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. 2017 Dec 27;10(2):1474–1479. doi: 10.1021/acsami.7b13183

Multiphoton-Polymerized 3D Protein Assay

Richard Wollhofen †, Markus Axmann ‡, Peter Freudenthaler §, Christian Gabriel ∥, Clemens Röhrl ‡, Herbert Stangl ‡, Thomas A Klar †, Jaroslaw Jacak †,§,*
PMCID: PMC5773935  PMID: 29280613

Abstract

graphic file with name am-2017-131838_0004.jpg

Multiphoton polymerization (MPP) enables 3D fabrication of micro- and nanoscale devices with complex geometries. Using MPP, we create a 3D platform for protein assays. Elevating the protein-binding sites above the substrate surface allows an optically sectioned readout, minimizing the inevitable background signal from nonspecific protein adsorption at the substrate surface. Two fluorescence-linked immunosorbent assays are demonstrated, the first one relying on streptavidin–biotin recognition and the second one on antibody recognition of apolipoprotein A1, a major constituent of high-density lipoprotein particles. Signal-to-noise ratios exceeding 1000 were achieved. The platform has high potential for 3D multiplexed recognition assays with an increased binding surface for on-chip flow cells.

Keywords: two photon lithography, direct laser writing, HDL, immunoassay, functional polymers, confocal microscopy

Introduction

Functional proteome analysis holds great promise for a better understanding of diseases at the individual patient level.1 Hence, technologies allowing proteome analysis continuously gain importance. Typically, the proteome is analyzed with protein microarrays. The relative amounts of target proteins in blood sera, saliva, urine, and so forth indicate the function of an organism and disease progression.2,3 The sore spot of many protein microarrays is insufficient passivation of the area surrounding the active spots, which thus limits assay performance.4 In particular, autofluorescence of the surface, unspecific binding of nontarget proteins, and imperfections in the passivation yield the background signal.5,6 Thereby, achievable contrast and assay sensitivity are reduced on flat substrates.4,6

Multiphoton polymerization (MPP) with near infrared lasers allows fabrication of complex 3D structures, with lateral and axial feature sizes down to 100 nm and 240 nm, respectively.7−11 The maximal size of the whole platform is only limited by the scanning range of the setup and can easily reach several cm.12 Therefore, MPP found many applications in research areas such as photonics,13−15 microelectronics,16,17 micromechanics,18,19 and biomedicine.20−24 For example, we immobilized streptavidin on MPP-fabricated dots and proved that the streptavidin remains capable of biotin binding.25 Nowadays, MPP enables writing of complex structures combining two or more photoresists, with defined contrast of chemical or physical properties.19,21,26−33 Nevertheless, applications such as 3D proteomic sensors have not been established with MPP yet.

In this contribution, we apply MPP to establish a 3D fluorescence immunosensor with the potential of being integrated into on-chip flow cells. The 3D platform consists of two types of acrylate polymers. The carrier scaffold is composed of a protein-repellant polymer containing polyethylene glycol. Binding pins in the nanometer range are written into the carrier scaffold with carboxyl-functional acrylates, enabling capture molecule binding.34−36 The binding pins are placed in elevated positions to achieve spatial separation from the substrate surface. The confocal readout separates the fluorescence from the detection antibodies specifically bound to the binding pins from the background signal from the surface. So far, optical sectioning has been used for imaging of cells on 3D polymer cell scaffolds.37

Results

The 3D platforms were tested for two recognition assays. First, a streptavidin–biotin interaction is shown. Second, we show antibody recognition of apolipoprotein A1 (ApoA1) in high-density lipoprotein (HDL) particles. HDLs are transport vehicles for lipids and proteins and are responsible for cholesterol transport from tissues to the liver. Screening of the HDL proteome has identified significant protein alterations in a variety of diseases, including cardiovascular diseases.38−42 Up to now, the characterization of the protein profile of HDL occurs with complex and time-consuming methods, for example, with liquid chromatography–mass spectrometry and size exclusion chromatography followed by reverse phase protein arrays.43 Our method represents a simplified approach for HDL protein profiling.

The photoresists used for MPP fabrication were a mixture of the monomers pentaerythritol triacrylate (PETA), 2-carboxyethylacrylate (CEA), and poly(ethylene glycol) diacrylate (PEGDA) (see the Experimental Section part for detailed information). An SEM image of a representative platform is shown in Figure 1b, with one column of binding pins shaded in blue. The platforms measure 16 μm × 16 μm × 5 μm, having a top square grid with 4 μm periodicity. Figure 1c sketches part of a scaffold (gray) with an attached binding pin (blue), which is covered with immobilized capture proteins. For a fluorescence readout, confocal sections were recorded and focused at the position of the binding pins. Fluorescence was excited by a 532 nm CW laser (Verdi-V5, Coherent) and a 660 nm CW laser (opus 660, Laser Quantum).

Figure 1.

Figure 1

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Fabrication and the readout of a 3D protein assay. (a) Sketch of the setup used for MPP structuring (excitation at 780 nm) and for the confocal readout (excitation at 532 and 660 nm). (b) SEM image of a 3D platform, with hanging binding pins (5 pins shaded blue). (c) Proteins are immobilized on adhesive binding pins (blue), followed by a confocal fluorescence readout. (d) Confocal optical sections show separation of the signal at the binding pins from the surface background signal. XZ and YZ slices were taken along the horizontal and vertical arrows, respectively. (e) For data acquisition, the binding pin signal was determined in 40 regions of interest (ROIs). For each ROI (6 × 6 pixels, 200 nm pixel size), the collected average photon number was determined. (f) Twenty-five ROIs were used to determine the background signal originating from the carrier scaffold.

