We explore the field of biology from 2000-2020.
Biology came of age during the second half of the twentieth century. However, some of the undisputed triumphs of biological science during that period gave rise to heady claims that the basic problems of biology had at last been solved, once and for all.
If there is one unifying thread discernible in the wealth of new biological discoveries that have been made during the first two decades of the twenty-first century, it is that those claims were premature, at best. Admittedly, the old reigning theoretical viewpoint in biology—compounded of the philosophical doctrines of materialism, reductionism, and mechanicism, together with the evolutionary “Modern Synthesis” of natural selection theory and genetics—most likely still remains the official position of most biologists today. I will refer to this viewpoint as the “mechanistic consensus,” seeing that one of its key tenets is the proposition that living things are “nothing but” complicated machines.
Today, in 2020, the old mechanistic consensus is being disputed in a way we have not seen since the height of the “neo-vitalist” and “organicist” movements of the 1920s and 1930s (see A Brief History of Biology: 1900–1950). The new theoretical outlook that is now challenging the mechanistic consensus exists in a variety of somewhat different forms, some of which go by the name of “systems biology” and “evolutionary developmental systems theory (evo-devo).” There are other, kindred approaches, as well.
What all these new approaches have in common is the realization that genetic reductionism and the machine metaphor, even when augmented by the theory of natural selection, are incapable of providing a theoretical framework capable of adequately explaining the mind-boggling complexity of the biological phenomena. In view of this fact, it has become evident that the mechanistic consensus is played out and new theoretical approaches are required.
To get a whiff of the flavor of such thinking, consider this statement by the developmental comparative psychologist, Robert Linkliter (born c. 1953):
Evolution has come to be increasingly discussed in terms of changes in developmental processes rather than simply in terms of changes in gene frequencies. This shift is based in large part on the recognition that since all phenotypic traits arise during ontogeny as products of individual development, a primary basis for evolutionary change must be variations in the patterns and processes of development. Further, the products of development are epigenetic, not just genetic, and this is the case even when considering the evolutionary process. (“The Growth of Developmental Thought: Implications for a New Evolutionary Psychology,” New Ideas in Psychology, 2008, 26: 353–369.)
Such ideas appear to be eminently sober and scientific. In no way do they represent a threat to the status of biology as a rigorous science. On the contrary, they steer a sensible middle course between the extreme and philosophically unsupportable mechanistic consensus, on the one hand, and those critics, whether religious or political, who would reject biological claims for extra-scientific reasons, on the other. The necessity of hewing to such an intermediate conceptual path explains the name of what is perhaps the foremost grouping of professional biologists contributing to this project: Third Way of Evolution.
In this article, we will first examine some of the discoveries that have contributed to this sea change in biological thinking. Afterwards, we will look at several other developments in biology since 2000, which though less closely associated with the new thinking are noteworthy, as well.
First, however, a little background.
At the end of the twentieth century, great hopes were placed in the effort of the Human Genome Project to sequence the entire human genetic endowment (see A Brief History of Biology: 1950–2000). Hard on the heels of that success came the complete sequencing of the genomes of many other species. The age of “Big Data” had begun and continues apace.
The age of Big Data has also been, of necessity, the age of computers in biology. The extraction of biologically meaningful information from Big Data through pattern recognition was only one of the ways in which computers were understood to hold extraordinary promise for advances in biological understanding.
Another was the ability to run simulations as a means of “verifying” theoretical predictions—so-called experiments in silico.
At the end of the twentieth century, great hopes were placed in the effort of the Human Genome Project to sequence the entire human genetic endowment.”
A third way in which computers are supposed to have had a profound impact upon biological thinking is heuristic. The terminology developed for the discipline of computer science has provided a rich fund of metaphors for thinking about biological phenomena, which have helped to paper over the philosophical shortcomings of the mechanistic consensus.
The nub of the problem is this. The language of biology (as evidenced by textbooks) is replete with intentional concepts expressing meaning, value, purpose, and agency, at the same time that these phenomena are officially excluded from the ontology of science.
