Dataset: T. pseudonana starve-recover experiments: Cell information
Data Citation:
Orellana, M. V., Lausted, C., Huang, S. (2024) Diatom (Thalassiosira pseudonana) cell information from experiments designed to study single-cell transcriptional profiling of nutrient acquisition heterogeneity in diatoms conducted in December of 2022. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2024-01-30 [if applicable, indicate subset used]. doi:10.26008/1912/bco-dmo.918860.1 [access date]
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DOI:10.26008/1912/bco-dmo.918860.1
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Baliga Laboratory Institute for Systems Biology
Temporal Extent: 2022-12-04 - 2022-12-09
Project:
Program:
Principal Investigator:
Monica V. Orellana (University of Washington, FHL)
Co-Principal Investigator:
Christopher Lausted (Institute for Systems Biology, ISB)
Scientist:
Sui Huang (Institute for Systems Biology, ISB)
BCO-DMO Data Manager:
Amber D. York (Woods Hole Oceanographic Institution, WHOI BCO-DMO)
Version:
1
Version Date:
2024-01-30
Restricted:
No
Release Date:
2024-06-01
Validated:
Yes
Current State:
Final no updates expected
Diatom (Thalassiosira pseudonana) cell information from experiments designed to study single-cell transcriptional profiling of nutrient acquisition heterogeneity in diatoms conducted in December of 2022
Abstract:
This dataset includes cell information for diatom Thalassiosira pseudonana grown during experiments conducted as part of a study of "Single-Cell transcriptional profiling of nutrient acquisition heterogeneity in diatoms." See "Related Datasets" section for T. pseudonana physiological data and gene information collected as part of the same study and experiments.
Study description:
Diatoms (Bacillariophyceae) are unicellular photosynthetic algae, accounting for about 40% of total marine primary production (equivalent to terrestrial rainforests) and critical ecological players in the contemporary ocean. Diatoms can form enormous blooms in the ocean that can be seen from space and are the base of food webs in coastal and upwelling systems, support essential fisheries, and are central to the biogeochemical cycling of important nutrients such as carbon and silicon. Over geological time, diatoms have influenced the world's climate by changing the carbon flux into the oceans.
Diatoms have traditionally been studied on a population level. Growth is often measured by the total increase in biomass, and gene expression is analyzed by isolating mRNA from thousands or millions of cells. These methods generate a valuable analysis on the population’s average functioning; however, they fail to show how each individual diatom cell contributes to the population phenotype. Bulk transcriptomes confound different stages and variability of cell states in heterogeneous populations. By contrast, single-cell transcriptomics measures gene expression in thousands of individual diatoms providing a quantitative and ultrahigh-resolution picture of transient cell states in population fractions enabling the reconstruction of the various phenotypic trajectories. Thus, the single-cell physiological and molecular parameters analysis allows an unsupervised assessment of cell heterogeneity within a population—a new dimension in diatoms and phytoplankton in general.
In this dataset, we examine the model diatom Thalassiosira pseudonana clonal cells grown in different nitrogen conditions, at the single cell level when grown in a light: dark cycle (12:12 h). Nitrogen is the major limiting nutrient for primary production and growth in the ocean’s surface, specifically for diatoms and the food webs they support. We investigate nutrient limitation, starvation and recovery. We used droplet-based, single-cell transcriptomics to analyze ten samples in two stages. In the first stage ("starvation"), six samples were collected over four days of culture as nutrient levels decreased. In the second stage ("recovery"), four samples were collected over twelve hours after nutrients were replenished.