Periodic Reporting for period 1 - MMED (Development of a Microfluidic Microbial Ecology Device and Mathematical Model to Study Antibiotic Response of Individual Cells)
Período documentado: 2019-01-14 hasta 2021-01-13
Antibiotic resistance is one of the biggest threats to global health today. Despite the available prevention and control strategies and efforts to develop new antibiotics, still effective strategies to control the most dangerous forms of antibiotic-resistant bacteria is needed. To discover effective strategies, a quantitative and deeper understanding of microbial behavior in their natural ecologies is crucial. The specific aim of this investigation is to develop a theoretical and experimental framework that mimics the natural microecology of bacteria and measuring their antibiotic responses to predict optimum survival strategies. Effect of antibiotic stress on bacterial individuals will be quantitatively investigated in the microfluidic microbial ecology device (MMED) that mimics various microecologies at the same time, while allowing antibiotic exposure. The mathematical microbial ecology model (MMEM) predicts the antibiotic responses of bacteria and bacterial survival strategies. This system will allow quantification of individuals’ optimum survival strategy under the influence of both microenvironmental changes and antibiotic exposure.
Traditionally, influence of antibiotics and stable microenvironments on growth and behavior of individual bacteria have been independently studied. However, there are quantitative and qualitative differences between exposing cells in stable or dynamic environments and in combination with antibiotic stress. Understanding the underlying molecular mechanisms those bacteria use to adapt to different stresses will bring transferable benefits for health, ecology, and science.
Overall objectives of this project are combining quantitative experimental measurements and theoretical studies using MMED to contribute to the discovery of new information regarding the antibiotic response of bacteria in artificial microhabitats. By developing ex vivo infection models or infection-on-a-chip platforms and infection-on-a-script models, MMED will provide a new foundation to understand the individuality of bacteria, working mechanisms of antibiotics, and facilitate the development of new antibiotics and culture of rare cells. Hence, the project findings can be transferred to cutting-edge tools to study microbiology and microecology, biofilm-free implants and medical kits, new antibiotics, and educational toolbox and simulators to study course of infection and antibiotic administration for medical research.
Traditionally, influence of antibiotics and stable microenvironments on growth and behavior of individual bacteria have been independently studied. However, there are quantitative and qualitative differences between exposing cells in stable or dynamic environments and in combination with antibiotic stress. Understanding the underlying molecular mechanisms those bacteria use to adapt to different stresses will bring transferable benefits for health, ecology, and science.
Overall objectives of this project are combining quantitative experimental measurements and theoretical studies using MMED to contribute to the discovery of new information regarding the antibiotic response of bacteria in artificial microhabitats. By developing ex vivo infection models or infection-on-a-chip platforms and infection-on-a-script models, MMED will provide a new foundation to understand the individuality of bacteria, working mechanisms of antibiotics, and facilitate the development of new antibiotics and culture of rare cells. Hence, the project findings can be transferred to cutting-edge tools to study microbiology and microecology, biofilm-free implants and medical kits, new antibiotics, and educational toolbox and simulators to study course of infection and antibiotic administration for medical research.
The design of microfluidic microbial ecology device (MMED) and the script for the mathematical microbial ecology model (MMEM) were generated, the MMED was fabricated, and the experiments have been conducted.
Simulations and experiments with Escherichia coli (E. coli) cells were performed both in topologically homogenous and heterogeneous microenvironments to determine the growth profile of cells under the influence of crowded microenvironments. The results of the simulations and experiments with E. coli cells in their artificial microhabitats were submitted for a scientific article: “Kaymaz, S., V., Demir, G. K., Elitas, M. (Submitted). Mathematical Modeling of Escherichia coli Kinetics to Predict Growth and Rifampicin-dependent Killing Profile”. Besides, previously generated data of isoniazid exposed M. smegmatis cells was published as a scientific article using the acquired analysis skills in this project: “Elitas, M., Dhar, N., McKinney D. J. (2021). Revealing antibiotic tolerance of Mycobacterium smegmatis Xanthine/Uracil Permease Mutant using microfluidics and single-cell analysis. Antibiotics, 7, 794. https://doi.org/10.3390/antibiotics10070794”.
Moreover, the results of the simulations and experiments of antibiotic exposed E. coli cells in the artificial microhabitats was submitted to the conference: “Kaymaz, S., V., Elitas, M. (Submitted to ETAI 2022). A deep learning approach for quantitative single-cell analysis of ciprofloxacin-treated Escherichia coli cells in heterogeneous microenvironments, https://spie.org/op22n/conferencedetails/emerging-topics-in-ai?utm_id=rop22scpw&SSO=1”. Next, a manuscript related to single-cell analysis of E. coli for ciprofloxacin killing in topologically different microenvironments is under preparation: “Kaymaz, S., V., Elitas, M. (Under preparation). Single-cell analysis of Escherichia coli for ciprofloxacin killing in topologically different microenvironments”. Furthermore, the simulation results generated to predict the rifampicin response of E. coli cells by traditional colony forming unit assays was submitted as a manuscript, as mentioned above. Finally, the developed mathematical model is being optimized to become a free, open access toolbox for researchers to build upon.
