INTRODUCTION

This disclosure pertains to the fields of Particle Analysis, Particle Sorting, and Multiplexed Assays. In particular, embodiments disclosed herein are capable of increased multiplexing in Flow Cytometry, Cell Sorting, and Bead-Based Multi-Analyte Assays.

BACKGROUND

Cellular analysis and sorting have reached a high level of sophistication, enabling their widespread use in life science research and medical diagnostics alike. Yet for all their remarkable success as technologies, much remains to be done in order to meet significant needs in terms of applications.

One area of continuing unmet need is that of multiplexing. Multiplexing refers to the practice of labeling cells, beads, or other particles with multiple types of biochemical or biophysical “tags” simultaneously and detecting those tags uniquely, so as to generate a richer set of information with each analysis. The most commonly used tags in microscopy and flow cytometry are fluorescent molecules, or fluorophores. A fluorophore may be a naturally occurring fluorophore; it may be an added reagent; it may be a fluorescent protein [like, e.g., Green Fluorescence Protein (GFP)] expressed by genetic manipulation; it may be a byproduct of chemical or biochemical reactions, etc. Fluorophores may be used as they are, relying on their native affinity for certain subcellular structures such as, e.g., DNA or RNA; or they may be linked to the highly specific biochemical entities known as antibodies, in a process referred to as conjugation. As a particular antibody binds to a matching antigen, often on the surface of a cell, the fluorophore conjugated to that antibody becomes a “tag” for that cell. The presence or absence of the fluorophore (and therefore of the antigen the fluorophore-conjugated antibody is intended to specifically bind to) can then be established by excitation of the cells in the sample by optical means and the detection (if present) of the fluorescence emission from the fluorophore. Fluorescence emission into a certain range of the optical spectrum, or band, is sometimes referred to in the art as a “color;” the ability to perform multiplexed analysis is therefore sometimes ranked by the number of simultaneous colors available for detection.

The use of multiple distinct tags (and detection of their associated colors) simultaneously allows the characterization of each cell to a much greater degree of detail than possible with the use of a single tag. In immunology particularly, cells are classified based on their expression of surface antigens. The identification of a large number of different surface antigens on various types of cells has motivated the creation of a rich taxonomy of cell types. To uniquely identify the exact type of cell under analysis, it is therefore often necessary to perform cell analysis protocols involving simultaneously a large number of distinct antibody-conjugated tags, each specifically designed to identify the presence of a particular type of antigen on the cell surface.

In flow cytometry of the prior art, methods have been devised to simultaneously label cells with up to twenty or more different fluorescent tags and detect their respective colors. Commercially available instrumentation is generally limited to simultaneous detection of fifteen colors or less, and most commonly less than about ten colors. One of the main challenges of routinely performing highly multiplexed analysis (as the practice of simultaneously detecting more than about a dozen separate colors is sometimes called) is the technical difficulty of keeping detection of each color (and its associated tag) separate from detection of all the other ones.FIG. 1illustrates one key aspect of the challenge of multiplexed measurement of fluorescence in the prior art. The graph in thisFIG. 1depicts various fluorescence emission curves (thin solid lines) of intensity (I) as a function of wavelength (λ), all curves having been normalized to their respective peak intensities. In applications of fluorescence detection, it is very commonly desirable to employ several different colors, or spectral bands, of the electromagnetic spectrum, and to assign each band to a different fluorophore. Different fluorophores can be selected, on the basis of their average emission spectra, so as to obtain relatively dense coverage of a certain range of the electromagnetic spectrum, and thereby maximize the amount of information that can be extracted in the course of a single experiment or analysis “run.” However, when striving to maximize spectral coverage, one of the common undesirable consequences is spectral overlap. The shaded portions inFIG. 1illustrate the problem caused by spectral overlap between adjacent fluorescence spectra. In this particular illustrative example, five spectral fluorescence “bands” or colors (the five emission curves peaking at different wavelengths) span a certain desired range of the electromagnetic spectrum, such as, e.g., the visible portion of the spectrum from about 400 nm to about 750 nm in wavelength. The shaded portions indicate sections of the spectrum where it is impossible, using spectral means alone, to decide whether the signal comes from one or the other of the two bands adjacent to the overlapping region; accordingly, the portions of the spectrum corresponding to significant overlap are commonly discarded, resulting in inefficient use of the spectrum. Additionally, even after discarding such portions, residual overlap remains in the other portions, resulting in contamination of one band from signals from other bands. Attempts at negating the deleterious effects of such contamination go under the heading of “compensation.” This spectral overlap problem is variously described in the literature and the community as the “crosstalk,” the “spillover,” the “compensation problem,” etc., and it is a major factor in limiting the maximum number of concurrent spectral bands, or colors, that can be employed in a fluorescence detection experiment.

