Programming Cell Adhesion for On-Chip Sequential Boolean Logic

Communication pubs.acs.org/JACS

Programming Cell Adhesion for On-Chip Sequential Boolean Logic Functions Xiangmeng Qu,†,∥ Shaopeng Wang,‡,∥ Zhilei Ge,‡,∥ Jianbang Wang,‡ Guangbao Yao,‡ Jiang Li,‡ Xiaolei Zuo,‡ Jiye Shi,§ Shiping Song,‡ Lihua Wang,‡ Li Li,† Hao Pei,*,† and Chunhai Fan*,‡ †

Shanghai Key Laboratory of Green Chemistry and Chemical Processes, School of Chemistry and Molecular Engineering, East China Normal University, 500 Dongchuan Road, Shanghai, 200241, P. R. China ‡ Division of Physical Biology & Bioimaging Center, Shanghai Synchrotron Radiation Facility, Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, P. R. China § Kellogg College, University of Oxford, Oxford, OX2 6PN, U.K. S Supporting Information *

with room-temperature on-chip cell manipulation,32 shedding new light on theranostics33−35 and regenerative medicine. Figure 1a shows the diagram of a single logic gate layer configured. Predesigned input signal strands enable program-

ABSTRACT: Programmable remodelling of cell surfaces enables high-precision regulation of cell behavior. In this work, we developed in vitro constructed DNA-based chemical reaction networks (CRNs) to program on-chip cell adhesion. We found that the RGD-functionalized DNA CRNs are entirely noninvasive when interfaced with the fluidic mosaic membrane of living cells. DNA toehold with different lengths could tunably alter the release kinetics of cells, which shows rapid release in minutes with the use of a 6-base toehold. We further demonstrated the realization of Boolean logic functions by using DNA strand displacement reactions, which include multi-input and sequential cell logic gates (AND, OR, XOR, and ANDOR). This study provides a highly generic tool for selforganization of biological systems.

C

Figure 1. Operational principle and architecture of D-CRNs for performing cell-based biocomputation in vitro using Boolean logic gates. (a) The abstract diagram of a single logic gate layer for programmable regulation of on-chip cell adhesion (right top) and detachment (right bottom). (b) A single input DNA NOT-gate for dynamic display of cell-specific ligands (RGD) by exploiting toeholdmediated DNA strand displacement mechanism. (c) D-CRNs for multi-input and sequential cell logic gates.

1−3

hemical reaction networks (CRNs) play important roles in various important cellular processes, which allow dynamic regulation of cell−cell communications and interactions between mammalian cells4−7 and the extracellular matrix (ECM).8−10 As a mimic of natural biosystems, artificial ECMs have been designed to dynamically display cell-specific ligands for reversible control of cell adhesion, providing a chemical approach for intelligent drug delivery,11,12 biological separation,10 and cell/tissue engineering.13 Nevertheless, most stimuli-responsive biointerfaces triggered by only single inputs, e.g., temperature,14 light,15 potential and/or specific biomolecular ligands,16 often do not satisfy the requirements for designing bioinspired computers with complex functions. It is thus highly desirable to develop programmable methods for regulating cell adhesion with multi-input simulation. DNA-based CRNs (D-CRNs) are intrinsically programmable and can be tuned to design modular cell-based biocomputation in vitro. 17−20 Especially, strand displacement reactions (SDRs)21,22 have demonstrated high potential for developing smart nanorobots,23−26 image processing,1 gene regulation,27−29 and neuron-like computation.30,31 In this work, we developed an SDR-based method to program cell adhesion with sequential Boolean logic functions.19,31 These D-CRNs work essentially in mild conditions and are fully compatible © 2017 American Chemical Society

mable regulation of on-chip cell adhesion and detachment, which forms the basis of multi-input and sequential cell logic gates. Specifically, the logic gate layer was constructed by anchoring DNA strands onto the surface of glass slides via the avidin−biotin interaction. A synthetic cell-adhesive peptide, RGD (Arg-Gly-Asp), linked on ssDNA was then hybridized with surface-confined DNA layers. Fluorescence microscopy showed that HeLa cells were attached on the RGD-coated surfaces after 2-h incubation, with extended spindle-shape-like morphology (Figure 1a). The regulation of on-chip cell behavior was triggered by input strands using SDR, in which an ssDNA (input strand) displaces the RGD coupled strand to form a double-stranded complex with the aid of a short toehold domain21 (Figure 1b). Since this system relies exclusively on Received: April 21, 2017 Published: July 17, 2017 10176

