ReadMe files were updated

.gitattributes

@@ -369,3 +369,29 @@ assays/Microfluidic[[:space:]]cultivation[[:space:]]with[[:space:]]gradient[[:sp
 assays/Microfluidic[[:space:]]cultivation[[:space:]]with[[:space:]]gradient[[:space:]]growth[[:space:]]light/dataset/UTEX2973/38_4217.tif filter=lfs diff=lfs merge=lfs -text
 assays/Microfluidic[[:space:]]cultivation[[:space:]]with[[:space:]]gradient[[:space:]]growth[[:space:]]light/dataset/UTEX2973/39_4210.tif filter=lfs diff=lfs merge=lfs -text
 assays/Microfluidic[[:space:]]cultivation[[:space:]]with[[:space:]]gradient[[:space:]]growth[[:space:]]light/dataset/UTEX2973/40_4112.tif filter=lfs diff=lfs merge=lfs -text
+assays/Growth[[:space:]]in[[:space:]]Multi-Cultivator/dataset/Figure_3.png filter=lfs diff=lfs merge=lfs -text
+assays/Growth[[:space:]]in[[:space:]]Multi-Cultivator/dataset/Supplement_6.png filter=lfs diff=lfs merge=lfs -text
+assays/Microfluidic[[:space:]]cultivation[[:space:]]with[[:space:]]gradient[[:space:]]growth[[:space:]]light[[:space:]]and[[:space:]]CO2[[:space:]]control/dataset/PCC7942/Calibration/Calibration.csv filter=lfs diff=lfs merge=lfs -text
+assays/Microfluidic[[:space:]]cultivation[[:space:]]with[[:space:]]gradient[[:space:]]growth[[:space:]]light[[:space:]]and[[:space:]]CO2[[:space:]]control/dataset/PCC7942/Calibration/Grad.tif filter=lfs diff=lfs merge=lfs -text
+assays/Microfluidic[[:space:]]cultivation[[:space:]]with[[:space:]]gradient[[:space:]]growth[[:space:]]light[[:space:]]and[[:space:]]CO2[[:space:]]control/dataset/PCC7942/Calibration/Homo.tif filter=lfs diff=lfs merge=lfs -text
+assays/Microfluidic[[:space:]]cultivation[[:space:]]with[[:space:]]gradient[[:space:]]growth[[:space:]]light[[:space:]]and[[:space:]]CO2[[:space:]]control/dataset/UTEX2973/Calibration/Calibration.csv filter=lfs diff=lfs merge=lfs -text
+assays/Microfluidic[[:space:]]cultivation[[:space:]]with[[:space:]]gradient[[:space:]]growth[[:space:]]light[[:space:]]and[[:space:]]CO2[[:space:]]control/dataset/UTEX2973/Calibration/Grad.tif filter=lfs diff=lfs merge=lfs -text
+assays/Microfluidic[[:space:]]cultivation[[:space:]]with[[:space:]]gradient[[:space:]]growth[[:space:]]light[[:space:]]and[[:space:]]CO2[[:space:]]control/dataset/UTEX2973/Calibration/Homo.tif filter=lfs diff=lfs merge=lfs -text
+assays/Microfluidic[[:space:]]cultivation[[:space:]]with[[:space:]]gradient[[:space:]]growth[[:space:]]light[[:space:]]and[[:space:]]day[[:space:]]night[[:space:]]cycle/dataset/PCC7942/Calibration/Calibration.csv filter=lfs diff=lfs merge=lfs -text
+assays/Microfluidic[[:space:]]cultivation[[:space:]]with[[:space:]]gradient[[:space:]]growth[[:space:]]light[[:space:]]and[[:space:]]day[[:space:]]night[[:space:]]cycle/dataset/PCC7942/Calibration/Grad.tif filter=lfs diff=lfs merge=lfs -text
+assays/Microfluidic[[:space:]]cultivation[[:space:]]with[[:space:]]gradient[[:space:]]growth[[:space:]]light[[:space:]]and[[:space:]]day[[:space:]]night[[:space:]]cycle/dataset/PCC7942/Calibration/Homo.tif filter=lfs diff=lfs merge=lfs -text
+assays/Microfluidic[[:space:]]cultivation[[:space:]]with[[:space:]]gradient[[:space:]]growth[[:space:]]light[[:space:]]and[[:space:]]day[[:space:]]night[[:space:]]cycle/dataset/UTEX2973/Calibration/Calibration.csv filter=lfs diff=lfs merge=lfs -text
