Luísa Jabbur

Luísa is a Fellow whose work revolves around understanding how bacteria anticipate and predict the seasons.

For over a century now, we have known that animals and plants (and many other kinds of eukaryotes) are capable of predicting the yearly changes in their environment and changing their metabolism, physiology or behavior in an anticipatory manner. Phenomena like migration, hibernation and flowering are some examples of this ability. The way these organisms do this is by measuring the length of the day and the night (also known as the “photoperiod”; hence, this ability is called photoperiodism) and using that as a cue of future environmental conditions.

During her PhD, Luísa discovered that, despite their much shorter generation time, bacteria are also capable of this kind of anticipatory response. She studied the cyanobacterium Synechococcus elongatus PCC 7942, an incredibly well-studied model bacterium within the circadian biology field, and learned that when these bacteria see short (winter-like) days, they are capable of surviving being exposed to cold 2-3x better than when they see long (summer-like) days. Surprisingly, this ability appears to follow very similar principles to that seen in complex eukaryotes. However, unlike most of the complex eukaryotes which are models for studying photoperiodic responses, cyanobacteria grow incredibly fast (doubling about once a day), have a small genome, are readily transformable and can be easily grown and studied in laboratory conditions.

At the JIC, Luísa is leveraging this timely discovery to understand the mechanisms behind this anticipatory activity, as well as how widespread this is among the Bacteria domain. This knowledge could help us better understand important seasonal phenomena such as algal blooms, and also serve as a basis for understanding both the functioning and the evolution of photoperiodic responses in bacteria and in complex eukaryotes.

Furthermore, Luísa plans on taking advantage of the fast generation times of cyanobacteria to predict how photoperiodic species might adapt to climate change. We know that climate change is already having an impact on photoperiodic responses, and this impact is only expected to increase. As temperatures get warmer and less predictable, previous day lengths that indicated that summer or winter are approaching become “misinformation”. This temporal mismatch leads to events such as improper timing of bird migration, with some species arriving too early or too late to their migratory spots. While animals and plants often have such long generation times that preclude experimental evolution studies, bacteria do not.

As such, we can evolve cyanobacteria in the lab under climate change conditions and see how they “solve” this temporal mismatch problem. Their solutions can hopefully guide future efforts to mitigate the effects that climate change will have upon seasonal phenomena.