Forum for Science, Industry and Business

Sponsored by:     3M 
Search our Site:

 

Artificial intelligence helps detect subtle differences in mutant worms

20.08.2012
Automated worm sorter

Research into the genetic factors behind certain disease mechanisms, illness progression and response to new drugs is frequently carried out using tiny multi-cellular animals such as nematodes, fruit flies or zebra fish.

Often, progress relies on the microscopic visual examination of many individual animals to detect mutants worthy of further study.

Now, scientists have demonstrated an automated system that uses artificial intelligence and cutting-edge image processing to rapidly examine large numbers of individual Caenorhabditis elegans, a species of nematode widely used in biological research. Beyond replacing existing manual examination steps using microfluidics and automated hardware, the system's ability to detect subtle differences from worm-to-worm – without human intervention – can identify genetic mutations that might not have been detected otherwise.

By allowing thousands of worms to be examined autonomously in a fraction of the time required for conventional manual screening, the technique could change the way that high throughput genetic screening is carried out using C. elegans.

Details of the research were scheduled to be reported August 19th in the advance online publication of the journal Nature Methods. The research has been supported by the National Institutes of Health (NIH), the National Science Foundation (NSF) and the Alfred P. Sloan Foundation.

"While humans are very good at pattern recognition, computers are much better than humans at detecting subtle differences, such as small changes in the location of dots or slight variations in the brightness of an image," said Hang Lu, the project's lead researcher and an associate professor in the School of Chemical & Biomolecular Engineering at the Georgia Institute of Technology. "This technique found differences that would have been almost impossible to pick out by hand."

Lu's research team is studying genes that affect the formation and development of synapses in the worms, work that could have implications for understanding human brain development. The researchers use a model in which synapses of specific neurons are labeled by a fluorescent protein. Their research involves creating mutations in the genomes of thousands of worms and examining the resulting changes in the synapses. Mutant worms identified in this way are studied further to help understand what genes may have caused the changes in the synapses.

One aspect the researchers are studying is why synapses form in the wrong locations, or are of the wrong sizes or types. The differences between the mutants and the normal or "wild type" worms indicate inappropriate developmental patterns caused by the genetic mutations.

Because of the large number of possible genes involved in these developmental processes, the researchers must examine thousands of worms – perhaps as many as 100,000 – to exhaust the search. Lu and her research group had earlier developed a microfluidic "worm sorter" that speeds up the process of examining worms under a microscope, but until now, there were two options for detecting the mutants: a human had to look at each animal, or a simple heuristic algorithm was used to make the sorting decision. Neither option is objective or adaptable to new problems.

Lu's system, an optimized version of earlier work by her group, uses a camera to record three-dimensional images of each worm as it passes through the sorter. The system compares each image set against what it has been taught the "wild type" worms should look like. Worms that are even subtly different from normal can be sorted out for further study.

"We feed the program wild-type images, and it teaches itself to recognize what differentiates the wild type. It uses this information to determine what a mutant type may look like – which is information we didn't provide to the system – and sorts the worms based on that," explained Matthew Crane, a graduate student who performed the work. "We don't have to show the computer every possible mutant, and that is very powerful. And the computer never gets bored."

While the system was designed to sort C. elegans for a specific research project, Lu believes the machine learning technology – which is borrowed from computer science – could be applied to other areas of biology that use model genetic organisms. The system's hardware and software are currently being used in several other laboratories beyond Georgia Tech.

"Our automated technique can be generalized to anything that relies on detecting a morphometric – or shape, size or brightness difference," Lu said. "We can apply this to anything that can be detected visually, and we think this could be expanded to studying many other problems related to learning, memory, neuro-degeneration and neural developmental diseases that this worm can be used to model."

Individual C. elegans are less than a millimeter long and thinner than a strand of hair, but have 302 neurons with well-defined synapses. While research using single cells can be simpler to do, studies using the worms are good in vivo models for many important processes relevant to human health.

Other researchers who contributed to this paper include student Jeffrey Stirman from Georgia Tech's interdisciplinary program in bioengineering, Professor James Rehg from Georgia Tech's School of Interactive Computing, and three researchers from the Department of Biology at Stanford University's Howard Hughes Medical Institute: Chan-Yen Ou, Peri Kurshan, and Professor Kang Shen.

The autonomous processing facilitated by the new system could allow researchers to examine more animals more rapidly, potentially opening up areas of study that are not feasible today.

"We are hoping that the technology will really change the approach people can take to this kind of research," said Lu. "We expect that this approach will enable people to do much larger scale experiments that can push the science forward beyond looking what individual mutations are doing in a specific situation."

