Future Research Leaders
I am extremely happy to share the news that the Swedish Foundation for Strategic Research has selected me as one of 16 young research leaders to receive their 15 million SEK grant awarded to give newly established researchers with high scientific and pedagogical competence the opportunity to develop as research leaders.
This grant is one of the more prestigious grants for young researchers in Sweden that I know of and I am very honored and thankful, both towards the foundation and my research group who have made this possible, to receive this grant. In combination with the DDLS funding from the Wallenberg Foundation, this will provide the lab with some very nice opportunities to explore more far-reaching endeavors in the next couple of years, which sets the stage for a very exciting half-decade to come!
Finally, I am also happy to see (after my ten-years old criticism of the gender distributions of these grants) that the distribution of grants this year was approximately gender-equal (seven out of 16 recipient were women). This is a good sign for both future Swedish research and the trustworthiness of these grants themselves.
Get ready for the future: Microbial Community Systems Biology
Phil Goetz at JCVI recently posted his reflections from the Summit of Systems Biology. I was not there, but I read his summary with interest. Now, what strikes me as interesting is the notion that “there were no talks on metagenomics. This also struck me as odd; bacterial communities seem like a natural systems biology problem.” Having been working with microbial communities for a while, I am surprised that the modeling perspective that is so prevalent in macro-organism ecosystems ecology have not yet really come to fruition in microbial ecology. With the tremendous amounts of sequences that are pouring over us from microbial communities, and with the plethora of functional metagenomics annotation that is made, how come that there has been so little research in the actual interactions between microorganisms within e.g. biofilms?
The problem is also connected to the lack of time-series data from community research. To be able to understand how a system behaves under changing conditions, we need to measure its reactions to various parameter changes over time. Instead of pooling metagenomes to reduce temporal “noise” we need to be better at identifying the changing parameters and then use the temporal differences to look for responses to the parameter changes. By applying a functional metagenomics perspective at each sample point, combining this with measured changes in community species structure (as measured e.g. by 16S or some other marker gene), and correlating this with changes in the parameters, we should be able to build a model of how the ecosystem responds to changing environments. With the large-scale sequencing technologies available today, and the possibilities given by metatranscriptomics, these ideas should be challenging but not impossible.
I am not saying that any of these things have not been done. But it has been done to a surprisingly small extent. I would highly appreciate reading a paper trying to build a mathematical model of how the ecosystem functions in bacterial communities shift in response to an environmental stressor. Because when someone builds such a model we suddenly have a tool to take microbial community research from an explorative perspective to an applied one. The applied perspective will be useful for actually protecting environments and ecosystem services, as well as for understanding how to manipulate microbial ecosystems to maximize the outtake beneficial to society. Also, the understanding the ecosystem dynamics of microbial systems could be carried over to macro-ecosystems and provide a small-scale ecosystem laboratory for all ecosystem research. Such a shift towards applied microbial community systems biology will be more or less necessary to be able to argue for more resources and time being spent on e.g. metagenomics. And I believe that we will soon be there, because the step is shorter than we might imagine.