Evidence map›Paper›PMID 38454313›Full record

ArticleEnvironmental science & technology2024

CyanoStrainChip: A Novel DNA Microarray Tool for High-Throughput Detection of Environmental Cyanobacteria at the Strain Level.

Hao-Yue Shu, Liang Zhao, Yanyan Jia, Fei-Fei Liu, Jiang Chen, Chih-Min Chang, Tao Jin, Jian Yang, Wen-Sheng Shu

Abstract read
In one paragraph

Article in Environmental science & technology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

1 citing paper in PubMed.

  1. Review
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

9 authors.

Hao-Yue ShuGuangdong Magigene Biotechnology Co., Ltd., Shenzhen 518081, PR China.ORCID 0000-0001-8784-8968
Liang ZhaoInstitute of Ecological Science, Guangzhou Key Laboratory of Subtropical Biodiversity and Biomonitoring, Guangdong Provincial Key Laboratory of Biotechnology for Plant Development, School of Life Sciences, South China Normal University, Guangzhou 510006, PR China.
Yanyan JiaSchool of Ecology, Sun Yat-sen University, Shenzhen 518107, PR China.
Fei-Fei LiuGuangdong Magigene Biotechnology Co., Ltd., Shenzhen 518081, PR China.
Jiang ChenGuangdong Magigene Biotechnology Co., Ltd., Shenzhen 518081, PR China.
Chih-Min ChangGuangdong Magigene Biotechnology Co., Ltd., Shenzhen 518081, PR China.
Tao JinGuangdong Magigene Biotechnology Co., Ltd., Shenzhen 518081, PR China.
Jian YangSchool of Food and Drug, Shenzhen Polytechnic, Shenzhen 518081, PR China.
Wen-Sheng ShuGuangdong Magigene Biotechnology Co., Ltd., Shenzhen 518081, PR China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Detecting cyanobacteria in environments is an important concern due to their crucial roles in ecosystems, and they can form blooms with the potential to harm humans and nonhuman entities. However, the most widely used methods for high-throughput detection of environmental cyanobacteria, such as 16S rRNA sequencing, typically provide above-species-level resolution, thereby disregarding intraspecific variation. To address this, we developed a novel DNA microarray tool, termed the CyanoStrainChip, that enables strain-level comprehensive profiling of environmental cyanobacteria. The CyanoStrainChip was designed to target 1277 strains; nearly all major groups of cyanobacteria are included by implementing 43,666 genome-wide, strain-specific probes. It demonstrated strong specificity by

Indexed as

CyanobacteriaMicrocystisEcosystemHarmful Algal BloomHumansLakesOligonucleotide Array Sequence AnalysisRNA, Ribosomal, 16SRNA, Ribosomal, 16Scyanobacteriaharmful bloomintraspecific variationmicroarraystrain-level detection

Identifiers

PMID38454313
PMCPMC10956431

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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.