Latest revision as of 00:48, 14 December 2019

M E A S U R E M E N T

Introducing new standards in measurement

We entered this project as the first Marburg iGEM team working with Synechococcus elongatus UTEX 2973, the fastest phototrophic organism. Missing knowledge in handling and cultivation of UTEX 2973 left us in front of many problems and questions. Especially the usage of different media, light conditions and other cultivation and measurement parameters were one of the biggest problems we discovered in scientific papers. Many of these problems are reasoned in the ongoing optimization and development of methods and instruments. Therefore it is hard to hold on to special methods; nevertheless, standardization is paramount in Synthetic Biology in order to be able to compare results with other scientists and reproduce their data.

L I G H T
M E A S U R E M E N T

Light measurement is a crucial aspect when working with phototrophic organisms.

At the beginning of our project we faced the first question: How to cultivate UTEX at 1500 μE? To answer this we had to measure the light conditions in our incubators and while doing this simple task the first part of standardization began. We discovered that nearly every paper is using different methods to measure their light conditions and that it is a really complex and important procedure. So we got in contact with Cyano and light measurement experts to confront this problem and standardize it. As we started doing growth curves we used to determine the light intensity via a planar quantum sensor sensitive only to photons with a wavelength between 400nm-700nm; coming from an angle of approximately 120°. Because of the way we setup our incubator, the illumination was coming from two different light sources, which needed to be measured individually. While our first attempts included measuring the intensity by facing the quantum sensor at the lights respectively and then converting these values by a factor accounting for spherical flux of light. As this method proved to be result in very inaccurate values of light intensity, we then came up with the idea to search for a scalar radiometer that has a detection surface of nearly 4π steradian. The instrument we found and fortunately got as sponsoring could provide us with exactly that. On top of that it only accounts for photosynthetic radiation. With the help of this instrument we then determined the exact amount of µmol photons/m² that can be used for photosynthesis (400nm-700nm) in every position in our incubator.

After we determined the light intensity via this method the doubling time of our strain reduced drastically from two hours to under 80 minutes. We believe that the standardization of measuring light intensity has a huge impact in the field of phototrophic biology. What we often time stumbled upon when we were looking into literature was that the information on light intensity in these papers were often inconsistent. Oftentimes the only values on the intensity were given in the unit µEinstein, but the needed details on how that number was measured, was missing. So some people would measure the intensities with a planar device, others would determine them via a spherical quantum sensor.

To go even further, we think that the spectrum of the respective lamp should also be considered when talking about standardization. The light spectrum of our two lamps look as illustrated by Fig. 1. Even though the standardization of the light quality seems to be a very hard task it should still be included in scientific works in order to give as much information as possible about the experimental setup.

Fig. 1: Light distribution inside our incubator setup.

We measured an equidistant grid of points at which we measured the average amount of photons (10 seconds) to minimize fluctuation. These data points were then interpolated with the help of a b spline surface to predict the amount of µmol photons at any given point of the incubator. This method is described in more detail on our model page. We believe that the standardization of measuring light intensity has a huge impact in the field of phototrophic biology and immensely helps to create reproducible experimental setups.

We could show that light intensity had a big effect on reporter gene expression. This displays the importance of standardization especially if one want to characterize parts such as promoters RBS terminator or engineer even more complex designs like genetic circuits or synthetic metabolic pathways. We propose a standardization of the light measurement process and inclusion of information, such as the way of measuring, light source and proper light intensities in every publication for phototrophic organisms.

R E P O R T E R S

Fluorescence + luminescence reporters

F A C S

FACS Measurements

Fluorescence Activated Cell Sorting (FACS) is a flow cytometry measurement technique that separates single cells with different fluorescence characteristics. In this method one gets accurate measuring results, because every single cell is individually analyzed. FACS analysis can be used for cell sorting, fluorescence analysis of single cells and cell counting of different sample mixtures.

