Sneak preview: manuscript almost ready for submission!
It has been a while since the last update. As you might remember, I moved across the ocean to continue my work at the Ludwig Maximilians University, which slowed things down work wise. Next to that, I am in the last year of my current Fellowship. This means that I am frantically writing job and grant applications at the moment to try and stay in the academic game and continue my research. However, while this slowed things down a little bit, I have been working on our transcriptomics project and I am very excited to report that we are nearing the finishing of the manuscript and will soon get ready to send it off for peer review!
But let's rewind and recall how it all started. Of course it started by me starting a crowd funding campaign with the help of the Experiment.com crew to fund this idea of trying to take the first steps to figure out what genes are in play when Ophiocordyceps fungi turn ants into zombies, and you all jumped in and generously donated! Subsequently, I went back to the lab to infect ants with Ophiocordyceps and collected the following samples:
These samples were subsequently used to extract RNA. We look at RNA because this gives us an indication which genes are being actively used during a certain situation. For example, if the fungus uses (aka expresses) a certain gene during manipulation that encodes for a neuromodulator, but it doesn't use that gene when manipulation has taken place and the ant has died, we will find a lot of RNA corresponding to that gene in the samples that we collected at the time of manipulation and far less in the dead ant samples. This looking at gene expression of an entire genome is called a transcriptome. When you have samples that contain the gene expression from 2 organisms at the same time we call this a mixed transcriptome.
Subsequently we sequenced these RNA samples using a technique called RNASeq. This results in millions of short pieces called reads. They are like little puzzle pieces that have to be placed in the right order to be able to know what genes they were transcribed from and how high the expression of that gene is. Initially, we tried to solve the puzzle by generating a de novo transcriptome from the reads from the control samples to use as a reference for our mixed infected ant samples: ant reads would map to the de novo ant transcriptome and fungal reads would map to the de novo fungus transcriptome. Long story short: whatever we tried, this resulted in a mess with fungal reads accidentally mapping to the ant reference and vice versa, so using the data this way we would maybe end up drawing the wrong conclusions.
To solve this problem we used the ant and fungus genomes as templates to place our RNA reads in the right order (aka map our reads) instead. To be able to do this, we first had to generate a genome for our Ophiocordyceps fungus because it hadn't been sequenced yet. Our Carpenter ant host has also not been sequenced, but another Carpenter ant has been so we used the genome of this related species. To visualize what we did, here is a schematic:
After mapping all the RNA reads we calculated which genes are higher or lower expressed in the infected ant samples versus their controls. We also looked at how gene expression changes between the situation in which the ant is being manipulated and still alive, and the situation in which manipulation has taken place and the ant had died.
Our hypothesis is that the expression of the genes involved in manipulated biting behavior go up during this event when compared to the control culture and down again after manipulation has taken place, the ant has died, and the fungus is going to switch to making the spore carrying structure to be able to spread to the next ant hosts. Following this logic we've found an array of genes that from the function assigned to them look very interesting and could very well be involved in manipulation! Here's a graph displaying the expression of some of the fungal neuromodulator candidates we found:
Comparing the genome of Ophiocordyceps with other fungal insect pathogens that don't manipulate behavior, we found that this fungus is indeed quite remarkable since the majority of the genes that show a significantly higher expression only during manipulated biting behavior, are not conserved in other insect pathogen genomes. Some of these genes are even completely unique for Ophiocordyceps and we don't know anything about their putative functions yet.
Now, the function of the candidate neuromodulators that we were able to identify I won't discuss here just yet as I need to leave some surprises for the actual publication :-). After publication, I will write a breakdown again of the paper itself, but I hope this sneak preview gives you already an idea of what to expect.
Talking about publication.....
As promised we are going to submit this work to an open access journal, so you, the crowd who chipped in to make this project happen, can actually read it without being blocked by paywalls. Moreover, I would like to try to get all the backers mentioned in the acknowledgements! Of course we'll have to see if the journal will agree to this as with over 100 backers this will make for quite a lengthy thank you note :-)! But it's worth a try. I would however need your consent to be mentioned so I would need you to do the following:
IF YOU'RE A BACKER OF THIS PROJECT WHO WOULD LIKE TO BE NAMED IN THE ACKNOWLEDGEMENTS, PLEASE SEND ME AN EMAIL IN WHICH YOU STATE YOUR NAME AND THAT YOU'D BE OKAY WITH BEING NAMED IN THE ACKNOWLEDGEMENT SECTION OF THE PAPER.