This project was supported by grant #2021-349 of the Strategic Focus Area Personalized Health and Related Technologies (PHRT) of the ETH Domain (Swiss Federal Institutes of Technology), the European Research Council starting grant (grant #803,336), and the Swiss National Science Foundation (grant #310030_197619). Additionally, we thank Guilhem Chenon and Jean Baudry for their work and development of the initial DropMap analyzer.

Microfluidic Droplet Assay for Single-Cell Cytokine Secretion Analysis

<ol>
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Specific aspects such as the beadline measurements of cells have been patented.

Cytokine release and secretion are frequently investigated in immunology and clinical medicine3. Unbalanced cytokine secretion can lead to detrimental effects for patients suffering from infections but also in neurological disease, inflammation, or cancer26,27,28. Even though their importance in health and disease is well established, studying cytokines and their secreting cells remains challenging as the current methodologies are not capable of accurately detecting and quantifying cytokines originating from a single cell in a time-resolved manner. For the workflow presented here, an established stimulation protocol with PBMC was used and their secretion of IL-6, TNF-&#945; and IL-1&#946; was measured. The choice of using PBMCs instead of individual, purified subpopulations stemmed from the previous application to investigate cytokine release syndromes (CRS)23, a condition characterized by highly elevated plasma concentrations of pro-inflammatory cytokines, including IL-6, TNF-&#945; and IL-1&#946;29. As CRS is usually not only linked to one population, we used PBMCs as they would be present in vivo. However, cellular subpopulations can be purified and assessed individually, if the scientific question demands this step. The incubation time, stimulation conditions and dynamic assay ranges were optimized to measure secretion for the three cytokines of interest. The workflow and data presented here demonstrate how to set up, calibrate, quantify, measure, and analyze time-resolved single-cell secretion of multiple cytokines. This protocol provides a blueprint on how multi-functional analysis of cytokine secretion could enable the large functional and dynamic diversity of the cytokine secreted in patients.
Several crucial aspects of the described assay protocol enable a unique biological readout. First, single-cell encapsulation in microfluidic droplets allowed the extraction of data for each individual cell. Events of multiple cell encapsulations can be detected and sorted in or out by image analysis, depending on the research question. Second, the inclusion of several independent in-droplet fluorescent immunoassays and the alignment of the functionalized nanoparticles allowed for the quantitative measurement of up to three cytokine concentrations in parallel. This multiplexing enabled the analysis of cytokine co-secretion patterns on a single-cell level. Third, immobilization of the droplets permitted the time-wise measurement and correlation of cytokine secretion for each secreting cell and allowed to distinguish co-occurrent from sequential secretion. The time resolution uniquely provided data on secretion patterns and subpopulations of different secretor types. Finally, parallelized image analysis enabled the efficient extraction and tracking of large amounts of data from measurements with over 20,000 individual cells. The extraction from single secretion curves further permitted the discovery of phenotypic subpopulations and functionalities.
Next to its unique readout, the assay also has technical advantages over standard cytokine analysis. Thanks to the small size of the encapsulation compartments of around 60 pL, absolute amounts of secreted cytokines can be detected directly from the biological source with detection limits fitting cell secretion. The assay miniaturization also uses smaller quantities of expensive bio-reagents. Furthermore, the setup requires very little specialized equipment, which is often already available in biology and bioengineering laboratories. Fluorescence microscopes are broadly available, and syringe pumps are frequently used in bioengineering laboratories or can be purchased at a relatively low cost. If a cell culture is present, the cost for the full equipment needed to run the experiments is around 148,000 Euros, with the majority contributed by the automated epifluorescent microscope (130,000 Euros). However, such an instrument can be often found in biological laboratories, and the rest of the cost is distributed to the syringe pump (13,000 Euros, but cheaper alternatives are available) and smaller equipment. The fabrication of the droplet chip and observation chamber is very well described17 and can be performed outside of a cleanroom environment with necessary infrastructure, such as ovens and plasma cleaners present in most bioengineering labs. Alternatively, different suppliers are available to supply interested laboratories with droplet generator chips. Due to the small volumes needed, the assay is cost-effective and simple to set up.
The ensure the highest degree of reproducibility, we identified some critical steps for the success of the protocol. A common problem for first-time users is droplet movement during the measurement. While the analysis software can track individual droplets to some degree, excessive movement leads to loss of single-cell resolution and inaccurate results. Movement can be avoided by using properly airtight measurement chambers, correct droplet size and chamber sizes, a short equilibration period before starting the measurement, and proper surfactant concentration. Another critical step is accurate focusing before starting the measurement. Improper focusing leads to significantly lowered fluorescence relocation values and the underestimation of the amount of secreted cytokine. Finally, depending on the question and protocol at hand, correct timing between the different steps is of utmost importance for reproducibility. Especially the waiting time between filling the chamber and starting the measurement should be consistent, otherwise the measurement window of the secreted cytokines might be missed.
Limitations of the presented technology include the restricted ability to further manipulate the cells after encapsulation. It is therefore currently not possible to add or remove stimulants, antibodies, or additional reagents. Additionally, since the cells are encapsulated in their isolated bioreactor, no interactions between cells (contact-based or paracrine signaling) can take place during the measurement. This limitation can be partially overcome with bulk incubations beforehand. Besides, enhanced autocrine effects from secreted cytokines are also possible and these effects cannot be quantified or excluded with certainty, as only antibody-detected secreted cytokines are measured. So, the isolated view on cytokine secretion must always be described in the context of the corresponding question and application. However, this limitation could also be used for the detailed study of encapsulated multiples, doublets, and triplets if of interest. This would provide an interesting setup useful to investigate cell-cell contact or paracrine-based questions. Lastly, also the dynamic range of the assay is limited and needs adaptation to the specific application. Here, we have adapted the dynamic range of the assay to the expected secreted amount of the measured cytokines.
To further advance the capabilities and applicability of the assay, several developments could be addressed in the future, in biological, technical and data analysis aspects. On the biological side, the measurement of additional cytokines, other secreted proteins, metabolic or cell surface markers could be integrated by adapting the assay. Furthermore, this assay could be integrated into a workflow alongside other cell-based assays to broaden the readouts (e.g., flow cytometry staining or sequencing). Additionally, the usability of the assay could be simplified, e.g., by creating an integrated microfluidic chip for droplet creation and observation, thereby potentially enabling a wider application outside bioengineering laboratories in a clinical setting. Regarding the data analysis, extraction and tracking of information from images could be extended by enhancing automation and using machine learning approaches, e.g., to detect the presence and position of the cell(s) and beadline in each droplet without fluorescent labeling. Doing so would open additional fluorescent channels that could be used for immunoassays, resulting in the measurement of even more cytokines in parallel.
The presented assay and the associated protocols and analysis can be applied for diverse potential use cases related to cytokine secretion dynamics. More specifically, the assay could potentially address fundamental immunological questions such as identifying cell-type and activation-specific cytokine-secretion profiles, polyfunctionality of cytokine-secreting cells, or the temporality and maintenance mechanisms of cytokine balances. Furthermore, in clinical applications, the platform might enable the unraveling of the role of cytokines during active or chronic inflammatory responses, as observed in COVID-1930, or provide a tool for stratifying patients and personalizing treatments based on unique signatures such as in autoinflammation31. In conclusion, quantitative time-resolved assessment of cytokine secretion from single cells is a much-needed method as it elucidates how a particular drug, infection, genetic alteration, or ex vivo stimulation induces a particular response.