+assays/Microfluidic[[:space:]]cultivation[[:space:]]with[[:space:]]gradient[[:space:]]growth[[:space:]]light[[:space:]]and[[:space:]]day[[:space:]]night[[:space:]]cycle/dataset/UTEX2973/Calibration/Grad.tif filter=lfs diff=lfs merge=lfs -text
+assays/Microfluidic[[:space:]]cultivation[[:space:]]with[[:space:]]gradient[[:space:]]growth[[:space:]]light[[:space:]]and[[:space:]]day[[:space:]]night[[:space:]]cycle/dataset/UTEX2973/Calibration/Homo.tif filter=lfs diff=lfs merge=lfs -text
+assays/Microfluidic[[:space:]]cultivation[[:space:]]with[[:space:]]gradient[[:space:]]growth[[:space:]]light/protocols/Calibration.ipynb filter=lfs diff=lfs merge=lfs -text
+assays/Microfluidic[[:space:]]cultivation[[:space:]]with[[:space:]]gradient[[:space:]]growth[[:space:]]light/dataset/PCC6803/Calibration/Calibration.csv filter=lfs diff=lfs merge=lfs -text
+assays/Microfluidic[[:space:]]cultivation[[:space:]]with[[:space:]]gradient[[:space:]]growth[[:space:]]light/dataset/PCC6803/Calibration/Grad.tif filter=lfs diff=lfs merge=lfs -text
+assays/Microfluidic[[:space:]]cultivation[[:space:]]with[[:space:]]gradient[[:space:]]growth[[:space:]]light/dataset/PCC6803/Calibration/Homo.tif filter=lfs diff=lfs merge=lfs -text
+assays/Microfluidic[[:space:]]cultivation[[:space:]]with[[:space:]]gradient[[:space:]]growth[[:space:]]light/dataset/PCC7942/Calibration/Calibration.csv filter=lfs diff=lfs merge=lfs -text
+assays/Microfluidic[[:space:]]cultivation[[:space:]]with[[:space:]]gradient[[:space:]]growth[[:space:]]light/dataset/PCC7942/Calibration/Grad.tif filter=lfs diff=lfs merge=lfs -text
+assays/Microfluidic[[:space:]]cultivation[[:space:]]with[[:space:]]gradient[[:space:]]growth[[:space:]]light/dataset/PCC7942/Calibration/Homo.tif filter=lfs diff=lfs merge=lfs -text
+assays/Microfluidic[[:space:]]cultivation[[:space:]]with[[:space:]]gradient[[:space:]]growth[[:space:]]light/dataset/UTEX2973/Calibration/Calibration.csv filter=lfs diff=lfs merge=lfs -text
+assays/Microfluidic[[:space:]]cultivation[[:space:]]with[[:space:]]gradient[[:space:]]growth[[:space:]]light/dataset/UTEX2973/Calibration/Grad.tif filter=lfs diff=lfs merge=lfs -text
+assays/Microfluidic[[:space:]]cultivation[[:space:]]with[[:space:]]gradient[[:space:]]growth[[:space:]]light/dataset/UTEX2973/Calibration/Homo.tif filter=lfs diff=lfs merge=lfs -text
+assays/Microfluidic[[:space:]]cultivation[[:space:]]with[[:space:]]homogeneous[[:space:]]growth[[:space:]]light/dataset/Figure_3.png filter=lfs diff=lfs merge=lfs -text
+assays/Microfluidic[[:space:]]cultivation[[:space:]]with[[:space:]]homogeneous[[:space:]]growth[[:space:]]light/dataset/Figure_4.png filter=lfs diff=lfs merge=lfs -text

README.md

+# A microfluidic system for the cultivation of cyanobacteria with precise light intensity and CO2 control: enabling growth data acquisition at single-cell resolution
+
+# Table of Contents
+1.	Abstract
+2.	Cyanobacteria model organisms
+3.	Assays
+4.	MibiNet 
+
+## 1.	Abstract
+
+Quantification of cell growth is central to any study of photoautotrophic microorganisms. However, cellular self-shading and limited CO2 control in conventional photobioreactors lead to heterogeneous conditions that obscure distinct correlations between the environment and cellular physiology. Here we present a microfluidic cultivation platform that enables precise analysis of cyanobacterial growth with spatio-temporal resolution. Since cyanobacteria are cultivated in monolayers, cellular self-shading does not occur, allowing