Mobile Menu

Single cell and spatial technologies

Developments in our technical ability to separate single cells from each other are growing rapidly. Alongside this, sequencing costs are continually falling. As a result, the impact of single cell analysis in transforming our understanding of disease is becoming more apparent. With new technologies and the ever-evolving genomics landscape, it is difficult to stay on top of the latest technologies and even more difficult to know when it is right for a particular research question. So how, and where, should we invest for the next era of single cell studies?

In our recent ‘Single Cell ONLINE’ webinar – Fuelling the Century of Biology with Single Cell and Spatial Technologies – a team of world leaders participated in an interactive panel discussion exploring the current state of single cell studies and what is on the horizon. Our speakers included Carlo Sala Frigerio (UCL), Stefania Giacomello (SciLifeLab), Christophe Fleury (10x Genomics), Florian Baumgartner (10x Genomics) and Wai Long Tam (Flemish Institute for Biotechnology – VIB).

Single cell and spatial technologies 

The single cell and spatial transcriptomics fields are rapidly expanding, and with them the repertoire of available technologies. Single cell measurements can provide a finer-grained picture of complex biology and unmask heterogeneity that is present within our tissues. Single cell techniques are able to dissociate tissues or use liquid samples to look at single cells. Unlike spatial technologies, they are able to associate a single transcript to an individual cell. However, information regarding the positions of these transcripts within the tissue are lost. The relationship between cells and their relative locations within a tissue is important for understanding disease pathology. Spatial technologies look at intact tissues providing a portrait of expression and the location of a mixture of transcripts. Both of these approaches enable different modalities to be used. Therefore, combining these techniques is of particular interest to define the spatial topography of cell type populations.

During the webinar, the panel discussed the various software tools mostly used for their analyses. The panel discussed that 10x Genomics’ Cell Ranger and Space Ranger are the methods of choice for processing single cell and spatial RNA-seq output data respectively. They also agreed that Satija Lab’s Seurat R package is the most widely used tool for analysing single-cell RNA-seq data. They discussed how it provides extensive examples on how to make the most out of the software and also how to analyse the data.

What are the biggest challenges?

The panel engaged in an interesting discussion about the biggest challenges in single cell and spatial research. Frigerio expressed that effectively scaling library preparation and analysis was a challenge. He noted that expanding single cell analysis into the million-cell scale would be very valuable. Additionally, he expressed the need to add other layers of information to the data. For example, using ATAC-seq to obtain information about chromatin modifications. In terms of spatial technologies, Frigerio recognised that the field is maturing quickly with lots of different methods becoming available. However, he emphasised that the instrumentation is not available in every laboratory and the analyses are still in development. As a result, he stressed the value of developing good collaborations with different facilities and individuals with the right expertise. He stated:

“One of the challenges is to form good collaborations with laboratories that can do these techniques and who are experts in it.”

Frigerio continued by highlighting the value of user-friendly interfaces particularly for groups who don’t yet have these collaborations.

Another challenge described by Giacomello was the ability to integrate different data types. She emphasised that enabling effective integration of different data types, such as imaging and sequencing base methods, in a readily available software would be extremely beneficial.

The Future

Naturally the discussion led to the future of these fields and what is currently showing promise. Tam was excited about the potential promise of 3D and 4D technologies. He said that these technologies could be used directly on an entire organ and could provide us with information about the dynamics within tissues during certain processes rather than just a static time point. This was echoed by Giacomello who discussed the importance of spatial omics. She was particularly interested in using these techniques to study metabolites in single cells and to also observe the structure of organelles. For example, combining gene expression at a spatial level with structural information could provide insight into how mitochondria are affected during Parkinson’s disease.

When questioned about using these technologies in a clinical space, Frigerio expressed the importance of developing reliable biomarkers. He described how new biomarkers could identify specific cell types that would enable tailored therapy. The panellists recognised that the obvious value of single cell and spatial technologies in a clinical space is the identification of clonal cells in cancer. They believed that these technologies could replace some existing sequencing approaches for identifying mutations in cancer cells and could also help identify why immunotherapies work in some cancers and not in others. However, Fleury emphasised that “PRICE is the big obstacle!”

They agreed that more targeted techniques would need to be developed that would lower costs and help with precision medicine.

Catch-up on our recent webinar – Fuelling the Century of Biology with Single Cell and Spatial Technologies – on demand now.

Image credit: By taylanibrahim –

Share this article