Pathway-Centric Analysis of Microbial Metabolic Potential and Expression Along Nutrient and Energy Gradients in the Western Atlantic Ocean
Bibliographic record
Abstract
Microbial communities play integral roles in driving nutrient and energy transformations in the ocean, collectively contributing to fundamental biogeochemical cycles. Although it is well known that these communities are stratified within the water column, there remains limited knowledge of how metabolic pathways are distributed and expressed. Here, we investigate pathway distribution and expression patterns from surface (5 m) to deep dark ocean (4000 m) at three stations along a 2765 km transect in the western South Atlantic Ocean. This study is based on new data, consisting of 43 samples for 16S rRNA gene sequencing, 20 samples for metagenomics and 19 samples for metatranscriptomics. Consistent with previous observations, we observed vertical zonation of microbial community structure largely partitioned between light and dark ocean waters. The metabolic pathways inferred from genomic sequence information and gene expression stratified with depth. For example, expression of photosynthetic pathways increased in sunlit waters. Conversely, expression of pathways related to carbon conversion processes, particularly those involving recalcitrant and organic carbon degradation pathways (i.e., oxidation of formaldehyde) increased in dark ocean waters. We also observed correlations between indicator taxa for specific depths with the selective expression of metabolic pathways. For example, SAR202, prevalent in deep waters, was strongly correlated with expression of the methanol oxidation pathway. From a biogeographic perspective, microbial communities along the transect encoded similar metabolic potential with some latitudinal stratification in gene expression. For example, at a station influenced by input from the Amazon River, expression of pathways related to oxidative stress was increased. Finally, when pairing distinct correlations between specific particulate metabolites (e.g., DMSP, AMP and MTA) and both the taxonomic microbial community and metatranscriptomic pathways across depth and space, we were able to observe how changes in the marine metabolite pool may be influenced by microbial function and vice versa. Taken together, these results indicate that marine microbial communities encode a core repertoire of widely distributed metabolic pathways that are differentially regulated along nutrient and energy gradients. Such pathway distribution patterns are consistent with robustness in microbial food webs and indicate a high degree of functional redundancy.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".