Variable selection and multivariate methods for the identification of microorganisms by flow cytometry

Application of flow cytometry for rapid, high-throughput, multiparametric analysis of environmental microbiomes

Quantification of the abundance and understanding of the dynamics of the microbial communities is essential to establish a basis for microbiome characterization. The conventional techniques used for the quantification of microbes are complicated and time-consuming. With scientific advancement, many techniques evolved and came into account. Among them, flow cytometry is a robust, high-throughput technique through which microbial dynamics, morphology, microbial distribution, physiological characteristics, and many more attributes can be studied in a high-throughput manner with comparatively less time and resources. Flow cytometry, when combined with other omics-based methods, offers a rapid and efficient platform to analyze and understand the composition of microbiome at the cellular level. The microbial diversity observed through flow cytometry will not be equivalent to that obtained by sequencing methods, but this integrated approach holds great potential for high throughput characterization of microbiomes. Flow cytometry is regarded as an established characterization tool in haematology, oncology, immunology, and medical microbiology research; however, its application in environmental microbiology is yet to be explored. This comprehensive review aims to delve into the diverse environmental applications of flow cytometry across various domains, including but not limited to bioremediation, landfills, anaerobic digestion, industrial bioprocesses, water quality regulation, and soil quality regulation. By conducting an in-depth analysis, this article seeks to shed light on the potential benefits and challenges associated with the utilization of flow cytometry in addressing environmental concerns.

Flow Cytometric Single-Cell Identification of Populations in Synthetic Bacterial Communities

Bacterial cells can be characterized in terms of their cell properties using flow cytometry. Flow cytometry is able to deliver multiparametric measurements of up to 50,000 cells per second. However, there has not yet been a thorough survey concerning the identification of the population to which bacterial single cells belong based on flow cytometry data. This paper not only aims to assess the quality of flow cytometry data when measuring bacterial populations, but also suggests an alternative approach for analyzing synthetic microbial communities. We created so-called in silico communities, which allow us to explore the possibilities of bacterial flow cytometry data using supervised machine learning techniques. We can identify single cells with an accuracy >90% for more than half of the communities consisting out of two bacterial populations. In order to assess to what extent an in silico community is representative for its synthetic counterpart, we created so-called abundance gradients, a combination of synthetic (i.e., in vitro) communities containing two bacterial populations in varying abundances. By showing that we are able to retrieve an abundance gradient using a combination of in silico communities and supervised machine learning techniques, we argue that in silico communities form a viable representation for synthetic bacterial communities, opening up new opportunities for the analysis of synthetic communities and bacterial flow cytometry data in general.

Computational analysis of high-throughput flow cytometry data

INTRODUCTION

Flow cytometry has been around for over 40 years, but only recently has the opportunity arisen to move into the high-throughput domain. The technology is now available and is highly competitive with imaging tools under the right conditions. Flow cytometry has, however, been a technology that has focused on its unique ability to study single cells and appropriate analytical tools are readily available to handle this traditional role of the technology.

AREAS COVERED

Expansion of flow cytometry to a high-throughput (HT) and high-content technology requires both advances in hardware and analytical tools. The historical perspective of flow cytometry operation as well as how the field has changed and what the key changes have been discussed. The authors provide a background and compelling arguments for moving toward HT flow, where there are many innovative opportunities. With alternative approaches now available for flow cytometry, there will be a considerable number of new applications. These opportunities show strong capability for drug screening and functional studies with cells in suspension.

EXPERT OPINION

There is no doubt that HT flow is a rich technology awaiting acceptance by the pharmaceutical community. It can provide a powerful phenotypic analytical toolset that has the capacity to change many current approaches to HT screening. The previous restrictions on the technology, based on its reduced capacity for sample throughput, are no longer a major issue. Overcoming this barrier has transformed a mature technology into one that can focus on systems biology questions not previously considered possible.

