Fluorescent Growth Status Indicator
Device

Overview

Our project, E. color, aims to develop a fundamental tool that provides automatic detection of bacterial status by applying fluorescent proteins as real-time indicators. Here, we present three main experimental designs that could assist in determining classical bacterial statuses, which include the construction of fluorescent growth phase indicators, cell division indicators, and native color indicators *. For more details regarding our project background, please visit our Description page.

The construction processes of all designs are similar, which require

  1. Determination of phase-dependent promoters
  2. Choosing suitable fluorescent colors
  3. Measurement of fluorescent expression through superposition between fluorescent emission curve and OD growth curve

A ribosomal validation test is then performed to ensure our indicators demonstrate a phase-dependent pattern. The amplifier and degradation system are designed for further improvement of our construct.

Growth Phase Indicators

Overview

The E. coli growth curve can be generally divided into four main phases: lag, exponential, stationary and death phase. Our project focuses on the following periods: lag, early-exponential, mid-exponential, late-exponential and stationary phase**. Due to the non-proliferating nature, small colony size and low bacterial count during lag phase, color observation is challenging in this period. Therefore, we decided to merge lag phase with early-exponential phase and apply a single indicator for its detection.

Determination of Phase-Dependent Promoters

To enable our E. coli to express visible and dominant colors at each phase, the first step is to select promoters that regulate the expression of phase-dependent genes. By screening through the mRNA expression profile of 4313 genes expressed during E. coli growth derived from whole transcriptome analysis1, we came up with 8 genes that demonstrate high expression levels and are best suitable for representing each growth phase: dusB, cyoA, nirBDC, glpABC, ansB, hchA, rmf and slp. Genes were selected according to the following criteria:

  1. Regulated by no more than two promoters
  2. Phase-dependent property has been mentioned in other literature
  3. Genes with similar functions have also been shown to express at that specific phase

The table below shows the mRNA expression curve of these phase-dependent genes 1-7 hours after dilution (0h) from a 17h overnight stationary phase sample (unit: transcript reads). Detailed description regarding gene and promoter characteristics as well as their role in E. coli growth is depicted in the right column.

Phase Phase-Specific Promoter
Early-Exponential Phase

The early-exponential phase promoters we selected are dusB-fis promoter and cyoA promoter.

dusB-fis promoter (dusBp/fisp)

The dusB-fis promoter regulates the dusB-fis operon, which includes dusB and global regulator gene fis2. The latter encodes small nucleoid-associated protein Fis, whose synthesis is rapidly induced upon nutrient upshift during early-exponential growth3. Both dusB and fis exhibit a growth phase-dependent mRNA expression pattern, with maximum mRNA levels during early-exponential phase and decreasing levels in mid-exponential and late-exponential phases (blue line).

cyoA promoter (cyoAp)

cyoA encodes for cytochrome bo3 oxidase, which predominates in the E. coli aerobic respiratory chain. cyoAp is activated during lag and early-exponential phase due to fis global regulation, and is later repressed by ArcA and FNR under anaerobic conditions (orange line4,5). cyoA mRNA expression pattern shows a brief rise after 4h due to GadE regulation 6, but it is considered negligible when combined with late-exponential phase promoter ansB, which results in an even stronger mRNA expression.

Mid-Exponential Phase

The mid-exponential phase promoters we selected are nirBDC promoter and glpABC promoter.

nirBDC promoter (nirBp)

The nirBDC promoter regulates the nirBDC operon, which regulates anaerobic reduction and transport of nitrite in E. coli. mRNA expression of nirB is low at lag and early-exponential phase under aerobic conditions due to Fis inhibition. During mid-exponential phase (3-4h), nirBDC operon is induced due to FNR activation under anaerobic cell growth conditions. IHF poses an inhibition effect on nirB at late-exponential and stationary phases7. Worthy to note, nirBDC promoter may be repressed by Cra when cells are grown in minimal medium8.

glpABC promoter (glpABCp)

Glycerol utilization during anaerobic respiration has shown to be dominant in the mid-exponential phase of E. coli9. Genes from the glpABC operon encode glycerol-3-phosphate (G3P) dehydrogenase complex, which catalyze the oxidation of G3P and play a critical role in glycerol catabolism10. Fnr activates glpABCp and induces high expression of the glpABC operon throughout this period11 (3-4h, orange line).

