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Droplet barcoding: tracking mobile micro-reactors for high-throughput biology
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ScienceDirect Droplet barcoding: tracking mobile micro-reactors for high-throughput biology Todd A Duncombe and Petra S Dittrich Droplet microfluidics has become a powerful analytical platform in biological research for conducting high-throughput screening in millions of discrete micro-reactors per hour. While the method facilitates faster and cheaper testing than conventional microtiter plates, the mobile nature of droplets makes micro-reaction tracking a notable challenge. To address this, researchers are developing a variety of tracking methods, ranging from organizing droplets into an index or labeling droplets with a barcode. The optimal tracking approach depends on the criteria for each specific application. Considerations include the requisite assay readout, throughput, droplet library size, reagent tracking and more. In this review, we summarize different strategies for droplet micro-reaction tracking and comment on promising future approaches in droplet barcoding. Topics range from indexing droplets by sequence or in an array, labeling droplets with barcodes, and reagent barcoding to track the input conditions in parametric screens. Address Department of Biosystems Science and Engineering, ETH Zurich, 4058 Basel, Switzerland Corresponding author: Dittrich, Petra S ([email protected])
Current Opinion in Biotechnology 2019, 60:205–212 This review comes from a themed issue on Chemical biotechnology Edited by Thomas Ward and Sven Panke
https://doi.org/10.1016/j.copbio.2019.05.004 0958-1669/ã 2019 Elsevier Ltd. All rights reserved.
Introduction In the midst of an influenza epidemic and laboratory supply shortage, Dr Gyula Taka´tsy introduced microtiter plates in 1950 [1,2]. Since then, microtiter plates have become a keystone analytical platform in research and medicine due to their standardized, sterile and easy-to-interface array of discrete reaction chambers. In the last several decades, biological research has advanced toward precision science, with researchers directly interrogating the innumerable cellular and molecular interactions that precipitate life. The analytical throughput demands of many biochemical applications, ranging from www.sciencedirect.com
drug discovery to studying cellular heterogeneity, now far exceed the capacity of microtiter plates that host volumes in the microliter range. Furthermore, scaling down from microliter multiwell plates to nanoliter microarrays introduces severe limitations with respect to pipetting or spotting as well as potential evaporation of fluids. Droplet microfluidics has emerged as an alternative approach that exhibits many of the strengths of microtiter plates with several orders of magnitude improvements in throughput and cost. Using simple microfluidic architectures and flow controls, microfluidic approaches can generate millions of picoliter mono-disperse water-in-oil droplets per hour. Each droplet is stabilized by water–oil interfacial surfactants or nanoparticles [3] to ensure that the micro-reactions remain discrete. The low-volume and reagent consumption per test can reduce screening costs by a million-fold [4]. A growing portfolio of reagent delivery and droplet generation approaches has enabled precise control of droplet reagent composition, which is necessary for complex assays [5]. Moreover, significant progress has been made on adapting important readout modalities to droplet microfluidics, including label-free approaches such as mass spectrometry [6,7], absorption [8] and Raman spectroscopy [9]. Combination with sorting modules has led to a powerful microfluidic cytometry equivalent referred to as fluorescence-activated droplet sorting [10]. While droplet microfluidics has managed to fulfill many of the critical features of microtiter plates, it generates new challenges for reaction tracking. Mobile droplet microreactors lack the well-controlled spatial index of well plates. For functional genetic screens, it is essential to link an observed phenotype in a droplet with the underlying molecular sequence. Many enzymatic or cell growth assays require time-course measurements per individual reactions, which is impossible to achieve without the use of a droplet index. Parametric or combinatorial screens where reaction input conditions are systematically varied also require a robust approach for tracking the reagent composition of each reaction. For certain assays, a droplet barcode is required, where a code refers to a specific droplet or its contents. In others, a droplet index is sufficient, where an organization method makes droplets uniquely identifiable. These terms and others used in the review are defined in Box 1. To avoid additional readouts, tracking schemes are optimally implemented such that the input conditions of the Current Opinion in Biotechnology 2019, 60:205–212
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Box 1 Review terminology Droplet Barcode: A readable code that refers to a specific droplet. Examples include particle barcoding [23,26] and sequence barcoding [12,13]. Reagent Barcode: A readable code that refers to the reagents contained in a droplet. This approach is used in parametric screening applications [14,45]. Droplet Index: An organization of individual droplets such that each droplet is uniquely identifiable. Examples include serial sequences [11] and spatial arrays [17,19]. Combination Encoding: A coding strategy based on the elements contained but irrespective to their organization. For example, ratiometric fluorescent barcodes [14,39].
concentration and in a defined order provide a barcode for their adjacent micro-reactor. Sequence barcoding has an advantage over particle barcoding in that it cannot interfere with the micro-reactors. This is of particular importance for unknown or precious samples. A combinatorial drug-screening platform used this barcoding strategy to analyze cells from a single cancer biopsy. The individual samples and conditions were tracked by a fluorescent barcoding droplet sequence adjacent to the cells under investigation [12].
droplet, the barcode or index, and assay performance can be readout simultaneously. Furthermore, as droplet microfluidic readouts vary widely for different applications — from fluorescence microscopy to mass spectrometry — there are different requirements for appropriate tracking methods. In this review, we discuss both the utility and limitations of various droplet microreaction tracking methods and comment on potential future developments in droplet barcoding (Figure 1).
