Reconsidering the evidence for learning in single cells

In a commentary on this exchange, Kellogg, 1958 remarked that Jensen’s worm analogy was poorly chosen, since there was ample evidence that worms can learn. Kellogg saw in the Gelber-Jensen debate a reflection of the problem that had vexed some of the greatest thinkers: where do we draw the line between ‘higher’ and ‘lower’ organisms? If learning is one of those ‘higher’ faculties, then the demonstration of learning in single-celled organisms contradicts Loeb’s (and Jensen’s) idea that the behavior of apparently ‘lower’ organisms like Paramecia can be explained by various kinds of tropisms, without reference to ‘higher’ faculties.

Shortly after the Gelber-Jensen debate, Katz and Deterline, 1958 replicated Gelber but again raised the issue of changes to the culture due to the presence of the bacteria. They arrived at this conclusion on the basis of an experiment in which the culture was vigorously stirred immediately after the final training trial, before an additional ‘post-stir’ test, finding that stirring eliminated all conditioned responding. Their interpretation was that stirring dispersed any residual concentration of bacteria in the vicinity of the wire, which they assumed was driving the response to the wire. However, there is another interpretation of this result: it is a form of contingency degradation (Rescorla, 1968). The stirring procedure effectively decorrelated the wire (CS) and bacteria (US). It is well-known from Rescorla’s experiments and many others that this procedure suppresses conditioned responding to the CS, even when holding fixed the number of CS-US pairings. Indeed, a later experiment by Hennessey et al., 1979 used Rescorla’s ‘truly random control’, which explicitly decorrelates the CS and the US, finding that this eliminates learning of an avoidance response to a vibratory CS. It is also important to point out that procedurally, Katz and Deterline deviated in an important way from Gelber by measuring the number of bacteria in the vicinity of the wire rather than the number adhered to the wire, which means that in effect they were partially measuring ‘contextual’ conditioning.

Gelber’s subsequent career is hard to track after the lapse of years. The news story in Figure 1, from the Tucson Daily Citizen of 19 October 1960, describes her as a ‘refugee’ from the University of Chicago, holding a contract of $100,000 from the NIH and launching an institute for ‘off beat’ science. As to what became of this venture, we have no clue. In 1964, Gelber presented her Paramecium work at the symposium on ‘Learning and Associated Phenomena in Invertebrates’ in Cambridge, England (Thorpe and Davenport, 1965; McConnell, 1966). In 1969, she conducted a pilot study for the National Institute of Mental Health on what retired scientists do, having become by then one of her own subjects. She died in 1991. The Wikipedia entry on her arose from our enquiries. We would be delighted to know from any readers who can add to the limited story of her life that we have been able to piece together.

Taking stock, we believe that Gelber’s experiments, though not without their limitations, convincingly demonstrated Pavlovian conditioning in Paramecia. Sadly, her critics seem to have won in the long term. Most reviews of the literature, if they mention Gelber’s work at all, quickly dismiss it on the basis that it was confounded by more plausible alternative explanations (e.g. Warren, 1965; Applewhite, 1979). An exception is the review of invertebrate learning by McConnell, 1966, who was sympathetic to Gelber’s conclusions. In discussing the Katz and Deterline stirring result, he wryly noted that “since these authors failed to control for the effects of ‘vigorous stirring’ on the behavior of Paramecia, and since even an overtrained rat that was ‘well shaken’ right after a final training trial might choose not to run the maze if returned to it immediately, the issue cannot be resolved on the basis of these studies alone’ (p. 112). McConnell, 1966 himself showed conditioning in planaria; his reports of RNA-based memory transfer during regeneration and cannibalism provoked a controversy to which we return in the next section.

In surveying much of this work, it is hard not to feel that participants divided into those opposed to the possibility of learning in single-cell organisms and those sympathetic to the possibility and that their interpretations were strongly influenced by these prejudgements. One of the challenges in revisiting these controversies is how to formulate experiments which can transcend ideological stances and elicit compelling scientific insights.

