AGBT Flashback: Scale Biosciences’ QuantumScale

Back at AGBT two months ago, Scale Biosciences CEO Giovanna Prout was kind enough to spend thirty minutes of her hectic schedule with me discussing Scale's QuantumScale technology, which embarrassingly I've let those notes be sucked into a maelstrom of procrastination.  I was reminded of my delay by the announcement this week of Scale partnering with the Chan Zuckerberg Institute (CZI) to apply the technology to CZI's "100 Million Cell Challenge" and planned "Billion Cells" single cell expression profiling projects.  The QuantumScale technology is now fully commercially available.

QuantumScale has eye-popping specs.  It is possible to profile 4 million cells in a single experiment, with those cells divided among up to 9216 samples using ScalePlex technology, which I covered last June.

Scale has partnered with Ultima to enable Ultima indexing kits enabling native Ultima libraries, rather than requiring a conversion step.

A quick review: Scale's approach to single cell profiling avoids any specialized encapsulation equipment ala 10X Genomics by fixing cells so that the cell remnant serves as the addressable unit for indexing reads.  After labeling, pooling a sample and then splitting it again enables combinatorial barcoding.

Library preparation starts with the option of using ScalePlex to index multiple samples.  Fixed samples then are processed with reverse transcriptase and indexed on the first barcoding plate.  The entire set of indexed samples is then pooled and added to the QuantumScale barcoding plate.  QuantumScale, as I covered in September, doesn't just add a well=specific barcode to each new split of the pool, but instead each well has the capability to index at much higher, well, Scale.  In the Fall Prout was keeping quiet about the exact means QuantumScale used to achieve this, but at AGBT she revealed it relies on indexing beads - 800K per well.  The entire workflow can be completed in a day and a half.  And she is confident the technology can go to even higher levels of indexing; they just need sequencing costs to drop further to enable such plans.  Though right now the cost per cell is quite good - library prep costs of 0.8 cents/cell for 4M cells or 1.0 cents per cell for 2M cells or just $5K all-in to profile 84K cells . She also noted the entire protocol - including the microbeads - is very friendly for liquid handling robots. 

Prout also mentioned that Scale is developing a probe-based workflow for Formalin Fixed Paraffin Embedded (FFPE) samples, the dominant sample type of large tissue archives but also the nightmare of molecular profilers as the FFPE preparation process and the deparaffinization tend to both damage and break any nucleic acids.  It actually could be worse: very early FFPE protocols used unbuffered formalin and tended to completely destroy nucleic acids.   

I can still remember the first stirrings of single cell sequencing about a decade and a half ago, when it truly meant "single cell sequencing" - data was generated for individual cells in wells.  We're so spoiled in genomics by routine exponential climbing of the price/performance curve, but its still astounding to contemplate profiling 4M cells and potentially dividing that largesse over a matrix of over 9K different conditions and replicates.  But that is the corollary of those fantastic growth curves: what is barely imaginable today will be fodder for proof-of-concept in a couple of years and then routine a decade later.  And with the growing power of machine learning models, the demand for such ginormous datasets seems to be on a nearly vertical upward curve.  QuantumScale is emblematic of such growth of genomics capabilities, now we can sit back and see what biological insights tumble forth from the experiments it enables.