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Record W2966823935 · doi:10.1016/j.watres.2019.114941

Phytoplankton growth characterization in short term MPN culture assays using 18S metabarcoding and qRT-PCR

2019· article· en· W2966823935 on OpenAlexafffund
Brian Petri, Subba Rao Chaganti, Po-Shun Chan, Daniel D. Heath

Bibliographic record

VenueWater Research · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine Ecology and Invasive Species
Canadian institutionsUniversity of WindsorTrojan Technologies (Canada)
FundersNational Research Council CanadaNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsBiologyPhytoplanktonPolymerase chain reactionMicrobiologyEcologyGeneGeneticsNutrient

Abstract

fetched live from OpenAlex

The most probable number dilution-culture assay (MPN) is used to enumerate viable phytoplankton in regulatory tests of ballast water treatment systems. However the United States Coast Guard has not yet accepted MPN, in part due to concerns of biased results due to cells being viable but not growing. MPN does not assess the fate of every cell, and thus the bias can only be evaluated by a companion method that assesses the ability of the various taxa to grow. This growth ability (“growability”) is the complement of the bias, and has been evaluated by microscopic taxonomy of before-culture and after-culture samples. However, microscopic taxonomy is extremely laborious and few data have been produced for phytoplankton growability in MPN assays. To address the need for more and more reliable growability data, a method was developed using next-generation sequencing (NGS) and quantitative real time PCR (qRT-PCR) techniques that target the V9 region of the 18S rRNA gene for the taxonomic identification and growth assessment of eukaryotic phytoplankton, respectively. This growability method was applied to MPN samples from a ballast water management system test that were incubated with two different enrichment media at two different temperatures. DNA was extracted from filters of before-culture and after-culture samples, and assessed for taxonomy by NGS and for PCR template DNA concentration by qRT-PCR. Growth ratios based on changes in 18S template concentration over the incubation period were calculated for each taxon, and dead-cell DNA persistence through a 14 day incubation was verified to be <1% and did not influence the growth calculations. In total, 95 of 97 eukaryotic phytoplankton in the before-culture sample demonstrated growth, with definitive growth ratios ranging from 4.0 × 101–2.6 × 105. An additional 13 taxa demonstrated growth from non-detect in before-culture samples. Taxa-based growability values were 87–88% in individual incubation conditions with no statistical differences among conditions, and 98% for all conditions combined. When growability was weighted by the before-culture abundance of each taxa, relevant to regulations based on all organisms regardless of taxa, community-based growability was >99% in each condition and in all conditions combined because the most abundant taxa all exhibited growth. This study verifies that conventional phytoplankton MPN assays produce accurate results with low bias from undetected viable cells, regardless of enrichments and incubation temperatures. This work can provide regulatory confidence for broader acceptance of MPN assays without limitations.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.002

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 head0.049
GPT teacher head0.303
Teacher spread0.254 · 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

Citations6
Published2019
Admission routes2
Has abstractyes

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