If single cells can learn then they must be using a non-synaptic form of memory storage. The idea that intracellular molecules store memories has a long history, mainly in the study of multicellular organisms. We have already mentioned McConnell’s studies of planarians; similar ideas were espoused by Georges Ungar based on his studies of rodents (Ungar and Irwin, 1967; Ungar et al., 1968). These studies indicated that memories could be transferred from one organism to another by injection or ingestion of processed brain material. Clearly no synaptic information could survive such processing, so transfer could presumably only occur if the memory substrate was molecular. However, these findings were the subject of much controversy. The failure of careful attempts to replicate them led to a strong consensus against their validity and this line of research eventually died out (Byrne et al., 1966; Travis, 1980; Smith, 1974; Setlow, 1997). Nonetheless, several lines of recent work have revisited these studies (Smalheiser et al., 2001; Shomrat and Levin, 2013). For example, Bédécarrats et al., 2018 showed that long-term sensitization of the siphon-withdrawal reflex in Aplysia could be transferred by injection of RNA from a trained animal into an untrained animal. This study further showed that this form of transfer was mediated by increased excitability of sensory (but not motor) neurons, and depended on DNA methylation, although the study did not establish either RNA or DNA methylation as the engram storage mechanism. In another line of work, Dias and Ressler, 2014 showed that fear conditioning in rodents could be transferred from parents to offspring, an effect that was associated with changes in DNA methylation. These studies not only revive the molecular memory hypothesis, but also point towards specific intracellular mechanisms.

The significance of DNA methylation lies in the fact that DNA methylation state can control transcription. Thus, the set of proteins expressed in a cell can be altered by changes in DNA methylation, which are known to occur in an experience-dependent manner. For example, after fear conditioning, the methylation states of 9.2% of genes in the hippocampus of rats were found to be altered (Duke et al., 2017). As first pointed out by Crick, 1984, and later elaborated by Holliday, 1999, DNA methylation is a potentially stable medium for heritable memory storage, because the methylation state will persist in the face of DNA replication, thanks to the semi-conservative action of DNA methyltransferases. A related idea, put forward independently in Lisman et al., 2018, is that a stable memory could arise from the tug-of-war between enzymatic phosphorylation and dephosphorylation. In essence, the idea is to achieve stability through change: a molecular substrate maintains its activation state by means of continual enzymatic activity. Crick and Lisman suggested that this could solve the problem of molecular turnover that vexes synaptic theories of memory. Consistent with this hypothesis, inhibition of DNA methyltransferase disrupts the formation and maintenance of memory, although it remains to be seen whether methylation states themselves constitute the engram (Miller and Sweatt, 2007; Miller et al., 2010). The proposals of Crick and Lisman apply generally to enzymatic modification processes (e.g. acetylation or glycosylation) acting on macromolecules, provided that the biochemical dynamics can generate the appropriate stable states (Prabakaran et al., 2012).

An important distinction between the forms of dynamical information storage proposed by Crick and Lisman and the storage provided by DNA is that the latter is largely stable in the absence of enzymatic activity, under conditions of thermodynamic equilibrium. In contrast, the former typically relies on enzymatic activity and is only stable if driven away from thermodynamic equilibrium by chemical potential differences generated by core metabolic processes. In other words, the latter may accurately retain information in the absence of a cell over a substantially longer period than the former, which may lose information rapidly in the absence of supporting enzymatic activity.

Another candidate medium for intracellular memory storage is histone modification. In eukaryotes, DNA is wrapped around nucleosomes, composed of histone proteins, to form chromatin. Gene transcription can be controlled by changes in the modification state (acetylation, methylation, ubiquitination, etc.) of these histones. In the cell biology literature, an influential hypothesis posits the existence of a histone ‘code’ (Jenuwein and Allis, 2001; Turner, 2002) or ‘language’ (Lee et al., 2010) that stores information non-genetically, although the nature of that information has been a matter of debate (Sims and Reinberg, 2008; Henikoff and Shilatifard, 2011). Early work demonstrated that learning was accompanied by increased histone acetylation in the rat hippocampus (Schmitt and Matthies, 1979), and more recent work has established that memory can be enhanced by increases in histone acetylation (Levenson et al., 2004; Vecsey et al., 2007; Stefanko et al., 2009). Bronfman et al., 2016 provide an extensive survey of the molecular correlates of learning and memory.

