Summary of Study ST001197
This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR000807. The data can be accessed directly via it's Project DOI: 10.21228/M8CD73 This work is supported by NIH grant, U2C- DK119886.
See: https://www.metabolomicsworkbench.org/about/howtocite.php
| Study ID | ST001197 |
| Study Title | GC-MS Analysis of Insoluble/Polymeric Amino Acids (part-III) |
| Study Summary | Cyanobacteria are a model photoautotroph and a chassis for the sustainable production of fuels and chemicals. Yet, knowledge of photoautotrophic metabolism in the natural environment of day/night cycles is lacking yet has implications for improved yield from plants, algae, and cyanobacteria. Here, a thorough approach to characterizing diverse metabolites—including carbohydrates, lipids, amino acids, pigments, co-factors, nucleic acids and polysaccharides—in the model cyanobacterium Synechocystis sp. PCC 6803 (S. 6803) under sinusoidal diurnal light-dark cycles was developed and applied. A custom photobioreactor and novel multi-platform mass spectrometry workflow enabled metabolite profiling every 30-120 minutes across a 24-hour diurnal sinusoidal LD (“sinLD”) cycle peaking at 1,600 mol photons m 2 s-1. We report widespread oscillations across the sinLD cycle with 90%, 94%, and 40% of the identified polar/semi-polar, non-polar, and polymeric metabolites displaying statistically significant oscillations, respectively. Microbial growth displayed distinct lag, biomass accumulation, and cell division phases of growth. During the lag phase, amino acids (AA) and nucleic acids (NA) accumulated to high levels per cell followed by decreased levels during the biomass accumulation phase, presumably due to protein and DNA synthesis. Insoluble carbohydrates displayed sharp oscillations per cell at the day-to-night transition. Potential bottlenecks in central carbon metabolism are highlighted. Together, this report provides a comprehensive view of photosynthetic metabolite behavior with high temporal resolution, offering insight into the impact of growth synchronization to light cycles via circadian rhythms. Incorporation into computational modeling and metabolic engineering efforts promises to improve industrially-relevant strain design. |
| Institute | Colorado State University |
| Department | Chemical and Biological Engineering |
| Last Name | Peebles |
| First Name | Christie |
| Address | 700 Meridian Ave, Fort Collins, CO 80523 |
| christie.peebles@colostate.edu | |
| Phone | 970-491-6779 |
| Submit Date | 2019-03-02 |
| Raw Data Available | Yes |
| Analysis Type Detail | GC-MS |
| Release Date | 2019-07-17 |
| Release Version | 1 |
Select appropriate tab below to view additional metadata details:
Combined analysis:
| Analysis ID | AN001993 |
|---|---|
| Analysis type | MS |
| Chromatography type | GC |
| Chromatography system | Thermo ISQ |
| Column | Trace 1310 GC |
| MS Type | EI |
| MS instrument type | GC-TOF |
| MS instrument name | Thermo ISQ |
| Ion Mode | POSITIVE |
| Units | spectral abundance per cell |
MS:
| MS ID: | MS001846 |
| Analysis ID: | AN001993 |
| Instrument Name: | Thermo ISQ |
| Instrument Type: | GC-TOF |
| MS Type: | EI |
| MS Comments: | Raw data was converted to *.CSV with Waters® Databridge. For idMS/MS (RP-LC-MS runs), a file was converted for low-collision, high-collision, and LockSpray for each sample. Peaks were detected within the XCMS workflow using the Centwave algorithm (Smith et al. 2006). |
| Ion Mode: | POSITIVE |
