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Microfluidic implementation of functional cytometric microbeads for improved multiplexed cytokine quantification Ya Liu, Jiyu Li, Dinglong Hu, Josh H. M. Lam, Dong Sun, Stella W. Pang, and Raymond H. W. Lam Citation: Biomicrofluidics 12, 044112 (2018); doi: 10.1063/1.5044449 View online: https://doi.org/10.1063/1.5044449 View Table of Contents: http://aip.scitation.org/toc/bmf/12/4 Published by the American Institute of Physics Articles you may be interested in Micropipette-powered droplet based microfluidics Biomicrofluidics 12, 044106 (2018); 10.1063/1.5037795 Preface to Special Topic: Bio-Transport Processes and Drug Delivery in Physiological Micro-Devices Biomicrofluidics 12, 042101 (2018); 10.1063/1.5050428 Impact of poloxamer 188 (Pluronic F-68) additive on cell mechanical properties, quantification by real-time deformability cytometry Biomicrofluidics 12, 044118 (2018); 10.1063/1.5040316 A microfluidic device for isolation and characterization of transendothelial migrating cancer cells Biomicrofluidics 11, 014105 (2017); 10.1063/1.4974012 Serial integration of Dean-structured sample cores with linear inertial focussing for enhanced particle and cell sorting Biomicrofluidics 12, 044104 (2018); 10.1063/1.5038965 Engineered microfluidic bioreactor for examining the three-dimensional breast tumor microenvironment Biomicrofluidics 12, 034102 (2018); 10.1063/1.5016433

Microfluidic implementation of functional cytometric microbeads … · 2018. 9. 26. · Micropipette-powered droplet based microfluidics Biomicrofluidics 12, 044106 (2018); 10.1063/1.5037795

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  • Microfluidic implementation of functional cytometric microbeads for improvedmultiplexed cytokine quantificationYa Liu, Jiyu Li, Dinglong Hu, Josh H. M. Lam, Dong Sun, Stella W. Pang, and Raymond H. W. Lam

    Citation: Biomicrofluidics 12, 044112 (2018); doi: 10.1063/1.5044449View online: https://doi.org/10.1063/1.5044449View Table of Contents: http://aip.scitation.org/toc/bmf/12/4Published by the American Institute of Physics

    Articles you may be interested inMicropipette-powered droplet based microfluidicsBiomicrofluidics 12, 044106 (2018); 10.1063/1.5037795

    Preface to Special Topic: Bio-Transport Processes and Drug Delivery in Physiological Micro-DevicesBiomicrofluidics 12, 042101 (2018); 10.1063/1.5050428

    Impact of poloxamer 188 (Pluronic F-68) additive on cell mechanical properties, quantification by real-timedeformability cytometryBiomicrofluidics 12, 044118 (2018); 10.1063/1.5040316

    A microfluidic device for isolation and characterization of transendothelial migrating cancer cellsBiomicrofluidics 11, 014105 (2017); 10.1063/1.4974012

    Serial integration of Dean-structured sample cores with linear inertial focussing for enhanced particle and cellsortingBiomicrofluidics 12, 044104 (2018); 10.1063/1.5038965

    Engineered microfluidic bioreactor for examining the three-dimensional breast tumor microenvironmentBiomicrofluidics 12, 034102 (2018); 10.1063/1.5016433

    http://oasc12039.247realmedia.com/RealMedia/ads/click_lx.ads/www.aip.org/pt/adcenter/pdfcover_test/L-37/1103208371/x01/AIP-PT/BMF_ArticleDL_0618/BMF_1640x440Banner_2-18.jpg/434f71374e315a556e61414141774c75?xhttp://aip.scitation.org/author/Liu%2C+Yahttp://aip.scitation.org/author/Li%2C+Jiyuhttp://aip.scitation.org/author/Hu%2C+Dinglonghttp://aip.scitation.org/author/Lam%2C+Josh+H+Mhttp://aip.scitation.org/author/Sun%2C+Donghttp://aip.scitation.org/author/Pang%2C+Stella+Whttp://aip.scitation.org/author/Lam%2C+Raymond+H+W/loi/bmfhttps://doi.org/10.1063/1.5044449http://aip.scitation.org/toc/bmf/12/4http://aip.scitation.org/publisher/http://aip.scitation.org/doi/abs/10.1063/1.5037795http://aip.scitation.org/doi/abs/10.1063/1.5050428http://aip.scitation.org/doi/abs/10.1063/1.5040316http://aip.scitation.org/doi/abs/10.1063/1.5040316http://aip.scitation.org/doi/abs/10.1063/1.4974012http://aip.scitation.org/doi/abs/10.1063/1.5038965http://aip.scitation.org/doi/abs/10.1063/1.5038965http://aip.scitation.org/doi/abs/10.1063/1.5016433

  • Microfluidic implementation of functional cytometricmicrobeads for improved multiplexed cytokinequantification

