FIELD OF THE INVENTION

[0001] The present invention is in the field of microbiology and relates to methods for measuring the modulation of bacterial growth. In particular, the present invention relates to the selection of microbiota from natural occurring microbiological communities to prepare model microbiota to study the effects of chemicals or other microorganisms on the growth dynamics of assemblies of microorganisms.

BACKGROUND OF THE INVENTION

[0002] Solid media for cultivation of microorganisms have been used since early 19th century and remain the gold standard for microbiologists. They allow the isolation of single colonies of bacteria and yeasts. The addition of antibiotics or precise formulation of media composition, such that only a subset of microorganisms are able to grow, can render the growth media selective. One major drawback of cultivation of microorganisms on Petri plates containing solid media is the very low throughput. Some efforts have been made to automate their use of mainly to improve throughput for diagnostics (Previ Isola, Biomerieux) or screening (Colony Piking robot, Tecan). Both solutions rely on robotics, which are expensive, complicated to put in place and run, require a significant investment and are not practical for studying interactions between different organisms or between microorganisms and arrays of chemicals.

[0003] Another classical approach involves the use of liquid cultures in various containers: classically tubes and flasks, and more recently microtiter plates. Microtiter plates allow parallelization and the possibility of working with larger numbers of samples. They remain the standard solution for parallelization, high-throughput screening, handling of chemical or mutant libraries as well as for antibiotic susceptibility testing. Automatizing microtiter plates was developed by various companies specialized in robotics and is used to increase the throughput for screening in industrial settings and implement more complex workflows. It remains limited by the heterogeneities inherent in the microtiter-based culture (multiple interfaces, poor mixing, evaporation of small volumes, etc.). Also, measuring growth modulation of a biological system such as bacterial cultures commonly requires a high number of replicates to compensate for the inherent variability in growth kinetics. Hence, even using robotic solutions remains expensive, technologically complicated to put in place, and limited in throughput.

[0004] Some effort has been made to develop time lapse microscopy coupled with microchannels where growth of individual cells can be dynamically followed using video microscopy. Said method is powerful and can be used to study fine growth dynamics and influences of various compounds. Nevertheless, this method is limited in throughput and by the kind of interactions that can be studied. Only the influence of selected chemicals can be examined and not the effects of other microbes.

[0005] In fundamental microbiology and in various industrial applications of microbiology there is an interest in measuring the modulation of bacterial growth of either individual species or of a comprehensive population of all bacteria making up a specific ecological niche, the microbiota. Microbiota is the sum of all microorganisms populating a given ecological niche such as different (human) skin areas, the gut, the oral cavity, but also different environments such as soil, water. With the advent of the research on the microbiome, it has become clear that besides pathogenic bacteria that are harmful to living organisms, there are many bacterial species that interact in positive ways to stimulate homeostasis. Because of this expanding impact on microbiology on all aspects of human and environmental health, there is increasing interest in understanding the dynamics of various microbial communities and how they change in response to perturbations. It is of interest to understand the conditions that stimulate the growth and development of microbial species with beneficial and harmful effects. [0006] There are few in vitro test methods available. They commonly comprise epidermal skin model in the case of skin microbiome analysis as growth support for bacterial strains and measurements such as specifically measuring skin adhesion. However, usually only very few bacterial strains can be tested at the same time making this method inappropriate for testing of a more complex bacterial community as is required for a representative test analysis for modulation of the microbiome. Changes in abundance are tested commonly by real-time quantitative PCR.

[0007] Thus, model systems are missing that evaluate the impact of chemical compounds, cosmetic ingredients or drug compounds on the modulation of the microbiome in an easy noncomplex manner. Commonly real-life data need to be generated in animal models or in human trials to determine the effect of such substances on the microbiota which are rather low throughput, cumbersome and complex in measurement. That prevents studying of growth dynamics of communities of bacteria for many substances at the same time. To solve this problem the inventors have: a) characterized by deep sequencing the overall microbiome composition for human target samples (in this specific case the skin microbiome from different body areas), b) determined a "reference microbiome composition" across gender, age, skin phototype, c) isolated the strains from human individuals to create master cell banks of such strains, d) and developed a simple method to measure growth modulation of all strains of such representative skin microbiome by OD measurement and kinetic growth analysis in microtiterplate culture that can be easily automated and parallelized.