In flow cytometry, the sample with the cells gets hydrodynamically focused in a single stream. The cells arrange in a row, so that they can be illuminated with a laser one by one. The cells get excited by the laser and emit light at various wavelengths, which is then detected by a photon detector. The detector can detect and separate different fluorescence intensities at a definite range of wavelengths. Through this, cells can be categorized via different fluorescent characteristics and, if needed, separated into defined categories by a deflection system using electromagnetic fields.

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 capillary. A forward scatter detector (FSC) and a stream side scatter detector (SSC) are placed around the stream.

Flow cytrometry for growth curves

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.

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 sample has changed - mainly due to them slowly sinking to the bottom of the cuvette while not being shaken. This leads to high measurement errors.

Cell counting offers a promising alternative, as they are independent of factors that could influence OD measurements: Impurity in the sample 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.

In order to construct an actual growth curve out of this, another important part is needed: counting beads. The 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, i.e. the fluorescence of the beads or the fluorescence of 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:

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:

A/B x C/D = concentration of sample as cells/µL
Where:
A = number of cell events
B = number of bead events
C = assigned bead count of the lot (beads/50 µL)
D = volume of sample (µL)

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.

Fig. 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 2x10³ to 10⁵ 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.

Fig. 1 - Setup for the creation of growth curves through cell counting with flow cytometry.

Comparing flow cytometry measurements to optical density measurements we were able to find some striking differences. Using the exact same samples and paying very close attention to work carefully we created two 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), the cell counts show us a still exponentially growing culture (Fig. 3). 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!

GrowthCurveOD — Fig.2 - Growth of *S. elongatus* UTEX 2973 and PCC 7942 measured by optical density.

CellCountFlowCytometry — Fig.3 - Growth of *S. elongatus* UTEX 2973 and PCC 7942 measured by flow cytometry.

Cell cytometry to examine gene expression levels

In our project we chose to use flow cytometry as an accurate method, to analyze gene expression levels of genetic constructs. 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. Using a similar setup as in our growth curve experiments, we analyzed the strength of the fluorescence signal over time: As expected, no YFP expressing cells could be counted in the wild type strain.

UTEXwtYFP — Fig.4 - YFP expression of the wild type strain.

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 throughout the whole experiment, while at higher light intensities a wider range of fluorescence intensities could be observed.

ConjugantYFPexpression — Fig.5 - YFP expression of a conjugant strain.

P A R T
M E A S U R E M E N T

Establishing a high throughput measurement workflow for cyanobacteria.

For our project it was indispensable to establish a measurement workflow that is not only applicable to UTEX 2973 and other cyanobacterias but also has a high throughput. While we worked on our Marburg Collection 2.0 with 55 parts we came to the conclusion it was also necessary to develop a measurement method that was suitable to such a large collection. Therefore we elaborated different workflows - containing different cultivation vessels and parameters - and revised them after evaluating the results. In the end we were able to establish a workflow specially designed for our methods to cultivate and characterize the parts from our Marburg Collection 2.0, that is tailored to Synechococcus elongatus UTEX 2973.

Experimental Procedure

The results of our part characterization were obtained by fluorescence and luminescence measurements. But before the light could be measured we had to elaborate a cultivating and measuring workflow.

For the cultivation-workflow we tested different well plate formats and growing parameters for the best growing conditions. Due to the size of the Marburg Collection 2.0 (55 parts) and space limitation in our incubator, our first thought was using well-plates. We started with 96-well-plates and found out that it was impossible to cultivate Synechococcus elongatus UTEX 2973 in an incubator with 130 rpm. The rpm of the incubator was limited because cultures in flasks had to be incubated at the same time, presenting risks of falling over at higher rpm. After revising the workflow over and over we came to the conclusion, that it is favorable to cultivate the UTEX 2973 in transparent 24-well-plates, because, in contrary to 96-well-plates, there was enough movement in the wells to prevent the cells from forming a pellet/cloud. At 130 rpm we found a compromise between cultivating flasks and 24-well-plates in the same incubator.

Additionally, it was necessary to use transparent wells to ensure every well would be provided with similar light conditions. Concerning the light conditions, we evaluated that the cells showed good growth in the wells at low-light conditions (around 500 µE). The evaporation of medium played an important role in cultivation using well-plates thanks to their relatively small volume and large surface area.