    Ya Liu,1 Jiyu Li,1 Dinglong Hu,1 Josh H. M. Lam,1 Dong Sun,1,2

    Stella W. Pang,3,4 and Raymond H. W. Lam1,2,3,5,a)1Department of Mechanical and Biomedical Engineering, City University of Hong Kong,Hong Kong 999077, China2Centre for Robotics and Automation, City University of Hong Kong, Hong Kong 999077,China3Centre for Biosystems, Neuroscience, and Nanotechnology, City University of Hong Kong,Hong Kong 999077, China4Department of Electronic Engineering, City University of Hong Kong, Hong Kong 999077,China5City University of Hong Kong Shenzhen Research Institute, Shenzhen 518057, China

    (Received 12 June 2018; accepted 30 July 2018; published online 10 August 2018)

    Functional microbeads have been widely applied in molecular identification and other

    biochemical applications in the past decade, owing to the compatibility with flow

    cytometry and the commercially available microbeads for a wide range of molecular

    identification. Nevertheless, there is still a technical hurdle caused by the significant

    sample volume required (�50 ll), limited molecular detection limit (�20 pg/ml),complicated liquid/microbead handling procedures, and the long reaction time (>2 h).In this work, we optimize the operation of an automated microbead-based microfluidic

    device for the reagent mixing and the dynamic cytokine detection. In particular, we

    adopt fluorescence microscopy for quantification of multiple microbeads in each

    microchamber instead of flow cytometry for a lower detection limit. The operation

    parameters are then configured for improved measurement performance. As demon-

    strated, we consider the cytokine secretion of human macrophage-differentiating lym-

    phocytes stimulated by lipopolysaccharides. We examine requirements on the mixing

    duration, minimal sample volume, and the image analysis scheme for the smaller bio-

    sample volume (

  • designed for the flow cytometry as a highly sensitive detection scheme. For example, Rufer et al.developed a flow cytometry scheme of microbeads to test the telomere length for revealing the

    replicative tendency of lymphocytes11 and implicating the possible inflammatory status. Liu et al.devised multi-functional microbeads for the simultaneous determination of multiple DNA and

    protein biomolecules using flow cytometry.12

    Importantly, the mixture of different kinds of functional microbeads can offer a multiplex

    detection mode and support the quantification of multiple simultaneously, varying the biochemi-

    cal characteristics. In particular, the multiplex detection matches perfectly with the necessary

    requirements of immune system diagnosis, in which multiple cytokine levels from the same

    sample have to be quantified individually. Although many other conventional gold standard

    techniques, such as the enzyme-linked immunosorbent assay (ELISA)13 and enzyme-linked

    immunospot assay (ELISPOT),14–18 have also been modified and improved as immunoassays,

    the multiplex microbead detection mode has an outstanding performance in terms of the high

    throughput and sensitivity.19 Hildesheim et al. applied the functional microbeads to test hun-dreds of specimens and proved the reliability of multi-array microbeads in determining the

    cytokine levels of multiple samples with a low volume.10 While very effective, the multiplex

    microbeads with flow cytometer still need further improvements in terms of the large sample

    volume, long labeling time, and complicated washing process.9

    Microfluidics is an ideal strategy for processing the microparticles and liquid biosamples

    for the microbead-based detection, with the great reduction in reagent consumption and automa-

    tion of tedious liquid and microbead handling20,21 with very high precision and consis-

    tency.22–26 Further, mixing in microfluidics can effectively speed up the transport rates and

    reactions of reagents and biomolecules.27–29 Han et al. reported a quantitative microengravingstrategy capable of recording the rates of cytokine secretion from stimulated human peripheral

    blood mononuclear cells.30 In fact, there are already microfluidic techniques integrating with

    the microbead sensing schemes.31–34 Frisk et al. presented a microfluidic device embedded withsilica beads to monitor the proteolytic activity through signal amplification.33 Choi et al. devel-oped a microfluidic biochemical testing system based on magnetic beads’ protein analysis and

    bio-molecule detection.35 Zhang et al. developed a microfluidic chip with quantum dot for theHepatitis B virus genotyping at a lower detection limit.36 An immunoassay platform integrated

    with the antibody-conjugated microbeads was designed by Han et al. for the immunobindingassays and the identification of cancer marker.37 Similarly, Zhu et al. reported a microparticlearray for the detection of human chorionic gonadotropin and prostate specific antigen in serum

    samples, potentially for the point-of-care diagnosis of diseases.38

    Many of the reported microbead-based microfluidic devices support the molecular expres-

    sion at only one time point, rather than profiling their transient dynamics. For example, the

    dynamic variations of cytokine levels in the body reflect more representatively the correspond-

    ing immune status and immune diseases.39 Recently, we have reported a microfluidic mixing-

    assisted multiplexed dynamic cytokine profiling strategy compatible with the commercially

    available cytometric microbeads,40 yet the configuration parameters for the liquid handling,

    reagent mixing, and measurement performance have not been optimized. This work describes

    the required procedures and expected results of configuring the measurement parameters (e.g.,

    reagent mixing time and image analysis strategy) for the multiplex molecular quantification

    with the reduced detection limit and process time. By performing the same procedures,

    such microbead microfluidic strategy can be further applied for the detection using any other

    functional microbeads. In addition, we demonstrate the feasibility and performance of the

    microfluidic microbead-based measurement on the dynamic cytokine secretion from the human

    monocytic leukemia cells stimulated with lipopolysaccharides.

