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− | Fluorescence Activated Cell Sorting (FACS) is a flow cytometry measurement technique that separates single cells with different fluorescence characteristics. In this method you get accurate measuring results, because every single cell is analyzed on its own. FACS analysis can be used for cell sorting, fluorescence analysis of single cells and cell counting of different sample mixtures.<br> | + | </div> |
− | In flow cytometry, the sample with the cells get hydrodynamically focused in a single stream. The cells arrange in a row, so that they can pass a laser one by one. The cells get excited by the laser and emit light at various wavelengths, which is then detected by a fluorescence analysator. The detector can detect and separate different fluorescence intensities at a definite range of wavelengths. Through this cells can be categorized by different fluorescent characteristics and if wanted separated into defined categories by a deflection system using electromagnetic fields. <br> | + | </div> |
− | Furthermore, it is possible to determine the cell volume and size, as well as to distinguish between different kinds of cells, particles or cell clumps. For this, there are scatter detectors around the capilar. A forward scatter detector (FSC) and a stream side scatter detector (SSC) are placed around the stream.<br><br> | + | <div id="rbn3" class="popup"> |
− | | + | <div class="popup-container"> |
− | <h2>Flow cytrometry for growth curves</h2> | + | <div class="popup-header"> |
− | With the flow cytometry device available to us we were able to capture highly accurate cell counts. This brought us the idea of implementing this technique in a way less related to fluorescent reporters: counting cells in our cultures to capture growth curves instead of relying on optical density measurements. <br><br> | + | <h1 class="title">Fluorescence-Activated Cell Sorting (FACS)</h1> |
− | Measurements of optical density are highly influenced by a multitude of factors. When measuring samples it is common to receive different results every time the same sample is measured, as in the meantime the distribution of cells inside of the probe has changed - mainly due to them slowly sinking to the bottom of the cuvette while not being shaken. This leads to high measurement errors. <br><br> | + | <button type="button" onclick="hide('rbn3')">X</button> |
− | Cell counts offer a promising alternative, as they are independent of factors that could influence OD measurements: impurity in the probe can distort OD measurements, while in flow cytometry the polluting particles will mostly be clearly distinguishable from the other counts. Especially with cyanobacterial cultures this can be used as a huge advantage: the autofluorescence of the cell gives us a clear way to select for the right event counts in our device, which we can then gate in order to receive just the number of cells with the fitting fluorescence signal.<br><br> | + | </div> |
− | In order to construct an actual growth curve out of this, another important part is needed: counting beads. <br>Those beads emit a distinct fluorescent signal that can be clearly detected and distinguished from other events. Using different filters we can select for the fluorescence we want to look at, one of them being the one of the beads and the other one from our cyanobacteria. The event number of the counting beads can now be used to determine the exact number of cells in the culture - this is how it works:<br> | + | <div class="popup-content" style="text-align: justify; text-align-last: justify;"> |
− | One counts the beads and sets a fixed number as the stop-criteria, meaning that the event count will stop after a certain amount of beads has been counted. Afterwards one can look at the number of cyanobacterial cells that have been counted in the same time the fixed amount of beads has passed and can calculate back to the whole culture volume in order to determine the amount of cells in the culture using the following formula:<br><br> | + | <p> |
− | A/B x C/D=concentration of sample as cells/µL<br> | + | Fluorescence Activated Cell Sorting (FACS) is a flow cytometry measurement technique that separates single cells with different fluorescence characteristics. In this method you get accurate measuring results, because every single cell is analyzed on its own. FACS analysis can be used for cell sorting, fluorescence analysis of single cells and cell counting of different sample mixtures.<br> |