Genome-wide analysis of longevity in nutrient-deprived Saccharomyces cerevisiae reveals importance of recycling in maintaining cell viability

Although typically cosseted in the laboratory with constant temperatures and plentiful nutrients, microbes are frequently exposed to much more stressful conditions in their natural environments where survival and competitive fitness depend upon both growth rate when conditions are favourable and on persistence in a viable and recoverable state when they are not. In order to determine the role of genetic heterogeneity in environmental fitness we present a novel approach that combines the power of fluorescence-activated cell sorting with barcode microarray analysis and apply this to determining the importance of every gene in the Saccharomyces cerevisiae genome in a high-throughput, genome-wide fitness screen. We have grown > 6000 heterozygous mutants together and exposed them to a starvation stress before using fluorescence-activated cell sorting to identify and isolate those individual cells that have not survived the stress applied. Barcode array analysis of the sorted and total populations reveals the importance of cellular recycling mechanisms (autophagy, pexophagy and ribosome breakdown) in maintaining cell viability during starvation and provides compelling evidence for an important role for fatty acid degradation in maintaining viability. In addition, we have developed a semi-batch fermentor system that is a more realistic model of environmental fitness than either batch or chemostat culture. Barcode array analysis revealed that arginine biosynthesis was important for fitness in semi-batch culture and modelling of this regime showed that rapid emergence from lag phase led to greatly increased fitness. One hundred and twenty-five strains with deletions in unclassified proteins were identified as being over-represented in the sorted fraction, while 27 unclassified proteins caused a haploinsufficient phenotype in semi-batch culture. These methods thus provide a screen to identifying other genes and pathways that have a role in maintaining cell viability.

Multivariate data analysis methods for the interpretation of microbial flow cytometric data

Flow cytometry is an important technique in cell biology and immunology and has been applied by many groups to the analysis of microorganisms. This has been made possible by developments in hardware that is now sensitive enough to be used routinely for analysis of microbes. However, in contrast to advances in the technology that underpin flow cytometry, there has not been concomitant progress in the software tools required to analyse, display and disseminate the data and manual analysis, of individual samples remains a limiting aspect of the technology. We present two new data sets that illustrate common applications of flow cytometry in microbiology and demonstrate the application of manual data analysis, automated visualisation (including the first description of a new piece of software we are developing to facilitate this), genetic programming, principal components analysis and artificial neural nets to these data. The data analysis methods described here are equally applicable to flow cytometric applications with other cell types.

Evaluation of the response of Lactobacillus rhamnosus VTT E-97800 to sucrose-induced osmotic stress

Environmental osmotic changes are one of the stresses live probiotics may encounter either in their natural habitats or as a result of usage in food formulations and processing. Response to osmotic stress, induced by sucrose, of the probiotic strain Lactobacillus rhamnosus VTT E-97800 (E800) was investigated. The fluorescence-based approach used, by combined staining with caboxyfluorescein (cFDA) and propidium iodide (PI) could give insights on the osmotic-induced changes of microbial esterase activity and membrane integrity; also the extrusion of intracellular accumulated carboxyfluorescein (cF) upon energizing with glucose. Comparison of the flowcytometric viability assessment with the conventional culture techniques revealed that sucrose-stressed cells had a slight loss of culturability (logN/N(0) approximately -0.3) at 1.2 and 1.5M sucrose concentration though they could perform an enzymatic conversion of cFDA into cF. The presence of such metabolically active bacteria in food might be critical as they may excrete toxic or food spoilage metabolites. Moreover, the perturbation of cF extrusion activities became a limiting factor for reproductive capacities. There was no change in the cell morphology. These results proved the ability of the strain of study to tolerate sucrose, even at extreme concentrations and these must be taken into consideration for its usage in the formulation/processing of sugar-based foods, e.g. jams, candies, etc.

Membrane-based on-line optical analysis system for rapid detection of bacteria and spores

We report here the adaptation of our electronic microchip technology towards the development of a new method for detecting and enumerating bacterial cells and spores. This new approach is based on the immuno-localization of bacterial spores captured on a membrane filter microchip placed within a flow cell. A combination of microfluidic, optical, and software components enables the integration of staining of the bacterial species with fully automated assays. The quantitation of the analyte signal is achieved through the measurement of a collective response or alternatively through the identification and counting of individual spores and particles. This new instrument displays outstanding analytical characteristics, and presents a limit of detection of approximately 500 spores when tested with Bacillus globigii (Bg), a commonly used simulant for Bacillus anthracis (Ba), with a total analysis time of only 5 min. Additionally, the system performed well when tested with real postal dust samples spiked with Bg in the presence of other common contaminants. This new approach is highly customizable towards a large number of relevant toxic chemicals, environmental factors, and analytes of relevance to clinical chemistry applications.

Gut microorganisms, mammalian metabolism and personalized health care

The mammalian gut microbiota interact extensively with the host through metabolic exchange and co-metabolism of substrates. Such metabolome-metabolome interactions are poorly understood, but might be implicated in the aetiology of many human diseases. In this paper, we assess the importance of the gut microbiota in influencing the disposition, fate and toxicity of drugs in the host, and conclude that appropriate consideration of individual human gut microbial activities will be a necessary part of future personalized health-care paradigms.