Late-Exponential Phase

The late-exponential phase promoter we selected is ansB promoter.

ansB promoter (ansBp1, ansBp2)

Bacteria start to catabolize amino acids as an alternative energy source after complete glucose depletion at late-exponential phase 12. The ansB promoter encodes for L-asparaginase II, which participates in the metabolism of asparagine. FNR and CRP co-activate ansBp during such anaerobic growth, while Fis downregulates its activity3,13. ansB reaches peak mRNA level at 4.5h and drops abruptly after entering stationary phase. Upregulation of ansB in late-exponential phase has also been observed in Saccharomyces cerevisiae14.

Stationary Phase

The stationary phase promoters we selected are hchA promoter, rmf promoter, and slp promoter.

hchA promoter (hchAp1, hchAp2)

hchA encodes stress-inducible heat shock protein Hsp31. Entry into the stationary phase leads to enhanced transcription from its σS-dependent promoters hchAp1 and hchAp2***. Hsp31 performs a protective function under a wide range of stress conditions, and hchA null mutants exhibit a decrease ability to survive in deep stationary phase15. Therefore, we believe it can be a strong indicator of the stationary phase (orange line).

rmf promoter (rmfp)

rmfp is regulated by ppGpp, which increases during stress conditions16. rmf encodes ribosome modulation factor (RMF), a stationary phase-specific inhibitor of ribosome function which facilitates the formation of inactive ribosome dimers under stringent circumstances17. rmf mRNA expression is enhanced after entrance into stationary phase (5h, blue line)

slp promoter (slpp)

slp is a carbon source starvation-induced stress response gene that encodes Slp (stationary-phase lipoprotein). The slp promoter is activated in response to carbon starvation and hydrogen peroxide stress18, which increases transcription of slp mRNA during transition into the stationary phase (gray line). Slp protein is also a major membrane component in stationary phase cultures grown in complex mediums19.

Choosing Suitable Color Reporters

Our ultimate goal is to ensure that the expression of each phase-dependent promoter could be easily detected by our real-time monitoring device. Therefore, we decided to apply color reporters that are easily visible, and arrange “Promoter-Reporter pairs” so that each color specifically represents a certain phase. Fluorescent genes are selected from FPbase, an open-source fluorescent protein (FP) database, according to the following standards:

  1. Short maturation time: increases accuracy of determining the “initiation” of a phase by reducing the time lapse between promoter activation and the expression of mature fluorescent protein
  2. Brightness: enhances the readability and convenience of identifying colors

Furthermore, the RGB Color Model is used as a reference for color mixing, from which we discovered that applying additive primary colors: red, green and blue as our indicator would provide clearer distinction between consecutive growth phases during transition. Therefore, we selected mCherry, mCerulean, yPet and AmilCP as our reporters. The table below shows their basic characteristics.

Reporters (Fluorescent protein / Chromoprotein) Max. excitation / emission wavelength (nm) Color Maturation time Brightness
mCherry 587 / 610 Red 15 min 15.84
mCerulean 433/ 475 Green 6.6 min 16.17
yPet 517 / 530 Yellow 9.7 min 80.8
AmilCP**** Absorbance maximum: 588 Blue 1 hr N/A

“Promoter-Reporter” Functional Test

To construct our “Promoter-Reporter pairs”, phase-dependent promoters were cloned from the genomic DNA of E. coli K-12 MG1655 and annealed with fluorescent gene fragments using Gibson assembly. Each construct was then transformed into E. coli K-12 DH5α and cultured for measurement of OD value and fluorescent expression. Originally, we expected a decline in fluorescence intensity after the termination of promoter activation. However, from the fluorescence intensity-time graph, we discovered that fluorescence continuously remained. Two hypotheses were proposed for the cause of lasting fluorescence: 1. Continuous production of fluorescent protein 2. Slow degradation of fluorescent protein by E. coli. Fast SsrA degradation tag BBa_K1051207 was applied to our construct to test which hypothesis is correct. For more information, please visit our Results page.

