Multispectral image analysis of binary encoded microspheres for highly multiplexed suspension arrays

Abstract

To push the 100-plex envelope of suspension array technology, we have developed fully automated methods to acquire multispectral images of multiplexed quantum-dot (QD) encoded microspheres, to segment them in the images, to classify them based on their color code, and to quantify the multiplexed assays. Instead of coding microspheres with two colors and n levels, microspheres were coded with n colors and two levels (present or absent), thus transforming the classification problem from analog to digital. Images of multiplexed microspheres, sedimented at the bottom of microwells, were acquired through a tunable filter at the peak luminescence wavelength of each QD coding species in the system and the assay label wavelength. Another image of the light scattered from microspheres was captured in the excitation bandwidth that was utilized to localize microspheres in multispectral luminescence images. Objects in the acquired images are segmented and luminescence from each identified microsphere in each channel is recorded, based on which the "color code" of each microsphere is determined by applying a mathematical model and a classification algorithm. Our image analysis procedures could identify and classify microspheres with more than 97% accuracy, and the assay CVs were under 20%. These proof-of-principle results demonstrate that highly multiplexed quantification of specific proteins is possible with this rapid, small-sample volume format.

Keywords: image analysis; imaging cytometry; imaging-based systems; microscopy; microsphere-based arrays; multiplexed assays; quantum dots; suspension arrays.

Figure 1

a) Microsphere zones defined by watershed crestlines by applying watershed-based segmentation algorithm to SLI at 455nm; b) identification and localization of microspheres in a fluorescent image (at 575nm) by superimposing watershed crestlines identified in a), followed by zone-specific grayscale thresholding and area filtering

Figure 2

Scatter plots explaining the rationale for utilizing r values instead of IPAT values to perform classification on assayed microspheres: a) and b) show scatter plots between IPAT values observed in 525nm and 575nm detection channels for classes 0000-1000 and *0000-1000, respectively; c) and d) represent r_QD525 vs. r_QD575 scatter plots for classes 0000-1000 and *0000-1000, respectively. Labeling with QD497 (*) brings the 0000 cluster lie very close to and overlap with 1000 cluster in scatter plots in IPAT space lowering the classification efficiency; however in r space *0000 and 1000 clusters remain well demarcated and classification efficiency is high. 0000 and *0000 clusters are marked with ‘×’, and 1000 clusters are marked with ‘+’.

Figure 3

r_QD497 distributions for a) 0001 and, b) *0001 calibrator sets. r_QD497 distribution for 0001 was used to set 0.1 as upper threshold (marked by --- in histogram for 0001) on r_QD497 for untagged microspheres.

Figure 4

r_QD497 distributions for microspheres from classes a) *0001 and, b) 1001, as identified by our classification algorithm, in the assay mixture. Mean r_QD497 values for *0001 and 1001 microspheres were close to the expected values and thus, underscored the capability of our 4-channel classification to correctly classify microspheres and to correctly quantify the capture target on them. Also, r_QD497 values have low variability emphasizing accuracy of our analysis procedures.

Figure 5

Standard curve (model fitted as four-parameter logistic using SoftMax Pro v. 5.2) for QD497-tagged biotin was generated via microsphere-based immunoassay. Data was generated from standard dilutions at concentrations 592, 296, 148, 74, 37, 18.5, 9.25, 4.63, 2.31 and 1.16nM using duplicates for each concentration. Error bars denote the standard deviation between duplicates. Based on r_QD497 = 0.1 as upper threshold for untagged microspheres (see Figure 3), marked by ‘---’, we observed that the lowest limit of detection for our SAv-Biotin assay system is ~ 4.63nM. For the generation of curve, microspheres from class 0001 were used for tagging with biotin-QD497.