Editorial: Aerobic and anaerobic fermentation of gaseous and liquid one carbon feedstocks to produce food, feed, biopolymers and value-added products
Bibliographic record
Abstract
Alliance to Feed the Earth in Disasters, Fairbanks, United States Correspondence: m.lackner@circe.at Dear readers, We are proud to present you 9 articles by 54 leading authors from industry and academia around the topics of microbial utilization of one-carbon feedstocks and gas fermentation. Fermentation is among the oldest technologies of mankind, and biocatalysts are known to offer low-cost and selective production of various target products, from commodities such as fuels to high-value compounds such as bioactive and pharmaceutical ingredients. First generation biofuels have shown that competition over agricultural land can lead to determinantal effects, amongst them price pressure on feed and food, direct and indirect land use change, putting pressure on our climate, and resource consumption, e.g. of fertilizers and water. Biobased and/or biodegradable polymers (bioplastics), alternative proteins, and other compounds of interest should ideally be made from waste resources, such as agricultural and forest residues, or industrial waste streams (both liquid and gas). Significant research efforts have been undertaken to develop more efficient processes for lignocellulosic hydrolysis, to provide 2 nd generation fermentable sugars, but it has yet to fulfill scaling projections. An alternative concept is to convert waste biomass into gaseous feedstocks, amongst them biogas (from wet biomass) and synthesis gas (from dry biomass), yielding well-defined feedstocks in the form of CO, CO2/H2 and CH4, which can be subjected to gas fermentation. Alternatively, (electro)chemical catalysis can be used to generate syngas, methanol or formate from CO2 and renewable electricity or H2. CO2 is in this context can either originate from industrial point sources or direct air capture. Methanol and CH4 have already been used at scale, and with renewable electricity becoming more widely available, power-to-gas processes and electrosynthesis open the way for additional one-carbon feedstocks such as CO2 which is also available from various point sources.This research topic includes two articles describing the potential of aerobic methane utilization and upgrading into single cell protein (García Martínez and coworkers) or PHB (Safaeian and coworkers). Salusjärvi and coworkers describe a potential bioproduction scenario for the biopolymer precursors beta-alanine and L-lactic acid using metabolic engineering of the aerobic, facultative lithoautotrophic strain Rhodococcus opacus. Production of both compounds could be demonstrated using CO2, H2 and O2, and in the case of beta-alanine also in an electrobioreactor set-up using CO2 and providing H2 and O2 by water electrolysis. Another litoautotroph, the well-studied gram-negative Cupriavidus necator was adapted by Wickham-Smith and coworkers to higher tolerance of carbon monoxide, thus enabling the use of syngas by C. neactor in bioproduction processes. The work of Dahlin and coworkers is another example of one carbon utilization with a non-model organism, in this case the microalgae Picochlorum renovo which was engineered for photoformatotrophy, ie. utilization of formate driven by energy harvested from light. Shirvani and coworkers presented a concept for a process chain from biomass to methanol using biomass gasification and chemical syngas-tomethanol conversion to provide the model feedstock. It could be demonstrated that the model aerobic, methylotrophic yeast Komagataella phaffii is able to grow on ammonia generated during biomass gasification as a by-product, thus paving the way for nitrogen recovery from low-value biogenic feedstocks. In the context of methylotrophy, Singh and coworkers review the development of microbial platforms to enable a methanol-based bioindustry. Anaerobic one-carbon feedstock utilization by acetogens is another interesting route for carbon-and energy-efficient bioproduction. The work of Nogle and coworkers in this research topic describes the discovery of a plasmid replication origin in the model acetogen Clostridium autoethanogenum and its utilization in heterologous expression of the pathway for isopropanol production. Finally, a thermostable and anaerobic fluorescent marker is described by Hocq and coworkers which was used to characterize a promoter library in the thermophilic acetogen Thermoanaerobacter kivui.We wish you many insights from the articles in this "Frontiers in Bioengineering and Biotechnology" topic.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.005 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.010 | 0.010 |
| Insufficient payload (model declined to judge) | 0.033 | 0.023 |
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".