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Direct quantitative analysis of HCV RNA by atomic force microscopy without labeling or amplification.

Jung YJ, Albrecht JA, Kwak JW, Park JW - Nucleic Acids Res. (2012)

Bottom Line: Adhesion force maps were generated with criteria including the mean force value, probability of obtaining the specific curves and hydrodynamic distance.The maps for the samples whose concentrations ranged from 0.76 fM to 6.0 fM showed that cluster number has a linear relationship with RNA concentration, while the difference between the observed number and the calculated one increased at low concentrations.Because the detection limit is expected to be enhanced by a factor of 10 000 when a spot of 1 micron diameter is employed, it is believed that HCV RNA of a few copy numbers can be detected by the use of AFM.

View Article: PubMed Central - PubMed

Affiliation: Nanogea Corporation, 6162 Bristol Parkway, Culver City, CA 90230, USA. yjung@nanogea.com

ABSTRACT
Force-based atomic force microscopy (AFM) was used to detect HCV (hepatitis C virus) RNA directly and to quantitatively analyse it without the need for reverse transcription or amplification. Capture and detection DNA probes were designed. The former was spotted onto a substrate with a conventional microarrayer, and the latter was immobilized on an AFM probe. To control the spacing between the immobilized DNAs on the surface, dendron self-assembly was employed. Force-distance curves showed that the mean force of the specific unbinding events was 32 ± 5 pN, and the hydrodynamic distance of the captured RNA was 30-60 nm. Adhesion force maps were generated with criteria including the mean force value, probability of obtaining the specific curves and hydrodynamic distance. The maps for the samples whose concentrations ranged from 0.76 fM to 6.0 fM showed that cluster number has a linear relationship with RNA concentration, while the difference between the observed number and the calculated one increased at low concentrations. Because the detection limit is expected to be enhanced by a factor of 10 000 when a spot of 1 micron diameter is employed, it is believed that HCV RNA of a few copy numbers can be detected by the use of AFM.

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Related in: MedlinePlus

Relationship between the average normalized count number and RNA concentration (copy number). A good linear correlation (r = 0.999) was noted. The open circles represent normalized values, the error bar indicates the standard deviation, and the filled squares show the averaged normalized values. The filled triangles represent the calculated count number, the value of which was consistently smaller than the observed one. The solid and broken lines are parallel.
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gks953-F5: Relationship between the average normalized count number and RNA concentration (copy number). A good linear correlation (r = 0.999) was noted. The open circles represent normalized values, the error bar indicates the standard deviation, and the filled squares show the averaged normalized values. The filled triangles represent the calculated count number, the value of which was consistently smaller than the observed one. The solid and broken lines are parallel.

Mentions: To count the captured RNAs at various concentrations, two or three microarrayed spots were examined for each concentration (6.0, 5.7, 4.3, 2.6 and 0.76 fM), and one or two maps were generated for each to consider the variation within and among spots. To minimize the variation within spots, HCV RNA adhesion force maps were recorded around the center of the spots at each measurement. Nevertheless, a certain amount of variation occurred within spots (e.g. 9 versus 6 at 4.3 fM, 6 versus 8 at 2.6 fM and 4 versus 2 at 0.76 fM). One must normalize the average cluster numbers to a standard diameter (200 µm) because a larger area yields a smaller cluster number at a fixed concentration (Table 2). The normalized values showed variation at a fixed concentration (10.1–12.5 for 6.0 fM, 10.2–10.3 for 5.7 fM, 5.2–9.8 for 4.3 fM, 3.8–6.0 for 2.6 fM and 1.5–3.0 for 0.76 fM). The average count numbers were 10.8, 10.3, 8.1, 5.4 and 2.3 at concentrations of 6.0, 5.7, 4.3, 2.6 and 0.76 fM, respectively. The relationship between average count number and RNA concentration is shown in Figure 5. The open circles represent the normalized values, the error bars indicate the standard deviation and the filled squares show the averaged normalized values. A fairly good linear correlation (r = 0.999) was observed between averaged normalized value and RNA concentration. The filled triangles represent the calculated count number, whose value was consistently smaller than the observed one. The solid and broken lines are parallel. The difference with respect to the observed values was 14% at 6.0 fM and 48% at 0.76 fM. The difference may have been due to an error in the mapping and cluster counting and/or inaccuracy in the concentration determined by reverse transcription and PCR. To understand the difference, investigating more samples of lower concentration including 0.76 fM is necessary.Figure 5.


