Bacteria exhibit impressive swimming abilities, which, while fascinating, pose significant risks to human health. In healthcare settings, one prevalent bacterial infection results from bacteria infiltrating the body through catheters—slender tubes placed in the urinary tract.
Above, a diagram of simulated bacterial progress up a catheter tube lined with triangular fin-like protrusions. Below is an image created from high-speed video of actual bacteria attempting to swim upstream in a laboratory experiment. The bacteria's actual trajectories matched the simulated predictions remarkably well. Image Credit: X. Wan
Despite the intended function of catheters to withdraw fluids from patients, bacteria can navigate against the flow and traverse catheter tubes with their unique swimming motion, resulting in catheter-associated urinary infections amounting to approximately $300 million annually in the US
A new kind of catheter tube that prevents bacteria from migrating upstream has now been created at Caltech through an interdisciplinary project, negating the need for antibiotics or other chemical antimicrobial treatments. The new design reduced the number of bacteria that can swim upstream in lab experiments by a factor of 100, thanks to innovative artificial intelligence (AI) technology.
On January 3rd, 2024, the research was published in the journal Science Advances. The laboratories of Paul Sternberg, Bren Professor of Biology; John Brady, Chevron Professor of Chemical Engineering and Mechanical Engineering; Anima Anandkumar, Bren Professor of Computing and Mathematical Sciences; Chiara Daraio, G. Bradford Jones Professor of Mechanical Engineering and Applied Physics and Investigator for the Heritage Medical Research Institute, collaborated on the project.
Similar to the flow in a river’s current, where the water’s velocity varies from fast in the center to slow near the banks, fluid in catheter tubes exhibits an effect known as Poiseuille flow, where fluid movement is faster in the center but slower near the wall.
Since the bacteria are self-propelling, bacteria move in tubular structures in a special way that involves taking two steps forward along the wall and one step back in the middle. This phenomenon had previously been modeled by Brady lab researchers.
One day, I shared this intriguing phenomenon with Chiara Daraio, framing it simply as a ‘cool thing,’ and her response shifted the conversation toward a practical application. Chiara’s research often plays with all kinds of interesting geometries, and she suggested tackling this problem with simple geometries.
Tingtao Edmond Zhou, Postdoctoral Scholar and Study Co-first Author, Chemical Engineering, California Institute of Technology
In response to that recommendation, the group created tubes with shark-fin-like triangular protrusions inside the tube walls. The geometric structures successfully redirected the movement of the bacteria, pushing them toward the center of the tube where the faster flow pushed them back downstream, according to the promising results of the simulations. The fin-like curvature of the triangles created vortices that further hampered bacterial growth.
Zhou and associates sought to confirm the design through experimentation, but the team required more knowledge in biology. Zhou contacted Olivia Xuan Wan, a Postdoctoral Scholar working in the Sternberg lab, about it.
I study nematode navigation, and this project resonated deeply with my specialized interest in motion trajectories.
Olivia Xuan Wan, Study Co-first Author and Postdoctoral Scholar, California Institute of Technology
The Sternberg laboratory has dedicated years to studying the navigation mechanisms of Caenorhabditis elegans, a minute soil-dwelling nematode, often researched in laboratories. Their extensive toolkit enables them to observe and analyze the movements of these microscopic organisms effectively.
The group moved swiftly from theoretical modeling to real-world experimentation, tracking the growth of bacteria with high-speed cameras and 3D printed catheter tubes. The upstream bacterial movement is reduced by two orders of magnitude (a 100-fold decrease) in the tubes containing the triangular inclusions.
After that, the group carried out more simulations to ascertain which triangular obstacle shape would prevent bacteria from swimming upstream. Then, using optimized triangular designs, the team created microfluidic channels that are similar to regular catheter tubes so that the team could watch the movement of E. coli bacteria under different flow circumstances.
The simulated predictions and the observed trajectories of the E. coli in these microfluidic environments matched nearly exactly.
As the researchers worked to keep refining the geometric tube design, the team’s collaboration grew. Neural operators, a cutting-edge AI technique, are provided to the project by artificial intelligence specialists at the Anandkumar laboratory.
The catheter design optimization calculations are sped up by this technology, taking only minutes instead of days. The final model suggested modifications to the geometric layout, enhancing the triangle forms’ effectiveness and preventing additional bacteria from migrating upstream. In simulations, the final design increased the effectiveness of the original triangular shapes by 5%.
A collaborative spirit defines Caltech. Caltech people help each other. This endeavor was truly an interdisciplinary journey, weaving together diverse fields of study.
Paul W. Sternberg, Study Co-Author, Division of Biology and Biological Engineering, California Institute of Technology
Zhou says, “Our journey from theory to simulation, experiment, and, finally, to real-time monitoring within these microfluidic landscapes is a compelling demonstration of how theoretical concepts can be brought to life, offering tangible solutions to real-world challenges. I'm very lucky to be at Caltech with so many talented colleagues.”
Zhou and Wan are the study’s co-first authors. In addition to Anandkumar, Brady, Sternberg, and Daraio, additional Caltech co-authors are Graduate Student Zongyi Li and Alum Zhiwei Peng (Ph.D. '22).
Daniel Zhengyu Huang of Peking University in Beijing, formerly a Postdoctoral Scholar in the laboratory of Tapio Schneider, the Theodore Y. Wu Professor of Environmental Science, and Engineering and JPL Senior Research Scientist, is also a co-author.
The research was funded by the Donna and Benjamin M. Rosen Bioengineering Center, the Heritage Medical Research Institute, the National Science Foundation, the Schmidt Futures program, the PIMCO Future Leaders Scholarship, the Amazon AI4Science Fellowship, and Bren Professorships. Stenberg and Anandkumar are affiliated faculty members with the Tianqiao and Chrissy Chen Institute for Neuroscience at Caltech.
Journal Reference:
Zhou, T., et al. (2024).AI-aided geometric design of anti-infection catheters. Science Advances. doi/10.1126/sciadv.adj1741