An important objective in the development of droplet sequence barcoding is increasing its speed to meet the kilohertz frequency common in droplet production when using standard water-oil flow junction. The limiting factor is the time required to actively insert coding droplets into the micro-reactor droplet sequence. Currently, the simplest approach involves generating coding droplets on demand with active valves. Song et al. demonstrated that sequence barcoding could be sped up by selecting from a pre-generated library of coding droplets [13]. To further speed up sequence barcoding, coding droplet selection in the future could be performed with a dielectrophoretic droplet sorting tool, which has demonstrated droplet sorting at 30 kHz [10]. While droplet sequence barcoding still requires significant development in speed and the sophistication of coding droplet schemes, it will be a prominent droplet tracking strategy going forward.
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Tracking droplets in sequence is the simplest way to index droplets in a microfluidic channel but it is also susceptible to disruption since droplet integrity and sequence must be maintained throughout the platform. Off-chip droplet collection that disrupts sequence or microfluidic designs that can result in droplet splitting are incompatible. In one example of droplet sequence indexing, combinatorial droplets for enzyme screening were deterministically generated at several hertz using an array of pneumatic valves [11]. The valves dosed the various input reagents consisting of substrates and matrix metalloproteinases, in a droplet formation region and then the droplets flowed downstream to a surfactant-oil environment where the enzymatic reaction was observed. In this application, the droplet composition is userdefined by the operation of the pneumatic valves and their respective readout sequence is a sufficient index of their composition.
As an alternative to indexing by flow sequence, droplets can also be indexed on a surface. Arraying droplets within microwells [14], chemical micropatterns [7], microdevice designs [15,16], dielectric trapping [17], or many other approaches [18] allows for a spatial index for each micro-reaction, similar to that of microtiter plates. This approach adds another process step for deposition and can limit the throughput to thousands of droplets per hour. Nonetheless, this method provides additional features, which are beneficial for screening applications. Repeated addition of compounds to all or selected droplets can be conducted with a capillary and an automated stage [17,19]. Microfluidic designs can generate chemical gradient droplet arrays [16,20]. The use of static droplets provides some advantages; for example one can perform assays with adherent cells or assays that require longer incubation times. Moreover, static droplets can be combined with tailored surface chemistries [18] or printed microarrays for multiplexed readouts [21]. Micro-reactions are easily monitored over time with microscopy and can later be selectively collected or dried on the substrate for subsequent analysis, such as matrix assisted laser desorption ionization mass spectrometry [7,19].
Permutation Encoding: A coding strategy based on the elements contained and their respective organization. Examples include micro-patterned hydrogels [42], nucleic acid-based barcodes [23,26,31,43], and droplet sequence barcoding [12,13].
Most droplet generation applications – such as single-cell encapsulation – are not deterministic. Droplet contents can vary stochastically and their generated sequence has no utility as an index. A novel approach is droplet sequence barcoding, depicted in Figure 2a, in which coding droplets are inserted into the micro-reactor droplet sequence. Several coding droplets filled with fluorescent dyes [12] or magnetic particles [13] of a defined Current Opinion in Biotechnology 2019, 60:205–212
In recent work by Cole et al. [17], depicted in Figure 2b, a high-speed fluorescence-based droplet sorter was utilized before arraying droplets. This allowed for the www.sciencedirect.com
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Droplet microfluidic platforms can generate millions of discrete water-in-oil micro-reactors per hour. The high throughput nature of droplet microfluidics makes it an alluring platform for many applications in biological research, from metabolic engineering and drug discovery to directed evolution and the generation of artificial cells. A notable challenge of droplet microfluidics is that the reactors are 10 s of microns in size and mobile, making it hard to keep track of them. Various droplet tracking methods have been developed to index or barcode droplets for reliable identification.
selection of micro-reactions containing a single-cell and the elimination of the large proportion of undesired droplets containing zero or multiples cells. Additional droplets could be deterministically added to generate the desired micro-reaction, for example combining different types of single cells. This approach relies on an automated stage to orient a capillary above capture regions and thus prints droplets at a maximum speed of a few hertz. In the future, a rapid (>100 Hz) droplet seeding approach could dramatically extend droplet array more high-throughput screening indexing for applications.
Particle barcode A conceptually simple strategy for micro-reactor tracking is the use of a particle barcode to track the contents of each droplet. This is analogous to stores using stickers with the Universal Product Code – encoded with sequential vertical lines – to label and track inventory [22]. A particle barcoded droplet index requires the following: a coding strategy compatible with the assay readout; a sufficiently sized particle with chemical properties that are compatible with the micro-reaction; and a reliable approach for incorporating individual barcoded-particles www.sciencedirect.com
into droplets at a speed that is commensurate with droplet generation. The simplest approach to encapsulate particles in droplets is via stochastic particle encapsulation where the distribution of particles in droplets follows the Poisson distribution [23]. While this technique is compatible with droplet generation at kilohertz speeds, it results in many droplets that either lack or contain more than one particle. Encapsulation efficiency can be extended beyond the Poisson distribution by periodically arranging the particles before droplet formation. This has been accomplished with inertial microfluidic devices [24] or by densely packing deformable particles [25,26]. Nucleic acid barcoding
Nucleic acid barcodes have been used for multiplexed sequencing since the late 1980s [27]. In the modern incarnation [28], an oligonucleotide barcode is incorporated onto the nucleic acid samples of interest. Samples are then pooled for parallel sequencing and distinguished from one-another in data analysis by their unique barcode. Barcoded nucleic acid sequencing was adapted to droplet microfluidics for high-throughput Current Opinion in Biotechnology 2019, 60:205–212
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Figure 2
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Microfluidic tools for precise droplet manipulation allow for droplet sequence barcoding and for droplet indexing on a microarray. (a) Song et al. [13] barcoded micro-reactors within a droplet sequence by inserting coding droplets adjacent to the desired micro-reactor. Coding droplets contained magnetic nanoparticles at one of four concentrations. The barcode was structured by the sequence of coding droplets. For example, ‘0000’ — four 0 droplets in sequence — as Code 0 and ‘0001’ as Code 1. This droplet sequence barcoding approach has a coding capacity of over 104 and could be rapidly decoded using a giant magnetoresistance (GMR) sensor integrated into their platform. Reprinted with permission from Ref. [13]. Copyright 2017 American Chemical Society. (b) Cole et al. [17] selected single-cell containing droplets using a droplet sorter and then spotted them on the substrate using an automated stage. The droplet position in the array serves as its spatial index. Copyright 2017 National Academy of Sciences.
