A new book by Pulitzer-winning physician-scientist Siddhartha Mukherjee will be released from Simon & Schuster on October 25, 2022.
The DNA double helix is often the image spiraling at the center of 21st century advances in biomedicine and the growing bioeconomy. And yet, DNA is molecularly inert. DNA, the code for genes, is not alive and is not strictly necessary for life. Ought life be at the center of our communication of living systems? Is not the Cell a superior symbol of life and our manipulation of living systems?
A code for life isn’t a code without the life that instantiates it. A code for life must be translated. The cell is the basic unit of that translation. The cell is the minimal viable package of life as we know it. Therefore, cell biology is at the center of biomedicine’s greatest transformations, suggests Pulitzer-winning physician-scientist Siddhartha Mukherjee in his latest book, The Song of the Cell: The Exploration of Medicine and the New Human.
The Song of the Cell begins with the discovery of cells and of germ theory, featuring characters such as Louis Pasteur and Robert Koch, who brought the cell “into intimate contact with pathology and medicine.” This intercourse would transform biomedicine, leading to the insight that we can treat disease by thinking at the cellular level. The slightest rearrangement of sick cells might be the path toward alleviating suffering for the organism: eroding the cell walls of a bacterium while sparing our human cells; inventing a medium that coaxes sperm and egg to dance into cellular union for in vitro fertilization (IVF); designing molecular missiles that home to the receptors decorating the exterior of cancer cells; teaching adult skin cells to remember their embryonic state for regenerative medicines.
Mukherjee uses the bulk of the book to elucidate key cell types in the human body, along with their “connective relationships” that enable key organs and organ systems to function. This includes the immune system, the heart, the brain, and so on. Mukherjee’s distinctive style features compelling anecdotes and human stories that animate the scientific (and unscientific) processes that have led to our current state of understanding. In his chapter on neurons and the brain, for example, he integrates Santiago Ramon y Cajal’s meticulous black ink sketches of neurons into Mukherjee’s own personal encounter with clinical depression. In one lucid section, he interviews Dr. Helen Mayberg, a pioneering neurologist who takes seriously the descriptive power of her patients’ metaphors, as they suffer from “caves,” “holes,” “voids,” and “force fields” that render their lives gray. Dr. Mayberg aims to stimulate patients’ neuronal cells in a manner that brings back the color.
Beyond exposing the insight and inventiveness that has arisen out of cell-based thinking, it seems that Mukherjee’s bigger project is an epistemological one. The early chapters of The Song of the Cell continually hint at the potential for redefining the basic unit of biology as the cell rather than the gene. The choice to center biomedicine around cells is, above all, a conspicuous choice not to center it around genes (the subject of Mukherjee’s previous book, The Gene), because genes dominate popular science communication.
This choice of cells over genes is most welcome. Cells are alive. Genes are not. Letters—such as the As, Cs, Gs, and Ts that represent the nucleotides of DNA, which make up our genes—must be synthesized into a word or poem or song that offers a glimpse into deeper truths. A key idea embedded in this thinking is that of emergence. Whether in ancient myth or modern art, creation tends to be an emergent process, not a linearly coded script. The cell is our current best guess for the basic unit of life’s emergence, turning a finite set of chemical building blocks—nucleic acids, proteins, sugars, fats—into a replicative, evolving system for fighting stasis and entropy. The cell’s song is one for our times, for it is the song of biology’s emergence out of chemistry and physics, into the “frenetically active process” of homeostasis.
Re-centering our view of biology has practical consequences, too, for how we think about diagnosing and treating disease, and for inventing new medicines. Centering cells presents a challenge: which type of cell to place at the center? Rather than default to the apparent simplicity of DNA as a symbol because it represents the one master code for life, the tension in defining the diversity of cells—a mapping process still far from complete in cutting-edge biology laboratories—can help to create a more thoughtful library of cellular metaphors to shape both the practice and communication of biology.
Further, effective problem solving is often about operating at the right level, or the right scale. The cell feels like appropriate level at which to interrogate many of the diseases that ail us, because the senses that guide our own perceptions of sickness and health—the smoldering pain of inflammation, the tunnel vision of a migraine, the dizziness of a fluttering heart—are emergent.
This, unfortunately, is sort of where Mukherjee leaves the reader, under-exploring the consequences of a biology of emergence. Many practical and profound questions have to do with the ways that each scale of life feeds back on the others. In a tome on Cells and “the future human” I wished that Mukherjee had created more space for seeking the ways that cells will shape and be shaped by the future, of humanity and otherwise.
We are entering a phase of real-world bioengineering that features the modularization of cellular parts within cells, of cells within organs, of organs within bodies, and of bodies within ecosystems. In this reality, we would be unwise to assume that any whole is the mere sum of its parts.
