Growth curves “Strength and growth come only through continuous effort and struggle.” - Napoleon Hill Although this 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 different 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 (read here what else we learned from him[link to Golden Skype Call]) 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. Fluorescence Activated Cell Sorting (FACS) 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. 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. 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. FACS 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 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. 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. In order to construct an actual growth curve out of this, another important part is needed: counting beads. 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: 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. 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. Comparing flow cytometry measurements to optical density measurements we were able to find some striking differences. 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]. 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! FACS in our project: In our project we chose to investigate our organism with a FACS device, as a second measurement method, to compare the YFP-expression from our parts and compare it with a standard plate reader. In our growth curve experiments we measured the YFP-expression over the cell number. With the aid of beads we could determine the ratio of count of cells. In our measurements we could determine the number of cells, how many cells are on a certain OD, to gain more accurate information in our growth curves experiment. Our first experiments were with UDAR 4787, which has a pAM 4787 construct build in. After the transformation of the pAM 4787 construct into Synechococcus elongatus, the cells have a YFP- and an antibiotic resistance cassette against spectinomycin. The culture only keeps the pAM 4787 construct, if there is a certain concentration of antibiotic in the environment. With FACS we could demonstrate the YFP-expression of the pAMs-construct in Synechococcus elongatus. We compared this with the autofluorescence of the wild type UTEX 2973, which is caused by the chlorophyll in cyanobacteria and could see the significant higher intensity of the fluorescence from the construct. Further we wanted to explore with our experiments, whether the expression of the fluorescence of the YFP protein is dependent from different growing phases. How would parameters like OD, exponential and stationary growing or light conditions affect the production of the YFP protein. We compared the expression from cultures growing at 600 μE and 1500 μE to see which light condition would be optimal. The results can be see in the following graphic. Another point is to explore whether the YFP expression would be the strongest during the exponential growing phase. As an outlook of this measurement method it would be really interesting to analyze more different constructs to see measure the strength of a promoter construct via fluorescence. Light measurement: At a very early stage of our project we noticed that standardization in the phototrophic community needs to have an overhaul to allow for reproducible experiments. As we started doing growth curves we used to determine the light intensity via a planar quantum sensor that can only absorb photons from an angle of approximately 120° and only counts photons having a wavelength between 400nm-700nm. 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. We then came up with the idea to search for a scalar radiometer that has a detection surface of nearly 4π steradian, can only measures photosynthetic active radiation. With the help of this method we used to determine the exact amount of µmol photonsm2s that can be used for photosynthesis. (400nm-700nm). After we determined the light intensity via this method the doubling time of our strain drastically reduced. Doubling times from two hours we had before were now beaten and we achieved new lows of about 90 mins for the first time. 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 for literature on our iGEM project 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. During our skype call with James Golden he emphasized that a lot of experiments are simply not reproducible, because there is no way to tell how much light one has to expose their organisms to. Additionally we got the feedback of Dr. Nicolas Schmelling that even professional cultivation devices from companies which are specialized on building them, can not deliver consistent and even illumination. 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 follows. [evtl. nur Bild der Spektren] 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. 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.[Link zur 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 (FACS link) 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.