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Chip Identifies Bacterial Infection In Minutes, Not Days




Bacterial infections kill tens of thousands of North Americans every year. The fact it can take days to find out which bacteria are behind the infections and even longer to establish exactly which drugs will work, doesn't help. Now according to a new study, a chip that identifies bacteria in minutes promises to slash those timescales. And not only does the chip identify the specific pathogen, it can also tell which drugs it is resistant to, say researchers from the University of Toronto (U of T) in Canada.

Co-senior author Shana Kelley, of the department of Pharmacy and Biochemistry at U of T, and colleagues, write about their work in a 12 June online issue of Nature Communications.

Kelley says in a statement that drug-resistant bacteria are emerging all the time because antibiotics are either over-used or not used appropriately.

But this is not necessarily due to deliberate misuse or sloppy practice: a major factor can be the length of time it takes to find out exactly what is behind the infection and just as importantly, which drugs to treat it with.

It can be a race against time, and if time runs out, doctors have to make potentially life-saving decisions based on incomplete information.

What is missing is a "technology that rapidly offers physicians detailed information about the specific cause of the infection," says Kelley.

Electronic devices that give a simple readout, based on highly sensitive and specific diagnostic tests that use small panels of biomarkers, already exist.

But what is needed is a device that can "interrogate samples for many dozens of biomarkers," write the authors in their background information.

One of the barriers to developing such a device is how to design an inexpensive platform that can accommodate large arrays of electrode-based sensors.

With this challenge in mind, Kelley and colleagues set out to develop and test such a device.

They already knew the way to go was to use electronic chips, like the ones used for small panels of biomarkers, but somehow they needed to change the design so the chips could cope with what they describe as "highly multiplexed electrochemical sensing" in order to screen for many biomarkers at the same time.

And they found a way to do just this, using "solution-based circuits formed on chip".

They designed and tested such a chip that could detect bacteria at concentrations found in patients with a urinary infection.

"The chip reported accurately on the type of bacteria in a sample, along with whether the pathogen possessed drug resistance," say first author Brian Lam, a Chemistry PhD student at U of T.

The solution-based circuit concept allowed the chip to use the liquids in which the patient samples are immersed as a "switch", so the team could look separately for each biomarker in turn, says co-senior author Ted Sargent, from the department of Electrical and Computer Engineering at U of T.

"The solution-based circuits switch the information-carrying signal readout channels and eliminate all measurable crosstalk from adjacent, biomolecule-specific microsensors," note the authors.

"We also show that signature molecules can be accurately read 2 minutes after sample introduction," they add.

Ihor Boszko, director of a Toronto-based business that develops in vitro diagnostics tools says the team's new concept could have significant practical implications.

It will enable rapid screening for multiple viruses or bacteria that produce similar symptoms, and:

"It also allows for simple and cost effective manufacturing of highly multiplexed electrochemical detectors, which will certainly have a significant impact on the availability of effective diagnostic tools," says Boszko.

The study is a good example of the kind of innovations that can occur when experts from different fields work together: in this case computer engineers, biologists, chemists, pharmacists, and more.

In another remarkable example of interdisciplinary teamwork, a study published early 2013 in the British Journal of Cancer describes how cancer researchers and astronomers put their heads together and adapted computerized stargazing techniques developed for spotting distant galaxies to identify biomarkers in tumors to determine how aggressive they are.

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