The physics of life and living things

 kw: book reviews, nonfiction, biophysics, dna, biomolecules, self-assembly

A friend of mine is a biophysicist. I asked him once what he does. He said he wasn't working in biophysics, but was writing computer code for a government agency. I didn't press further. When I saw that a book about biophysics I decided to read it: So Simple a Beginning: How Four Physical Principles Shape Our Living World by Raghuveer Parthasarathy. The book's title opens a key sentence in the last paragraph of Darwin's On the Origin of Species.

I was a physics major in 1969 and 1970. While physics deals with phenomena on all scales, from the gravitational and electromagnetic fields that can span the universe to the Planck Length, the smallest possible "useful" unit of length, most physicists at that time worked with subatomic particles, smaller than an atom by a factor of about 10,000, but still very large compared to the Planck Length: If a proton were enlarged to span the distance between Hartford, CT and Providence, RI, about 100 km, the Planck Length would become about the size of a proton.

If we move up in the scale of things to the nano-realm, from the size of an atom (an iron atom's diameter is 0.26 nanometers) and that of a DNA molecule (~10 nm in diameter, but very, very long) to the size of bacterial cells (500 nm to 10,000 nm), and further to the cells of animals and plants (10,000 - 100,000 nm), we are in the realm of biophysics.

The author first presents four physical principles that govern living things:

• Self-assembly – biological things typically "build themselves", such as the "liquid membrane" of a cell or a cell's nucleus, or a soap bubble as seen here. The electrochemical properties of all biomolecules facilitate their roles.

• Regulatory Circuits – phenomena such as the expression of a gene involve feedback loops with several elements.
• Predictable Randomness – this is the basis of statistical inference, and underlies Brownian Motion, which is the "motor" of many actions within cells.
• Scaling – relationships between length, area and volume regulate what is possible at different sizes, and underlie the dramatic difference between the kinds of legs that work for a rhinoceros beetle, compared to those of a rhinoceros, for example.

The book contains many illustrations drawn by the author, such as the ones shown above. 

The author proceeds from basic facts about atoms and molecules to the molecules need to operate a living cell, primarily DNA, RNA, proteins, sugars and lipids (fats). Examples of self-assembly introduce the ways these molecules' properties facilitate the construction of all the organelles in a cell. Certain operations require more specialized machinery; an example is ferrying certain products over longer distances (clear across an animal cell, which is 10-100x as wide as a bacterium, for example), because Brownian motion is too slow. This is carried out by special kinds of molecules that "walk" along the fibers that form an internal skeleton of the cell. Shorter range transport is typically carried out quite efficiently by relying on Brownian movement to jostle molecules around until they latch onto their targets. When a motion of a micron or so is needed, transport time is around a microsecond.

The four principles listed above are emergent properties of biomolecules in an environment warm enough for Brownian motion to help them go where they need to go, at least inside bacterial cells. Over evolutionary time, mechanisms have been developed that facilitate larger-scale things and operations, right up to the size of a blue whale or redwood tree. This was apparently a hard problem. The "boring billion" refers to a billion-year period during which bacteria and archaea, having developed quite a lot of sophistication, including the ability to aggregate into large assemblages such as stromatolites, didn't do much at all. Finally, eukaryotic cells arose, and things got a lot less boring. Animals, plants, fungi and protozoa are composed of eukaryotic cells (the word means "cells with a nucleus"). The largest eukaryotic cells are the neurons that run end-to-end in large animals such as whales or giant squids. The largest bacteria or archaea are 1/100 millimeter long (well, there are a very few species of bacteria that are 10-20 mm long and 3/4 mm diameter. All the rest are microscopic).

The last section of the book deals with the genetic revolution, first in reading ("sequencing") DNA and now writing it, or editing it. The prospect of "designer babies" and "clone armies" emphasizes that these matters have moral aspects. We have to work out "who decides what is moral" (particularly because most genetic scientists are atheists and so have no external moral compass). The author is optimistic that this can be carried out without much drama. 

I am less optimistic. The author discusses Chinese researcher He Jiankui, who announced having used CRISPR/CAS9 to gene-edit twin embryos. The girls were born in 2018. The Chinese government, partially under outside pressure, reacted strongly, shut down He's lab and jailed him. I suspect the next researcher who decides to give it a go won't announce anything. This may have already happened. Not everyone is willing to wait for consensus. The technique of "gene drive", which can rapidly send a species, such as a noxious sort of mosquito, into extinction, is an even scarier prospect. There is no guarantee that a gene drive that works in the Anopheles mosquito only will not mutate into one that crosses into another species, and eventually spreads and spreads. Think of "Ice-Nine" in Cat's Cradle by Kurt Vonnegut.

On another note: In the present technical environment dominated by Big Data, the author presents a good case for understanding—based on hypothesis, experiment, synthesis, and theory—wherever possible. He uses the example of making numerous experiments with a ball, rolled down a ramp and off the table, and measuring where it hits the floor. One could prepare a table based on thousands of such experiments. Then someone could use that table to determine, based on a ball's velocity and height from the floor, to predict where it will land. But a smaller number of experiments can underlie the development of a formula by which one can calculate the landing distance, without needing to interpolate from a table. The formula is based on understanding what gravity does, and experiments to confirm the strength of gravity. It isn't too extreme to say that Big Data is often used blindly. Physics, including biophysics, leads to understanding and removes the blinders.

I probably haven't demonstrated a great deal of my own understanding of biophysics. I have a lot to think over. This book is a marvelous introduction to the subject.

Errata: On p.266, illustrating how gene drive works, the example is a species of mosquito, gray in color. Sometimes a mutation occurs, yielding a black insect. In mid-discussion this sentence occurs, "Suppose just one individual has the gray mutation." It should be "…black mutation", as is clear from the accompanying illustration and the rest of the discussion.