homogeneous illumination and precise knowledge of the photon-flux density at single-cell resolution. A single chip contains multiple channels, each connected to several hundred growth chambers. In combination with an externally applied light gradient, this setup enables high-throughput multi-parameter analysis in short time. In addition, the multilayered microfluidic design allows continuous perfusion of defined gas mixtures. Transversal CO2 diffusion across the intermediate polydimethylsiloxane membrane results in homogeneous CO2 supply, with a unique exchange-surface to cultivation-volume ratio. Three cyanobacterial model strains were examined under various, static and dynamic environmental conditions. Phase-contrast and chlorophyll fluorescence images were recorded by automated time-lapse microscopy. Deep-learning trained cell segmentation was used to efficiently analyse large image stacks, thereby generating statistically reliable data. Cell division was highly synchronized, and growth was robust under continuous illumination but stopped rapidly upon initiating dark phases. CO2-Limitation, often a limiting factor in photobioreactors, was only observed when the device was operated under reduced CO2 between 50 and 0 ppm. Here we provide comprehensive and precise data on cyanobacterial growth at single-cell resolution, accessible for further growth studies and modeling.
+
+## 2.	Cyanobacterial model organisms
+
+This ARC contains growth data on three different cyanobacteria model organisms
+
+2.1. Synechococcus elongatus UTEX2973 (Abb. UTEX2973)
+
+2.2 Synechococcus elongatus PCC7942 (Abb. PCC7942)
+
+2.3 Synechocystis. sp. PCC6803 (Abb. PCC6803)
+
+## 3. Assays
+
+3.1 Growth of UTEX2973 in the Multi-Cultivator 1000-OD cultivation system
+
+3.2 Microfluidic cultivation with homogeneous growth light
+
+3.3 Microfluidic cultivation with gradient growth light
+
+3.4 Microfluidic cultivation with gradient growth light and day night cycle
+
+3.5 Microfluidic cultivation with gradient growth light and CO2 control
+
+Detailed metadata description can be found in the corresponding `isa.assay` files. 
+
+## 4. SFB 1535 MibiNet- Microbial networking – from organelles to cross-kingdom communities 
+This ARC is part of the [MibiNet project A07](https://www.sfb1535.hhu.de/projects/research-area-a/a07)

assays/Growth in Multi-Cultivator/README.md

-The script was used to plot and analyse the raw data from the MC 1000-OD cultivation system. Growth rates from multiple runs were then selected. Mean values and standart deviations were calculated in Origin2020 Pro. Then the data was plotted.
\ No newline at end of file
+*"Cyanobacteria were then transferred into the MC-1000 OD Multi-Cultivator (Photon Systems Instruments; Czeck Republic) (MC) for growth experiments. The MC allows online monitoring of the culture's optical density (OD) at 680 and 720 nm. Culture tubes were filled with 50 mL of BG11 medium and cells were inoculated to an OD720 of 0.1. The OD720 correlates linearly to biomass in the range from 0.05–0.4. The calculation of the growth rate included the following steps: i.) all OD720 values under 0.05 and over 0.4 were cut off. ii.) The natural logarithm of the cutoff OD720 over time was formed. ii.) A linear model was fitted onto the natural logarithm using numpy.34 iv.) The slope of the linear model is the growth rate.