Infections often cause complex host reactions involving the innate and adaptive immune systems1,2. Upon infection or recognition of infectious agents, host cells can produce a diverse range of chemo- and cytokines, which are small proteins known as critical communicators and modulatory of the immune system3. Pro-inflammatory cytokines are released early upon infection to initiate the immune response, followed later on by anti-inflammatory cytokines, which are critical to prevent tissue damage and subsequent chronic or autoinflammatory diseases. This balance between threat elimination and tissue protection manifests as a wide repertoire of cytokines exerting different functions during the infection, allowing for a fine-tuning of the response4,5. Within this mixture, unique signatures can be observed depending on the pathogen and the signals they induce, the tissue location, and the immune cells from which they originate. However, cytokine release also appears to constitute a multi-functional biological process unique to each cell population, diverse in secretion dynamics and individual response. This heterogeneity has been described in the literature for many years, for instance, among T-cell subpopulations6,7, where investigations into autoinflammatory diseases and severe COVID-19 infections exhibited a large functional diversity of inflammatory markers within and in between patients8,9. Lately, the advent of single-cell sequencing highlighted the high plasticity and crosstalk between subpopulations within immune microenvironments that were not previously apparent, indicating that single-cell methods are necessary to capture this heterogeneity10,11. While novel methods are being developed to analyze the transcriptome, phenotypic analysis remains challenging, as this requires simultaneous, quantitative, and time-resolved measurements of protein secretion on a single-cell level. Such measurements allow us to investigate secreting cell identities, dynamics, and secretion patterns (slow/fast, early/late, simultaneous/sequential) for a repertoire or a panel of cytokines. By enabling the study of the dynamics of cytokine release during an immune response quantitatively and with temporal resolution, the resulting insights might allow for an understanding of the cellular ensemble and the induced response.
In standard protocols, cytokines are usually detected in the supernatant of cell suspensions and serum using enzyme-linked immunosorbent assay (ELISA), yielding bulk-secreted amounts. Bulk measurements do not allow for quantification of the cytokine amounts produced by each cell, a problem especially highlighted in heterogeneous cell samples. Alternative methods such as intracellular cytokine staining, enzyme-linked immunospot (ELISpot) assay or micro-engraved assays (e.g., Isoplexis) detect cytokines expressed by individual cells but provide endpoint measurements only12,13. This means that secretion dynamics and changes that might happen in the cellular secretion pattern over the incubation time are ignored. Additionally, endpoint measurements cannot differentiate between simultaneous and sequential cytokine secretion, so the true extent of simultaneous polyfunctionality of immune cells in cytokine secretion remains unclear using these methods.
Single-cell resolution can be achieved using droplet microfluidics to generate and process picoliter-sized physical compartments in order to study immune cells on their unique cytokine secretion phenotypes on the single-cell level14,15. These compartments consist of water-in-oil emulsions and can be generated using microfluidic chips16,17. Indeed, droplet-based microfluidic assays have demonstrated extreme versatility in enabling the analysis of different biological samples and repertoires on the single-cell level and their integration with upstream (cell and reagent processing) and downstream processes (single-cell sorting, proteomics or sequencing)18,19,20,21,22. In particular, setups that permit droplet immobilization allow for the measurement of a single-cell functionality over time, which is valuable for the analysis of protein secretion18. Furthermore, integrating multiplexed, quantitative assays facilitates additional investigations in previously inaccessible dimensions, into processes such as co-secretion and the identification of polyfunctional immune cells23,24.
In this protocol, we describe an immobilized droplet-based single-cell workflow to detect, quantify and temporally measure the secretion of up to three cytokines in parallel from individual cells17,23. The technology offers the ability to monitor cytokine responses from over 20,000 cells in parallel.
The presented workflow consists of the microfluidic encapsulation of single immune cells and functionalized nanoparticles into 60 pL water-in-oil droplets. The immobilization of &#62;100,000 droplets in an observation chamber and time-resolved fluorescence microscopy allow for the measurement of cytokine secretion dynamics within each droplet and each cytokine (Figure 1A). For each individual cell within a droplet, the cytokine secretion is measured by a sandwich immunoassay, where magnetic nanoparticles functionalized with a specific capture antibody bind the secreted cytokine, leading to the subsequent relocation and binding of fluorescently labeled detection antibodies (Figure 1B,C). A beadline is formed by aligning the magnetic nanoparticles, to which fluorescence relocation can be quantified in the presence of cytokine. Here, fluorescence relocation is defined as the average fluorescence intensity found on the beadline divided by the average fluorescence intensity of the remaining droplet. This assay can be multiplexed for several cytokines by mixing differently functionalized nanoparticle batches and respective detection antibodies labeled in different fluorescence channels23, resulting in specific fluorescence relocations in the different channels. With the help of a customized analysis script, fluorescence relocation values can be extracted, and the images can be converted into secretion dynamic profiles for every individual cell and cytokine. Therefore, the resulting datasets yield numerous readouts, such as the quantitative secretion measurement over time, the identification of co-secreting subpopulations, and the distributions of the cells according to secreted amounts, rates, and combinations of cytokines.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/66492/66492fig01.jpg" /> 
Figure 1: Workflow and assay principle. (A) Overview of the workflow for analyzing&#160;cytokine-secreting cells after stimulation. Single-cell suspensions and magnetic nanoparticles are prepared and encapsulated into 60 pL in volume oil/water emulsions (droplets). Droplets are immobilized and nanoparticles aligned inside a magnetic field before measurement for up to 4 h every 30 min. Finally, images are analyzed, and the parameters for every droplet, timepoint and fluorescent channel are extracted. This figure has been modified from17. (B) Principle of the droplet sandwich bioassay. Functionalized nanoparticles bind the secreted cytokines, which leads to the subsequent relocation of fluorescently labeled detection antibodies to the nanoparticles. This relocation of fluorescence is quantified and validated with calibration experiments performed with recombinant cytokines. Mixing different functionalized nanoparticles allows the multiplexed measurements of up to three cytokines simultaneously. (C) In cell-based experiments, droplets are followed over the measurement time and secreting cells are identified by an overtime increase of fluorescence relocation onto the nanoparticles. Schematics are not up to scale. Figure created with BioRender.com. <a href="https://www.jove.com/files/ftp_upload/66492/66492fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