single-cell analysis [23] by the use of oligonucleotidebarcoded microbeads. The barcoded beads were synthesized by performing 12 split-pool nucleic acid addition cycles to generate a potential 412, or 16 million distinct codes. Barcoded beads are incorporated into droplets concurrently with single cells during droplet generation at [23] or above [26] the Poisson distribution. Each droplet acts as a discrete reaction chamber for attaching barcodes onto the molecules of interest for thousands of single cells before pooled sequencing. This streamlined approach reduced costs to $0.05 per single-cell [29] and revolutionized the fields of single-cell genomics and transcriptomics [30].
Optical barcoding
There has been a significant effort in developing a wide variety of optically barcoded particles due to their utility in multiplexed bioassays [34]. The particles function as a solid-phase supports coding for a specific capture reagent. This barcoded bead-based assay [35] allows for much higher multiplexing than what is currently possible with conventional affinity assays [31,35–37]. While these optically coded particles have yet to be adapted for droplet indexing applications, they could readily be applied using a similar particle encapsulation approach as the one described for nucleic acid barcoding. Spectral beads
A limitation of the in-droplet barcoding followed by pooled sequencing approach is the inability to compare the sequencing analysis with corresponding measurements of protein abundance, enzyme activity, cell viability, and others. A promising future direction of barcoding approaches will focus on translating the underlying oligonucleotide barcodes into orthogonal readouts such as fluorescence [31,32] or mass spectrometry [33] that can be related to the underlying genome. This will greatly extend the utility of droplet microfluidics in functional genetic screening and directed evolution. Current Opinion in Biotechnology 2019, 60:205–212
Combinatorial fluorescent barcodes utilize ratiometric barcoding to generate large sets of spectrally distinct beads, in which the relative fluorescence intensity between different fluorophores serves as the basis for the code. The barcoded particles are synthesized by precisely mixing various fluorophores in gel precursor solution followed by droplet production and polymerization to form microbeads [38,39]. Combinations of quantum dots are often used due to their resistance to photobleaching and a single UV excitation source [40]. The largest spectral bead library demonstrated to date www.sciencedirect.com
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utilized a custom microfluidic mixer to combine five lanthanide nanophosphors with distinct fluorescent profiles at different ratios. This produced a library of 1023 spectrally distinct beads [39]. To assist with the complex deconvolution for bead identification and assay readout, the authors published an open source code for detecting these beads [41]. Spatial patterns
While the 1000 spectral combinations are sufficient for multiplexed bioassays, they are unable to cover the coding space necessary for tracking a million droplets. As an example, a nucleic acid sequence that is 12 bases long with 4 base pairs has a permutatory barcoding space of over 16 million. Ratiometric spectral beads consisting of 12 distinct ratios for 4 fluorophores – referred to as a combination with repetitions – exhibit a barcoding space of 1365. The code-space discrepancy arises from the addition of a sequence-based readout, which allows for permutation rather than combination barcoding. One approach to solve this code-space discrepancy is the use of spatially micropatterned hydrogels which are readout by their spatial distribution of features in a similar manner to the original Universal Product Codes [42]. Gel precursor solution flows into a microfluidic device and is directly photopatterned through a photomask into spatially
barcoded gels. Using this approach, the theoretical coding capacity is in the billions. Generating such large libraries, however, is not practical as each barcode design requires a unique photomask. Furthermore, the spatial readout may be slower than what is desired in droplet microfluidic assays. A potential alternative barcode with a large code-space that can be readout rapidly, is fluorescence-based permutation encoding. A prominent example is commercialized by NanoString Technologies Inc. [31,43]. Their technology – used for a variety of multiplexed bioassays – utilizes a nucleic acid template to selfassemble fluorophores in a specific order. The code is set by the order of nucleic acid binding regions and complimentary strands attach the desired fluorophores. During the readout, one end of the nucleic acid strand is attached to a surface. An electric field is then applied that stretches the nucleic acid so that the fluorophore sequence can be observed via fluorescence microscopy. A genetically encoded fluorescence barcoding scheme similar to this could plausibly be incorporated onto the nucleic acid particle barcodes [32] for performing multiomics analysis. A combined genetic and fluorescent barcode would allow for both optical assays conducted with microscopy and genetic assays conducted with sequencing to be associated with one another for each individual droplet (Figure 3).
