2023 Year in Review
Construction ends. The search begins.
2023 was NewLimit’s first full calendar year of operations.
A few highlights from the year:
50X more reprogramming factor sets tested in partial reprogramming experiments than the field has explored cumulatively
20X increase in the signal-to-noise of our pooled screen demultiplexing assay
7X the number of factors we can deliver to human cells
2X the number of NewLimit team members (12 -> 24)
+3 functional assays to discriminate human T cell age
+2 metrics where our in silico reprogramming models surpassed state-of-the-art
Writing epigenetic states
In order to discover partial reprogramming factors, we first have to deliver these factors to old, human cells alongside the command-and-control machinery that allows us to turn them on and off. Our team spent the year’s opening months to make this aspiration a reality.
Delivering transgenes to real cells from human donors is a known hard problem that has plagued scientists and drug developers for decades. Most large scale genetic screens have avoided solving it altogether by restricting their experiments to cancerous cell lines that are eager to take up foreign genetic material. Our work requires more than just a passable solution to this problem. We need to get combinations of reprogramming factors into old cells, not just one at a time, and we need tight control over expression of those factors.
Our team was undeterred by this challenging history and iterated across dozens of delivery chemistries on our way to a solution. We turned our main conference room into a war room and treated each new piece of data like a dispatch from the frontier. After months of concerted effort, we had built tools that achieved all the metrics we needed for high performance discovery screens and more. We also uncovered previously unknown “rules” of the molecular systems we employ that have enabled new designs in the months since.
Reading designs from nucleotides
The classic way to test many partial reprogramming factors would be to put each unique combination into old cells in separate test tubes, then measure what happens. This encodes the design of the experiment in physical space. This would limit the number of factor sets we could test to the number of test tubes we could line up and manipulate in the lab.
NewLimit’s Discovery Engine instead delivers reprogramming factors to a pool of old cells all at the same time. The stochastic nature of life ensures that each cell randomly receives a different combination of factors. In order to figure out which factors each cell receives, we pair them with nucleic acid barcodes that we can measure later. Rather than encoding the design in physical space, we encode it in nucleotides.
Analyzing these complex experiments requires us to read these barcodes with high fidelity alongside a measurement of the reprogramming effects that we capture with single cell genomics. Any barcode that isn’t detected properly represents an injection of noise and inefficiency into our experiments.
At the beginning of the year, the best methods available for our system detected somewhere between half and three-quarters of the barcodes present in each cell. Our team combed the scientific literature for tricks to improve performance – step by step, stacking one trick on top of another, a series of small improvements compounded to achieve a detection sensitivity >95% and specificity >99%. The overall signal to noise ratio of this read-out improved >20X from January to December.
Our team further took this chemistry and developed a new sequencing technology we call pxbc-seq. To our knowledge, this technology is capable of measuring these “perturbation (px) barcodes (bc)” at single cell resolution with higher fidelity and lower costs than ever before. This technology unlocks larger, selection-based screening experiments that will allow us to test 10^4 reprogramming sets in a single dish.
We believe these chemistry improvements uniquely enable us to test more combinations of reprogramming factors than has been possible previously.
Revving the Discovery Engine
Together, these molecular tools allowed us to execute the largest partial reprogramming experiments in the world, to our knowledge. In July, we executed the first experiment to test more than 100 combinations of partial reprogramming factors. In October, we completed the first experiment that tested more than 100 unique factors. In December, we completed the first screen that tested more than 1000 factor combinations.
To our knowledge, the partial reprogramming field had tested <20 combinations of factors prior to NewLimit’s founding. The largest single experiment tested 16 sets. We can now test nearly two orders-of-magnitude more sets in a single experiment than was possible at the beginning of 2023.
Each of these discovery screens has allowed us to accumulate a large data corpus of partial reprogramming effects to enable our predictive modeling efforts.
Predicting reprogramming outcomes in silico
No matter how sophisticated our experimental tools, we will never be able to test all of the reprogramming factor sets that are possible. There are simply far too many combinations to explore exclusively in the world of atoms. To help us search this massive space of possibilities, NewLimit is developing in silico reprogramming models to predict the effect of partial reprogramming interventions in the world of bits.
Our growing data corpus enabled us to build better models than ever before in 2023. Our in silico reprogramming model takes as input a set of reprogramming factors and a starting cell state, then predicts the phenotype that results from partial reprogramming. Our models now explain a great deal of the variation we’ve observed and, to the best of our knowledge, achieve state-of-the-art performance.
We’re now guiding our future experiments using these models alongside the judgment of our scientists.
Validating therapeutic utility
Our Discovery Engine reveals partial reprogramming factors that make old cells look like young cells based on their molecular phenotype. Developing therapeutics requires us to make old cells act like young cells, performing their obligate functions more effectively.
Our Immunology team has been heads-down throughout the year implementing a suite of functional assays that can distinguish functional differences between young and aged human T cells, then determine if those functions are improved by reprogramming. In January, we had 0 functional assays running and no real ability to measure the impact of our reprogramming interventions beyond apparent phenotypes.
By December, our team had implemented a half-dozen assays for T cell function that measure everything from a cell’s ability to sound the alarm on an infection, to the potential of each cell to coordinate a humoral response. By combining a few of the assays, we have begun to tell old and young T cells apart based on their functions, as well as their phenotypes.
As our Discovery Engine begins to emit promising interventions, our team is now prepared to test them with rigor.
We’ve built the Discovery Engine we first envisioned at NewLimit’s inception. We’re now in a position to run the Engine and make discoveries to drive our therapeutic programs. Each month, we grow increasingly confident that age is reversible.
We’re merely at the beginning of a long road to new medicines, but we take pride in how rapidly we’re accelerating. Come join us!