Newswise — New York, NY — May 9, 2023 — A few years ago, biomedical engineering researchers Professor Tal Danino’s lab learned how naturally pattern-forming bacteria could be engineered and applied. I was brainstorming about. There are many types of bacteria, such as proteus mirabilis (P. mirabilis), which self-assemble into defined patterns visible to the naked eye on solid surfaces. These bacteria are able to sense several stimuli in nature and respond to these cues by ‘crowding’. This is the highly coordinated rapid movement of bacteria driven by flagella, long tail-like structures that cause whip-like movements to propel the bacteria.
For inspiration, Danino’s team at Columbia Engineering, who has extensive experience using synthetic biology techniques to engineer bacteria, wondered where else similar patterns could be found in nature, and what their function might be. Discussed what it was. They saw how tree rings record the age and climatic history of trees, and came up with the idea of applying it. P. mirabilis Sounds as a recording system. They were also interested in applying AI to characterize distinct features of bacterial colony patterns. I realized that this approach can be used to decipher manipulated patterns.
“This seemed like an untapped opportunity to create a natural system of record for a given cue,” says Danino, a member of the Data Science Institute (DSI) at Columbia University.
A new study published on May 4 found that nature chemical biology, researchers collaborated P. mirabilis, is common in soil and water, and sometimes in the human gut, and is known for its eyeball-like colony pattern. When bacteria are grown on Petri dishes in solid growth medium, they alternate between bacterial growth phases that form visible dense circles and bacterial migration phases called ‘crowding’ movements that expand the colony outwards.
The researchers engineered the bacteria by adding what synthetic biologists call “genetic circuits,” systems of genetic parts that are logically organized to direct the bacteria to behave in a desired way. Genetically engineered bacteria sense the presence of inputs the researchers choose, from temperature to sugar molecules to heavy metals such as mercury and copper, and respond by altering their swarming abilities, producing visible output patterns. changed.
Andrew Lane, Percy K., Vida L.W. Hudson Professor of Biomedical Engineering, DSI Member, and Jia Guo, Assistant Professor of Neurobiology (Psychiatry) at Columbia University Irving Medical Center As a result, the researchers applied deep learning. – Her AI technology on the cutting edge – deciphers the environment from patterns in the same way that scientists observe the rings of tree trunks to understand the history of the environment. They developed a model that could classify patterns as a whole to predict things like sugar concentration in a sample, and a model that could delineate or “segment” edges in patterns to predict things like how many times the temperature changed during colony growth. I used a model that could .
Advantages of cooperating with P. mirabilis That is, compared to many typical artificial bacterial patterns, the native bacterial pattern is P. mirabilis Patterns are visible to the naked eye without expensive visualization techniques and are formed on a durable, easy-to-work solid agar medium. These properties increase the applicability of the system as a sensor reading in a variety of settings. Using deep learning to interpret patterns allows researchers to extract information about the concentration of input molecules from even complex patterns.
“Our goal is to develop this system as a low-cost system for detecting and recording the status of pollutants and toxic compounds in the environment,” said the lead author of the study and a recent Ph.D. said Anjali Doshi of the Danino lab. “To our knowledge, this is the first study in which a naturally patterning bacterial species has been engineered by synthetic biologists to alter its native swarming ability and function as a sensor.”
Such studies can help researchers better understand how native patterns form and can also contribute to other areas of biotechnology beyond sensors. Being able to control bacteria as a group rather than as individuals, and control their movement and organization within colonies, will help researchers build larger-scale, living materials that allow bacteria to live “smarter.” It can help therapy by allowing better control over the behavior of bacteria in the body, which may also help the Danino Lab’s parallel goal of manipulating
This study is a novel approach to construct macroscale bacterial recorders and extends the framework for engineering emergent microbial behavior. The researchers next plan to engineer the bacteria to detect a wider range of contaminants and toxins, shifting the system to safer ‘probiotic’ bacteria. Ultimately, we aim to develop a device for applying the recording system outside the laboratory.
###
About research
journal: nature chemical biology
The title of the study is “Manipulated bacterial community patterns as spatial records of environmental inputs”
Authors: Anjali Doshi 1, Marian Shaw 1, Ruxandra Tonea 1, Soonhee Moon 1, Rosalía Minyety 1, Anish Doshi 2, Andrew Laine 1, Jia Guo 3,4 & Tal Danino 1,5,61 College of Biomedical Engineering, Columbia University2 Department of Electrical Engineering and Computer Science, University of California, Berkeley3 Department of Psychiatry, Columbia University4 Mortimer B. Zuckerman Brain and Brain Behavior Institute, Columbia University5 Columbia University Herbert Irving Comprehensive Cancer Center6 Columbia University Data Science Institute
This work was supported by an NSF CAREER Award (1847356 to TD), the Blavatnik Fund for Innovations in Health (TD), and an NSF Graduate Research Fellowship (AD, Fellow ID 2018264757).
AD, MS, JG, AL, and TD are named as inventors in provisional patent applications filed with the United States Patent and Trademark Office by Columbia University relating to all aspects of this work. The remaining authors declare no competing interests.
###
Link:
Paper: https://www.nature.com/articles/s41589-023-01325-2
Doi: 10.1038/s41589-023-01325-2
###