    MATERIALS AND METHODS

    Cell culture

    Frozen human monocytic leukemia cells (THP-1) were thawed by gentle agitation in water

    bath at 37 �C and were transferred into a centrifuge tube containing 9.0 ml culture medium

    044112-2 Liu et al. Biomicrofluidics 12, 044112 (2018)

  • [90% Roswell Park Memorial Institute (RPMI)-1640, 10% fetal bovine serum (FBS), and

    0.05 mM 2-mercaptoethanol]. The tube was spun at 125�g for 5 min. The cells were re-suspendedwith the medium (volume: 5 ml) and cultured in a 10 cm2 flask. All cells were maintained in an

    incubator at 37 �C supplied with 5% CO2.Before stimulation and cytokine detection, the promonocytic THP-1 cells were pretreated

    with 50 ng/ml phorbol 12-myristate 13-acetate41 (PMA; Sigma-Aldrich) for 48 h42 for the mac-

    rophage differentiation. The PMA-treated THP-1 cells were then maintained in the PMA free

    growth medium for another 24 h.

    Cell viability test

    Reagents of the LIVE/DEAD Cell Viability kit (cat# L-3224, Life Technologies) were added

    into the culture media for 20 min to stain with different fluorescence signals for live and dead

    cells (Fig. S1 in the supplementary material). Fluorescence images (TE300, Nikon, Tokyo, Japan)

    were then captured using an inverted fluorescence microscope (Zyla 4.2, Andor, Belfast, UK).

    Immune cell stimulation

    Reagents, such as polyhydroxyalkanoates (PHA)43 and lipopolysaccharides (LPS),44 are

    widely adopted to stimulate the cytokine secretion of immune cells for their roles in the

    immune response. Here, we have chosen LPS (cat# L5886, Sigma-Aldrich) as the external stim-

    ulant. We applied LPS to the PMA- treated THP-1 cells in each test with a defined concentra-

    tion of 0, 10, or 100 ng/ml. We then collected and quantified the cytokine concentration in the

    culture media of PMA-treated THP-1 cells at multiple time points (0, 2, 4, 6, 8, 10, and 12 h).

    Calibration by flow cytometry

    The cytokine-sensitive fluorescence microbeads (cat# 551811, BD Biosciences) were cali-

    brated using premixed human cytokines samples with known levels of IL-8, IL-1b, IL-6, IL-10,TNF, and IL-12p70. For each cytokine type, through diluting a standard solution (5000 pg/ml),

    multiple cytokine samples were prepared with different defined cytokine concentrations from 5

    to 5000 pg/ml. Next, each of the diluted samples (volume: 50 ll and concentrations: 5–5000 pg/ml) was incubated with antibody-conjugated detection microbeads (volume: 50 ll and concen-tration: 103 beads/ll) and phycoerythrin-conjugated secondary antibodies (concentration: 10 lg/ml) together for 3 h at room temperature to form a sandwich complex, of which the fluores-

    cence intensity should reveal the cytokine concentration. After incubating and washing the

    microbeads with 1 ml phosphate-buffered saline (PBS), the spectrum of fluorescence intensity

    was investigated using flow cytometry (BD FACSVerseTM, BD Biosciences, San Jose, CA,

    USA) with the allophycocyanin (APC) channel.

    Device fabrication

    The device fabrication was based on replica molding of polydimethylisoxane (PDMS) as

    described in Fig. S2 in the supplementary material. Two silicon wafers were fabricated by photoli-

    thography with SU-8 photoresist (SU-8, Microchem) for microchannels in the upper control layer

    (SU-8 2010; height: 20 lm) and the chamber layer at the bottom (SU-8 100; height: 100 lm). Forthe middle flow layer (height: 20 lm), another silicon wafer was patterned with AZ-50XT photore-sist (AZ Electronic Materials) and then reflowed at 120 �C for 1 min after photolithography. Allthe mold surfaces was salinized with trichloro (1H, 1H, 2H, 2H-perfluoro-octyl)silane (Sigma-

    Aldrich) to facilitate the release of the molded PDMS layers in the later demolding step.

