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Label-free biomarker detection from whole blood.

Stern E, Vacic A, Rajan NK, Criscione JM, Park J, Ilic BR, Mooney DJ, Reed MA, Fahmy TM - Nat Nanotechnol (2009)

Bottom Line: However, detecting these biomarkers in physiological fluid samples is difficult because of problems such as biofouling and non-specific binding, and the resulting need to use purified buffers greatly reduces the clinical relevance of these sensors.This two-stage approach isolates the detector from the complex environment of whole blood, and reduces its minimum required sensitivity by effectively pre-concentrating the biomarkers.This study marks the first use of label-free nanosensors with physiological solutions, positioning this technology for rapid translation to clinical settings.

View Article: PubMed Central - PubMed

Affiliation: Department of Biomedical Engineering, School of Engineering and Applied Science, Yale University, New Haven, Connecticut 06511, USA.

ABSTRACT
Label-free nanosensors can detect disease markers to provide point-of-care diagnosis that is low-cost, rapid, specific and sensitive. However, detecting these biomarkers in physiological fluid samples is difficult because of problems such as biofouling and non-specific binding, and the resulting need to use purified buffers greatly reduces the clinical relevance of these sensors. Here, we overcome this limitation by using distinct components within the sensor to perform purification and detection. A microfluidic purification chip simultaneously captures multiple biomarkers from blood samples and releases them, after washing, into purified buffer for sensing by a silicon nanoribbon detector. This two-stage approach isolates the detector from the complex environment of whole blood, and reduces its minimum required sensitivity by effectively pre-concentrating the biomarkers. We show specific and quantitative detection of two model cancer antigens from a 10 microl sample of whole blood in less than 20 min. This study marks the first use of label-free nanosensors with physiological solutions, positioning this technology for rapid translation to clinical settings.

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Label-free sensingAll sensing measurements were performed at VDS = 1V and VG = -5V and all sample introductions occurred at time = 0. Normalizations were performed by dividing device currents by the pre-addition (time < 0) current level average. a, Response of an anti-PSA functionalized sensor to a MPC-purified blood sample initially containing 2.5 ng/mL PSA (and also 30 U/mL CA15.3), or a control sample containing neither. b, Response of an anti-CA15.3 functionalized sensor to a MPC-purified blood sample blood sample initially containing 30 U/mL CA15.3 (and also 2.5 ng/mL PSA), or a control sample containing neither. c, Normalized response of two anti-PSA and d, two anti-CA15.3 functionalized devices to MPC-purified blood containing both PSA and CA 15.3, with concentrations labeled. A least squares fit is represented by a solid black line, over the selected region (line endpoints). The ratio of the the normalized slopes calibrates the ratio of concentrations.
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Figure 4: Label-free sensingAll sensing measurements were performed at VDS = 1V and VG = -5V and all sample introductions occurred at time = 0. Normalizations were performed by dividing device currents by the pre-addition (time < 0) current level average. a, Response of an anti-PSA functionalized sensor to a MPC-purified blood sample initially containing 2.5 ng/mL PSA (and also 30 U/mL CA15.3), or a control sample containing neither. b, Response of an anti-CA15.3 functionalized sensor to a MPC-purified blood sample blood sample initially containing 30 U/mL CA15.3 (and also 2.5 ng/mL PSA), or a control sample containing neither. c, Normalized response of two anti-PSA and d, two anti-CA15.3 functionalized devices to MPC-purified blood containing both PSA and CA 15.3, with concentrations labeled. A least squares fit is represented by a solid black line, over the selected region (line endpoints). The ratio of the the normalized slopes calibrates the ratio of concentrations.

Mentions: Next, we applied these devices to sensing the biomarkers from the MPC-purified whole blood samples. The normalized responses of these same devices to MPC-purified, antigen-spiked blood samples containing both 2.5 ng/mL PSA and 30 U/mL CA15.3 (as well as negative controls) are shown in Fig. 4a and 4b, respectively. After the injection transient noise subsides11, device current levels were increased by antigen binding due to the negative charge conferred to the antigens by the basic sensing buffer. Similar signals were obtained with a PSA/CA15.3 spiked sensing buffer positive control, and no device response was observed with an unspiked, MPC-purified blood negative control. To reduce potential transient electrical signals upon injection, buffer salt concentrations of the functionalized devices and the MPC-purifies samples are kept the same. The positive signal is observed to increase linearly in time, following well-known ligand-receptor kinetics,29 in which initial rates at low relative analyte concentrations are directly proportional to the species concentration30. In fact, the asymptotic saturation value of the device response is weakly dependent on the concentration for reversible reactions with a low dissociation constant29 which is the case for the antigen-antibody interactions. Thus, we focus on the initial kinetic reaction rates instead of endpoint detection30.


Label-free biomarker detection from whole blood.

