Evidence map›Paper›PMID 31223339›Full record

ArticleBiotechnology for biofuels2019

A quantitative image analysis pipeline for the characterization of filamentous fungal morphologies as a tool to uncover targets for morphology engineering: a case study using

Timothy C Cairns, Claudia Feurstein, Xiaomei Zheng, Ping Zheng, Jibin Sun, Vera Meyer

Open access · goldAbstract read
In one paragraph

Article in Biotechnology for biofuels, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
2.8field-weighted citation impact, top 8% of its field
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

32 citing papers in PubMed, 62 citations in OpenAlex.

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  20. CRISPR/Cas9-Based Genome Editing and Its Application inJournal of fungi (Basel, Switzerland) · 2022
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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

6 authors at 1 institution in 2 countries.

Timothy C Cairns *1Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308 People's Republic of China.ORCID 0000-0001-7106-224X
Claudia Feurstein *1Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308 People's Republic of China.
Xiaomei Zheng1Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308 People's Republic of China.ORCID 0000-0001-9136-0666
Ping Zheng1Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308 People's Republic of China.ORCID 0000-0001-9434-9892
Jibin Sun1Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308 People's Republic of China.ORCID 0000-0002-0208-504X
Vera Meyer1Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308 People's Republic of China.ORCID 0000-0002-2298-2258
Chinese Academy of Sciences · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFungal fermentation is used to produce a diverse repertoire of enzymes, chemicals, and drugs for various industries. During submerged cultivation, filamentous fungi form a range of macromorphologies, including dispersed mycelia, clumped aggregates, or pellets, which have critical implications for rheological aspects during fermentation, gas/nutrient transfer, and, thus, product titres. An important component of strain engineering efforts is the ability to quantitatively assess fungal growth phenotypes, which will drive novel leads for morphologically optimized production strains.

resultsIn this study, we developed an automated image analysis pipeline to quantify the morphology of pelleted and dispersed growth (MPD) which rapidly and reproducibly measures dispersed and pelleted macromorphologies from any submerged fungal culture. It (i) enables capture and analysis of several hundred images per user/day, (ii) is designed to quantitatively assess heterogeneous cultures consisting of dispersed and pelleted forms, (iii) gives a quantitative measurement of culture heterogeneity, (iv) automatically generates key Euclidian parameters for individual fungal structures including particle diameter, aspect ratio, area, and solidity, which are also assembled into a previously described dimensionless morphology number MN, (v) has an in-built quality control check which enables end-users to easily confirm the accuracy of the automated calls, and (vi) is easily adaptable to user-specified magnifications and macromorphological definitions. To concomitantly provide proof of principle for the utility of this image analysis pipeline, and provide new leads for morphologically optimized fungal strains, we generated a morphological mutant in the cell factory

conclusionThe MPD image analysis pipeline is a simple, rapid, and flexible approach to quantify diverse fungal morphologies. As an exemplar, we have demonstrated that the putative endosomal transport gene

Indexed as

Aspergillus nigerCRISPRDispersed myceliaEndocytosisImage analysisMorphology engineeringPelletPolar growthProtein secretionTet-on

Identifiers

PMID31223339
PMCPMC6570962
OpenAlexW2950191408

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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.