    Polymethylsiloxane (PDMS; Sylgard-184, Dow Corning) was prepared by mixing the

    monomer and curing agent with a ratio of 10:1 for three layers of PDMS substrates. A PDMS

    substrate with a thickness of 5 mm was prepared by pouring the PDMS pre-polymer on the con-

    trol layer mold. On the other hand, a layer of 35 lm-thick PDMS was spincoated on the flowlayer mold. After cutting and peeling off the control layer, its channel side and the chamber

    layer were treated with oxygen plasma (energy: 10 kJ; Harrick plasma cleaner PDC-002). These

    044112-3 Liu et al. Biomicrofluidics 12, 044112 (2018)

    ftp://ftp.aip.org/epaps/biomicrofluidics/E-BIOMGB-12-013804ftp://ftp.aip.org/epaps/biomicrofluidics/E-BIOMGB-12-013804

  • two layers were then aligned and bonded under a stereomicroscope. After cutting and peeling

    off the control-flow substrate, holes were then punched at the liquid inlets and outlets (diameter:

    0.5 mm). Another PDMS substrate with a thickness of 1 mm was prepared by pouring the

    PDMS pre-polymer on the chamber layer mold. After baking and peeling off the chamber sub-

    strate, holes were punched on this layer for the detection chambers (diameter: 1 mm). The

    control-flow substrate was then bonded on the chamber substrate using the oxygen plasma. The

    entire stacked PDMS substrate was further bonded on a glass slide (width: 25 mm; length:

    75 mm; and thickness: 170 lm) using the oxygen plasma again. The microfluidic device wasthen baked at 75 �C for 2 h to ensure thorough crosslinking of PDMS.

    Device preparation

    The microfluidic device was sterilized by baking at 100 �C for >10 h and applying UV expo-sure for >2 h. All the control channels were filled with distilled water. The syringe tubing(TygonTM tubing, US Plastics, Lima, OH) was connected to the control inlets of the device and

    the computer-controlled pressure supplies (pressure: 0–30 psi).45,46 Phycoerythrin-conjugated sec-

    ondary antibody solution (�50 lg/ml), detection microbeads, and wash buffer was injectedthrough the corresponding liquid inlets with the air pressure manifold (pressure: 0 or 0.2 psi). All

    the control valves were maintained with a pressure of 30 psi so that all the flow channels and

    detection chambers can be closed completely. The device was then placed on an inverted micro-

    scope (objectives: 20�; working distance: 0.35 mm; TE300, Nikon, Tokyo, Japan) installed witha camera (Zyla 4.2, Andor, Belfast, UK) and an environment-controlled chamber (37 �C and 5%CO2). The acquired fluorescence micrographs were a series of 1024 pixel� 1024 pixel 16-bitgray-scale images.

    Statistics

    All error bars in plots are standard errors. p-values are determined by comparing twogroups of data using Student’s two-tailed, unpaired T-test. An asterisk in a plot represents a sig-

    nificant difference between two data groups (p< 0.05).

    RESULTS AND DISCUSSION

    Influence of sample extraction volume

    We investigated feasibility of functional microbead arrays for detection of cytokine concen-

    trations in a cell culture with multiple time points by four experiment groups. In each of the

    experiments, we prepared the THP-1 cells (cell density: 1� 106 cells/ml) growing in 5 ml ofmedia in a culture flask. Once the cells were further stimulated by LPS, we regularly extracted

    a volume of media from the cell culture to perform the cytokine quantification using the stan-

    dard protocol at different time points (0, 2, 4, 6, 8, 10, and 12 h). It was expected that the

    detected cytokine levels should vary with time, as such dynamics of immune cells upon exter-

    nal stimuli can reflect some immune response characteristics. Afterwards, we examined the via-

    bility of the cells remaining in the flask. The first experiment group considered extracting a

    sample volume of 5 ll in each cytokine measurement with refilling 5 ll of fresh media; whilethe second group considered the same extraction volume but skipped the media refill. The sam-

    ple will then be diluted by adding the fresh culture media with a volume of 45 ll. The thirdand fourth groups were the same as the first two groups except that a larger extraction volume

    of 50 ll was considered. An additional group was the control case included only the cell viabil-ity test but no medium extraction or cytokine detection steps. Furthermore, we have performed

    5 repeated experiments for each of the above cases. There was no significant reduction in cell

    viability, defined as the percentage of live cells in the entire (live and dead) cell population,

    among all the five groups (Fig. S1 in the supplementary material).

    The experiment groups correspond to different variations in the biochemical concentrations

    in the cell environment. The medium extraction step reduces the remaining medium volume

    with the immune cells; and therefore, the same cytokine secretion rate of the cells would then

    044112-4 Liu et al. Biomicrofluidics 12, 044112 (2018)

    ftp://ftp.aip.org/epaps/biomicrofluidics/E-BIOMGB-12-013804

  • induce a relative higher cytokine concentration in the media. On the other hand, the media refill

    step would dilute the cytokine level in the media. In these experiments, we have further con-

    verted the detected cytokine concentrations at different time points [Fig. 1(a)] to the cytokine

    secretion rate (unit: pg/h per cell) among the first four experiment groups [Fig. 1(b)]. As the

    cytokine secretion profiles are significant different among the experiment cases, our results indi-

    cate that the different temporary cytokine levels can vary the cytokine secretion rates over the

    monitored experiment period. To eliminate the effects caused by the media extraction step, we

    need to consider largely reducing the sample volume in each cytokine detection. Yet, we have

    examined that the convention cytokine detection procedures using flow cytometry only supports

    an accuracy measurement for a minimal sample volume. Together, an alternative quantification

    method for the cytometric microbeads is required for the profiling of cell cytokine secretion

    dynamics.

