Here are two examples of researchers looking for "design principles" in living organisms, showing that an engineering focus leads to scientific progress.

Cell Replication as System Engineering

The job of an efficiency expert is to find better ways to get more things done in less time at less cost. From "Taylorism" in the early 20th century, through "Operations Research" in the days of World War II, to "systems engineering" today, efficiency expertise has grown into an essential discipline for manufacturing and project scheduling. Recently, Rami Pugatch, a systems biologist at the Institute for Advanced Study in Princeton, looked at the humble lab bacterium E. coli with the eyes of an efficiency expert. PhysOrg explains how he approached "cellular replication as a systems engineering problem" —

The paper describes the problem of task scheduling in cellular replication processes and ultimately produces a mathematical distribution that characterizes an optimal replication strategy for E. coli cells. The scope of Pugatch’s work encompasses individual cellular processes, algorithmic descriptions of optimized replication, systems engineering concepts, and even the history of the concept of the self-replicating factory. [Emphasis added.]

The history referred to is John von Neumann’s 1948 theoretical work on how to build a self-replicating factory. Pugatch finds that a replicating bacterium meets those requirements: it keeps all ingredients in well-stocked reservoirs for each task, it schedules them optimally, and duplicates the instructions as part of the job. The bacterium even succeeds when resources are scarce, a "hard-to-solve scheduling problem" according to the paper published in PNAS.

Bacterial self-replication is a complex process composed of many de novo synthesis steps catalyzed by a myriad of molecular processing units, e.g., the transcription — translation machinery, metabolic enzymes, and the replisome. Successful completion of all production tasks requires a schedule — a temporal assignment of each of the production tasks to its respective processing units that respects ordering and resource constraints. Most intracellular growth processes are well characterized. However, the manner in which they are coordinated under the control of a scheduling policy is not well understood. When fast replication is favored, a schedule that minimizes the completion time is desirable. However, if resources are scarce, it is typically computationally hard to find such a schedule, in the worst case. Here, we show that optimal scheduling naturally emerges in cellular self-replication. Optimal doubling time is obtained by maintaining a sufficiently large inventory of intermediate metabolites and processing units required for self-replication and additionally requiring that these processing units be "greedy," i.e., not idle if they can perform a production task. We calculate the distribution of doubling times of such optimally scheduled self-replicating factories, and find it has a universal form — log-Frechet, not sensitive to many microscopic details. Analyzing two recent datasets of Escherichia coli growing in a stationary medium, we find excellent agreement between the observed doubling-time distribution and the predicted universal distribution, suggesting E. coli is optimally scheduling its replication.

The paper makes no mention of evolution or natural selection; neither does the PhysOrg summary. Instead, one finds the language of "PERT" (project evaluation and review technique), "critical path," and other terms familiar to system engineers.

When von Neumann proposed the self-replicating factory, it was a futuristic idea that science fiction writers latched onto, envisioning space-traveling robots that could replicate themselves with resources found on planets they landed on as they spread throughout the galaxy. But right here on earth, we have a perfect example in one of the smallest, "simplest" living organisms.

Surprisingly, our analysis of recently measured datasets of E. coli exponentially growing in a stationary medium reveals that the measured distribution of doubling times fits well to the predicted distribution of doubling times of an optimally scheduled self-replicating factory. [PNAS]

Such a [von Neumann] factory is called "non-trivial" if it includes a universal constructor as a component. The duplicative process is not considered to be complete until a copy of the instructions is provided. Instead of directing their own replication, the instructions are instead duplicated from a template by a separate dedicated machine that is not triggered until the completion of the factory replication phase. This is closely analogous to actual cellular processes. [PhysOrg]

It took an engineer’s eye to see this connection. Now, our understanding of bacterial replication is enriched accordingly, with no reference to natural selection. In fact, this revelation of the process creates new problems for neo-Darwinism: how could a self-replicating von Neumann machine emerge in piecemeal fashion, without all the parts, instructions, and "universal constructor" already present?

Materials Science

Meanwhile, the strongest biological substance known has come to light. This material can withstand 5 gigapascals of tension, equivalent to a string the width of spaghetti holding 3,000 half-kilogram bags of sugar, according to the BBC News. What is it? It’s the radula, or tooth, of the humble limpet, a snail-like aquatic animal with a spiral shell. And who found it? An engineer. The University of Portsmouth explains:

Professor Asa Barber from the University’s School of Engineering led the study. He said: "Nature is a wonderful source of inspiration for structures that have excellent mechanical properties. All the things we observe around us, such as trees, the shells of sea creatures and the limpet teeth studied in this work, have evolved to be effective at what they do.

"Until now we thought that spider silk was the strongest biological material because of its super-strength and potential applications in everything from bullet-proof vests to computer electronics but now we have discovered that limpet teeth exhibit a strength that is potentially higher."

Aha! the Darwinist says. See? Barber said they "have evolved to be effective at what they do." Upon reading the material, though, evolutionary theory had nothing to do with the findings. It was little more than a throwaway line that the professor uttered probably out of habit. He’s an engineer, after all, who knows good design when he sees it:

"This discovery means that the fibrous structures found in limpet teeth could be mimicked and used in high-performance engineering applications such as Formula 1 racing cars, the hulls of boats and aircraft structures.

"Engineers are always interested in making these structures stronger to improve their performance or lighter so they use less material."

Barber’s work involved testing the tensile strength of the limpet teeth with specially designed instruments. It was difficult work. The teeth are only a millimeter long, and very thin. The limpet uses its radula to scrape algae from the rocks on which it feeds. Barber’s team found that, because the way the teeth are constructed with a mineral called goethite, its properties would scale: i.e., the same principles would work on larger sizes, since the strength of the material is not dependent on the size.

Finding out about effective designs in nature and then making structures based on these designs is known as ‘bioinspiration’.

Professor Barber said: "Biology is a great source of inspiration when designing new structures but with so many biological structures to consider, it can take time to discover which may be useful."

"Bioinspiration" — there’s a neologism that’s a keeper. Think of the prospects for finding more designs out there! As the BBC News article says, "We should be thinking about making our own structures following the same design principles." Good idea. Design is an inspiration to explore, discover, understand, then imitate.

Image: Patella vulgata, by Tango22 (Own work) [GFDL or CC BY-SA 3.0], via Wikimedia Commons.