Representative confocal slices of a platform incubated with HDL are shown in Figure 1d. The binding pin signal in the XY slice (4 μm above the surface) is well-separated from the surface background signal, which is visible in the XZ and YZ slices. For fluorescence analysis of each platform, a mask of regions of interest (ROIs) that resembles the geometry of the 40 binding pins was overlaid on each image; see Figure 1e. To correct for nonspecific protein adsorption to the scaffold, a mask of 25 ROIs is placed on the image (Figure 1f). Within these ROIs, the fluorescence signal from a platform was analyzed.

The first fluorescence-linked immunosorbent assay (FLISA) relies on the streptavidin–biotin interaction; see Figure 2a. First, Alexa 555-labeled streptavidin was immobilized on the binding pins, followed by passivation of remaining binding sites with fetal bovine serum. In the next step, the platform has been incubated with a biotinylated mouse-IgG antibody as antigen. As a probe, a secondary ATTO 655-labeled anti-(mouse-IgG) antibody was used. Figure 2b depicts a confocal microscopy image of a platform incubated with Alexa 555-labeled streptavidin; Figure 2c shows the corresponding ATTO 655-labeled anti-(mouse-IgG) antibody signal. To estimate the number of proteins per binding pin, single molecule signals were recorded. The fluorescence of individual molecules, sparsely distributed on glass, was collected. For individual Alexa 555-streptavidin molecules, 84 ± 52 fluorescence photons were collected. For single ATTO 655-anti-(mouse-IgG) antibodies, an average fluorescence photon count of 62 ± 43 was measured.

Figure 2.

Figure 2

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Streptavidin-based fluorescence-linked immunosorbent assay (FLISA) on a 3D platform. (a) First, Alexa 555-streptavidin is immobilized on the binding pins. A biotinylated mouse IgG antibody represents the antigen. Detection is performed with an ATTO 655-labeled secondary anti-(mouse-IgG) antibody. (b) Confocal XY-scan of Alexa 555-streptavidin (excitation 532 nm). (c) Confocal XY-scan of ATTO 655-anti-(mouse-IgG) (excitation 660 nm). Linear color scales are shown in the insets. (d) Logarithmic bar chart of Alexa 555 (green) and ATTO 655 (red) fluorescence signals from two experiments, showing the positive assay (left) and the control sample testing for unspecific binding of the secondary antibody (right, without the biotinylated mouse IgG antibody). The specific ATTO 655 signal is ∼165 times higher than the unspecific signal. (e) Logarithmic profiles of confocal fluorescence images along the white dashed lines in (b,c), showing a signal to noise ratio of ∼103.

The reported single pin signals show a relatively large SD. This strong pin-to-pin fluctuation is mainly caused by the stochastic chemical labeling process of the proteins and lipoproteins.44,45 Typically, labeling as well as protein adhesion to the pins are stochastic processes. Furthermore, proteins as well as lipoproteins may form clusters during storage.44,45 Hence, a broad (Poissonian-like) distribution of the signals of the pins is expected. For the intensity analysis of a whole array, we averaged the signal of all 40 pins. The calculated standard error of this average is typically below 15%.

We calculated the ratio of binding pin fluorescence to individual molecule fluorescence to give an estimate for the number of molecules per binding pin (neglecting different photon emission probabilities at the interfaces of glass, polymer, and buffer). The calculated average numbers of molecules per binding pin are ∼3140 streptavidin molecules and ∼950 secondary antibodies.

Figure 2d displays the average fluorescence signal obtained from a positive assay and from a control sample, where the primary biotinylated mouse IgG antibody was left out. The specific antibody signal is 165 times higher, compared to the control sample. Figure 2e shows logarithmic profiles of the fluorescence images in Figure 2b,c, with a signal to noise ratio exceeding 3 orders of magnitude. The selective recognition of the biotinylated antibody on streptavidin-coated binding pins proves the functionality of the immobilized proteins as well as the applicability of the platform for immunoassays.

A medically more relevant application of the new platform was tested with a FLISA of ApoA1, the main constituent of the HDL particle; see Figure 3a. First, HDL was immobilized on the structure. Passivation of remaining adhesive surfaces was performed with bovine serum albumin in this case because fetal bovine serum contains (bovine) HDL particles. The passivated platform was incubated with the chicken anti-ApoA1 antibody. For visualization of the binding, an Alexa 555-labeled anti-(chicken-IgY) antibody was used. Figure 3b shows a confocal image of a platform incubated with Alexa 647-labeled HDL. Figure 3c depicts the corresponding Alexa 555-anti-(chicken-IgY) fluorescence signal. To determine the number of molecules per binding pin, single molecule signals were measured. The collected average fluorescence photon counts of Alexa 647-HDL and the Alexa 555-anti-(chicken-IgY) antibody were 278 ± 211 and 85 ± 71, respectively. By calculating the ratio of binding pin fluorescence to individual molecule fluorescence, we get an estimated average number of ∼500 HDL molecules and ∼1420 secondary antibodies per binding pin. These numbers indicate that on average, three Alexa 555-labeled antibodies were attached to one HDL particle via chicken anti-ApoA1 antibodies. The selectivity of the binding was tested in control experiments without incubation with HDL or without chicken anti-ApoA1 antibodies. A comparison of a positive assay versus two control samples is shown in a logarithmic bar chart in Figure 3d. The detected signals of Alexa 647-HDL and the Alexa 555-labeled anti-(chicken-IgY) antibody are comparable for the positive assay (left). For the first control experiment (middle, unspec. binding 1st ab), HDL particles were omitted to determine the nonspecific chicken anti-ApoA1 antibody adsorption, which was detected with the Alexa 555-anti-(chicken-IgY) antibody. The Alexa 555 signal was lower by 3 orders of magnitude compared to the positive assay. For the second control (right, unspec. binding 2nd ab), the primary chicken antibody was not added to the HDL carrying binding pins. Adding the Alexa 555-anti-(chicken-IgY) antibody for detection, a more than 300 times lower signal compared to the positive assay was observed. Figure 3e depicts logarithmic profiles of the Alexa 647-HDL (red) and Alexa 555-labeled anti-(chicken-IgY) antibody (green) fluorescence signals along the dashed lines in Figure 3b,c. The selective recognition of ApoA1 proves the applicability of our platforms for HDL profiling.