The project described was supported by Award Numbers R01GM088333, R21EB012803 and R01AG035317 from the National Institutes of Health. This material is also based on work supported by the National Science Foundation under Grant No. CAREER CBET-0954578. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National lnstitutes of Health or the National Science Foundation.

Citation: Matthew M Crane, Jeffrey N Stirman, Chan-Yen Ou, Peri T Kurshan, James M Rehg, Kang Shen & Hang Lu, Autonomous screening of C. elegans identifies genes implicated in synaptogenesis, DOI: 10.1038/NMETH.2141

John Toon | EurekAlert!
Further information:
http://www.gatech.edu

More articles from Life Sciences:

nachricht Two Group A Streptococcus genes linked to 'flesh-eating' bacterial infections
25.09.2017 | University of Maryland

nachricht Rainbow colors reveal cell history: Uncovering β-cell heterogeneity
22.09.2017 | DFG-Forschungszentrum für Regenerative Therapien TU Dresden

All articles from Life Sciences >>>

The most recent press releases about innovation >>>

Die letzten 5 Focus-News des innovations-reports im Überblick:

Im Focus: LaserTAB: More efficient and precise contacts thanks to human-robot collaboration

At the productronica trade fair in Munich this November, the Fraunhofer Institute for Laser Technology ILT will be presenting Laser-Based Tape-Automated Bonding, LaserTAB for short. The experts from Aachen will be demonstrating how new battery cells and power electronics can be micro-welded more efficiently and precisely than ever before thanks to new optics and robot support.

Fraunhofer ILT from Aachen relies on a clever combination of robotics and a laser scanner with new optics as well as process monitoring, which it has developed...

Im Focus: The pyrenoid is a carbon-fixing liquid droplet

Plants and algae use the enzyme Rubisco to fix carbon dioxide, removing it from the atmosphere and converting it into biomass. Algae have figured out a way to increase the efficiency of carbon fixation. They gather most of their Rubisco into a ball-shaped microcompartment called the pyrenoid, which they flood with a high local concentration of carbon dioxide. A team of scientists at Princeton University, the Carnegie Institution for Science, Stanford University and the Max Plank Institute of Biochemistry have unravelled the mysteries of how the pyrenoid is assembled. These insights can help to engineer crops that remove more carbon dioxide from the atmosphere while producing more food.

A warming planet

Im Focus: Highly precise wiring in the Cerebral Cortex

Our brains house extremely complex neuronal circuits, whose detailed structures are still largely unknown. This is especially true for the so-called cerebral cortex of mammals, where among other things vision, thoughts or spatial orientation are being computed. Here the rules by which nerve cells are connected to each other are only partly understood. A team of scientists around Moritz Helmstaedter at the Frankfiurt Max Planck Institute for Brain Research and Helene Schmidt (Humboldt University in Berlin) have now discovered a surprisingly precise nerve cell connectivity pattern in the part of the cerebral cortex that is responsible for orienting the individual animal or human in space.

The researchers report online in Nature (Schmidt et al., 2017. Axonal synapse sorting in medial entorhinal cortex, DOI: 10.1038/nature24005) that synapses in...

Im Focus: Tiny lasers from a gallery of whispers

New technique promises tunable laser devices

Whispering gallery mode (WGM) resonators are used to make tiny micro-lasers, sensors, switches, routers and other devices. These tiny structures rely on a...

Im Focus: Ultrafast snapshots of relaxing electrons in solids

Using ultrafast flashes of laser and x-ray radiation, scientists at the Max Planck Institute of Quantum Optics (Garching, Germany) took snapshots of the briefest electron motion inside a solid material to date. The electron motion lasted only 750 billionths of the billionth of a second before it fainted, setting a new record of human capability to capture ultrafast processes inside solids!

When x-rays shine onto solid materials or large molecules, an electron is pushed away from its original place near the nucleus of the atom, leaving a hole...

All Focus news of the innovation-report >>>

Anzeige

Anzeige

Event News

“Lasers in Composites Symposium” in Aachen – from Science to Application

19.09.2017 | Event News

I-ESA 2018 – Call for Papers

12.09.2017 | Event News

EMBO at Basel Life, a new conference on current and emerging life science research

06.09.2017 | Event News

 
Latest News

An international team of physicists a coherent amplification effect in laser excited dielectrics

25.09.2017 | Physics and Astronomy

LaserTAB: More efficient and precise contacts thanks to human-robot collaboration

25.09.2017 | Trade Fair News

Highest-energy cosmic rays have extragalactic origin

25.09.2017 | Physics and Astronomy

VideoLinks
B2B-VideoLinks
More VideoLinks >>>