In parallel with these findings, molecular biologists grappling with the information processing that takes place within the organism have begun to suggest that signaling networks may implement forms of learning (Koseska and Bastiaens, 2017; Csermely et al., 2020). In this respect, Koshland’s studies of habituation of signaling responses in PC12 cells, a mammalian cell line of neuroendocrine origin, are especially resonant (McFadden and Koshland, 1990). Koshland’s work was undertaken in full awareness of learning studies conducted by Kandel and Thompson in animals but his pioneering efforts have not been explored further. This reflects, perhaps, the intellectual distance between cognitive science and molecular biology, which the present paper seeks to bridge. The information processing demands on a single-celled organism, which must fend for itself, are presumably quite different from those confronting a single cell within a multi-cellular organism during development and homeostasis, so what role learning plays within the organism remains a tantalizing open question.

Beatrice Gelber, though she could not have known about the specifics of DNA methylation or histone modification, was uncannily prophetic about these developments:

"This paper presents a new approach to behavioral problems which might be called molecular biopsychology… Simply stated, it is hypothesized that the memory engram must be coded in macromolecules… As the geneticist studies the inherited characteristics of an organism the psychologist studies the modification of this inherited matrix by interaction with the environment. Possibly the biochemical and cellular physiological processes which encode new responses are continuous throughout the phyla (as genetic codes are) and therefore would be reasonably similar for a protozoan and a mammal." (Gelber, 1962a, p. 166).

The idea that intracellular mechanisms of memory storage might be conserved across phyla is tantalizing yet untested. The demise of behavioral studies in Paramecia and other ciliates has meant that, despite the wealth of knowledge about ciliate biology, we still know quite little about the molecular mechanisms underlying Gelber’s findings. Nonetheless, we do know that many intracellular pathways that have been implicated in multicellular memory formation exist in ciliates (Table 1). For example, ciliates express calmodulin, MAP kinases, voltage-gated calcium channels, in addition to utilizing various epigenetic mechanisms that might be plausible memory substrates, such as DNA methylation and histone modification. In like manner, key molecular components of neurons and synapses emerged in organisms without nervous systems, including unicellular organisms (Ryan and Grant, 2009; Arendt, 2020). We believe it is an ideal time to revisit the phylogenetic origins of learning experimentally and theoretically.

Single cells continue to surprise us. Robert Hooke, peering through his microscope in the 17th century, first likened cells to the small rooms (cellula) inhabited by monks. Fast forward to the 21st century, and it is now banal for cell biologists to think of the cell as a miniature computer, capable of sophisticated information processing (Bray, 2009). Among their many capabilities, it is now appreciated that cells have memory, possibly in the form of a ‘histone code’ (Jenuwein and Allis, 2001; Turner, 2002), though a precise computational understanding of this code has remained elusive. Whatever the memory code may be, its implications for neuroscience are far-reaching: we may finally be poised to link cellular memory codes with cognitive information processing. In this context, the studies by Gelber and others of learning in Paramecia become freighted with significance. They suggest that single cells have the ability to carry out a form of information processing that neuroscientists have traditionally attributed to networks of cells. We still do not understand how Paramecia accomplish this feat. If the hypothesis is correct, then single cells hold more surprises in store for us.

We are grateful to Aaron Lisec (Special Collections Research Center, Southern Illinois University Library), Catherine Uecker (Special Collections Research Center, University of Chicago Library), Frances Gabbay and Chris Davis for their help with obtaining information about Beatrice Gelber; to Susan Healey, editor of Animal Behaviour, for help tracking down Gelber’s conference publication; to Richard Morton-Jack for uncovering the photograph shown in Figure 1 and other pertinent information; to Kim Reis, Director of Sales and Licensing at Imagn, for permission to use the images in Figure 1; and to Hanna Hillman for creating the diagram of Gelber’s experiments.