It was also essential to know the volume in the wells for measuring in the plate reader. Therefore we compared different seals for the well plates and in the end we came to the conclusion that using a semipermeable foil is the best solution. The evaporation could be minimalized and the cells were able to get enough CO2 thanks to improvement in air circulation. By using a foil it was possible to cultivate the cells for 2-3 days without losing significant amounts of media.

As described before we used the workflow as shown in Fig. 1 to cultivate and measure our parts. The cultivation started by picking colonies from BG11-agar-plates that were transformed via triparental conjugation. For every part we picked three different colonies and inoculated them in 1.0 mL BG11-media with 0.5 µl Spectinomycin. Thus in the first 24-well-plates we could inoculate eight different parts with three biological replicates. When the cultures grew to OD₇₃₀=0.6-0.8 they were inoculated to 1.0 mL of OD₇₃₀=0.1 into the wells A1-3 (part 1) and A4-6 (part 2) of another 24-well-plate. At the same time the Well B6 was inoculated with 1.0 mL of an OD₇₃₀= 0.1 untransformed culture that was used as a blank while evaluating the results. When all the cultures in the second 24-well-plate reached OD₇₃₀=0.6-0.8 they got inoculated twice in the same well-plate. It was done by inoculating the wells A1-3 into the wells C1-3 and D1-3 creating technical replicates of the same part (analog for A4-6 and the UDAR inoculating to B4 and B5). When the wells C1-D6 (and the UDAR) reached an OD₇₃₀=0.6-0.8 the cultures were transferred into a 96-well-plate. Every well of the 24-well-plate was measured three times. Following this workflow we were able to measure three biological replicates and two technical replicates for every biological replicate. It enabled us to have a good statistical database and gives our results a stronger meaning and significance. While working with this workflow it was essential to keep the cultures in their exponential phase because it would significantly speed up the growth by reducing the lag-phase to an absolute minimum.

For the measurement we decided to transfer the cultures into black/white well plates and luminescence was measured in white ones. We measured in 96-well-plates because it enabled us to measure every part three times by consuming only 600 µl of the 1.0 ml 24-well-cultures. Furthermore we could measure eight parts simultaneously in one plate. (four 24-well-plates lead into one 96-well-plate for measurement)

Fluorescence measurement

After transfering the cultures into the 96-well-plate the fluorescence of the parts was measured. More precisely, the activity of the parts was determined by the expression of the sYFP. The sYFP fluorescence served as an indicator and the sequence for the sYFP was in the same cassette as the considered part. For our measurement we created a program that measured the OD₇₃₀ and the fluorescence of the wells with the following settings:

OD measure with plate reader: Settings: 730 nm, three measuring points (circle)
Fluorescence Settings: Excitation 488 nm, Emission 518 nm size 2x2 (circle), frame 1200 μm strengthener:optimal

In order to measure the OD in each well we determined the absorption at 730 nm. Further we measured multiple points in each well, where 3x3 points (circular) with a gap of 1350nm to the border of the well showed consistent results with small standard deviations. We used the same settings for all fluorescence measurements. While using sYFP as a signal for our part measurement we have set the emission wavelength to 515 nm and the excitation wavelength to 527 nm, fitting the exact wavelengths of sYFP.

G R O W T H
C U R V E S

Varying our growth conditions we were finally able to achieve doubling times of under 80 minutes.

“Strength and growth come only through continuous effort and struggle.” - Napoleon Hill

Although the quote was certainly never meant in this way, it is quite fitting to our project, as the growth of our Synechococcus elongatus strain UTEX 2973 was one of the key aspects throughout the year. Our goal to create the fastest phototrophic chassis was fueled by our unwavered dream of accelerated research on the multitude of mechanisms and possibilities that phototrophic organisms have to offer. We were quick to learn that this goal was not as close as we might have thought. On our way we encountered countless obstacles, some easier to overcome than others - one of the most resilient ones being the growth conditions we had to provide. Actually reaching the technical values we wanted was not the main issue, no, the hardest part was finding the holy grail of growth conditions, the perfect combination of parameters to cultivate our strain in.

