An Integrated Approach to Improving Efficiency in Photosynthetic Microbial Systems
Bibliographic record
Abstract
Cyanobacteria-based biotechnology is regarded as a promising opportunity for renewable bioenergy and bioproducts. As cyanobacteria are photosynthetic microorganisms, they only require sunlight, carbon dioxide, nutrients, and water to grow, and can be cultivated using non-arable land and non-potable water. These characteristics, along with their rapid growth rates and amenability to genetic modifications, merit research of cyanobacteria for roles in mitigating greenhouse gas emissions and carbon capture and sequestration. Despite these favourable attributes, cyanobacterial bioenergy has yet to become successful at an industrial scale. This thesis explores, through use of metagenomics, metaproteomics, growth experiments, and modelling, fundamental and applied strategies to improve the productivity and feasibility of cyanobacteria in biotechnology. A photosynthetic microbial mat, sourced from highly productive haloalkaline soda lakes, was previously used as inoculum for enrichment of a mono-cyanobacterial microbial consortium. In this thesis, the microbial composition and function of the productive haloalkaline lakes of origin were analyzed using metagenomics and metaproteomics (Chapter 2). This analysis showed high diversity and functional redundancy within the mat community, and suggested approaches for niche differentiation between phototrophic species, as well as mechanisms for lateral gene transfer and biogeographic dispersal. In Chapter 3, the cyanobacterial enrichment culture was used to conduct growth experiments in conjunction with red light transmitting filters, composed of organic semiconducting materials with the potential to produce electricity. These growth experiments were used to model photosynthesis and to determine under which conditions electricity-producing light filters could be advantageous to photosynthetic growth and overall energy output. Lastly, in Chapter 4, the cyanobacterial enrichment culture underwent a prolonged dark and anoxic incubation, similar to what might be experienced in their natural lake habitat. This incubation resulted in the lysis of cyanobacterial cells and release of a highly valued pigment compound, phycocyanin. The molecular mechanism behind the lytic process was investigated using metagenomics and metaproteomics. In conclusion, this body of work examined fundamental microbiological and ecological processes in a highly productive photosynthetic mat and used biological principles to facilitate improvement of cyanobacterial biotechnology systems.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".