Article pubs.acs.org/accounts
Glycosylated Conductive Polymer: A Multimodal Biointerface for Studying Carbohydrate−Protein Interactions Xiangqun Zeng,*,† Ke Qu,† and Abdul Rehman†,‡ †
Department of Chemistry, Oakland University, Rochester, Michigan 48309, United States Department of Chemistry, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia
‡
CONSPECTUS: Carbohydrate−protein interactions occur through glycoproteins, glycolipids, or polysaccharides displayed on the cell surface with lectins. However, studying these interactions is challenging because of the complexity and heterogeneity of the cell surface, the inherent structural complexity of carbohydrates, and the typically weak affinities of the binding reactions between the lectins and monovalent carbohydrates. The lack of chromophores and fluorophores in carbohydrate structures often drives such investigations toward fluorescence labeling techniques, which usually require tedious and complex synthetic work to conjugate fluorescent tags with additional risk of altering the reaction dynamics. Probing these interactions directly on the cell surface is even more difficult since cells could be too fragile for labeling or labile dynamics could be affected by the labeled molecules that may interfere with the cellular activities, resulting in unwanted cell responses. In contrast, label-free biosensors allow real-time monitoring of carbohydrate−protein interactions in their natural states. A prerequisite, though, for this strategy to work is to mimic the coding information on potential interactions of cell surfaces onto different biosensing platforms, while the complementary binding process can be transduced into a useful signal noninvasively. Through carbohydrate self-assembled monolayers and glycopolymer scaffolds, the multivalency of the naturally existing simple and complex carbohydrates can be mimicked and exploited with label-free readouts (e.g., optical, acoustic, mechanical, electrochemical, and electrical sensors), yet such inquiries reflect only limited aspects of complicated biointeraction processes due to the unimodal transduction. In this Account, we illustrate that functionalized glycosylated conductive polymer scaffolds are the ideal multimodal biointerfaces that not only simplify the immobilization process for surface fabrication via electrochemical polymerization but also enable the simultaneous analysis of the binding events with orthogonal electrical, optical, or mass sensing label-free readouts. We established this approach using polyaniline and polythiophene as examples. Two general methods were demonstrated for glycosylated polymer fabrications (i.e., electropolymerization of monomer bearing α-mannoside residues or click chemistry based mannose conjugation to electrochemically preformed quinone fused polymer with potential to introduce different carbohydrate moieties and construct glycan arrays in a similar manner). Their conjugated π system extending over a large number of recurrent monomer units renders them sensitive optoelectronic materials. The carbohydrate−protein interactions on the side chain could disrupt the electrostatic, H-bonding, steric, or van der Waals interactions within or between polymers, leading to a change of conductivity or optical absorption of the conductive polymers. This will allow concurrent interrogation of these interactions with adjoining biological processes and mechanisms in multimodal fashion. Furthermore, the functionalized glycosylated conductive polymers can be designed and synthesized with controlled oxidation states, desired ionic dopants, and the imperative density and orientation of the sugar ligands that enable the assessment of differential receptor binding profiles of carbohydrate−protein interactions with much more detailed information and high accuracy. Finally, the glycosylated biosensing interfaces were successfully validated for their applications in Gram-negative bacterial detection, antibiotic resistance studies, and antimicrobial susceptibility assays, all based on inferring carbohydrate−protein interactions directly on cell surfaces, thus illustrating their potential uses in infectious disease research, clinical diagnostics, and environmental monitoring of harmful pathogens.
