Timing is everything, especially when you are as tiny as a phytoplankton at the base of the marine food web and have only a few days to find the nutrients you need to grow and replicate. This is especially true in parts of the ocean where nutrients essential for life (e.g., nitrogen, phosphorus) are scarce. Yet, in the nutrient-limited oligotrophic gyres which cover much of our planet, there is an astounding diversity of microorganisms that manage to thrive and mediate the cycling of elements, including carbon. Size differences amongst even single-cell organisms are massive, ranging from bacteria less than a micron across to large eukaryotes you can see with your eye. The ocean is constantly mixing, presenting ongoing challenges to organisms to find enough resources to grow. In this complex environment, one of the only constants is the day-night cycle, a massive fluctuation in energy that all organisms, photosynthesizing or not, must be able to manage.
Much like our own behaviors sync to the day-night cycle (many of us sleep at night and are active in the day, though some of us have an offset rhythm and sleep during the day), phytoplankton in sunlit waters are known to exhibit diel behaviors. In the summer of 2015 and supported by the Simons Foundation Collaboration on Ocean Processes and Ecology (SCOPE), two ships set out from the Hawaiian Islands to make surface ocean measurements of microbial processes (e.g., photosynthesis), gene expression via RNA sequencing, and metabolic products (e.g., lipids) via mass spectrometry. The team sampled as frequently as feasible for several days to search for patterns and principles amongst the dynamics of microbial interactions, matter transformations, and energy transfer. Onboard, 42 scientists from nine research institutions joined together to work around the clock to study how day-night cycles are imprinted on microorganisms in the surface ocean (Figure 1).
In our paper, we set out to integrate these diel datasets – encompassing gene expression as well as the concentrations of lipids and intermediate metabolic molecules – to explore how diel forcing of light-driven processes at the base of the marine food web affects community-level processes. Studies of the ocean microbiome’s diel processes have been published before, but never with so many diverse datasets that have the potential to connect the gene expression of large eukaryotic phytoplankton and small streamlined bacteria to the production of organic carbon. Having so many concurrent measurements to synthesize was both a blessing and a curse – with each data set comes caveats and considerations that must be taken into account before drawing biological or ecological conclusions. However, because each dataset provides a slightly different window into the microbial community, integrating many different datasets provides more power to conclusions we may be able to draw.
Given these challenges, we initiated a synthesis effort to adapt quantitative ecological frameworks and complex systems analysis to the large datasets – just as essential as all the seawater we filtered back in 2015. Our large team gathered in a series of multi-day workshops (pre-COVID and then, leveraging video calls during COVID) to plan, analyze, and discuss data analysis and emergent patterns. Not all the data was analyzed at first, but when it was, we decided to let the data speak for itself rather than impose assumptions about what should be happening when, and how components might be related. The simple initial questions we asked were “Which of these thousands of biological variables has 24-hour periodicity?” and “In all of those diel variables, are there common patterns in the timing and shape of their oscillations?”. We found that there were diel oscillations in gene expression and biomolecular concentration which were well described by four types of oscillations (ones that had peak times in the morning, afternoon, dusk at night).
We then asked, “Do certain processes occur at specific times of day for broad groups of organisms?”. After grouping taxa into the coarse taxonomic bins “cyanobacteria”, “heterotrophic bacteria”, and “eukaryotic phytoplankton” we found that many, but not all, processes were synchronized across these groups (Figure 2). We were encouraged by the fact that we found cyanobacteria and eukaryotic phytoplankton to be expressing photosynthesis transcripts in the morning, something that has been found previously in oceanic ecosystems. Though sometimes finding what others have found can feel kind of ‘blah’, it also provides more confidence in other, newer results. The diversity and breadth of our datasets allowed us to demonstrate not only the photosynthesis activity, but the resulting accumulation of fixed carbon, and the response by heterotrophic bacteria, which synchronously expressed both sugar transporters and carbon metabolism genes.
Though carbon metabolisms were amazingly synchronous, we found that nitrogen metabolism was often asynchronous. Transcription of genes associated with nitrogen acquisition and assimilation had 24-hour periodicity for many different organisms, but the timing of the transcription was spread across the day and night. This finding leaped off the R-console when we were analyzing which KEGG orthologues with diel cycles had the most similar oscillations across multiple organisms – many of the genes with the least synchronized expression across organisms were related to nitrogen utilization. Our interpretation of this finding draws on the ecological concept of the temporal storage effect, where organisms specialize in growing at different times instead of competing simultaneously for resources. When considering a single nitrogen substrate, such as ammonia, different timing of its uptake can be thought of as organisms occupying different temporal niches. Alternatively, taking up a different form of nitrogen, such as an amino acid, can be thought of as partitioning types of resources that fill the same requirement. Both temporal niche partitioning and substrate partitioning reduce competition and can help to maintain species coexistence. We found evidence for both types of resource partitioning occurring with diel periodicity. Convincing ourselves and our coauthor team of these findings was no easy task. However, the multiple types of data again benefited us, with the diel oscillations of nitrogen-containing biomolecules adding corroborating evidence.
Indeed, the diel cycle was imprinted on all types of cellular processes and biomolecule concentrations, even those, like iron acquisition, that we would not necessarily expect. Having thought about diel cycles for over 7 years, we don’t think we’ll ever again consider an ecological question without at least a bit of that framework in mind.
After all, timing is everything.
The authors would like to thank Audra Davidson (Georgia Tech) for help with preparing this blog post.
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