Interview: Single-cell nanopore sequencing allows high-throughput multiomic analyses of cellular diversity in disease

Date: Thursday 29th August 2019

Time: 4pm BST/11am EDT/8am PDT/1am Sydney

Speaker: Ghamdan Al-Eryani, Garvan Institute of Medical Research

Ghamdan Al-Eryani is currently completing his PhD in the Tumour Progression group located at the Garvan Institute of Medical Research in Sydney, Australia where he is developing and implementing single-cell technologies to understand how the immune system works in cancer. Ahead of his webinar on Thursday 29th August, we caught up with Ghamdan to discuss his work and the impact whole-genome sequencing and single-cell methodologies is having on our understanding of cancer and the immune system.

What are your current research interests?

At the moment I’m working on single-cell methodologies, because I’m really interested in answering questions on tumour immunity and systems immunology but as we don’t have the methods, I’ve gone more into the deep end of coming up with new tools to answer these questions.

What first ignited your interest in transcriptomics and the immune system?

It started off when I was doing my honours degree and one of the first single-cell high throughput papers came out – it hit me just how much information is contained in each cell. Just like when we try to study the demography of population, while it seems easy to make everyone into a number, every individual is important, and so is every cell, and we’d previously been clumping together all of these individual behaviours together. Transcriptomics is the best method to understand each individual cell in the specific moment in systems immunology. However, we are getting better at multi-modal information pulling, so with the single cell platform we can now pull a few of the proteome using DNA barcode anti-bodies, along with the transcriptome.

How is long-read sequencing changing the study of genomics, transcriptomics and immunology? How has it benefited your work?

There are currently a lot of limitations in the way we are trying to understand how cells are interacting with each other, in cancer or whatever disease you’re interested in, because at the moment when you describe a cell it’s purely based on the quantification of a gene. So, for example in CD8 T-cells, you’re calling it CD8 because a certain amount of genes are more expressed than the CD4. But you’re actually not looking at the sequence information - there’s a lot of evolutionary aspects that have been fundamental to developing an immune system, that we aren’t actually able to pull out. We can just state cell type, or gene counts. One of the reasons people have been doing that is because with short-read sequencing you just look at the 150 to 200 base pairs, so you’re not getting the entire full-length transcript, and you’re losing things like isoform expression as well.

I honestly think long-read sequencing has already started a new revolution - we have genomic aberration papers coming out, using long-read sequencing, as well as work looking at T-cell and B-cell receptors, which you wouldn’t be able to study without long-read sequencing. So, I think that being able to get that information will help us understand everything.

What impact could a deeper understanding of the cellular dynamics of cancer have?

Once again, we have to understand the dynamics of cellular behaviour and how cells interact with each other based on gene counts. We see the importance of looking at the genomic feature of the actual nucleotide sequence in cancer, where a founder cell has an initial mutation that then accrues more and more mutations over time. I’m sure there are a lot of cases where the difference between cell ‘A’ and whatever daughter cell downstream is to do with the genomic sequence information, and so to try and understand that we have to look at somatic mutations, which we can do with long-read sequencing. I’m really interested in being able to identify the earliest clone within a snapshot of a single cell capture, so that the earliest genomic cellular clone of a cancer cell would have the least amount of mutations which could be used to track the lineage and how the mutations have accumulated. The recruitment or behaviour of cells surrounding it is really going to be a paradigm change in our understanding of cancers.

What have been the main challenges in your work, and how have you approached them?

The biggest challenge was convincing people that we’re on the advent of long read sequencing following single cell capture, and get on board. Initially, this project wasn’t part of my PhD as my main work was actually looking at tumour immunity in breast cancers. I was a first-year PhD student in my second month and I needed to convince everyone that nanopore sequencing on single cell captures would help me look at the T-cell and B-cell receptor and answer the question of T-cell antigen stimulating mechanics of killing tumour cells. But now I have succeeded in selected enrichment, targeted capture methods and the rewards have been really great.

What’s next for your research?

Applying single cell nanopore sequencing to anything I can get my hands on! I’m really interested in breast cancer and melanoma and we’re going to try to use the technology to try to understand the effects of immunotherapy. But also, further developing and improving the bioinformatic pipeline of MuSeq, which stands for ‘Mutation Splicing and Expression Sequencing’. The informatics has been a bit challenging, in that how do we make this more cost effective – developing a method is nothing if you don’t make it accessible to everyone. So that’s something I’m going to be spending a lot of time on as well.