Figure 3.

Figure 3

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HDL-ApoA1 lipoprotein assay on a 3D platform. (a) Alexa 647-labeled HDL is immobilized on the binding pin. The chicken anti-ApoA1 antibody binds to ApoA1. A secondary Alexa 555-labeled anti-(chicken-IgY) antibody is used for detection. (b) Confocal XY-scan of Alexa 647-HDL (excitation 660 nm). (c) Confocal XY-scan of Alexa 555-labeled anti-(chicken-IgY) antibody (excitation 532 nm). Linear color scales are shown in the insets. (d) Logarithmic bar chart of a positive assay (left) and two negative controls (middle, right) to test for unspecific binding of the primary antibody (1st ab) and the secondary antibody (2nd ab). Middle: No HDL was immobilized, but both antibodies were applied. Right: HDL was immobilized, no primary antibody was used, but the secondary Alexa 555-labeled anti-(chicken-IgY) antibody was applied. (e) Logarithmic profiles of confocal fluorescence images, along the white dashed lines in (b,c). The signal to noise ratio exceeds 103.

Discussion

An obvious advantage of a confocally readout assay, elevated 4 μm above the substrate, is the suppression of background fluorescence from unspecific binding to the substrate. Optical sectioning provided by confocal or multiphoton microscopy enables to observe a single focal plane with a shallow depth of field. The out-of-focus signal is suppressed, which enables higher contrast and sensitivity.46,47 Numerous standard biochip readers use confocal detection for 2D assays, without taking advantage of optical sectioning. Nevertheless, an existing standard reader would allow straightforward integration of 3D assays into existing workflows.

Moreover, there is another big advantage of the proposed 3D assay: the increase in the reactive surface area. In the current case, the proteins were attached to hanging binding pins as shown in Figure 1b,c. The binding pin dimensions were ∼450 nm in diameter and ∼1 μm in height. The calculated surface was therefore ∼1.41 μm2 (assuming a cylinder with a half sphere on top), which is ∼9 times larger compared to a two-dimensional spot with the same diameter (0.16 μm2). Therefore, an almost tenfold higher number of capture molecules can be presented on the same footprint by the additional extent along the axial direction. This number could easily be further improved, for example, by stacking such structures or writing of longer pins. Especially, in the case of low numerical aperture (NA) objective lenses (NA = 0.5, λ = 650 nm), which are typically used in microarray scanners,48 the binding surface in the readout volume could be increased more than 100 times by using subdiffraction structuring, as described in more detail in the Supporting Information. Consequently, on the same footprint, the steric accessibility, the amount of binding sites, and the functional density could also be increased.49,50 A higher functional density allows fabrication of even smaller devices, enabling higher throughput and lower sample consumption.5,6,51−54 Particularly, microfluidics would benefit from the increased binding surface because channels of ∼100 μm width limit the available footprint. MPP can be readily combined with microfluidics to overcome diffusive limitations: higher velocities of the Poiseuille flow can be reached for elevated reactive binding pins.55−57 To improve the biocompatibility, the platforms could be fabricated out of unsensitized photoresists, avoiding the addition of potentially fluorescent or toxic photoinitiators.58

So far, only micro-bead assays,59,60 a 2.5D polymer living graft polymerization assay,61 and stacked 2D FLISA microarrays46,49,62 have been realized and introduced as 3D assays. On the one hand, because the stacked 2D FLISA consists of planar assays,49 the background signal is present in each section. On the other hand, micro-bead assays have limitations relating to microfluidics because the micro-bead colloids often clot and disturb the flow and mixing.63−65

In our experiments, the lipoproteins have been purified and 5 ng of HDL has been used for incubation. If an average weight of ∼210 kD is assumed,66 24 fmol of HDL molecules per platform has been used for prototyping (lower concentrations have not been tested). So far, our unique methodology presented here shows the detection of HDL over 3 orders of magnitude of dynamic range via antibody binding to Apo-A1 using a three-dimensional structure. Thereby, this limit arises from the biochemical interaction/binding selectivity and not from the physical signal detection as shown previously using another system, likewise with single-molecule sensitivity.5,6