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Barcoded particles can be encapsulated into droplets to track droplets and label their content. Macosco et al. [44] introduced high-throughput single-cell sequencing by performing molecular barcoding in droplets. They encapsulated particles functionalized with barcoded primers in droplets containing single cells. The cell mRNA is hybridized to the barcoded primers in the droplet. Droplets are subsequently broken; then the beads are washed and pooled. Reverse-transcription is performed in bulk to generate single-cell transcriptomes attached to microparticles (STAMPs). The pooled sample is then sent for sequencing. The barcoded primers are used to deconvolve the single cells during data analysis. Reprinted from Ref. [44], Copyright 2015 with permission from Elsevier. www.sciencedirect.com
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Reagent barcoding facilitates droplet-based screening of large parameter spaces by leveraging non-deterministic condition generation. (a) Kulesa et al. [14] developed a combinatorial drug discovery platform that relied on stochastically seeding a large library of droplets containing antibiotics, compounds with cells, or blanks into microwells. (b) Fluorescence imaging was used to identify the relative position of reagents in the array using a ratiometric fluorescence reagent barcode. (c) Then, droplets were merged to perform the combinatorial drug synergy screen. The fluorescence image representing the cell viability screen is displayed in the black and white image. The colorful inset in the upper right displays the fluorescent barcode before droplet merging. Copyright 2017 National Academy of Sciences.
Reagent barcode Droplet microfluidics can be used for optimizing reactions over a large parameter space of conditions, which is useful in applications like drug screening, toxicity testing, and chemical synthesis. During such a screen, tracking the input conditions of each droplet with robust internal concentration standards is more important than tracking the individual droplets. When a well-calibrated set of internal standards is used for each reagent, relatively simple non-deterministic approaches can explore a large parameter space of conditions. For example, oscillating fluidic flows controlled by external pumps were used to generate droplet conditions over a large parameter space to optimize cell-free expression in droplets [45]. Distinct and non-interacting fluorophores were included in each input reagent and were incorporated into the final droplet at equal proportions as their corresponding reagents. The assay outcome and the input conditions were then read simultaneously as a final readout. Using this approach, millions of conditions can be tested per hour, providing a detailed map of interacting biomolecular components. A similar reagent tracking strategy was recently applied to study the synergetic effects of a 4000 compound library Current Opinion in Biotechnology 2019, 60:205–212
with a panel of 10 antibiotics [14]. Fluorescently barcoded droplets consisting of either antibiotics, compounds with cells, or blanks (for negative controls) were randomly assembled into a large microwell array that places two droplets in contact. The device was then imaged to determine the reagent composition of each droplet by its barcode and their position array. Then droplet merging was induced and cell growth was monitored to assess the synergetic antibiotic response. In total, they assessed 100 000 combinations. Similar approaches for tracking combinatorial conditions are also possible by merging droplets on-chip [46] (Figure 4).
Conclusions There are many demonstrated and emerging new technologies to track droplets. However, many of these approaches are not routinely used today. Limitations include the number of barcodes that can be encoded and produced, the time and complexity required to incorporate a barcode, and the requirement that the barcode should not interfere with the actual assay readout from the micro-reactor. For example, a fluorescence assay reduces the wavelength-space of optical barcodes or the barcode itself could alter the chemistry of the reaction. However, the rapid adoption of droplet-based single-cell sequencing [30] has shown how a well-designed droplet www.sciencedirect.com
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barcoding strategy [23] can revolutionize bioanalytical methods when it works reliably and offers valuable new insight. We expect that future droplet barcoding or indexing technologies that efficiently track droplets in other readouts, or enable multimodal analysis, will have a similarly significant impact in biological research.
Conflict of interest statement Nothing declared.
12. Eduati F, Utharala R, Madhavan D, Neumann UP, Longerich T, Cramer T, Saez-Rodriguez J, Merten CA: A microfluidics platform for combinatorial drug screening on cancer biopsies. Nat Commun 2018, 9:2434. Combinatorial drug screening to perform thousands of discrete tests on cells from a single biopsy. Reaction conditions were encoded by adding barcoding droplets in sequence. 13. Song W, Lin G, Ge J, Fassbender J, Makarov D: Encoding microreactors with droplet chains in microfluidics. ACS Sens 2017, 2:1839-1846. A sequence of barcoding droplets were selected from a pre-generated large library and inserted adjacent to the droplet reactors of interest.
We gratefully acknowledge funding from the Swiss National Science Foundation (NCCR Molecular Systems Engineering).
14. Kulesa A, Kehe J, Hurtado J, Tawde P, Blainey PC: Combinatorial drug discovery in nanoliter droplets. Proc Natl Acad Sci U S A 2017, 115:6685-6690. Fluorescently barcoded droplets were stochastically seeded in a microarray, and subsequently merged, to perform high-throughput combinatorial screen of drug-antibiotic synergies.
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preparation of quantum-dot barcodes. Angew Chem Int Ed 2008, 47:5577-5581. 39. Nguyen HQ, Baxter BC, Brower K, Diaz-Botia CA, DeRisi JL, Fordyce PM, Thorn KS: Programmable microfluidic synthesis of over one thousand uniquely identifiable spectral codes. Adv Opt Mater 2017, 5:1600548. The authors demonstrate a library of 1023 spectrally encoded microspheres by ratiometrically combining lanthanide nanophosphors. 40. Rosenthal SJ: Bar-coding biomolecules with fluorescent nanocrystals. Nat Biotechnol 2001, 19:621-622. 41. Harink B, Nguyen H, Thorn K, Fordyce P: An open-source software analysis package for Microspheres with Ratiometric Barcode Lanthanide Encoding (MRBLEs). PLoS One 2019, 14: e0203725. 42. Pregibon DC, Toner M, Doyle PS: Multifunctional encoded particles for high-throughput biomolecule analysis. Science (80) 2007, 315:1393-1396. Photo-patterned hydrogel particles can encode billions of barcodes. 43. Yavuz AA, Glas B, Ihle M, Hacioglu H, Wehefritz K: Patent US 2017/0016909 A1 - Simultaneous quantification of a plurality of proteins in a user-defined region of a cross-sectioned tissue. 2017. 44. Macosko EZ, Basu A, Satija R, Nemesh J, Shekhar K, Goldman M, Tirosh I, Bialas AR, Kamitaki N, Martersteck EM et al.: Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Cell 2015, 161:1202-1214. 45. Hori Y, Kantak C, Murray RM, Abate AR: Cell-free extract based optimization of biomolecular circuits with droplet microfluidics. Lab Chip 2017, 17:3037-3042. The authors demonstrate that the use of barcoded reagents and systematically varied flow rates controlled by external pumps is a relatively facile approach to assess a parametric reaction space. 46. Brouzes E, Medkova M, Savenelli N, Marran D, Twardowski M, Hutchison JB, Rothberg JM, Link DR, Perrimon N, Samuels ML: Droplet microfluidic technology for single-cell highthroughput screening. Proc Natl Acad Sci U S A 2009, 106:14195-14200.