Digging through literature we found various setups that were seemingly the “optimal growth conditions” for S. elongatus UTEX 2973 and it was apparent that in order to find the optimal conditions, we ultimately had to try all of them out by ourselves. So we set one of our biggest projects in motion, recording numerous different growth curves with many different parameters.

Before calibrating key parameters like CO2 concentration, light intensity and temperature, we conducted some smaller trials on various other criteria, such as lid type, flask size, flask type and culture volume, as those are not heavily affected by the other parameters. Through these experiments, we could clearly identify a set that enabled the best growth for our chassis: plastic lids on 250ml erlenmeyer flasks with three chicanes and 50ml culture volume. Having fixed these initial parameters we set sail to the sea of endlessly variable growth conditions in hope to discover the true needs of S. elongatus UTEX 2973.

As phototrophic chassis primarily require light and CO2 for their growth, those were the two parameters we were most interested in, but due to the UTEX 2973 strain being reportedly tolerant to higher temperatures than most other S. elongatus strains (Tan et al., 2018), this was another aspect to be tested. As time was scarce, we parallelized our measurements, meaning that while different temperatures or CO2 concentrations were put on trial we were able to compare the growth under different light intensities. At this point it is important to mention that the light intensities in our incubator were not always set the same way: in the beginning we measured the light distribution with a planar light measurement device, using a conversion chart we acquired from Prof. Dr. Annegret Wilde from Freiburg to convert the values to theoretical spherical values, but after our insightful talk to Prof. Dr. James W. Golden, we hurried to get hold of a spherical measurement device to make sure we could accurately set the light intensities - and the difference was striking: the doubling time of our cultures increased by a huge amount which was an important step into the right direction for us.