DOI: 10.1021/jacs.7b04040 J. Am. Chem. Soc. 2017, 139, 10176−10179

Communication

Journal of the American Chemical Society

Figure 2. (a) Schematic illustration of reversible cell binding on chip that led to DNA modification on the fluid-mosaic structure of cell membranes. (b) The patched distribution of DNA strands on fixed cells (top panel) and homogeneous distribution of DNA strands on live cells (bottom panel) confirming the directional interaction in D-CRNs. Fluorescence live cell adhesion and detachment on glass surface. (c, d) Kinetic characterization of D-CRNs by conducting FACS analysis on released cells upon the addition of input strand at different time intervals (0, 2.5, 5, 7.5, 10, and 20 min).

to participate in feedback regulation of integrin-mediated cell adhesion. We further demonstrated that the kinetics of cell release was dependent on the toehold length (Figure S2), with a longer length resulting in faster kinetics. We next designed an RGD-interfaced gate architecture with basic logic functions (AND, OR, XOR) for programmable regulation of on-chip cell adhesion (Figure 3). In an AND operation, the output was “1” only when both inputs were applied. The basic building blocks are domains where each domain has its complementary domain a′. Input 1 (IN1: strand a′b′) and input 2 (IN2: strand c′d′) bind to the base strand (strand abcd) sequential (Figure S3), which displace RGD coupled strand via three-way branch migration, thus triggering the cell detachment. Distinct responsive gates can be realized by changing DNA logic elements. In an OR logic gate, we employed three-domain input strands (Figure S5, IN1: a′b′c′ and IN2: b′c′d′). The addition of IN1 (or IN2) that bound to the open toehold (toehold a on the 3′-end or toehold d on the 5′-end) of the base strand displaced the RGD-coupled strand via branch migration. Similarly, we constructed an XOR logic gate consisting of a two-domain base strand (ab) and strand a′b′c′ (IN1) and strand abc (IN2) as inputs (Figure S6). The addition of IN1 (or IN2) bounds to the open toehold a of the base strand (or the open toehold c′ of the RGD coupled strand), allowing SDR to proceed. The input operation could be visualized under fluorescence imaging when IN1 and IN2 were labeled with Cy3 (red) and FAM (green), respectively, and confirmed using polyacrylamide gel electrophoresis (PAGE) (Figures S4, S6, and S8). FACS analysis demonstrated the successful operation with appropriate output.

the DNA sequence design, the design of logical control of onchip cell adhesion is feasible (e.g., an XOR logic gate, Figure 1c). When neither input was applied, the RGD encoding terminator NOT-gate36 blocked SDR, promoting cell attachment. D-CRNs are intrinsically noninvasive and fast responsive, which enables cell behaviors to be programmably regulated. Reversible binding of cells on chip was easily achieved by adding exchange strands that released the RGD-containing strands. This process led to a patch with DNA strands on cells (Figure 2a). To confirm this directional interaction, we labeled the RGD-tagged DNA with Cy3, which only binds to the contact region between cells and surface. The fluidic state of cells was fixed by using 4% paraformaldehyde, which covalently cross-linked meshwork on the membrane. When cells were released upon the addition of an input strand, they resembled “eye balls” with bright red corneas (Figure 2b, top panel). In contrast, the distribution of dyed RGD-containing strands was homogeneous over the cell surface when cells were not fixed (Figure 2b, bottom panel), since the fluid mosaic structure of cell membrane allows free diffusion.36 We next examined the kinetics of cell release (Figure 2c−d). FACS analysis revealed the gradual increase of the number of released cells. Nearly all cells were released within ∼10 min when using a 6-base toehold. The fast kinetics was further supported by the biphasic, transient integrin-mediated calcium signaling. Attachment of cells preloaded with a Ca2+ indicator Fluo-4 AM onto RGD-coated surfaces induced a characteristic increase of Ca2+ concentration (Figure S1). The increase was biphasic, with an initial rapid rise within 25 s, followed by returning to the initial level within 5 min. Such a Ca2+ concentration increase is known 10177