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ScienceDirect Droplet barcoding: tracking mobile micro-reactors for high-throughput biology Todd A Duncombe and Petra S Dittrich Droplet microfluidics has become a powerful analytical platform in biological research for conducting high-throughput screening in millions of discrete micro-reactors per hour. While the method facilitates faster and cheaper testing than conventional microtiter plates, the mobile nature of droplets makes micro-reaction tracking a notable challenge. To address this, researchers are developing a variety of tracking methods, ranging from organizing droplets into an index or labeling droplets with a barcode. The optimal tracking approach depends on the criteria for each specific application. Considerations include the requisite assay readout, throughput, droplet library size, reagent tracking and more. In this review, we summarize different strategies for droplet micro-reaction tracking and comment on promising future approaches in droplet barcoding. Topics range from indexing droplets by sequence or in an array, labeling droplets with barcodes, and reagent barcoding to track the input conditions in parametric screens. Address Department of Biosystems Science and Engineering, ETH Zurich, 4058 Basel, Switzerland Corresponding author: Dittrich, Petra S ([email protected])
Current Opinion in Biotechnology 2019, 60:205–212 This review comes from a themed issue on Chemical biotechnology Edited by Thomas Ward and Sven Panke
https://doi.org/10.1016/j.copbio.2019.05.004 0958-1669/ã 2019 Elsevier Ltd. All rights reserved.
Introduction In the midst of an influenza epidemic and laboratory supply shortage, Dr Gyula Taka´tsy introduced microtiter plates in 1950 [1,2]. Since then, microtiter plates have become a keystone analytical platform in research and medicine due to their standardized, sterile and easy-to-interface array of discrete reaction chambers. In the last several decades, biological research has advanced toward precision science, with researchers directly interrogating the innumerable cellular and molecular interactions that precipitate life. The analytical throughput demands of many biochemical applications, ranging from www.sciencedirect.com
drug discovery to studying cellular heterogeneity, now far exceed the capacity of microtiter plates that host volumes in the microliter range. Furthermore, scaling down from microliter multiwell plates to nanoliter microarrays introduces severe limitations with respect to pipetting or spotting as well as potential evaporation of fluids. Droplet microfluidics has emerged as an alternative approach that exhibits many of the strengths of microtiter plates with several orders of magnitude improvements in throughput and cost. Using simple microfluidic architectures and flow controls, microfluidic approaches can generate millions of picoliter mono-disperse water-in-oil droplets per hour. Each droplet is stabilized by water–oil interfacial surfactants or nanoparticles [3] to ensure that the micro-reactions remain discrete. The low-volume and reagent consumption per test can reduce screening costs by a million-fold [4]. A growing portfolio of reagent delivery and droplet generation approaches has enabled precise control of droplet reagent composition, which is necessary for complex assays [5]. Moreover, significant progress has been made on adapting important readout modalities to droplet microfluidics, including label-free approaches such as mass spectrometry [6,7], absorption [8] and Raman spectroscopy [9]. Combination with sorting modules has led to a powerful microfluidic cytometry equivalent referred to as fluorescence-activated droplet sorting [10]. While droplet microfluidics has managed to fulfill many of the critical features of microtiter plates, it generates new challenges for reaction tracking. Mobile droplet microreactors lack the well-controlled spatial index of well plates. For functional genetic screens, it is essential to link an observed phenotype in a droplet with the underlying molecular sequence. Many enzymatic or cell growth assays require time-course measurements per individual reactions, which is impossible to achieve without the use of a droplet index. Parametric or combinatorial screens where reaction input conditions are systematically varied also require a robust approach for tracking the reagent composition of each reaction. For certain assays, a droplet barcode is required, where a code refers to a specific droplet or its contents. In others, a droplet index is sufficient, where an organization method makes droplets uniquely identifiable. These terms and others used in the review are defined in Box 1. To avoid additional readouts, tracking schemes are optimally implemented such that the input conditions of the Current Opinion in Biotechnology 2019, 60:205–212
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Box 1 Review terminology Droplet Barcode: A readable code that refers to a specific droplet. Examples include particle barcoding [23,26] and sequence barcoding [12,13]. Reagent Barcode: A readable code that refers to the reagents contained in a droplet. This approach is used in parametric screening applications [14,45]. Droplet Index: An organization of individual droplets such that each droplet is uniquely identifiable. Examples include serial sequences [11] and spatial arrays [17,19]. Combination Encoding: A coding strategy based on the elements contained but irrespective to their organization. For example, ratiometric fluorescent barcodes [14,39].
concentration and in a defined order provide a barcode for their adjacent micro-reactor. Sequence barcoding has an advantage over particle barcoding in that it cannot interfere with the micro-reactors. This is of particular importance for unknown or precious samples. A combinatorial drug-screening platform used this barcoding strategy to analyze cells from a single cancer biopsy. The individual samples and conditions were tracked by a fluorescent barcoding droplet sequence adjacent to the cells under investigation [12].
droplet, the barcode or index, and assay performance can be readout simultaneously. Furthermore, as droplet microfluidic readouts vary widely for different applications — from fluorescence microscopy to mass spectrometry — there are different requirements for appropriate tracking methods. In this review, we discuss both the utility and limitations of various droplet microreaction tracking methods and comment on potential future developments in droplet barcoding (Figure 1).
