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Metabolic role of aldehyde dehydrogenases in <i>Pseudomonas putida</i> KT2440

2020· article· en· W3020700237 on OpenAlexaff
Adriana Julián‐Sánchez, Adeli P. Castrejón-Gonzaga, Gabriel Moreno‐Hagelsieb, Rosario A. Muñoz‐Clares, Héctor Riveros‐Rosas

Bibliographic record

VenueThe FASEB Journal · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAmino Acid Enzymes and Metabolism
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsPseudomonas putidaAldehyde dehydrogenaseBiologyPhylogenetic treeGeneBacteriaGeneticsPhylogeneticsGenomeBiochemistry

Abstract

fetched live from OpenAlex

Pseudomonas is one of the most complex bacterial genera and is currently the genus of Gram‐negative bacteria with the largest number of species. Pseudomonas include a metabolically versatile group of organisms that are known to occupy numerous ecological niches. Pseudomonas putida is a non‐pathogenic, soil bacterium with a flexible and robust metabolism. P. putida KT2440 possesses a large genome (5,564 genes), lending to its adaptability to varying environments. The repertoire of P. putida genes, which are substantially conserved among different strains, is populated with sophisticated regulatory systems that are foundational to respond and adapt to diverse environments. P. putida KT2440 possesses an unexpected high number (32) of aldehyde dehydrogenase ( aldh ) genes (by comparison humans possess only 19 different aldh genes), but only a few of these ALDHs have been characterized. To obtain insights about the metabolic role performed by each one of the 32 ALDHs found in P. putida KT2440, the genomic neighborhoods of aldh genes were analyzed and compared with neighborhoods in other Pseudomonas strains. Thus, phylogenetic analyses and genomic context data of aldh genes were used to predict the functional role of ALDHs in P. putida KT2440. Our results show that ALDHs belong to 24 different ALDH families. Among them, we found ALDH families 3, 4, 5, 6, 7, 9, 10, 11, 14, 18, 21, 26, 27, and 28, as well as 10 additional families not named yet by the ALDH nomenclature committee (ALDH28 family is also called cd07129 by NCBI’s Conserved Domain Database (CDD) < https://www.ncbi.nlm.nih.gov/cdd >). These ALDHs seem to play several metabolic roles such as glyceraldehyde 3‐phosphate and succinate semialdehyde metabolism, betaine aldehyde and proline synthesis, beta alanine, propanoate and amino acids catabolism, among others. It is interesting to note that P. putida KT2440 possesses several ALDH isoenzymes that belong to the same family. Three ALDH proteins from P. putida KT2440 belong to the ALDH28 family, while each of the families 5, 6, 14, 26, 27 and 29 is represented by two ALDH proteins (ALDH29 family is also called cd07100 by NCBI’s CDD). This diversity, as well as the genomic context of the corresponding a ldh genes, suggest that different ALDH isoenzymes within a same ALDH family are used to challenge different metabolic conditions. These results show that the metabolic role of a particular ALDH protein is dependent of both, kinetic properties of the enzyme as well as the proteins that are coexpressed with it (operon). Therefore, a specific ALDH family can participate in more than one metabolic pathway, thus contributing to the ability of this bacterium to survive and adapt to varying environments. Support or Funding Information Supported by DGAPA‐UNAM grant IN218819. Linear representation of Pseudomonas putida KT2440 chromosome 1, mapping 32 aldehyde dehydrogenase ( aldh ) gene loci. ALDH families are indicated between parenthesis. Figure 1

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.009
GPT teacher head0.218
Teacher spread0.209 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

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Citations1
Published2020
Admission routes1
Has abstractyes

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