[0008] Cultivation of bacteria and fungi in droplets has been perfected by the applicant under aerobic, anaerobic and microaerophilic conditions and including a wide variety of culture media. High throughput culturomics is achieved with up to 10 ⁹ individual droplets that can be created in a single day using up to (but not limited to) 40 different growth media. This method was developed for the skin microbiome but the same principle can be applied to any type of microbiota.

[0009] Using a "representative microbiota community" makes screening of many substances for their impact on the microbiota for the first time feasible without complex studies comprising enrolment of patients or test individuals, applying substances, collection samples, processing samples for sequencing analysis etc. [0010] Due to the complexities of microbial communities that constitute most of the microbiota of interest (human, animal, plant, and environmental), standard microbiological methods, such as screening for growth modulation by optical density measurements in microtiter plates, do not provide the necessary throughput to capture growth dynamics of a large number of strains under a variety of conditions (presence of various chemicals, other strains, etc.). The use of microfluidic technology surmounts this problem of throughput by using droplets as incubation vessels for microbes and increasing the throughput by orders of magnitude. The present invention reports the use of droplet microfluidics for studying the growth dynamics of communities of bacteria in the presence of various perturbations such as various chemicals or other microorganisms. The present invention can be used to establish model microbial assemblies representative of microbiota of interest (skin microbiota, intestinal, plant, etc.) and to examine their growth dynamics after perturbations such as with an array of chemicals or other microorganisms.

BRIEF DESCRIPTION OF THE INVENTION

[0011] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one skilled in the art to which this technology belongs. Although all methods and materials similar or equivalent to those described herein may be used in practice or in testing the present technology, the preferred methods, devices and materials are now described.

[0012] The present invention uses microfluidics droplets for studying the growth dynamics of communities of bacteria in the presence of various perturbations such as various chemicals or other microorganisms and to establish microbial assemblies model which is representative of a microbiota of interest and to examine their growth dynamics after perturbations such as with an array of chemicals or other microorganisms.

[0013] These microbiota models are then used for testing for interactions with arrays of chemical compounds or with other microbial species as follows: High-throughput incorporation of a chemical library (or a microorganism or microorganisms of interest whose effect is to be tested) in microfluidic droplets along with the appropriate barcodes for facile downstream identification of active extracts

Encapsulation of single cells of each individual bacterial strain from the model microbiota in microfluidic droplets along with appropriate barcodes

Fusion of droplets containing the chemical library (or a microorganism of interest) with the droplets containing bacteria

Incubation under appropriate conditions (temperature and atmosphere, i.e. aerobic and anaerobic) - Sorting of droplets based on the effects of the chemical compounds on growth (some chemicals may enhance the growth of microorganisms and lead to the production of higher biomass, some chemicals may have neutral effects in they produce no change in the microbial biomass, and some chemicals may have inhibitory effects where the production of biomass by the microorganisms is detectably diminished) - Identification of active compounds by analysis of the barcodes and downstream bioinformatic analysis

BRIEF DESCRIPTION OF THE FIGURES

[0014] Figure 1: A schematic representation of encapsulation of bacteria in droplets, fusion of said droplets with droplets containing the chemical array and their incubation under specific conditions.

[0015] Figure 2: A schematic representation of sorting droplets based on inhibition, enhancement or no effect of bacterial growth and identification of the active compounds.

[0016] Figure 3: Analysis of the bacterial biomass present in the droplets, wherein the biomass can be detected by proxies for optical density. [0017] Figure 4: Bacterial species identified by color-coding the droplet population with mixtures of different concentrations of at least 2 fluorescent indicator dyes by creating a matrix of droplet population, wherein each droplet population for each bacterial strain is labeled with a specific dye mixture. [0018] Figure 5: Scheme of the droplet barcode library preparation for lllumina sequencing.

[0019] Figure 6: Enrichment of droplets with desired biomass increase presented by ratio of abundance of barcodes in sorted vs. unsorted population.

