How’s this for an admission that design principles motivate scientific progress?

For an engineer, successful design of a new product needs to meet multiple objectives such as maximizing targeted mechanical performance and minimizing the cost. Some of these objectives are incompatible, thus tradeoffs are necessary. Similarly, living organisms are also constantly … optimizing multiple objectives such as growth rate and resistance to environmental fluctuations. A central task for systems biology is to unravel the corresponding mechanisms, or the design principles ultimately determined…, especially how a system prioritizes the multiple objectives and makes necessary compromises.

That’s a great quote except for the parts we left out. In the first ellipsis, the authors of a paper in PNAS insert these words: “[are also constantly] under selection pressure to maximize their fitness to the environment through [optimizing]…” The second ellipsis adds, “by evolution.” But since engineers are neither under the pressure of natural selection nor working by blind chance, the extraneous words destroy the comparison, and thereby contribute nothing to the meaning.

The paper deals with an interesting problem in biology. Our noses contain millions of olfactory sensory neurons (OSNs). Each neuron expresses one and only one type of olfactory receptor (OR, a molecular machine that recognizes a particular odor molecule). There are hundreds, in some animals thousands, of different receptor types. How does each receptor get its fair share in the distribution? It’s “one of the most intriguing problems in neurobiology,” the authors say; “how can both monoallelic and diverse expression of OR be ensured at the same time?”

The answer “remains elusive after several decades of intensive investigations” — until one thinks like an engineer. At a key point in the paper, despite other attestations about evolution, they make their breakthrough with these words: “Then from an engineering perspective, a better design to achieve single-allele activation is…” and so forth [emphasis added]. The body hits the optimization target successfully just like a good engineer. Actually, it does it better. Their simple model, flowchart and all, is less sophisticated than the nose itself.

The final paragraph nicely states the centrality of design principles in their research (and says nothing more about evolution):

In summary, we have constructed and analyzed a comprehensive model that revealed a mechanism for achieving diverse and monoallelic OR gene expression. A proper combination of mechanisms, but none of the individual one, can achieve the desired diverse and monoallelic OR expression. Given that multiobjective optimization is ubiquitous in biological systems, this synergetic and sequential application of different mechanisms is likely to be a general design principle on biological process regulation, and shed light on problems in other fields as well. This work aims at using a minimal model to reveal the essential elements that regulate the OR selection process. For example, [four examples given]…. Future studies will reveal these possible fine-tuning elements and address its implications in other processes of gene regulations.

A statement from the University of Pittsburgh about this paper doesn’t mention design or evolution, but summarizes the principle finding as “a basic physics principle called cooperativity, in which elements in a system influence the behavior of one another rather than function independently.” The synergy between neurons the scientists witnessed gave them the chills. “We are amazed that nature has solved the seemingly daunting engineering process of olfactory receptor expression in such a simple way,” one said.

Designed Winnowing

Another paper, this one in Current Biology, addresses the same problem from another angle. “A genetic approach in mice reveals a new facet of odorant receptor (OR) regulation,” the summary begins. “Adventitious expression of multiple ORs activates post-selection refinement (PSR).” As the neurons sort themselves out in the olfactory epithelium during development, failures occur. Some neurons, contrary to the rules, express more than one receptor. Don’t worry; a cleanup crew is on hand to take care of them:

Here we used a genetic approach in mice to reveal a new facet of OR regulation that corrects adventitious activation of multiple OR alleles, restoring monogenic OR expression and unique neuronal identity. Using the tetM71tg model system, in which the M71 OR is expressed in >95% of mature OSNs and potently suppresses the expression of the endogenous OR repertoire, we provide clear evidence of a post-selection refinement (PSR) process that winnows down the number of ORs. We further demonstrate that PSR efficiency is linked to OR expression level, suggesting an underlying competitive process and shedding light on OR gene switching and the fundamental mechanism of singular OR choice.