It would be desirable, then, to provide a way to perform highly multiplexed analyses of particles or cells with a reduced or eliminated impact of spectral crosstalk.

In cell analysis of the prior art, methods have also been devised to simultaneously label cells with up to thirty or more different tags and detect their respective characteristics. For example, the technique known in the art as mass cytometry employs not fluorescence as a way to distinguish different tags, but mass spectrometry, where the tags incorporate not fluorophores, but different isotopes of rare earths identifiable by their mass spectra. One major drawback of this approach is that the protocol of analysis is destructive to the sample, the cells and their tags becoming elementally vaporized in the process of generating the mass spectra. This approach is therefore not suited to the selection and sorting of cells or other particles following their identification by analysis.

It would be further desirable, then, to provide a way to perform selection and sorting of particles or cells based on nondestructive highly multiplexed analysis with a reduced or eliminated impact of spectral crosstalk.

In bead-based multiplexing assays of the prior art, the substrate for the capture of analytes is the surface of a color-coded microsphere (also referred to as “bead”). The measurement of analytes (e.g., antigens) by so-called sandwich immunoassays is typically performed with, e.g., antigen-specific primary antibodies attached to the surface of the microsphere; the analytes are captured by the primary antibodies; and the reporting is typically performed using, e.g., secondary antibodies conjugated to fluorescent reporter molecules. Similar methods of the prior art are used for measurement of other analytes, including proteins, enzymes, hormones, drugs, nucleic acids, and other biological and synthetic molecules. To provide for simultaneous measurement of different analytes (multiplexing), each microsphere is internally stained with one or more dyes (colors) in precise amounts spanning a range of discrete levels. Each particular level of dye A (and optionally in combination with particular levels of dye B, dye C, etc.) is assigned to, e.g., a specific primary capture antibody attached to the surface of the microsphere. As color-coded beads are mixed with a sample, they each capture a certain analyte; a second step provides the secondary binding of the reporter molecule. The resulting bead+analytes+reporters complex is then passed through a particle analysis apparatus substantially very similar to a flow cytometer, where one light source is used to excite the dye or dyes in each bead, and another light source is used to excite the reporter fluorophore. The unique color code (combination of specific staining levels of dye A and optionally dye B, dye C, etc.) assigned to each capture entity allows the simultaneous analysis of tens or hundreds of analytes in a sample; the dye-based color coding of each bead is used to classify the results as the beads pass through. In current commercial offerings, there is a practical limit to the number of color-coded bead types that can be used simultaneously in a multiplex assay. One fluorescence detection spectral band is reserved for the reporter molecules, reducing the spectral range available for coding the beads; accordingly, it has been challenging to fashion more than two or three separate fluorescence detection bands out of the remaining available spectrum. Each band providing about 10 discrete levels of fluorescence for multiplexing, the total number of possible combinations is about 10 for one dye, about 100 for two dyes, and about 1,000 for three dyes. Current commercial offerings cap at 500 the number of practically available multiplexing combinations, limiting the number of individual analytes that can be examined in a single measurement run.

It would be further desirable, then, to provide a way to perform bead-based multiplexing with a greater number of simultaneously distinguishable beads, to enable the performance of multiplexing assays with a greater number of simultaneously measured analytes.

SUMMARY

One aspect of the present disclosure is directed to an apparatus for analyzing an optical signal decay. In some embodiments, the apparatus includes: a source of a beam of pulsed optical energy; a sample holder configured to expose a sample to the beam; a detector including a number of spectral detection channels, the channels being sensitive to distinct wavelength sections of the electromagnetic spectrum and being configured to detect optical signals resulting from interactions between the beam and the sample, the channels being further configured to convert the optical signals into respective electrical signals; a first optical path from the source of the beam to the sample; a second optical path from the sample to the detector; and a signal processing module configured to perform a method. In some embodiments, the method includes: receiving the electrical signals from the detector; mathematically combining individual decay curves in the electrical signals into a decay supercurve, the supercurve comprising a number of components, each component having a time constant and a relative contribution to the supercurve; and numerically fitting a model to the supercurve.

In some embodiments, numerically fitting comprises using at least one of: linear regression, nonlinear regression, least squares fitting, nonlinear least squares fitting, partial least squares fitting, weighted fitting, constrained fitting, Levenberg-Marquardt algorithm, Bayesian analysis, principal component analysis, cluster analysis, support vector machines, neural networks, machine learning, deep learning, and combinations thereof.

