PARTICLE CHARACTERIZATION USING OPTICAL MICROSCOPY
20220012456 · 2022-01-13
Assignee
Inventors
- Tuomas Pertti Jonathan Knowles (Cambridge, GB)
- Pavan Kumar Challa (Cambridge, GB)
- Kadi Liis Saar (Cambridge, GB)
- Quentin Alexis Peter (Cambridge, GB)
- Clemens Kaminski (Cambridge, GB)
- Oliver Vanderpoorten (Cambridge, GB)
Cpc classification
G02B21/0016
PHYSICS
G02B21/008
PHYSICS
International classification
Abstract
A method of optically characterizing individual molecules/molecular complexes, or other particles, in solution. The method comprises flowing a solution comprising the molecules/molecular complexes into an imaging region of a microfluidic channel, wherein the imaging region of the microfluidic channel has a first lateral dimension of greater than 1 μm in an x-direction wherein the x-direction is perpendicular to a direction of the flow; capturing a succession of images of the individual molecules/molecular complexes in the imaging region; tracking movement of the individual molecules/molecular complexes in at least the x-direction in the imaging region using the succession of images; and characterizing the individual molecules/molecular complexes from the tracked movement. In some implementations the characterizing comprises determining a diffusion coefficient of the molecules/molecular complexes from the tracked movement.
Claims
1. A method of optically characterizing individual molecules/molecular complexes in solution, the method comprising: flowing a solution comprising the molecules/molecular complexes into an imaging region of a microfluidic channel, wherein the imaging region of the microfluidic channel has a first lateral dimension of greater than 1 μm in an x-direction wherein the x-direction is perpendicular to a direction of the flow; capturing a succession of images of the individual molecules/molecular complexes in the imaging region; tracking movement of the individual molecules/molecular complexes in at least the x-direction in the imaging region using the succession of images; characterizing the individual molecules/molecular complexes from the tracked movement.
2. A method as claimed in claim 1 wherein the characterizing comprises determining a diffusion coefficient of the molecules/molecular complexes from the tracked movement.
3. A method as claimed in claim 1 wherein the tracking further comprises tracking movement of the molecules/molecular complexes in a y-direction along the direction of the flow, and generating an approximately flat flow profile for the flowing solution in the x-direction.
4. A method as claimed in claim 3 wherein generating the approximately flat flow profile comprises flowing the solution using electro-osmosis.
5. A method as claimed in claim 1 comprising flowing the solution into a manifold, and flowing the solution from the manifold into a plurality of the imaging regions in a respective plurality of the microfluidic channels coupled to the manifold.
6. A method as claimed in claim 3 wherein the microfluidic channels coupled to the manifold are blind microfluidic channels.
7. A method as claimed in claim 1 wherein the microfluidic channel has an outlet, and wherein the tracking of movement of the molecules/molecular complexes is performed whilst the solution is flowing through the microfluidic channel.
8. A method as claimed in claim 1 wherein capturing the succession of images comprises capturing the images using interferometric scattering optical microscopy.
9. A method as claimed in claim 8 wherein the imaging region has a light-reflecting interface, and wherein capturing the images using interferometric scattering optical microscopy comprises, for each image, illuminating a molecule/molecular complex in the imaging region with coherent light using an objective lens such that the light is reflected from the interface and scattered by the molecule/molecular complex; capturing the reflected light and the scattered light using the objective lens; and providing the captured reflected and scattered light to an imaging device to image interference between the reflected light and the scattered light.
10. A method as claimed in claim 8 further comprising restricting movement of the molecules/molecular complexes in a z-direction in the imaging region, wherein the z-direction is a lateral direction perpendicular to the x-direction, wherein the restricting comprises limiting movement of the molecules/molecular complexes in the z-direction to a distance of less than 2λ, 3/2λ, λ, or
11. A method as claimed in claim 8 wherein capturing the succession of images comprises, for each of the images of the succession of images, capturing a sequence of interference images, wherein an interference images comprises an image of interference generated by light scattered by the molecules/molecular complexes, and processing the sequence of interference images to provide the image of the succession of images.
12. A method as claimed in claim 11 wherein processing the sequence of interference images comprises determining a location map image representing a map of one or both of intensity maxima and intensity minima across the sequence of interference images.
13. A method as claimed in claim 12 wherein processing the sequence of interference images further comprises low-pass filtering the location map image.
14. A method as claimed in claim 8 further comprising determining a mass of an individual molecule/molecular complex from one or more images captured using the interferometric scattering optical microscopy.
15. A method as claimed in claim 14 wherein the characterizing comprises determining a ratio of the mass to a size of the individual molecule/molecular complex.
