Biology subjects

Heyse, J.

Publications and source records attributed to Heyse, J..

5 recordsLinked to original sources

bioRxiv2022

Real-Time Flow Cytometry to assess qualitative and quantitative responses of oral pathobionts during exposure to antiseptics

Antiseptics are widely used in oral healthcare to prevent or treat oral diseases, such as gingivitis and periodontitis. However, the incidence of bacteria being tolerant to standard antiseptics has sharply increased over the last few years. This stresses the urgency for surveillance against tolerant organisms, as well as the discovery of novel antimicrobials. Traditionally, susceptibility to antimicrobials is assessed by broth micro-dilution or disc diffusion assays, both of which are time-consuming, labor-intensive and provide limited information on the mode of action of the antimicrobials. The above-mentioned limitations highlight the need for the development of new methods to monitor and further understand antimicrobial susceptibility. Here, we used real-time flow cytometry, combined with membrane permeability staining, as a quick and sensitive technology to study the quantitative and qualitative response of two oral pathobionts to different concentrations of chlorhexidine, cetylpyridinium chloride or triclosan. Apart from the real-time monitoring of cell damage, we further applied a phenotypic fingerprint method to differentiate between the bacterial subpopulations that arose due to treatment. We quantified the pathobiont damage rate of different antiseptics at different concentrations within 15 minutes of exposure and identified the conditions under which the bacteria were most susceptible. Moreover, we detected species-specific and treatment-specific phenotypic subpopulations. This proves that real-time flow cytometry can provide information on the susceptibility of different microorganisms in a short time frame while differentiating between antiseptics and thus could be a valuable tool in the discovery of novel antimicrobial compounds while at the same time deciphering their mode of action.

microbiology↗

bioRxiv2021

Predicting the presence and abundance of bacterial taxa in environmental communities through flow cytometric fingerprinting

Microbiome management research and applications rely on temporally-resolved measurements of community composition. Current technologies to assess community composition either make use of cultivation or sequencing of genomic material, which can become time consuming and/or laborious in case high-throughput measurements are required. Here, using data from a shrimp hatchery as an economically relevant case study, we combined 16S rRNA gene amplicon sequencing and flow cytometry data to develop a computational workflow that allows the prediction of taxon abundances based on flow cytometry measurements. The first stage of our pipeline consists of a classifier to predict the presence or absence of the taxon of interest, with yields an average accuracy of 88.13{+/-}4.78 % across the top 50 OTUs of our dataset. In the second stage, this classifier was combined with a regression model to predict the relative abundances of the taxon of interest, which yields an average R2 of 0.35{+/-}0.24 across the top 50 OTUs of our dataset. Application of the models on flow cytometry time series data showed that the generated models can predict the temporal dynamics of a large fraction of the investigated taxa. Using cell-sorting we validated that the model correctly associates taxa to regions in the cytometric fingerprint where they are detected using 16S rRNA gene amplicon sequencing. Finally, we applied the approach of our pipeline on two other datasets of microbial ecosystems. This pipeline represents an addition to the expanding toolbox for flow cytometry-based monitoring of bacterial communities and complements the current plating- and marker gene-based methods. ImportanceMonitoring of microbial community composition is crucial for both microbiome management research and applications. Existing technologies, such as plating and amplicon sequencing, can become laborious and expensive when high-throughput measurements are required. Over the recent years, flow cytometry-based measurements of community diversity have been shown to correlate well to those derived from 16S rRNA gene amplicon sequencing in several aquatic ecosystems, suggesting there is a link between the taxonomic community composition and phenotypic properties as derived through flow cytometry. Here, we further integrated 16S rRNA gene amplicon sequencing and flow cytometry survey data in order to construct models that enable the prediction of both the presence and the abundance of individual bacterial taxa in mixed communities using flow cytometric fingerprinting. The developed pipeline holds great potential to be integrated in routine monitoring schemes and early warning systems for biotechnological applications.

microbiology↗

bioRxiv2020

Rearing water microbiomes in white leg shrimp (Litopenaeus vannamei) larviculture assemble stochastically and are influenced by the microbiomes of live feed products

The development of effective management strategies to reduce the occurrence of diseases in aquaculture is hampered by the limited knowledge on the microbial ecology of these systems. In this study, the dynamics and dominant community assembly processes in the rearing water of Litopenaeus vannamei larviculture tanks were determined. Additionally, the contribution of peripheral microbiomes, such as those of live and dry feeds, to the rearing water microbiome were quantified. The community assembly in the hatchery rearing water over time was dominated by stochasticity, which explains the observed heterogeneity between replicate cultivations. The community undergoes two shifts that match with the dynamics of the algal abundances in the rearing water. Source tracking analysis revealed that 37% of all bacteria in the hatchery rearing water were either introduced by the live or dry feeds, or during water exchanges. The contribution of the microbiome from the algae was the largest, followed by that of the Artemia, the exchange water and the dry feeds. Our findings provide fundamental knowledge on the assembly processes and dynamics of rearing water microbiomes and illustrate the crucial role of these peripheral microbiomes in maintaining health-promoting rearing water microbiomes. Originality-Significance StatementMost studies on rearing water microbiomes are characterized by sampling resolutions of multiple days and by few replicate cultivations. Through an 18-day sampling campaign in a Litopenaeus vannamei hatchery where five replicate cultivations were studied at a sampling resolution of one day, we studied the microbiome dynamics in this system. We show that the community assembly is dominated by stochasticity, which explains the heterogeneity between replicate cultivations. The dynamics of the algal community in the rearing water induced shifts in community composition at two differerent timepoints. Finally, we quantified the contribution of live and dry feed microbiomes to the rearing water community for the first time. We found that the contribution of each source was dependent on its taxonomic composition, the bacterial load caused by the addition of this source and the timing of the introduction. These new insights will aid in the further development of effective microbiome management to reduce the frequency and magnitude of bacterial diseases.

microbiology↗

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↗

bioRxiv2018

Coculturing bacteria leads to reduced phenotypic heterogeneities

Isogenic bacterial populations are known to exhibit phenotypic heterogeneity at the single cell level. Because of difficulties in assessing the phenotypic heterogeneity of a single taxon in a mixed community, the importance of this deeper level of organisation remains relatively unknown for natural communities. In this study, we have used membrane-based microcosms that allow the probing of the phenotypic heterogeneity of a single taxon while interacting with a synthetic or natural community. Individual taxa were studied under axenic conditions, as members of a coculture with physical separation, and as a mixed culture. Phenotypic heterogeneity was assessed through both flow cytometry and Raman spectroscopy. Using this setup, we investigated the effect of microbial interactions on the individual phenotypic heterogeneities of two interacting drinking water isolates. We have demonstrated that interactions between these bacteria lead to an adjustment of their individual phenotypic diversities, and that this adjustment is conditional on the bacterial taxon.\n\nImportanceLaboratory studies have shown the impact of phenotypic heterogeneity on the survival and functionality of isogenic populations. As phenotypic heterogeneity is known to play an important role in pathogenicity and virulence, antibiotics resistance, biotechnological applications and ecosystem properties, it is crucial to understand its influencing factors. An unanswered question is whether bacteria in mixed communities influence the phenotypic heterogeneity of their community partners. We found that coculturing bacteria leads to a reduction in their individual phenotypic heterogeneities, which led us to the hypothesis that the individual phenotypic diversity of a taxon is dependent on the community composition.

microbiology↗