In some embodiments, each time constant and each relative contribution each correspond to at least one adjustable parameter of the model, wherein the model comprises a plurality of parameters, and wherein one or more of the plurality of parameters is adjusted by fitting.

In some embodiments, the source of the beam of pulsed optical energy is an internally modulated laser.

In some embodiments, the signal processing module comprises one of: an FPGA, a DSP chip, an ASIC, a CPU, a microprocessor, a microcontroller, a single-board computer, a standalone computer, and a cloud-based processor.

In some embodiments, the optical signals comprise a fluorescence signal.

In some embodiments, the sample comprises a suspension of particles; the apparatus further including: a flow path for the suspension of particles; and a flowcell configured as an optical excitation chamber for generating the optical signals from interactions between the beam of pulsed optical energy and the particles, such that the flowcell is connected with the flow path, the first optical path, and the second optical path.

In some embodiments, the apparatus comprises a flow cytometer.

In some embodiments, the apparatus further includes: a particle sorting actuator connected with the flow path; an actuator driver connected with the actuator, the driver configured to receive actuation signals from the signal processing module; and at least one particle collection receptacle connected with the flow path.

In some embodiments, the particle sorting actuator is based on at least one flow diversion in the flow path.

In some embodiments, the particle sorting actuator is based on one of: a transient bubble, a pressurizable chamber, a pressurizable/depressurizable chamber pair, and a pressure transducer.

Another aspect of the present disclosure is directed to an apparatus for analyzing an optical signal decay. In some embodiments, the apparatus includes: a source of a beam of pulsed optical energy; a sample holder configured to expose a sample to the beam; a detector including a number of spectral detection channels, the channels being sensitive to distinct wavelength sections of the electromagnetic spectrum and being configured to detect optical signals resulting from interactions between the beam and the sample, the channels being further configured to convert the optical signals into respective electrical signals; a first optical path from the source of the beam to the sample; a second optical path from the sample to the detector; and a signal processing module configured to perform a method. In some embodiments, the method includes: receiving the electrical signals from the detector; mathematically combining individual decay curves in the electrical signals into a decay supercurve, the supercurve comprising a number of components, each component having a time constant and a relative contribution to the supercurve; allocating individual components of the supercurve to discrete bins of predetermined time constants; and numerically fitting a model to the supercurve.

In some embodiments, numerically fitting comprises using at least one of: linear regression, nonlinear regression, least squares fitting, nonlinear least squares fitting, partial least squares fitting, weighted fitting, constrained fitting, Levenberg-Marquardt algorithm, Bayesian analysis, principal component analysis, cluster analysis, support vector machines, neural networks, machine learning, deep learning, and combinations thereof.

In some embodiments, each time constant and each relative contribution each correspond to at least one adjustable parameter of the model, wherein the model comprises a plurality of parameters, and wherein one or more of the plurality of parameters is adjusted by fitting.

In some embodiments, the source of the beam of pulsed optical energy is an internally modulated laser.

In some embodiments, the signal processing module comprises one of: an FPGA, a DSP chip, an ASIC, a CPU, a microprocessor, a microcontroller, a single-board computer, a standalone computer, and a cloud-based processor.

In some embodiments, the optical signals comprise a fluorescence signal.

In some embodiments, the sample includes a suspension of particles; the apparatus further including: a flow path for the suspension of particles; and a flowcell configured as an optical excitation chamber for generating the optical signals from interactions between the beam of pulsed optical energy and the particles, such that the flowcell is connected with the flow path, the first optical path, and the second optical path.

In some embodiments, the apparatus comprises a flow cytometer.

In some embodiments, the apparatus further includes: a particle sorting actuator connected with the flow path; an actuator driver connected with the actuator, the driver configured to receive actuation signals from the signal processing module; and at least one particle collection receptacle connected with the flow path.

In some embodiments, the particle sorting actuator is based on at least one flow diversion in the flow path.

In some embodiments, the particle sorting actuator is based on one of a transient bubble, a pressurizable chamber, a pressurizable/depressurizable chamber pair, and a pressure transducer.

An apparatus for analyzing an optical signal decay, comprising:a source of a beam of pulsed optical energy;a sample holder configured to expose a sample to said beam;a detector, the detector comprising a number of spectral detection channels, said channels being sensitive to distinct wavelength sections of the electromagnetic spectrum and being configured to detect optical signals resulting from interactions between said beam and said sample, said channels being further configured to convert said optical signals into respective electrical signals;a first optical path from said source of said beam to said sample;a second optical path from said sample to said detector; anda signal processing module, capable of:receiving said electrical signals from said detector;mathematically combining individual decay curves in said electrical signals into a decay supercurve, said supercurve comprising a number of components, each component having a time constant and a relative contribution to said supercurve;extracting time constants from said supercurve; andquantifying the relative contribution of individual components to said supercurve.