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INTRODUCTION
into diverse fundamental biological processes, thereby involving in cell−cell communications. Particularly, interactions between carbohydrate structures (e.g., free carbohydrates or carbohydrate fragments of glycoproteins, glycolipids, and proteoglycans) and
Biological molecular interactions (or biointeractions) are central to virtually every process in living cells. Carbohydrates and glycoconjugates are abundant among those interacting molecules existing as essential components of the surfaces of all cells,1,2 including pathogens and viruses, having complementary coding information for cellular functions, translating sugar-based signals © XXXX American Chemical Society
Received: April 12, 2016
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Accounts of Chemical Research Table 1. Comparison of Carbohydrates with DNA and Proteins DNA
protein
monomer linkage format covalent linkage synthesis
biomacromolecule
nucleotide linear phosphate replication (in vivo amplification); polymerase chain reaction (PCR, in vitro enzyme-mediated synthesis)
amino acid linear amide gene-mediated translation (biosynthesis); peptide synthesis
main functions in the living systems
encode genetic information
catalyze biochemical reaction; ligand binding; cell signaling; structural component
proteins (e.g., lectins, antibodies, or enzymes) that recognize them play vital roles in recognition cascades, ranging from cell signaling, intracellular trafficking, cell adhesion and proliferation, and viral/bacterial infection to apoptosis and immune responses.3,4 To understand the biological roles of these carbohydrate/glycoconjugate interactions or to evaluate their potential as disease biomarkers will require tools to quantitatively assess the carbohydrate binding reactions so that the thermodynamics, kinetics, and structural complementarity of carbohydrate−protein interactions can be obtained at both molecular and cellular levels.
carbohydrate monosaccharide linear and branched glycosidic bond enzymatic synthesis; photosynthesis; chemical synthesis (oligosaccharide synthesis) energy storage; structural component; recognition element; cell signaling
Table 2. Typical Biological Interactions and Their Molar Affinities bio-interaction protein−protein DNA−DNA, DNA− protein lipid−protein carbohydrate−protein
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binding forces van der Waals, hydrogen bonding, electrostatic van der Waals, hydrogen bonding, electrostatic van der Waals, hydrogen bonding, electrostatic van der Waals, hydrogen bonding
affinity (M−1) 104−1012 106−1013 105−107 104−106
through the nature-inspired multivalent binding approaches and by using a multimodal transduction mechanism, thereby enhancing the reliability and information on the data. For this purpose, an overview of existing methods for characterization of carbohydrate−protein interactions is presented first, paving the way to demonstrate the multimodality of label-free biosensors that we developed, which exploit the unique properties of conductive polymers (CPs) as the signal transduction platform. Then, we highlight two examples of applications of glycosylated CP sensors as a multimodal platform for cellular analysis, that is, for detection of bacteria and for studying bacterial antibiotic resistance.
CHARACTERISTICS OF CARBOHYDRATE−PROTEIN INTERACTIONS As summarized in Table 1, in contrast to DNA and proteins, carbohydrates can be classified into two groups, monosaccharides, which feature the polyhydroxy backbone, and complex carbohydrates, which are composed of different numbers of monosaccharide units joined together via the glycosidic bonds (ether linkages) between the “anomeric” hydroxyl group of one monosaccharide and any of the hydroxyl groups of the second monosaccharide, with loss of water molecule. Therefore, the count of possible complex carbohydrates is quite phenomenal; that is, >10 million tetrasaccharides can be assembled from just nine monosaccharides. Recent advancement in chemical and enzymatic synthesis of complex carbohydrates have made them available for studying their interactions with other biomolecules in many important biological processes. However, the studies of carbohydrate−protein interactions are challenged by the complexity and heterogeneity of cell surfaces, the inherent structural complexity of carbohydrates, the weak binding of the monovalent glycans, and the lack of chromophores or fluorophores in carbohydrate structures.5 Contrary to protein−protein or protein−DNA interactions, most carbohydrate binding proteins (lectins) are oligomeric with multiple glycan-binding sites. C-type lectins often require divalent metal ions (e.g., Ca(II)) to facilitate the carbohydrate−protein binding reactions. Thus, compared with other biological interactions (Table 2), carbohydrate− protein interactions in nature are much weaker (affinity = 104− 106 M−1) because of the shallow binding pockets in lectins that can be exposed to the solvents. Nature usually compensates the low affinity of carbohydrate−protein interactions by multivalent glycan scaffolds on the cell surface in which sequential or simultaneous multivalent binding between glycan clusters and proteins can result in stronger affinity, thereby leading to an enhanced effective binding by several orders of magnitude, usually referred to as avidity. These inherently weak affinities of carbohydrate binding reactions alongside other characteristics make their analysis even more challenging. This Account focuses on the latest developments in using label-free carbohydrate and lectin biosensors for studying carbohydrate−protein interactions