[0020] Figure 7: Results from growth modulation screening for a skin microbiome model after A: 24 h; B: 48 h; C: 72 h. Impact of a plant derived ingredient at different concentrations (from

0.000001% to 5%) on the growth of bacterial strains present in the facial microbiota model of healthy skin is shown. Diagnonal line background indicates stimulation of growth, dotted background indicates inhibition. The significance and the associated p values are indicated by asterisk DETAILED DESCRIPTION OF THE INVENTION

[0021] The present invention relates to the use of droplet microfluidics to study the effects of chemicals or other microorganisms on the growth dynamics of assemblies of microorganisms.

[0022] The applicant's invention relates to the use of a representative (skin) microbiome model to study the effects of defined chemicals, ingredient mixtures such as plant lysates or other complex mixtures of substances of known or unknown identity or other microorganisms (including phages and viruses) on the growth dynamics of assemblies of microorganisms.

[0023] As used herein, the term "microorganism" refers to bacteria, fungi, yeast, archaea, viruses and phages.

[0024] As used herein, the term "biological substance" refers to plant extracts, supernatants of bacterial or yeast cultures, antibodies, peptides, carbohydrate molecules, lipids, proteins, etc.

[0025] As used herein, the term "chemical substance" refers to any material with a definite chemical composition and comprises any organic or inorganic substance of a particular molecular identity and may exist in different physical states such as a liquid, a solid or gas. Examples comprise but are not limiting to alcohols, aldehydes, esters, terpenes, aromatics, ketones, lactones, thiols, hormones, amines, siderophores, acids, antimicrobials, fungicides, toxins. [0026] As used herein, the term "chemical or biological library" refers to the collection of biological or chemical substances organized in an ordered way that may contain hundreds or thousands of different substances.

[0027] As used herein, the term "microbiota" refers to ecological communities of commensal, symbiotic and pathogenic microorganisms found in and on all multicellular organisms studied to date from plants to animals. Microbiota includes bacteria, archaea, protists, fungi, viruses or phages.

[0028] As used herein, the term "growth medium" refers to a solid, liquid or semi-solid designed to support the growth of microorganisms or cells. Different types of media are used for growing the different types of cells.

[0029] As used herein, a "microfluidic system" is a "microfluidic device" or "microfluidic chip" or "synthesis chip" or "lab-on-a-chip" or "chip" is a unit or device that permits the manipulation and transfer of microliters or nanoliters or picoliters of liquid ("droplet", "microfluidic droplet") into a substrate comprising micro-channels. The device is configured to allow the manipulation of liquids, including reagents and solvents, to be transferred or conveyed within the micro channels and reaction chamber using mechanical or non-mechanical pumps.

[0030] As used herein, the term "droplet" refers to a measure of volume and further relates to an isolated portion of a fluid. As used herein, the terms "first", "second" and "third" population of droplets are used to discriminate droplets according to their content. As the method is performed in a microfluidic system, the term "droplet" also refers to "microfluidic droplet".

[0031] Microbiota are of great importance for human health and all earth ecosystems, yet current research is hampered by the absence of standardized and reproducible model microbial systems. The adoption of standard model organisms in cell and molecular biology allowed great leaps in the understanding of physiological processes by enabling reproducible experimentation and controlled perturbations. Microbiome research and various associated industrial applications would likewise benefit from the establishment of carefully designed model communities of microbes that could be used for controlled experimentation as a representative of the more complex microbiota.

[0032] On the industrial side, e.g. the cosmetics and pharmaceutical industries are interested in testing the effects of various chemical compounds on the human microbiota. The development of a microbial community model with sufficient complexity to accurately represent these microbiomes would greatly facilitate such testing. Microfluidic technology permits the creation of such a microbial community system as well as the subsequent testing of the effects of various chemical compounds and/or other microorganisms on the microbiome.

[0033] To create a microbial community model that accurately represents a microbiota ecosystem, the species of bacteria to include in the model system need to be chosen and isolated from the original microbiota in pure culture. They are then stored in microtiter plates to form a master cell bank and revived for the need of experiments. The isolated strains are recombined to form model microbiota as a reference microbiome composition. These reference microbiome compositions can be used for testing interactions between the microbiomes and arrays of chemical compounds, ingredient mixtures such as plant lysates or other complex mixtures of substances of known or unknown identity or other microorganisms (including phages and viruses) or with other microbial species.