<table><tbody><tr><td>008-FluoroSurfactant</td><td>RAN Biotechnologies</td><td>008-FluoroSurfactant-10G</td><td></td></tr><tr><td>2-Stream flow-focusing droplet maker, 30 &amp;micro;m nozzle, PFOS hydrophobic surface treatment</td><td>Wunderli chips</td><td></td><td></td></tr><tr><td>Alexa Fluor 647 NHS Ester&amp;nbsp;</td><td>ThermoFisher</td><td>A20006</td><td>https://www.thermofisher.com/ch/en/home/references/protocols/cell-and-tissue-analysis/labeling-chemistry-protocols/fluorescent-amine-reactive-alexa-fluor-dye-labeling-of-igm-antibodies.html</td></tr><tr><td>Anti-Human IL-1&amp;beta; (Monoclonal Mouse), AF647 labelled in-house</td><td>PeproTech</td><td>500-M01B</td><td></td></tr><tr><td>ARcare92524 double-sided adhesive tape</td><td>Adhesvies Reasearch</td><td>ARcare92524</td><td></td></tr><tr><td>Bio-Adembeads Streptavidin plus 300nm</td><td>Ademtech</td><td>Cat#03233</td><td></td></tr><tr><td>Biotinylated Goat Anti-Human IL-1&amp;beta;</td><td>PeproTech</td><td>500-P21BGBT</td><td></td></tr><tr><td>Bovine Serum Albumin (BSA)</td><td>Sigma-Aldrich</td><td>A3059</td><td></td></tr><tr><td>Cell Scraper</td><td>TPP</td><td>99002</td><td></td></tr><tr><td>CellTrace Violet Cell Proliferation Kit</td><td>Invitrogen</td><td>C34557</td><td>Cell staining solution</td></tr><tr><td>Chromafil Xtra PTFE-45/25 syringe filters</td><td>Macherey-Nagel</td><td>729205</td><td></td></tr><tr><td>Costar 6-well Clear Flat Bottom Ultra-Low Attachment</td><td>Corning</td><td>3471</td><td></td></tr><tr><td>Countess Cell Counting Chamber Slides</td><td>Invitrogen</td><td>C10283</td><td></td></tr><tr><td>D-Biotin</td><td>Fluorochem</td><td>M02926</td><td></td></tr><tr><td>DPBS, no calcium, no magnesium</td><td>Gibco&amp;nbsp;</td><td>14196-094</td><td></td></tr><tr><td>epT.I.P.S.&amp;nbsp;Standard 2-200 &amp;micro;l</td><td>Eppendorf</td><td>30000889</td><td></td></tr><tr><td>Ethylenediaminetetraacetic acid disodium salt solution</td><td>Sigma-Aldrich</td><td>3690</td><td></td></tr><tr><td>EZ-LINK-NHS-PEG4-Biotin</td><td>ThermoFisher</td><td>A39259</td><td>https://www.thermofisher.com/order/catalog/product/20217</td></tr><tr><td>FcR Blocking Reagent, human</td><td>Miltenyi Biotec</td><td>130-059-901</td><td></td></tr><tr><td>Fetal Bovine Serum</td><td>Gibco&amp;nbsp;</td><td>10270-106</td><td></td></tr><tr><td>Handy dish soap</td><td>Migros</td><td>5.01002E+11</td><td></td></tr><tr><td>HEPES (1 M)</td><td>Gibco&amp;nbsp;</td><td>15630-080</td><td></td></tr><tr><td>HFE-7500 Oil 3M TM Novec</td><td>Fluorochem</td><td>B40045191</td><td></td></tr><tr><td>Idex F-120 Fingertight One-Piece Fitting, Standard Knurl, Natural PEEK, 1/16&quot; OD Tubing, 10-32 Coned</td><td>Cole-Parmer</td><td>GZ-02014-15</td><td></td></tr><tr><td>IL-6 Monoclonal Antibody (MQ2-13A5 - Rat), FITC</td><td>ThermoFisher</td><td>11-7069-81</td><td></td></tr><tr><td>IL-6 Monoclonal Antibody (MQ2-39C3), Biotin</td><td>ThermoFisher</td><td>13-7068-85</td><td></td></tr><tr><td>KnockOut Serum Replacement</td><td>ThermoFisher</td><td>10828-010</td><td></td></tr><tr><td>Loctite AA 3491 curable UV glue</td><td>Henkel AG &amp;amp; Co</td><td>3491</td><td></td></tr><tr><td>Microscope slides (76x26x1mm, clear white)</td><td>Menzel Gl&amp;auml;ser</td><td></td><td></td></tr><tr><td>Mineral oil light</td><td>Sigma-Aldrich</td><td>330779</td><td></td></tr><tr><td>NanoPort Assembly Headless, 10-32 Coned, for 1/16&quot; OD</td><td>Idex</td><td>N-333</td><td></td></tr><tr><td>Neodymium block magnet</td><td>K&amp;amp;J Magnetics</td><td>BZX082</td><td></td></tr><tr><td>Omnifix-F Spritze, 1 ml, LS</td><td>Braun</td><td>9161406V</td><td></td></tr><tr><td>Penicillin-Streptomycin (10,000 U/mL)</td><td>Gibco&amp;nbsp;</td><td>15140-122&amp;nbsp;</td><td></td></tr><tr><td>Phosphate buffered saline</td><td>Sigma-Aldrich</td><td>P4417</td><td></td></tr><tr><td>Pluronic F-127, 0.2 &amp;micro;m filtered (10% Solution in Water)</td><td>ThermoFisher</td><td>P6866</td><td></td></tr><tr><td>Precision wipes</td><td>Kimtech Science</td><td>5511</td><td></td></tr><tr><td>PTFE microtubing 0.30 &amp;times; 0.76 mm</td><td>FisherScientific</td><td>1191-9445</td><td></td></tr><tr><td>PTFE microtubing 0.56 &amp;times; 1.07 mm</td><td>FisherScientific</td><td>1192-9445</td><td></td></tr><tr><td>Recombinant Human IL-1&amp;beta;</td><td>Peprotech</td><td>Cat#200-01B</td><td></td></tr><tr><td>Recombinant Human IL-6</td><td>Peprotech</td><td>Cat#200-06</td><td></td></tr><tr><td>Recombinant human serum albumine (HSA)</td><td>Sigma-Aldrich</td><td>A9731</td><td></td></tr><tr><td>Recombinant Human TNF-&amp;alpha;</td><td>Peprotech</td><td>Cat#300-01A</td><td></td></tr><tr><td>Reusable biopsy punch diameter 0.75 mm and 6 mm</td><td>Stiefel</td><td>&amp;nbsp;504529 and 504532</td><td></td></tr><tr><td>RPMI 1640 Medium, no phenol red</td><td>Gibco</td><td>11835-030</td><td></td></tr><tr><td>Standard LPS, E. coli K12</td><td>InvivoGen</td><td>tlrl-eklps</td><td></td></tr><tr><td>Sterican needles 23 G for 0.56 mm diameter microtubing</td><td>FisherScientific</td><td>15351547</td><td></td></tr><tr><td>Sterican needles 27 G for 0.30mm diameter microtubing</td><td>FisherScientific</td><td>15341557</td><td></td></tr><tr><td>TNF alpha Monoclonal Antibody (MAb11), PE</td><td>ThermoFisher</td><td>12-7349-81</td><td></td></tr><tr><td>TNF-alpha Monoclonal Antibody (MAb1), biotinylated in-house</td><td>ThermoFisher</td><td>14-7348-85</td><td></td></tr><tr><td>Trypan Blue Stain (0.4%) for use with the Countess Automated Cell Counter</td><td>Invitrogen</td><td>T10282</td><td></td></tr><tr><td>Vacuum Filtration &quot;rapid&quot;-Filtermax</td><td>TPP</td><td>99500</td><td></td></tr><tr><td>Devices</td><td></td><td></td><td></td></tr><tr><td>Cameo 4 automatic cutting machine</td><td>Silhouette</td><td></td><td></td></tr><tr><td>Cetoni Base 120 + 3x NEMESYS Low Pressure Syringe Pumps</td><td>Cetoni</td><td>NEM-B101-03 A</td><td></td></tr><tr><td>Countess II Automated Cell Counter</td><td>ThermoFisher</td><td></td><td></td></tr><tr><td>Inverted Epi-fluorescence microscope Ti2</td><td>Nikon</td><td>ECLIPSE Ti2-E, Ti2-E/B*1</td><td></td></tr><tr><td>OKO Lab Cage Incubator, dark panels</td><td>OKO Lab</td><td></td><td></td></tr><tr><td>ORCA-Fusion Digital CMOS camera</td><td>Hammatsu</td><td>C14440</td><td></td></tr><tr><td>SOLA Light Engine</td><td>Lumencor</td><td>sola 80-10247</td><td></td></tr></tbody></table>