Ligation

Ligation was performed to combine the “Promoter-Reporter pairs” to form an integrated construct, enabling E. coli to express distinct color in each phase (Figure). We discovered that color is nearly undetectable during the early-exponential phase when bacteria is cultured in both solid and liquid medium due to low bacterial concentration and small colony size. Therefore, the early-exponential phase promoter-reporter pair was not ligated into our construct, and the fluorescent protein we used was changed. Another observation is that the hchA promoter expressed earlier than we expected. AmilCP, which has a slightly longer maturation time (1h), was used to delay its expression and enable a more accurate indication of the stationary phase. The “Promoter-Reporter pairs” we applied for our final construct are presented as follows (Table). The ligation plasmid is then transformed into E. coli K-12 DH5α for detection. The OD600 value measurements are then carried out and the photos are taken as well. For more information regarding our ligation process, please visit our Results page.

Phase Promoter Fluorescent Protein
Mid-exponential nirBDC mCerulean
Late-exponential glpABC mCherry
Stationary hchA AmilCP

 

Validation Biomarker of Growth Phase Indicators

Overview

In our project, phase-dependent promoters and color reporters were initially selected according to the physiological characteristics of E. coli K-12 DH5α. As an advanced foundational tool aiming to expand its application range in all sorts of bacterial types and culture conditions, validation of our growth phase indicators is indispensable to check whether our construct works in agreement with other biomarkers that could exemplify bacterial growth phase. Since bacterial growth is a consecutive and dynamic process, establishing a generic standard for the distinction between different phases is challenging. Therefore, we searched for genetic/molecular biomarkers of E. coli growth in order to verify that our growth phase indicators are viable.

Applying the MCrg Strain for Growth Phase Validation

Ribosome dynamics serve as a potential marker of bacterial growth and show a phase-dependent pattern (figure20). E. coli MCrg strain, a kind gift from Dr. Nikolay, expresses fluorescent-labeled ribosomal proteins L19-GFP and S2-mCherry, which could assist in real-time monitoring of ribosome dynamics21. By transforming our “Promoter-Reporter” combined construct into MCrg competent cells, we were able to differentiate growth phases by measuring fluorescence.

Ribosome RNA (rRNA) concentration (triangle) is tightly coupled with growth rate (square), which demonstrates a sharp increase in lag phase, rapid decrease throughout the exponential phase during nutrient deprivation, and low, stable expression throughout the stationary phase. Lag phase: 0-2h, Exponential phase: 2-6h, Stationary phase: after 6-10h.

 

Fluorescent Intensity Amplifier

Overview

To ensure that each growth phase indicator expresses sufficient fluorescent signal and that all indicators have similar intensity, an amplifier system is necessary for fine-tuning the expression of specific colors. Our project referred to the original fluorescent intensity amplifier design of iGEM team Cambridge 2007, which is composed of an activator gene and a downstream promoter (Figure). After receiving PoPS input, the activator gene would induce the promoter and thus result in an amplified PoPS output. Applying this system in our project could increase the expression of our mid-exponential phase indicator by producing a more observable color. for more information, please visit iGEM team Cambridge 2007 wiki page.

Design

The mid-exponential phase promoters are combined with phiR73, the PO promoter activator, and the PO promoter is combined with mCerulean, the intended mid log phase fluorescent protein. This will allow a 35-fold increase in fluorescent protein expression.