+A CO2-Controller 2000 (PECON; Germany) connected to the MC enabled aeration of the culture with defined CO2 concentrations. Data was plotted and analyzed with a custom python notebook available at: https://github.com/JuBiotech/Supplement-to-Witting-et-al.-2024."* 
+
+Growth rates from multiple MC runs were collected from the Python scripts and imported into ORigin2020Pro. Calculation of means, standard deviation and hyperbolic tangent model fitting were performed in Origin2020 Pro.
+
+
+# Figure 3
+
+![File structure](dataset/Figure_3.png)
+
+*"Fig. 3 Cyanobacterial growth at different light-intensities under homogeneous and constant growth-light illumination. A: Data was acquired by time-lapse microscopy, recording phase contrast and chlorophyll fluorescence images. B: Images were preprocessed in Fiji before cell instance segmentation was performed using a deep learning model that was trained on annotated sample images. DL based cell segmentation was performed on phase-contrast images to derive cell number (and area) over time from which growth rates were determined using an exponential growth model. Video examples of the time-lapse microscopy and cell segmentation can be found in the ESI† material. C: Total cell area of segmented cells over the cultivation time. D: Mean cell area per frame over cultivation time. E: Number of segmented cells over the cultivation time. F: Colony based growth analysis derived from image data at single-cell resolution of UTEX2973 under homogeneous illumination in comparison to laboratory-scale MC cultivation (n = 2). The microfluidic device was operated without CO2 control. The ambient air had a CO2 concentration of approximately 400 ppm. The MC cultivations were performed with ambient and with CO2 enriched air."*
+
+
+# Figure S7
+
+![File structure](dataset/Supplement_6.png)
+
+*"Figure S7. elongatus in Multi-Cultivator with CO2 enriched air S. elongatus UTEX2973 was
+cultivated in the Multi-Cultivator at ambient air (≈ 400 ppm = 0.040%), 3% and 5% CO2. Temperature was 37 °C and BG11 medium was used. No difference between 3% and 5% CO2 was observed
+indicating, that S. elongatus UTEX2973 grows at maximum speed when using these conditions."*
+
+**Witting et al., 2025,Lab on a Chip, 25(3), 319–329. https://doi.org/10.1039/D4LC00567H**
\ No newline at end of file

assays/Microfluidic cultivation with gradient growth light and CO2 control/README.md

+# Microfluidic cultivation
+*''The platform presented in this work allows carrying out different experimental modes: microfluidic cultivations can be performed either with or without CO2 control, depending on the chip configuration. Without the additional gas control layer, CO2 availability depends on the surrounding atmosphere. The microfluidic cultivation chip can be illuminated homogeneously or a light-intensity gradient can be applied. The light-intensity can be constant, but also dynamic profiles, for example day–night cycles can be applied.
+Before starting an experiment, cyanobacteria were precultivated in the MC. Therefore, cyanobacteria were inoculated to an OD720 of 0.1 and cultivated for approximately 24 h. Prior to inoculation the tubing for BG11 medium supply and outflow were connected. BG11 medium was perfused at a flow rate of 200 nL min−1. After the cell inoculation, growth chambers containing cyanobacteria were selected manually for time-lapse imaging. Pictures were taken every 1 hour for experiments with homogeneous growth-light illumination and every 2 hours in experiments with gradient growth light-illumination. For microfluidic experiments with CO2 control, a premixed synthetic air bottle containing 200 ppm CO2 was used. Final CO2 concentrations were achieved by mixing defined volume flow rates of the synthetic air, N2 and O2 using red-y-smart thermal mass flow controllers (Vögtlin; Germany). Gas was perfused through the gas layer in countercurrent to medium flow. All experiments were performed at 37 °C. The Spectra Tune Lab light engine was set to emit Planck's radiation distribution at 5800 K, mimicking the spectrum emitted by the sun.37 Day–night rhythms were programmed in μwave and started simultaneously with the time-lapse sequence.''*
+
+# Growth-light calibration
+*''For direct light-intensity measurements of the homogeneous and gradient illumination (data shown in Fig. 4A), the sensor spot of a Li-180 Spectrometer (Li-Cor Biosciences; USA) was mounted on the X–Y-Stage and during measurements it was moved relative to the ringlight. Therefore, the ringlight and the Li-180 sensor were mounted at a comparable distance as between the ringlight and the microfluidic chip.
