ArticleMolecules (Basel, Switzerland)2021
Imaging Flow Cytometry to Study Biofilm-Associated Microbial Aggregates.
Article in Molecules (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 19 citations in OpenAlex.
- A particle-resolved framework for quantifying microbial colonization and vector risk on environmental microplastics.Eco-Environment & Health · 2026Article
- High-throughput bacterial aggregation analysis in droplets.Scientific reports · 2025Article
- Methods for screening and evaluation of antimicrobial activity: A review of protocols, advantages, and limitations.European journal of microbiology & immunology · 2024Review
- Global transcriptome analysis of Pseudomonas aeruginosa NT06 response to potassium chloride, sodium lactate, sodium citrate, and microaerophilic conditions in a fish ecosystem.FEMS microbiology letters · 2024Article
- Advancing understanding of microbial biofilms through machine learning-powered studies.Food science and biotechnology · 2023Review
- High-throughput measurement of double strand break global repair phenotype in peripheral blood mononuclear cells after long-term cryopreservation.Cytometry. Part A : the journal of the International Society for Analytical Cytology · 2023Article
- Imaging Flow Cytometry Demonstrates Physiological and Morphological Diversity within Treated Probiotic Bacteria Groups.International journal of molecular sciences · 2023Article
- Article
- Horizontal Transfer of Virulence Factors by Pathogenic Enterobacteria to Marine Saprotrophic Bacteria during Co-Cultivation in Biofilm.Biotech (Basel (Switzerland)) · 2022Article
- Context-dependent differences in the functional responses of Lactobacillaceae strains to fermentable sugars.Frontiers in microbiology · 2022Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The aim of the research was to design an advanced analytical tool for the precise characterization of microbial aggregates from biofilms formed on food-processing surfaces. The approach combined imaging flow cytometry with a machine learning-based interpretation protocol. Biofilm samples were collected from three diagnostic points of the food-processing lines at two independent time points. The samples were investigated for the complexity of microbial aggregates and cellular metabolic activity. Thus, aggregates and singlets of biofilm-associated microbes were simultaneously examined for the percentages of active, mid-active, and nonactive (dead) cells to evaluate the physiology of the microbial cells forming the biofilm structures. The tested diagnostic points demonstrated significant differences in the complexity of microbial aggregates. The significant percentages of the bacterial aggregates were associated with the dominance of active microbial cells, e.g., 75.3% revealed for a mushroom crate. This confirmed the protective role of cellular aggregates for the survival of active microbial cells. Moreover, the approach enabled discriminating small and large aggregates of microbial cells. The developed tool provided more detailed characteristics of bacterial aggregates within a biofilm structure combined with high-throughput screening potential. The designed methodology showed the prospect of facilitating the detection of invasive biofilm forms in the food industry environment.
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Registered trials
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.