An important objective in the development of droplet sequence barcoding is increasing its speed to meet the kilohertz frequency common in droplet production when using standard water-oil flow junction. The limiting factor is the time required to actively insert coding droplets into the micro-reactor droplet sequence. Currently, the simplest approach involves generating coding droplets on demand with active valves. Song et al. demonstrated that sequence barcoding could be sped up by selecting from a pre-generated library of coding droplets [13]. To further speed up sequence barcoding, coding droplet selection in the future could be performed with a dielectrophoretic droplet sorting tool, which has demonstrated droplet sorting at 30 kHz [10]. While droplet sequence barcoding still requires significant development in speed and the sophistication of coding droplet schemes, it will be a prominent droplet tracking strategy going forward.
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Tracking droplets in sequence is the simplest way to index droplets in a microfluidic channel but it is also susceptible to disruption since droplet integrity and sequence must be maintained throughout the platform. Off-chip droplet collection that disrupts sequence or microfluidic designs that can result in droplet splitting are incompatible. In one example of droplet sequence indexing, combinatorial droplets for enzyme screening were deterministically generated at several hertz using an array of pneumatic valves [11]. The valves dosed the various input reagents consisting of substrates and matrix metalloproteinases, in a droplet formation region and then the droplets flowed downstream to a surfactant-oil environment where the enzymatic reaction was observed. In this application, the droplet composition is userdefined by the operation of the pneumatic valves and their respective readout sequence is a sufficient index of their composition.
As an alternative to indexing by flow sequence, droplets can also be indexed on a surface. Arraying droplets within microwells [14], chemical micropatterns [7], microdevice designs [15,16], dielectric trapping [17], or many other approaches [18] allows for a spatial index for each micro-reaction, similar to that of microtiter plates. This approach adds another process step for deposition and can limit the throughput to thousands of droplets per hour. Nonetheless, this method provides additional features, which are beneficial for screening applications. Repeated addition of compounds to all or selected droplets can be conducted with a capillary and an automated stage [17,19]. Microfluidic designs can generate chemical gradient droplet arrays [16,20]. The use of static droplets provides some advantages; for example one can perform assays with adherent cells or assays that require longer incubation times. Moreover, static droplets can be combined with tailored surface chemistries [18] or printed microarrays for multiplexed readouts [21]. Micro-reactions are easily monitored over time with microscopy and can later be selectively collected or dried on the substrate for subsequent analysis, such as matrix assisted laser desorption ionization mass spectrometry [7,19].
Permutation Encoding: A coding strategy based on the elements contained and their respective organization. Examples include micro-patterned hydrogels [42], nucleic acid-based barcodes [23,26,31,43], and droplet sequence barcoding [12,13].
Most droplet generation applications – such as single-cell encapsulation – are not deterministic. Droplet contents can vary stochastically and their generated sequence has no utility as an index. A novel approach is droplet sequence barcoding, depicted in Figure 2a, in which coding droplets are inserted into the micro-reactor droplet sequence. Several coding droplets filled with fluorescent dyes [12] or magnetic particles [13] of a defined Current Opinion in Biotechnology 2019, 60:205–212
In recent work by Cole et al. [17], depicted in Figure 2b, a high-speed fluorescence-based droplet sorter was utilized before arraying droplets. This allowed for the www.sciencedirect.com
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Droplet microfluidic platforms can generate millions of discrete water-in-oil micro-reactors per hour. The high throughput nature of droplet microfluidics makes it an alluring platform for many applications in biological research, from metabolic engineering and drug discovery to directed evolution and the generation of artificial cells. A notable challenge of droplet microfluidics is that the reactors are 10 s of microns in size and mobile, making it hard to keep track of them. Various droplet tracking methods have been developed to index or barcode droplets for reliable identification.
selection of micro-reactions containing a single-cell and the elimination of the large proportion of undesired droplets containing zero or multiples cells. Additional droplets could be deterministically added to generate the desired micro-reaction, for example combining different types of single cells. This approach relies on an automated stage to orient a capillary above capture regions and thus prints droplets at a maximum speed of a few hertz. In the future, a rapid (>100 Hz) droplet seeding approach could dramatically extend droplet array more high-throughput screening indexing for applications.
