You’re exploring in the dark on a secret mission. You need a dozen compatriots to initiate operations. How do you know when the minimum number is assembled, when you cannot see them or talk to them? The answer is quorum sensing: using techniques to silently count the friends near you. When you have a quorum, you start the mission.

These days, radio communication makes the imaginary secret mission a cinch. Without sight or sound, members of a team can know where their compatriots are on hand-held devices using encrypted messaging. In ordinary life, many people use apps like Apple’s “Find My Friends” to see where family members are before starting a birthday party. We take quorum sensing for granted, but we are purposeful, intelligent agents. Distributed robot systems designed by MIT use biomimetic algorithms pre-programmed into them by engineers.

Quorum sensing is used all the time by… (wait for it…) bacteria. Microbes can wait to commence an activity until a threshold density of neighboring conspecifics is detected. This skill has been observed in other microbes, like slime molds, and in higher organisms that exhibit collective behaviors, like insects, fish, and birds. Robot designers are learning tricks from the simplest of life forms: how to communicate with and respond to other unseen members of a population. Quorum sensing (QS) extends the concept of the interactome from intracellular to intercellular, converting a population of individuals into a super-organism. In this sense, a population of bacteria is a multicellular life form. This puts increased pressure on Darwinian notions of a “simple” cell. Could a lucky protocell, all alone, survive without a population of protocells able to communicate and coordinate their behaviors?

Requirements for Quorum Sensing

Consider the requirements for quorum sensing. The most rudimentary specifications include a sensor, a receptor, and a response plan. Bacteria employ QS by sending out specific molecules into the environment. On their surfaces, they post receptors for molecules from other members of their species. The incoming count is measured. When a threshold is reached, the signal triggers changes in gene expression, leading to pre-programmed actions coordinated with the other members of the swarm. These could include forming a biofilm, altering migration behavior, or switching on defensive maneuvers. Some bioluminescent microbes will only “turn on the lights” when a threshold density is detected.

Already we can see that a QS algorithm is irreducibly complex, but in real life examples, additional requirements become apparent. For instance, there is the need for “quorum quenching” — turning off the response when conditions change. The bacterium must also discern the degree of similarity of incoming signal molecules. In news about QS echoed on Phys.org, researchers from Aalto University in Finland likened the skill to understanding dialects and foreign languages:

“We did a ‘bacterial language check’ and found that bacteria using very similar languages can understand each other, just like a Dutch person might understand some German. We also tested communication between bacteria using very different languages and found that they couldn’t understand each other at all — just like a conversation between people speaking Finnish, Dutch and Arabic wouldn’t get far,” says Christopher Jonkergouw, the doctoral student who led the study. [Emphasis added.]

In the military, soldiers with different English dialects can generally understand one another to get by and continue their mission. They might even understand natives in other cultures who speak Pidgin, assisted by some gestures and facial expressions. There comes a point of “no comprendo” when the languages are too different, as anyone knows who has traveled abroad. The point is that beyond the threshold of comprehension, more is required for communication: language training, a smartphone translation app, or a human interpreter. Recall the consternation of Japanese soldiers in World War II listening in to the Navajo “code talkers” communicating American military strategies over the radio.

Bacteria Have a Similar Problem

The Aalto researchers identified over 160 bacterial “languages” spoken in molecular “words.” Molecules that are structurally similar can trigger a response up to a point, after which the bacteria do not respond. This knowledge is a first step for scientists wishing to intervene in bacterial responses like antibacterial resistance.

With these tools, the researchers have shown that we can accurately estimate the connections between bacterial languages and predict whether they can be understood. These findings will be valuable in further refining the team’s new treatment approach, and they also have implications for biotechnology — bacterial languages can be used to coordinate tasks between groups in bacterial communities, or even in bacterial microprocessors.

The team’s paper in Angewandte Chemie doesn’t use the language metaphor, but it elaborates on the methods for determining the limits of bacterial responses to similar molecules. Prior work on QS has focused on a few of these molecules, most prominently the homoserine lactones (HSLs). Like dialects, HSLs as a class include structurally similar forms, considered “cognate” — i.e., members of a family.