DOI: 10.1021/jacs.7b04040 J. Am. Chem. Soc. 2017, 139, 10176−10179

Communication

Journal of the American Chemical Society

Figure 3. Predicted and recorded multi-input and sequential cell logic gates. (Gate) Boolean logic functions. (Architecture) Configurations for sequential cell logic gates, including AND, OR, XOR, and AND-OR. (Fluorescence imaging) Visualization of the input operation under fluorescence imaging in which IN1 and IN2 were labeled with Cy3 (red) and FAM (green), respectively. Scale bars: 10 um. The addition of either IN1 or IN2 was defined as the “on” or “1” state, and the “off” or “0” state corresponded to no addition of input. (Truth Table) Logic relationships between inputs and output. (Cell Number) Gate outputs assayed by FACS analysis. Cell population responding to input signals as per gate-specific truth tables. A common output threshold is set as 1500 (vertical blue line).

The modular design of logic gates enables more complex operations that can simulate the CRN traces. We then constructed a two-layered circuit in which a logical AND (in solution) feeds into a logical OR (on chip). As depicted in Figure 3, the upstream AND gate required the addition of both IN1 and IN2 to proceed SDR, through a process of branch migration that unbound strand a′b′. This strands subsequently served as one of the inputs to a downstream OR gate. The downstream OR gate was designed such that the addition of either strand b′c′ (IN3) or strand a′b′ that bound to the open toehold of the base strand inverted the RGD encoding NOTgate via branch migration, causing the cell detachment. FACS analysis of the resulting cell population verified proper implementation of AND-OR operation (Figure 3). D-CRNs represent an effective programming language for regulating dynamic behavior of arbitrary molecular systems.3 Especially, interfacing cell factors to DNA provides a unique and promising means for temporal and spatial control of the cell−substrate interactions. As a straightforward extension, we expect this system can be similarly extended to regulate bacterial environmental and social behavior. For instance, DNA aptamers could be used to program on-chip bacterial adhesion. This should enable spatial constrains to initiate quorum sensing and related growth, which may find potential applications in growing unculturable bacteria and antibiotics.37,38

Programming cell behavior and functions in living organisms using digital logic has become a recent focus in synthetic biology,39,40 which has important implications in designing human-machine interfaces and cell-based therapy. Likewise, in vitro logical manipulation of cells should pave the way to rational control of artificial systems modeling organ-level physiology, especially organs-on-chips that have proven to be of high utility for drug discovery and development. Engineered chemical systems (e.g., D-CRNs developed here) with autonomous functions thus provide a generic tool for in vitro regulating signal transduction pathways,41 metabolic pathways,42 and genetic regulatory networks.43 In summary, we have constructed a series of on-chip DNAbased logic gates (AND, OR, XOR, and AND-OR) that regulate mammalian cells adhesion in response to the Boolean combination of ssDNA inputs. The modular design and construction of DNA-based logic gates allows sophisticated engineering of hierarchical circuits performing complex computational control of mammalian cells adhesion. We find that the mechanism of D-CRNs relies on sequential recognition and SDR, which provides a highly generic and programmable tool for logical control of mammalian cells behavior with accuracy and predictability. Given the biological nature of these DNA-based computing components, it is possible to program cell behavior in intro for biomedical applications. 10178