Particle barcode A conceptually simple strategy for micro-reactor tracking is the use of a particle barcode to track the contents of each droplet. This is analogous to stores using stickers with the Universal Product Code – encoded with sequential vertical lines – to label and track inventory [22]. A particle barcoded droplet index requires the following: a coding strategy compatible with the assay readout; a sufficiently sized particle with chemical properties that are compatible with the micro-reaction; and a reliable approach for incorporating individual barcoded-particles www.sciencedirect.com
into droplets at a speed that is commensurate with droplet generation. The simplest approach to encapsulate particles in droplets is via stochastic particle encapsulation where the distribution of particles in droplets follows the Poisson distribution [23]. While this technique is compatible with droplet generation at kilohertz speeds, it results in many droplets that either lack or contain more than one particle. Encapsulation efficiency can be extended beyond the Poisson distribution by periodically arranging the particles before droplet formation. This has been accomplished with inertial microfluidic devices [24] or by densely packing deformable particles [25,26]. Nucleic acid barcoding
Nucleic acid barcodes have been used for multiplexed sequencing since the late 1980s [27]. In the modern incarnation [28], an oligonucleotide barcode is incorporated onto the nucleic acid samples of interest. Samples are then pooled for parallel sequencing and distinguished from one-another in data analysis by their unique barcode. Barcoded nucleic acid sequencing was adapted to droplet microfluidics for high-throughput Current Opinion in Biotechnology 2019, 60:205–212
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Figure 2
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Microfluidic tools for precise droplet manipulation allow for droplet sequence barcoding and for droplet indexing on a microarray. (a) Song et al. [13] barcoded micro-reactors within a droplet sequence by inserting coding droplets adjacent to the desired micro-reactor. Coding droplets contained magnetic nanoparticles at one of four concentrations. The barcode was structured by the sequence of coding droplets. For example, ‘0000’ — four 0 droplets in sequence — as Code 0 and ‘0001’ as Code 1. This droplet sequence barcoding approach has a coding capacity of over 104 and could be rapidly decoded using a giant magnetoresistance (GMR) sensor integrated into their platform. Reprinted with permission from Ref. [13]. Copyright 2017 American Chemical Society. (b) Cole et al. [17] selected single-cell containing droplets using a droplet sorter and then spotted them on the substrate using an automated stage. The droplet position in the array serves as its spatial index. Copyright 2017 National Academy of Sciences.
single-cell analysis [23] by the use of oligonucleotidebarcoded microbeads. The barcoded beads were synthesized by performing 12 split-pool nucleic acid addition cycles to generate a potential 412, or 16 million distinct codes. Barcoded beads are incorporated into droplets concurrently with single cells during droplet generation at [23] or above [26] the Poisson distribution. Each droplet acts as a discrete reaction chamber for attaching barcodes onto the molecules of interest for thousands of single cells before pooled sequencing. This streamlined approach reduced costs to $0.05 per single-cell [29] and revolutionized the fields of single-cell genomics and transcriptomics [30].
Optical barcoding
There has been a significant effort in developing a wide variety of optically barcoded particles due to their utility in multiplexed bioassays [34]. The particles function as a solid-phase supports coding for a specific capture reagent. This barcoded bead-based assay [35] allows for much higher multiplexing than what is currently possible with conventional affinity assays [31,35–37]. While these optically coded particles have yet to be adapted for droplet indexing applications, they could readily be applied using a similar particle encapsulation approach as the one described for nucleic acid barcoding. Spectral beads
A limitation of the in-droplet barcoding followed by pooled sequencing approach is the inability to compare the sequencing analysis with corresponding measurements of protein abundance, enzyme activity, cell viability, and others. A promising future direction of barcoding approaches will focus on translating the underlying oligonucleotide barcodes into orthogonal readouts such as fluorescence [31,32] or mass spectrometry [33] that can be related to the underlying genome. This will greatly extend the utility of droplet microfluidics in functional genetic screening and directed evolution. Current Opinion in Biotechnology 2019, 60:205–212
Combinatorial fluorescent barcodes utilize ratiometric barcoding to generate large sets of spectrally distinct beads, in which the relative fluorescence intensity between different fluorophores serves as the basis for the code. The barcoded particles are synthesized by precisely mixing various fluorophores in gel precursor solution followed by droplet production and polymerization to form microbeads [38,39]. Combinations of quantum dots are often used due to their resistance to photobleaching and a single UV excitation source [40]. The largest spectral bead library demonstrated to date www.sciencedirect.com
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utilized a custom microfluidic mixer to combine five lanthanide nanophosphors with distinct fluorescent profiles at different ratios. This produced a library of 1023 spectrally distinct beads [39]. To assist with the complex deconvolution for bead identification and assay readout, the authors published an open source code for detecting these beads [41]. Spatial patterns
While the 1000 spectral combinations are sufficient for multiplexed bioassays, they are unable to cover the coding space necessary for tracking a million droplets. As an example, a nucleic acid sequence that is 12 bases long with 4 base pairs has a permutatory barcoding space of over 16 million. Ratiometric spectral beads consisting of 12 distinct ratios for 4 fluorophores – referred to as a combination with repetitions – exhibit a barcoding space of 1365. The code-space discrepancy arises from the addition of a sequence-based readout, which allows for permutation rather than combination barcoding. One approach to solve this code-space discrepancy is the use of spatially micropatterned hydrogels which are readout by their spatial distribution of features in a similar manner to the original Universal Product Codes [42]. Gel precursor solution flows into a microfluidic device and is directly photopatterned through a photomask into spatially
barcoded gels. Using this approach, the theoretical coding capacity is in the billions. Generating such large libraries, however, is not practical as each barcode design requires a unique photomask. Furthermore, the spatial readout may be slower than what is desired in droplet microfluidic assays. A potential alternative barcode with a large code-space that can be readout rapidly, is fluorescence-based permutation encoding. A prominent example is commercialized by NanoString Technologies Inc. [31,43]. Their technology – used for a variety of multiplexed bioassays – utilizes a nucleic acid template to selfassemble fluorophores in a specific order. The code is set by the order of nucleic acid binding regions and complimentary strands attach the desired fluorophores. During the readout, one end of the nucleic acid strand is attached to a surface. An electric field is then applied that stretches the nucleic acid so that the fluorophore sequence can be observed via fluorescence microscopy. A genetically encoded fluorescence barcoding scheme similar to this could plausibly be incorporated onto the nucleic acid particle barcodes [32] for performing multiomics analysis. A combined genetic and fluorescent barcode would allow for both optical assays conducted with microscopy and genetic assays conducted with sequencing to be associated with one another for each individual droplet (Figure 3).
