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Imaging mass spectrometry-guided fast identification of antifungal secondary metabolites from Penicillium polonicum

Overview of attention for article published in Applied Microbiology and Biotechnology, July 2018
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Title
Imaging mass spectrometry-guided fast identification of antifungal secondary metabolites from Penicillium polonicum
Published in
Applied Microbiology and Biotechnology, July 2018
DOI 10.1007/s00253-018-9218-8
Pubmed ID
Authors

Jing Bai, Peng Zhang, Guanhu Bao, Jin-Gang Gu, Lida Han, Li-Wen Zhang, Yuquan Xu

Abstract

The discovery of antibiotics from microorganisms using classic bioactivity screens suffers from heavy labor and high re-discovery rate. Recently, largely uncovered biosynthetic potentials were unveiled by new approaches, such as genetic manipulation of "silent" biosynthetic gene clusters, innovative data acquisition, and processing methods. In this work, a fast and efficient antibiotic identification pipeline based on the MALDI-TOF imaging mass spectrometry was applied to study the antifungal metabolites during the confrontation of two fungal species, Penicillium polonicum and wilt-inducing fungus Fusarium oxysporum. By visualizing the spatial distribution of metabolites directly on the microbial colony and surrounding media, we predicted the antifungal candidates before isolating pure compounds and individually testing their bioactivity, which subsequently guided the identification of target molecules using classic chromatographic methods. Via this procedure, we successfully identified two antifungal metabolites, fructigenine A and B, which belong to indole alkaloid class and were not reported for antifungal activity. Our work assigned new bioactivity to previously reported compounds and more importantly showed the efficiency of this approach towards quick discovery of bioactive compounds, which can help study the vast unexploited synthetic potential of microbial secondary metabolites.

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The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 27 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 4 15%
Student > Master 3 11%
Professor 2 7%
Lecturer 2 7%
Student > Ph. D. Student 2 7%
Other 1 4%
Unknown 13 48%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 6 22%
Chemistry 4 15%
Agricultural and Biological Sciences 2 7%
Veterinary Science and Veterinary Medicine 1 4%
Business, Management and Accounting 1 4%
Other 0 0%
Unknown 13 48%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 July 2018.
All research outputs
#21,608,038
of 24,119,703 outputs
Outputs from Applied Microbiology and Biotechnology
#6,994
of 8,034 outputs
Outputs of similar age
#291,754
of 333,466 outputs
Outputs of similar age from Applied Microbiology and Biotechnology
#96
of 136 outputs
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So far Altmetric has tracked 8,034 research outputs from this source. They receive a mean Attention Score of 4.3. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 136 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.