| Title |
SParticle, an algorithm for the analysis of filamentous microorganisms in submerged cultures
|
|---|---|
| Published in |
Antonie van Leeuwenhoek, September 2017
|
| DOI | 10.1007/s10482-017-0939-y |
| Pubmed ID | |
| Authors |
Joost Willemse, Ferhat Büke, Dino van Dissel, Sanne Grevink, Dennis Claessen, Gilles P. van Wezel |
| Abstract |
Streptomycetes are filamentous bacteria that produce a plethora of bioactive natural products and industrial enzymes. Their mycelial lifestyle typically results in high heterogeneity in bioreactors, with morphologies ranging from fragments and open mycelial mats to dense pellets. There is a strong correlation between morphology and production in submerged cultures, with small and open mycelia favouring enzyme production, while most antibiotics are produced mainly in pellets. Here we describe SParticle, a Streptomyces Particle analysis method that combines whole slide imaging with automated image analysis to characterize the morphology of submerged grown Streptomyces cultures. SParticle allows the analysis of over a thousand particles per hour, offering a high throughput method for the imaging and statistical analysis of mycelial morphologies. The software is available as a plugin for the open source software ImageJ and allows users to create custom filters for other microbes. Therefore, SParticle is a widely applicable tool for the analysis of filamentous microorganisms in submerged cultures. |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 20% |
| United Kingdom | 1 | 20% |
| Unknown | 3 | 60% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 31 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 6 | 19% |
| Researcher | 4 | 13% |
| Student > Bachelor | 3 | 10% |
| Other | 3 | 10% |
| Student > Master | 3 | 10% |
| Other | 6 | 19% |
| Unknown | 6 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 9 | 29% |
| Agricultural and Biological Sciences | 4 | 13% |
| Engineering | 2 | 6% |
| Unspecified | 1 | 3% |
| Energy | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 13 | 42% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 02 November 2017.
All research outputs
#14,393,352
of 23,508,125 outputs
Outputs from Antonie van Leeuwenhoek
#1,286
of 2,049 outputs
Outputs of similar age
#170,717
of 317,120 outputs
Outputs of similar age from Antonie van Leeuwenhoek
#15
of 31 outputs
Altmetric has tracked 23,508,125 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,049 research outputs from this source. They receive a mean Attention Score of 3.7. This one is in the 35th percentile – i.e., 35% of its peers scored the same or lower than it.
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We're also able to compare this research output to 31 others from the same source and published within six weeks on either side of this one. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.