    Microfluidic immunoassay operation

    The goal of this work is to transform the standard protocol of a commercial cytometric

    microbead array (cat# 551811, BD Biosciences) into equivalent microfluidic procedures with a

    large reduction in required sample size and detection time. In typical microbead detections, as

    shown in Fig. 2 (left), microbeads coated with antibodies were pipetted and mixed up with bio-samples to capture target cytokine molecules on the bead surfaces, followed by the discharge of

    all the reagents and the addition of secondary antibody molecules modified with fluorescence.

    Accordingly, the multiple cytokine concentrations revealed by the captured cytokines on bead

    surfaces were then transferred to corresponding fluorescence intensities and quantified by vari-

    ous techniques such as flow cytometry. Similarly, we executed these procedures using micro-

    fluidics (Fig. 2, right), in which the required sample volume for each detection can be largelyminiaturized from �50 ll to

  • the miniaturized syringe tubes in the conventional procedures for storage of extracted samples

    and other reagents. As the microbeads are confined in the microfluidic device, microfluidic

    mixers should be integrated with the microchambers for the required mixing process. For the

    same reason, we need to adopt another applicable imaging technique for quantifying fluores-

    cence intensity of the microbeads in the microchambers.

    Based on the above requirements, an integrated microfluidic device composed of an array

    of 4� 4 detection regions was successfully designed [Fig. 3(a)] and fabricated [Fig. 3(b)]. Thistesting device is based on our recently reported work.40 Each detection region contains a micro-

    chamber (diameter: 1 mm; height: 1 mm; and volume: 0.79 ll) and a bypass channel. The devicecontains three layers: control/mixing layer (red/blue), flow layer (black), and chamber layer(green). The control/mixing layer was above the flow layer; and the chamber layer was at thebottom. To measure the cytokine level, we first injected cytokine sensitive microbeads (diame-

    ter: 7 lm) with a density of 103 beads/ll into a microchamber (diameter: 1 mm and depth:1 mm) through multiple inlets controlled by different microvalves. Thus, there were �785

    FIG. 2. Detection schemes using flow cytometry (left) and proposed microfluidic procedures (right).

    044112-6 Liu et al. Biomicrofluidics 12, 044112 (2018)

  • microbeads in each detection chamber. After 30 min, the microbeads could sink into the cham-

    ber bottom and be kept afterward. The microchamber and the microchannel in each detection

    region were then filled with the extracted samples and the phycoerythrin-conjugated fluores-

    cence secondary antibodies, respectively.

    After closing the inlet and outlet of pneumatic microvalves in the detection region, we

    incubated the microbeads with the biosample and reagents. Meanwhile, three microvalves [inset

    of Fig. 3(b)] along the microchannel of a mixer region were pressurized with a peristaltic

    sequence of the three pressurization patterns (on-on-off, off-on-on, and then on-off-on). The

    switching time between the pressurization patterns was set as 250 ms (Fig. S3 in the supplemen-

    tary material). The microvalves also mixed the liquids in the mixing region based on the Taylor

    Dispersion effect.47,48 We then injected wash buffer (PBS) into the detection chamber and con-

    ducted the microbeads washing process for 30 s. Using the washed microbeads, corresponding

    fluorescence images for cytokine molecules (488 nm) and bead bodies (647 nm) were collected

    in order to measure the corresponding cytokine concentration and label the position of the bead

    body, respectively.

    Minimal incubation and mixing duration

    In the typical protocols of commercial cytometric microbeads, the procedures are rather

    tedious, including several times of washing and centrifugal steps; and the required incubation

    time is long (�3 h) as the molecular transport is mainly governed by diffusion. The microflui-dic operations of these microbeads can automate the required procedures. Further, the continu-

    ous microvalve-driven mixing can be applied during the incubation and therefore we expect a

    shorter incubation time. We are interested in investigating the required incubation duration

    of the microfluidic immunoassay for promising measurements. In the experiments, we have

    measured prepared cytokine solutions (IL-10) with a defined concentration (1250 pg/ml) for

    FIG. 3. (a) Design of the microfluidic immunoassay device. Scale bar: 2 mm. (b) A fabricated device (left) and one detec-tion region including a chamber and a mixing channel (right). There are three microvalves (blue dotted boxes) driving themixing flow in the chamber region. Scale bar: 500 lm.

    044112-7 Liu et al. Biomicrofluidics 12, 044112 (2018)

    ftp://ftp.aip.org/epaps/biomicrofluidics/E-BIOMGB-12-013804ftp://ftp.aip.org/epaps/biomicrofluidics/E-BIOMGB-12-013804

  • different incubation and mixing durations of the microfluidic immunoassay. We have consid-

    ered eight mixing durations from 5 min to 40 min and the results. In each measurement, we cap-

    tured the fluorescence images for the bead body (647 nm) and cytokine concentration (488 nm)

    [Fig. 4(a)]. We then only considered the average cytokine-related fluorescence intensity over

    the microbead region. The results (Fig. 4) indicate that an insufficient mixing time induces an

    underestimated cytokine values; and the mixing time of 30 min is sufficient for a promising

    measurement. In other words, the microfluidic implementation of the cytometric microbeads

    can shorten the measurement duration from 3 h to 30 min.

