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Record W4385663766 · doi:10.3389/fmars.2023.1152647

Characterizing host-pathogen interactions between Zostera marina and Labyrinthula zosterae

2023· article· en· W4385663766 on OpenAlexaff
Yaamini R. Venkataraman, Amanda Shore, Sukanya Dayal, James Sanghyun Lee, Mahsa Alidoost Salimi, Grace Crandall, Malina M. Loeher, Mark Stoops, Megan Swanger, Morgan E. Eisenlord, Kathryn L. Van Alstyne, Mark D. Fast, Colleen A. Burge, Maya L. Groner

Bibliographic record

VenueFrontiers in Marine Science · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal plant biology
Canadian institutionsUniversity of Prince Edward Island
FundersDivision of Ocean SciencesUniversity of WashingtonNational Science Foundation
KeywordsZostera marinaBiologyTranscriptomePathogenHost (biology)SeagrassShootBotanyFoundation speciesEcologyEcosystemMicrobiologyGeneGene expressionGenetics

Abstract

fetched live from OpenAlex

Introduction Seagrass meadows serve as an integral component of coastal ecosystems but are declining rapidly due to numerous anthropogenic stressors including climate change. Eelgrass wasting disease, caused by opportunistic Labyrinthula spp., is an increasing concern with rising seawater temperature. To better understand the host-pathogen interaction, we paired whole organism physiological assays with dual transcriptomic analysis of the infected host and parasite. Methods Eelgrass ( Zostera marina ) shoots were placed in one of two temperature treatments, 11° C or 18° C, acclimated for 10 days, and exposed to a waterborne inoculation containing infectious Labyrinthula zosterae ( Lz ) or sterile seawater. At two- and five-days post-exposure, pathogen load, visible disease signs, whole leaf phenolic content, and both host- and pathogen- transcriptomes were characterized. Results Two days after exposure, more than 90% of plants had visible lesions and Lz DNA was detectable in 100% percent of sampled plants in the Lz exposed treatment. Concentrations of total phenolic compounds were lower after 5 days of combined exposure to warmer temperatures and Lz , but were unaffected in other treatments. Concentrations of condensed tannins were not affected by Lz or temperature, and did not change over time. Analysis of the eelgrass transcriptome revealed 540 differentially expressed genes in response to Lz exposure, but not temperature. Lz -exposed plants had gene expression patterns consistent with increased defense responses through altered regulation of phytohormone biosynthesis, stress response, and immune function pathways. Analysis of the pathogen transcriptome revealed up-regulation of genes potentially involved in breakdown of host defense, chemotaxis, phagocytosis, and metabolism. Discussion The lack of a significant temperature signal was unexpected but suggests a more pronounced physiological response to Lz infection as compared to temperature. Pre-acclimation of eelgrass plants to the temperature treatments may have contributed to the limited physiological responses to temperature. Collectively, these data characterize a widespread physiological response to pathogen attack and demonstrate the value of paired transcriptomics to understand infections in a host-pathogen system.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.318
Threshold uncertainty score0.579

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.014
GPT teacher head0.225
Teacher spread0.211 · 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 teacher head, 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

Citations10
Published2023
Admission routes1
Has abstractyes

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