Evidence map›Paper›PMID 24133644›Full record

ArticleSpringerPlus2013

Identification of harmful cyanobacteria in the Sacramento-San Joaquin Delta and Clear Lake, California by DNA barcoding.

Tomofumi Kurobe, Dolores V Baxa, Cécile E Mioni, Raphael M Kudela, Thomas R Smythe, Scott Waller, Andrew D Chapman, Swee J Teh

Abstract read
In one paragraph

Article in SpringerPlus, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

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  7. Metagenome-Assembled Genome Sequence ofMicrobiology resource announcements · 2020
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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

8 authors.

Tomofumi KurobeGreenwater Laboratories, Palatka, FL 32177 USA.
Dolores V Baxa
Cécile E Mioni
Raphael M Kudela
Thomas R Smythe
Scott Waller
Andrew D Chapman
Swee J Teh

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accurate identification of cyanobacteria using traditional morphological taxonomy is challenging due to the magnitude of phenotypic plasticity among natural algal assemblages. In this study, molecular approach was utilized to facilitate the accurate identification of cyanobacteria in the Sacramento-San Joaquin Delta and in Clear Lake in Northern California where recurring blooms have been observed over the past decades. Algal samples were collected from both water bodies in 2011 and the samples containing diverse cyanobacteria as identified by morphological taxonomy were chosen for the molecular analysis. The 16S ribosomal RNA genes (16S rDNA) and the adjacent internal transcribed spacer (ITS) regions were amplified by PCR from the mixed algal samples using cyanobacteria generic primers. The obtained sequences were analyzed by similarity search (BLASTN) and phylogenetic analysis (16S rDNA) to differentiate species sharing significantly similar sequences. A total of 185 plasmid clones were obtained of which 77 were successfully identified to the species level: Aphanizomenon flos-aquae, Dolichospermum lemmermannii (taxonomic synonym: Anabaena lemmermannii), Limnoraphis robusta (taxonomic synonym: Lyngbya hieronymusii f. robusta) and Microcystis aeruginosa. To date, Dolichospermum and Limnoraphis found in Clear Lake have only been identified to the genus lavel by microscopy. During the course of this study, morphological identification and DNA barcoding confirmed A. flos-aquae as the predominant cyanobacterium in the Sacramento-San Joaquin Delta indicating a shift from M. aeruginosa that have dominated the blooms in the past decade. Lastly, the species-specific identification of Limnoraphis robusta in Clear Lake is another significant finding as this cyanobacterium has, thus far, only been reported in Lake Atitlan blooms in Guatemala.

Indexed as

16S ribosomal DNADNA barcodingHarmful cyanobacteriaInternal transcribed spacer region

Identifiers

PMID24133644
PMCPMC3797325

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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.