Diving into Spatial Omics: Field Notes from My First Summit

I’m starting this blog to share my thoughts and experiences as an MS student trying to find my footing in the field of bioinformatics. As the name — which I’m actually quite proud of — suggests, these are my unfiltered and potentially unmapped thoughts on whatever topic happens to excite me any given week. The reason I'm blogging publicly is to motivate myself to explore topics I enjoy, build a professional presence in bioinformatics, and keep a personal log of experiments and ideas to reflect on and share. Hopefully, the name Low Coverage Thoughts will one day feel like an ironic nod to these early steps in the field.

This past week, I had the pleasure of attending the 3rd Spatial Biology for Drug Development Summit. It was my first conference in Boston, and overall it was a great experience — not only free to attend, but also with free food (which means a lot for a grad student). I came in with only my own research and no hands-on experience in spatial transcriptomics, proteomics, or any of the other spatial omics being marketed. It felt a bit like a language immersion experience: dropping yourself in a new country armed with only a couple months of Duolingo and trying to learn from the source. And I’d say it worked — by picking the brains of all the amazing professionals there and listening to their talks, I now have a better sense of how spatial omics is being applied, as well as some of its challenges and limitations.

If I had to complain about one thing, it would be that instrument companies are reluctant to give specific best-use cases for their products, since everyone wants to claim they have the “do-it-all” sequencing technology. Trying to understand the molecular biology behind all the different methods was intimidating at first. So for this part of the blog, I want to focus on how the scientists I met at the conference actually use them. The two main classes of spatial transcriptomics methods are ISH (in-situ hybridization) and ISC (in-situ capture). If you think of these methods like tools in a photographer’s bag, ISH and ISC are like different lenses. ISH is your zoom lens: you choose which genes to focus on, but the results are high-resolution and accurate. ISC is your wide-angle lens, capturing all genes in the sample, but with limited resolution. Because of these trade-offs, biopharma companies tend to use ISC for discovery or preliminary tests, and ISH for gathering more conclusive evidence for potential targets. Interestingly, all the biopharma employees I spoke with used only one or the other. I haven’t yet drawn conclusions about why, but it’s something I wanted to note here.

One discussion that came up more times than I can count was the idea of establishing more collaborative consortia between developers and users of spatial omics technologies. I see the benefits — broader adoption and more standardized workflows — but my initial “low coverage thought”™ is that it’s easier said than done. I’m no businessman, but there seems to be a power struggle among the major players in the spatial omics market. From conversations with employees at Novartis, Pfizer, and others, 10x Visium seems to be the most commonly used tool for transcriptional profiling, likely because 10x is already a major player in single-cell sequencing. However, with ongoing patent disputes and stock fluctuations, the door may still be open for another company to take hold of this emerging market. Perhaps collaboration and innovation will ultimately win out — only time will tell.

To wrap things up, the future of spatial omics looks very promising. The ongoing battle for the golden resolution-to-coverage ratio will likely continue to drive improvements in these platforms. I’m particularly interested in spatial multi-omics approaches that capture proteins and other molecules alongside transcripts (a topic for a future post). On the applications side, spatial omics is already driving major breakthroughs, like the work from Dr. William Hwang’s lab at Mass General Brigham — he gave probably the best research presentation I’ve heard all week. Beyond that, I’m excited to see what spatial genomics can reveal in organogenesis, neuroscience, and regenerative medicine, which I hope to cover in future posts.

All of this makes it an exciting time to be learning, exploring, and writing about bioinformatics.