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CURRENT TECHNIQUES TO STUDY CARBOHYDRATE−PROTEIN INTERACTIONS The development of better analytical techniques to characterize complex carbohydrates and carbohydrate−protein interactions has been an active area of research. X-ray diffraction, nuclear magnetic resonance (NMR), and mass spectroscopy (MS) are routinely used to characterize the structural aspects of the carbohydrates or carbohydrate binding complexes. To study the binding kinetics and thermodynamics of carbohydrate−protein interactions, two types of assays are commonly used: assays that directly monitor the biointeractions of carbohydrates in solutions and assays (often called biosensors) in which either carbohydrate or lectin is immobilized on a solid substrate.6 Isothermal titration calorimetry (ITC) is a solution based assay that directly measures the heat released or absorbed to estimate the thermodynamic properties of molecular interactions. However, it requires a large number of interaction molecules, and the extremely low concentrations of membrane receptors present in biological tissues make it very difficult to obtain sufficient amount of samples, rendering many microcalorimetric determinations of thermodynamic parameters impossible. Contrarily, an assay based on surface immobilization (e.g., surface plasmon resonance (SPR) biosensors) can obtain the thermodynamic parameters of biomolecule interactions by measuring dissociation constant over a range of temperatures, combined with van’t Hoff plot analysis. This methodology provides complementary information to ITC. Importantly, surface based methods or biosensors B
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Figure 1. Graphic illustration of the different carbohydrate models.
van der Waals forces, (ii) covalent immobilization via chemical linkage reactions, or (iii) bioaffinity interactions (antibody− antigen immobilization). Covalent immobilizations provide the most stable layers and are often the preferred methods for systematic study of carbohydrate−protein interactions. We developed a number of carbohydrate biointerfaces via covalent immobilization that can quantitatively analyze carbohydrate− protein interactions through noninvasive and label-free quartz crystal microbalance (QCM), SPR, and electrochemical readouts. For example, carbohydrate SAMs12,13 were fabricated by spontaneous association of carbohydrate molecules under equilibrium conditions yielding stable, structurally well-defined two-dimensional aggregates. Initially, synthesis of sugar derivatives with a pendant alkane−thiol group and subsequent formation of SAM on gold substrate were demonstrated. However, as the complexity of tethered sugars increases, the synthesis of sugars anchored with alkanethiol becomes costly with no guarantee that the complexed carbohydrate thiolate will form a structurally well-defined monolayer. Therefore, a direct chemical transformation introducing sugar moieties onto preformed functionalized SAMs via suitable interface reactions for anchoring sugar units,14 including Diels−Alder reaction, thiol addition, disulfide exchange, and Cu(I)-catalyzed cycloaddition reaction was demonstrated. This method allows virtually any surface to be prepared using well-developed click chemistry.
can detect very low concentrations of analytes, allowing simultaneous measurements of the binding kinetics.7 However, the surface based assay requires the design and development of a proper multivalent carbohydrate scaffold with controlled immobilization on transducer substrate. A plethora of sugar scaffolds including glycoclusters, cyclodextrins, glycodendrimers, carbohydrate self-assembled monolayers (SAMs), glyconanoparticles, and glycoliposomes have been designed with a fluorescent tag and tested for studying the carbohydrate−protein interactions (Figure 1)5 with fluorescence readout.8,9 Fluorescence-based readouts are end point readouts, and little is learned about the kinetics of interactions. Moreover, studying carbohydrate−protein interaction at the cell surface using carbohydrate/lectin arrays is challenging.10 The diversity and structural complexity of carbohydrates lead to the heterogeneous distribution of surface domains.11 Often cells or proteins on cells have structures that are too fragile for labeling or labile dynamics is affected by the labeled molecules. More importantly, for a complete picture of the carbohydrate−protein interactions, parameters like thermodynamics, kinetics, hydration, molecular conformation, and structural complementarity should be simultaneously examined using label-free techniques.
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LABEL-FREE BIOSENSORS FOR STUDYING CARBOHYDRATE−PROTEIN INTERACTIONS Label-free biosensors are uniquely positioned in real-time monitoring of biointeractions in their natural states, allowing the determination of the affinity and kinetics of the binding reactions, though they require carbohydrate or lectin immobilizations on an electrode. Typically, the binding reactions can be transduced as optical, acoustic, mechanical, electrochemical, and electrical signals; however, nonspecific adsorption is a serious problem in label-free methods.