Conclusions and Outlook

In summary, we have shown the applicability of 3D MPP platforms for proteomics. A two-component structure consisting of a protein-repellant scaffold and submicrometer-sized protein-adhesive binding pins was used as a 3D protein recognition platform. We tested the 3D platforms for two FLISA immunoassays. The first FLISA was a streptavidin–biotin dummy system; the second FLISA was designed for protein profiling of HDL particles. Using a confocal readout, we obtained a signal to noise ratio of over 3 orders of magnitude for the optical signal in both cases. In principle, the design of the 3D platform is flexible, enabling versatile applicability for molecular recognition assays, tissue engineering, and fluid dynamic analysis. The three-dimensional nature of our system increases the surface area with the detection volume and thereby the sensitivity and the magnitude of the dynamic range. Typically, the dynamic range is limited, on the one hand, by the analyte concentration and on the other hand by the number of immobilized probe molecules (specific signal) and the local background. In the case of small dot surfaces, the reaction area limits the number of probe molecules on the surface and hence the maximally obtained signal. Multiplexing has not been tested within one microarray. Multichannel microfluidics might circumvent this limitation.67 A multiplexed analysis may also be achieved by fabricating binding pins with different chemical functionalities.26,68,69 Using orthogonal chemistry would then allow placement and covalent coupling of different capture molecules. Binding pins with functional polymers could be used to immobilize gold nanoparticles, using them as anchors for label-free plasmonic sensing.70,71 Last but not least, the enhancement of the reactive surface due to the 3D geometry and the possibility of optical sectioning provides completely new access to the protein chip design.

Experimental Section

The photoresists used for MPP fabrication were a mixture of the monomers PETA (Sigma-Aldrich), CEA (Sigma-Aldrich), and PEGDA (average Mn 575, Sigma-Aldrich). The photoresist used for the protein-repellant scaffold consists of a monomer mixture of 4:1 PEGDA–PETA with 1 wt % IRGACURE 819 (BASF Schweiz AG) as the photoinitiator. The binding pins were structured with a photoresist composed of a 9:1 PETA–CEA monomer mixture with 1 wt % IRGACURE 819 as the photoinitiator. Figure 1a shows a sketch of the setup used for MPP lithography and confocal fluorescence microscopy. Acrylate polymerization was initiated via multiphoton absorption of 780 nm ultrashort laser pulses (50 MHz repetition rate, 100 fs pulse duration, FemtoRay 780, Menlo Systems GmbH), focused with an oil immersion objective lens (Zeiss α-plan Apochromat, 100×, NA = 1.46). First, the carrier scaffold was fabricated using the protein-repellant PEGDA–PETA photoresist. Next, the binding pins were written using the protein-adhesive PETA–CEA photoresist. Detailed descriptions of the lithography setup and the fabrication process are given in the Supporting Information.

Acknowledgments

We would like to cordially thank Heidi Piglmayer-Brezina for taking the SEM images and Habed Habibzadeh, Bernhard Fragner, and Alfred Nimmervoll for technical support.

Supporting Information Available

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acsami.7b13183.

  • HDL preparation and the labeling procedure, a detailed setup description, fabrication protocol, protein assay protocols, data acquisition protocols, and an estimation of surface enhancement by 3D MPP structuring (PDF)

The work was funded by the Austrian Science Fund (FWF) projects P 26461 (T.A.K., C.G.), P 29110-B21 (H.S., M.A.) and P 25763-B13 (C.R.). Additionally, the work was funded by the Interreg European Fund project ATCZ14 (J.J.) and the Upper Austrian University of Applied Sciences basic funding BF-PolFunk (J.J.).

The authors declare no competing financial interest.

Supplementary Material

am7b13183_si_001.pdf (205.6KB, pdf)