Direct quantitative analysis of HCV RNA by atomic force microscopy without labeling or amplification.

Jung YJ, Albrecht JA, Kwak JW, Park JW - Nucleic Acids Res. (2012)

Relationship between the average normalized count number and RNA concentration (copy number). A good linear correlation (r = 0.999) was noted. The open circles represent normalized values, the error bar indicates the standard deviation, and the filled squares show the averaged normalized values. The filled triangles represent the calculated count number, the value of which was consistently smaller than the observed one. The solid and broken lines are parallel.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC3526272&req=5

gks953-F5: Relationship between the average normalized count number and RNA concentration (copy number). A good linear correlation (r = 0.999) was noted. The open circles represent normalized values, the error bar indicates the standard deviation, and the filled squares show the averaged normalized values. The filled triangles represent the calculated count number, the value of which was consistently smaller than the observed one. The solid and broken lines are parallel.
Mentions: To count the captured RNAs at various concentrations, two or three microarrayed spots were examined for each concentration (6.0, 5.7, 4.3, 2.6 and 0.76 fM), and one or two maps were generated for each to consider the variation within and among spots. To minimize the variation within spots, HCV RNA adhesion force maps were recorded around the center of the spots at each measurement. Nevertheless, a certain amount of variation occurred within spots (e.g. 9 versus 6 at 4.3 fM, 6 versus 8 at 2.6 fM and 4 versus 2 at 0.76 fM). One must normalize the average cluster numbers to a standard diameter (200 µm) because a larger area yields a smaller cluster number at a fixed concentration (Table 2). The normalized values showed variation at a fixed concentration (10.1–12.5 for 6.0 fM, 10.2–10.3 for 5.7 fM, 5.2–9.8 for 4.3 fM, 3.8–6.0 for 2.6 fM and 1.5–3.0 for 0.76 fM). The average count numbers were 10.8, 10.3, 8.1, 5.4 and 2.3 at concentrations of 6.0, 5.7, 4.3, 2.6 and 0.76 fM, respectively. The relationship between average count number and RNA concentration is shown in Figure 5. The open circles represent the normalized values, the error bars indicate the standard deviation and the filled squares show the averaged normalized values. A fairly good linear correlation (r = 0.999) was observed between averaged normalized value and RNA concentration. The filled triangles represent the calculated count number, whose value was consistently smaller than the observed one. The solid and broken lines are parallel. The difference with respect to the observed values was 14% at 6.0 fM and 48% at 0.76 fM. The difference may have been due to an error in the mapping and cluster counting and/or inaccuracy in the concentration determined by reverse transcription and PCR. To understand the difference, investigating more samples of lower concentration including 0.76 fM is necessary.Figure 5.

Bottom Line: Adhesion force maps were generated with criteria including the mean force value, probability of obtaining the specific curves and hydrodynamic distance.The maps for the samples whose concentrations ranged from 0.76 fM to 6.0 fM showed that cluster number has a linear relationship with RNA concentration, while the difference between the observed number and the calculated one increased at low concentrations.Because the detection limit is expected to be enhanced by a factor of 10 000 when a spot of 1 micron diameter is employed, it is believed that HCV RNA of a few copy numbers can be detected by the use of AFM.

View Article: PubMed Central - PubMed

Affiliation: Nanogea Corporation, 6162 Bristol Parkway, Culver City, CA 90230, USA. yjung@nanogea.com

ABSTRACT
Force-based atomic force microscopy (AFM) was used to detect HCV (hepatitis C virus) RNA directly and to quantitatively analyse it without the need for reverse transcription or amplification. Capture and detection DNA probes were designed. The former was spotted onto a substrate with a conventional microarrayer, and the latter was immobilized on an AFM probe. To control the spacing between the immobilized DNAs on the surface, dendron self-assembly was employed. Force-distance curves showed that the mean force of the specific unbinding events was 32 ± 5 pN, and the hydrodynamic distance of the captured RNA was 30-60 nm. Adhesion force maps were generated with criteria including the mean force value, probability of obtaining the specific curves and hydrodynamic distance. The maps for the samples whose concentrations ranged from 0.76 fM to 6.0 fM showed that cluster number has a linear relationship with RNA concentration, while the difference between the observed number and the calculated one increased at low concentrations. Because the detection limit is expected to be enhanced by a factor of 10 000 when a spot of 1 micron diameter is employed, it is believed that HCV RNA of a few copy numbers can be detected by the use of AFM.

Show MeSH
Related in: MedlinePlus