Detection of microbial disturbances in a drinking water microbial community through continuous acquisition and advanced analysis of flow cytometry data

ABSTRACT Microbial flow cytometry can rapidly characterize the status of microbial communities. Upon measurement, large amounts of quantitative single-cell data are generated, which need to be analyzed appropriately. Cytometric fingerprinting approaches are often used for this purpose. Traditional approaches either require a manual annotation of regions of interest, do not fully consider the multivariate characteristics of the data, or result in many community-describing variables. To address these shortcomings, we propose an automated model-based fingerprinting approach based on Gaussian mixture models, which we call PhenoGMM. The method successfully quantifies changes in microbial community structure based on flow cytometry data, which can be expressed in terms of cytometric diversity. We evaluate the performance of PhenoGMM using data sets from both synthetic and natural ecosystems and compare the method with a generic binning fingerprinting approach. PhenoGMM supports the rapid and quantitative screening of microbial community structure and dynamics. IMPORTANCE Microorganisms are vital components in various ecosystems on Earth. In order to investigate the microbial diversity, researchers have largely relied on the analysis of 16S rRNA gene sequences from DNA. Flow cytometry has been proposed as an alternative technology to characterize microbial community diversity and dynamics. The technology enables a fast measurement of optical properties of individual cells. So-called fingerprinting techniques are needed in order to describe microbial community diversity and dynamics based on flow cytometry data. In this work, we propose a more advanced fingerprinting strategy based on Gaussian mixture models. We evaluated our workflow on data sets from both synthetic and natural ecosystems, illustrating its general applicability for the analysis of microbial flow cytometry data. PhenoGMM supports a rapid and quantitative analysis of microbial community structure using flow cytometry.

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PhenoGMM: Gaussian mixture modelling of microbial cytometry data enables efficient predictions of biodiversity

10.1101/641464 ◽

2019 ◽

Cited By ~ 2

Author(s):

Peter Rubbens ◽

Ruben Props ◽

Frederiek-Maarten Kerckhof ◽

Nico Boon ◽

Willem Waegeman

Keyword(s):

Flow Cytometry ◽

Microbial Community ◽

16S Rrna ◽

16S Rrna Gene ◽

Microbial Diversity ◽

Amplicon Sequencing ◽

Gaussian Mixture ◽

Community Diversity ◽

Rrna Gene ◽

Flow Cytometry Data

AbstractMicrobial flow cytometry allows to rapidly characterize microbial communities. Recent research has demonstrated a moderate to strong connection between the cytometric diversity and taxonomic diversity based on 16S rRNA gene amplicon sequencing data. This creates the opportunity to integrate both types of data to study and predict the microbial community diversity in an automated and efficient way. However, microbial flow cytometry data results in a number of unique challenges that need to be addressed. The results of our work are threefold: i) We expand current microbial cytometry fingerprinting approaches by proposing and validating a model-based fingerprinting approach based upon Gaussian Mixture Models, which we called PhenoGMM. ii) We show that microbial diversity can be rapidly estimated by PhenoGMM. In combination with a supervised machine learning model, diversity estimations based on 16S rRNA gene amplicon sequencing data can be predicted. iii) We evaluate our method extensively by using multiple datasets from different ecosystems and compare its predictive power with a generic binning fingerprinting approach that is commonly used in microbial flow cytometry. These results demonstrate the strong connection between the genetic make-up of a microbial community and its phenotypic properties as measured by flow cytometry. Our workflow facilitates the study of microbial diversity and community dynamics using flow cytometry in a fast and quantitative way.ImportanceMicroorganisms are vital components in various ecoystems on Earth. In order to investigate the microbial diversity, researchers have largely relied on the analysis of 16S rRNA gene sequences from DNA. Flow cytometry has been proposed as an alternative technique to characterize microbial community diversity and dynamics. It is an optical technique, able to rapidly characterize a number of phenotypic properties of individual cells. So-called fingerprinting techniques are needed in order to describe microbial community diversity and dynamics based on flow cytometry data. In this work, we propose a more advanced fingerprinting strategy based on Gaussian Mixture Models. When samples have been analyzed by both flow cytometry and 16S rRNA gene amplicon sequencing, we show that supervised machine learning models can be used to find the relationship between the two types of data. We evaluate our workflow on datasets from different ecosystems, illustrating its general applicability for the analysisof microbial flow cytometry data. PhenoGMM facilitates the rapid characterization and predictive modelling of microbial diversity using flow cytometry.