Polymer Biointerface Design
One key feature of the carbohydrate−protein interactions is their multivalent recognition pattern. SAM is a two-dimensional multivalent carbohydrate scaffold. Mimicking the multivalent interactions of carbohydrates often require three-dimensional multivalent structures. Glycopolymers including macrocycles and spherical dendrimers have been explored to generate such structures. Of two approaches, one is to synthesize the monomers with carbohydrates, followed by the formation of glycopolymer via polymerization process. This method is limited by monomer synthesis step. Additionally, the induced carbohydrates could introduce steric hindrance in polymerization affecting the chain growth process. Alternatively, polymer scaffolds can be generated first. Then carbohydrates can be
SAM Biointerface Design
Nonspecific adsorption can be minimized by innovations in biointerface design and fabrication so that the binding reactions at the interface are specific reflecting those in biological conditions. The immobilization of carbohydrate or lectin is usually achieved through three main approaches: (i) physisorption via C
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The synthesis of CPs is usually initiated by the oxidation of the monomeric unit, resulting in a positively charged polymer backbone that is counterbalanced by the incorporation of anionic doping species. CPs can also form at the electrode surface by electropolymerization, which permits easy control of their thickness and morphology with high permeability to allow the diffusion of analyte. The immobilization of biological molecules into CPs can be achieved via doping, entrapment, or covalent grafting. Doping is generally applicable only to anionic biomolecules whereas entrapment is applicable to a wide selection of biomolecules as well as cells. Alternatively, biomolecules such as carbohydrate can be covalently tethered onto the CP backbone. Compared with noncovalent approaches, chemical tethering is beneficial in providing control over the density and distribution of biomolecules over the surface. Both methods can significantly change the surface and bulk properties of CPs including surface topography, modulus, surface energy, and conductivity and are extensively utilized to control the presence and presentation of cell or biomolecule adhesion motifs of the resulting CPs.19 More interestingly, different redox states of CPs have very different optical, electrochemical, and electronic properties. The interconversion between different redox states can give rise to simultaneous changes in the polymer conformations, doping levels, conductivities, and colors, which have been explored for controlled integration with important biomolecules such as carbohydrates and advanced fabrication technologies. As shown in Figure 3, glycopolythiophenes containing sialic acid or man-
conjugated onto them using coupling chemistry. The key step in this method is postsynthetic modification installing both neutral and charged carbohydrates, producing multidentate ligands. Both naturally isolated lectins and their synthetic homologues (e.g., boronic acid polymers)15,16 were utilized in our group to characterize the glycopolymer selectivity and multivalent affinity with lectins. Glycopolymers17,18 containing alkanethiol functions as well as cross-linked surface-grafted glycopolymer structures were developed for label-free characterization of carbohydrate− protein interactions. These glycopolymers showed substantially minimized possible cross-reactivity and significantly enhanced specificity and sensitivity for carbohydrate−protein interactions. The use of cross-linked polymer decreased the flexibility of the polymer backbone between the carbohydrate binding sites. Therefore, the cost of conformational entropy for multivalent binding was minimized.
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MULTIMODAL GLYCOSYLATED CONDUCTIVE POLYMERS AS BIOSENSING MATERIALS CPs are organic polymers that conduct electricity. They are classified based on the mode of charge propagation, which is linked to the chemical structure of the polymer. The two main categories are redox polymers and electronically conducting polymers (Figure 2). The structural characterization of electronic
Figure 3. (a) Impedimetric detection of lectins based on poly(pyrrolelactosyl) and poly(pyrrole-3′-sialyllactosyl) backbone and (b) glycopolythiophene assemblies from the chemical synthesis for the optical transduction. Redrawn from reference 20 and 21.
Figure 2. Representative examples of the electrochemically active polymers.