− | Where:<br> | + | In flow cytometry, the sample with the cells get hydrodynamically focused in a single stream. The cells arrange in a row, so that they can pass a laser one by one. The cells get excited by the laser and emit light at various wavelengths, which is then detected by a fluorescence analysator. The detector can detect and separate different fluorescence intensities at a definite range of wavelengths. Through this cells can be categorized by different fluorescent characteristics and if wanted separated into defined categories by a deflection system using electromagnetic fields. <br> |
− | A = number of cell events<br> | + | Furthermore, it is possible to determine the cell volume and size, as well as to distinguish between different kinds of cells, particles or cell clumps. For this, there are scatter detectors around the capilar. A forward scatter detector (FSC) and a stream side scatter detector (SSC) are placed around the stream.<br><br> |
− | B = number of bead events<br> | + | |
− | C = assigned bead count of the lot (beads/50 µL)<br> | + | <h2>Flow cytrometry for growth curves</h2> |
− | D = volume of sample (µL)<br><br> | + | With the flow cytometry device available to us we were able to capture highly accurate cell counts. This brought us the idea of implementing this technique in a way less related to fluorescent reporters: counting cells in our cultures to capture growth curves instead of relying on optical density measurements. <br><br> |
− | | + | Measurements of optical density are highly influenced by a multitude of factors. When measuring samples it is common to receive different results every time the same sample is measured, as in the meantime the distribution of cells inside of the probe has changed - mainly due to them slowly sinking to the bottom of the cuvette while not being shaken. This leads to high measurement errors. <br><br> |
− | As one can already see from the formula, usually 50µl of beads are added to each sample that is run through the flow cytometer. This allows for accurate comparability.<br> | + | Cell counts offer a promising alternative, as they are independent of factors that could influence OD measurements: impurity in the probe can distort OD measurements, while in flow cytometry the polluting particles will mostly be clearly distinguishable from the other counts. Especially with cyanobacterial cultures this can be used as a huge advantage: the autofluorescence of the cell gives us a clear way to select for the right event counts in our device, which we can then gate in order to receive just the number of cells with the fitting fluorescence signal.<br><br> |
− | Figure 1 shows our setup for the measurement of growth curves. The gated beads are counted to an event number of 1000. Meanwhile our cells are counted in a defined gate reaching from 2x10^3 to 10^5 relative fluorescence units. For detection of autofluorescence the APC filter was used. APC stands for Allophycocyanin, as this filter is designed to show the fluorescence of excited Allophycocyanin from red algae - a protein similar to phycocyanin in cyanobacteria, which is the reason why this setup works well to show cyanobacterial autofluorescence.<br><br> | + | In order to construct an actual growth curve out of this, another important part is needed: counting beads. <br>Those beads emit a distinct fluorescent signal that can be clearly detected and distinguished from other events. Using different filters we can select for the fluorescence we want to look at, one of them being the one of the beads and the other one from our cyanobacteria. The event number of the counting beads can now be used to determine the exact number of cells in the culture - this is how it works:<br> |
− | | + | One counts the beads and sets a fixed number as the stop-criteria, meaning that the event count will stop after a certain amount of beads has been counted. Afterwards one can look at the number of cyanobacterial cells that have been counted in the same time the fixed amount of beads has passed and can calculate back to the whole culture volume in order to determine the amount of cells in the culture using the following formula:<br><br> |
− | <figure> | + | A/B x C/D=concentration of sample as cells/µL<br> |
− | <img src="https://static.igem.org/mediawiki/2019/f/f2/T--Marburg--CellCountSetup.png" alt="CellCountSetup">
| + | Where:<br> |
− | <figcaption>
| + | A = number of cell events<br> |
− | Fig.1 - Setup for the creation of growth curves through cell counts with flow cytometry.