+The light-intensity gradient was calibrated prior to each experiment to assign a specific light-intensity for all cultivation chambers. An exemplary calibration is illustrated in detail in the ESI† material. Each calibration procedure included the following three main steps:
+i.) Using the LI-190R Terrestrial Quantum Sensor under homogeneous illumination of the growth light, the photon flux density (PFD) in the photosynthetic active range of illumination [μE m−2 s−1] was measured at various power settings [%] in the light engine's control software. A linear correlation was found between power setting and the resulting PFD.
+ii.) Instead of the cultivation chip, a microscopy calibration slide of homogeneous color and density (Chroma Technology, USA) was mounted in the same optical plane. Using the 2× objective, the microscope was focused on the top surface of this calibration slide. Then bright-field images of the calibration slide were taken with the Zyla camera under homogeneous growth-light illumination at various power settings. A linear correlation between the light engine's power settings and the averaged camera grey-values was found. By replacing the power levels with the corresponding PFD values from i), a linear correlation between camera pixel grey values and PFD can be derived.
+iii.) Finally, the half-circle cover was installed to generate the light-intensity gradient. Bright-field images of the calibration slide under gradient illumination at specific power settings were taken. During capture, no additional microscopy illumination was applied. The light-intensity gradient illumination resulted in linearly increasing camera grey values, resolving the gradient at camera resolution. By replacing the grey values with the corresponding PFD from ii.), the light-intensity gradient can now be described as linear function of PFD over position. The microscope's objective can not be moved relative to the ringlight. Hence, when a cultivation chip is later placed in the microscope the knowledge of the linear relation of the PFD in dependence on X-position allows to assign specific light-intensity values to each growth chamber.''*
+
+All the notebooks needed to analyse the data are uploaded into the protocols folder. Data plotting and hyperbolic tangent model fitting was performed in Origin2020 Pro.
+
+# Figure 4
+
+![File structure](dataset/Figure_4.png)
+
+*"A: Light-intensity profiles across the light cone emitted by the ringlight (homogeneous illumination mode and longitudinal to the light-intensity gradient). B: Growth data of UTEX2973 from microfluidic cultivations under light-intensity gradient illumination and under homogeneous illumination for comparison. Under light-intensity gradient illumination, each data point resembles growth inside distinct chambers from a single, continuously performed experiment (cultivation time approximately 4 days). Data points obtained during homogeneous illumination, include standard deviation and the number of replicates (n = analyzed chambers). These replicates were obtained from multiple chambers on the same chip, but the corresponding light-intensity was varied over several independent experiments (cultivation time approximately 32 days). C: Growth data of three different cyanobacteria strains under gradient growth-light illumination during microfluidic cultivation. Each datapoint represents a single growth chamber."*
+
+**Witting et al., 2025,Lab on a Chip, 25(3), 319–329. https://doi.org/10.1039/D4LC00567H**
\ No newline at end of file

assays/Microfluidic cultivation with gradient growth light and day night cycle/README.md

+# Microfluidic cultivation
+*''The platform presented in this work allows carrying out different experimental modes: microfluidic cultivations can be performed either with or without CO2 control, depending on the chip configuration. Without the additional gas control layer, CO2 availability depends on the surrounding atmosphere. The microfluidic cultivation chip can be illuminated homogeneously or a light-intensity gradient can be applied. The light-intensity can be constant, but also dynamic profiles, for example day–night cycles can be applied.