CPs is their conjugated π system extending over a large number of recurrent monomer units. Change of the conformation such as planar−nonplanar transition due to various stimuli can lead to significant conductivity as well as optical absorption changes (wavelength or absorbance). Studies have shown that the conductivity of CPs is highly sensitive to the nature and regiospecificity of the side chains. The CP conformation could also depend on the electrostatic, H-bonding, steric, or van der Waals interactions within or between polymers. These interactions are expected to be disrupted or altered upon receptor binding, leading to a change of conductivity or optical absorption of the CPs. Thus, CPs can be designed as sensitive multimodal sensory materials based on binding-induced conformation changes.
nose ligands were prepared and evaluated for their ability to bind lectins, virus, and bacteria using colorimetric readout. The spacer-length between the polymer backbone and the ligand was varied to optimize binding interactions.20 In another study, the disaccharide lactosyl group and the trisaccharide 3′-sialyllactosyl group were conjugated to the pyrrole nitrogen through the chemical synthesis and electro-oxidation of pyrrole-lactosyl and pyrrole-3′-sialyllactosyl allowing the formation of thin and reproducible poly(pyrrole-saccharide) films.21 The binding of these glycosylated polypyrroles with lectins peanut agglutinin (PNA) and Maackia amurensis agglutinin were characterized by the impedance transduction mechanism using a hydroquinone redox probe. Thus, CPs can provide a multimodal signal D
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manno-PANI since the fast proton transfer process will be the dominant ion-transport process during lectin (concanavalin A, Con A)−mannose binding events. Con A has an isoelectric point of about pH = 5 and requires calcium or manganese ions at each of its four saccharide binding sites. At neutral and alkaline pH, Con A exists as a tetramer of four identical subunits of approximately 26 000 Da each. Below pH 5.6, Con A dissociates into active dimers of 52 000 Da. Since the binding of Con A with manno-PANI requires the incorporation of Ca(II), it could make the polyaniline positively charged. To maintain electroneutrality, it will subsequently result in deprotonation of polyaniline, which should lead to significant change of the optical and electrical properties of polyaniline for sensitive readout of Con A−mannose binding reaction. We characterized the binding of manno-PANI with Con A in HEPES buffer by both optical and electrical readouts. The bulky zwitterion of HEPES trapped in the polymer makes it less likely as counterion to be transported into or out of the polymer to balance the charge. This allowed us to observe the proton transport during the carbohydrate−protein binding reactions if binding of Con A to mannose residues of polyaniline at electrode surfaces can result in the change of oxidation states due to deprotonation (Figure 4). The manno-PANI was shown to maintain the bioactivity of the carbohydrate and directly transduce the mannose−Con A binding to the changes of optical (Figure 5, UV−vis) and electrical signals (Figure 6d (top curve), impedance by EIS). The polyaniline film underwent pHdependent changes in the visible/near-infrared range, which was demonstrated as an optical pH-sensor giving the titration curves covering the pH range of 1−12.23 From Figure 5, the changes of the optical signals upon manno-PANI binding with Con A is almost identical to those observed for o-methylpolyaniline when pH is changed from 2 to 9,24 suggesting the change of amine to imine functionality of manno-PANI during the binding events. X-ray photoelectron spectrometry (XPS) experiments showed that the atomic concentration of amine is decreased 41% but that of the imine increased 49% after Con A binds with manno-PANI, which confirms that the Con A binding with the manno-PANI film triggers the switching of amine functionalities in the polyaniline backbone, converting them to imine form. The crystal structures of Con A showed that there are aspartate and glutamate residues around the calcium ion. The negatively
transduction platform to study the interactions between biomolecules and their binding partners to allow multifaceted thermodynamic, kinetic, and structural information to be obtained in a high throughput, rapid, and multiplexed manner. In the following sections, we will utilize polyaniline and polythiophene as examples to illustrate the approaches and benefits of the glycosylated CPs as a label-free platform in studying carbohydrate−protein interactions at both molecular and cellular levels. Their potential biomedical application in bacterial detection and antibiotic resistance of bacterial infection will also be discussed.