    Detection limit of cytometric microbeads in the microfluidic setting

    We calibrated fluorescence intensity against cytokine concentration of six types of microbe-

    ads (TNF, IL-6, IL-8, IL-10, IL-1b, and IL-12p70) in order to determine the detection limit ofmeasurement using the microfluidic immunoassay. We considered cytokine concentrations in

    the range of 1–5000 pg/ml. Our results (Fig. 5) exhibit the linearity (R2> 0.9) of fluorescenceintensity and cytokine concentration in the log scale, agreeing with the reported characteristics

    FIG. 4. (a) Fluorescence images of IL-10 expressions on cytometric microbeads (red: bead body and green: stained cyto-kine intensity) at different mixing times. Scale bar: 100 lm. (b) Stained cytokine intensity verses mixing time. Each datapoint is the average level of >8 repeated measurements. The asterisk indicates a p-value < 0.05 comparing to the intensitylevel of 40 min mixing time.

    044112-8 Liu et al. Biomicrofluidics 12, 044112 (2018)

  • of cytometric microbeads. The cytokine detection limit in the microfluidic setting is �5 pg/ml,which is significantly better than the detection using flow cytometry (20 pg/ml). This improve-

    ment can be explained by the fact that the fluorescence intensity is obtained from all the

    captured microbeads in a fluorescence image rather than a single microbead as in the flow

    cytometry detection. Additionally, longer exposure duration (>200 ms) can be applied in themicrofluidic measurement because microbeads are static in the microchambers, comparing to

    the shorter effective exposure time (�60 ms) on the flowing microbeads during the flowcytometry operation.

    Profiling cytokine secretion dynamics of immune cells

    We have further applied the microfluidic immunoassay strategy to monitor the cytokine

    dynamics of the PMA-treated THP-1 cells stimulated by different levels of LPS (1, 10, and

    100 ng/ml). We adopted the cells at the coverage of 1� 106 cells/ml growing in a 10 cm2 cul-ture flask. The culture media was extracted from the flask with a volume of 5repeated measurements.

    044112-9 Liu et al. Biomicrofluidics 12, 044112 (2018)

  • the effects of LPS on the secrete cytokines of the THP-1 cells. For instance, LPS can induce

    the secretion of IL-8, IL-1b, and TNF. The secretion of the three cytokines are, in general, witha higher rate for the cells stimulated by 10 ng/ml LPS, with statistically significant differences

    in the cytokine concentration between the 10 ng/ml LPS group and the other groups of the dif-

    ferent LPS concentrations for all the cases in Fig. 6. It seems that the secretion of IL-8 and

    TNF can be stimulated with the highest effectiveness within a range of the stimulant concentra-

    tion. It should be also highlighted that the microfluidic immunoassay offers promising monitor-

    ing of the dynamics IL-1b due to its lower detection limit (�5 pg/ml) over the flow cytometrymeasurement (20 pg/ml).

    We have briefly confirmed the accuracy of cytokine concentrations measured by the

    microfluidic immunoassay. For the TNF monitoring, we extracted an extra sample volume

    of 5 ll with a dilution to 50 ll for the flow cytometry measurement. The measured valuesfrom both methods show a good agreement (no significant difference is observed), as shown

    in Fig. 7; and therefore, we believe that the microfluidic immunoassay strategy can offer

    an equivalent cytokine concentration value, but a lower detection limit than the flow

    cytometry.

    FIG. 6. Concentrations of IL-8, IL-1b, and TNF in the media of PMA-treated THP-1 cells stimulated by different levels ofLPS over 12 h. N> 10 from four repeated cell stimulation experiments.

    044112-10 Liu et al. Biomicrofluidics 12, 044112 (2018)

  • CONCLUSION

    This research investigates the design of a microfluidic immunoassay device consisting of

    multiple detection regions for cytokine measurement using commercial functional cytometric

    microbeads. Such microfluidic strategy offers some key advantages over the microbeads quantifi-

    cation using flow cytometry. Despite the reduced reagent volume, the required biosample volume

    is largely reduced from 50 ll to 10) and flow cytometry (N� 1000) on TNF concentration in thecultured media of PMA-treated THP-1 cells stimulated by 10 ng/ml of LPS.

    044112-11 Liu et al. Biomicrofluidics 12, 044112 (2018)

    ftp://ftp.aip.org/epaps/biomicrofluidics/E-BIOMGB-12-013804

  • 1X. Gao and S. Nie, Anal. Chem. 76(8), 2406–2410 (2004).2T. R. Sathe, A. Agrawal, and S. Nie, Anal. Chem. 78(16), 5627–5632 (2006).3U. Resch-Genger, M. Grabolle, S. Cavaliere-Jaricot, R. Nitschke, and T. Nann, Nat. Methods 5(9), 763–775 (2008).4M. Oelke, M. V. Maus, D. Didiano, C. H. June, A. Mackensen, and J. P. Schneck, Nat. Med. 9(5), 619–625 (2003).5A. Sukhanova, A. S. Susha, A. Bek, S. Mayilo, A. L. Rogach, J. Feldmann, V. Oleinikov, B. Reveil, B. Donvito, and J.H. Cohen, Nano Lett. 7(8), 2322–2327 (2007).