An apparatus for analyzing an optical signal decay, comprising:a source of a beam of pulsed optical energy, wherein said source of said beam of pulsed optical energy is an internally modulated laser;a flowcell configured as an optical excitation chamber for exposing to said beam a sample comprising a suspension of particles and for generating optical signals from interactions between said beam and said particles;a detector, the detector comprising a number of spectral detection channels, said channels being sensitive to distinct wavelength sections of the electromagnetic spectrum and being configured to detect said optical signals, said channels being further configured to convert said optical signals into respective electrical signals, wherein said optical signals comprise a fluorescence signal;a first optical path from said source of said beam to said sample, said first optical path being connected with said flowcell;a second optical path from said sample to said detector, said second optical path being connected with said flowcell;a signal processing module, wherein said signal processing module comprises one of an FPGA, a DSP chip, an ASIC, a CPU, a microprocessor, a microcontroller, a single-board computer, a standalone computer, and a cloud-based processor, said signal processing module being further capable of:receiving said electrical signals from said detector;mathematically combining individual decay curves in said electrical signals into a decay supercurve, said supercurve comprising a number of components, each component having a time constant and a relative contribution to said supercurve;extracting time constants from said supercurve; andquantifying the relative contribution of individual components to said supercurve;a flow cytometer;a flow path for said suspension of particles, said flow path being connected with said flowcell;a particle sorting actuator connected with said flow path, wherein said particle sorting actuator is based on at least one flow diversion in said flow path, and wherein said particle sorting actuator is further based on one of a transient bubble, a pressurizable chamber, a pressurizable/depressurizable chamber pair, and a pressure transducer;an actuator driver connected with said actuator, said driver being configured to receive actuation signals from said signal processing module; andat least one particle collection receptacle connected with said flow path.

An apparatus for analyzing an optical signal decay, comprising:a source of a beam of pulsed optical energy;a sample holder configured to expose a sample to said beam;a detector, the detector comprising a number of spectral detection channels, said channels being sensitive to distinct wavelength sections of the electromagnetic spectrum and being configured to detect optical signals resulting from interactions between said beam and said sample, said channels being further configured to convert said optical signals into respective electrical signals;a first optical path from said source of said beam to said sample;a second optical path from said sample to said detector; anda signal processing module, capable of:receiving said electrical signals from said detector;mathematically combining individual decay curves in said electrical signals into a decay supercurve, said supercurve comprising a number of components, each component having a time constant and a relative contribution to said supercurve;allocating individual components of said supercurve to discrete bins of predetermined time constants; andquantifying the relative contribution of individual components to said supercurve.

An apparatus for analyzing an optical signal decay, comprising:a source of a beam of pulsed optical energy, wherein said source of said beam of pulsed optical energy is an internally modulated laser;a flowcell configured as an optical excitation chamber for exposing to said beam a sample comprising a suspension of particles and for generating optical signals from interactions between said beam and said particles;a detector, the detector comprising a number of spectral detection channels, said channels being sensitive to distinct wavelength sections of the electromagnetic spectrum and being configured to detect said optical signals, said channels being further configured to convert said optical signals into respective electrical signals, wherein said optical signals comprise a fluorescence signal;a first optical path from said source of said beam to said sample, said first optical path being connected with said flowcell;a second optical path from said sample to said detector, said second optical path being connected with said flowcell;a signal processing module, wherein said signal processing module comprises one of an FPGA, a DSP chip, an ASIC, a CPU, a microprocessor, a microcontroller, a single-board computer, a standalone computer, and a cloud-based processor, said signal processing module being further capable of:receiving said electrical signals from said detector;mathematically combining individual decay curves in said electrical signals into a decay supercurve, said supercurve comprising a number of components, each component having a time constant and a relative contribution to said supercurve;allocating individual components of said supercurve to discrete bins of predetermined time constants; andquantifying the relative contribution of individual components to said supercurve;a flow cytometer;a flow path for said suspension of particles, said flow path being connected with said flowcell;a particle sorting actuator connected with said flow path, wherein said particle sorting actuator is based on at least one flow diversion in said flow path, and wherein said particle sorting actuator is further based on one of a transient bubble, a pressurizable chamber, a pressurizable/depressurizable chamber pair, and a pressure transducer;an actuator driver connected with said actuator, said driver being configured to receive actuation signals from said signal processing module; andat least one particle collection receptacle connected with said flow path.