microfluidic approach to resolve simultaneous and sequential cytokine secretion of individual polyfunctional cells

Infections, autoimmune diseases, desired and adverse immunological responses to treatment can lead to a complex and dynamic cytokine response in vivo. This response involves numerous immune cells secreting various cytokines to orchestrate the immune reaction. However, the secretion dynamics, amounts, and co-occurrence of the different cytokines by various cell subtypes remain poorly understood due to a lack of appropriate tools to study them. Here, we describe a protocol using a microfluidic droplet platform that allows the time-resolved quantitative measurement of secretion dynamics for several cytokines in parallel on the single-cell level. This is enabled by the encapsulation of individual cells into microfluidic droplets together with a multiplexed immunoassay for parallel quantification of cytokine concentrations, their immobilization for dynamic fluorescent imaging, and the analysis of the respective images to derive secreted quantities and dynamics. The protocol describes the preparation of functionalized magnetic nanoparticles, calibration experiments, cell preparation, and the encapsulation of the cells and nanoparticles into droplets for fluorescent imaging and subsequent image and data analysis using the example of lipopolysaccharide-stimulated human peripheral blood mononuclear cells. The presented platform identified distinct cytokine secretion behavior for single and co-secreting cells, characterizing the expected phenotypic heterogeneity in the measured cell sample. Furthermore, the modular nature of the assay allows its adaptation and application to study a variety of proteins, cytokines, and cell samples, potentially leading to a deeper understanding of the interplay between different immune cell types and the role of the different cytokines secreted dynamically to shape the tightly regulated immune response. These new insights could be particularly interesting in the studies of immune dysregulations or in identifying target populations in therapy and drug development.