    6Y. Liu, L. Liu, Y. He, Q. He, and H. Ma, Biosens. Bioelectron. 77, 886–893 (2016).7H. Shibata, Y. J. Heo, T. Okitsu, Y. Matsunaga, T. Kawanishi, and S. Takeuchi, Proc. Natl. Acad. Sci. U. S. A. 107(42),17894–17898 (2010).

    8S. Wu, L. Liu, G. Li, F. Jing, H. Mao, Q. Jin, W. Zhai, H. Zhang, J. Zhao, and C. Jia, Talanta 156–157, 48–54 (2016).9P. Chen, M. T. Chung, W. McHugh, R. Nidetz, Y. Li, J. Fu, T. T. Cornell, T. P. Shanley, and K. Kurabayashi, ACS Nano9(4), 4173–4181 (2015).

    10V. Krishhan, I. H. Khan, and P. A. Luciw, Crit. Rev. Biotechnol. 29(1), 29–43 (2009).11N. Rufer, W. Dragowska, G. Thornbury, E. Roosnek, and P. M. Lansdorp, Nat. Biotechnol. 16(8), 743–747 (1998).12X. Liu, T. Bing, and D. Shangguan, ACS Appl. Mater. Interfaces 9(11), 9462–9469 (2017).13A. V. Orjalo, D. Bhaumik, B. K. Gengler, G. K. Scott, and J. Campisi, Proc. Natl. Acad. Sci. U. S. A. 106(40),

    17031–17036 (2009).14D. P. Harris, L. Haynes, P. C. Sayles, D. K. Duso, S. M. Eaton, N. M. Lepak, L. L. Johnson, S. L. Swain, and F. E. Lund,

    Nat. Immunol. 1(6), 475–482 (2000).15J. E. Snyder, W. J. Bowers, A. M. Livingstone, F. E.-H. Lee, H. J. Federoff, and T. R. Mosmann, Nat. Med. 9(2),

    231–236 (2003).16M. Mohrs, C. M. Blankespoor, Z.-E. Wang, G. G. Loots, V. Afzal, H. Hadeiba, K. Shinkai, E. M. Rubin, and R. M.

    Locksley, Nat. Immunol. 2(9), 842–847 (2001).17J. H. Cox, G. Ferrari, and S. Janetzki, Methods 38(4), 274–282 (2006).18K. Mahnke, Y. Qian, S. Fondel, J. Brueck, C. Becker, and A. H. Enk, Cancer Res. 65(15), 7007–7012 (2005).19M. F. Elshal and J. P. McCoy, Methods 38(4), 317–323 (2006).20Q. D. Tran, T. F. Kong, D. Hu, Marcos, and R. H. Lam, Lab Chip 16(15), 2813–2819 (2016).21H. C. F. Marcos, T. R. Powers, and R. Stocker, Phys. Rev. Lett. 102(15), 158103 (2009).22H. Huang, X. L. Zheng, J. S. Zheng, J. Pan, and X. Y. Pu, Biomed. Microdevices 11(1), 213–216 (2009).23L. A. Legendre, J. M. Bienvenue, M. G. Roper, J. P. Ferrance, and J. P. Landers, Anal. Chem. 78(5), 1444–1451 (2006).24G. M. Whitesides, Nature 442(7101), 368–373 (2006).25K. F. Lei, C.-H. Chang, and M.-J. Chen, ACS Appl. Mater. Interfaces 9(15), 13092–13101 (2017).26C.-H. Huang, K. F. Lei, and N.-M. Tsang, Lab Chip 16(15), 2911–2920 (2016).27C.-C. Hong, J.-W. Choi, and C. H. Ahn, Lab Chip 4(2), 109–113 (2004).28B. He, B. J. Burke, X. Zhang, R. Zhang, and F. E. Regnier, Anal. Chem. 73(9), 1942–1947 (2001).29G. G. Yaralioglu, I. O. Wygant, T. C. Marentis, and B. T. Khuri-Yakub, Anal. Chem. 76(13), 3694–3698 (2004).30Q. Han, E. M. Bradshaw, B. Nilsson, D. A. Hafler, and J. C. Love, Lab Chip 10(11), 1391–1400 (2010).31C. Lim and Y. Zhang, Biosens. Bioelectron. 22(7), 1197–1204 (2007).32K. G. McKenzie, L. K. Lafleur, B. R. Lutz, and P. Yager, Lab Chip 9(24), 3543–3548 (2009).33M. L. Frisk, E. Berthier, W. H. Tepp, E. A. Johnson, and D. J. Beebe, Lab Chip 8(11), 1793–1800 (2008).34T. Lilliehorn, M. Nilsson, U. Simu, S. Johansson, M. Almqvist, J. Nilsson, and T. Laurell, Sens. Actuators B 106(2),