Applying the ssrA Degradation System

Overview

To distinguish different E. coli growth statuses more sharply and precisely, the degradation system is added to our construct. TEV protease cleavage site BBa_J18918 and HIV-1 protease cleavage site BBa_I712015 enhances the degradation rate of fluorescent proteins to minimize the interference of lasting fluorescence on subsequent phases, and reduces signal overlap between consecutive phases. In our design, the TEV protease and HIV-1 protease are applied to tightly control the initiation time point of degradation.

Design

TEV protease cleavage site BBa_J18918 is inserted into mid-exponential phase fluorescent protein mCerulean to form a split protein, and the TEV protease BBa_K1319008 is combined with late-exponential phase-dependent promoter glpABC. When bacteria enters late-exponential phase, glpABC activates and initiates the expression of TEV protease, which cuts off mCerulean, resulting in time-dependent regulation of protein degradation. The HIV-1 protease cleavage site BBa_I712015 is inserted into late-exponential phase fluorescent protein mCherry, and the HIV-1 protease BBa_I712667 is combined with a stationary phase-dependent promoter hchA. This allows the fluorescence protein to be quickly degraded in the next phase.

Native Color Indicator

Overview

Dead cells in cell culture can greatly affect experiment data quality. We develop a vague idea to distinguish live and dead bacteria cells in an effortless and accelerated method using splitGFP 1 and 2 , the split fluorescent protein system, via adding proteinase to retain extracellular protein. Developing into test kit is our future approach.

Design

First, selected iGEM Part BBa_K1789003 is confirmed the correct part using Colony PCR with primer VF2/VR. Then, its excitation/emission range 470nm/510~530nm with K1789003/DH5 alpha/LB+CM is processed. After confirmation, we planned of using BBa_K608008 (J23104 + RBS) as template and RF cloning method, BBa_K1789003(splitGFP1) would be inserted to replace the original GFP.

Later is the simulating degradation part, where HIS tag would be fused with our observed fluorescent protein because we plan to extract splitGFP1 from crude protein using rapid and reliable protein extraction using the properties of HIS tag. All of this is to prove that the fluorescent protein of dead cells will not interfere with the measurements of native color.

Simulating Degradation

To make use of Native Color as an indicator for live cells, we needed to prove that the fluorescent protein of dead cells will not interfere with the measurements of native color. The degradation curve of fluorescent protein from K1789003 is to be drawn for Modeling, then the remaining fluorescent protein part to be accounted as background value and removed.

Our target is to find an effortless and accelerated approach, however, because of time limitation, we did not complete the purification process and the modeling of its degradation curve.

Future Approach

Developing rapid test kits using the properties of splitGFP and the foundation of native color- using K1789003-is what we envisioned as our future proposition. Although it is based on the theory of the simulation of degradation curve in experiment 2, it is still a vague concept at the moment. Our concept is as followed: If we could identify the extracellular fluorescent protein as one of expression of dead cells , then we can use splitGFP 2 to fuse with splitGFP 1 from the culture. Firstly, take a small sample from a culture. Secondly, add proteinase to retain extracellular protein. Finally, add the already extracted excess splitGFP2 to allow dead cells to glow.

Furthermore, the degradation curve will explain what our test kits can do:

  1. If the fluorescent protein degrades fast, it will prove that the captured splitGFP 1 by splitGFP2 is linked to the environment of the cell culture. The more fluorescence is observed by the naked eye, the more it represents unsuitable environment for the bacteria.
  2. If the fluorescent protein degrades slow, it will prove that the captured splitGFP 1 by splitGFP2 is linked to the total quantity of dead bacterial cells. Moreover, if this data could be used along with growth curve, it could even make up the lack of death phase in our project E. color.

 

Cell Division Indicator

Our project aims to develop a fundamental tool for monitoring microbial organisms' growth status. Cell division is an important phase that plays an important role in the research of cell cycles and the application of antibiotics. Therefore, we worked on this critical cell stage and came up with a plan of monitoring the start of cell division. After consulting with Dr. Yua-Ling Shih, Dr. Ting-Jen Cheng, and Dr. Wei-Chieh Cheng from Academia Sinica, we found that building a cell division monitoring tool may bring great changes to basic research.

