Revealing Noise-Filtering in Basic Circadian Networks

New research has revealed that even a simple circadian clock network has sophisticated noise-filtering abilities, offering new insight into how biological systems maintain precision amid the chaos of the natural world.

The study, published in Nature Communications, shows how biological clocks can adapt to environmental changes—like shifting light levels or temperature—while staying remarkably accurate. This has broad implications for understanding how organisms, from bacteria to humans, track time in sync with the Earth’s 24-hour cycle.

A team of researchers from the Sainsbury Laboratory at the University of Cambridge, Imperial College London, the University of Warwick, and Forschungszentrum Jülich found that circadian clocks can selectively filter out minor fluctuations in environmental signals while still responding to meaningful changes. This capability helps prevent the system from reacting to short-lived or irrelevant noise—like a passing cloud—while still adjusting to real shifts, such as seasonal day length.

Anyone who’s dealt with jet lag knows how crucial biological clocks are. Each cell in our body contains its own internal clock, managing rhythms across a 24-hour period. These clocks must strike a delicate balance: they need to stay stable over time, yet flexible enough to adjust to new environments.

Decoding Time with Cyanobacteria

To better understand this balancing act, the Locke Group at the Sainsbury Laboratory turned to one of the simplest organisms known to have a circadian clock: Synechococcus elongatus, a photosynthetic cyanobacterium. Like plants, this microbe relies on daylight to function efficiently, making it an ideal model for studying how clocks handle real-world light variation.

The team explored how the clock discriminates between meaningful environmental inputs and transient “noise” by tracking thousands of individual cyanobacteria over time.

The 'Green Mother Machine'

To study the accuracy of circadian rhythms in constant light, the researchers developed a custom microfluidic device called the Green Mother Machine. This setup allowed them to trap a single bacterial “mother” cell and observe its behavior through long-term fluorescent timelapse microscopy.

“We needed to monitor individual cells for days with precision that previous studies couldn’t match,”

Dr. Sasha Eremina, the study’s first author from the University of Cambridge.

Building the device was no small task. It took years of refining materials, chip design, and light controls to create a system that could support healthy, photosynthetic bacteria in such a controlled space.

“Getting cyanobacteria to grow in these environments was significantly more challenging than with other microbes,”

Dr. Bruno Martins, Assistant Professor at the University of Warwick.

A Clock That Resists Chaos

The study found that even with constant cellular “noise” disrupting regulatory mechanisms, the cyanobacterial clock remained robust and highly accurate. Genetic experiments showed that the natural clock operates at a kind of “noise minimum,” implying that evolutionary pressures have shaped it to optimize timing.

“This robustness allows the cellular clocks to tick in sync for hundreds of days,”

Dr. Philipp Thomas, a lecturer at Imperial College London.

At the heart of the clock lies a trio of Kai proteins, which link and unlink in a phosphorylation cycle that repeats every 24 hours. Mathematical modeling and mutagenesis confirmed that the stability of the system originates from this core oscillator, rather than the broader gene network.

“This finding is exciting for synthetic biology, where stable biological timers are in high demand,”

Dr. Eremina.

Adapting to Real-World Light

To simulate how these clocks handle real environmental conditions, the team exposed cyanobacteria to complex light-dark cycles—some based on actual Caribbean Ocean weather data. The experimental outcomes closely matched predictions from their mathematical models.

“Despite variable light inputs, the clock was able to tune out the noise while remaining responsive to meaningful changes,” said Professor James Locke. “It’s a powerful example of how even simple biological networks can display advanced filtering capabilities.”