(Nanowerk News) Researchers have demonstrated significant improvements for chip-based sensing devices used to detect or analyze substances. The achievement lays the foundation for highly sensitive integrated portable optofluid sensing devices that can be used to simultaneously perform different types of medical tests even when involving completely different types of bioparticles — such as virus and DNA particles — at widely varying concentrations.
As reported in OPTICAL (“Adaptive time modulation technique for multiplex on-chip particle detection across scales”), researchers led by Holger Schmidt of the WM Keck Center for Nanoscale Optofluidics at the University of California, Santa Cruz (UCSC), applied a new signal processing technique to an optofluid chip-based biosensor. This advancement enables seamless fluorescence detection of blended nanobeads in concentrations across eight times the order, from attomolar to nanomolar. This widens the range of concentrations over which these sensors can work by a factor of over 10,000.
“This work is our latest step in developing an integrated optofluid sensing device that is sensitive enough to detect single biomolecules and acts over a very wide range of concentrations,” said Schmidt. “We have shown that this can be done with a single method, which allows us to simultaneously measure and differentiate several types of particles at once even if they have very different concentrations.”
Create multi-purpose test kits
Although many types of chip-based assay kits have been developed, most focus on a single target or type of assay because biomolecules come in very different shapes and quantities. For example, the concentrations of various proteins used as disease biomarkers can vary by more than tenfold.
Schmidt’s group, in collaboration with Aaron Hawkins at Brigham Young University, are working to develop a test platform that can be used for many types of analysis. It is based on an optofluidic chip, which combines optical and microfluidic channels on a silicon or plastic chip. Particles are detected by irradiating them with a laser beam and then measuring the response of the particles with a light-sensitive detector.
The researchers have previously shown that their platform has the sensitivity needed to perform many types of analysis and can detect many types of particles, including nucleic acids, proteins, viruses, bacteria, and cancer biomarkers. However, until now, they have used separate detectors and signal analysis techniques to measure high and low concentrations of particles. This is necessary because if one type of particle type is present at very high concentrations, it creates a very large response that overpowers a much smaller signal than the other type of particles present at low concentrations.
Better signal processing
In the new work, Schmidt and graduate student Vahid Ganjalizadeh developed a signal processing method that can be used to simultaneously detect particles in high and low concentrations, even if their concentrations are not known in advance. To do this, they combined different signal modulation frequencies: High-frequency laser modulation to distinguish single particles at low concentrations and low-frequency laser modulation to detect large signals from multiple particles simultaneously at high concentrations.
“Second, we implemented a feedback loop that detects when the signal is very large and adjusts the input laser power accordingly,” says Schmidt. “In this way, we can detect large signals from high concentrations without overwhelming the weak signals that might be present from other species at low concentrations. This allows us to simultaneously detect particles that are present in very different concentrations.”
The researchers also applied a very fast algorithm they recently developed to identify single particle signals at low concentrations in real time. Machine learning also helps recognize signal patterns so that different types of particles can be distinguished with high accuracy. “This signal analysis advancement is ideal for enabling device operation in point of care where signal quality can be poor and where data analysis is required in real time,” said Schmidt.
Distinguish between low and high concentrations
The researchers demonstrated their new signal analysis approach by pumping an optofluid biosensor chip with solutions of nanobeads at different concentrations and with different fluorescence colors. They were able to correctly identify the concentrations of the yellow-green and red beads even though their concentrations differed by a factor of more than 10,000 in the mixture.
“While this work advances custom integrated sensors based on optical fluorescence signals, the signal analysis technique can be used with all kinds of time-dependent signals covering a wide range of concentrations,” said Schmidt. “This can include different optical signals but also electrical sensors.”
The team’s optofluid biosensing technology is currently being commercialized by medical device company Fluxus Inc. The researchers are also working to adapt their method to study the molecular products of artificial neural cell tissue organoids. This project, which is part of the UCSC Center for Live Cell Genomics, an NIH Center for Excellence in Genomic Science, could provide further insight into areas such as neurogenerative diseases and pediatric cancer.