This highly uncomfortable fact (from the point of view of the mechanistic consensus) cannot be denied, so it is mostly ignored. If pressed, the consensus biologist finds it extremely useful to point to the computer as a supposed existence proof of the reducibility of intentionality to the flow of “information,” understood mechanistically. After all, there is nothing metaphysically suspicious about the digital universe! What could be more rigorously scientific than that?
But, of course, none of this makes any sense. A computer is just a manmade artifact, like a car. Nothing a computer does has any meaning, value, or purpose apart from the human mind. The idea that computers help to make sense of living things on some fundamental level is a swindle, pure and simple.
None of this is to say that the language of information, communication, signs, signals, error, error-correction, proofreading, and on and on is not meaningful in a biological context. It is only to say that it by no means helps to support the mechanistic consensus. On the contrary, properly understood, it severely undermines it. The problem of accounting for the physical ground of the intentional (normative, teleological) character of life remains untouched and becomes more pressing with every passing day. The cogency of this argument has been dawning on more and more working biologist over the past 20 years.
To make matters worse (from the consensus perspective), Big Data has been a Big Bust. The promised insights have not been forthcoming. Over the course of the first two decades of the twenty-first century, it has become painfully clear that we are drowning in information out of which we have no hope of extracting understanding absent some profound new advances on the theoretical front.
...epigenetics consists of regulatory changes to DNA which differ from the usual direct but transient binding of an enzyme to DNA by means of a weak (hydrogen) bond.”
These, then, are the negative reasons for believing the old mechanistic consensus is on the way out. But what is more important is that the 21st century has seen an explosion of new discoveries which constitute positive evidence for the same conclusion. We will now explore the most important of these: the “epigenetics revolution.”
What is epigenetics? In a nutshell, epigenetics consists of regulatory changes to DNA which differ from the usual direct but transient binding of an enzyme to DNA by means of a weak (hydrogen) bond. Instead, in an epigenetic modification, an enzyme mediates a strong (covalent) bond between small molecules (such as methyl groups) and either DNA itself or the surrounding proteins (histones), which together with DNA comprise chromatin. Such modifications may be long-lasting.
To understand this complicated subject, it is helpful to briefly review the history of the gradual elucidation of gene regulation. Several distinct streams of experiments fed into what was to become the epigenetics revolution.
First, recall that the discovery that gene expression is under the control of other gene products (proteins) dates to the 1960s (see A Brief History of Biology: 1950–2000). This first phase in our understanding of gene regulation may perhaps be said to have reached its culmination in the demonstration in 1967 by Mark Ptashne (b. 1940) of specific binding between a protein (the λ phage repressor protein) and DNA.
The first generation’s discoveries were used in the ensuing decades by an army of other researchers to push the boundaries of our knowledge of gene regulation in a variety of different directions, including (but not limited to):
Another stream of experimentation and discovery that flowed into the epigenetics revolution was the invention of somatic cell nuclear transfer (SCNT) technology.
Commonly known as “cloning,” SCNT involves the transplantation of the nucleus of a somatic cell (as opposed to a gamete) of a donor organism into an enucleated ovum of another organism. In practice, the host and donor organisms must be of the same or closely related species (though there are efforts afoot to overcome this limitation). SCNT raises various important ethical and political issues that we have no space to enter into here.
In 1996, Keith Campbell (1954–2012) and Ian Wilmut (b. 1944) announced the birth of the lamb, Dolly, at the University of Edinburgh. Dolly was the first mammal to be successfully cloned, leading to an explosion of work in this field.
Though the technical proficiency behind these achievements cannot be doubted, there was little theoretical understanding up to that time of how cloning was possible. The next stream that fed into the epigenetics revolution was the concerted effort to understand what distinguishes embryonic stem cells from ordinary somatic cells at the molecular level.
The next stream that fed into the epigenetics revolution was the concerted effort to understand what distinguishes embryonic stem cells from ordinary somatic cells at the molecular level.”
In the embryonic development of metazoans, the embryonic stem cells that form the so-called “inner mass” of the blastocyst are said to be “pluripotent,” meaning they can potentially transform themselves into any other cell of the adult body. (However, only “totipotent” stem cells, derived from the earlier morula stage of development, can form a placenta, and hence lead to a new individual.)