The presented functional single-cell platform allowed the measurement of several parameters. First, and similar to standard techniques, the frequency of secreting cells is depicted at the end of the measurement (Figure 4A). Following the stimulation with 1 &#181;g/mL of lipopolysaccharide (LPS) for 6 h of peripheral blood mononuclear cells (PBMC), 5.81% of the cells secreted IL-6 (n= 1270), 4.55% TNF&#945; (n= 995) and 6.06% IL-1&#946; (n= 1326).
To quantify the cytokine secretion, calibration curves were generated with known concentrations of recombinant cytokines (Figure 4B). These calibration curves allow the quantification of the in-droplet cytokine concentrations over time. Exemplarily, the average in-droplet IL-6 concentration reached a plateau after 90 min for LPS-stimulated PBMC, whereas the average in-droplet IL-1&#946; increased more rapidly from 90 min, displaying the dynamic resolution of the platform and the possibility to extract cell subpopulations secreting specific cytokines (Figure 4C). As the concentration changes between measurement points, calculating dynamic secretion rates per cytokine is possible. Considering the average secretion rate for each cytokine (Figure 4D), IL-6 secreting cells exhibited a constant decrease in average secretion rate, while TNF&#945; and IL-1&#946; secreting cells both showed an increase in secretion rate after 90 min measurement time and a second decrease after 150 min.
Furthermore, it is possible to cluster cells into subpopulations depending on the secreted and co-secreted cytokines (Figure 4E). Here, IL-6 and TNF&#945; are single-secreted by 30.2% and 26.4% of the cells secreting IL-6 or TNF&#945;, respectively, whereas single-secreting IL-1&#946; cells made up 68.8% of all IL-1&#946; secreting cells. Additionally, the effects of co-secretion on secreted concentrations and secretion rates can be resolved (Figure 4F). By looking at IL-6-secreting cells, different amounts of IL-6 were secreted if the cells additionally produced TNF&#945; or IL-1&#946;. Similarly, the distribution of averaged secretion rates over the measurement statistically differed between the cells secreting only IL-6 or IL-6 alongside TNF&#945; (higher secretion rates) and IL-1&#946; (lower IL-6 secretion rates).
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/66492/66492fig04.jpg" /> 
Figure 4: Representative results of IL-6, TNF&#945; and IL-1&#946; secreting PBMC after 6 h stimulation with 1 &#181;g/mL LPS. (A) Percentage of PBMC secreting IL-6, TNF&#945; and IL-1&#946; at the end of the 4 h measurement. (B) Multiplexed cytokine calibration curves are generated with known concentrations of recombinant cytokines. This allows the quantification of cell experiments by computing from the relocation value the cytokine concentration within the droplet. Points were fitted using a non-linear one-phase association curve fit, r2=0.9926 (IL-6), 0.9901 (TNF&#945;), 0.9990 (IL-1&#946;). (C) Average secreted concentrations of IL-6, TNF&#945; and IL-1&#946; released by secreting PBMC over the 4 h measurement time. (D) Average secretion rates of IL-6, TNF&#945; and IL-1&#946; over the 4 h measurement time. (E) Relative percentage of co-secreting cells secreting IL-6, TNF&#945; or IL-1&#946; and combinations thereof. Normalized to all of the secreting cells detected for each cytokine. (F) Averaged IL-6 concentrations over the measurement time and average secretion rate (log) distributions for IL-6 secreting cells with co-secretion resolution (n=383 for IL-6 only, n=531 for IL-6 + TNF&#945;, n= 213 for IL-6 + IL-1&#946; and n=143 for IL-6+TNF&#945;+IL-1&#946;). Statistical differences in secretion rate distributions were assessed using two-sided, unpaired, nonparametric Kolmogorov-Smirnov tests with 95% confidence, the p-value are represented. ** (p &#60;0.002) and **** (p &#60;0.0001). The full line represents the median and the dotted line the quartiles. ntotal cells = 21 866. <a href="https://www.jove.com/files/ftp_upload/66492/66492fig04large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
To extract additional information on the single-cell level, a sigmoid function can be fitted to the concentration-time points of each cell and cytokine (Figure 5). An exemplary concentration over time dataset for one cell and the corresponding sigmoidal fit is depicted in Figure 5A. Here, the least squares fitting procedure yields the following parameters: C, corresponding to the upper plateau value of the curve, t50 quantifying the time-wise shift of the curve from zero, and the Hill slope m, describing the steepness of the rising part of the sigmoid curve with 10% and 90% concentration values reached throughout the measurement. From these fit parameters, some curve descriptors can be extracted as explained in step 7.12. yielding the Cmax, the highest concentration value of the data, tstart, the start time of secretion, defined as reaching 10% of the upper plateau concentration value, and SRlin, the secretion rate during the rising part of the curve.
To classify cell subpopulations, the curve descriptors obtained from all single-cell fits were classified into three categories each: Cmax values were grouped into low, medium, and high for tstart into early, medium, and late an SRlin into slow, medium and fast secretors. To illustrate this classification, four exemplary single-cell secretion curves and their corresponding curve descriptors are shown (Figure 5A-D), where curve A exhibits the characteristics of an early low secretor of medium rate, curve B is an early, slow, and high secretor, curve C an early fast high secretor, and curve D shows late low secretion. It is important to note that the cutoffs for these criteria are cell-, cytokine-, and assay parameter-specific, and need to be adapted for each research question. Furthermore, only IL-6 secretion of PBMC after 1 &#181;g/mL LPS stimulation for 6 h was considered here, meaning that most cells were early and high secretors with 80% and 79%, respectively (Figure 5E-F). Regarding the secretion rate, a bipolar response was observed with 55% of IL-6 secreting cells are slow secretors and 39% as fast secretors (Figure 5G).
To further characterize secretion behavior, the curve descriptors for each cell were plotted against each other and different clusters were extracted (Figure 5H-J). No clear correlation is given between tstart and Cmax (Figure 5H): the two largest populations were early low secretors and high secretors independent of secretion start. Considering the relation between tstart and SRlin (Figure 5I), most cells were early slow secretors with a clear population of early high secretors and few slow/medium to late secretors. Regarding SRlin and Cmax (Figure 5J) correlations, almost no fast low to medium secretors were present, with only a bigger population of fast low secretors. Furthermore, there was a large population of fast secretors that did not depend on the maximal measured concentration, and two populations of high secretors secreted either slow or fast. In summary, it can be concluded that investigating the relationship between the curve descriptors for individual cells yields a much more detailed analysis and can potentially extract new biological findings from single-cell secretion measurements.
With the analysis introduced above, we extracted the secretion dynamics of co-secreting cells (Figure 6). Two example curves show different dynamics of co-secretion for IL-6 and TNF&#945; from two single cells with a simultaneous start of both cytokines (Figure 6A), or a sequential secretion start, with IL-6 being secreted first (Figure 6B). To classify all co-secreting cells, a secretion delay of 60 min was defined, where all cells starting secretion within this range are considered simultaneous secretors and all cells with longer delays are considered sequential secretors. This analysis also allowed the possibility to observe which cytokine was secreted first. For IL-6 and TNF&#945;, mainly simultaneous co-secretion was observed in 76% of the cells (Figure 6C), while for IL-6 and IL-1&#946;, sequential co-secretion was observed in 86% of the cells with IL-6 being the first cytokine to be secreted in most cases (Figure 6D).
Looking at the starting time of secretion for the different cytokines for all individual co-secreting cells, no clear correlation between secretion starting times was observed in the performed experiments. For IL-6 and TNF&#945; co-secretion (Figure 6E), a larger vertical cluster around 0 min was present, corresponding to the co-secreting cells more prevalently starting with IL-6. For IL-6 and IL-1&#946; co-secretion (Figure 6F), most cells started secreting IL-6 around the start of the measurement, while IL-1&#946; was mainly secreted later. In summary, the analysis presented here enabled the identification of different secretor sub-populations and complex cytokine co-secretion dynamics.
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/66492/66492fig05.jpg" /> 
Figure 5: Detailed analysis of different secretion dynamic patterns for single IL-6 secreting cells curves. (A) Representative single-cell cytokine concentration data over measurement time with the fitted sigmoid curve and the extracted parameters. (B-D) Three exemplary single-cell cytokine concentration curves for the different cytokine secretor types found for IL-6 secretion after LPS stimulation. (E-G) Percentages of IL-6 secreting cells that are classified into the different secretor types with the following criteria (n=633): E. Cmax: low &#60;5 nM, high &#62;19.5 nM, F. tstart: early &#60;30 min, late &#62;120min, G. SRlin: slow &#60;250 molecules/s, fast &#62;750 molecules/s. (H-J) Relation between the three secretion curve descriptors Cmax, tstart and SRlin for each individual cell (n=633). The large population at Cmax=20nM results from reaching the upper detection limit of the assay. <a href="https://www.jove.com/files/ftp_upload/66492/66492fig05large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/66492/66492fig06v2.jpg" /> 
Figure 6: Extraction of co-secretion patterns from single-cell concentration curves. (A-B) Representative concentration curves for single cells co-secreting IL-6 and TNF&#945; (A) simultaneously and (B) sequentially, respectively. (C-D) Percentage of cells exhibiting simultaneous and sequential co-secretion of IL-6 and TNF&#945; (n=249), or IL-6 and IL-1&#946; (n=72), respectively. Sequential secretion is defined through the delay between cytokine secretion starts of more than 60 min. Colors indicate which of the cytokines started secretion first. (E-F) Relation between the secretion start times for the different cytokines for each secreting cell (nIL6-TNF&#945;=249, nIL6-IL1&#946;=72). <a href="https://www.jove.com/files/ftp_upload/66492/66492fig06largev2.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Read this Scientific Article Protocol about Author Spotlight: Unveiling the Polyfunctionality and Heterogeneity in Immune Responses at JoVE.com