| + | B = number of bead events<br> |
− | </figcaption>
| + | C = assigned bead count of the lot (beads/50 µL)<br> |
− | </figure> | + | D = volume of sample (µL)<br><br> |
| + | |
| + | As one can already see from the formula, usually 50µl of beads are added to each sample that is run through the flow cytometer. This allows for accurate comparability.<br> |
| + | Figure 1 shows our setup for the measurement of growth curves. The gated beads are counted to an event number of 1000. Meanwhile our cells are counted in a defined gate reaching from 2x10^3 to 10^5 relative fluorescence units. For detection of autofluorescence the APC filter was used. APC stands for Allophycocyanin, as this filter is designed to show the fluorescence of excited Allophycocyanin from red algae - a protein similar to phycocyanin in cyanobacteria, which is the reason why this setup works well to show cyanobacterial autofluorescence.<br><br> |
| + | |
| + | <figure> |
| + | <img src="https://static.igem.org/mediawiki/2019/f/f2/T--Marburg--CellCountSetup.png" alt="CellCountSetup"> |
| + | <figcaption> |
| + | Fig.1 - Setup for the creation of growth curves through cell counts with flow cytometry. |
| + | </figcaption> |
| + | </figure> |
| + | |
| + | |
| + | Comparing flow cytometry measurements to optical density measurements we were able to find some striking differences.<br> |
| + | Using the exact same probes and paying very close attention to work carefully we created to growth curves which, although showing the same tendency, differ from one another. While in the optical density measurements the culture seems to shift towards the stationary phase [Fig 2: Growth of S.elongatus UTEX 2973 and PCC 7942 measured by optical density], the cell counts show us a still exponentially growing culture [Fig 3: Growth of S.elongatus UTEX 2973 and PCC 7942 measured by cell count]. <br>Calculating the doubling time between two exact same time points for both approaches we were again able to find a difference: while the OD730 measurements resulted in a calculated doubling time of 108 minutes for the UTEX 2973 strain, the calculation using cell counts resulted in a doubling time of 94 minutes - a difference of 14 minutes between two measurement methods for the exact same samples! |
| + | |
| + | <figure> |
| + | <img src="https://static.igem.org/mediawiki/2019/6/65/T--Marburg--GrowthCurveOD.png" alt="GrowthCurveOD"> |
| + | <figcaption> |
| + | Fig.2 - Growth of S.elongatus UTEX 2973 and PCC 7942 measured by optical density. |
| + | </figcaption> |
| + | </figure> |
| + | |
| + | <figure> |
| + | <img src="https://static.igem.org/mediawiki/2019/9/99/T--Marburg--GrowthCurveCellCount.png" alt="CellCountSetup"> |
| + | <figcaption> |
| + | Fig.3 - Growth of S.elongatus UTEX 2973 and PCC 7942 measured by flow cytometry. |
| + | </figcaption> |
| + | </figure> |
| + | <br><br> |
| + | <h2>Cell cytometry to examine gene expression levels</h2> |
| + | |
| + | In our project we chose to use flow cytometry as an accurate method, to analyse gene expression levels of genetic constructs. <br> |
| + | In an extensive experiment we assessed the fluorescence of a transformed YFP-construct in our cured strain, showing that the shuttle vector with the minimal replication element can be maintained in S. elongatus UTEX 2973.<br> |
| + | Using a similar setup as in our growth curve experiments, we analysed the strength of the fluorescence signal over time: <br><br> |
| + | As expected, no YFP expressing cells could be counted in the wild type strain. |
| + | <figure> |
| + | <img src="https://static.igem.org/mediawiki/2019/2/27/T--Marburg--UDARyfpFACSmeasurement.png" alt="UTEXwtYFP"> |
| + | <figcaption> |
| + | Fig.4 - YFP expression of the wild type strain. |
| + | </figcaption> |
| + | </figure> |
| + | <br><br> |
| + | For the conjugant strain it was obvious that a steady fluorescent signal could be obtained. For a lower light intensity the strength of the signal stayed the same throughtout the whole experiment, while at higher light intensities a shift towards higher fluorescence intensities could be observed. |
| + | <br><br> |
| + | <figure> |
| + | <img src="https://static.igem.org/mediawiki/2019/a/a7/T--Marburg--ConjugantYFPexpression.png" alt="ConjugantYFPexpression"> |
| + | <figcaption> |
| + | Fig.5 - YFP expression of a conjugant strain. |
| + | </figcaption> |
| + | </figure> |
| + | |
| + | |
| + | </p> |
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