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Record W3109471759 · doi:10.3390/app10238565

Lincomycin-Induced Transcriptional Alterations in the Green Alga Raphidocelis subcapitata

2020· article· en· W3109471759 on OpenAlexaff
Qiang Zhang, Yi Bai, Zhi Chen, Jiezhang Mo, Yulu Tian, Jiahua Guo

Bibliographic record

VenueApplied Sciences · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsConcordia University
FundersKey Research and Development Projects of Shaanxi Province
KeywordsPhotosynthesisTranscriptomeLincomycinBiologyAlgaeBiochemistryGrowth inhibitionMetabolismBotanyChemistryCell growthGeneGene expression

Abstract

fetched live from OpenAlex

Lincomycin (LIN), as a waterborne contaminant, may pose a threat to algal health and may affect the provision of ecosystem services. In addition, the molecular mechanisms of lincomycin in algae are still unknown. Here, we attempted to use the transcriptome analysis to elucidate for the first time the potential impact of LIN at an environmentally relevant concentration on the algal growth, and verify the hypothesis that lincomycin can disrupt algal protein synthesis by combining with its subunits of ribosome at high-LIN level. In this study, 7-day growth inhibition tests and RNA-seq sequencing were conducted in Raphidocelis subcapitata (R. subcapitata) in response to a LIN at the concentrations of 0.5 µg L−1 (low), 5 µg L−1 (medium), and 400 µg L−1 (high) treatment groups. A negligible influence on algal growth and merely 21 (21 up- and 0 downregulated) differentially expressed genes (DEGs) was observed at low concentration of LIN, and medium groups showed a 13.4% inhibition and 92 (64 up- and 48 downregulated) DEGs, while high-LIN dosing caused 65.4% reduction in algal growth and 2514 (663 up- and 1851 downregulated) DEGs. In 0.5 and 5 µg L−1 groups, LIN upregulated the genes in the process of photosynthesis consisting of photosynthesis-antenna proteins, and porphyrin and chlorophyll metabolism pathways, suggesting that photosynthesis at low LIN exposure was more sensitive than algal growth. Whereas DEGs in the 400 µg L−1 group were mostly enriched in carbohydrate, carbon fixation in photosynthetic organisms, and nucleotide metabolism pathways. Furthermore, genes involved in detoxification processes were nearly downregulated in high-LIN group. In addition, genes encoding the antioxidant enzymes in the peroxisome pathway such as superoxide dismutase (sod2), peroxin-2 (pex2), 2,4-dienoyl-CoA reductase ((3E)-enoyl-CoA-producing) (decr2) were upregulated, which are responsible for deleting extra intracellular reactive oxygen species (ROS) caused by LIN to protect algal health, suggesting the occurrence of oxidative stress. Taken together, this is the first meticulous study unraveling the molecular mechanism of antibiotics in algae.

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 score0.004
Threshold uncertainty score0.008

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.073
GPT teacher head0.287
Teacher spread0.215 · 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".

Quick stats

Citations1
Published2020
Admission routes1
Has abstractyes

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