[0034] Using the power of microfluidic technology, the microbiota model is hardly limited to specific number of species but commonly include from approximately up to 100 species to up to 1000 species. These microbiota models are then used for testing for interactions with arrays of chemical compounds or with other microbial species as follows:

High-throughput incorporation of a chemical library (or a microorganism or microorganisms whose effect is to be tested) in microfluidic droplets along with the appropriate barcodes for facile downstream identification of active extracts - Encapsulation of single cells of each individual bacterial strain from the model microbiota in microfluidic droplets along with appropriate barcodes

Fusion of droplets containing the chemical library (or a microorganism of interest) with the droplets containing bacteria Incubation under appropriate conditions (temperatures in the range of 10 °C to 95 °C and under aerobic, microaerophilic or anaerobic atmosphere conditions)

Sorting of droplets on based the effects of the chemical compounds on growth (enhancement, neutrality, or inhibition) - Identification of active compounds by analysis of the barcodes and downstream bioinformatic analysis

[0035] Cultivation of bacteria and fungi in droplets has been perfected by the applicant under aerobic, anaerobic and microaerophilic conditions and including a wide variety of culture media. High throughput culturomics is achieved with up to 10 ⁹ individual droplets that can be created in a single day using up to (but not limited to) 40 different growth media. This method was developed for the skin microbiome but the same principle can be applied to any type of microbiota.

[0036] Due to the complexities of microbial communities that constitute most of the microbiota of interest (human, animal, plant, and environmental), standard microbiological methods, such as screening for growth modulation by optical density measurements in microtiter plates, do not provide the necessary throughput to capture growth dynamics of a large number of strains under a variety of conditions (presence of various chemicals, other strains, etc.). The use of microfluidic technology surmounts this problem of throughput by using droplets as incubation vessels for microbes and increasing the throughput by orders of magnitude. The present invention reports the use of droplet microfluidics for studying the growth dynamics of communities of bacteria in the presence of various perturbations such as various chemicals or other microorganisms. The present invention can be used to establish model microbial assemblies representative of microbiota of interest (skin microbiota, intestinal, plant, etc.) and to examine their growth dynamics after perturbations such as with an array of chemicals or other microorganisms. [0037] To create a model microbial community that accurately represents a microbiota ecosystem, the species of bacteria to include in the model system need to be chosen and isolated from the original microbiota in pure culture. They are then stored in microtiter plates and revived for the need of experiments. For ease of use, such models -if comprising lower number of strains, i.e., between 1-500 strains, preferably 1-200 strains and even more preferably 1-150 strains can be directly cultivated in liquid culture such like culturing in microtiter plates. These model microbiota are then used for testing for interactions with arrays of chemical compounds, ingredient mixtures such as plant lysates or other complex mixtures of substances of known or unknown identity or other microorganisms (including phages and viruses) or with other microbial species as follows:

• Inoculation of bacterial strains in liquid culture using strain-specific suitable conditions such as growth medium, temperature (10 - 95 °C) and atmospheric condition (aerobic, anaerobic, microaerophilic)

• Inoculating each strain for each compound, mixture or microorganisms testing in at least one culture or replicates thereof

• Selecting for each compound, mixture or microorganism one concentration or amount or optionally testing various concentrations or amounts and mixing all components for testing growth kinetics

• Comparing the growth kinetics of each strain being such treated in comparison with a strain that is cultured without the addition of a compound, mixture or microorganism

• And determining the change in growth under treatment

• Conducting the method as described above wherein the measurement of the growth kinetic is done by means of OD measurement or alternative fluorescent measurement, scattering or image analysis, i.e., grey values.

