Overview

This year, the 2022 NYCU-Taipei iGEM Team — “E. color”, presents a gene-edited E. coli DH5α product which could provide real-time, remote monitoring of bacterial growth by integrating the use of growth status indicators with a user-friendly detection device. Our product aims to benefit researchers in both laboratories and the biomanufacturing industry using bacteria as a host-vector system. By using reporters to indicate different growth statuses, this foundational advance could increase the convenience and efficiency of microbial use in basic research and industrial settings, with hope of bringing impact to the whole scientific community.

Background

“E. color" aims to develop growth status indicators assisted by real-time detection which provides method optimization for experiments applied in microbiological research.

Present Methods of Monitoring Bacterial Growth

Escherichia coli is a model organism frequently used in laboratories, and is one of the most well-established expression platforms for the synthesis of recombinant proteins.1, 2 Understanding microbial growth characteristics is vital for cloning and recombinant protein expression.3 The duration and cell concentration at lag, exponential and stationary phases differ according to factors including culture medium, vector, strain, temperature, inducer, etc.4 Various approaches have been developed to monitor microbial growth, each with advantages and shortcomings(Table. 1).5

Table. 1) Comparison of common techniques for monitoring microbial amount

Approach Culture cell count OD600 measurement Flow cytometry / qPCR Biochemical assay (ATP assay, DNA concentration assay)
Advantages
  • Easy to quantify
  • Easy to determine presence on contamination
  • Fast
  • Sample is recoverable
  • Very accurate enumeration
  • DNA is stable for long time once extracted
  • DNA can be used for downstream applications
Disadvantages
  • Requires time for bacteria to grow into colony
  • Unable to quantify complex communities
  • Precipitants in liquid culture reduce accuracy
  • Expensive and technique-demanding
  • Expensive reagents
  • Do not provide true cell count

Traditionally, scientists calculate cell concentration by obtaining liquid culture samples and reading OD600 values on a spectrophotometer. The optical density (OD) number indicates the growth status and the right time to execute specific steps. This method poses disadvantages due to the following reasons:

  1. Metabolites released from dead bacteria form precipitants in the liquid culture, which causes inaccuracy in measurement.
  2. Researchers must constantly check the growth status and OD of E. coli cultures to determine the optimal induction point and induction period before conducting the experiment. This requires researchers to do it in-person and stay near the laboratory while experimenting.
  3. Frequently taking the liquid culture out of the incubator causes uncertainty by introducing extra variables to the bacteria, such as temperature and humidity.

Inspiration for the Design of Growth Status Indicators

Before deciding on our project, we discovered that many labs in our school use E. coli for their experiments. Despite being an important biological model, the repeated process of taking the liquid culture out from the incubator and measuring OD is time-consuming.

We also conducted a public survey in order to collect information on how researchers monitor bacterial growth status, because we would like to know their perspective whether they believe that development of an auxiliary tool is helpful to their research.

After learning that many researchers believe that development of an auxiliary tool for monitoring bacterial growth is necessary, we started to seek solutions to the problem. For more information regarding our survey results, please visit our Integrated HP page.

Meanwhile, our team discussed the future trend of synthetic biology, and came up with the conclusion that “automation” and “precision” are two essential key points for successful application of synthetic biology in society.

With the understanding that repetitive manual operations are required for many experimental procedures, we set off to search for a more precise and efficient method, and discovered that real-time monitoring of fluorescence is a goal worth looking forward to. This motivated us to choose the development of fluorescent growth status indicators with a real-tracking system as our project.

Expanding Our Indicator Design to Other Bacterial Growth Characteristics

There are many other essential growth characteristics beside bacterial growth phase and cell concentration. Cellular division plays an essential role in bacterial growth, which is a crucial time point for the addition of antibiotics due to its high cell wall synthesis and recycling rate. Inhibition of cell cycle proteins also provide insight for the development of antibiotics.6(Click me!)

Furthermore, bacterial survival status is also a fundamental property which could be implemented in clinical settings as a drug screening tool if an indicator is developed. For more information regarding how our project is applied in the industrial and medical field, please visit our Implementation page.

 

Approach

Building on Past Achievements

In our project, we developed an alternative approach for monitoring E. coli growth status by integrating synthetic biology with novel hardware design. Building on the achievement of team MIT 20067, who used scents as natural reporters of different E. coli growth phases, our team went a step further and proposed an improved version of phase monitoring. We decided to use fluorescent proteins to replace ester-producing enzymes, which enables quantitative measurements of protein expression. We also expanded our fluorescence indicators to detect all phases within the curve, which improves the integrity of the product.