Here, we move beyond the commonly utilized HSL QS signalling systems and explore how chemical diversity in ligands can serve as a guiding principle to understand and circumvent non-cognate binding interactions. We explore the chemical diversity in a comprehensive set of known QS ligands and, based on the hypothesis that diversity in ligand chemical structures minimizes non-cognate interactions, experimentally assess a set of structurally similar as well as a diverging set of QS signalling systems (Figure 1). Using this approach, we significantly expand upon the known and available synthetic orthogonal QS signalling systems and provide a clear strategy towards future expansion efforts of additional synthetic orthogonal signalling systems.

Beyond the threshold of recognition, the signal molecule no longer triggers a response. The researchers “repaired” one such mutant molecule to see if the response could be regained:

Extensive screening from multiple ligation and transformation attempts generated a limited number of colonies that all contained non-synonymous mutations, resulting in amino acid substitutions. In the case of PauR, four sequenced colonies (from different ligations and transformations) all contained a point mutation in S129 a serine involved in AHL binding, within the autoinducer binding domain (Figure S2). Four clones of PluR contained non-synonymous mutations, all resulting also in amino acid substitutions. We hypothesized that constitutive expression severely affects viability in E. coli, so to overcome this, we controlled the expression of the receptor proteins with L-rhamnose (Figure 4b). This resulted in functional (and sequencing verified) constructs that we were able to experimentally assess.

It was a bit like intervening in a conversation to help a listener understand a word the speaker was mispronouncing. The mutations did not help the bacterium understand the signal. Less likely would a mutation help the listening bacterium come up with an improved response.

QS as a Life Trait

Rocks do not do quorum sensing. Could one boulder care how many others are around, using the information to initiate a programmed response? A critic might point to collective behaviors of particles in clouds, tornados, hurricanes, or other emergent phenomena. Such cases, however, do not send signals, receive signals, and respond by triggering embedded instructions. They simply respond to laws of physics. Life is different. From the smallest cell to the greatest whale or redwood tree, algorithmic processes like QS distinguish the biotic from the abiotic.

QS signalling systems are ubiquitous in prokaryotes, and novel [i.e., previously unknown] QS ligands are continually being identified. Furthermore, increasing evidence alludes to interspecies and even interkingdom signalling systems, expanding the range, scope, and complexity of intercellular signal recognition.

Within our own bodies there are examples of QS, for example in the immune system, hormone signaling, and blood clotting. Additionally, microbes in the gut use quorum sensing to respond to changes in food intake and wellness.

The authors know that QS is a characteristic of living things. They have nothing to say about Darwinian evolution, probably because we humans intuitively know intelligent design when we see it. Else why would scientists try to imitate it with engineering projects?

Cellular cooperation forms one of the defining features of higher organisms. The differentiation into various cell types allows cells to divide tasks and specialize. Prokaryotes have also developed methods to organizemore complex architectures. Bacteria utilize small molecules in quorum sensing (QS) as a form of intercellular signalling, which enables them to synchronize and organize behaviour on a population-wide or even community-wide level to facilitate bacterial biofilm architectures, promote plant colonization, or commence the production of a range of virulence factors. Consequently, these intercellular signalling systems have attracted widespread interest in biotechnology, where the potential to control community-wide responses has sparked innovations in microbiome therapeutics, microbial factories, and cellular computing.

Jonathan McLatchie wrote about quorum sensing here in 2010. His article embedded a TED talk by Bonnie Bassler that is worth watching again. Denyse O’Leary mentioned QS briefly in 2021 as an indicator of cognition, but there has been little mention of it otherwise in these pages. I hope this review of the latest news on QS will raise more awareness about this fascinating phenomenon. Perhaps it will prompt some ID scientists to take the lead in de-Darwinizing it for human health. In the meantime, all of us can use it as one more illustration of specified complexity and low probability that justifies The Design Inference.