Award: OCE-1633939

Natural microbial communities in the ocean are the primary drivers of organic carbon turnover, acting as catalysts for the uptake, synthesis, and degradation of different molecules that can be transferred between species as food or signals. For decades, the ability to measure the expression of thousands of cellular functions persisting in a natural marine microbial community in situ and link these functions to carbon cycling has been a research goal. Since proteins carry out the majority of molecular functions and are tightly regulated within the cell, the characterization, quantification, and the timing of expression of proteins and how that can reflect their activity and metabolic goals has been a central theme of this project.  Although there have been studies that have successfully linked bacterial metaproteomic (i.e. community proteomic) responses to important biogeochemical cycles in situ, most metaproteomic analysis pipelines are adaptations of traditional single-species proteomic methods developed for simple single-organism environments. Complex communities, such as an ocean microbiome, contain thousands of different species. The complexity of all the possible protein sequences and the relatedness due to co-evolutionary histories generates complications when assigning peptide mass spectra to proteins from specific species. In many cases, an identified peptide can be found in homologous proteins originating from different members in the community. We have improved upon the accuracy of microbiome-based proteomics by creating and making available an open source algorithm that allows investigators to examine complex communities and track their changing functions and taxonomic structure through the accurate peptide assignments, avoiding protein inferences.

In our recent publications we have demonstrated that our methods allow us to simultaneously track >20 classes of bacteria and, in doing so, we revealed that the ocean microbiome’s functional roles with and without algal input reveal different metabolic strategies through time. Importantly, we observed that carbon acquisition and degradation precedes nitrogen acquisition when algal particulate organic matter is provided as a food source and these additions of food did not change the community structure through time. In fact, three dominant bacteria classes controlled the flow of carbon and nitrogen in these complex Bering Strait microbiomes. Over our relatively short time course of six days, the functions attributed to these classes changed as a function of time under different nutrient inputs. Most interestingly, we discovered that the rate of change of functions expressed by the microbiome is faster than the rate of change of the taxonomic composition suggesting that within these complex communities, the diversity of enzymes encoded in bacterial genomes allows the community to adapt to and utilize new food additions or changing environmental conditions over six days. We also revealed that microbiome communities that receive an input of food they are not accustomed to will have a lag of 2-3 days prior to actively transferring and degrading the organic matter. Despite significant difference in community taxonomic distributions, the process of organic degradation showed a high degree of functional consistency. At least for the Arctic Ocean, this observation argues that bacterioplankton collected from different water masses and having differing taxonomy may nevertheless have a predictable order and high degree of functional consistency in the cycling of materials.

The cycling of organic material in the ocean is dependent on complex microbial communities that collectively metabolize, degrade and recycle organic material. The insights from our peptide-centric approach suggests that functional responses of microbial communities are shared across diverse taxonomic groups. These results should encourage researchers to consider a broader view of protein synthesis rather than to rely on select enzymes or element specific pathways. The conclusions are clear that many functional responses can cross major bacterial class levels and suggests that, at least for Arctic microbial communities, bacterioplankton from different water masses and having differing taxonomy may nevertheless have a predictable order and high degree of functional consistency driving biogeochemical profiles.  

Broader Impacts. This project and the long-term collaboration on which it was built acted as a conduit for interdisciplinary training of graduate students and postdocs in both research and minority serving institutions. This award supported 2 Ph.D.’s who received highly interdisciplinary training and 5 undergraduate students at ODU and UW. Lab members in the Nunn group have mentored 4 high school students who identify as females on projects resulting in three 1^st place prizes in the Washington State Science Fair Research Division BioExpo and received monetary scholarships.

We have developed an algorithm and accompanying web application for automated analysis and visualization of meta-proteomics search results. This tool is now a web application (https://www.yeastrc.org/metagomics) and is currently used by those studying environmental and human-based microbiomes.

All chemical data and raw and processed mass spectrometry files and software reside in publicly available databases for use by multiple communities and all methods and findings have been reported in 9 peer-reviewed publications.

 

Last Modified: 01/08/2021
Modified by: Brook L Nunn