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POLYANILINE AS SOLID REDOX PROBE, OPTICAL PROBE, AND PH SENSITIVE PROBE Polyaniline (PANI) is an attractive electronic CP since it has different oxidation states with different colors and has an acid/ base doping response. Colors, charges, and conformations of multiple oxidation states and pH sensitive response make polyaniline ideal material as a multimodal signal transduction substrate for studying carbohydrate−protein interactions. We designed and synthesized an aniline monomer bearing α-mannoside at the ortho-position of the aniline ring. Mannosylated polyaniline was formed using one-step electrochemical polymerization by cyclic voltammetry in 4-(2-hydroxylethyl)-1-piperazineethanesulfonic acid (HEPES) buffer at pH = 7 onto optically transparent indium tin oxide (ITO) electrode. Electrochemical polymerization of mannosylated aniline by selection of the polymerization conditions (e.g., the potential, the bathing solution) provides advantages of controlled thickness, porosity, and oxidation states of the formed polyaniline. Electrochemical polymerization in HEPES, a bulky zwitterion in solution, could trap it into the formed CP resulting in a nonpermselective polyaniline film (i.e., while counterions and associated co-ions could all be doped). This approach resulted in an emeraldine (half-oxidized) polyaniline rather than fully oxidized pernigraniline, which is beneficial for both electrochemical and optical signal transduction of its binding with lectin, owing to polyaniline’s protonated amine functionality.22 The rate of ion transport is usually the slow-step during CP redox switching with a maximum on the order of a few hundred milliseconds, which has been the greatest obstacles toward building rapidly responsive electrochemical devices featuring CPs. However, this slow step was utilized here with this nonpermselective HEPES doped
Figure 4. Schematic of the amine to imine conversion of the mannosylated polyaniline upon Con A binding. E
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monosaccharides, disaccharides, trisaccharides, oligosaccharides, and polysaccharides directly by known chemical reactions to the preformed CP templates. This method simplifies the synthesis step and is ideal for fabricating glycosylated CPs with a broad range of carbohydrates. Furthermore, such postpolymerization functionalization can offer an effective way to control orientation of carbohydrate residues at low cost and high yield. We illustrated this approach with a mannosylated quinone-fused polythiophene. In contrast to the manno-PANI film, the mannose is conjugated to the preformed quinone-fused polythiophene (Figure 7).26,27 Figure 5. UV−vis spectra of the mannosylated polyaniline upon Con A binding.
charged carboxylate group(s) could also serve as the catalyst for the deprotonation of electron-deprived manno-PANI through a few water molecules (i.e., there is a bond network −COO−···(H2O)n···+HN).25,23 The manno-PANI film showed good stability with maximum drift of only 3% over a 20-week test. The surface morphology of the manno-PANI system was investigated by the scanning electron microscopy technique. The manno-PANI showed textile structure (Figure 6a), and after binding with Con A, a sponge-like structure resulted (Figure 6b). The glycosylated polyaniline system has been shown to be very specific to Con A against control lectins and thus has been used as a lectin sensor to detect Escherichia coli W1485 via its binding with the bacterial O-antigen lipopolysaccharide (LPS) with impedance measurements (Figure 6d, bottom curve). This study provides mechanistic support for the electrical and optical dual mode readouts for the carbohydrate−protein binding events and suggests that use of glycosylated polyaniline will allow probing of the molecular mechanisms of binding of carbohydrate with C-type lectins via monitoring the deprotonation of the glycosylated polyaniline scaffolds.
Figure 7. Conjugation of the thiolated carbohydrate moieties to the conductive polymer mediated by the quinone.
The quinone is attached to the thiophene monomer via a delocalized π electron-rich alkyne bridge (abbreviated as TQ) allowing fast kinetics of quinone redox processes,28 providing the needed sensitivity to transduce the carbohydrate−protein binding for cellular analysis. The monomer was electropolymerized to form the electroactive polymer. The quinone functionality enables the classical Michael addition reaction. The thiolated mannose (abbreviated as SM) serves as the nucleophile to attack the unsaturated ketone portion of the quinone, conjugating the carbohydrate moieties to the conductive polythiophene films and achieving the constitution of the glycopolymer biointerface. This biointerface fabrication method boasts the advantage that different carbohydrate moieties could be introduced in a similar fashion, supporting the versatility of fabricating the glycan arrays and facilitating the more rapid and efficient construction of the glycan-functionalized label-free CP interfaces for a variety of biomedical investigations.