DOI: 10.1021/jacs.7b04040 J. Am. Chem. Soc. 2017, 139, 10176−10179

Communication

Journal of the American Chemical Society

■

(15) Rape, A. D.; Zibinsky, M.; Murthy, N.; Kumar, S. Nat. Commun. 2015, 6, 8129. (16) Lutolf, M.; Hubbell, J. Nat. Biotechnol. 2005, 23, 47−55. (17) Amir, Y.; Ben-Ishay, E.; Levner, D.; Ittah, S.; Abu-Horowitz, A.; Bachelet, I. Nat. Nanotechnol. 2014, 9, 353−357. (18) You, M.; Zhu, G.; Chen, T.; Donovan, M. J.; Tan, W. J. Am. Chem. Soc. 2015, 137, 667−674. (19) Groves, B.; Chen, Y.-J.; Zurla, C.; Pochekailov, S.; Kirschman, J. L.; Santangelo, P. J.; Seelig, G. Nat. Nanotechnol. 2015, 11, 287−294. (20) Pei, H.; Liang, L.; Yao, G.; Li, J.; Huang, Q.; Fan, C. Angew. Chem. 2012, 124, 9154−9158. (21) Zhang, D. Y.; Seelig, G. Nat. Chem. 2011, 3, 103−113. (22) Chen, S. X.; Zhang, D. Y.; Seelig, G. Nat. Chem. 2013, 5, 782− 789. (23) Gu, H.; Chao, J.; Xiao, S.-J.; Seeman, N. C. Nature 2010, 465, 202−205. (24) You, M.; Chen, Y.; Zhang, X.; Liu, H.; Wang, R.; Wang, K.; Williams, K. R.; Tan, W. Angew. Chem., Int. Ed. 2012, 51, 2457−2460. (25) Lund, K.; Manzo, A. J.; Dabby, N.; Michelotti, N.; JohnsonBuck, A.; Nangreave, J.; Taylor, S.; Pei, R.; Stojanovic, M. N.; Walter, N. G.; Winfree, E.; Yan, H. Nature 2010, 465, 206−210. (26) Qu, X.; Zhu, D.; Yao, G.; Su, S.; Chao, J.; Liu, H.; Zuo, X.; Wang, L.; Shi, J.; Wang, L.; Huang, W.; Pei, H.; Fan, C. Angew. Chem., Int. Ed. 2017, 56, 1855−1858. (27) Lage, J. M.; Leamon, J. H.; Pejovic, T.; Hamann, S.; Lacey, M.; Dillon, D.; Segraves, R.; Vossbrinck, B.; González, A.; Pinkel, D.; Albertson, D. G.; Costa, J.; Lizardi, P. M. Genome Res. 2003, 13, 294− 307. (28) Paez, J. G.; Lin, M.; Beroukhim, R.; Lee, J. C.; Zhao, X.; Richter, D. J.; Gabriel, S.; Herman, P.; Sasaki, H.; Altshuler, D.; Li, C.; Meyerson, M.; Sellers, W. R. Nucleic Acids Res. 2004, 32, e71−e71. (29) Benenson, Y.; Gil, B.; Ben-Dor, U.; Adar, R.; Shapiro, E. Nature 2004, 429, 423−429. (30) Qian, L.; Winfree, E.; Bruck, J. Nature 2011, 475, 368−372. (31) Qian, L.; Winfree, E. Science 2011, 332, 1196−1201. (32) Wang, S.; Cai, X.; Wang, L.; Li, J.; Li, Q.; Zuo, X.; Shi, J.; Huang, Q.; Fan, C. Chem. Sci. 2016, 7, 2722−2727. (33) Pei, H.; Zuo, X.; Zhu, D.; Huang, Q.; Fan, C. Acc. Chem. Res. 2014, 47, 550−559. (34) Pei, H.; Li, J.; Lv, M.; Wang, J.; Gao, J.; Lu, J.; Li, Y.; Huang, Q.; Hu, J.; Fan, C. J. Am. Chem. Soc. 2012, 134, 13843−13849. (35) Pei, H.; Li, F.; Wan, Y.; Wei, M.; Liu, H.; Su, Y.; Chen, N.; Huang, Q.; Fan, C. J. Am. Chem. Soc. 2012, 134, 11876−11879. (36) Bonnet, J.; Yin, P.; Ortiz, M. E.; Subsoontorn, P.; Endy, D. Science 2013, 340, 599−603. (37) Zelada-Guillén, G. A.; Riu, J.; Düzgün, A.; Rius, F. X. Angew. Chem., Int. Ed. 2009, 48, 7334−7337. (38) van der Mei, H. C.; Rustema-Abbing, M.; de Vries, J.; Busscher, H. J. Appl. Environ. Microbiol. 2008, 74, 5511−5515. (39) Ausländer, S.; Ausländer, D.; Müller, M.; Wieland, M.; Fussenegger, M. Nature 2012, 487, 123−127. (40) Daniel, R.; Rubens, J. R.; Sarpeshkar, R.; Lu, T. K. Nature 2013, 497, 619−623. (41) Farzadfard, F.; Lu, T. K. Science 2014, 346, 1256272. (42) Keasling, J. D. ACS Chem. Biol. 2008, 3, 64−76. (43) Andrianantoandro, E.; Basu, S.; Karig, D. K.; Weiss, R. Mol. Syst. Biol. 2006, 2, 2006.0028.

ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/jacs.7b04040. Experimental procedures; additional table and figures (PDF)

■

AUTHOR INFORMATION

Corresponding Authors

*[email protected] (H.P.) *[email protected] (C.F.) ORCID

Jiang Li: 0000-0003-2372-6624 Xiaolei Zuo: 0000-0001-7505-2727 Shiping Song: 0000-0002-0791-8012 Lihua Wang: 0000-0002-6198-7561 Hao Pei: 0000-0002-6885-6708 Chunhai Fan: 0000-0002-7171-7338 Author Contributions ∥

X.Q., S.W., and Z.G. contributed equally.

Notes

The authors declare no competing financial interest.

■

ACKNOWLEDGMENTS This work was supported by the Ministry of Science and Technology (2013CB932803, 2013CB933802, 2016YFA0201200, 2016YFA0400900), NSFC (Grant Numbers 21422508, 31470960, 21373260, 91123037, 21505045), CAS (QYZDJ-SSW-SLH031), Shanghai Pujiang Talent Project (16PJ1402700, 15PJ1401800), and China Postdoctoral Science Foundation (2015M581565). H.P. and L.L. gratefully acknowledge the start-up funding from East China Normal University.

■

REFERENCES

(1) Chirieleison, S. M.; Allen, P. B.; Simpson, Z. B.; Ellington, A. D.; Chen, X. Nat. Chem. 2013, 5, 1000−1005. (2) Chen, Y.-J.; Dalchau, N.; Srinivas, N.; Phillips, A.; Cardelli, L.; Soloveichik, D.; Seelig, G. Nat. Nanotechnol. 2013, 8, 755−762. (3) Soloveichik, D.; Seelig, G.; Winfree, E. Proc. Natl. Acad. Sci. U. S. A. 2010, 107, 5393−5398. (4) Albrecht, D. R.; Underhill, G. H.; Wassermann, T. B.; Sah, R. L.; Bhatia, S. N. Nat. Methods 2006, 3, 369−375. (5) Dutta, D.; Pulsipher, A.; Luo, W.; Yousaf, M. N. J. Am. Chem. Soc. 2011, 133, 8704−8713. (6) El Muslemany, K. M.; Twite, A. A.; ElSohly, A. M.; Obermeyer, A. C.; Mathies, R. A.; Francis, M. B. J. Am. Chem. Soc. 2014, 136, 12600−12606. (7) Basu, S.; Gerchman, Y.; Collins, C. H.; Arnold, F. H.; Weiss, R. Nature 2005, 434, 1130−1134. (8) Cabezas, M. D.; Mirkin, C. A.; Mrksich, M. Nano Lett. 2017, 17, 1373−1377. (9) Sottos, N. R. Nat. Chem. 2014, 6, 381−383. (10) Hudalla, G. A.; Murphy, W. L. Soft Matter 2011, 7, 9561−9571. (11) Blanco, E.; Shen, H.; Ferrari, M. Nat. Biotechnol. 2015, 33, 941− 951. (12) Li, J.; Pei, H.; Zhu, B.; Liang, L.; Wei, M.; He, Y.; Chen, N.; Li, D.; Huang, Q.; Fan, C. ACS Nano 2011, 5, 8783−8789. (13) Martino, M. M.; Briquez, P. S.; Güc,̧ E.; Tortelli, F.; Kilarski, W. W.; Metzger, S.; Rice, J. J.; Kuhn, G. A.; Müller, R.; Swartz, M. A.; Hubbell, J. A. Science 2014, 343, 885−888. (14) Pati, F.; Jang, J.; Ha, D.-H.; Kim, S. W.; Rhie, J.-W.; Shim, J.-H.; Kim, D.-H.; Cho, D.-W. Nat. Commun. 2014, 5, 3935. 10179

DOI: 10.1021/jacs.7b04040 J. Am. Chem. Soc. 2017, 139, 10176−10179