Details
| Originalsprache | Englisch |
|---|---|
| Seiten (von - bis) | 299-307 |
| Seitenumfang | 9 |
| Fachzeitschrift | Engineering in life sciences |
| Jahrgang | 22 |
| Ausgabenummer | 3-4 |
| Frühes Online-Datum | 10 Dez. 2021 |
| Publikationsstatus | Veröffentlicht - 28 März 2022 |
Abstract
Bacillus spp. endospores are important dormant cell forms and are distributed widely in environmental samples. While these endospores can have important industrial value (e.g. use in animal feed as probiotics), they can also be pathogenic for humans and animals, emphasizing the need for effective endospore detection. Standard spore detection by colony forming units (CFU) is time-consuming, elaborate and prone to error. Manual spore detection by spore count in cell counting chambers via phase-contrast microscopy is less time-consuming. However, it requires a trained person to conduct. Thus, the development of a facilitated spore detection tool is necessary. This work presents two alternative quantification methods: first, a colorimetric assay for detecting the biomarker dipicolinic acid (DPA) adapted to modern needs and applied for Bacillus spp. and second, a model-based automated spore detection algorithm for spore count in phase-contrast microscopic pictures. This automated spore count tool advances manual spore detection in cell counting chambers, and does not require human overview after sample preparation. In conclusion, this developed model detected various Bacillus spp. endospores with a correctness of 85–89%, and allows an automation and time-saving of Bacillus endospore detection. In the laboratory routine, endospore detection and counting was achieved within 5–10 min, compared to up to 48 h with conventional methods. The DPA-assay on the other hand enabled very accurate spore detection by simple colorimetric measurement and can thus be applied as a reference method.
ASJC Scopus Sachgebiete
- Biochemie, Genetik und Molekularbiologie (insg.)
- Biotechnologie
- Chemische Verfahrenstechnik (insg.)
- Bioengineering
- Umweltwissenschaften (insg.)
- Environmental engineering
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in: Engineering in life sciences, Jahrgang 22, Nr. 3-4, 28.03.2022, S. 299-307.
Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review
}
TY - JOUR
T1 - Facilitated endospore detection for Bacillus spp. through automated algorithm-based image processing
AU - Biermann, Riekje
AU - Niemeyer, Laura
AU - Rösner, Laura
AU - Ude, Christian
AU - Lindner, Patrick
AU - Bice, Ismet
AU - Beutel, Sascha
N1 - Funding Information: The authors would like to thank the Open Access fund of Leibniz University Hannover for the funding of the publication of this article. Open Acces funding enabled and organized by Projekt DEAL.
PY - 2022/3/28
Y1 - 2022/3/28
N2 - Bacillus spp. endospores are important dormant cell forms and are distributed widely in environmental samples. While these endospores can have important industrial value (e.g. use in animal feed as probiotics), they can also be pathogenic for humans and animals, emphasizing the need for effective endospore detection. Standard spore detection by colony forming units (CFU) is time-consuming, elaborate and prone to error. Manual spore detection by spore count in cell counting chambers via phase-contrast microscopy is less time-consuming. However, it requires a trained person to conduct. Thus, the development of a facilitated spore detection tool is necessary. This work presents two alternative quantification methods: first, a colorimetric assay for detecting the biomarker dipicolinic acid (DPA) adapted to modern needs and applied for Bacillus spp. and second, a model-based automated spore detection algorithm for spore count in phase-contrast microscopic pictures. This automated spore count tool advances manual spore detection in cell counting chambers, and does not require human overview after sample preparation. In conclusion, this developed model detected various Bacillus spp. endospores with a correctness of 85–89%, and allows an automation and time-saving of Bacillus endospore detection. In the laboratory routine, endospore detection and counting was achieved within 5–10 min, compared to up to 48 h with conventional methods. The DPA-assay on the other hand enabled very accurate spore detection by simple colorimetric measurement and can thus be applied as a reference method.
AB - Bacillus spp. endospores are important dormant cell forms and are distributed widely in environmental samples. While these endospores can have important industrial value (e.g. use in animal feed as probiotics), they can also be pathogenic for humans and animals, emphasizing the need for effective endospore detection. Standard spore detection by colony forming units (CFU) is time-consuming, elaborate and prone to error. Manual spore detection by spore count in cell counting chambers via phase-contrast microscopy is less time-consuming. However, it requires a trained person to conduct. Thus, the development of a facilitated spore detection tool is necessary. This work presents two alternative quantification methods: first, a colorimetric assay for detecting the biomarker dipicolinic acid (DPA) adapted to modern needs and applied for Bacillus spp. and second, a model-based automated spore detection algorithm for spore count in phase-contrast microscopic pictures. This automated spore count tool advances manual spore detection in cell counting chambers, and does not require human overview after sample preparation. In conclusion, this developed model detected various Bacillus spp. endospores with a correctness of 85–89%, and allows an automation and time-saving of Bacillus endospore detection. In the laboratory routine, endospore detection and counting was achieved within 5–10 min, compared to up to 48 h with conventional methods. The DPA-assay on the other hand enabled very accurate spore detection by simple colorimetric measurement and can thus be applied as a reference method.
KW - automated spore detection
KW - cell counting
KW - digital image processing
KW - DPA assay
KW - spore detection
UR - http://www.scopus.com/inward/record.url?scp=85120951372&partnerID=8YFLogxK
U2 - 10.1002/elsc.202100137
DO - 10.1002/elsc.202100137
M3 - Article
AN - SCOPUS:85120951372
VL - 22
SP - 299
EP - 307
JO - Engineering in life sciences
JF - Engineering in life sciences
SN - 1618-0240
IS - 3-4
ER -