[0038] Using the above mentioned methods a representative model of human skin microbiome was established. By deep sequencing the overall microbiome composition for human skin microbiome from different body areas was characterized. Thus, a "reference microbiome composition" across gender, age, skin phototype was determined. The identified strains were isolated from human individuals to create master cell banks of such strains. An overview of the composition of the thus obtained representative skin microbiota is presented in tab. 1. A suitable microbiome model of human skin microbiota may thus be characterized by any of the following criteria:

• comprising genera with a prevalence of at least 1%, preferably >5%, more preferably >10% and most preferably >20% on the human skin (Tab. 1), • comprising at least 1, preferably 2 and most preferably >3 genera as listed in Tab. 1,

• comprising pathobiont bacterial strains,

• containing at least one of the following species: Staphylococcus aureus, Staphylococcus epidermidis, Cutibacterium acnes. [0039] According to the present invention, barcodes can be of different nature such as but not limited to barcodes consisting of nucleotide (DNA) combinations that can be analyzed by sequencing or varying concentrations of dyes or mixtures of dyes, more preferably of fluorescent dyes or fluorescent particles. The current invention is not thought to limit the investigation of microbiota to those inhabiting living organisms such as humans, animals or plants. Although the current invention describes bacterial species, the microbiota also comprises fungi, yeast, archaea, viruses and phages and shall not be limited to bacteria only.

[0040] Microbial species forming microbiota can be selected from a wide variety of origins comprising ecological communities of commensal, symbiotic and pathogenic microorganisms of skin, gastrointestinal tract, mouth, nose, respiratory organs, vagina or urogenital tract or other surfaces of plants or animals or environmental samples.

[0041] The present invention refers to a method for assessing the effect of a chemical or biological substance on the growth of microorganisms comprising the steps of: a) generating a first population of droplets, wherein said droplets of first population comprise chemical or biological compounds from a chemical or biological library, b) generating a second population of droplets, wherein said second population of droplets comprise microorganisms, c) fusing the droplets of first and second population, thereby generating a third population of droplets, wherein said third population comprises compounds from a chemical or biological library and microorganisms, d) incubating said third population of droplets under specific conditions of temperature and atmosphere, e) analyzing the effect of the chemical or biological compounds on the growth of microorganisms; the effects can include enhancement or inhibtion of microbial biomass production. [0042] In one embodiment, the chemical or biological substance is selected from the group comprising an antibody, an organic, an inorganic compound, a pharmaceutically active substance and/or an organism.

[0043] In one embodiment the droplet size is in the 20 pL range. [0044] In one embodiment, the first populations of droplets further comprises a unique DNA barcode.

[0045] In one embodiment, the barcodes can be analyzed by sequencing or varying concentrations of dyes or mixtures of dyes, more preferably of fluorescent dyes or fluorescent particles. [0046] In one embodiment, in the droplet library, each individual droplet contains a single chemical compound from the chemical library along with a unique DNA barcode for facile downstream identification by sequencing.

[0047] In one embodiment, the microorganism to be analyzed is selected from the group comprising bacteria, fungi and/or viruses. [0048] In one embodiment, the microorganism to be analyzed is an anaerobic bacterium.

[0049] In one embodiment, the effect of the chemical or biological compound is analyzed via a potential change of the microbial biomass.

[0050] In one embodiment, the effect of the chemical or biological compound is enhancement, neutrality, or inhibition on cell growth. [0051] The method for assessing the effect of a chemical or biological substance on the growth of microrganisms further comprises the step of adding a fluorescent marker (such as a cell viability dye, or a fluorescent dye that specifically stains DNA, RNA, lipids, or peptidoglycan) to the microorganism to be analyzed. [0052] The present invention refers to an microfluidic apparatus for assessing the effect of a chemical or biological substance on the growth of a microorganism comprising:

(a) a first microfluidic device for incorporating a chemical or biological substance into a first population of droplet; (b) a second microfluidic device for incorporating a microorganism into a second population of droplets;

(c) a microchannel wherein the first and second population of droplets from the first and second microfluidic devices are combined and said first and second population of droplets are fused;

(d) a sorting unit. [0053] In one embodiment, the apparatus further comprising a fluorescent detector.

[0054] In one embodiment, the sorting unit is connected to a FACS.

[0055] In one embodiment, the chemical or biological substance is selected from the group comprising an antibody, an organic, an inorganic compound, a pharmaceutically active substance and/or an organism. [0056] In one embodiment, the droplet size is in the 20 pL range.

[0057] In one embodiment, the first populations of droplets further comprises a unique DNA barcode.