@@ Line 108: / Line 108: @@
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            <div class="popup-header">
-             <h1 class="title">Reporter</h1>
+             <h1 class="title">Reporters</h1>
              <button type="button" onclick="hide('reporter')">X</button>
            </div>
@@ Line 116: / Line 116: @@
                  When working in Synthetic Biology, reporter genes such as fluorescence proteins are indispensable elements to characterize BioBricks. For a good characterization a suitable reporter is required. But reporters can be more than just merely a detection tool for transcriptional activity but they can also give a deeper insight into cellular conditions beyond the genetic context. We provide a <a href="https://2019.igem.org/Team:Marburg/Results#marburg_collection" target="_blank">diverse set of reporters</a> not only for the purpose of <a href="https://2019.igem.org/Team:Marburg/Improve">describing genetic tools</a> but also for the sensing of a variety of parameters which are crucial for cyanobacteria.
+<br> <br>
+As an addition to the fluorescent reporters, we included a set of luminescent reporters to bring measurements of genetic constructs to a new level as they mostly bypass autofluorescence from cyanobacterial cells. The red-shifted version of NanoLuc -namely teLuc- bears the potential of the best reporter in <i>S. elongatus</i> as its absorbance bypasses autofluorescent signals better than NanoLuc and shows a higher relative bioluminescent signal<a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5678970/" target="_blank">(Yeh <i>et al.</i>, 2017)</a>.
              </p>
@@ Line 154: / Line 156: @@
          <p style="text-align: justify; margin-bottom: 1em;">
-               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>
+               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 capillary. A forward scatter detector (FSC) and a stream side scatter detector (SSC) are placed around the stream.<br><br>
              </p>
+<p>
-               <h2 class="subtitle" style="font-size: 1.5rem !important; text-align:center">Flow cytrometry for growth curves</h2>
+               <u>Flow cytrometry for growth curves</u>
+</p>
                <p>
                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 sample 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>
-               Cell counts offer a promising alternative, as they are independent of factors that could influence OD measurements: impurity in the sample 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>
+               Cell counting offers a promising alternative, as they are independent of factors that could influence OD measurements: Impurity in the sample 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>
                In order to construct an actual growth curve out of this, another important part is needed: counting beads. The 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, i.e. the fluorescence of the beads or the fluorescence of 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><br>
@@ Line 187: / Line 190: @@
                          <img src="https://static.igem.org/mediawiki/2019/f/f2/T--Marburg--CellCountSetup.png" >
                          <figcaption>
-                             Fig. 1 - Setup for the creation of growth curves through cell counts with flow cytometry.
+                             Fig. 1 - Setup for the creation of growth curves through cell counting with flow cytometry.
                          </figcaption>
                          </figure></center>
@@ Line 195: / Line 198: @@
                Comparing flow cytometry measurements to optical density measurements we were able to find some striking differences.
-               Using the exact same samples 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), the cell counts show us a still exponentially growing culture (Fig. 3). 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!
+               Using the exact same samples and paying very close attention to work carefully we created two 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), the cell counts show us a still exponentially growing culture (Fig. 3). 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!
                </p>
 <center><figure Style="text-align:center">
@@ Line 201: / Line 204: @@
                          <img src="https://static.igem.org/mediawiki/2019/6/65/T--Marburg--GrowthCurveOD.png" alt="GrowthCurveOD">
                          <figcaption>
-                             Fig.2 - Growth of <i>S. elongatus</i> UTEX 2973 and PCC 7942 measured by optical density.
+                             Fig.2 - Growth of <i>S. elongatus</i> UTEX 2973 and PCC 7942 measured by optical density.<br><br>
                          </figcaption>
                          </figure></center>
@@ Line 207: / Line 210: @@
 <center><figure Style="text-align:center">
                          <!-- add this for centered pics-->
-                         <img src="https://static.igem.org/mediawiki/2019/9/99/T--Marburg--GrowthCurveCellCount.png" alt="CellCountSetup">
+                         <img src="https://static.igem.org/mediawiki/2019/9/99/T--Marburg--GrowthCurveCellCount.png" alt="CellCountFlowCytometry">
                          <figcaption>
                              Fig.3 - Growth of <i>S. elongatus</i> UTEX 2973 and PCC 7942 measured by flow cytometry.
@@ Line 215: / Line 218: @@
                <br><br>
-               <h2 class="subtitle" style="font-size: 1.5rem !important; text-align:center" >Cell cytometry to examine gene expression levels</h2>
+<p>
+               <u>Cell cytometry to examine gene expression levels</u>
+</p>
                <p>
-               In our project we chose to use flow cytometry as an accurate method, to analyse gene expression levels of genetic constructs.
+               In our project we chose to use flow cytometry as an accurate method, to analyze gene expression levels of genetic constructs.
                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 <i>S. elongatus</i> UTEX 2973.
-               Using a similar setup as in our growth curve experiments, we analysed the strength of the fluorescence signal over time:
+               Using a similar setup as in our growth curve experiments, we analyzed the strength of the fluorescence signal over time:
                As expected, no YFP expressing cells could be counted in the wild type strain.
                </p>
@@ Line 234: / Line 239: @@
                <br><br>
                <p>
-               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 throughout the whole experiment, while at higher light intensities a shift towards higher fluorescence intensities could be observed.
+               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 throughout the whole experiment, while at higher light intensities a  wider range of fluorescence intensities could be observed.
              </p>
                <br><br>
@@ Line 359: / Line 364: @@
                      </p>
                      <p>
-           <h2 class="subtitle" style="font-size: 1.5rem !important; text-align:center" text-align=center>Fluorescence measurement</h2>
+           <u>Fluorescence measurement</u>
+</p>
 <p>
                      After transfering the cultures into the 96-well-plate the fluorescence of the parts was measured.

Difference between revisions of "Team:Marburg/Measurement"

Latest revision as of 00:48, 14 December 2019

M E A S U R E M E N T

Introducing new standards in measurement

L I G H T M E A S U R E M E N T

Light measurement

R E P O R T E R S

Reporters

F A C S

Fluorescence-Activated Cell Sorting (FACS)

P A R T M E A S U R E M E N T

Part Measurement

G R O W T H C U R V E S

Growth Curves

L I G H T
M E A S U R E M E N T

P A R T
M E A S U R E M E N T

G R O W T H
C U R V E S