From The Swiss Federal Institute of Technology in Lausanne [EPFL-École Polytechnique Fédérale de Lausanne] (CH): “Intelligent microscopes for detecting rare biological events”
9.11.22
EPFL biophysicists have developed control software that optimizes how fluorescence microscopes collect data on living samples. Their control loop, used to image mitochondrial and bacterial sites of division in detail, is released as an open source plug-in and could inspire a new generation of intelligent microscopes.
Imagine you’re a PhD student with a fluorescent microscope and a sample of live bacteria. What’s the best way use these resources to obtain detailed observations of bacterial division from the sample?
You may be tempted to forgo food and rest, to sit at the microscope non-stop and acquire images when bacterial finally division starts. (It can take hours for one bacterium to divide!) It’s not as crazy as it sounds, since manual detection and acquisition control is widespread in many of the sciences.
Alternatively, you may want to set the microscope to take images indiscriminately and as often as possible. But excessive light depletes the fluorescence from the sample faster and can prematurely destroy living samples. Plus, you’d generate many uninteresting images, since only a few would contain images of dividing bacteria.
Another solution would be to use artificial intelligence to detect precursors to bacterial division and use these to automatically update the microscope’s control software to take more pictures of the event.
Drum roll… yes, EPFL biophysicists have indeed found a way to automate microscope control for imaging biological events in detail while limiting stress on the sample, all with the help of artificial neural networks. Their technique works for bacterial cell division, and for mitochondrial division. The details of their intelligent microscope are described in Nature Methods [below].
“An intelligent microscope is kind of like a self-driving car. It needs to process certain types of information, subtle patterns that it then responds to by changing its behavior,” explains principal investigator Suliana Manley of EPFL’s Laboratory of Experimental Biophysics. “By using a neural network, we can detect much more subtle events and use them to drive changes in acquisition speed.”
Suliana Manley in one of the labs of EPFL’s Laboratory of Experimental Biophysics. © 2022 EPFL / Hillary Sanctuary.
Manley and her colleagues first solved how to detect mitochondrial division, more difficult than for bacteria such as C. crescentus. Mitochondrial division is unpredictable, since it occurs infrequently, and can happen almost anywhere within the mitochondrial network at any moment. But the scientists solved the problem by training the neural network to look out for mitochondrial constrictions, a change in shape of mitochondria that leads to division, combined with observations of a protein known to be enriched at sites of division.
When both constrictions and protein levels are high, the microscope switches into high-speed imaging to capture many images of division events in detail. When constriction and protein levels are low, the microscope then switches to low-speed imaging to avoid exposing the sample to excessive light.
One of Manley’s fluorescence microscopes. © Hillary Sanctuary 2022/EPFL.
With this intelligent fluorescent microscope, the scientists showed that they could observe the sample for longer compared to standard fast imaging. While the sample was more stressed compared to standard slow imaging, they were able to obtain more meaningful data.
“The potential of intelligent microscopy includes measuring what standard acquisitions would miss,” Manley explains. “We capture more events, measure smaller constrictions, and can follow each division in greater detail.”
The scientists are making the control framework available as an open source plug-in for the open microscope software Micro-Manager, with the aim of allowing other scientists to integrate artificial intelligence into their own microscopes.
Artboard by Willi Stepp © 2022 EPFL.
© Hillary Sanctuary 2022/EPFL.
Science paper:
Nature Methods
See the full article here .
five-ways-keep-your-child-safe-school-shootings
Please help promote STEM in your local schools.
The Swiss Federal Institute of Technology in Lausanne [EPFL-École Polytechnique Fédérale de Lausanne] (CH) is a research institute and university in Lausanne, Switzerland, that specializes in natural sciences and engineering. It is one of the two Swiss Federal Institutes of Technology, and it has three main missions: education, research and technology transfer.
The QS World University Rankings ranks EPFL(CH) 14th in the world across all fields in their 2020/2021 ranking, whereas Times Higher Education World University Rankings ranks EPFL(CH) as the world’s 19th best school for Engineering and Technology in 2020.
EPFL(CH) is located in the French-speaking part of Switzerland; the sister institution in the German-speaking part of Switzerland is The Swiss Federal Institute of Technology ETH Zürich [Eidgenössische Technische Hochschule Zürich] (CH). Associated with several specialized research institutes, the two universities form The Domain of the Swiss Federal Institutes of Technology (ETH Domain) [ETH-Bereich; Domaine des Écoles Polytechniques Fédérales] (CH) which is directly dependent on the Federal Department of Economic Affairs, Education and Research. In connection with research and teaching activities, EPFL(CH) operates a nuclear reactor CROCUS; a Tokamak Fusion reactor; a Blue Gene/Q Supercomputer; and P3 bio-hazard facilities.
