neuron activity output – optogenetic (acute activation) and chemogenetic (chronic). To investigate these issues in an intact neuromotor system.   

Expertise: Long noncoding RNAs and biotech

The human genome expresses vast numbers of noncoding RNAs (ncRNA) that fulfill diverse roles in gene regulation, cell biology, development and human disease. These roles are usually mediated by sequence motifs and secondary structures that are bound by proteins and can regulate epigenetic, transcriptional and translational pathways. These functional domains can be optimised and engineered into RNA devices that are commonly used in synthetic biology. We propose that natural ncRNAs comprise a promising basis for the discovery and development of RNA therapies to treat human disease. Accordingly, the Mercer laboratory is focused on the rational design and assembly of synthetic RNA therapies and biotechnologies. Our laboratory has capabilities in the computational design of synthetic RNAs tailored according to precise custom requirements, enzymatic DNA synthesis to build genes, genomes and libraries, and the in vitro manufacture of high-quality RNAs for in vivo therapeutic applications.

Expertise: lncRNA, circRNA

The Wolvetang group at AIBN-UQ has a longstanding interest in understanding the roles of non-coding RNAs in the human brain. We identified the first two neuronal activity dependent LncRNAs in the brain revealing that NEAT1 is responsive to neuronal activity and hyperactive in epilepsy models (Barry et al. Scientific Reports. (2017) Jan 5;7:40127, highly cited paper) and linking GOMAFU to schizophrenia (Mol.Psych. (2014) Apr;19(4):486-94.), and wrote a highly cited review paper on the subject (Briggs et al Neuron (2015) 88(5), 861-877). Our expertise lies in genome editing of human patient specific pluripotent stem cells and the establishment of human brain organoid models that are extremely well-suited for interrogating the function of coding and non-coding RNA species in human brain development and disease or for testing of RNA-based therapeutics. We further have expertise in interrogating the transcriptomes of neural cell types in human brain organoids via scRNAseq or through in situ detection of RNA species with RNA scope, and have established high density multi electrode array based methods that are able to quantify neuronal activity and connectivity in our human cellular model systems. We have developed a particular interest in exploring the functional roles of circRNAs at the synapse and in evaluating their potential as cell type specific biomarkers of disease and have recently started to use our models to explore the impacts of viral pathogens such as ZIKA virus (Slonchak et al BioRxiv (2021) https://doi.org/10.1101/2021.05.18.444753, Setoh et al  Nature Microbiology (2019) May;4(5):876-87), and COVID19 (paper in prep) on the human brain, providing novel opportunities for testing of RNA-based therapeutics.

Expertise: Spatial transcriptomics

Nguyen group is investigating neuroinflammation and cancer ecosystem by integrating advanced transcriptomics technologies and machine learning analyses. The group is pioneering the applications of spatial transcriptomics and single-cell sequencing to study transcriptional regulations at cellular resolution and within physiological tissue context.

For technology applications, the group has developed advanced sequencing approaches to study the transcriptome. We have established a low-cost and high-throughput sequencing protocols to detect long non-coding RNA, by developing an improved version and the first application of Capped Analysis of Gene Expression (CAGE) in Australia. We invented a new way to capture and quantify rare, functional small RNA (Nguyen et al., Nat Protocol, 2018). The method was applied to identify a new class of small RNA needed for DNA damage repair (Rossiello et al., Nat Communications, 2017). Recently, using single-cell RNA sequencing (scRNAseq), we constructed a comprehensive single-cell immune atlas of spinal cord injury, finding differential responses across time and space (Manuscript in preparation). We pioneered spatial transcriptomics sequencing (STseq), a method to profile the whole transcriptome of thousands of tissue regions, while preserving tissue morphology. We produced the first STseq data set of a traumatic brain injury model, confirming the spatial enrichment of activated astrocytes in the hippocampus region during injury repair (Willis et al, Cell, 2020). For patient samples, our lab developed a protocol for performing spatial sequencing of formalin fixed tissue sections (FFPE), including those with partially degraded RNA. The FFPE spatial method opens the potential for studying spatiotemporal changes in a vast collection of clinical samples.

For data analysis, the group has developed advanced computational and statistical methods to analyse genomics data. We have produced eight software programs and a range of analysis pipelines. We created two pioneered spatial analysis programs widely used by researchers worldwide for automated cancer cell identification (Tan et al., Bioinformatics, 2019 - SpaCell, >5000 downloads) and cell-type, cell progression and cell-cell interaction spatial data analysis (Pham et al., 2020, bioRxiv125658 - stLearn, >20,000 downloads). The analyses have found new classes of cancer markers that involve cellular phenotypes such as cell shape (Bioinformatics, 2019), cell-cell interaction (Pham et al., 2020, bioRxiv125658; Tran et al., 2020, bioRxiv290833), and spatial distribution (Tran et al. J Immunother Cancer, 2020; Artificial Neural Network, 2020). In addition, we demonstrated the successful combination of histological images with sequencing data in a model to improve the accuracy of the cell classification accuracy in the brain and cancer (Tan et al. Bioinformatics, 2019; Pham et al., 2020 bioRxiv125658) and to study transcriptional regulation specific for each anatomical region across the tissue (Pham et al., 2020, bioRxiv125658). 

Expertise: Clinician researcher-neurologist with a special interest in epilepsy

Neurological disorders are a major cause of death and disability in our society. Of greatest concern is the absolute increase in disability-adjusted life years for neurological conditions over 15 years (2003-2018), highlighting the imperative need for new therapeutic strategies such as RNA therapeutics.

Our research focus is to move from symptomatic treatment for patients, which occurs in a reactive fashion, to a more proactive treatment approach of developing innovative therapeutic strategies based on the underlying pathology. RNA biology holds great promise for better understanding the cause and enabling the development of novel therapeutic targets, to improve the outcome of neurological disorders.