Evidence map›Paper›PMID 25114712›Full record

ArticlePlant methods2014

A novel cost effective and high-throughput isolation and identification method for marine microalgae.

Martin T Jahn, Katrin Schmidt, Thomas Mock

Abstract read
In one paragraph

Article in Plant methods, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. The need for smart microalgal bioprospecting.Natural products and bioprospecting · 2025
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Martin T JahnSchool of Environmental Sciences, University of East Anglia, Norwich Research Park, Norwich NR4 7TJ, UK ; Current address: Department of Botany II, Julius-Maximilians University Würzburg, Julius-von-Sachs-Platz 3, 97082 Würzburg, Germany.
Katrin SchmidtSchool of Environmental Sciences, University of East Anglia, Norwich Research Park, Norwich NR4 7TJ, UK.
Thomas MockSchool of Environmental Sciences, University of East Anglia, Norwich Research Park, Norwich NR4 7TJ, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMarine microalgae are of major ecologic and emerging economic importance. Biotechnological screening schemes of microalgae for specific traits and laboratory experiments to advance our knowledge on algal biology and evolution strongly benefit from culture collections reflecting a maximum of the natural inter- and intraspecific diversity. However, standard procedures for strain isolation and identification, namely DNA extraction, purification, amplification, sequencing and taxonomic identification still include considerable constraints increasing the time required to establish new cultures.

resultsIn this study, we report a cost effective and high-throughput isolation and identification method for marine microalgae. The throughput was increased by applying strain isolation on plates and taxonomic identification by direct PCR (dPCR) of phylogenetic marker genes in combination with a novel sequencing electropherogram based screening method to assess the taxonomic diversity and identity of the isolated cultures. For validation of the effectiveness of this approach, we isolated and identified a range of unialgal cultures from natural phytoplankton communities sampled in the Arctic Ocean. These cultures include the isolate of a novel marine Chlorophyceae strain among several different diatoms.

conclusionsWe provide an efficient and effective approach leading from natural phytoplankton communities to isolated and taxonomically identified algal strains in only a few weeks. Validated with sensitive Arctic phytoplankton, this approach overcomes the constraints of standard molecular characterisation and establishment of unialgal cultures.

Indexed as

CultivationDirect PCRIsolationMarine microalgaeTaxonomy

Identifiers

PMID25114712
PMCPMC4128616

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.