Caratterizzante Microbiome Dynamics – flusso Cytometry basato su flussi di lavoro da colture Pure di comunità naturali

This method can help answer key questions in microbial ecology and biotechnology for example, which ecological concepts drive any given ecosystem. The main advantage of this technique is that it can be used to close the follow rapid microbiome dynamics with the short interval sampling regime while remaining highly cost effective. This method can be used for to get information on biotechnological and natural microbial communities and also on animal and human microbiomes for nutritional and health states.

Demonstrating the procedure will be Florian Schattenberg, technician and SediMeter operator in our laboratory. To dry a biogas community sample, use a modified one milliliter pipette tip to transfer 200 microliters of the viscous digestate to a two milliliter tube containing 1.7 milliliters of PBS. After thorough mixing, place the tubes in an ultrasonic bath for one minute to disband any large cell aggregates and attach cells sticking to plant cell residues.

After the sonication, mix the sample thoroughly and filter the cells through a 50 micrometer pore mesh strainer into a 2 milliliter plastic tube. Divide the filtrate into four 400th microliter aliquots and centrifuge the aliquots two times, discarding the supernatant completely both times to mechanically de-water the microbe sample as thoroughly as possible. Then dry the sample in a heated vacuum centrifuge to create a stable pellet and store the pellet at four degrees Celsius protected from light.

For stabilization and fixation of activated sludge samples, centrifuge four milliliters of the cells and re-suspend the pellet in four milliliters of two percent formaldehyde in PBS. After 30 minutes at room temperature, centrifuge the stabilized cell sample and fix the pellet in four milliliters of 70%ethanol for minus 20 degrees Celsius storage. Mix and transfer 0.6 milliliters of the fixed cell suspension to a glass tube containing 1.4 milliliters of PBS and after thorough mixing, sonicate for 10 minutes as demonstrated.

At the end of the sonication, collect the cells by centrifugation, and re-suspend the pellet in two milliliters of fresh PBS. After thorough mixing, sonicate the cells as just demonstrated for five minutes and adjust the OD 700 nanometer to 035 with fresh PBS. Collect the cells by centrifugation, and re-suspend the pellet in one mililiter of permeabablization buffer containing 0.11 molar citric acid, and 4.1 milimolar tween 20, with thorough mixing, for 20 minute incubation at room temperature.

Then collect the cells by centrifugation, and thoroughly re-suspend the pellet in two mililiters of staining solution containing 0.68 micromolar DAPI, for in at least 60 minute incubation at room temperature, protected from light. For bead calibration, load the bead mix for linear calibration into the flow cytometer, and measure the beads continuously while manipulating the nozzle and laser optics positions to pre-calibrate the instrument in the linear range. When the bead peaks can be fit into a pre-set calibration template, switch to log mode, and load a logarithmic calibration bead sample.

Fit the logarithmic bead peaks to their pre-set calibration template to fine tune the hardware of the instrument, and use the photomultiplier tube gain setting to make any necessary final adjustments to the bead position The most critical aspect of this procedure is maintaining consistent measurements to allow comparability between experiments. Therefore, daily cytometer calibration, and the use of beads in the biological stum-lids are vital to the success of slow cytromic microbiome dialysis. When the cells are ready, mix and filtrate the samples and add the logarithmic bead mix to the cells.

Now mix and load the sample onto the cytometer and create a gate to include the stained cells and exclude the noise and beads. Then analyze the sample set consecutively at a maximum speed of 3, 000 events per second until 250, 000 cells are detected within the cell gate. To analyze the flow cytometry data, develop a master gate template for use on all of the samples.

Start by loading the flow cytometry standard files into an appropriate flow cytometry analysis program and process the samples successively. Load the samples, double-click a measurement and select the X and Y axis parameters, from their respective drop down menus to open a forward scatter versus DAPI fluorescence plot. Use the polygon drawing tool to reproduce the previously generated measurement cell gate to exclude the beads and noise, and name the gate accordingly.

Drag the cell gate entry into the all samples group list, and double click the cell gate to selectively display only the cell events. Define the sub-communities prevalent in a sample with the elliptical gate tool, and pool them. Then add additional sub-community allocations and subsequent samples until the master gate template fits all of the samples.

Control the master gate's template with the side scatter scanning method to resolve sub-communities clustering close to each other. Then, add all of the sub-communities to the table editor, and set the output statistic to frequency of parent. Use the table editor to export the relative sub-community abundances into an appropriate spreadsheet software, and adapt the data formatting according to the guidelines in the sidebar manual.

Then, to visualize the sub-community dynamics and correlations, install and load the R package, and load and normalize the txt file. Forward scatter versus DAPI fluorescence plots reveal the cell cycle states of pure strain cultures at different points in a batch culture. Using a master gate template then allows quantification of the proportion of cells with one, two, or multiple chromosomes, revealing, for example, the ability of this representative microbe to replicate its chromosomes faster than its generation time.

When investigating complex microbial communities over time, the pace and significance of the community shift can be easily visualized with a dot plot sequence. The dominant sub-communities in different stages of the experiment can be clearly identified using the cytometric bar code tool. Combining this data with the frequency distribution of the relative sub-community abundances allows the selection of gates demonstrating significant abundance changes at key time points.

Visualization of this data in a non-metric multidimensional scaling plot can facilitate a deeper understanding of the community dynamics. Biogas communities can potentially face spatial heterogeneities due to agitation limitations. The exemplary bio gas community sample points exhibit little spatial, but pronounced temporal heterogeneity.

Strong positive or negative correlations with abiotic paramaters like product tighters, can help with understanding and optimizing ecosystems and biotechnological processes. Furthermore, they facilitate the identification of gates of special interest for subsequent sorting and analysis. While establishing this procedure, it is advised to evaluate different fixation and staining procedures to assess their performance and stability for each new sample set.

After the sorting, further approaches such as ampliconsic fencing, metagenomics, and proteomics can be applied to select the top communities which give information on proto genetic affiliation on activity states off metabolic pathways. This method paved the way for microbial ecologists and bio process engineers to follow microbiome dynamics natural and controlled ecosystems with a reasonable investment of resources.