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POLYTHIOPHENE AS SOLID REDOX, ELECTROCHEMICAL, AND MASS-SENSITIVE PROBE The manno-PANI interface demonstrated above has multimodal functionality; however, this approach may become challenging for aniline monomers with complex carbohydrate structures because of the stereochemistry of carbohydrates whose bioactivity may not be maintained during the electrochemical polymerization step. An alternative approach was developed to allow the coupling of commercially available underivatized
Figure 6. (a) Manno-PANI on the ITO electrode, (b) manno-PANI−Con A sensing layer, (c) E. coli detection with the manno-PANI−Con A sensing layer, and (d) top curve, EIS response of manno-PANI binding with Con A; bottom curve: EIS response of manno-PANI-Con A binding with different bacteria in Ca2+ (1mM) HEPES buffer. F
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Figure 8. Schematics of the two modes of bacterial detection: direct pili−carbohydrate binding and Con A-mediated LPS−mannose binding.
Figure 9. Calibration curves of signals drawn from multimodal polythiophene interface where logarithm of E. coli concentrations is plotted against (A) SWV electrochemical signals and (B) QCM frequency signals. Reproduced with permission from ref 27. Copyright 2015 American Chemical Society.
The biointerface designed was assessed for its general applicability in label-free multimodal detection of E. coli for analysis of cells utilizing carbohydrate−protein interactions. The O-antigens of lipopolysaccharide (LPS) and fimbriae proteins are the most striking characteristics of Gram-negative bacteria. The sensing of both LPS and fimbriae proteins was characterized with dual-mode electrochemical and QCM transducers, although the optical transduction can also be carried out like the polyaniline example. We characterized the interactions of fimbriae proteins with the conjugated mannose moieties of this biointerface via the direct pili−carbohydrate binding mode. In parallel, Con A could be used as the mediator for the binding of the LPS on the bacterial surface with Con A (Figure 8). The built-in polythiophene solid-state redox probe enabled mass and electrochemical dual-mode readouts, eliminating the need for redox mediators and labels, thus promoting noninvasiveness. Moreover, the electrochemical readout is a signal OFF approach, featuring the decrease of the output current signals with the increase of the analyte concentration, while the QCM readout furnishes the opposite signal ON approach, in which the output frequency signals increase with the amount of the analytes. Our results showed the flexibility to target two different biomarkers of the cellular surfaces (i.e., carbohydrates and proteins) simultaneously to elucidate higher dimensionality in studying the biointeractions, thereby enhancing the information content. This complementary and orthogonal readout enables internal crossvalidation, providing more reliable information from each single binding event for further complete analysis. So the integration of these advantages conveyed to the whole system enhanced sensitivity and broadened the dynamic range with greater reliability. It is worthwhile to note in Figure 9, that for two different binding modes, the LPS−Con A−mannose binding format facilitated more rigid binding of the bacteria, providing 32-fold and
300-fold enhancements in the detection limits for the electrochemical and QCM readouts, respectively (LOD = 25 cells/mL for electrochemical sensor and LOD = 50 cells/mL for QCM sensor). The logarithmic linear ranges were also enlarged with this approach compared with the direct mannose−pili fimbriae protein interactions. Through frequency-resistance analysis of QCM, we showed that the anchoring of the cells at a rigid carbohydrate interface by the pili proteins where cells are lying outside the extinction depth of the acoustic wave is still valid for the interpretation of the binding phenomena.27,29 In fact, this relatively weak and flexible fimbriae-related adhesion represents dynamic and true biological conditions where high mobility of cells creates large freedom of movement that may result in the replacement of one species with others, generating varying responses, and measuring these responses in real time by integrated electrochemical and QCM readout (EQCM) can have significant consequences for cellular interaction studies.
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POLYTHIOPHENE BIOINTERFACE FOR ANTIMICROBIAL SUSCEPTIBILITY ASSAYS Certain antibiotics act on cell wall biosynthesis, dramatically affecting the cell surface carbohydrate and lectin expression and adhesion. These effects, such as the alteration of LPS chain length, can modify or retard the bacterial/cellular binding with the substrates. Thus, real-time information regarding these alterations in carbohydrate−protein interactions can not only provide a fast bacterial susceptibility testing but also explain the fundamental mechanisms of the differences in mode of action of antibiotics or other clinical drugs, their influence on cell surface morphology, and their efficacies. