Periodic Reporting for period 1 - INGENE (Integrating Nutrient economy in phytoplankton GENomics and Evolution)
Reporting period: 2021-06-01 to 2023-05-31
Phytoplankton are a diverse group of unicellular photosynthetic microorganisms. They are responsible for half of global primary production, produce as much oxygen as plants, and fuel aquatic food webs. Phytoplankton transform inorganic forms of Carbon (CO2), Water (H2O), Nitrogen (N) and Phosphorus (P) into organic macromolecules. Phytoplankton is often limited by the availability of N and P. An increased understanding on how phytoplanktonic microorganisms respond to N and P availability is critical to predict changes affecting phytoplankton communities and, therefore, the functioning of aquatic ecosystems. This is particularly important under the current global change scenario, which is associated with changes in nutrient availability. While previous studies have unraveled different genomic strategies of the bacterial planktonic component in response to nutrient limitation, little is known about the genomic strategy of planktonic eukaryotes. This project leverages the biological and genomic resource available in ubiquitous marine eukaryotic picoalgae, which are the smallest (cell diameter <2 µm) eukaryotic phytoplankton and may represent up to 80% of the biomass in coastal environments. During this Marie Sklodowska Curie action (MSCA), I have combined bioinformatic analyses with laboratory experiments to investigate the impact of nutrients on the genomic structure and evolution of phytoplankton.
The first objective of INGENE project was about the short-term (hours) physiological responses of phytoplankton to N and P deplete conditions. We used batch cultures of Ostreococcus tauri, which is the smallest eukaryotic algae on Earth, to analyze the changes in the cellular elemental composition and gene expression associated with changes in N and P availability (Figure 1). This was a large scale experiment, 60 samples have been saved for C, N, P analyses and centrifuged to analyze messenger RNA (ie gene expression). The RNA extraction was already performed and sequencing is planned during the summer 2023. We expect changes in gene expression depending on N and P levels, and differences in the N and P content of the genes expressed under low and high nutrient levels.
The objectives 2 and 4 of INGENE aimed at analyzing the long-term signatures of N and P scarcity on phytoplankton genomes. I compiled a dataset of N and P content from complete genomes and protein coding genes for prokaryotic and eukaryotic species. I also compiled the cellular P and N content from a literature survey and estimated these values for 5 additional species from measurements performed in the laboratory. I joined both datasets and found an association between the P content of the genome sequence and the total P content of the cell. Moreover, I estimated that the P content of the genome represents up to 57% of the total P content of the cell in phytoplankton species. This is higher than the N content of the genome, which represents up to 9% of the total N content of the cell. As a consequence, selection on DNA mutations changing the P or N content of the genome may have a non-negligible impact on genome evolution. I investigated this hypothesis by the analysis of a mathematical model linking the growth rate of phytoplankton to the P requirement of a cell. This approach enabled me to explore the size of deletion mutations, which decrease genome P content, susceptible to be selected for in natural populations.
I also investigated the N economy in the RNA and proteins of phytoplankton. Amino acids, which are the molecules that form proteins, are coded by messenger RNA sequences of three nucleotides, which are called codons. Some amino acids can be coded by more than one codon, and those codons that code for the same amino acid are called synonymous codons. A higher frequency of N cheap codons has been previously reported in plants and bacteria. The effect of changes in the usage of synonymous codons on the N requirements in messenger RNA scales up with the number of mRNA copies, so that we expect important gene to gene variations as there is a 4 order of magnitude difference between lowly expressed and highly expressed genes. I investigated if selection for N content was detectable on highly transcribed genes and found evidences that codon usage was more biased towards N poor codons in highly expressed genes. I will complete these analyses in the coming months.
The third objective was about estimating the effect of N and P on phytoplankton mutations. In collaboration with Dr. Krasovec, a CNRS research fellow from the host laboratory, we performed mutation accumulation (MA) experiments using phytoplankton cultures that grew with low N and P levels. We hypothetisize that low N and P levels might promote the occurence of mutations, as these low nutrient levels can be stressful for phytoplankton. Some of the mutation accumulation lines produced during MA experiments were already sequenced and the rest are being currently sequenced. I am currently analyzing the data.
The objectives 2 and 4 of INGENE aimed at analyzing the long-term signatures of N and P scarcity on phytoplankton genomes. I compiled a dataset of N and P content from complete genomes and protein coding genes for prokaryotic and eukaryotic species. I also compiled the cellular P and N content from a literature survey and estimated these values for 5 additional species from measurements performed in the laboratory. I joined both datasets and found an association between the P content of the genome sequence and the total P content of the cell. Moreover, I estimated that the P content of the genome represents up to 57% of the total P content of the cell in phytoplankton species. This is higher than the N content of the genome, which represents up to 9% of the total N content of the cell. As a consequence, selection on DNA mutations changing the P or N content of the genome may have a non-negligible impact on genome evolution. I investigated this hypothesis by the analysis of a mathematical model linking the growth rate of phytoplankton to the P requirement of a cell. This approach enabled me to explore the size of deletion mutations, which decrease genome P content, susceptible to be selected for in natural populations.
I also investigated the N economy in the RNA and proteins of phytoplankton. Amino acids, which are the molecules that form proteins, are coded by messenger RNA sequences of three nucleotides, which are called codons. Some amino acids can be coded by more than one codon, and those codons that code for the same amino acid are called synonymous codons. A higher frequency of N cheap codons has been previously reported in plants and bacteria. The effect of changes in the usage of synonymous codons on the N requirements in messenger RNA scales up with the number of mRNA copies, so that we expect important gene to gene variations as there is a 4 order of magnitude difference between lowly expressed and highly expressed genes. I investigated if selection for N content was detectable on highly transcribed genes and found evidences that codon usage was more biased towards N poor codons in highly expressed genes. I will complete these analyses in the coming months.
The third objective was about estimating the effect of N and P on phytoplankton mutations. In collaboration with Dr. Krasovec, a CNRS research fellow from the host laboratory, we performed mutation accumulation (MA) experiments using phytoplankton cultures that grew with low N and P levels. We hypothetisize that low N and P levels might promote the occurence of mutations, as these low nutrient levels can be stressful for phytoplankton. Some of the mutation accumulation lines produced during MA experiments were already sequenced and the rest are being currently sequenced. I am currently analyzing the data.
INGENE project will contribute to increase the mechanistic understanding of the effect of nutrients on phytoplankton. This is particularly important under the current global change scenario. Nutrient concentrations are increasing in coastal areas due to human activities, and decreasing in other oceanic zones due to changes in water temperatures and currents. Therefore, knowing how mutation rates and short-term physiological responses are impacted by nutrient levels can contribute to figure out the capacity of phytoplankton to adapt to these new nutrient conditions.
INGENE integrates genomics, bioinformatics, and ecophysiology. The multidisciplinary framework provided by this project can be accommodated to other resources (e.g. organic compounds) and organisms (e.g. yeast, bacteria, plants, animals). In this way, INGENE can contribute to investigations carried out in other model organisms and scientific fields.
INGENE integrates genomics, bioinformatics, and ecophysiology. The multidisciplinary framework provided by this project can be accommodated to other resources (e.g. organic compounds) and organisms (e.g. yeast, bacteria, plants, animals). In this way, INGENE can contribute to investigations carried out in other model organisms and scientific fields.