In this project the generated data is accessible via a HTTP web repository: https://mmed.sabanciuniv.edu/.
The results of the projects were faithfully communicated to different audiences. The press releases by the Press Office at SU was announced the updates and events related to projects through: http://gazetesu.sabanciuniv.edu/en. Yearly one-day training school for the primary school students was performed at Sabanci University. Several high schools and universities were visited, and the project was presented. Simple microfluidics devices were shared to the high school students at the summer school at Sabanci University: http://liseyazokulu.sabanciuniv.edu. Social media (Facebook, LinkedIn, and Twitter) usage provided access to reach young people, inspire them, and encourage them to consider a career path in science in Europe. Besides, CORDIS and Elitas laboratory webpage were used for the dissemination of the project results: http://myweb.sabanciuniv.edu/melitas/marie-curie-project-at-biomechatronics-group/. Still, popular science articles will be published with jargon-free, simple language to disseminate the results of the project. Since, new experiments will be conducted using the MMED and MMEM frameworks, the newsletter of EU and SU, EU Research and Innovation magazines will be informed and updated with the significant research results.
Simulations and experiments with Escherichia coli (E. coli) cells were performed both in topologically homogenous and heterogeneous microenvironments to determine the growth profile of cells under the influence of crowded microenvironments. The results of the simulations and experiments with E. coli cells in their artificial microhabitats were submitted for a scientific article: “Kaymaz, S., V., Demir, G. K., Elitas, M. (Submitted). Mathematical Modeling of Escherichia coli Kinetics to Predict Growth and Rifampicin-dependent Killing Profile”. Besides, previously generated data of isoniazid exposed M. smegmatis cells was published as a scientific article using the acquired analysis skills in this project: “Elitas, M., Dhar, N., McKinney D. J. (2021). Revealing antibiotic tolerance of Mycobacterium smegmatis Xanthine/Uracil Permease Mutant using microfluidics and single-cell analysis. Antibiotics, 7, 794. https://doi.org/10.3390/antibiotics10070794”.
Moreover, the results of the simulations and experiments of antibiotic exposed E. coli cells in the artificial microhabitats was submitted to the conference: “Kaymaz, S., V., Elitas, M. (Submitted to ETAI 2022). A deep learning approach for quantitative single-cell analysis of ciprofloxacin-treated Escherichia coli cells in heterogeneous microenvironments, https://spie.org/op22n/conferencedetails/emerging-topics-in-ai?utm_id=rop22scpw&SSO=1”. Next, a manuscript related to single-cell analysis of E. coli for ciprofloxacin killing in topologically different microenvironments is under preparation: “Kaymaz, S., V., Elitas, M. (Under preparation). Single-cell analysis of Escherichia coli for ciprofloxacin killing in topologically different microenvironments”. Furthermore, the simulation results generated to predict the rifampicin response of E. coli cells by traditional colony forming unit assays was submitted as a manuscript, as mentioned above. Finally, the developed mathematical model is being optimized to become a free, open access toolbox for researchers to build upon.
In this project the generated data is accessible via a HTTP web repository: https://mmed.sabanciuniv.edu/.
The results of the projects were faithfully communicated to different audiences. The press releases by the Press Office at SU was announced the updates and events related to projects through: http://gazetesu.sabanciuniv.edu/en. Yearly one-day training school for the primary school students was performed at Sabanci University. Several high schools and universities were visited, and the project was presented. Simple microfluidics devices were shared to the high school students at the summer school at Sabanci University: http://liseyazokulu.sabanciuniv.edu. Social media (Facebook, LinkedIn, and Twitter) usage provided access to reach young people, inspire them, and encourage them to consider a career path in science in Europe. Besides, CORDIS and Elitas laboratory webpage were used for the dissemination of the project results: http://myweb.sabanciuniv.edu/melitas/marie-curie-project-at-biomechatronics-group/. Still, popular science articles will be published with jargon-free, simple language to disseminate the results of the project. Since, new experiments will be conducted using the MMED and MMEM frameworks, the newsletter of EU and SU, EU Research and Innovation magazines will be informed and updated with the significant research results.
The results might contribute to advance socio-economic status of Europe with developing new antibiotics, medications as an alternative to antibiotics, biofilm-free biomedical implants, a simulator (MMEM) and toolbox (MMED) for educational training. Socio-economically, the project supported two female graduate students. Hande Karamahmutoglu was a master student at Sabanci University, currently she is a doctoral student at KU Leuven and Sumeyra Vural Kaymaz performs her doctoral studies at Sabanci University, she conducts her doctoral studies on understanding antibiotic killing mechanisms, as well. Besides, the developed numerical model will be a free, open access toolbox for researchers to build upon. The produced data will be deposited in publicity accessible databases, https://mmed.sabanciuniv.edu/. This data might be useful for the researchers who interrogate antibiotic action mechanisms using traditional assays or microfluidics. Besides, researchers who cannot afford performing time-lapse experiments but needs single-cell data, they can use the generated image data. One of the societal implications of the project was being a female, young scientist who has a passion to pursue her career in academia, I became a role model not only for my female students but also my junior colleagues at Sabanci University, who was also supported by H2020 -MSCA-IF programs.