Periodic Reporting for period 4 - EcOILogy (Microbial life in oil)
Okres sprawozdawczy: 2020-03-01 do 2020-08-31
We recently discovered microorganisms in minuscule water droplets (1-3 µl) entrapped in oil from a natural oil seep. In EcOILogy, I propose that biodegradation of oil resources takes place in such minuscule water droplets dispersed in the oil phase. EcOILogy aims to investigate the generic principles of life in oil. We study if such droplets are a common phenomenon in degraded oil resources and how significant the respective degradation activities are. To this end, we develop reverse stable isotope labelling (RIL) for quantifying minute microbial activities (WP 1). The droplets provide unique micro-ecosystems, all experiencing identical boundary conditions with no dispersal of microorganisms between the isolated droplets.
Outcome of the action: Microbial life in minuscule water droplets enclosed in heavy oil is a common trait of natural oil seeps. The water droplets are very densely populated and actively degrade the oil as indicated by reverse stable isotope labelling. The generation time of the microorganisms is around one year. Moreover, the composition of the microbial communities is strongly influenced by the lack of dispersal which also limits the adaptation of the community to environmental factors such as salinity. Lack of disperal also induces strong core communities.
We furthermore discovered that the text book concept of growth in batch cultures does not hold. In contrast to the classical textbook knowledge that the lag phase is a time where the cells adapt to the new cultivation conditions and express enzymes, the phenomenon of the lag phase is probably due to a mixture of active and inactive cells. Some cells grow exponentially from the beginning and outnumber the large background of inactive cells with time, which indicates the start of the logarithmic growth phase.
Thus, EcOilogy opens new horizons for microbial degradation of our most important energy resources with far-reaching implications for fundamental, interdisciplinary understanding of ecological processes, bioremediation, and oil exploration.
Analysing several droplets from oil sampled at the Pitch Lake in Trinidad-Tobago, we found that they contained a surprisingly high microbial density of approximately 10e9 cells/ml, which is equivalent to a dense Escherichia coli culture of OD 1 (Pannekens et al., 2020). Life-dead staining revealed that the cells are alive, which is supported by the ATP content per cell, which is equivalent to average values reported in the literature for microbial cultures. Computer tomography showed that the droplets are homogenously distributed in the oil with sizes ranging from nanoliter to µL. Droplets larger than 100 nL are densely populated while smaller droplets often did not contain microbes. We could also show that the minuscule water droplet can be found in different oil seeps indicating that they are a common trait of oil reservoirs (Pannekens et al., 2020). A large part of the cells is also present in biofilms on the oil-water interface with approximately 100 times more cells at the droplet wall compared to suspended cells in the droplet volume.
To measure the overall degradation activity of microorganisms in oil, we first developed a new method, the reverse stable isotope labelling (RIL). To this end, 13C-bicarbonate was added to the buffer system at 10 atom percent of 13C/12C. Biodegradation of oil leads to the evolution of 12C-CO2 and 13C-CO2 in a ratio of ca. 99/1 (close to natural abundance) which changes the stable isotope ratio of the buffer system (set to 10 atom %). Degradation of oil from the Pitch Lake in Trinidad was followed over three years and showed that RIL can be applied to measure oil degradation with autochthonous microbial communities. However, the activity measurements revealed extremely long generation times around 1 year, even when sulfate was added as electron acceptor.
We also investigated the microbial community assembly of the droplets and could show that dispersal is an essential parameter for the composition. The 16S rRNA genes of over 100 droplets were sequenced and the salinity was determined. Although salinity is known as a major parameter influencing microbial community compositions, the droplet communities were very similar despite different salinities. This indicates that the strictly isolated microbial ecosystems were not able to adapt to the different salinities, indicating the importance of dispersal for microbial ecosystem assembly. Moreover, we found that a microbial core community is also strongly dependent on dispersal since the droplets showed a surprising high core community compared to other systems. The data suggest that at very low and very high dispersal rates larger core communities are established. At medium dispersal rates communities differ more.
Raman microspectroscopy was applied for characterizing the metabolism of cells during the growth curve with 13C-label. The data suggest that during the lag phase a few cells start growing exponentially from the beginning which is normally not recognized because of the larger background of inactive cells. Only when the number of exponentially growing cells approaches the background numbers, this becomes visible as growth, indicating the transition from the lag phase to the logarithmic phase.
The results are published in several journals and presented on conferences.
A major outcome is the discovery of the essential role of dispersal for microbial community assembly and adaptation to environmental conditions. In the absence of dispersal, microbial communities did not show significant adaptation to environmental parameters such as salinity, which is otherwise known as a dominant determinant of community compositions. Furthermore, limited dispersal can lead to high taxonomic predictability and core communities.
We also developed a new concept explaining the classical growth curve of batch cultures. We found that the apparently slow increase of cell numbers in the lag phase is not due to the adaptation of cells to the new conditions as described in text books. Rather, a few cells start growing logarithmically from the beginning which cannot be seen in the large background of the inactive cells from the inoculum. With time, the growing cells approach the number of inactive cells which becomes visible as a slow increase of cell numbers and the transition to the logarithmic phase.