16. A method as claimed in claim 1 wherein capturing the succession of images comprises capturing the images using an interferometric scattering optical microscope, and wherein a focus of the interferometric scattering optical microscope is set away from an edge of the microfluidic channel in a z-direction perpendicular to the x-direction.
17. A method as claimed in claim 1 wherein the molecules/molecular complexes comprises a biological molecules/complexes, and wherein the solution comprises an aqueous solution.
18. A system for optically characterizing individual molecules/molecular complexes in solution, the system comprising: a microfluidic channel having an imaging region, wherein the imaging region of the microfluidic channel has a first lateral dimension of greater than 1 μm in an x-direction, wherein the x-direction is perpendicular to a direction of flow in the imaging region of the microfluidic channel; a drive system to flow a solution comprising the molecules/molecular complexes into the imaging region; an optical image capture system to capture a succession of images of the individual molecules/molecular complexes in the imaging region; a processor to track movement of the individual molecules/molecular complexes in at least the x-direction in the imaging region using the succession of images and to determine data characterizing the individual molecules/molecular complexes from the tracked movement.
19. A system as claimed in claim 18 comprising a microfluidic manifold and plurality of the microfluidic channels coupled to the microfluidic manifold each with a respective imaging region; and wherein the drive system comprises an electro-osmotic drive system.
20. A system as claimed in claim 18 wherein the imaging region has a light-reflecting interface, and wherein the optical image capture system comprises an interferometric scattering optical microscope, the microscope comprising: a source of coherent light; an objective lens to direct the coherent light to illuminate the imaging region such that the light is reflected from the interface and scattered by a molecule/molecular complex in the imaging region, wherein the objective lens is configured to capture the reflected light and the scattered light; and an imaging device configured to image interference between the reflected light and the scattered light.
21.-22. (canceled)
Description
DRAWINGS
[0030] These and other aspects of the system will now be further described by way of example only, with reference to the accompanying figures, in which:
[0031]
[0032]
[0033]
[0034]
[0035]
[0036] In the figures like elements are indicated by like reference numerals.
DESCRIPTION
[0037] Referring to
[0038] The objective lens 112, which may be an oil immersion objective, focusses the illumination on a detection region 114. In the example of
[0039] The illumination is reflected from a reflecting interface 122, e.g. between the lower surface 116a of the chamber/channel 116 and the solution 118. The illumination is also scattered by the particle(s) 120. Both the reflected light and the scattered light is captured by objective lens 112, passed back along the optical path of the illumination, and directed into a separate path 124, in this example by a beam splitter 126. The reflected light and scattered light is then imaged. For example the reflected light and scattered light is focused onto an image sensor 130 by imaging optics such as a lens 128. The image sensor (camera) may be, for example a CMOS image sensor or an EMCCD image sensor; it may have a frame rate sufficient to capture and track movement of an imaged particle as described later.
[0040] In some implementations the beam splitter 126 may be replaced by e.g. a filter cube to collect fluorescence.
[0041]
[0042] The system includes a set of microfluidic channels 210 coupled to an inlet manifold 214. Each channel has a respective imaging region 212, also shown in cross-section in
[0043] The manifold 214 has a fluid inlet 220 and, optionally, a fluid outlet 222 (via the outlet manifold in the inset). Solution is driven into the inlet and may pass out through the outlet. Where the channels are blind channels they can nonetheless be filed with solution as air can diffuse out through the walls and ends of the microfluidic channels. The solution is driven by a fluid drive system 224, schematically illustrated by a syringe pump. However for such a fluid drive the flow speed profile across the lateral width of a channel is parabolic, decreasing towards the edges of the channel. In some implementations, therefore, an electro-osmotic drive system is employed not shown), which has a more uniform flow profile until very close to the channel edges. Such an electro-osmotic drive system may comprise a high voltage DC power supply with a first polarity (anode) terminal electrically coupled to the solution at one end (e.g. upstream) of the set of microfluidic channels and a second polarity (cathode) terminal electrically coupled to the solution at another end (e.g. downstream) of the set of microfluidic channels.
[0044] In an example implementation the microfluidic channels and manifold(s) may be formed in a polymer 218, such as PDMS. The channels may be formed using the standard soft lithography techniques for microfluidics, for example with a replica mould. Where the resist is spin coated the lower profile structures may be fabricated first. The replica mould may be used to fabricate a PDMS-based microfluidic structure, which may be sealed with glass e.g. a coverslip.
[0045] The use of restricted height channels limits motion of the images particles in the z-direction, reducing the risk that a particle becomes difficult to track by disappearing at one location (due to destructive interference) and reappearing at another, different location. There is also substantially no convection in such channels, so that the observed particle motion is governed by diffusion. The observed diffusion is in the x- and y-directions and constrained (on long time scales) in the z-direction; it may be observed in either 1D or 2D, depending upon the imaging system/sensor employed.