[0058] In one embodiment, the barcodes can be analyzed by sequencing or varying concentrations of dyes or mixtures of dyes, more preferably of fluorescent dyes or fluorescent particles.

[0059] In one embodiment, in the droplet library, each individual droplet contains a single chemical compound from the chemical library along with a unique DNA barcode for facile downstream identification.

[0060] In one embodiment, the microorganism to be analyzed is selected from the group comprising bacteria, fungi and/or viruses. [0061] In one embodiment, the microorganism to be analyzed is an anaerobic bacterium.

[0062] In one embodiment, the effect of the chemical or biological compound is analyzed via fluorescent, OD, or image analysis.

[0063] In one embodiment, the effect of the chemical or biological compound is enhancement, neutrality, or inhibition on cell growth.

High-throughput incorporation of the chemical library in microfluidic droplets

[0064] As used herein, a droplet library refers to a library containing a defined chemical array is generated to screen for effects on growth on bacteria. In the droplet library, each individual droplet contains a single chemical compound from the chemical library along with a unique DNA barcode for facile downstream identification. As used herein, the chemical array comprises at least two chemicals and up to thousands of distinct chemicals.

Encapsulation of representative (skin) bacteria in droplets and incubation.

[0065] The encapsulation of bacteria in the appropriate growth medium in microfluidic droplets is performed using specialized microfluidic chips. Briefly, the sample preparation is sufficiently diluted and the bacteria are encapsulated in droplets on a PDMS-based microfluidic chip. Dilution is required to ensure the single bacterial cell per droplet. Droplets are comprised of cells and the culture medium along with the fluorescent dyes (such as a cell viability dye, or a fluorescent dye that specifically stains DNA, RNA, lipids, or peptidoglycan) that are incorporated at the same time or added later, according to the needs of the workflow. Each droplet contains single bacteria of the model microbiome along with a unique barcode. The droplet size is generally in the ~ 20 pL range.

Fusion of droplets containing bacteria with droplets containing the chemical array and their incubation under appropriate conditions

[0066] To carry out the testing of the effects of the chemical compounds on the growth of bacteria, the droplets containing the chemical library have to be fused with the droplets containing bacteria. This will be done using the proprietary workflow using a specific microfluidic chip on the Biomillenia platform. The droplets will then be incubated off the chip under the appropriate conditions (temperature and atmosphere) before being reinjected onto a microfluidic chip subjected to sorting. Alternatively, the droplets can also be sorted by other means such as FACS. A schematic representation of this part of the workflow is shown in Figure 1.

Droplets sorting based on inhibition, enhancement or no effect of bacterial growth and identification of the active compounds.

[0067] After sufficient incubation of droplets that depends on the growth kinetics of the microbiota or bacterial community under study, but is in the range of 12h-7 days, are subjected to high-throughput sorting on the microfluidic platform, and the droplets containing compounds having the desired activity on growth (enhancement, neutrality, inhibition) are separated from the droplets with no activity (as shown diagrammatically in Figure 2).

[0068] The separation of the droplets based on the effect on growth (enhancement, neutrality, or inhibition) is done by examining the bacterial biomass present in the droplets (as shown diagrammatically below). The bacterial biomass can be detected by proxies for optical density such as but not limited to imaging or fluorescent measurement (e.g. cell staining fluorescent dyes). The gating for sorting is adjusted to include the appropriate fractions of the total bacterial population (Figure 3).

[0069] This process can be run either once or will be iterated several times to eliminate possible false-positive and false-negatives by averaging a high number of replicate droplets for each bacterial species. This is easily done by droplet microfluidics but is hardly feasible with any other method such as robotic handling of microtiter plates due to the high number of replicates needed. Bacterial populations of different biomass may be sorted due to variabilities in growth induced by the chemical or biological substances. [0070] The examination (via the barcodes) of the content of the gates from the sample treated by libraries of biological or chemical substances reveals the distributions of species present. Shifts in these distributions induced by presence of chemicals are indicative of the effect of that specific chemical compound. Given the large number of droplets involved, this statistical approach smooths some of the inevitable biological variability that arises in the system.