Author Spotlight: Unveiling the Polyfunctionality and Heterogeneity in Immune Responses

The protocol describes an advanced microfluidic platform to quantitatively measure cytokine secretion dynamics of individual human peripheral blood mononuclear cells. The platform measures up to three cytokines in parallel (IL-6, TNF&#945;, and IL-1&#946;) for each individual cell stimulated with lipopolysaccharide as an example.

Microfluidic Approach to Resolve Simultaneous and Sequential Cytokine Secretion of Individual Polyfunctional Cells

Infections, autoimmune diseases, desired and adverse immunological responses to treatment can lead to a complex and dynamic cytokine response in vivo. ...

microfluidic-approach-to-resolve-simultaneous-sequential-cytokine

Research

JoVE Journal

Immunology and Infection

1.6K Views.  ETH Zürich. In dit project richten we ons op het ontwikkelen en toepassen van nieuwe analytische strategieën, die de directe, kwantitatieve en diepgaande analyse van cellulaire functionaliteiten met een resolutie van één cel mogelijk maken. En dus, door verder te gaan dan pure meting van één datapunt, willen we deze multifunctionaliteit, die voortkomt uit complexe reacties in de gastheer en in weefsel, beter begrijpen en benutten. Het verkrijgen van een volledig beg...

Video: Auteur in de schijnwerpers: onthulling van de polyfunctionaliteit en heterogeniteit in immuunresponsen

On-Chip Endothelial Inflammatory Phenotyping

Atherogenesis is potentiated by metabolic abnormalities that contribute to a heightened state of systemic inflammation resulting in endothelial dysfunction. However, early functional changes in endothelium that signify an individual's level of risk are not directly assessed clinically to help guide therapeutic strategy. Moreover, the regulation of inflammation by local hemodynamics contributes to the non-random spatial distribution of atherosclerosis, but the mechanisms are difficult to delineate in vivo. We describe a lab-on-a-chip based approach to quantitatively assay metabolic perturbation of inflammatory events in human endothelial cells (EC) and monocytes under precise flow conditions. Standard methods of soft lithography are used to microfabricate vascular mimetic microfluidic chambers (VMMC), which are bound directly to cultured EC monolayers.1 These devices have the advantage of using small volumes of reagents while providing a platform for directly imaging the inflammatory events at the membrane of EC exposed to a well-defined shear field. We have successfully applied these devices to investigate cytokine-,2 lipid-3, 4 and RAGE-induced5 inflammation in human aortic EC (HAEC). Here we document the use of the VMMC to assay monocytic cell (THP-1) rolling and arrest on HAEC monolayers that are conditioned under differential shear characteristics and activated by the inflammatory cytokine TNF-&alpha;. Studies such as these are providing mechanistic insight into atherosusceptibility under metabolic risk factors.

Microfluidic flow chambers etched by photolithography and fabricated from PDMS are applied to probe functional outcomes associated with EC dysfunction and inflammation. In a representative experiment, the ability of differential shear stress to modulate monocytic cell adhesion to cytokine activated EC monolayers is demonstrated.

Atherogenesis is potentiated by metabolic abnormalities that contribute to a heightened state of systemic inflammation resulting in endothelial ...

Bioengineering

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations

Immunophenotypic characterization and molecular analysis have long been used to delineate heterogeneity and define distinct cell populations. FACS is inherently a single-cell assay, however prior to molecular analysis, the target cells are often prospectively isolated in bulk, thereby losing single-cell resolution. Single-cell gene expression analysis provides a means to understand molecular differences between individual cells in heterogeneous cell populations. In bulk cell analysis an overrepresentation of a distinct cell type results in biases and occlusions of signals from rare cells with biological importance. By utilizing FACS index sorting coupled to single-cell gene expression analysis, populations can be investigated without the loss of single-cell resolution while cells with intermediate cell surface marker expression are also captured, enabling evaluation of the relevance of continuous surface marker expression. Here, we describe an approach that combines single-cell reverse transcription quantitative PCR (RT-qPCR) and FACS index sorting to simultaneously characterize the molecular and immunophenotypic heterogeneity within cell populations.
In contrast to single-cell RNA sequencing methods, the use of qPCR with specific target amplification allows for robust measurements of low-abundance transcripts with fewer dropouts, while it is not confounded by issues related to cell-to-cell variations in read depth. Moreover, by directly index-sorting single-cells into lysis buffer this method, allows for cDNA synthesis and specific target pre-amplification to be performed in one step as well as for correlation of subsequently derived molecular signatures with cell surface marker expression. The described approach has been developed to investigate hematopoietic single-cells, but have also been used successfully on other cell types.
In conclusion, the approach described herein allows for sensitive measurement of mRNA expression for a panel of pre-selected genes with the possibility to develop protocols for subsequent prospective isolation of molecularly distinct subpopulations.

Bulk gene expression measurements cloud individual cell differences in heterogeneous cell populations. Here, we describe a protocol for how single-cell gene expression analysis and index sorting by Florescence Activated Cell Sorting (FACS) can be combined to delineate heterogeneity and immunophenotypically characterize molecularly distinct cell populations.

Immunophenotypic characterization and molecular analysis have long been used to delineate heterogeneity and define distinct cell populations. FACS is ...