[0046]
[0047] As shown in
[0048]
[0049] Starting at step S400 the procedure processes the raw interference images from the iSCAT microscope to determine images for use in particle motion tracking. In some implementations these raw images are part of a video stream, which may be a compressed video stream, e.g. an AVI-compressed video stream. In this case image frames may be decompressed before processing.
[0050] At step S400 the procedure captures i.e. inputs raw interference images from the iSCAT microscope and, at S402, averages a sequence of N such images to determine a mean background image. The iSCAT camera captures variation in the interference generated by an imaged particle moving in the solution and the averaging process reduces or removes such variation, reducing this to an average background level. Thus at step S404 the mean background image is subtracted from each of the raw images of the sequence to determine a sequence of background-corrected images. The number N of averaged images may be chosen such that there is significant interference intensity variation amongst the images; it may include more than one maximum/minimum intensity variation.
[0051] The background image may be considered as an instantaneous or local image as there may be a shift in the background over time. For example, for each frame, the background may be estimated by taking the median (or mean) of N local frames. For example, a video of length M might be separated in M/N segments. Each segment of length N may then be analysed.
[0052] Alternatively, a stack of N frames may be selected around each frame so that the frame is in the middle. After subtraction of the background image the image may be normalized by the square root of the intensity to obtain a more uniform noise intensity. Some implementations of the algorithm look for an intensity variation larger than the local noise, which is proportional to the square root of the local intensity. It can therefore be helpful to normalise the noise intensity on the image. Optionally the procedure may subtract a median of the resulting stack (image sequence) to suppress remaining invariant features.
[0053] A result of step S404 is a sequence of images in which the stationary background has been suppressed. These images are then processed to identify one or more locations of intensity variation. For example in one implementation the sequence of background-corrected images is processed to determine a location map image identifying locations of intensity maxima within the images (S406). The sequence of background-corrected images may also be processed to determine a location map image identifying locations of intensity minima within the images, where an intensity minimum is one in which the intensity falls below a previously subtracted background level (S406). Optionally these location map images may be combined or correlated, for example by multiplying values of corresponding pixels, to improve the location map (S408). Optionally an average, e.g. median, value of a location map image may be subtracted from each of the pixels to further suppress stationary features and artefacts, for example image compression artefacts.
[0054] The location map images may include multiple intensity maxima for the same particle at closely located positions. To avoid confusing the motion tracking the location map images may thus be spatially low-pass filtered, for example using a Gaussian kernel (S410). If necessary, for example if the frames coordinates are not stable, rotation and/or deformation detection may be used to perform image registration.
[0055]
[0056] Motion tracking may be applied to the location map images (S412), for example using off the shelf software such as TrackMate Tinevez, J Y.; Perry, N. & Schindelin, J. et al. (2016), “TrackMate: An open and extensible platform for single-particle tracking”, Methods 115: 80-90, PMID 27713081 (on Google Scholar). An output of the motion tracking may comprise, for example, coordinates of a particle in one or more dimensions, such as x and optionally y-dimensions, over time. This data may be used to determine other data characterizing a particle (S414), such as a mean square displacement of the particle over a period of time, or a mean square displacement of the particle in the x or y-direction over a period of time. Other features may be derived, for example speed of motion. Optionally a correction may be made for a known e.g. calibrated speed of flow in the y-direction; this may be a function of x.
[0057] In some implementations higher level particle characterization data may be determined, such as a diffusion coefficient for the particle; and/or an estimated effective size (dimension, area, or volume) for the particle may be determined. For 3D diffusion the diffusion coefficient is inversely proportional to particle size (radius); for 2D diffusion it is inversely proportional to log of the particle size.
[0058] In some implementations particle characterization data may also be obtained from the (raw) iSCAT images. In particular the iSCAT signal, that is the image contrast, depends upon the polarizability of the imaged particle. It appears that the polarizability of a particle such as a molecule/molecular complex as measured by iSCAT contrast depends on the mass of the particle. For example an approximately linear relationship between these has been observed by Piliaril and Sandoghdar, arXiv 1310.7460
[0059] Optionally an estimated particle mass, as determined above, and an estimated particle size, as determined above, may be used in combination to characterize the particle. For example a ratio of one to the other may be determined. This may be used to classify, or potentially even to identify, the particle.
[0060] Many alternatives will occur to the skilled person. The invention is not limited to the described embodiments and encompasses modifications apparent to those skilled in the art lying within the spirit and scope of the claims appended hereto.