A Call for Context (in Cell Culture)
By studying how cells coordinate, we can cross the chasm that divides the bench and our bodies.
This is Part 1 in our New Science research series, where our Fellows explain the visions behind their work. This post was written by Diana Leung.
If you put me on a desert island, I would die an early and pathetic death, and I wonder if that’s what happens to cells in culture, to some extent.
Cell culture originated in the 20th century. The initial goal was simple: Make cells viable long enough to study them. And because the cells in our modern labs seem happy enough, the practice hasn't changed much in the last few decades. But a constellation of experiments suggests that a cell’s properties are conditional on context — neighbors and environment — and there is much to explore about how they behave outside of a dish in a lab.
On Change & Identity
Cell culture exerts a slew of selection pressures on living cells. Media and environmental conditions are not neutral. Scientists almost exclusively study a subset of cell types and behaviors that they can reproduce in normal laboratory environments. When you take cells from the body and try to grow them in cell culture, many don’t survive. Those that do survive change with time: Over a number of growth cycles, most primary cells drift from their original identity — properties like stemness, morphology, and gene expression patterns. After a time, they are thrown out, no longer relevant for experiments. Other cells pick up mutations and become immortalized spontaneously. A cell’s identity is fluid, easily deformed by its contextual container, and constantly reacting to the environment.
It’s telling that the cells which prosper most in culture are not cells that are representative of cells in our bodies. The first human cells to successfully thrive in cell culture were unusually aggressive cancer cells taken from Henrietta Lacks in 1951. They’re so well-suited for the lab environment, in fact, that they are often studied accidentally because they contaminate and outcompete normal cell types in vitro. HeLa has grown so distinct from its human origins that it has been proposed to be categorized as its own species, with varying subspecies by lab or region. The robustness and adaptability of HeLa cells that make it a poor team player in the multicellular context are characteristics that contribute to its success in culture.
In an interesting mirror to HeLa cells and the usual negative framing around cancer, some cancers can adapt to welcoming cellular environments, eventually integrating harmlessly into their hosts. For example, a specific type of cancer can merge with mouse embryos to become viable chimeras. There are also neonatal cancers that don’t require medical intervention because they are expected to spontaneously regress. Given sufficient signals/direction, a ‘bad’ cell can integrate into a functional body. On the other hand, stem cells, for all of their therapeutic potential, also drift and accumulate cancer mutations if they are cultured for an extended length of time. They often develop into tumors, too, for lack of sufficient direction. In all of these contexts, the question is less about a cell’s original identity, and more about how they integrate into the larger system.
For multicellular organisms, we ultimately evaluate functionality at the organismal level. Here, every kind of cell plays a role in a larger ecosystem, and the identity of each cell changes as its context changes. To study these cells in isolation destroys the signals that maintain their functional identity. You can have the right parts, but without the right organization and integration, we will see them as a pathology, a cancer. So how can we understand the factors that inform a cell’s identity from first principles? These are the questions that I’m exploring at New Science.
Consider two ways to understand what happens to cells when their neighbors and environments shift: From the top down, or from the bottom up.
Aging is a great example of the former. While working at Yale, I was introduced to epigenetic clocks, which are algorithms that calculate biological age based on how many sites, across the human genome, are covered in methyl groups. This methylation data is used to predict a person’s risks for illness or death, and to devise models that predict age, morbidity, and mortality. Such statistical models are intriguing in their ability to predict high-level phenomena like how people age, when they might die, and whether they’ll get sick. But they are limited in their ability to suggest biological mechanisms.
So I turned to a nascent field called cell systems, which is about understanding how changes in a cell’s multicellular context can shape its behavior; a bottom-up approach. At Boston Children’s Hospital, Xu Zhou’s lab is examining the interactions between macrophages and fibroblasts, two cell types commonly found in mammalian tissues and involved in tissue homeostasis. Zhou previously found that fibroblasts regulate the carrying capacity of macrophages, or how many of these cells can grow in the body. Fibroblasts help to increase macrophage counts during an inflammatory response, and hold it steady at other times. His work offers a template for examining how emergent properties arise from individual parts. When we isolate cells and grow them in culture, we miss these emergent properties entirely.
In Zhou’s lab, I am co-culturing fibroblasts and macrophages and using the tools of RNA-seq and metabolomics to examine the differential expression and phenotype of these cells in monoculture versus coculture. My aim is to study these cells from the bottom up: to explore the emergent properties of mixed cell systems; of how the presence of other cell types influences their behavior. Other scientists, such as Michael Levin and Michael Todhunter, are conducting related experiments to organize normal frog cells into living robots, or to examine the impact of growth media and other culture conditions on cell viability, respectively. Those efforts, too, will significantly improve our ability to predict and manipulate cell dynamics.
A historical, scientific focus on individual cells, and individual genes, has led to impressive accomplishments. We can now induce differentiation of cell types with a specific set of transcription factors, and we can grow organoids that self-organize to recapitulate subsystems. But we do not fully understand the various knobs that we are turning to trigger those behaviors. Expanding the repertoire of cell culture and artificial differentiation, today, more resembles art than science.
I suspect that greater attention on how parts interact as a whole, as opposed to measuring characteristics of parts themselves, will help us grasp those unique factors that inform a cell’s identity. Getting at this ground truth will improve stem cell and regenerative therapies in vivo, as we direct engineered cells to better interact with their neighboring cells.
Biological systems have often been analogized to machines, but it can also be useful to cast multicellularity as a system of coordinating individuals, with the interest of aligning local behavior with global goals. This is why cells in the body parallel individuals in a society. But we’ve only scratched the surface. We will surely uncover more surprising connections when we study cells from the bottom-up, and in their natural context.
Edited by Niko McCarty
Thanks to Oliver Yeung, Brian Toledo, Alexey Guzey, Sasha Targ, Brian Timar, and Steven Elleman for reading.
Cite this essay:
Leung, D. “A Call for Context (in Cell Culture).” newscience.org. 2022 September. https://doi.org/10.56416/021uwn
This is good stuff, thanks. Delighted you are using a cell systems approach! I'm guessing you have probably read Daniel J. Nicholson's paper, Is the Cell Really a Machine? (Journal of Theoretical Biology, 2019). If not, here's a link: https://philpapers.org/rec/NICITC ) Marvellous paper, with some deep insights into how our understanding of cells, and organisms, has been distorted by the lab techniques we have used to study those cells, and by the mechanistic analogies that we tended to adapt as a result of using those techniques. Well worth reading, if you haven't already! Anyway, well done again on this very clearly-written and informative post, and on the excellent and important research you are doing.