Biology subjects

Garcia-Timermans, C.

Publications and source records attributed to Garcia-Timermans, C..

4 recordsLinked to original sources

bioRxiv2023

Unlocking the Mechanism of Action: A Cost-Effective Flow Cytometry Approach for Accelerating Antimicrobial Drug Development

Antimicrobial resistance is one of the greatest challenges to global health. While the development of new antimicrobials can combat resistance, low profitability is reducing the number of new compounds brought to the market. Elucidating the mechanism of action is crucial for developing new antimicrobials. This process can become expensive as there are no universally applicable pipelines and scientific expertise in different fields is required. One way to determine the mechanism of action is the use of predictive modeling, as antimicrobials can be classified into limited groups.. We demonstrate a cost-effective flow cytometry approach for determining the mechanisms of action of new compounds. Cultures of Actinomyces viscosus and Fusobacterium nucleatum were treated with a range of antimicrobials and measured by flow cytometry. A Gaussian mixture mask was applied over the data to construct a phenotypic fingerprint. The fingerprints were used to train random forest classifiers, and classifiers were used to predict the mechanism of action of cephalothin. Significant statistical differences were found among the 10 different treatment groups. A pairwise comparison between treatment groups showed a statistical difference for 35 out of 45 pairs for Actinomyces viscosus and 32 out of 45 pairs for Fusobacterium nucleatum after 3.5h of treatment. The best performing random forest classifier yielded a Matthews correlation coefficient of 0.92 and the mechanism of action of cephalothin could be successfully predicted. These findings suggest that flow cytometry can be a cheap and fast alternative for determining the mechanism of action of new antimicrobials.

microbiology↗

bioRxiv2023

Unwanted coliforms can hide in mature drinking water biofilms, grown in full-scale distribution networks

Biofilms within drinking water distribution systems serve as a habitat for drinking water microorganisms. However, biofilms can negatively impact drinking water quality by causing water discoloration and deterioration and can be a reservoir for unwanted microorganisms. In this study, we investigated whether indicator organisms for drinking water quality, such as coliforms, can settle in mature drinking water biofilms. Therefore, a biofilm monitor consisting of glass rings was used to grow and sample drinking water biofilms. Two mature drinking water biofilms were characterized by flow cytometry, ATP measurements, confocal laser scanning microscopy and 16S rRNA sequencing. Biofilms developed under treated chlorinated surface water supply exhibited lower cell densities in comparison with biofilms resulting from treated groundwater. Overall, the phenotypic as well as the genotypic characteristics were significantly different between both biofilms. In addition, the response of the biofilm microbiome and possible biofilm detachment after minor water quality changes were investigated. Limited changes in pH and free chlorine addition, to simulate operational changes that are relevant for practice, were evaluated. It was shown that both biofilms remained resilient. Finally, mature biofilms were prone to invasion of the coliform, Serratia fonticola. After spiking low concentrations (i.e. {+/-} 100 cells/100 mL) of the coliform to the corresponding bulk water samples, the coliforms were able to attach and get established within the mature biofilms. These outcomes are emphasizing the need for continued research on biofilm detachment and its implications for water contamination in distribution networks. ImportanceThe revelation that even low concentrations of coliforms can infiltrate into mature drinking water biofilms highlights a potential public health concern. Nowadays, the measurement of coliform bacteria is used as an indicator for fecal contamination and to control the effectiveness of disinfection processes and the cleanliness and integrity of distribution systems. In Flanders (Belgium), 533 out of 18840 measurements exceeded the established norm for the coliform indicator parameter in 2021, however, the source of microbial contamination is mostly unknown. Here, we showed that mature biofilms, are susceptible to invasion of Serratia fonticola. These findings emphasize the importance of understanding and managing biofilms in drinking water distribution systems, not only for their potential to influence water quality, but also for their role in harboring and potentially disseminating pathogens. Further research into biofilm detachment, long-term responses to operational changes, and pathogen persistence within biofilms is crucial to inform strategies for safeguarding drinking water quality.