For example, when discussing the regenerative power of pluripotent stem cells, Mukherjee raises the philosophical thought experiment of the Delphic boat, also known as the Ship of Theseus. The boat is made of many pieces of wood, each of which is replaced for repairs over the years, with the boat’s structure unchanged. Eventually none of the boat’s original wood remains: Is it the same boat?
Mukherjee raises the Delphic boat in one paragraph at the end of the chapter on stem cells, as a metaphor related to the possibility of stem cell-enabled regeneration in perpetuity. He does not follow any of the threads of potential answers. Given the current state of cellular engineering, about which Mukherjee is a world expert from his work as a physician-scientist, this book could have used an entire section dedicated to probing this question and, importantly, the ways this thought experiment falls apart.
We are entering a phase of real-world bioengineering that features the modularization of cellular parts within cells, of cells within organs, of organs within bodies, and of bodies within ecosystems. In this reality, we would be unwise to assume that any whole is the mere sum of its parts. Wholeness at any one of these scales of life—organelle, cell, organ, body, ecosystem—is what is at stake if we allow biological reductionism to assume away the relation between those scales.
In other words, Mukherjee succeeds in providing a masterful and compelling narrative of the lives of many of the cells that emerge to enliven us. Like his previous books, it is a worthwhile read for anyone curious about the role of cells in disease and in health. And yet, he fails to offer the broader context of The Song of the Cell.
As leading agronomist and essayist Wes Jackson has written, “The sequence of amino acids that is at home in the human cell, when produced inside the bacterial cell, does not fold quite right. Something about the E. coli internal environment affects the tertiary structure of the protein and makes it inactive. The whole in this case, the E. coli cell, affects the part—the newly made protein. Where is the priority of part now?” [1]
Beyond the ways that different kingdoms of life translate the same genetic code, the practical situation for humanity today relates to the ways that the different disciplines of modern life use values and culture to influence our genes, cells, bodies, and environment. It may be that humans will soon become a bit like the Delphic boat, infused with the buzz of fresh cells to repopulate different niches within our bodies, for healthier, longer lives. But in biology, as in writing, a mixed metaphor can cause something of a cacophony. For we are not boats with parts to be replaced piecemeal. And nor are whales, nor alpine forests, nor topsoil. Life isn’t a sum of parts, and neither is a song that rings true.
[1] Wes Jackson, "Visions and Assumptions," in Nature as Measure (p. 52-53).
Avalanche rescue dogs train to find and dig out people buried in snow slides
By the time he is three, Lume, like Huckleberry, will be a fully trained avy pup and will join seven other avy dogs on Breckenridge ski patrol team. Some of the team members, both human and canine, are also certified to work with Colorado Rapid Avalanche Deployment, a coordinated response team that works with the Summit County Sheriff’s office for avalanche emergencies outside of the ski slopes’ boundaries.
There have been 19 avalanche deaths in the U.S. this season, according to avalanche.org, which tracks slides; eight in Colorado. During the entirety of last season there were 17. Avalanche season runs from November through June, but avalanches can occur year-round.
High tech and high stakes
Complementing avy dogs’ ability to smell people buried in a slide, avalanche detection, rescue and recovery is becoming increasingly high tech. There are transceivers, signal locators, ground scanners and drones, which are considered “games changers” by many in avalanche rescue and recovery
For a person buried in an avalanche, the chance of survival plummets after 20 minutes, so every moment counts.
A drone can provide thermal imaging of objects caught in a slide; what looks like a rock from far away might be a human with a heat signature. Transceivers, also known as beacons, send a signal from an avalanche victim to a companion. Signal locators, like RECCO reflectors which are often sewn directly into gear, can echo back a radar signal sent by a detector; most ski resorts have RECCO detector units.
Research suggests that Ground Penetrating Radar (GPR), an electromagnetic tool used by geophysicists to pull images from inside the ground, could be used to locate an avalanche victim. A new study from the Department of Energy’s Sandia National Laboratories suggests that a computer program developed to pinpoint the source of a chemical or biological terrorist attack could also be used to find someone submerged in an avalanche. The search algorithm allows for small robots (described as cockroach-sized) to “swarm” a search area. Researchers say that this distributed optimization algorithm can help find avalanche victims four times faster than current search mechanisms. For a person buried in an avalanche, the chance of survival plummets after 20 minutes, so every moment counts.
