Mtakai Ngara

Current position

Posstdoctoral researcher

Current project

Every cell is unique and generates distinct molecular response(s) in disease. Understanding these molecular perturbations at single cell resolution is critical in unravelling complex, yet important diseases such as type 2 diabetes (T2D).   My main focus will be to identify and functionally validate networks of genes that exhibit altered synchronization in T2D in a cell type-specific manner. I will use existing islet single cell RNAseq data sets and participate in the generation of new data sets. Functional validation will include multiple CRISPR mutations in cell lines followed by scRNAseq, as well as PatchSeq experiments.  As a side project I will in a collaborative effort profile distinct cell subpopulations within the small intestines with the goal of describing how they are perturbed in T2D. This has the potential to enhance our molecular understanding of the disease and generate novel targets in T2D. 

Background

After completing my undergraduate studies in Biochemistry at Egerton University (Kenya), I pursued an MSc. Bioinformatics at University of Manchester (UK, on a distance learning scholarship) then joined Rickard Sandberg group at Karolinska Institutet for a PhD in Medical Science. Here, I mainly worked on applying both computational and single-cell RNA sequencing (scRNA-seq) methods in understanding the development of Plasmodium falciparum during the blood stage of malaria infection. Additionally, I evaluated the impact of six prominent scRNA-seq protocols and key computational parameters adopted in scRNA-seq workflows for subpopulation discovery wtihin homogenous cells (mESCs). In collaboration with Sten Jacobsen lab at Oxford, we characterized the transcriptional profile of cancer stem cells in patients having moderate to severe Myelodysplastic syndrome.   
Over the years, I have gained competence in gene expression analysis at population and single-cell level. I have hands-on experience running Smart-seq2 protocol, one of the most popular scRNA-seq methods that enables full polyA+ transcript profiling.  

I look forward to applying these technologies to T2D research and working in close collaboration with different teams at LUDC!