Evidence map›Paper›PMID 34518910›Full record

ArticleAdvances in biochemical engineering/biotechnology2022

Screening Strategies for Biosurfactant Discovery.

Marla Trindade, Nombuso Sithole, Sonja Kubicki, Stephan Thies, Anita Burger

Abstract read
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In one paragraph

Article in Advances in biochemical engineering/biotechnology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

5 authors.

Marla TrindadeInstitute for Microbial Biotechnology and Metagenomics, University of the Western Cape, Cape Town, South Africa. ituffin@uwc.ac.za.
Nombuso SitholeInstitute for Microbial Biotechnology and Metagenomics, University of the Western Cape, Cape Town, South Africa.
Sonja KubickiInstitute of Molecular Enzyme Technology, Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany.
Stephan ThiesInstitute of Molecular Enzyme Technology, Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany.
Anita BurgerInstitute for Microbial Biotechnology and Metagenomics, University of the Western Cape, Cape Town, South Africa.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The isolation and screening of bacteria and fungi for the production of surface-active compounds has been the basis for the majority of the biosurfactants discovered to date. Hence, a wide variety of well-established and relatively simple methods are available for screening, mostly focused on the detection of surface or interfacial activity of the culture supernatant. However, the success of any biodiscovery effort, specifically aiming to access novelty, relies directly on the characteristics being screened for and the uniqueness of the microorganisms being screened. Therefore, given that rather few novel biosurfactant structures have been discovered during the last decade, advanced strategies are now needed to widen access to novel chemistries and properties. In addition, more modern Omics technologies should be considered to the traditional culture-based approaches for biosurfactant discovery. This chapter summarizes the screening methods and strategies typically used for the discovery of biosurfactants and highlights some of the Omics-based approaches that have resulted in the discovery of unique biosurfactants. These studies illustrate the potentially enormous diversity that has yet to be unlocked and how we can begin to tap into these biological resources.

Indexed as

FungiSurface-Active AgentsBacteriaSurface-Active AgentsBioprospectingFunctional propertiesHigh-throughputMicrobialOMICSOSMACSequence-basedSurface-active

Identifiers

PMID34518910

What OpenQuestion holds

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Registered trials

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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.