Soil microbial adaptation to carbon deprivation: shifts in lignocellulolytic gene profiles following long-term plant exclusion
Bibliographic record
Abstract
BACKGROUND: Lignocellulose represents a primary input of organic carbon (C) into soils, yet the identity of specific microorganisms and genes which drive lignocellulose turnover in soils remains poorly understood. To address this knowledge gap, we used a 10-year grassland plant-exclusion experiment to investigate how reduced plant C inputs affect microbial communities and their lignocellulolytic potential using a combination of metagenomic sequencing and untargeted metabolomics. We specifically tested the hypothesis that microbial community function in bare fallow plots would transition towards microbiota with genes for recalcitrant biomass degradation (i.e., lignocellulose), when compared to grassland plots with high labile C inputs. RESULTS: Long-term plant exclusion lowered soil C and nitrogen (N) and reduced cellulose content, whilst hemicellulose and lignin were unchanged. Similarly soil microbiomes were highly distinct in long-term bare soils, along with soil extracellular enzyme profiles, though short-term plant-removal effects were less apparent. Plant exclusion resulted in a general enrichment of Firmicutes, Thaumarchaeota, Acidobacteria, Fusobacteria, and Ascomycota, with a general reduction in Actinobacteria. However, changes in bare soil lignocellulose degradation genes were more associated with discrete taxa from diverse lineages, particularly the Proteobacteria. Grouping of lignocellulose-degrading genes into broad substrate classes (cellulases, hemicellulases and lignases) revealed a possible increase in lignin degradation genes under plant exclusion confirming our hypothesis, although all other changes were at the level of the carbohydrate-active enzyme (CAZy) family. Intriguingly, untargeted metabolome profiles were highly responsive to plant exclusion, even after only one year. Bare soils were depleted in oligosaccharides and enriched in monosaccharides, fatty and carboxylic acids, supporting emerging evidence of long-term persistent C being within simple compounds. CONCLUSIONS: Together our data show that extracellular lignin degrading enzymes increase under long-term plant exclusion. There is now a need for increased focus on the microbial metabolic mechanisms which regulate the processing and persistence of enzymatically released compounds, particularly in energy limited soils.
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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 | 0.000 | 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 | 0.001 |
| 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".