Genetics

A Versatile Automated Platform for Micro-scale Cell Stimulation Experiments

Study of cells in culture (in vitro analysis) has provided important insight into complex biological systems. Conventional methods and equipment for in vitro analysis are well suited to study of large numbers of cells (&ge;105) in milliliter-scale volumes (&ge;0.1 ml). However, there are many instances in which it is necessary or desirable to scale down culture size to reduce consumption of the cells of interest and/or reagents required for their culture, stimulation, or processing. Unfortunately, conventional approaches do not support precise and reproducible manipulation of micro-scale cultures, and the microfluidics-based automated systems currently available are too complex and specialized for routine use by most laboratories. To address this problem, we have developed a simple and versatile technology platform for automated culture, stimulation, and recovery of small populations of cells (100 - 2,000 cells) in micro-scale volumes (1 - 20 &mu;l). The platform consists of a set of fibronectin-coated microcapillaries ("cell perfusion chambers"), within which micro-scale cultures are established, maintained, and stimulated; a digital microfluidics (DMF) device outfitted with "transfer" microcapillaries ("central hub"), which routes cells and reagents to and from the perfusion chambers; a high-precision syringe pump, which powers transport of materials between the perfusion chambers and the central hub; and an electronic interface that provides control over transport of materials, which is coordinated and automated via pre-determined scripts. As an example, we used the platform to facilitate study of transcriptional responses elicited in immune cells upon challenge with bacteria. Use of the platform enabled us to reduce consumption of cells and reagents, minimize experiment-to-experiment variability, and re-direct hands-on labor. Given the advantages that it confers, as well as its accessibility and versatility, our platform should find use in a wide variety of laboratories and applications, and prove especially useful in facilitating analysis of cells and stimuli that are available in only limited quantities.

We have developed an automated cell culture and interrogation platform for micro-scale cell stimulation experiments. The platform offers simple, versatile, and precise control in cultivating and stimulating small populations of cells, and recovering lysates for molecular analyses. The platform is well suited to studies that use precious cells and/or reagents.

Study of cells in culture (in vitro analysis) has provided important insight into complex biological systems. Conventional methods and equipment for in ...

A Microfluidic Chip for the Versatile Chemical Analysis of Single Cells

We present a microfluidic device that enables the quantitative determination of intracellular biomolecules in multiple single cells in parallel. For this purpose, the cells are passively trapped in the middle of a microchamber. Upon activation of the control layer, the cell is isolated from the surrounding volume in a small chamber. The surrounding volume can then be exchanged without affecting the isolated cell. However, upon short opening and closing of the chamber, the solution in the chamber can be replaced within a few hundred milliseconds. Due to the reversibility of the chambers, the cells can be exposed to different solutions sequentially in a highly controllable fashion, e.g. for incubation, washing, and finally, cell lysis. The tightly sealed microchambers enable the retention of the lysate, minimize and control the dilution after cell lysis. Since lysis and analysis occur at the same location, high sensitivity is retained because no further dilution or loss of the analytes occurs during transport. The microchamber design therefore enables the reliable and reproducible analysis of very small copy numbers of intracellular molecules (attomoles, zeptomoles) released from individual cells. Furthermore, many microchambers can be arranged in an array format, allowing the analysis of many cells at once, given that suitable optical instruments are used for monitoring. We have already used the platform for proof-of-concept studies to analyze intracellular proteins, enzymes, cofactors and second messengers in either relative or absolute quantifiable manner.

In this article we present a microfluidic chip for single cell analysis. It allows the quantification of intracellular proteins, enzymes, cofactors, and second messengers by means of fluorescent assays or immunoassays.&#160;

We present a microfluidic device that enables the quantitative determination of intracellular biomolecules in multiple single cells in parallel. For this ...

A Pipette-Tip Based Method for Seeding Cells to Droplet Microfluidic Platforms

Amongst various microfluidic platform designs frequently used for cellular analysis, droplet-microfluidics provides a robust tool for isolating and analyzing cells at the single-cell level by eliminating the influence of external factors on the cellular microenvironment. Encapsulation of cells in droplets is dictated by the Poisson distribution as a function of the number of cells present in each droplet and the average number of cells per volume of droplet. Primary cells, especially immune cells, or clinical specimens can be scarce and loss-less encapsulation of cells remains challenging. In this paper, we present a new methodology that uses pipette-tips to load cells to droplet-based microfluidic devices without the significant loss of cells. With various cell types , we demonstrate efficient cell encapsulation in droplets that closely corresponds to the encapsulation efficiency predicted by the Poisson distribution. Our method ensures loss-less loading of cells to microfluidic platforms and can be easily adapted for downstream single cell analysis, e.g., to decode cellular interactions between different cell types.

This article presents a protocol for seeding scarce population of cells using pipette-tips to droplet microfluidic devices in order to provide higher encapsulation efficiency of cells in droplets.

Amongst various microfluidic platform designs frequently used for cellular analysis, droplet-microfluidics provides a robust tool for isolating and ...

Engineering

A Label-free Technique for the Spatio-temporal Imaging of Single Cell Secretions

Inter-cellular communication is an integral part of a complex system that helps in maintaining basic cellular activities. As a result, the malfunctioning of such signaling can lead to many disorders. To understand cell-to-cell signaling, it is essential to study the spatial and temporal nature of the secreted molecules from the cell without disturbing the local environment. Various assays have been developed to study protein secretion, however, these methods are typically based on fluorescent probes which disrupt the relevant signaling pathways. To overcome this limitation, a label-free technique is required.
In this paper, we describe the fabrication and application of a label-free localized surface plasmon resonance imaging (LSPRi) technology capable of detecting protein secretions from a single cell. The plasmonic nanostructures are lithographically patterned onto a standard glass coverslip and can be excited using visible light on commercially available light microscopes. Only a small fraction of the coverslip is covered by the nanostructures and hence this technique is well suited for combining common techniques such as fluorescence and bright-field imaging.
A multidisciplinary approach is used in this protocol which incorporates sensor nanofabrication and subsequent biofunctionalization, binding kinetics characterization of ligand and analyte, the integration of the chip and live cells, and the analysis of the measured signal. As a whole, this technology enables a general label-free approach towards mapping cellular secretions and correlating them with the responses of nearby cells.

Inter-cellular communication is critical for controlling various physiological activities within and outside the cell. This paper describes a protocol for measuring the spatio-temporal nature of single cell secretions. To achieve this, a multidisciplinary approach is used which integrates label-free nanoplasmonic sensing with live cell imaging.