Stern E, Vacic A, Rajan NK, Criscione JM, Park J, Ilic BR, Mooney DJ, Reed MA, Fahmy TM - Nat Nanotechnol (2009)

Label-free sensingAll sensing measurements were performed at VDS = 1V and VG = -5V and all sample introductions occurred at time = 0. Normalizations were performed by dividing device currents by the pre-addition (time < 0) current level average. a, Response of an anti-PSA functionalized sensor to a MPC-purified blood sample initially containing 2.5 ng/mL PSA (and also 30 U/mL CA15.3), or a control sample containing neither. b, Response of an anti-CA15.3 functionalized sensor to a MPC-purified blood sample blood sample initially containing 30 U/mL CA15.3 (and also 2.5 ng/mL PSA), or a control sample containing neither. c, Normalized response of two anti-PSA and d, two anti-CA15.3 functionalized devices to MPC-purified blood containing both PSA and CA 15.3, with concentrations labeled. A least squares fit is represented by a solid black line, over the selected region (line endpoints). The ratio of the the normalized slopes calibrates the ratio of concentrations.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2818341&req=5

Figure 4: Label-free sensingAll sensing measurements were performed at VDS = 1V and VG = -5V and all sample introductions occurred at time = 0. Normalizations were performed by dividing device currents by the pre-addition (time < 0) current level average. a, Response of an anti-PSA functionalized sensor to a MPC-purified blood sample initially containing 2.5 ng/mL PSA (and also 30 U/mL CA15.3), or a control sample containing neither. b, Response of an anti-CA15.3 functionalized sensor to a MPC-purified blood sample blood sample initially containing 30 U/mL CA15.3 (and also 2.5 ng/mL PSA), or a control sample containing neither. c, Normalized response of two anti-PSA and d, two anti-CA15.3 functionalized devices to MPC-purified blood containing both PSA and CA 15.3, with concentrations labeled. A least squares fit is represented by a solid black line, over the selected region (line endpoints). The ratio of the the normalized slopes calibrates the ratio of concentrations.
Mentions: Next, we applied these devices to sensing the biomarkers from the MPC-purified whole blood samples. The normalized responses of these same devices to MPC-purified, antigen-spiked blood samples containing both 2.5 ng/mL PSA and 30 U/mL CA15.3 (as well as negative controls) are shown in Fig. 4a and 4b, respectively. After the injection transient noise subsides11, device current levels were increased by antigen binding due to the negative charge conferred to the antigens by the basic sensing buffer. Similar signals were obtained with a PSA/CA15.3 spiked sensing buffer positive control, and no device response was observed with an unspiked, MPC-purified blood negative control. To reduce potential transient electrical signals upon injection, buffer salt concentrations of the functionalized devices and the MPC-purifies samples are kept the same. The positive signal is observed to increase linearly in time, following well-known ligand-receptor kinetics,29 in which initial rates at low relative analyte concentrations are directly proportional to the species concentration30. In fact, the asymptotic saturation value of the device response is weakly dependent on the concentration for reversible reactions with a low dissociation constant29 which is the case for the antigen-antibody interactions. Thus, we focus on the initial kinetic reaction rates instead of endpoint detection30.

Bottom Line: However, detecting these biomarkers in physiological fluid samples is difficult because of problems such as biofouling and non-specific binding, and the resulting need to use purified buffers greatly reduces the clinical relevance of these sensors.This two-stage approach isolates the detector from the complex environment of whole blood, and reduces its minimum required sensitivity by effectively pre-concentrating the biomarkers.This study marks the first use of label-free nanosensors with physiological solutions, positioning this technology for rapid translation to clinical settings.

View Article: PubMed Central - PubMed

Affiliation: Department of Biomedical Engineering, School of Engineering and Applied Science, Yale University, New Haven, Connecticut 06511, USA.

ABSTRACT
Label-free nanosensors can detect disease markers to provide point-of-care diagnosis that is low-cost, rapid, specific and sensitive. However, detecting these biomarkers in physiological fluid samples is difficult because of problems such as biofouling and non-specific binding, and the resulting need to use purified buffers greatly reduces the clinical relevance of these sensors. Here, we overcome this limitation by using distinct components within the sensor to perform purification and detection. A microfluidic purification chip simultaneously captures multiple biomarkers from blood samples and releases them, after washing, into purified buffer for sensing by a silicon nanoribbon detector. This two-stage approach isolates the detector from the complex environment of whole blood, and reduces its minimum required sensitivity by effectively pre-concentrating the biomarkers. We show specific and quantitative detection of two model cancer antigens from a 10 microl sample of whole blood in less than 20 min. This study marks the first use of label-free nanosensors with physiological solutions, positioning this technology for rapid translation to clinical settings.

Show MeSH
Related in: MedlinePlus