ETH Zürich, EPFL (Swiss Federal Institute of Technology in Lausanne) [École Polytechnique Fédérale de Lausanne](CH), and four associated research institutes form The Domain of the Swiss Federal Institutes of Technology (ETH Domain) [ETH-Bereich; Domaine des Écoles polytechniques fédérales] (CH) with the aim of collaborating on scientific projects.
The roots of modern-day EPFL(CH) can be traced back to the foundation of a private school under the name École Spéciale de Lausanne in 1853 at the initiative of Lois Rivier, a graduate of the École Centrale Paris (FR) and John Gay the then professor and rector of the Académie de Lausanne. At its inception it had only 11 students and the offices were located at Rue du Valentin in Lausanne. In 1869, it became the technical department of the public Académie de Lausanne. When the Académie was reorganized and acquired the status of a university in 1890, the technical faculty changed its name to École d’Ingénieurs de l’Université de Lausanne. In 1946, it was renamed the École polytechnique de l’Université de Lausanne (EPUL). In 1969, the EPUL was separated from the rest of the University of Lausanne and became a federal institute under its current name. EPFL(CH), like ETH Zürich (CH), is thus directly controlled by the Swiss federal government. In contrast, all other universities in Switzerland are controlled by their respective cantonal governments. Following the nomination of Patrick Aebischer as president in 2000, EPFL(CH) has started to develop into the field of life sciences. It absorbed the Swiss Institute for Experimental Cancer Research (ISREC) in 2008.
In 1946, there were 360 students. In 1969, EPFL(CH) had 1,400 students and 55 professors. In the past two decades the university has grown rapidly and as of 2012 roughly 14,000 people study or work on campus, about 9,300 of these being Bachelor, Master or PhD students. The environment at modern day EPFL(CH) is highly international with the school attracting students and researchers from all over the world. More than 125 countries are represented on the campus and the university has two official languages, French and English.
Organization
EPFL is organized into eight schools, themselves formed of institutes that group research units (laboratories or chairs) around common themes:
School of Basic Sciences
Institute of Mathematics
Institute of Chemical Sciences and Engineering
Institute of Physics
European Centre of Atomic and Molecular Computations
Bernoulli Center
Biomedical Imaging Research Center
Interdisciplinary Center for Electron Microscopy
MPG-EPFL Centre for Molecular Nanosciences and Technology
Swiss Plasma Center
Laboratory of Astrophysics
School of Engineering
Institute of Electrical Engineering
Institute of Mechanical Engineering
Institute of Materials
Institute of Microengineering
Institute of Bioengineering
School of Architecture, Civil and Environmental Engineering
Institute of Architecture
Civil Engineering Institute
Institute of Urban and Regional Sciences
Environmental Engineering Institute
School of Computer and Communication Sciences
Algorithms & Theoretical Computer Science
Artificial Intelligence & Machine Learning
Computational Biology
Computer Architecture & Integrated Systems
Data Management & Information Retrieval
Graphics & Vision
Human-Computer Interaction
Information & Communication Theory
Networking
Programming Languages & Formal Methods
Security & Cryptography
Signal & Image Processing
Systems
School of Life Sciences
Bachelor-Master Teaching Section in Life Sciences and Technologies
Brain Mind Institute
Institute of Bioengineering
Swiss Institute for Experimental Cancer Research
Global Health Institute
Ten Technology Platforms & Core Facilities (PTECH)
Center for Phenogenomics
NCCR Synaptic Bases of Mental Diseases
College of Management of Technology
Swiss Finance Institute at EPFL
Section of Management of Technology and Entrepreneurship
Institute of Technology and Public Policy
Institute of Management of Technology and Entrepreneurship
Section of Financial Engineering
College of Humanities
Human and social sciences teaching program
EPFL Middle East
Section of Energy Management and Sustainability
In addition to the eight schools there are seven closely related institutions
Swiss Cancer Centre
Center for Biomedical Imaging (CIBM)
Centre for Advanced Modelling Science (CADMOS)
École Cantonale d’art de Lausanne (ECAL)
Campus Biotech
Wyss Center for Bio- and Neuro-engineering
Swiss National Supercomputing Centre
sciencesprings 
Reply