An avy dog in training is picking up scent
Sarah McLear
While rescue gear has been evolving, predicting when a slab will fall remains an emerging science — kind of where weather forecasting science was in the 1980s. Avalanche forecasting still relies on documenting avalanches by going out and looking,” says Ethan Greene, director of the Colorado Avalanche Information Center (CAIC). “So if there's a big snowstorm, and as you might remember, most avalanches happened during snowstorms, we could have 10,000 avalanches that release and we document 50,” says Greene. “Avalanche forecasting is essentially pattern recognition,” he adds--and understanding the layering structure of snow.
However, determining where the hazards lie can be tricky. While a dense layer of snow over a softer, weaker layer may be a recipe for an avalanche, there’s so much variability in snowpack that no one formula can predict the trigger. Further, observing and measuring snow at a single point may not be representative of all nearby slopes. Finally, there’s not enough historical data to help avalanche scientists create better prediction models.
That, however, may be changing.
Last year, an international group of researchers created computer simulations of snow cover using 16 years of meteorological data to forecast avalanche hazards, publishing their research in Cold Regions Science and Technology. They believe their models, which categorize different kinds of avalanches, can support forecasting and determine whether the avalanche is natural (caused by temperature changes, wind, additional snowfall) or artificial (triggered by a human or animal).
With smell receptors ranging from 800 million for an average dog, to 4 billion for scent hounds, canines remain key to finding people caught in slides.
With data from two sites in British Columbia and one in Switzerland, researchers built computer simulations of five different avalanche types. “In terms of real time avalanche forecasting, this has potential to fill in a lot of data gaps, where we don't have field observations of what the snow looks like,” says Simon Horton, a postdoctoral fellow with the Simon Fraser University Centre for Natural Hazards Research and a forecaster with Avalanche Canada, who participated in the study. While complex models that simulate snowpack layers have been around for a few decades, they weren’t easy to apply until recently. “It's been difficult to find out how to apply that to actual decision-making and improving safety,” says Horton. If you can derive avalanche problem types from simulated snowpack properties, he says, you’ll learn “a lot about how you want to manage that risk.”
The five categories include “new snow,” which is unstable and slides down the slope, “wet snow,” when rain or heat makes it liquidly, as well as “wind-drifted snow,” “persistent weak layers” and “old snow.” “That's when there's some type of deeply buried weak layer in the snow that releases without any real change in the weather,” Horton explains. “These ones tend to cause the most accidents.” One step by a person on that structurally weak layer of snow will cause a slide. Horton is hopeful that computer simulations of avalanche types can be used by scientists in different snow climates to help predict hazard levels.
Greene is doubtful. “If you have six slopes that are lined up next to each other, and you're going to try to predict which one avalanches and the exact dimensions and what time, that's going to be really hard to do. And I think it's going to be a long time before we're able to do that,” says Greene.
What both researchers do agree on, though, is that what avalanche prediction really needs is better imagery through satellite detection. “Just being able to count the number of avalanches that are out there will have a huge impact on what we do,” Greene says. “[Satellites] will change what we do, dramatically.” In a 2022 paper, scientists at the University of Aberdeen in England used satellites to study two deadly Himalayan avalanches. The imaging helped them determine that sediment from a 2016 ice avalanche plus subsequent snow avalanches contributed to the 2021 avalanche that caused a flash flood, killing over 200 people. The researchers say that understanding the avalanches characteristics through satellite imagery can inform them how one such event increases the magnitude of another in the same area.
Avy dogs trainers hide in dug-out holes in the snow, teaching the dogs to find buried victims
Sarah McLear
Lifesaving combo: human tech and Mother Nature’s gear
Even as avalanche forecasting evolves, dogs with their built-in rescue mechanisms will remain invaluable. With smell receptors ranging from 800 million for an average dog, to 4 billion for scent hounds, canines remain key to finding people caught in slides. (Humans in comparison, have a meager 12 million.) A new study published in the Journal of Neuroscience revealed that in dogs smell and vision are connected in the brain, which has not been found in other animals. “They can detect the smell of their owner's fingerprints on a glass slide six weeks after they touched it,” says Nicholas Dodman, professor emeritus at Cummings School of Veterinary Medicine at Tufts University. “And they can track from a boat where a box filled with meat was buried in the water, 100 feet below,” says Dodman, who is also co-founder and president of the Center for Canine Behavior Studies.
Another recent study from Queens College in Belfast, United Kingdom, further confirms that dogs can smell when humans are stressed. They can also detect the smell of a person’s breath and the smell of the skin cells of a deceased person.
The emerging avalanche-predicting human-made tech and the incredible nature-made tech of dogs’ olfactory talents is the lifesaving “equipment” that Leffler believes in. Even when human-made technology develops further, it will be most efficient when used together with the millions of dogs’ smell receptors, Leffler believes. “It is a combination of technology and the avalanche dog that will always be effective in finding an avalanche victim.”