References

  1. Lee J.-R.; Magee D. M.; Gaster R. S.; LaBaer J.; Wang S. X. Emerging Protein Array Technologies for Proteomics. Expert Rev. Proteomics 2013, 10, 65–75. 10.1586/epr.12.67. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Hartmann M.; Roeraade J.; Stoll D.; Templin M. F.; Joos T. O. Protein Microarrays for Diagnostic Assays. Anal. Bioanal. Chem. 2009, 393, 1407–1416. 10.1007/s00216-008-2379-z. [DOI] [PubMed] [Google Scholar]
  3. Mitchell P. A Perspective on Protein Microarrays. Nat. Biotechnol. 2002, 20, 225–229. 10.1038/nbt0302-225. [DOI] [PubMed] [Google Scholar]
  4. Jonkheijm P.; Weinrich D.; Schröder H.; Niemeyer C. M.; Waldmann H. Chemical Strategies for Generating Protein Biochips. Angew. Chem., Int. Ed. 2008, 47, 9618–9647. 10.1002/anie.200801711. [DOI] [PubMed] [Google Scholar]
  5. Hesse J.; Jacak J.; Kasper M.; Regl G.; Eichberger T.; Winklmayr M.; Aberger F.; Sonnleitner M.; Schlapak R.; Howorka S.; Muresan L.; Frischauf A.-M.; Schütz G. J. RNA Expression Profiling at the Single Molecule Level. Genome Res. 2006, 16, 1041–1045. 10.1101/gr.4999906. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Schmidt R.; Jacak J.; Schirwitz C.; Stadler V.; Michel G.; Marmé N.; Schütz G. J.; Hoheisel J. D.; Knemeyer J.-P. Single-Molecule Detection on a Protein-Array Assay Platform for the Exposure of a Tuberculosis Antigen. J. Proteome Res. 2011, 10, 1316–1322. 10.1021/pr101070j. [DOI] [PubMed] [Google Scholar]
  7. Maruo S.; Nakamura O.; Kawata S. Three-Dimensional Microfabrication with Two-Photon-Absorbed Photopolymerization. Opt. Lett. 1997, 22, 132–134. 10.1364/ol.22.000132. [DOI] [PubMed] [Google Scholar]
  8. Farsari M.; Vamvakaki M.; Chichkov B. N. Multiphoton Polymerization of Hybrid Materials. J. Opt. 2010, 12, 124001. 10.1088/2040-8978/12/12/124001. [DOI] [Google Scholar]
  9. Li L.; Fourkas J. T. Multiphoton Polymerization. Mater. Today 2007, 10, 30–37. 10.1016/s1369-7021(07)70130-x. [DOI] [Google Scholar]
  10. Fischer J.; Wegener M. Three-Dimensional Optical Laser Lithography Beyond the Diffraction Limit. Laser Photonics Rev. 2013, 7, 22–44. 10.1002/lpor.201100046. [DOI] [Google Scholar]
  11. DeVoe R. J.; Kalweit H. W.; Leatherdale C. A.; Williams T. R.. Voxel Shapes in Two-Photon Microfabrication. Proc. SPIE 4797: Multiphoton Absorption and Nonlinear Transmission Processes: Materials, Theory, and Applications, 2003; pp 310–316.
  12. Bückmann T.; Stenger N.; Kadic M.; Kaschke J.; Frölich A.; Kennerknecht T.; Eberl C.; Thiel M.; Wegener M. Tailored 3D Mechanical Metamaterials Made by Dip-In Direct-Laser-Writing Optical Lithography. Adv. Mater. 2012, 24, 2710–2714. 10.1002/adma.201200584. [DOI] [PubMed] [Google Scholar]
  13. Sherwood T.; Young A. C.; Takayesu J.; Jen A. K.Y.; Dalton L. R.; Chen A. Microring Resonators on Side-Polished Optical Fiber. IEEE Photonics Technol. Lett. 2005, 17, 2107–2109. 10.1109/lpt.2005.854405. [DOI] [Google Scholar]
  14. Yokoyama S.; Nakahama T.; Miki H.; Mashiko S. Fabrication of Three-Dimensional Microstructure in Optical-Gain Medium Using Two-Photon-Induced Photopolymerization Technique. Thin Solid Films 2003, 438, 452–456. 10.1016/s0040-6090(03)00804-6. [DOI] [Google Scholar]
  15. Haberko J.; Muller N.; Scheffold F. Direct Laser Writing of Three-Dimensional Network Structures as Templates for Disordered Photonic Materials. Phys. Rev. A 2013, 88, 043822. 10.1103/physreva.88.043822. [DOI] [Google Scholar]
  16. Kim J. H.; Chang W. S.; Kim D.; Yang J. R.; Han J. T.; Lee G.-W.; Kim J. T.; Seol S. K. 3D Printing of Reduced Graphene Oxide Nanowires. Adv. Mater. 2015, 27, 157–161. 10.1002/adma.201404380. [DOI] [PubMed] [Google Scholar]
  17. Skylar-Scott M. A.; Gunasekaran S.; Lewis J. A. Laser-Assisted Direct Ink Writing of Planar and 3D Metal Architectures. Proc. Natl. Acad. Sci. U.S.A. 2016, 113, 6137–6142. 10.1073/pnas.1525131113. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Maruo S.; Ikuta K.; Korogi H. Force-Controllable, Optically Driven Micromachines Fabricated by Single-Step Two-Photon Microstereolithography. J. Microelectromech. Syst. 2003, 12, 533–539. 10.1109/jmems.2003.817894. [DOI] [Google Scholar]
  19. Zandrini T.; Taniguchi S.; Maruo S. Magnetically Driven Micromachines Created by Two-Photon Microfabrication and Selective Electroless Magnetite Plating for Lab-on-a-Chip Applications. Micromachines 2017, 8, 35. 10.3390/mi8020035. [DOI] [Google Scholar]