We would also like to refer to team Cambridge 2007, who designed sensitivity tuners and color generators to optimize biosensor function, and apply sensitivity tuners to our construct so that promoter expression can be flexibly modulated. With the consensus on developing an optimized method with wide input-sensitivity and low technical threshold, our real-time detection device would automatically process information and enable users to easily track bacterial growth status on an interactive mobile platform.

Growth Status Indicators

Our team plans to address the inconvenience of past microbial monitoring methods by using reporters to indicate different E. coli growth statuses, which include determination of bacterial growth phase, survival status and time point of cell division.

With synthetic biology, we designed growth phase indicators consisting of phase-dependent promoters fused with reporter genes. We divided the growth curve into 4 periods: early-exponential, mid-exponential, late-exponential and stationary phase. Each phase will be assigned with a different color so researchers can obtain the E. coli status without taking the flask out of the incubator. Our native color indicator consists of reporter genes fused with a constitutive promoter, and our cell division indicator consists of reporter genes fused with promoters expressed specifically during cell division. For more information regarding our project design, please visit our Design page.

Real-Time Detection Device

We also constructed a real-time monitoring device that detects bacterial growth in both solid and liquid cultures. Reporter signals emitted from the culture will be collected by an Arduino device. Information is then processed by analyzing software YOLOv5 and OpenCV then transmitted to user mobile devices by LINE Bot. That way, users can remotely monitor their bacterial culture and look back upon past image records with a simple touch of the screen.

Our product can be broadly applied based on experimental requirements, and serves as an auxiliary tool for traditional methods by making it more convenient and accessible. With the advantages of time-saving, low cost and low technical-threshold, “E. color” presents to users a hopeful method for improving the working environment of microbiological researchers. Please visit our Device page for more information.

Project Goals

Our success in being able to distinguish different E. coli growth statuses will be the start of a total game changer for scientific, medical and biotechnological industries.

We anticipate to fulfill the following goals, which involves three aspects:

  1. Improve the working environment of microbiological researchers

    We aim to improve the working environment of microbiological researchers. By using our product, researchers can trace the bacteria remotely, saving time, manpower and the need of taking them out to measure their status. Moreover, our project strives to increase the accessibility of our product by reducing cost and technical threshold.

  2. Enhance the efficiency and productivity of mass production

    We hope to enhance the yield and efficiency of mass production. Our design would hopefully aid in determining the induction time point for protein expression, thus leading to better quantity and quality of recombinant drug/protein.

  3. Auxiliary tool for drug screening in clinical environments

    We anticipate that our design can serve as an auxiliary tool for drug screening in clinical settings and can help test whether bacteria is susceptible or resistant to the target drug.

Check out our Project Design!

 

    Reference

  1. Blount Z. D. (2015). The unexhausted potential of E. coli. eLife, 4, e05826. https://doi.org/10.7554/eLife.05826

  2. Rosano, G. L., & Ceccarelli, E. A. (2014). Recombinant protein expression in Escherichia coli: advances and challenges. Frontiers in microbiology, 5, 172. https://doi.org/10.3389/fmicb.2014.00172

  3. Fakruddin, M., Mohammad Mazumdar, R., Bin Mannan, K. S., Chowdhury, A., & Hossain, M. N. (2012). Critical Factors Affecting the Success of Cloning, Expression, and Mass Production of Enzymes by Recombinant E. coli. ISRN biotechnology, 2013, 590587. https://doi.org/10.5402/2013/590587

  4. Sandomenico, A., Sivaccumar, J. P., & Ruvo, M. (2020). Evolution of Escherichia coli Expression System in Producing Antibody Recombinant Fragments. International journal of molecular sciences, 21(17), 6324. https://doi.org/10.3390/ijms21176324

  5. Brown, D. C., & Turner, R. J. (2022). Assessing Microbial Monitoring Methods for Challenging Environmental Strains and Cultures. Microbiology Research, 13(2), 235-257. https://doi.org/10.1101/2021.10.05.463247

  6. Lock, R. L., & Harry, E. J. (2008). Cell-division inhibitors: new insights for future antibiotics. Nature reviews. Drug discovery, 7(4), 324–338. https://doi.org/10.1038/nrd2510

  7. MIT 2006 iGEM team: https://2006.igem.org/wiki/index.php/MIT_2006

  8. Cambridge 2007 iGEM team: https://2007.igem.org/wiki/index.php/Cambridge
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