Bacteriological examination of ballast water in Singapore Harbour by flow cytometry with FISH

In this study the concentrations of total bacteria, enterobacteria, Vibrio spp., and E. coli have been compared for ballast water samples taken from ships in Singapore Harbour. The cell concentrations were enumerated using FISH and flow cytometry. The data were highly variable, reflecting the many influences upon ballast water as it is utilized in the shipping industry. The concentration of bacterial species was determined as a proportion of the total concentration of cells for the ballast water sampled. For the ballast water sampled these concentrations were 0.67-39.55% for eubacteria, 0-2.46% for enterobacteria, 0.18-35.82% for Vibrio spp., and 0-2.46% for E. coli. Using FISH and flow cytometry, an informative determination of the bacterial hazards of ship ballast water can be made.

New approach for serological testing for leptospirosis by using detection of leptospira agglutination by flow cytometry light scatter analysis

Leptospirosis is considered an important reemerging infectious disease worldwide. The standard and most widespread method for the diagnosis of leptospirosis is the microscopic agglutination test (MAT). This test is laborious and time-consuming, and the interpretation of the results is subjective. In the present work we describe an application of flow cytometry (FCM) as a tool for the serological diagnosis of leptospirosis. The analysis is based on the sensitivity of FCM to the size and shape of the bacteria analyzed by measurement of light scatter parameters: forward scatter (FSC) and side scatter (SSC). The addition of positive serum to an infecting leptospiral serovar results in a shift of the light scatter parameter to a different location with higher FSC and SSC values, indicating the formation of leptospiral aggregates. By using immunofluorescent staining, we have shown that the large particles formed are the agglutinated leptospires. Quantification of the agglutination process has been achieved by calculating an agglutination factor (Af), based on changes in the light scatter parameters measured by FCM. Af enables us to determine the specificity of the serological reaction of the patient serum with each leptospiral serovar. In this work, 27 serum samples from 18 leptospirosis patients were tested by both the MAT and the FCM techniques, in which each serum sample was tested against 13 serovars. Twenty-six human serum samples derived from patients with a variety of other defined illnesses were used as negative controls and enabled us to define the Af threshold value as < 9.3 for negative patients, while any value higher than that would be a positive result for leptospirosis. Compared to MAT, the FCM technique was found to be more specific and sensitive, especially in identifying the serogroup in the acute phase of the disease. The whole process was found to be rapid and took less than 1.5 h. Moreover, FCM analysis is objective and can be automated for the handling of large numbers of samples.

Detection of frequency resonance energy transfer pair on double-labeled microsphere and Bacillus anthracis spores by flow cytometry

Development of an ultrasensitive biosensor for biological hazards in the environment is a major need for pollutant control and for the detection of biological warfare. Fluorescence methods combined with immunodiagnostic methods are the most common. To minimize background noise, arising from the unspecific adsorption effect, we have adapted the FRET (frequency resonance energy transfer) effect to the immunofluorescence method. FRET will increase the selectivity of the diagnosis process by introducing a requirement for two different reporter molecules that have to label the antigen surface at a distance that will enable FRET. Utilizing the multiparameter capability of flow cytometry analysis to analyze the double-labeling/FRET immunostaining will lead to a highly selective and sensitive diagnostic method. This work examined the FRET interaction of fluorescence-labeled avidin molecules on biotin-coated microspheres as a model system. As target system, we have used labeled polyclonal antibodies on Bacillus anthracis spores. The antibodies used were purified immunoglobulin G (IgG) molecules raised in rabbits against B. anthracis exosoporium components. The antibodies were fluorescence labeled by a donor-acceptor chromophore pair, alexa488 as a donor and alexa594 as an acceptor. On labeling the spores with alexa488-IgG as a donor and alexa594-IgG as an acceptor, excitation at 488 nm results in quenching of the alexa-488 fluorescence (E(q) = 35%) and appearance of the alexa594 fluorescence (E(s) = 22%), as detected by flow cytometry analysis. The FRET effect leads to a further isolated gate (FL1/FL3) for the target spores compared to competitive spores such as B. thuringiensis subsp. israelensis and B. subtilis. This new approach, combining FRET labeling and flow cytometry analysis, improved the selectivity of the B. anthracis spores by a factor of 10 with respect to B. thuringiensis subsp. israelensis and a factor of 100 with respect to B. subtilis as control spores.