  20. Melissinaki V.; Gill A. A.; Ortega I.; Vamvakaki M.; Ranella A.; Haycock J. W.; Fotakis C.; Farsari M.; Claeyssens F. Direct Laser Writing of 3D Scaffolds for Neural Tissue Engineering Applications. Biofabrication 2011, 3, 045005. 10.1088/1758-5082/3/4/045005. [DOI] [PubMed] [Google Scholar]
  21. Klein F.; Richter B.; Striebel T.; Franz C. M.; von Freymann G.; Wegener M.; Bastmeyer M. Two-Component Polymer Scaffolds for Controlled Three-Dimensional Cell Culture. Adv. Mater. 2011, 23, 1341–1345. 10.1002/adma.201004060. [DOI] [PubMed] [Google Scholar]
  22. Torgersen J.; Ovsianikov A.; Mironov V.; Pucher N.; Qin X.; Li Z.; Cicha K.; Machacek T.; Liska R.; Jantsch V.; Stampfl J. Photo-Sensitive Hydrogels for Three-Dimensional Laser Microfabrication in the Presence of Whole Organisms. J. Biomed. Opt. 2012, 17, 105008. 10.1117/1.jbo.17.10.105008. [DOI] [PubMed] [Google Scholar]
  23. Wiesbauer M.; Wollhofen R.; Vasic B.; Schilcher K.; Jacak J.; Klar T. A. Nano-anchors with Single Protein Capacity Produced with STED Lithography. Nano Lett. 2013, 13, 5672–5678. 10.1021/nl4033523. [DOI] [PubMed] [Google Scholar]
  24. Claeyssens F.; Hasan E. A.; Gaidukeviciute A.; Achilleos D. S.; Ranella A.; Reinhardt C.; Ovsianikov A.; Shizhou X.; Fotakis C.; Vamvakaki M.; Chichkov B. N.; Farsari M. Three-Dimensional Biodegradable Structures Fabricated by Two-Photon Polymerization. Langmuir 2009, 25, 3219–3223. 10.1021/la803803m. [DOI] [PubMed] [Google Scholar]
  25. Wolfesberger C.; Wollhofen R.; Buchegger B.; Jacak J.; Klar T. A. Streptavidin Functionalized Polymer Nanodots Fabricated by Visible Light Lithography. J. Nanobiotechnol. 2015, 13, 27. 10.1186/s12951-015-0084-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Ceylan H.; Yasa I. C.; Sitti M. 3D Chemical Patterning of Micromaterials for Encoded Functionality. Adv. Mater. 2017, 29, 1605072. 10.1002/adma.201605072. [DOI] [PubMed] [Google Scholar]
  27. Farrer R. A.; LaFratta C. N.; Li L.; Praino J.; Naughton M. J.; Saleh B. E. A.; Teich M. C.; Fourkas J. T. Selective Functionalization of 3-D Polymer Microstructures. J. Am. Chem. Soc. 2006, 128, 1796–1797. 10.1021/ja0583620. [DOI] [PubMed] [Google Scholar]
  28. Claus T. K.; Richter B.; Hahn V.; Welle A.; Kayser S.; Wegener M.; Bastmeyer M.; Delaittre G.; Barner-Kowollik C. Simultaneous Dual Encoding of Three-Dimensional Structures by Light-Induced Modular Ligation. Angew. Chem., Int. Ed. 2016, 55, 3817–3822. 10.1002/anie.201509937. [DOI] [PubMed] [Google Scholar]
  29. Quick A. S.; Fischer J.; Richter B.; Pauloehrl T.; Trouillet V.; Wegener M.; Barner-Kowollik C. Preparation of Reactive Three-Dimensional Microstructures via Direct Laser Writing and Thiol-ene Chemistry. Macromol. Rapid Commun. 2013, 34, 335–340. 10.1002/marc.201200796. [DOI] [PubMed] [Google Scholar]
  30. Richter B.; Hahn V.; Bertels S.; Claus T. K.; Wegener M.; Delaittre G.; Barner-Kowollik C.; Bastmeyer M. Guiding Cell Attachment in 3D Microscaffolds Selectively Functionalized with Two Distinct Adhesion Proteins. Adv. Mater. 2017, 29, 1604342. 10.1002/adma.201604342. [DOI] [PubMed] [Google Scholar]
  31. Richter B.; Pauloehrl T.; Kaschke J.; Fichtner D.; Fischer J.; Greiner A. M.; Wedlich D.; Wegener M.; Delaittre G.; Barner-Kowollik C.; Bastmeyer M. Three-Dimensional Microscaffolds Exhibiting Spatially Resolved Surface Chemistry. Adv. Mater. 2013, 25, 6117–6122. 10.1002/adma.201302678. [DOI] [PubMed] [Google Scholar]
  32. Scheiwe A. C.; Frank S. C.; Autenrieth T. J.; Bastmeyer M.; Wegener M. Subcellular Stretch-Induced Cytoskeletal Response of Single Fibroblasts within 3D Designer Scaffolds. Biomaterials 2015, 44, 186–194. 10.1016/j.biomaterials.2014.12.018. [DOI] [PubMed] [Google Scholar]
  33. Rekštyte S. Direct Laser Fabrication of Composite Material 3D Microstructured Scaffolds. J. Laser Micro/Nanoeng. 2014, 9, 25–30. 10.2961/jlmn.2014.01.0006. [DOI] [Google Scholar]
  34. Park K.; Ju Y. M.; Son J. S.; Ahn K.-D.; Han D. K. Surface Modification of Biodegradable Electrospun Nanofiber Scaffolds and Their Interaction with Fibroblasts. J. Biomater. Sci., Polym. Ed. 2007, 18, 369–382. 10.1163/156856207780424997. [DOI] [PubMed] [Google Scholar]
  35. Arima Y.; Iwata H. Effects of Surface Functional Groups on Protein Adsorption and Subsequent Cell Adhesion Using Self-Assembled Monolayers. J. Mater. Chem. 2007, 17, 4079–4087. 10.1039/b708099a. [DOI] [PubMed] [Google Scholar]
  36. Löfås S.; Johnsson B. A Novel Hydrogel Matrix on Gold Surfaces in Surface Plasmon Resonance Sensors for Fast and Efficient Covalent Immobilization of Ligands. J. Chem. Soc., Chem. Commun. 1990, 1526–1528. 10.1039/c39900001526. [DOI] [Google Scholar]
