Literature DB >> 30529573

Aspergillus fumigatus branching complexity in vitro: 2D images and dynamic modeling.

Katarina M Rajković1, Nebojša T Milošević2, Suzana Otašević3, Sanja Jeremić4, Valentina Arsić Arsenijević5.   

Abstract

BACKGROUND: Aspergillus fumigatus causes serious infections in humans, and its virulence correlates with hyphal growth, branching and formation of the filamentous mycelium. The filamentous mycelium is a complex structure inconvenient for quantity analysis. In this study, we monitored the branching of A. fumigatus filamentous mycelium in vitro at different points in time in order to assess the complexity degree and develop a dynamic model for the branching complexity.
METHOD: We used fractal analysis of microscopic images (FAMI) to measure the fractal dimensions (D) of the branching complexity within 24 h of incubation.
RESULTS: By photographing the filamentous mycelium dynamically and processing the images, the D variation curve of A. fumigatus complexity degree was obtained. We acquired the D variation curve which contained initial exponential period and stationary period of A. fumigatus branching. Further, the obtained data of D was modeled via the logistic model (LM) to develop a dynamic model of A. fumigatus branching for the prediction of the specific growth rate of branching value (0.23 h-1).
CONCLUSIONS: Developed FAMI and LM models present a simple and non-destructive method of predicting the evolution of branching complexity of A. fumigatus. These models are useful as laboratory measurements for the prediction of hyphal and mycelium development, especially relevant to the pathogenesis study of aspergillosis, as well as pathogenesis of other diseases caused by moulds.
Copyright © 2018. Published by Elsevier Ltd.

Entities:  

Keywords:  Aspergilus fumigatus; Branching complexity; Fractal dimensions; Logistic model; Specific growth rate

Mesh:

Year:  2018        PMID: 30529573     DOI: 10.1016/j.compbiomed.2018.11.022

Source DB:  PubMed          Journal:  Comput Biol Med        ISSN: 0010-4825            Impact factor:   4.589


  2 in total

1.  Computational image analysis reveals the structural complexity of Toxoplasma gondii tissue cysts.

Authors:  Neda Bauman; Andjelija Ilić; Olivera Lijeskić; Aleksandra Uzelac; Ivana Klun; Jelena Srbljanović; Vladimir Ćirković; Branko Bobić; Tijana Štajner; Olgica Djurković-Djaković
Journal:  PLoS One       Date:  2020-08-18       Impact factor: 3.240

2.  Rapid and concise quantification of mycelial growth by microscopic image intensity model and application to mass cultivation of fungi.

Authors:  Soo Kweon Lee; Ju Hun Lee; Hyeong Ryeol Kim; Youngsang Chun; Ja Hyun Lee; Chulhwan Park; Hah Young Yoo; Seung Wook Kim
Journal:  Sci Rep       Date:  2021-12-17       Impact factor: 4.379

  2 in total

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