Flow cytometry and conventional enumeration of microorganisms in ships' ballast water and marine samples

Conventional methods for bacteriological testing of water quality take long periods of time to complete. This makes them inappropriate for a shipping industry that is attempting to comply with the International Maritime Organization's anticipated regulations for ballast water discharge. Flow cytometry for the analysis of marine and ship's ballast water is a comparatively fast and accurate method. Compared to a 5% standard error for flow cytometry analysis the standard methods of culturing and epifluorescence analysis have errors of 2-58% and 10-30%, respectively. Also, unlike culturing methods, flow cytometry is capable of detecting both non-viable and viable but non-culturable microorganisms which can still pose health risks. The great variability in both cell concentrations and microbial content for the samples tested is an indication of the difficulties facing microbial monitoring programmes. The concentration of microorganisms in the ballast tank was generally lower than in local seawater. The proportion of aerobic, microaerophilic, and facultative anaerobic microorganisms present appeared to be influenced by conditions in the ballast tank. The gradual creation of anaerobic conditions in a ballast tank could lead to the accumulation of facultative anaerobic microorganisms, which might represent a potential source of pathogenic species.

Evolutionary engineering of industrially important microbial phenotypes

The tremendous complexity of dynamic interactions in cellular systems often impedes practical applications of metabolic engineering that are largely based on available molecular or functional knowledge. In contrast, evolutionary engineering follows nature's 'engineering' principle by variation and selection. Thus, it is a complementary strategy that offers compelling scientific and applied advantages for strain development and process optimization, provided a desired phenotype is amenable to direct or indirect selection. In addition to simple empirical strain development by random mutation and direct selection on plates, evolutionary engineering also encompasses recombination and continuous evolution of large populations over many generations. Two distinct evolutionary engineering applications are likely to gain more relevance in the future: first, as an integral component in metabolic engineering of strains with improved phenotypes, and second, to elucidate the molecular basis of desired phenotypes for subsequent transfer to other hosts. The latter will profit from the broader availability of recently developed methodologies for global response analysis at the genetic and metabolic level. These methodologies facilitate identification of the molecular basis of evolved phenotypes. It is anticipated that, together with novel analytical techniques, bioinformatics, and computer modeling of cellular functions and activities, evolutionary engineering is likely to find its place in the metabolic engineer's toolbox for research and strain development. This review presents evolutionary engineering of whole cells as an emerging methodology that draws on the latest advances from a wide range of scientific and technical disciplines.

Pattern recognition in flow cytometry

BACKGROUND

Analytical flow cytometry (AFC), by quantifying sometimes more than 10 optical parameters on cells at rates of approximately 10(3) cells/s, rapidly generates vast quantities of multidimensional data, which provides a considerable challenge for data analysis. We review the application of multivariate data analysis and pattern recognition techniques to flow cytometry.

METHODS

Approaches were divided into two broad types depending on whether the aim was identification or clustering. Multivariate statistical approaches, supervised artificial neural networks (ANNs), problems of overlapping character distributions, unbounded data sets, missing parameters, scaling up, and estimating proportions of different types of cells comprised the first category. Classic clustering methods, fuzzy clustering, and unsupervised ANNs comprised the second category. We demonstrate the state of the art by using AFC data on marine phytoplankton populations.

RESULTS AND CONCLUSIONS

Information held within the large quantities of data generated by AFC was tractable using ANNs, but for field studies the problem of obtaining suitable training data needs to be resolved, and coping with an almost infinite number of cell categories needs further research.

Detection of subgroups from flow cytometry measurements of heterotrophic bacterioplankton by image analysis

BACKGROUND

Flow cytometry is an invaluable tool for the analysis of large series of samples in aquatic microbial ecology. However, analysis of the resulting data is often inefficient or does not reflect the complexity of natural communities. Because bacterioplankton assemblages frequently fall into several clusters with respect to their cellular properties, these subgroups seem to be a promising level of abstraction. Image analysis was used to detect clusters from flow cytometry data. The method was tested on a bacterial community under heavy protozoan grazing pressure.

METHODS

A bivariate histogram of flow cytometry data was transformed into a gray-scale image for image analysis. After low-pass filtration, regional maxima were delimited by a watershed algorithm. The resulting areas were then used as gates on the original measurements.