Inter-cellular communication is an integral part of a complex system that helps in maintaining basic cellular activities. As a result, the malfunctioning ...

Microfluidic Buffer Exchange for Interference-free Micro/Nanoparticle Cell Engineering

Engineering cells with active-ingredient-loaded micro/nanoparticles (NPs) is becoming an increasingly popular method to enhance native therapeutic properties, enable bio imaging and control cell phenotype. A critical yet inadequately addressed issue is the significant number of particles that remain unbound after cell labeling which cannot be readily removed by conventional centrifugation. This leads to an increase in bio imaging background noise and can impart transformative effects onto neighboring non-target cells. In this protocol, we present an inertial microfluidics-based buffer exchange strategy termed as Dean Flow Fractionation (DFF) to efficiently separate labeled cells from free NPs in a high throughput manner. The developed spiral microdevice facilitates continuous collection (&#62;90% cell recovery) of purified cells (THP-1 and MSCs) suspended in new buffer solution, while achieving &#62;95% depletion of unbound fluorescent dye or dye-loaded NPs (silica or PLGA). This single-step, size-based cell purification strategy enables high cell processing throughput (106 cells/min) and is highly useful for large-volume cell purification of micro/nanoparticle engineered cells to achieve interference-free clinical application.

This protocol describes the use of an inertial microfluidics-based buffer exchange strategy to purify micro/nanoparticle engineered cells with efficient depletion of unbound particles.

Engineering cells with active-ingredient-loaded micro/nanoparticles (NPs) is becoming an increasingly popular method to enhance native therapeutic ...

Multiplex Cytokine Profiling of Stimulated Mouse Splenocytes Using a Cytometric Bead-based Immunoassay Platform

Bead-based immunoassays employ the same basic principle as sandwich immunoassays. Capture beads, which can be differentiated by size and internal allophycocyanin (APC) fluorescence intensity, are conjugated to antibodies specific to a particular analyte. Next, a selected panel of defined capture bead sets is incubated with a biological sample containing target analytes specific to the capture antibodies. A biotinylated detection antibody cocktail is added, which leads to the formation of capture bead-analyte-detection antibody sandwiches.
Finally, streptavidin-phycoerythrin (SA-PE) is added, which binds to biotinylated detection antibodies, providing fluorescent signal intensities in proportion to the amount of bound analyte. The PE fluorescent signal of analyte-specific beads regions is quantified using flow cytometry, and the concentrations of particular analytes are determined using data analysis software and the standard curve generated in the assay.
In this experiment, we use a mouse T helper cytokine panel to simultaneously quantify the concentration of 13 separate cytokine targets in tissue culture supernatants collected from mouse splenocytes cultured under various stimulatory conditions.

This protocol describes the quantification of multiple cytokine targets simultaneously in tissue culture supernatants collected from stimulated mouse splenocytes using multiplex bead based immunoassay platform and a flow cytometer.

Bead-based immunoassays employ the same basic principle as sandwich immunoassays. Capture beads, which can be differentiated by size and internal ...

Single-cell Analysis of Immunophenotype and Cytokine Production in Peripheral Whole Blood via Mass Cytometry

Cytokines play a pivotal role in the pathogenesis of autoimmune diseases. Hence, the measurement of cytokine levels has been the focus of multiple studies in an attempt to understand the precise mechanisms that lead to the breakdown of self-tolerance and subsequent autoimmunity. Approaches thus far have been based on the study of one specific aspect of the immune system (a single or few cell types or cytokines), and do not offer a global assessment of complex autoimmune disease. While patient sera-based studies have afforded important insights into autoimmunity, they do not provide the specific cellular source of the dysregulated cytokines detected. A comprehensive single-cell approach to evaluate cytokine production in multiple immune cell subsets, within the context of &#34;intrinsic&#34; patient-specific plasma circulating factors, is described here. This approach enables monitoring of the patient-specific immune phenotype (surface markers) and function (cytokines), either in its native &#34;intrinsic pathogenic&#34; disease state, or in the presence of therapeutic agents (in vivo or ex vivo).

Here we describe a single-cell proteomic approach to evaluate immune phenotypic and functional (intracellular cytokine induction) alterations in peripheral whole blood samples, analyzed via mass cytometry.

Cytokines play a pivotal role in the pathogenesis of autoimmune diseases. Hence, the measurement of cytokine levels has been the focus of multiple studies ...

Optimized Whole Blood Immunoassays for Analyzing Fungal and Viral Immunity

Whole Blood Assay with Dual Co-Stimulation for Antigen-Specific Analysis of Host Immunity to Fungal and Viral Pathogens

Rapid and resource-efficient sample processing, high throughput, and high robustness are critical for effective scientific and clinical application of advanced antigen-specific immunoassays. Traditionally, such immunoassays, especially antigen-specific T-cell analysis by flow cytometry or enzyme-linked immunosorbent spot assays, often rely on the isolation of peripheral blood mononuclear cells. This process is time-consuming, subject to many pre-analytic confounders, and requires large blood volumes. Whole blood-based assays provide a facile alternative with increased pre-analytic robustness and lower blood volume requirements. Furthermore, whole blood-based assays allow for the preservation of inter-cellular interactions that are not captured by assays using isolated cell subsets. Recently, a refined whole blood immunoassay with dual anti-CD28 and anti-CD49d co-stimulation for comprehensive analysis of both antigen-specific T-cell functions and complex intercellular interactions in response to various fungal and viral antigens has been proposed. This protocol provides guidance for the preparation of stimulation tubes, blood stimulation, and downstream sample processing for flow cytometry, cytokine secretion assays, and transcriptional analyses. This includes a validated and functionally equivalent, previously unpublished, low-volume protocol (250 &#181;L) to make flow cytometric and cytokine-based T-cell monitoring more accessible for studies in pediatric patients or preclinical studies in small animals (e.g., mice). Altogether, these protocols provide a versatile toolbox for complex antigen-specific immune analysis in both clinical and translational research settings.

Author Spotlight: Advancing Immune Monitoring in Critical Care Patients Using Whole Blood Assays

Whole blood-based immunoassays provide a facile and resource-efficient tool to analyze antigen-specific immunity for diagnostic and research purposes. This article provides an optimized whole blood-based protocol with dual co-stimulation for comprehensive analysis of host immunity to fungal and viral pathogens, including a low-volume version for pediatric patients and small animals.

Rapid and resource-efficient sample processing, high throughput, and high robustness are critical for effective scientific and clinical application of ...

Microfluidic Approach to Resolve Simultaneous and Sequential Cytokine Secretion of Individual Polyfunctional Cells

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