[0071] Additionally, the affected bacterial species can be identified by color-coding the droplet population with mixtures of varying concentrations of at least 2 fluorescent indicator dyes creating a matrix of droplet population with each a specific dye mixture for each bacterial strain. An example is shown in the Figure 4.

Identification of active and inactive compounds by sequencing of the barcodes and downstream bioinformatic analysis

[0072] The active and inactive compounds in these droplets are identified based on the barcodes present. The sorted droplets are demulsified and the DNA contents analyzed for the frequency of the barcodes in the sorted droplet population.

[0073] In another application, the microbial model population might not be challenged with regard to the impact of chemical substances or drug compounds on the microbiota model but with the challenge of other bacterial species such as but not limited to pathobiont bacteria. [0074] Typical applications include but are not limited to: a) screening of chemical compound libraries on the growth of the microbiota or specific species thereof such as for cosmetic ingredient screening, pharmaceutical compound screening, environmental pollutions etc.; b) screening of different concentrations of chemical compound libraries, of pharmaceutical compounds, environmental pollutions etc.; c) screening of nutrient factors, d) screening of commensal and or pathobiont strains on growth of the microbiota, and other applications that can be described by analogy. Compound libraries might include but are not limited to chemically synthesized molecules, molecules synthesized by biological means (in vivo production or in vitro making e.g. by cell free systems), molecules extracted from natural sources by appropriate means etc. Compound libraries might be dissolved in various solvents such as aqueous solutions or organic solvents. Depending on the nature of the solvent specific emulsion techniques for droplet making might be needed such as but not limited to surfactants or nanoparticles. EXAMPLES

Example 1

[0075] Using the above mentioned methods a representative model of human skin microbiome was established. By deep sequencing the overall microbiome composition for human skin microbiome from different body areas was characterized. Thus, a "reference microbiome composition" across gender, age, skin phototype was determined. The identified strains were isolated from human individuals to create master cell banks of such strains. An overview of the composition of the thus obtained representative skin microbiota is presented in tab. 1. A suitable microbiome model of human skin microbiota may thus be characterized by any of the following criteria:

• comprising genera with a prevalence of at least 1%, preferably >5%, more preferably >10% and most preferably >20% on the human skin (Tab. 1),

• comprising at least 1, preferably 2 and most preferably >3 genera as listed in Tab. 1,

• comprising pathobiont bacterial strains,

• containing at least one of the following species: Staphylococcus aureus, Staphylococcus epidermidis, Cutibacterium acnes.

The most important pathobionts from the representative skin microbiota

[0076] Within many genera that are listed in Tab. 1 there are species or even strains, that are defined as pathobionts. For instance, in the staphylococcus genus, there is the well-known S. aureus. As revealed by this study at the species level, S. aureus is a present in samples of 17.5% of the participants with an average abundance of 0.4%. Within the same genus, even if it is described as a commensal in most of the literature, S. epidermidis exhibits also pathobiont features since it was found to be responsible of death in premature infants and nosocomial infections. In the genus cutibacterium, some strains of C. acnes are known to be related with acne. In this study, C. acnes is found in 100% of the samples with a mean abundance of 47%. Regarding the genera with a lower prevalence, pathobionts are also found in the taxa acinetobacter, escherichia, bacillus, pseudomonas and more. Table 1: Representative skin microbiota - list of taxa at the genus level sorted by prevalence. Example 2

[0077] The above described methods were performed by testing the representative model of skin microbiome of example 1 in combination with a selected array of test compounds. As presented in Fig. 1 bacterial cells of the representative skin microbiota were encapulated within droplets wherein each droplet contains a single cell. These droplets are then fused with parallel droplets containing test compounds of a chemical library. After incubation (9 h) of the droplets in aerobic conditions. The droplets were sorted as shown in Fig. 2 by selecting droplets with increased biomass from the population of droplets (cf. Fig. 3).

[0078] The sorted droplets are demulsified and the DNA contents analyzed for the frequency of the barcodes in the sorted droplet population. For detection and quantification of nucleic acids of skin microbiota by lllumina sequencing the nucleic acids of each droplet were barcode labelled to prepare a library. The scheme for library preparation is shown in Fig. 5. Based on the barcodes active and inactive compounds can be identified.