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Barcoded particles can be encapsulated into droplets to track droplets and label their content. Macosco et al. [44] introduced high-throughput single-cell sequencing by performing molecular barcoding in droplets. They encapsulated particles functionalized with barcoded primers in droplets containing single cells. The cell mRNA is hybridized to the barcoded primers in the droplet. Droplets are subsequently broken; then the beads are washed and pooled. Reverse-transcription is performed in bulk to generate single-cell transcriptomes attached to microparticles (STAMPs). The pooled sample is then sent for sequencing. The barcoded primers are used to deconvolve the single cells during data analysis. Reprinted from Ref. [44], Copyright 2015 with permission from Elsevier. www.sciencedirect.com
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Reagent barcoding facilitates droplet-based screening of large parameter spaces by leveraging non-deterministic condition generation. (a) Kulesa et al. [14] developed a combinatorial drug discovery platform that relied on stochastically seeding a large library of droplets containing antibiotics, compounds with cells, or blanks into microwells. (b) Fluorescence imaging was used to identify the relative position of reagents in the array using a ratiometric fluorescence reagent barcode. (c) Then, droplets were merged to perform the combinatorial drug synergy screen. The fluorescence image representing the cell viability screen is displayed in the black and white image. The colorful inset in the upper right displays the fluorescent barcode before droplet merging. Copyright 2017 National Academy of Sciences.
Reagent barcode Droplet microfluidics can be used for optimizing reactions over a large parameter space of conditions, which is useful in applications like drug screening, toxicity testing, and chemical synthesis. During such a screen, tracking the input conditions of each droplet with robust internal concentration standards is more important than tracking the individual droplets. When a well-calibrated set of internal standards is used for each reagent, relatively simple non-deterministic approaches can explore a large parameter space of conditions. For example, oscillating fluidic flows controlled by external pumps were used to generate droplet conditions over a large parameter space to optimize cell-free expression in droplets [45]. Distinct and non-interacting fluorophores were included in each input reagent and were incorporated into the final droplet at equal proportions as their corresponding reagents. The assay outcome and the input conditions were then read simultaneously as a final readout. Using this approach, millions of conditions can be tested per hour, providing a detailed map of interacting biomolecular components. A similar reagent tracking strategy was recently applied to study the synergetic effects of a 4000 compound library Current Opinion in Biotechnology 2019, 60:205–212
with a panel of 10 antibiotics [14]. Fluorescently barcoded droplets consisting of either antibiotics, compounds with cells, or blanks (for negative controls) were randomly assembled into a large microwell array that places two droplets in contact. The device was then imaged to determine the reagent composition of each droplet by its barcode and their position array. Then droplet merging was induced and cell growth was monitored to assess the synergetic antibiotic response. In total, they assessed 100 000 combinations. Similar approaches for tracking combinatorial conditions are also possible by merging droplets on-chip [46] (Figure 4).
Conclusions There are many demonstrated and emerging new technologies to track droplets. However, many of these approaches are not routinely used today. Limitations include the number of barcodes that can be encoded and produced, the time and complexity required to incorporate a barcode, and the requirement that the barcode should not interfere with the actual assay readout from the micro-reactor. For example, a fluorescence assay reduces the wavelength-space of optical barcodes or the barcode itself could alter the chemistry of the reaction. However, the rapid adoption of droplet-based single-cell sequencing [30] has shown how a well-designed droplet www.sciencedirect.com
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barcoding strategy [23] can revolutionize bioanalytical methods when it works reliably and offers valuable new insight. We expect that future droplet barcoding or indexing technologies that efficiently track droplets in other readouts, or enable multimodal analysis, will have a similarly significant impact in biological research.
Conflict of interest statement Nothing declared.
12. Eduati F, Utharala R, Madhavan D, Neumann UP, Longerich T, Cramer T, Saez-Rodriguez J, Merten CA: A microfluidics platform for combinatorial drug screening on cancer biopsies. Nat Commun 2018, 9:2434. Combinatorial drug screening to perform thousands of discrete tests on cells from a single biopsy. Reaction conditions were encoded by adding barcoding droplets in sequence. 13. Song W, Lin G, Ge J, Fassbender J, Makarov D: Encoding microreactors with droplet chains in microfluidics. ACS Sens 2017, 2:1839-1846. A sequence of barcoding droplets were selected from a pre-generated large library and inserted adjacent to the droplet reactors of interest.
We gratefully acknowledge funding from the Swiss National Science Foundation (NCCR Molecular Systems Engineering).
14. Kulesa A, Kehe J, Hurtado J, Tawde P, Blainey PC: Combinatorial drug discovery in nanoliter droplets. Proc Natl Acad Sci U S A 2017, 115:6685-6690. Fluorescently barcoded droplets were stochastically seeded in a microarray, and subsequently merged, to perform high-throughput combinatorial screen of drug-antibiotic synergies.
References and recommended reading
15. Yasuga H, Kamiya K, Takeuchi S, Miki N: Self-generation of twodimensional droplet array using oil-water immiscibility and replacement. Lab Chip 2018, 18:1130-1137.
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