  37. Accardo A.; Blatché M.-C.; Courson R.; Loubinoux I.; Thibault C.; Malaquin L.; Vieu C. Multiphoton Direct Laser Writing and 3D Imaging of Polymeric Freestanding Architectures for Cell Colonization. Small 2017, 13, 1700621. 10.1002/smll.201700621. [DOI] [PubMed] [Google Scholar]
  38. Burillo E.; Jorge I.; Martínez-López D.; Camafeita E.; Blanco-Colio L. M.; Trevisan-Herraz M.; Ezkurdia I.; Egido J.; Michel J.-B.; Meilhac O.; Vázquez J.; Martin-Ventura J. L. Quantitative HDL Proteomics Identifies Peroxiredoxin-6 as a Biomarker of Human Abdominal Aortic Aneurysm. Sci. Rep. 2016, 6, 38477. 10.1038/srep38477. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Davidsson P.; Hulthe J.; Fagerberg B.; Camejo G. Proteomics of Apolipoproteins and Associated Proteins from Plasma High-Density Lipoproteins. Arterioscler., Thromb., Vasc. Biol. 2010, 30, 156–163. 10.1161/atvbaha.108.179317. [DOI] [PubMed] [Google Scholar]
  40. Heinecke J. W. The HDL Proteome: A marker–and perhaps mediator–of coronary artery disease. J. Lipid Res. 2009, 50, S167–S171. 10.1194/jlr.r800097-jlr200. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Heinecke J. W. HDL’s Protein Cargo: Friend or foe in cardioprotection?. Circulation 2013, 127, 868–869. 10.1161/circulationaha.112.000889. [DOI] [PubMed] [Google Scholar]
  42. Vaisar T.; Tang C.; Babenko I.; Hutchins P.; Wimberger J.; Suffredini A. F.; Heinecke J. W. Inflammatory Remodeling of the HDL Proteome Impairs Cholesterol Efflux Capacity. J. Lipid Res. 2015, 56, 1519–1530. 10.1194/jlr.m059089. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Yassine H. N.; Jackson A. M.; Borges C. R.; Billheimer D.; Koh H.; Smith D.; Reaven P.; Lau S. S.; Borchers C. H. The Application of Multiple Reaction Monitoring and Multi-Analyte Profiling to HDL Proteins. Lipids Health Dis. 2014, 13, 8. 10.1186/1476-511x-13-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Goding J. W.Monoclonal Antibodies: Principle and Practice: Production and Application of Monoclonal Antibodies in Cell Biology, Biochemistry and Immunology, 3rd ed.; Academic: London, 1996. [Google Scholar]
  45. Lusa S.; Jauhiainen M.; Metso J.; Somerharju P.; Ehnholm C. The Mechanism of Human Plasma Phospholipid Transfer Protein-Induced Enlargement of High-Density Lipoprotein Particles: Evidence for Particle Fusion. Biochem. J. 1996, 313, 275–282. 10.1042/bj3130275. [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Ghafari H.; Zhou Y.; Ali S.; Hanley Q. S. Confocal Detection of Planar Homogeneous and Heterogeneous Immunosorbent Assays. J. Biomed. Opt. 2009, 14, 064022. 10.1117/1.3268772. [DOI] [PubMed] [Google Scholar]
  47. Wright S. J.; Centonze V. E.; Stricker S. A.; DeVries P. J.; Paddock S. W.; Schatten G.. Introduction to Confocal Microscopy and Three-Dimensional Reconstruction. Methods in Cell Biology; Academic Press, 1993; Vol. 38, pp 1–45. [DOI] [PubMed] [Google Scholar]
  48. Schena M.Microarray Analysis; Wiley-Liss: Hoboken, NJ, 2003. [Google Scholar]
  49. Ghafari H.; Hanley Q. S. Analysis of Layered Assays and Volume Microarrays in Stratified Media. Analyst 2012, 137, 5520–5526. 10.1039/c2an35767d. [DOI] [PubMed] [Google Scholar]
  50. Kusnezow W.; Syagailo Y. V.; Rüffer S.; Baudenstiel N.; Gauer C.; Hoheisel J. D.; Wild D.; Goychuk I. Optimal Design of Microarray Immunoassays to Compensate for Kinetic Limitations. Mol. Cell. Proteomics 2006, 5, 1681–1696. 10.1074/mcp.t500035-mcp200. [DOI] [PubMed] [Google Scholar]
  51. Marcy Y.; Ishoey T.; Lasken R. S.; Stockwell T. B.; Walenz B. P.; Halpern A. L.; Beeson K. Y.; Goldberg S. M. D.; Quake S. R. Nanoliter Reactors Improve Multiple Displacement Amplification of Genomes from Single Cells. PLoS Genet. 2007, 3, e155 10.1371/journal.pgen.0030155. [DOI] [PMC free article] [PubMed] [Google Scholar]
  52. Burgin E.; Salehi-Reyhani A.; Barclay M.; Brown A.; Kaplinsky J.; Novakova M.; Neil M. A. A.; Ces O.; Willison K. R.; Klug D. R. Absolute Quantification of Protein Copy Number Using a Single-Molecule-Sensitive Microarray. Analyst 2014, 139, 3235–3244. 10.1039/c4an00091a. [DOI] [PubMed] [Google Scholar]
  53. Templin M. F.; Stoll D.; Schrenk M.; Traub P. C.; Vöhringer C. F.; Joos T. O. Protein Microarray Technology. Trends Biotechnol. 2002, 20, 160–166. 10.1016/s0167-7799(01)01910-2. [DOI] [PubMed] [Google Scholar]
  54. Ekins R. P.; Chu F. W. Multianalyte Microspot Immunoassay–Microanalytical “Compact Disk” of the Future. Clin. Chem. 1991, 37, 1955–1967. [PubMed] [Google Scholar]