(Learn more about the consultation on the Integrated Human Practice page)

We designed an engineering construct, which was expected to have an obvious change in the observation every time the bacteria starts to do cell division. Construct consisting of a promoter that specifically marks the start of cell divisions and a fluorescent protein that indicates the transcription of the very promoter, brings color change to the users' eyes.

Selection of Promoters

In order to create a cell division fluorescent indicator, we looked for promoters that oscillate in the cell cycle. By literature searching, we picked the following promoters: ftsZ1p, ftsZ2p, and ftsQ2p+ftsQ1p.

The ftsZ1p and ftsZ2p are promoters of the important cell division protein FtsZ, and its activity were oscillating during the cell cycle.22 However, there are research showing these promoters contribute a relatively weak effect to the transcription of FtsZ, this is why we search for alternative promoters. Then we found promoters ftsQ2p and ftsQ1p.

Promoters ftsQ2p+ ftsQ1p were chosen for two reasons. First, they are the promoters of critical cell division proteins FtsZ, and we found the research saying “There have been several reports suggesting that transcription of ftsZ is periodic in the cell cycle, with transcription taking place just before cell division.”.23 Second, based on the previous research, we looked through the promoters of the FtsZ protein and found that the combination of ftsQ2p+ftsQ1p contributes enormously to the transcription of FtsZ.23

Selection of Fluorescent Protein

The average time of an E. coli cell cycle is 40 minutes. We had to find a fluorescent protein with a short maturation time and half-life. After discussion and consideration of our budgets, mCherry was chosen. It has a 15-minute maturation time, and a 40-minute half-life, which leads it to become the best fluorescent protein for us to use in our design.

    Reference

  1. Smith, A., Kaczmar, A., Bamford, R. A., Smith, C., Frustaci, S., Kovacs-Simon, A., O'Neill, P., Moore, K., Paszkiewicz, K., Titball, R. W., & Pagliara, S. (2018). The Culture Environment Influences Both Gene Regulation and Phenotypic Heterogeneity in Escherichia coli. Frontiers in microbiology, 9, 1739. https://doi.org/10.3389/fmicb.2018.01739

  2. Mallik, P., Pratt, T. S., Beach, M. B., Bradley, M. D., Undamatla, J., & Osuna, R. (2004). Growth phase-dependent regulation and stringent control of fis are conserved processes in enteric bacteria and involve a single promoter (fis P) in Escherichia coli. Journal of bacteriology, 186(1), 122-135. https://doi.org/10.1128/JB.186.1.122-135.2004

  3. Nafissi, M., Chau, J., Xu, J., & Johnson, R. C. (2012). Robust translation of the nucleoid protein Fis requires a remote upstream AU element and is enhanced by RNA secondary structure. Journal of bacteriology, 194(10), 2458-2469. https://doi.org/10.1128/JB.00053-12

  4. Bradley, M. D., Beach, M. B., de Koning, A., Pratt, T. S., & Osuna, R. (2007). Effects of Fis on Escherichia coli gene expression during different growth stages. Microbiology (Reading, England), 153(Pt 9), 2922-2940. https://doi.org/10.1099/mic.0.2007/008565-0

  5. Cotter, P. A., & Gunsalus, R. P. (1992). Contribution of the fnr and arcA gene products in coordinate regulation of cytochrome o and d oxidase (cyoABCDE and cydAB) genes in Escherichia coli. FEMS microbiology letters, 70(1), 31-36. https://doi.org/10.1016/0378-1097(92)90558-6

  6. Hommais, F., Krin, E., Coppée, J. Y., Lacroix, C., Yeramian, E., Danchin, A., & Bertin, P. (2004). GadE (YhiE): a novel activator involved in the response to acid environment in Escherichia coli. Microbiology (Reading, England), 150(Pt 1), 61-72. https://doi.org/10.1099/mic.0.26659-0

  7. Browning, D. F., Cole, J. A., & Busby, S. J. (2000). Suppression of FNR-dependent transcription activation at the Escherichia coli nir promoter by Fis, IHF and H-NS: modulation of transcription initiation by a complex nucleo-protein assembly. Molecular microbiology, 37(5), 1258–1269. https://doi.org/10.1046/j.1365-2958.2000.02087.x

  8. Tyson, K., Busby, S., & Cole, J. (1997). Catabolite regulation of two Escherichia coli operons encoding nitrite reductases: role of the Cra protein. Archives of microbiology, 168(3), 240–244. https://doi.org/10.1007/s002030050494

  9. Poladyan, A., Avagyan, A., Vassilian, A., & Trchounian, A. (2013). Oxidative and reductive routes of glycerol and glucose fermentation by Escherichia coli batch cultures and their regulation by oxidizing and reducing reagents at different pHs. Current microbiology, 66(1), 49–55.

  10. Khademian, M., & Imlay, J. A. (2017). Escherichia coli cytochrome c peroxidase is a respiratory oxidase that enables the use of hydrogen peroxide as a terminal electron acceptor. Proceedings of the National Academy of Sciences of the United States of America, 114(33), E6922–E6931. https://doi.org/10.1073/pnas.1701587114

  11. Unden, G., & Bongaerts, J. (1997). Alternative respiratory pathways of Escherichia coli: energetics and transcriptional regulation in response to electron acceptors. Biochimica et Biophysica Acta (BBA)-Bioenergetics, 1320(3), 217-234.

  12. Robbins, J. W., Jr, & Taylor, K. B. (1989). Optimization of Escherichia coli growth by controlled addition of glucose. Biotechnology and bioengineering, 34(10), 1289–1294. https://doi.org/10.1002/bit.260341007

  13. Jennings, M. P., & Beacham, I. R. (1993). Co-dependent positive regulation of the ansB promoter of Escherichia coli by CRP and the FNR protein: a molecular analysis. Molecular microbiology, 9(1), 155–164. https://doi.org/10.1111/j.1365-2958.1993.tb01677.x

  14. Oliveira, E. M., Carvajal, E., & Bon, E. P. (1999). L-asparaginase II of saccharomyces cerevisiae. Activity profile during growth using an ure2 mutant P40-3C and a P40-3C + URE2p strain. Applied biochemistry and biotechnology, 77-79, 311–316. https://doi.org/10.1385/abab:77:1-3:311

  15. Mujacic, M., & Baneyx, F. (2006). Regulation of Escherichia coli hchA, a stress-inducible gene encoding molecular chaperone Hsp31. Molecular microbiology, 60(6), 1576–1589. https://doi.org/10.1111/j.1365-2958.2006.05207.x

  16. Izutsu, K., Wada, A., & Wada, C. (2001). Expression of ribosome modulation factor (RMF) in Escherichia coli requires ppGpp. Genes to cells : devoted to molecular & cellular mechanisms, 6(8), 665–676. https://doi.org/10.1046/j.1365-2443.2001.00457.x

  17. Wada, A., Igarashi, K., Yoshimura, S., Aimoto, S., & Ishihama, A. (1995). Ribosome modulation factor: stationary growth phase-specific inhibitor of ribosome functions from Escherichia coli. Biochemical and biophysical research communications, 214(2), 410–417. https://doi.org/10.1006/bbrc.1995.2302

  18. Li, X., Xie, Y., Jin, J., Liu, H., Gao, X., Xiong, L., & Zhang, H. (2018). Carbon starvation-induced lipoprotein Slp directs the synthesis of catalase and expression of OxyR regulator to protect against hydrogen peroxide stress in Escherichia coli. BioRxiv, 386003. https://doi.org/10.1101/386003