RESULTS

Three clusters could be detected from the bacterial assemblage. Protozoan grazing had a strong impact on the bacterial community, which could be analyzed in detail at the level of individual subgroups.

CONCLUSIONS

Investigation at the level of bacterial subgroups allowed a more detailed analysis than whole-community statistics and delivered essential and ecologically meaningful information. Image analysis proved to be an adequate tool to detect the subgroups without a priori knowledge.

Phenotypic biomonitoring using multivariate flow cytometric analysis of multi-stained microorganisms

A new method for monitoring phenotypic profiles of pure cultures and complex microbial communities was evaluated. The approach was to stain microorganisms with a battery of fluorescent dyes prior to flow cytometry analysis (FCM) and to analyse the data using multivariate methods, including principal component analysis and partial least squares. The FCM method was quantitatively evaluated using different mixtures of pure cultures as well as microbial communities. The results showed that the method could quantitatively and reproducibly resolve both populations and communities of microorganisms with 5% abundance in a diverse microbial background. The feasibility of monitoring complex microbial communities over time during the biodegradation of naphthalene using the FCM method was demonstrated. The biodegradation of naphthalene occurred to differing extents in microcosms representing three different types of aromatic-contaminated groundwater and a sample of bio-basin water. The FCM method distinguished each of these four microbial communities. The phenotypic profiles were compared with genotypic profiles generated by random-amplified polymorphic DNA analysis. The genotypic profiles of the microbial communities described only the microbial composition, and not their functional change, whereas the phenotypic profiles seemed to contain information on both the composition and the functional change of the microorganisms. Furthermore, event analysis of the FCM data showed that microbial communities with initially differing compositions could converge towards a similar composition if they had a capacity for high levels of degradation, whereas microbial communities with similar initial compositions could diverge if they differed in biodegrading ability.

Individual Escherichia coli cells studied from light scattering with the scanning flow cytometer

BACKGROUND

Flow cytometry is a powerful tool for the analysis of individual particles in a flow. Differential light scattering (an indicatrix) was used for many years to obtain morphologic information about microorganisms. The indicatrices play the same role for individual particle recognition as a spectrum for substance characterization. We combined two techniques to analyze the indicatrix of the cells for the purpose of developing a database of light-scattering functions of cells.

METHODS

The scanning flow cytometer (SFC) allows the measurement of the entire indicatrix of individual particles at polar angles ranging from 5 degrees to 100 degrees. In this work, light-scattering properties of Escherichia coli have been studied both experimentally and theoretically with the SFC and the T-matrix method, respectively. The T-matrix method was used because of the nonspherical shape of E. coli cells, which were modeled by a prolate spheroid.

RESULTS

The indicatrices of E. coli cells were stimulated with T-matrix method at polar angles ranging from 10 degrees to 60 degrees. The absolute cross-section of light scattering of E. coli has been determined comparing the cross section of polystyrene particles modeled by a homogeneous sphere. The E. coli indicatrices were compared for logarithmic and stationary phases of cell growth.

CONCLUSIONS

The indicatrices of E. coli were reproducible and could be used for identification of these cells in biologic suspensions. The angular location of the indicatrix minimum can be used in separation of cells in logarithmic and stationary phases. To use effectively the indicatrices for that purpose, the light-scattering properties of other microorganisms have to be studied.

Flow cytometric analysis of microorganisms

The application of flow cytometry to microorganisms is as old as the technique itself, but it has historically been underexploited for microbial applications. This is now being reversed and microbiologists are ideally placed to benefit from recent technological advances. While earlier papers demonstrated the use of flow cytometry for studies of viability and taxonomy, recent developments in bioinformatics and reporter gene technologies are leading to novel applications in microbiology. Variants of green fluorescent protein have been used for the study of conditional microbial gene regulation in medically important host-pathogen interactions and fluorescence-activated cell sorting is being applied to the isolation of novel mutants in directed evolution studies. This paper reviews the reasons for the delay in the application of flow cytometry to microbial problems, the range of applications, and their limitations and considers the progress made in developing new strategies for use in microbiological investigations.

Instrumentation of biotechnological processes

Modern bioprocesses are monitored by on-line sensing devices mounted either in situ or externally. In addition to sensor probes, more and more analytical subsystems are being exploited to monitor the state of a bioprocess on-line and in real time. Some of these subsystems deliver signals that are useful for documentation only, other, less delayed systems generate signals useful for closed loop process control. Various conventional and non-conventional monitoring instruments are evaluated; their usefulness, benefits and associated pitfalls are discussed.