100 Million Cell Challenge Expands Single Cell Transcriptomics

Expanding single-cell sequencing studies can help scientists discover rare cell types, better understand disease states, and track cellular changes over time. However, processing, analyzing, and analyzing vast numbers of single cells is expensive, time-consuming, and labor-intensive.

To remove the barriers associated with scale-up, Scale Biosciences 100 million cell challengeThey, along with several other companies and organizations, have pledged to subsidize high-profile single cell research. Winners will be able to leverage cutting-edge technology to sequence and analyze more cells than ever before. In this innovation spotlight, Giovanna Prout We discuss the motivation for developing this challenge to support biomedical research at the single cell level.

What prompted you to develop this challenge?

We thrive on the success of the global scientific community in discoveries in biology. We wanted to provide access to a new, impactful tool that could spark ideas for large-scale single-cell transcriptome studies without having to worry about implementation and cost burden. The challenge was also inspired by the intention to showcase the community of industry partners who can work together to make such a program possible. Our partnerships with the Chan Zuckerberg Initiative (CZI), Ultima, NVIDIA, and Bioturing allow us to offer challenge winners and non-winners free or reduced costs to run their ambitious projects.

What currently limits single cell research?

Single cell research has historically been limited by technological limitations, cost and lack of flexibility in how studies are designed. A technology that emerged almost a decade ago is reaching the limits of its capabilities. Scale Biosciences is here to take the lead and enable single-cell experiments at an unprecedented scale by commercializing technologies designed for ease of use without sacrificing performance or reproducibility. For example, the new QuantumScale RNA platform allows processing of up to 2 million cells or nuclei with the flexibility to accommodate one to several thousand samples or conditions in an easy and efficient workflow that takes just 1.5 days. We’ve also priced it so researchers can scale up their experiments dramatically. The cost is less than 1 cent per cell, or $100 per sample.

Why is scale-up so important in single cell research?

This is a very important question because we know that more is not always better. But in this case, yes! Human development, health, and disease are incredibly complex. To understand this complexity, further studies incorporating more diversity, including age, ancestry, gender, and sample type, are needed. Additionally, scaling up experiments allows more conditions and replicates to be run at once, facilitating large-scale and complex genetic screening in drug development for faster and more robust target selection and validation. AI-based models are also being trained and validated for predictive science, but these models need to be fed much more diverse data. These themes are reflected in the projects selected to receive full grants from the 100 Million Cell Challenge.

Why did you choose 100 million as your target number?

When we started this project, we thought 100 million cells was ambitious. Nothing like this has ever been done before. But the scientific world is pretty amazing. It showed how much pent-up demand there is for large-scale projects at the right price. Nonetheless, we believe we are only scratching the surface of what researchers will do with tools like ours.

What were the key parameters you were looking for in this proposal?

We were looking for projects that had the potential to impact human health. Projects worth 50 million cells selected to receive full grants included projects focused on four areas of biomedical research:

• Global health equity: research across continents and diverse populations by age and ancestry.
• Disease characterization: Temporarily observe large numbers of patients and tissues to fully understand disease-specific mechanisms.
• Cancer Biology: New Approaches to Understanding Treatment Response
• Therapeutic Innovation: New Platforms for Disease Disruption and Drug Development

How did researchers react to this opportunity?

We have seen a tremendous response to this program, with a total of one billion cell projects submitted by researchers in 27 countries. Many researchers are studying important challenges in global health. We received over 140 unique proposals.

How has the challenge evolved over time?

This challenge requires unprecedented levels of industry collaboration. We initially partnered with Ultima Genomics and NVIDIA to announce a program to grant grants to projects worth 100 million cells. CZI then joined, adding new features to the program and securing the resources to fully fund research equivalent to 50 million cells. The overwhelming response led Bioturing to join, and the partners collectively agreed to support research on more than 600 million cells by extending partial grants to all projects that meet certain eligibility criteria.

What was the final result of this challenge?

We presented our fully subsidized project at the American Society of Human Genetics meeting in Denver in November 2024 and look forward to receiving samples from program participants and returning data on hundreds of millions of cells.

What are some of the winning projects?

Selected projects span a remarkable range of applications, from expanding the first global atlas of pediatric health to examining population-specific differences in cancer outcomes.

Below is the full list of winners.

• Federico Gaiti, Princess Margaret Cancer Center: Identification of molecular dependencies in glioblastoma cells involved in neuronal crosstalk
• Caleb Webber, Dementia Research UK: Zebrafish forebrain disease modeling
• Sophia George, University of Miami: Cancer patient cohort tissue and PBMC samples from the African Caribbean Single Cell Network
• Kevin Matthew Byrd, Virginia Commonwealth University: Mapping the Pediatric Suction Interface at Single Cell Resolution
• David van Heel, Queen Mary University of London: Deep omics of South Asian populations to improve the health of communities in the UK and around the world
• Tom Taghon, Ghent University: Molecular drivers of human T cell development
• Drew Neavin, Garvan Institute for Medical Research: Identify patients at risk for drug-induced cardiotoxicity
• Luis Barreiro (University of Chicago): Uncovering immune variations in diverse populations
• Barbara Treutlein, ETH Zurich: Predictive modeling of cell state-specific responses to small molecule perturbations in human organoids
• Jack Lewis, Allen Brain Science Institute: Sympathetic Nervous System Atlas
• John Tsang, Yale University/Chan Zuckerberg Biohub New York: Detoxifying the immune health of populations around the world.
• Konstantin Chuana (MIT): Protein platform to perturb human PBMCs with transcriptome readout
• Christine Disteche, University of Washington: Single-cell transcriptome analysis of sex differences in normal human development and genetic conditions with abnormal sex chromosome numbers
• April Foster, Wellcome Sanger Institute: Disturbing signals for understanding human development.