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Biochemical metabolomic profiling of the Crown-of-Thorns Starfish (Acanthaster): New insight into its biology for improved pest management

2022· article· en· W4310253058 on OpenAlexfundno aff
Omar Mendoza‐Porras, Thao V. Nguyen, Rohan Shah, Peter Thomas‐Hall, Lee Bastin, Dione J. Deaker, Cherie A. Motti, Maria Byrne, David J. Beale

Bibliographic record

VenueThe Science of The Total Environment · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicCoral and Marine Ecosystems Studies
Canadian institutionsnot available
FundersLizard Island Reef Research FoundationCanadian Orthopaedic Trauma SocietyAfrican Institute for Mathematical SciencesIan Potter FoundationCommonwealth Scientific and Industrial Research Organisation
KeywordsMetabolomicsMetaboliteBiochemistryStarfishBiologyHypoxanthineInosineAcanthasterAmino acidEnzymeCoral reefEcology

Abstract

fetched live from OpenAlex

The Crown-of-Thorns Starfish (COTS), Acanthaster species, is a voracious coral predator that destroys coral reefs when in outbreak status. The baseline metabolite and lipid biomolecules of 10 COTS tissues, including eggs from gravid females, were investigated in this study to provide insight into their biology and identify avenues for control. Targeted and untargeted metabolite- and lipidomics-based mass spectrometry approaches were used to obtain tissue-specific metabolite and lipid profiles. Across all COTS tissues, 410 metabolites and 367 lipids were identified. Most abundant were amino acids and peptides (18.7%) and wax esters (17%). There were 262 metabolites and 192 lipids identified in COTS eggs. Wax esters were more abundant in the eggs (30%) followed by triacylglycerols (TG), amino acids, and peptides. The diversity of asterosaponins in eggs (34) was higher than in tissues (2). Several asterosaponins known to modulate sperm acrosome reaction were putatively identified, including glycoside B, asterosaponin-4 (Co-Aris III), and regularoside B (asterosaponin A). The saponins saponin A, thornasteroside A, hillaside B, and non-saponins dictyol J and axinellamine B which have been shown to possess defensive properties, were found in abundance in gonads, skin, and radial nerve tissues. Inosine and 2-hexyldecanoic acid are the most abundant metabolites in tissues and eggs. As a secondary metabolite of purine degradation, inosine plays an important role in purine biosynthesis, while 2-hexyldecanoic acid is known to suppress side-chain crystallization during the synthesis of amphiphilic macromolecules (i.e., phospholipids). These significant spatial changes in metabolite, lipid, and asterosaponin profiles enabled unique insights into key biological tissue-specific processes that could be manipulated to better control COTS populations. Our findings highlight COTS as a novel source of molecules with therapeutic and cosmetic properties (ceramides, sphingolipids, carnosine, and inosine). These outcomes will be highly relevant for the development of strategies for COTS management including chemotaxis-based biocontrol and exploitation of COTS carcasses for the extraction of commercial molecules.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

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 head0.012
GPT teacher head0.216
Teacher spread0.204 · 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 designObservational
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".

Quick stats

Citations11
Published2022
Admission routes1
Has abstractyes

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