During the late 1990s and early 2000s, concerted efforts were made to identify the molecular factors responsible for “reprogramming” somatic cells into the pluripotent state, thus making cloning possible. Such reprogrammed, or “de-differentiated,” cells came to be called “induced pluripotent stem cells” (iPS cells).
In 2006, Shinya Yamanaka (b. 1962) and Kazutoshi Takahashi (b. 1977) provided a theoretical account of a minimal “cocktail” of proteins that they thought would transform a somatic cell into an iPS. The following year, the efficacy of their recipe was experimentally confirmed by the Yamanaka team itself, as well as by two other teams led James Thomson (b. 1958) and Rudolf Jaenisch (b. 1942).
Finally, all of these streams of research led into the heart of epigenetics—the control of gene expression by a secondary system of long-term genetic modification laid on top of the primary, lac operon–type system (see our article A Brief History of Biology: 1950–2000). The most prominent example of this secondary system is DNA methylation.
It had long been known that methyl groups are associated with DNA in chromosomes, but the first glimmers of their biological role did not occur until the 1970s, when Gary Felsenfeld (b. 1929), Robin Holliday (1932–2014), Arthur Riggs (b. 1939), Adrian Bird (b. 1947), and others demonstrated that they play an important role in the regulation of gene expression.
This path-breaking work unleashed a torrent of research over the course of the last two decades of the 20th century and the beginning of the 21st by numerous investigators, including Charles David Allis (b. 1951), Moshe Szyf (b. 1955), Toshio Tsukiyama (b. 1962), Jack Taunton (born c. 1967), and many others too numerous to mention.
The startling new discovery of the “epigenome” has led, in turn, to increased insight into a number of related fields, notably developmental biology, where Richard Gordon (b. 1943), Scott F. Gilbert (b. 1949), Michael Levine (b. 1969), and many others are continuing to do ground-breaking work.
The startling new discovery of the “epigenome” has led, in turn, to increased insight into a number of related fields, notably developmental biology...”
This avenue of research, in turn, has had a profound impact on our understanding of evolution. The new “evo-devo” approach (already mentioned above) has been pursued by a small but influential group of investigators, including, notably, Rudolf Raff (1941–2019), Brian K. Hall (b. 1941), Stuart Newman (b. 1945), H. Frederik Nijhout (b. 1947), Wallace Arthur (b. 1952), Leo Buss (b. 1953), Gerd B. Müller (b. 1953), Pere Alberch (1954–1998), Andreas Wagner (b. 1967), and Gregory A. Wray (born c. 1979).
Wagner’s slogan, “the arrival of the fittest,” has served as an eloquent banner under which this kind of research has been, and continues to be, pursued. In other words, the evo-devo perspective seeks to place genetic variation in metazoans in the context of embryological development and physiological adaptation, more generally, instead of ascribing it blandly to “chance.”
In concert with evo-devo are the several other “network” and “systems” perspectives that have come to the fore over the past two or three decades.
Foremost among those who have attempted to apply graph theory and other mathematical formalisms to genetic, metabolic, and other living networks is Albert-László Barabási (b. 1967). Other names that must be mentioned in this regard include Brian Goodwin (1931–2009), John C. Gerhart (b. 1936), Michael Antonio Savageau (b. 1940), Athel Cornish-Bowden (b. 1943), Marc Kirschner (b. 1945), Douglas Kell (b. 1953), Hans Westerhoff (b. 1953), and Nigel Goldenfeld (b. 1957).
In 1999, the first successful model of the complete metabolic network of an organism, the bacterium Haemophilus influenzae, was produced by Bernhard Palsson (b. 1957) and Jeremy S. Edwards (born c. 1973).
Modeling of biological metabolic networks from a more global systems perspective has begun to find a foothold within the mainstream, as well. Among those who have contributed to this development, we may name Leroy Hood (b. 1938), George M. Whitesides (b. 1939), William Bialek (b. 1960), Hiroaki Kitano (b. 1961), and Uri Alon (b. 1969).
Another group of investigators has focused on the problem of the inherent adaptive capacity of the organism, and the way in which this capacity is logically prior to natural selection, thus refuting the claim that the theory of natural selection reduces teleology to mechanism. It doesn’t. On the contrary, natural selection presupposes the immanent teleology of the general adaptive capacity.