This paper had no use for Darwinian theory. The “selection” they speak of is not natural selection, but rather the initial choice of OR that each OSN expresses. How could a blind process know that expressing multiple ORs on the same neuron is a problem? How could it know what needs to be winnowed down? The paper calls this “Cleaning Up After Feedback.” It sounds designed. “The process we describe here may represent a ‘failsafe’ mechanism,” they say, when the normal process doesn’t generate a single outcome like it’s supposed to (e.g., one OR per neuron). Their summary explains why that might happen, and how the body is prepared to deal with it:

OR regulation generates >2,000 transcriptional outcomes, endowing an equal number of OSN identities. This extreme selectivity results from a slow initial phase, when individual OR alleles are infrequently activated, followed by a feedback stage halting the process and preserving singular choice. Mathematical modeling has determined parameters for activation and feedback that ensure a high probability of singular expression. These analyses also defined a failure rate, when activation proceeds too quickly, or feedback proceeds too slowly, resulting in neurons expressing multiple ORs. OSNs are unlikely to use feedback suppression to restore singular OR expression once more than one allele is activated. We have revealed a post-selection refinement (PSR) mechanism, which restores singular OR expression and unique neuronal identity.

This is a nice supplement to a previous article here on olfaction two months ago, where we learned how individual olfactory receptors (ORs) respond to not only the shape but vibrational energies of odor molecules, and then took a look down the line at the olfactory bulb to see how the switchboard maintains its complex wiring. Those were design features of the operational adult nose. Now, we see that the design principles of optimization, feedback, and refinement are at work in the initial setup stages of the neurons and their receptors. “From an engineering perspective,” it’s clearly design all the way down.

But Wait, There’s More

Yes, another recent paper shows a nose for “design principles” without mentioning evolution. This paper from Harvard, published in PNAS, uses the phrase “design principle” three times. The authors wanted to understand how a relatively small number of receptors can produce so many scent sensations. Humans only have about 300 ORs but can discriminate at least 2,100 odorant molecules. Other animals, like dogs, have much higher sensitivity. How is this possible? It’s by design. “Such remarkable molecular discrimination is thought to use a combinatorial code,” we know from earlier studies. Once again, we find optimization (an intelligent design science) at work. The receptor arrays are optimized for natural odor statistics, these scientists discovered:

We study a simple model of the olfactory receptors from which we derive design principles for optimally communicating odor information in a given natural environment. We use these results to discuss biological olfactory systems, and we propose how they can be used to improve artificial sensor arrays.

There you have it. Not only do the authors finding design principles useful for understanding the nose, they look forward to how to copy those principles for artificial noses. The optimization, by the way, continues all the way to the brain:

The activity of a single glomerulus is thus the total signal of the associated receptor type, so the information about the odor is encoded in the activity pattern of the glomeruli. This activity pattern is interpreted by the brain to learn about the composition and the concentration of the inhaled odor. We here study how receptor arrays can maximize the transmitted information.

Using an “information theoretic approach” to quantify how well a receptor array matches the odor statistics in the environment, they even make predictions:

Using an information theoretic model, we show that a receptor array is optimal for this task if it achieves two possibly conflicting goals: (i) Each receptor should respond to half of all odors and (ii) the response of different receptors should be uncorrelated when averaged over odors presented with natural statistics. We use these design principles to predict statistics of the affinities between receptors and odorant molecules for a broad class of odor statistics. We also show that optimal receptor arrays can be tuned to either resolve concentrations well or distinguish mixtures reliably. Finally, we use our results to predict properties of experimentally measured receptor arrays.

Naturally, biological noses, whether in humans or fruit flies, with their “remarkable molecular discrimination” abilities, vastly outperform the sensitivities of “artificial nose” devices created so far. Codes — optimization — information: design principles are propelling research into the secrets inside your nostrils.

Image credit: © Sergey Khamidulin — stock.adobe.com.