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Recent Bioinformatics Advances in the Analysis of High Throughput Flow Cytometry Data

Advances in Bioinformatics ◽

10.1155/2009/461763 ◽

2009 ◽

Vol 2009 ◽

pp. 1-2

Author(s):

Raphael Gottardo ◽

Ryan R. Brinkman ◽

George Luta ◽

Matt P. Wand

Keyword(s):

Flow Cytometry ◽

High Throughput ◽

Flow Cytometry Data

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Automated gating of flow cytometry data via robust model-based clustering

Cytometry Part A ◽

10.1002/cyto.a.20531 ◽

2008 ◽

Vol 73A (4) ◽

pp. 321-332 ◽

Cited By ~ 159

Author(s):

Kenneth Lo ◽

Ryan Remy Brinkman ◽

Raphael Gottardo

Keyword(s):

Flow Cytometry ◽

Model Based Clustering ◽

Flow Cytometry Data ◽

Model Based ◽

Robust Model

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A Multidimensional Flow Cytometry Data Classification

2009 Ninth IEEE International Conference on Bioinformatics and BioEngineering ◽

10.1109/bibe.2009.20 ◽

2009 ◽

Cited By ~ 3

Author(s):

Ming-Chih Shih ◽

Shou-Hsuan Stephen Huang ◽

Chung-Che Jeff Chang

Keyword(s):

Flow Cytometry ◽

Data Classification ◽

Flow Cytometry Data

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Interaction between typical sulfonamides and bacterial diversity in drinking water

Journal of Water and Health ◽

10.2166/wh.2018.210 ◽

2018 ◽

Vol 16 (6) ◽

pp. 914-920 ◽

Cited By ~ 2

Author(s):

Qing Wu ◽

Shuqun Li ◽

Xiaofei Zhao ◽

Xinhua Zhao

Keyword(s):

Drinking Water ◽

Community Structure ◽

Microbial Community ◽

Bacterial Community ◽

Bacterial Diversity ◽

Microbial Community Structure ◽

Antibiotic Use ◽

Community Diversity ◽

Wide Range ◽

Growth Of Bacteria

Abstract The abuse of antibiotics is becoming more serious as antibiotic use has increased. The sulfa antibiotics, sulfamerazine (SM1) and sulfamethoxazole (SMZ), are frequently detected in a wide range of environments. The interaction between SM1/SMZ and bacterial diversity in drinking water was investigated in this study. The results showed that after treatment with SM1 or SMZ at four different concentrations, the microbial community structure of the drinking water changed statistically significantly compared to the blank sample. At the genus level, the proportions of the different bacteria in drinking water may affect the degradation of the SM1/SMZ. The growth of bacteria in drinking water can be inhibited after the addition of SM1/SMZ, and bacterial community diversity in drinking water declined in this study. Furthermore, the resistance gene sul2 was induced by SM1 in the drinking water.

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Natural polyploidy in Vanilla planifolia (Orchidaceae)

Genome ◽

10.1139/g08-068 ◽

2008 ◽

Vol 51 (10) ◽

pp. 816-826 ◽

Cited By ~ 29

Author(s):

Séverine Bory ◽

Olivier Catrice ◽

Spencer Brown ◽

Ilia J. Leitch ◽

Rodolphe Gigant ◽

...

Keyword(s):

Flow Cytometry ◽

Phenotypic Variation ◽

Chromosome Numbers ◽

Reunion Island ◽

Vanilla Planifolia ◽

Root Cells ◽

Flow Cytometry Data ◽

Important Variation ◽

Réunion Island ◽

Stomatal Length

Vanilla planifolia accessions cultivated in Reunion Island display important phenotypic variation, but little genetic diversity is demonstrated by AFLP and SSR markers. This study, based on analyses of flow cytometry data, Feulgen microdensitometry data, chromosome counts, and stomatal length measurements, was performed to determine whether polyploidy could be responsible for some of the intraspecific phenotypic variation observed. Vanilla planifolia exhibited an important variation in somatic chromosome number in root cells, as well as endoreplication as revealed by flow cytometry. Nevertheless, the 2C-values of the 50 accessions studied segregated into three distinct groups averaging 5.03 pg (for most accessions), 7.67 pg (for the ‘Stérile’ phenotypes), and 10.00 pg (for the ‘Grosse Vanille’ phenotypes). For the three groups, chromosome numbers varied from 16 to 32, 16 to 38, and 22 to 54 chromosomes per cell, respectively. The stomatal length showed a significant variation from 37.75 µm to 48.25 µm. Given that 2C-values, mean chromosome numbers, and stomatal lengths were positively correlated and that ‘Stérile’ and ‘Grosse Vanille’ accessions were indistinguishable from ‘Classique’ accessions using molecular markers, the occurrence of recent autotriploid and autotetraploid types in Reunion Island is supported. This is the first report showing evidence of a recent autopolyploidy in V. planifolia contributing to the phenotypic variation observed in this species.

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Characterization, Microbial Community Structure, and Pathogen Occurrence in Urban Faucet Biofilms in South China

BioMed Research International ◽

10.1155/2015/401672 ◽

2015 ◽

Vol 2015 ◽

pp. 1-8

Author(s):

Huirong Lin ◽

Shuting Zhang ◽

Song Gong ◽

Shenghua Zhang ◽

Xin Yu

Keyword(s):