Among the scientists who have worked in this area, the following may be mentioned: Paul Bach-y-Rita (1934–2006), Martin Heisenberg (b. 1940), Mary Jane West-Eberhard (b. 1941), Eva Jablonka (b. 1952),) Mriganka Sur (b. 1953), and Massimo Pigliucci (b. 1964). West-Eberhard’s 2003 textbook, Developmental Plasticity and Evolution, has provided a convenient summary of the point of view adopted by workers in this field.
Other important work, some along more traditional lines, from the past two decades includes the following:
Two technological advances that have occurred over the last few decades have also had a profound impact on cell biology.
First came the discovery during the late 1980s, and subsequent refinement, of the so-called “knock-out gene” technique of producing organisms at will that are lacking specific traits. This work was pioneered by Oliver Smithies (1925–2017), Mario Capecchi (b. 1937), and Martin Evans (b. 1941), among others.
Next came the discovery of CRISPRs (clustered regularly interspaced short palindromic repeats) and the Cas-9 protein that interacts with them. A new kind of bioengineering technology based on the CRISPR-Cas9 system was developed in 2014 by George Church (b. 1954), Jennifer Doudna (b. 1964), Emmanuelle Charpentier (b. 1968), and Feng Zhang (b. 1981). This new tool has proven to be immensely useful to biologists probing the workings of cells at the molecular level.
In closing, let us briefly revisit the theme that has been woven like a bright red thread throughout the fabric of the history of biology (see the three previous articles in this series–namely, the problem of teleology and of the fundamental nature of living systems.
If it is true, as many biologists are now beginning to suspect, that the theory of natural selection in and of itself cannot account for the fundamental properties of life that separate it from inorganic matter, then the question arises with ever greater urgency: What is an organism, if not a machine?
In the year 2000, an answer of sorts to this question was penned, in the form of a brief manifesto, by three highly distinguished condensed-matter physicists–PersonLink slug=“david-pines” /> (1924–2018), Robert B. Laughlin (b. 1950), and Peter Guy Wolynes (b. 1953–along with two of their associates. Entitled “The Middle Way” (Proceedings of the National Academy of Sciences, 97: 32–37), this manifesto urged that biologists rethink the living state in terms of condensed-matter physics. (The “middle” in the title of the article referred to the scale of living matter as “intermediate between atomic and macroscopic dimensions.“)
Over the two decades since the Middle Way manifesto, a new field has arisen that has come to be known as “quantum biology.” Much of modern work in quantum biology grows out of pioneering studies of Per-Olov Löwdin (1916–2000) during the 1960s on proton tunneling as a mechanism of DNA mutation. (For somewhat later, often speculative, work on quantum biology, see A Brief History of Biology: 1950–2000)
The field remains controversial, because conventional quantum theory predicts the decoherence of quantum entangled states at such high temperatures as are characteristic of life. However, theoretical models of failure of decoherence under certain circumstances have been advanced in rebuttal, and more importantly, experimental evidence of quantum effects in such biological phenomena as photosynthesis continue to mount.
Among the most-noted advocates of this new approach who have emerged over the past few decades, the following may be mentioned: Lloyd Demetrius (b. 1938), Marshall Stoneham (1940–2011), Judith Klinman (b. 1941), Robert H. Austin (b. 1942), Stuart Hameroff (b. 1947), Jim Al-Khalili (b. 1962), Martin Bodo Plenio (b. 1968), Gregory D. Scholes (born c. 1968), Thorsten Ritz (born c. 1974), Gregory S. Engel (born c. 1977), Masoud Mohseni (born c. 1978), and Jennifer C. Brookes (born c. 1983).
A good summary of this work may be found in Brookes’s article, “Quantum Effects in Biology: Golden Rule in Enzymes, Olfaction, Photosynthesis, and Magnetodetection”, Proceedings of the Royal Society A, 2017, 473: 20160822.
Find out which influencers have most contributed to advancing the field of biology over the last two decades with a look at The Most Influential People in Biology, for the years 2000 – 2020.
And to find out which schools are driving the biology field forward today, check out The Most Influential Schools in Biology for the years 2000-2020.
Or, continue exploring the fascinating history of the biology discipline with a look back at a Brief History of Biology: Before 1900.