    851–858 (2005).35J.-W. Choi, K. W. Oh, J. H. Thomas, W. R. Heineman, H. B. Halsall, J. H. Nevin, A. J. Helmicki, H. T. Henderson, and

    C. H. Ahn, Lab Chip 2(1), 27–30 (2002).36H. Zhang, T. Xu, C.-W. Li, and M. Yang, Biosens. Bioelectron. 25(11), 2402–2407 (2010).37S. W. Han, E. Jang, and W.-G. Koh, Sens. Actuators B209, 242–251 (2015).38Q. Zhu and D. Trau, Anal. Chim. Acta 751, 146–154 (2012).39E.-K. Jo, J.-K. Park, and H. M. Dockrell, Curr. Opin. Infect. Dis. 16(3), 205–210 (2003).40X. Cui, Y. Liu, D. Hu, W. Qian, C. Tin, D. Sun, W. Chen, and R. H. Lam, Lab Chip 18, 522–531 (2018).41G. Priante, L. Bordin, E. Musacchio, G. Clari, and B. Baggio, Clin. Sci. 102(4), 403–409 (2002).42T. Naitoh, M. Kitahara, and N. Tsuruzoe, Cell. Signalling 13(5), 331–334 (2001).43W. A. Neaville, C. Tisler, A. Bhattacharya, K. Anklam, S. Gilbertson-White, R. Hamilton, K. Adler, D. F. DaSilva, K. A.

    Roberg, and K. T. Carlson-Dakes, J. Allergy Clin. Immunol. 112(4), 740–746 (2003).44X. Tang, D. Metzger, S. Leeman, and S. Amar, Proc. Natl. Acad. Sci. U. S. A. 103(37), 13777–13782 (2006).45R. H. Lam, X. Cui, W. Guo, and T. Thorsen, Lab Chip 16(9), 1652–1662 (2016).46C. Yang, D. Hu, B. Sun, X. Cui, Q. Zhu, and R. H. Lam, Microfluid. Nanofluid. 19(3), 711–720 (2015).47J. Marschewski, S. Jung, P. Ruch, N. Prasad, S. Mazzotti, B. Michel, and D. Poulikakos, Lab Chip 15(8), 1923–1933

    (2015).48H. Cottet, J.-P. Biron, and M. Martin, Analyst 139(14), 3552–3562 (2014).

    044112-12 Liu et al. Biomicrofluidics 12, 044112 (2018)

    https://doi.org/10.1021/ac0354600https://doi.org/10.1021/ac0610309https://doi.org/10.1038/nmeth.1248https://doi.org/10.1038/nm869https://doi.org/10.1021/nl070966+https://doi.org/10.1016/j.bios.2015.10.024https://doi.org/10.1073/pnas.1006911107https://doi.org/10.1016/j.talanta.2016.05.005https://doi.org/10.1021/acsnano.5b00396https://doi.org/10.1080/07388550802688847https://doi.org/10.1038/nbt0898-743https://doi.org/10.1021/acsami.7b00418https://doi.org/10.1073/pnas.0905299106https://doi.org/10.1038/82717https://doi.org/10.1038/nm821https://doi.org/10.1038/ni0901-842https://doi.org/10.1016/j.ymeth.2005.11.006https://doi.org/10.1158/0008-5472.CAN-05-0938https://doi.org/10.1016/j.ymeth.2005.11.010https://doi.org/10.1039/C6LC00615Ahttps://doi.org/10.1103/PhysRevLett.102.158103https://doi.org/10.1007/s10544-008-9226-zhttps://doi.org/10.1021/ac0516988https://doi.org/10.1038/nature05058https://doi.org/10.1021/acsami.7b03021https://doi.org/10.1039/C6LC00647Ghttps://doi.org/10.1039/b305892ahttps://doi.org/10.1021/ac000850xhttps://doi.org/10.1021/ac035220khttps://doi.org/10.1039/b926849ahttps://doi.org/10.1016/j.bios.2006.06.005https://doi.org/10.1039/b913806dhttps://doi.org/10.1039/b811075ahttps://doi.org/10.1016/j.snb.2004.07.003https://doi.org/10.1039/b107540nhttps://doi.org/10.1016/j.bios.2010.02.032https://doi.org/10.1016/j.snb.2014.11.115https://doi.org/10.1016/j.aca.2012.09.007https://doi.org/10.1097/00001432-200306000-00004https://doi.org/10.1039/C7LC01183Khttps://doi.org/10.1042/cs1020403https://doi.org/10.1016/S0898-6568(01)00152-8https://doi.org/10.1016/S0091-6749(03)01868-2https://doi.org/10.1073/pnas.0605988103https://doi.org/10.1039/C6LC00072Jhttps://doi.org/10.1007/s10404-015-1596-yhttps://doi.org/10.1039/C5LC00045Ahttps://doi.org/10.1039/C4AN00192C

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