GEODES Data Preview

We’ve been hard at work this fall processing all of the samples we collected for GEODES this summer. The RNA samples still need to be sequenced, but we’re already seeing some interesting trends in the environmental data we measured while sampling.

What have we been up to?

  • Extracting the RNA samples – we processed 108 in one day assembly-line style!
  • Measuring chlorophyll concentrations
  • Quantifying bacterial production (how much protein were the bacteria making)
  • Entering our written data into the computer. This is both more difficult and more important than it sounds.
  • Getting featured around the University of Wisconsin!


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What have we found? Many parameters in the lakes do show daily trends, but others do not. Sometimes a measurement was diel in one lake but not in the other! Below are some rough figures of what we’ve found -click on each plot for a larger image.

In the plots above, darker colors indicate warmer temperatures. The y axis is the depth we measured at, and the x axis is the hour the measurement was taken at. We collected our epilimnion (surface water) sample from the top to the black line. Mendota shows the strongest daily trends in temperature, and in its closely related measurement dissolved oxygen. This is also a good sanity check that we sampled at the right depth, as the black line should be at or slightly above the transition from warm to cool water.

In Lake Mendota and Trout Bog, conductivity and pH were closely correlated and changed right at the thermocline, where the temperature also sharply decreased.  Conductivity was uniformly low in Sparkling Lake, but the water does get slightly more acidic deeper down.

Chlorophyll is an interesting one. We expected this to follow diel trends because chlorophyll is produced to harvest energy from sunlight. It does in Trout Bog, but not in the other two lakes. Sparkling Lake, with its crystal clear waters doesn’t have much chlorophyll, as expected. But Mendota is notorious for its cyanobacterial blooms. What’s up with that?

Finally, the results of the bacterial production assays are pretty cool. The plots above show how much protein was being made at each time point, and is one measure of the “activity” of the microbial community. The first thing that jumps out is that there are time points with way more protein production than others, but that these high points are not at 24 hour intervals.

(Note: there can’t actually be negative protein production in Sparkling Lake. This means that the negative control for that time point was greater than the experimental samples, and that protein production was essentially zero).

What does this all mean?

It means we’re very curious about that RNA data.

  • Different process are indeed occurring in these three lakes, as shown by their differences in chlorophyll, protein production, and conductivity/pH.
  • Chlorophyll concentrations show diel trends in Trout Bog, but not Lake Mendota. Does this indicate different lifestyles or regulation strategies in photosynthetic microbes in these two lakes?
  • The timepoints with high bacterial production versus low bacterial production are very interesting. With the RNA data, we should be able to tell which taxa were active at the high time points (and not active in the low time points) AND what metabolic pathways they were using at that time.

Stay tuned for more updates as we get the RNA samples sequenced and analyzed!



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