[0079] Briefly summarized, 3 successive PCRs are necessary to obtain the full fragment to sequence. The Q5 DNA polymerase from NEB was used for all PCRs.

PCR 1:

[0080] The mix was prepared according to the manufacturer's instruction. 5 mI from the 100 mI mQ water containing resuspended droplets was used as DNA template. The cycling conditions are shown in table 2. PCR 2:

[0081] The mix was prepared according to the manufacturer's instruction. 5 mI from the 100 mI mQ water containing resuspended droplets was used as DNA template. The cycling conditions are shown in table 3.

PCR 3: [0082] The mix was prepared according to the manufacturer's instruction. 5 mI from the 100 mI mQ water containing resuspended droplets was used as DNA template. The cycling conditions are shown in table 4. Table 2: Cycling conditions of PCR 1

Table 3: Cycling conditions of PCR 2 Table 4: Cycling conditions of PCR 3

Quantification after PCR 3:

[0083] 2mI of each product from PCR 3 was used for DNA quantification. A Qubit fluorometer and the BR dsDNA kit were used according to manufacturer's instructions.

Library multiplexing:

[0084] All samples were pooled together in an equimolar way for library multiplexing. After pooling, purification on gel of the final library was done using the DNA clean and concentrator kit from ZymoResearch. The library was sent for lllumina HiSeq 2x75 paired-end sequencing at I2BC plateform. Sequencing data analyses:

[0085] Bioinformatical analyses of obtained sequencing data involved the following steps: i.) demultiplex data using bcl2fastq2-2.18.12; ii) remove adapter sequences by adapter trimming using cutadapt 1.15; iii) ensuring data quality by quality control using FastQC vO.11.5. Subsequently barcode splitter was used to determine the number of reads/barcodes in each sample. Combined with the total number of reads the relative abundance of each barcode was calculated. Finally the ratio between relative abundance of each barcode was calculated in sorted vs. unsorted populations for each experiment.

[0086] Exemplary results of DNA quantification is shown in Fig. 6. For two selected barcodes (BC46 and BC48) the enrichment of droplets with desired biomass increase is shown by showing the ratio of barcodes between the sorted and unsorted population. Hence, Fig. 6 shows that for both selected barcodes these barcodes represent a larger fraction of the overall population as compared to the unsorted population. As the sorted population is obtained by selecting droplets which show an increase in biomass due to incubation with test compounds. Therefore, Fig. 6 provides evidence that the present methods are suited for testing the effect of an array of test compouds on microorganisms which are part of a representative model of the skin microbiota. The presented data indicate that the applied method allows for detection and isolation of bacterial strains whose growth is affected under the applied conditions as well as identification of compounds or conditions which affect growth of bacterial strains. Example 3

[0087] A study was performed on 50 participants with healthy skin to establish representative microbiota.

[0088] The microbiota of their skin was analysed by sequencing (16S rRNA) allowing a very fine understanding of the prevalence, abundance and diversity of bacteria. Accordingly the most representative genus, species and strains of the cutaneous microbiota of subjects with healthy skin were identified. Biomillenia's microfluidic platform was then used to generate a bank of strains exclusively from the skin of healthy volunteers. [0089] On this basis, a facial microbiota model composed of 31 strains was developed that can be used to predict the impact of a compound on the bacterial populations present on the skin. Samples of the bacterial strains were cultivated on a multiwell-plate in the presence or absence of the plant derived ingredient for 24, 48 or 72 h. [0090] The effect of the this plant derived ingrdient in different concentrations (0.01, 0.05, 0,1 and 0.5%) was tested individually on each strain in the model and the results are presented in Fig. 7.

[0091] The OD value (for a strain grown in a medium + 0.01, 0.05, 0,1 and 0.5%) was compared to the OD value obtained for the same strain grown in the same medium without additions. [0092] Impact of an ingredient on the growth of bacterial strains present in the facial microbiota model of healthy skin is shown in Fig. 7. The observed data show that differential effect on bacterial growth by the plant derived ingredient in dependance of concentration can be detected for the various bacterial strains of the facial microbiota model of healthy skin within the multiwell plate model.