+Before starting an experiment, cyanobacteria were precultivated in the MC. Therefore, cyanobacteria were inoculated to an OD720 of 0.1 and cultivated for approximately 24 h. Prior to inoculation the tubing for BG11 medium supply and outflow were connected. BG11 medium was perfused at a flow rate of 200 nL min−1. After the cell inoculation, growth chambers containing cyanobacteria were selected manually for time-lapse imaging. Pictures were taken every 1 hour for experiments with homogeneous growth-light illumination and every 2 hours in experiments with gradient growth light-illumination. For microfluidic experiments with CO2 control, a premixed synthetic air bottle containing 200 ppm CO2 was used. Final CO2 concentrations were achieved by mixing defined volume flow rates of the synthetic air, N2 and O2 using red-y-smart thermal mass flow controllers (Vögtlin; Germany). Gas was perfused through the gas layer in countercurrent to medium flow. All experiments were performed at 37 °C. The Spectra Tune Lab light engine was set to emit Planck's radiation distribution at 5800 K, mimicking the spectrum emitted by the sun.37 Day–night rhythms were programmed in μwave and started simultaneously with the time-lapse sequence.''*
+
+# Growth-light calibration
+*''For direct light-intensity measurements of the homogeneous and gradient illumination (data shown in Fig. 4A), the sensor spot of a Li-180 Spectrometer (Li-Cor Biosciences; USA) was mounted on the X–Y-Stage and during measurements it was moved relative to the ringlight. Therefore, the ringlight and the Li-180 sensor were mounted at a comparable distance as between the ringlight and the microfluidic chip.
+The light-intensity gradient was calibrated prior to each experiment to assign a specific light-intensity for all cultivation chambers. An exemplary calibration is illustrated in detail in the ESI† material. Each calibration procedure included the following three main steps:
+i.) Using the LI-190R Terrestrial Quantum Sensor under homogeneous illumination of the growth light, the photon flux density (PFD) in the photosynthetic active range of illumination [μE m−2 s−1] was measured at various power settings [%] in the light engine's control software. A linear correlation was found between power setting and the resulting PFD.
+ii.) Instead of the cultivation chip, a microscopy calibration slide of homogeneous color and density (Chroma Technology, USA) was mounted in the same optical plane. Using the 2× objective, the microscope was focused on the top surface of this calibration slide. Then bright-field images of the calibration slide were taken with the Zyla camera under homogeneous growth-light illumination at various power settings. A linear correlation between the light engine's power settings and the averaged camera grey-values was found. By replacing the power levels with the corresponding PFD values from i), a linear correlation between camera pixel grey values and PFD can be derived.
+iii.) Finally, the half-circle cover was installed to generate the light-intensity gradient. Bright-field images of the calibration slide under gradient illumination at specific power settings were taken. During capture, no additional microscopy illumination was applied. The light-intensity gradient illumination resulted in linearly increasing camera grey values, resolving the gradient at camera resolution. By replacing the grey values with the corresponding PFD from ii.), the light-intensity gradient can now be described as linear function of PFD over position. The microscope's objective can not be moved relative to the ringlight. Hence, when a cultivation chip is later placed in the microscope the knowledge of the linear relation of the PFD in dependence on X-position allows to assign specific light-intensity values to each growth chamber.''*
+
+All the notebooks needed to analyse the data are uploaded into the protocols folder. Data plotting and hyperbolic tangent model fitting was performed in Origin2020 Pro.
+
+# Figure 4
+
+![File structure](dataset/Figure_4.png)
+
+*"A: Light-intensity profiles across the light cone emitted by the ringlight (homogeneous illumination mode and longitudinal to the light-intensity gradient). B: Growth data of UTEX2973 from microfluidic cultivations under light-intensity gradient illumination and under homogeneous illumination for comparison. Under light-intensity gradient illumination, each data point resembles growth inside distinct chambers from a single, continuously performed experiment (cultivation time approximately 4 days). Data points obtained during homogeneous illumination, include standard deviation and the number of replicates (n = analyzed chambers). These replicates were obtained from multiple chambers on the same chip, but the corresponding light-intensity was varied over several independent experiments (cultivation time approximately 32 days). C: Growth data of three different cyanobacteria strains under gradient growth-light illumination during microfluidic cultivation. Each datapoint represents a single growth chamber."*
+
+**Witting et al., 2025,Lab on a Chip, 25(3), 319–329. https://doi.org/10.1039/D4LC00567H**
\ No newline at end of file