Transformation of Benzene Derivatives in Acidic Conditions by the Fungus Hormoconis Resinae – Reductive, Oxidative, or Both?
Bibliographic record
Abstract
Hormoconis resinae (or Cladosporium resinae ), colloquially known as the kerosene fungus, is predominantly found in fuel tanks (Rafin and Veignie 2018). Its occurrence in fuel tanks was first reported in early 1960s. Since then, it has been considered as a serious threat by the petroleum industry for bio-deteriorating fuel quality, corroding storage tanks, and clogging pumps and filters (Sheridan et al. 1971). This fungus flourishes well in the presence of water and can thrive at a wider pH range (2-10), than most commonly studied bacteria, with optimum towards the acidic end (Rafin and Veignie 2018). As a biosafety level 1 organism (ATCC 2021) with wide natural prevalence, H. resinae is both safe to study and apply in the field. Thus, it can be utilized for developing bioremediation processes suitable for petroleum-contaminated sites. Contamination of groundwater sources by fuel pollutants has been an important public health concern for decades (Mitra and Roy 2011). Several components of fuel are known to be toxic even at low concentrations with deleterious health effects including teratogenicity and carcinogenicity (ATSDR 1995). Past research has mainly focussed on the degradation of n-alkanes, a major component of fuel, by H. resinae which used the n-alkanes as sole carbon and energy sources (Rafin and Veignie 2018). Benzene derivatives like toluene, benzaldehyde, benzoic acid are also often found as fuel pollutants. Though some studies have investigated the effects of benzene derivatives on the survival and growth of H. resinae (Cofone et al. 1973, Oh et al. 2001, Qi et al. 2002), not much work has been done on their biodegradation (Kato et al. 1990). Previous study showed a reductive transformation of benzoate to benzaldehyde, benzyl alcohol, and 1-phenyl-l,2-propanediol (Kato et al. 1990). More work was needed to study the further transformation of these products. Thus, the current study focussed on the transformation of benzaldehyde and benzyl alcohol in acidic conditions by H. resinae ATCC 34066. The main objectives were to study the effects of: culture media, glucose, and oxygen enrichment on the fungal growth in the presence of these benzene derivatives and their biodegradation kinetics and pathways. culture media, glucose, and oxygen enrichment on the fungal growth in the presence of these benzene derivatives and their biodegradation kinetics and pathways. Some experiments were also conducted with toluene as the contaminant. H. resinae was not able to transform toluene (1-200 ppm) at all, though it was able to grow on it in the presence of 1% glucose. The fungus was able to transform benzaldehyde (≤550 ppm) to benzyl alcohol (reductive) and benzoic acid (oxidative). Many monoaromatics such as catechol, resorcinol, hydroxybenzoic acids and aliphatic compounds such as fumaric acid, levulinic acid were also detected as the oxidation products of benzaldehyde by high-resolution liquid chromatography-mass spectrometry. The presence of glucose slowed down benzaldehyde transformation but increased the benzyl alcohol formation relative to benzoic acid, probably due to the further slower transformation of benzyl alcohol. Oxygen enrichment enhanced the benzaldehyde transformation. Glucose was a preferred culturing media as fungus grown on potato dextrose agar (PDA) showed a 5-week lag phase for benzaldehyde transformation. However, this PDA-cultured fungus, after growing on benzaldehyde, did not exhibit a lag phase and started benzaldehyde transformation immediately. Transformation of benzyl alcohol, as target contaminant, was slower and incomplete in the presence of glucose. Benzyl alcohol was transformed mainly to benzoic acid via an oxidative pathway. In summary, this study has shown that H. resinae can transform the benzene derivatives via both oxidative and reductive pathways. Moreover, H. resinae can use these compounds as sole carbon and energy sources.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".