  19. Price, G. P., & St John, A. C. (2000). Purification and analysis of expression of the stationary phase-inducible slp lipoprotein in Escherichia coli: role of the Mar system. FEMS microbiology letters, 193(1), 51–56. https://doi.org/10.1111/j.1574-6968.2000.tb09401.x

  20. Failmezger, J., Ludwig, J., Nieß, A., & Siemann-Herzberg, M. (2017). Quantifying ribosome dynamics in Escherichia coli using fluorescence. FEMS microbiology letters, 364(6), 10.1093/femsle/fnx055. https://doi.org/10.1093/femsle/fnx055

  21. Nikolay, R., Schloemer, R., Schmidt, S., Mueller, S., Heubach, A., & Deuerling, E. (2014). Validation of a fluorescence-based screening concept to identify ribosome assembly defects in Escherichia coli. Nucleic acids research, 42(12), e100. https://doi.org/10.1093/nar/gku381

  22. Garrido, T., Sánchez, M., Palacios, P., Aldea, M., & Vicente, M. (1993). Transcription of ftsZ oscillates during the cell cycle of Escherichia coli. The EMBO journal, 12(10), 3957–3965. https://doi.org/10.1002/j.1460-2075.1993.tb06073.x

  23. Dewar, S. J., & Dorazi, R. (2000). Control of division gene expression in Escherichia coli. FEMS microbiology letters, 187(1), 1–7. https://doi.org/10.1111/j.1574-6968.2000.tb09127.x

    Notes

  • “Native color” is a self-defined term used to represent a fluorescent color that constitutively and stably expresses in a bacteria during a survival state. This indicator is designed to distinguish between live and dead bacteria.

  • Exponential phase is a crucial phase among the bacterial growth curve due to its abrupt change in growth mechanisms. Besides its physiological importance, the exponential phase is also crucial for certain experimental manipulations, such as the addition of IPTG during recombinant protein expression, etc. Due to its broad application range and significance in research aspects, we decided to refine our indicators so that they can elaborately express in the early-, mid-, and late- exponential phase.

  • The sigma factor σS (also called σ38 or RpoS) is a bacterial transcription initiation factor which is activated during entry into stationary phase and in response to multiple stress conditions.

  • AmilCP is a chromoprotein that exhibits strong blue color and is matched with stationary phase promoter hchA due to its longer maturation time. Please visit our Engineering page for more details.

Overview

Our device aims at remotely reporting the growth phase of the bacteria colony. To do this, we first determined the most dominant background to emphasize the colony. Arduino are chosen as the detective system, and the rotating device is built for multiple measurements for cultured dishes. By detecting the color change, we are able to differentiate the colony growth phases since our bacteria express distinct colors during each phase. The software we used to process data are YoloV5 and OpenCV. In the end, the LineBot system is implemented for retrieving data remotely.

Choosing Background for Plate Detection

To enable easier detection of colonies on solid medium, suitable background color must be chosen to enhance the contrast between the plate and colony color. Through the data training process, we discovered that a dark background is optimal for highlighting bacterial colonies. Therefore, we applied dark green and black coloured paper as background material for camera detection.

Servo Motor Turntable with Arduino

The idea that monitoring culture dishes with a camera is simple yet limited in detecting numbers. To overcome this limitation, the rotating devices are designed and built with 3D printed.

Choosing Detection Device

We select arduino as the detection device for it is either easy to get started or rich in resources. Note that the use of cameras is not limited to the brand, as long as the picture quality is sufficient.

YoloV5 and OpenCV as Software

YoloV5 is a newer model for object detection, with the advantages of good accuracy, choice of different depth models, and accelerated training on 30-series graphics cards; Opencv is the most widely used python library for image processing, with many functions and high convenience.

LineBot as Interactive Platform

We use LineBot to avoid compatibility problems and information security issues. since it has been written in python itself, it also is more applicable.

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