microbiology↗

bioRxiv2020

Raman spectroscopy-based measurements of single-cell phenotypic diversity in microbial communities

Microbial cells experience physiological changes due to environmental change, such as pH and temperature, the release of bactericidal agents, or nutrient limitation. This, has been shown to affect community assembly and other processes such as stress tolerance, virulence or cell physiology. Metabolic stress is one such physiological changes and is typically quantified by measuring community phenotypic properties such as biomass growth, reactive oxygen species or cell permeability. However, community measurements do not take into account single-cell phenotypic diversity, important for a better understanding and management of microbial populations. Raman spectroscopy is a non-destructive alternative that provides detailed information on the biochemical make-up of each individual cell. Here, we introduce a method for describing single-cell phenotypic diversity using the Hill diversity framework of Raman spectra. Using the biomolecular profile of individual cells, we obtained a metric to compare cellular states and used it to study stress-induced changes. First, in two Escherichia coli populations either treated with ethanol or non-treated. Then, in two Saccharomyces cerevisiae subpopulations with either high or low expression of a stress reporter. In both cases, we were able to quantify single-cell phenotypic diversity and to discriminate metabolically stressed cells using a clustering algorithm. We also described how the lipid, protein and nucleic acid composition changed after the exposure to the stressor using information from the Raman spectra. Our results show that Raman spectroscopy delivers the necessary resolution to quantify phenotypic diversity within individual cells and that this information can be used to study stress-driven metabolic diversity in microbial communities. ImportanceMicrobes that live in the same community respond differently to stress. This phenomemon is known as phenotypic diversity. Describing this plethora of expressions can help to better understand and manage microbial processes. However, most tools to study phenotypic diversity only average the behaviour of the community. In this work, we present a way to quantify the phenotypic diversity of single cells using Raman spectroscopy - a tool that can describe the molecular profile of microbes. We demonstrate how this tool can be used to quantify the phenotypic diversity that arises after the exposure of microbes to stress. We also show its potential as an alarm system to detect when communities are changing into a stressed type.

molecular biology↗

bioRxiv2019

Characterizing phenotypic heterogeneity in isogenic bacterial populations using flow cytometry and Raman spectroscopy

Investigating phenotypic heterogeneity can help to better understand and manage microbial communities. However, characterizing phenotypic heterogeneity remains a challenge, as there is no standardized analysis framework. Several optical tools are available, which often describe properties of the individual cell. In this work, we compare Raman spectroscopy and flow cytometry to study phenotypic heterogeneity in bacterial populations. The growth phase of E. coli populations was characterized using both technologies. Our findings show that flow cytometry detects and quantifies shifts in phenotypic heterogeneity at the population level due to its high-throughput nature. Raman spectroscopy, on the other hand, offers a much higher resolution at the single-cell level (i.e. more biochemical information is recorded). Therefore, it is capable of identifying distinct phenotypic populations when coupled with standardized data analysis. In addition, it provides information about biomolecules that are present, which can be linked to cell functionality. We propose an automated workflow to distinguish between bacterial phenotypic populations using Raman spectroscopy and validated this approach with an external dataset. We recommend to apply flow cytometry to characterize phenotypic heterogeneity at the population level, and Raman spectroscopy to perform a more in-depth analysis of heterogeneity at the single-cell level. ImportanceSingle-cell techniques are frequently applied tools to study phenotypic characteristics of bacterial populations. As flow cytometry and Raman spectroscopy gain popularity in the field, there is a need to understand their advantages and limitations, as well as to create a more standardized data analysis framework. Our work shows that flow cytometry allows to study and quantify shifts at the bacterial population level, but since its resolution is limited for microbial purposes, distinct phenotypic populations cannot be distinguished at the single-cell level. Raman spectroscopy, combined with appropriate data analysis, has sufficient resolving power at the single-cell level, enabling the identification of distinct phenotypic populations. As regions in a Raman spectrum are associated with specific (bio)molecules, it is possible to link these to the cell state and/or its function.

bioengineering↗