One-by-One and All-at-Once: The Future of Cellular Phenotypic Screening

As scientists, we’re often subjected to certain stereotypes. We’re assumed to be smart and nerdy; we work long hours, wear lab coats, and obsess over data. Some or all of these traits and behaviors may ring true at a population level, but for individual scientists they don’t always stack up, as a wide variety of individuals make up the scientific community and those individuals often change behavior over time. The same disconnect applies to cells. We assume that the average phenotype is representative of all of the members of a population, but too often it is not. We really need to perform longitudinal phenotypic tracking at the single cell level to refine biological understanding. Unfortunately, that’s easier said than done.

Most biological processes are dynamic and unsynchronized. So, while we can expect the total biological system to respond in a certain manner, the data often represents a distribution of events occurring at a given timepoint and at the individual cell level. Individual cells typically interact with stimuli at different times and to differing degrees dependent on their activation states, localization, and gene expression patterns. As a result, studying cell properties in bulk or at a single timepoint often misses and misrepresents the underlying biology.

Currently, a wide variety of technologies are utilized by scientists in an attempt to define phenotype distributions within a given population. These often include time-consuming combinations of multiple techniques to piecewise-assemble the required information: cell lysate ELISAs to detect intracellular protein expression, FACS to resolve surface protein expression, microscopy imaging to assess cell behavior and morphology, and single cell RNA-Seq to collect single cell level gene expression data. Furthermore, many of these techniques provide only a static assessment that makes it difficult to determine whether observed differences reflect distinct biology or simply different cell states within the same biological process. Lastly, many of these techniques modify or destroy the cells during analysis. This means that these disparate measurements must be made on different cells, preventing scientists from directly connecting phenotype to gene expression within one individual cell. While data integration strategies may provide some new information, the cellular “reality” often remains elusive.

For all these reasons and more, Berkeley Lights’ platforms may be the next frontier in understanding complex cellular behaviors. These platforms are designed to help scientists capture refined, comprehensive single cell data that tracks phenotype and function over time with a direct correlation to gene expression.

Berkeley Lights’ platforms feature an OptoSelect™ chip that uses light to automatically move individual cells into discrete, nanoliter-sized NanoPen™ chambers that are ~100,000 times smaller than a microwell. The microfluidic design permits precise control over temperature, gas flow, and media perfusion, thereby allowing cells to be simultaneously cultured in thousands of pens. Cells can be cultured individually or in tandem with one or more additional cells to survey interactions. Cells are continuously imaged and monitored throughout the culture period, allowing users to track cell morphology, motility, and proliferation in bright field. By introducing fluorescent reagents, cells can also be assayed for cell surface markers, protein secretion patterns, and intracellular processes in real time.

Figure Caption: OptoSelect Chip and NanoPen chambers facilitate functional analytics of thousands of individual T-cells by simultaneously measuring cytokine release (IFN-gamma) and T cell surface protein expression (CD137 and CD8) in a single experiment.

Using the same NanoPens, assays can be performed on individual cells to screen additional phenotypes using up to four common fluorescence channels. This opens the door to an incredible range of options. For example, the technology can be applied to access phenotypes like cell surface protein markers, real time IgG/cytokine secretion, live/dead distributions, cell-cell interactions, cross-species antibody binding, and antigen recognition. With the addition of technologies like reporter cells and chemical probes, the number of potential assays expands rapidly, all of which are monitored over time within the chip.

This continuous data collection allows longitudinal phenotypic tracking with minimal input from the user, creating a “movie” rather than the static “snapshots” provided by earlier combinatorial approaches. This deep profiling captures incredibly detailed cellular/clonal “fingerprints” that can reveal previously hidden nuances. Going further, the optic control within these chips is used to extract specific cells of interest from individual NanoPen chambers for export to well plates for downstream RNA sequencing. This provides a direct connection between a specific cell's phenotype and function to its gene expression profile. Already, Berkeley Lights’ platforms are being utilized in longitudinal phenotypic screening studies by research groups advancing antibody discovery, cell line development, synthetic biology, T-cell receptor discovery, and CAR-T therapy.

Major advances in our understanding of biology are often preceded by the arrival of groundbreaking methods and instruments. Berkeley Lights’ new platforms generate deep profiles of individual cell phenotypes and functions that can then be linked directly to gene expression. This technology is the first step to unlocking exciting new advances in cell and gene therapies, protein therapeutics, and more.

Author Information: Mark White, Ph.D., Sr. Director, Marketing, T Cell Platforms Berkeley Lights