  55. Laza S. C.; Polo M.; Neves A. A. R.; Cingolani R.; Camposeo A.; Pisignano D. Two-Photon Continuous Flow Lithography. Adv. Mater. 2012, 24, 1304–1308. 10.1002/adma.201103357. [DOI] [PubMed] [Google Scholar]
  56. Wu D.; Wu S.-Z.; Xu J.; Niu L.-G.; Midorikawa K.; Sugioka K. Hybrid Femtosecond Laser Microfabrication to Achieve True 3D Glass/Polymer Composite Biochips with Multiscale Features and High Performance: The concept of ship-in-a-bottle biochip. Laser Photonics Rev. 2014, 8, 458–467. 10.1002/lpor.201400005. [DOI] [Google Scholar]
  57. Leary T. F.; Manafirasi S.; Maldarelli C. Mass Transfer in the Biomolecular Binding of a Target Against Probe Molecules on the Surface of Microbeads Sequestered in Wells in a Microfluidic Cell. Lab Chip 2015, 15, 459–477. 10.1039/c4lc01185f. [DOI] [PubMed] [Google Scholar]
  58. Jonušauskas L.; Gailevičius D.; Mikoliu̅naitė L.; Sakalauskas D.; Šakirzanovas S.; Juodkazis S.; Malinauskas M. Optically Clear and Resilient Free-Form μ-Optics 3D-Printed via Ultrafast Laser Lithography. Materials 2017, 10, 12. 10.3390/ma10010012. [DOI] [PMC free article] [PubMed] [Google Scholar]
  59. Chen J. A Microsphere-Based Assay for Multiplexed Single Nucleotide Polymorphism Analysis Using Single Base Chain Extension. Genome Res. 2000, 10, 549–557. 10.1101/gr.10.4.549. [DOI] [PMC free article] [PubMed] [Google Scholar]
  60. Treindl F.; Ruprecht B.; Beiter Y.; Schultz S.; Döttinger A.; Staebler A.; Joos T. O.; Kling S.; Poetz O.; Fehm T.; Neubauer H.; Kuster B.; Templin M. F. A Bead-Based Western for High-Throughput Cellular Signal Transduction Analyses. Nat. Commun. 2016, 7, 12852. 10.1038/ncomms12852. [DOI] [PMC free article] [PubMed] [Google Scholar]
  61. Lin Z.; Ma Y.; Zhao C.; Chen R.; Zhu X.; Zhang L.; Yan X.; Yang W. An Extremely Simple Method for Fabricating 3D Protein Microarrays with an Anti-Fouling Background and High Protein Capacity. Lab Chip 2014, 14, 2505–2514. 10.1039/c4lc00223g. [DOI] [PubMed] [Google Scholar]
  62. Ghafari H.; Parambath M.; Hanley Q. S. Macromolecular Binding and Kinetic Analysis with Optically Sectioned Planar Format Assays. Analyst 2012, 137, 4809–4814. 10.1039/c2an35134j. [DOI] [PubMed] [Google Scholar]
  63. Elshal M. F.; McCoy J. P. Multiplex Bead Array Assays: Performance Evaluation and Comparison of Sensitivity to ELISA. Methods 2006, 38, 317–323. 10.1016/j.ymeth.2005.11.010. [DOI] [PMC free article] [PubMed] [Google Scholar]
  64. Nolan J. P.; Mandy F. Multiplexed and Microparticle-Based Analyses: Quantitative Tools for the Large-Scale Analysis of Biological Systems. Cytometry, Part A 2006, 69, 318–325. 10.1002/cyto.a.20266. [DOI] [PMC free article] [PubMed] [Google Scholar]
  65. Sammak P.; Rosania G.; Zana L. J.; Ippolito K.; Bush J.; Friedman A.; Tencza S. B.; Kapur R.. Microbead-Based Test Plates and Test Methods for Fluorescence Imaging Systems. U.S. Patent 6,905,881, 2005.
  66. Cox A. C.; Tanford C. The Molecular Weights of Porcine Plasma High Density Lipoprotein and its Subunits. J. Biol. Chem. 1968, 243, 3083–3087. [PubMed] [Google Scholar]
  67. Diercks A. H.; Ozinsky A.; Hansen C. L.; Spotts J. M.; Rodriguez D. J.; Aderem A. A Microfluidic Device for Multiplexed Protein Detection in Nano-Liter Volumes. Anal. Biochem. 2009, 386, 30–35. 10.1016/j.ab.2008.12.012. [DOI] [PMC free article] [PubMed] [Google Scholar]
  68. Wollhofen R.; Buchegger B.; Eder C.; Jacak J.; Kreutzer J.; Klar T. A. Functional Photoresists for Sub-Diffraction Stimulated Emission Depletion Lithography. Opt. Mater. Express 2017, 7, 2538–2559. 10.1364/ome.7.002538. [DOI] [Google Scholar]
  69. Buchegger B.; Kreutzer J.; Plochberger B.; Wollhofen R.; Sivun D.; Jacak J.; Schütz G. J.; Schubert U.; Klar T. A. Stimulated Emission Depletion Lithography with Mercapto-Functional Polymers. ACS Nano 2016, 10, 1954–1959. 10.1021/acsnano.5b05863. [DOI] [PMC free article] [PubMed] [Google Scholar]
  70. Raschke G.; Kowarik S.; Franzl T.; Sönnichsen C.; Klar T. A.; Feldmann J.; Nichtl A.; Kürzinger K. Biomolecular Recognition Based on Single Gold Nanoparticle Light Scattering. Nano Lett. 2003, 3, 935–938. 10.1021/nl034223+. [DOI] [Google Scholar]
  71. Hernandez F. J.; Dondapati S. K.; Ozalp V. C.; Pinto A.; O’Sullivan C. K.; Klar T. A.; Katakis I. Label Free Optical Sensor for Avidin Based on Single Gold Nanoparticles Functionalized with Aptamers. J. Biophotonics 2009, 2, 227–231. 10.1002/jbio.200910006. [DOI] [PubMed] [Google Scholar]

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