Drinking Water ◽

Community Structure ◽

Microbial Community ◽

Microbial Community Structure ◽

Laser Scanning ◽

Matrix Material ◽

Water System ◽

Confocal Laser Scanning Microscope ◽

Extracellular Proteins ◽

Confocal Laser

The composition and microbial community structure of the drinking water system biofilms were investigated using microstructure analysis and 454 pyrosequencing technique in Xiamen city, southeast of China. SEM (scanning electron microscope) results showed different features of biofilm morphology in different fields of PVC pipe. Extracellular matrix material and sparse populations of bacteria (mainly rod-shaped and coccoid) were observed. CLSM (confocal laser scanning microscope) revealed different distributions of attached cells, extracellular proteins,α-polysaccharides, andβ-polysaccharides. The biofilms had complex bacterial compositions. Differences in bacteria diversity and composition from different tap materials and ages were observed. Proteobacteria was the common and predominant group in all biofilms samples. Some potential pathogens (Legionellales, Enterobacteriales, Chromatiales, and Pseudomonadales) and corrosive microorganisms were also found in the biofilms. This study provides the information of characterization and visualization of the drinking water biofilms matrix, as well as the microbial community structure and opportunistic pathogens occurrence.

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Normative data for flow cytometry immunophenotyping of benign lymph nodes sampled by surgical biopsy

Journal of Clinical Pathology ◽

10.1136/jclinpath-2017-204687 ◽

2017 ◽

Vol 71 (2) ◽

pp. 174-179 ◽

Cited By ~ 8

Author(s):

Gregory David Scott ◽

Susan K Atwater ◽

Dita A Gratzinger

Keyword(s):

Flow Cytometry ◽

Lymph Node ◽

T Cell ◽

Lymph Nodes ◽

Inflammatory Disease ◽

Clinical History ◽

Surgical Biopsy ◽

Data Set ◽

Flow Cytometry Data ◽

Benign Lymph Node

AimsTo create clinically relevant normative flow cytometry data for understudied benign lymph nodes and characterise outliers.MethodsClinical, histological and flow cytometry data were collected and distributions summarised for 380 benign lymph node excisional biopsies. Outliers for kappa:lambda light chain ratio, CD10:CD19 coexpression, CD5:CD19 coexpression, CD4:CD8 ratios and CD7 loss were summarised for histological pattern, concomitant diseases and follow-up course.ResultsWe generated the largest data set of benign lymph node immunophenotypes by an order of magnitude. B and T cell antigen outliers often had background immunosuppression or inflammatory disease but did not subsequently develop lymphoma.ConclusionsDiagnostic immunophenotyping data from benign lymph nodes provide normative ranges for clinical use. Outliers raising suspicion for B or T cell lymphoma are not infrequent (26% of benign lymph nodes). Caution is indicated when interpreting outliers in the absence of excisional biopsy or clinical history, particularly in patients with concomitant immunosuppression or inflammatory disease.

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Seasonal Dynamics in the Number and Composition of Coliform Bacteria in Drinking Water Reservoirs

10.1101/2021.02.16.428560 ◽

2021 ◽

Author(s):

Carolin Reitter ◽

Heike Petzoldt ◽

Andreas Korth ◽

Felix Schwab ◽

Claudia Stange ◽

...

Keyword(s):

Climate Change ◽

Drinking Water ◽

Microbial Community ◽

Water Temperature ◽

Surface Waters ◽

Coliform Bacteria ◽

List Type ◽

Water Production ◽

Water Reservoirs ◽

Drinking Water Production

AbstractWorldwide, surface waters like lakes and reservoirs are one of the major sources for drinking water production, especially in regions with water scarcity. In the last decades, they have undergone significant changes due to climate change. This includes not only an increase of the water temperature but also microbiological changes. In recent years, increased numbers of coliform bacteria have been observed in these surface waters. In our monitoring study we analyzed two drinking water reservoirs (Klingenberg and Kleine Kinzig Reservoir) over a two-year period in 2018 and 2019. We detected high numbers of coliform bacteria up to 2.4 x 104 bacteria per 100 ml during summer months, representing an increase of four orders of magnitude compared to winter. Diversity decreased to one or two species that dominated the entire water body, namely Enterobacter asburiae and Lelliottia spp., depending on the reservoir. Interestingly, the same, very closely related strains have been found in several reservoirs from different regions. Fecal indicator bacteria Escherichia coli and enterococci could only be detected in low concentrations. Furthermore, fecal marker genes were not detected in the reservoir, indicating that high concentrations of coliform bacteria were not due to fecal contamination. Microbial community revealed Frankiales and Burkholderiales as dominant orders. Enterobacterales, however, only had a frequency of 0.04% within the microbial community, which is not significantly affected by the extreme change in coliform bacteria number. Redundancy analysis revealed water temperature, oxygen as well as nutrients and metals (phosphate, manganese) as factors affecting the dominant species. We conclude that this sudden increase of coliform bacteria is an autochthonic process that can be considered as a mass proliferation or “coliform bloom” within the reservoir. It is correlated to higher water temperatures in summer and is therefore expected to occur more frequently in the near future, challenging drinking water production.HighlightsColiform bacteria proliferate in drinking water reservoirs to values above 104 per 100 mlThe genera Lelliottia and Enterobacter can form these “coliform blooms”Mass proliferation is an autochthonic process, not related to fecal contaminationsIt is related to water temperature and appears mainly in summerIt is expected to occur more often in future due to climate changeGraphical abstract

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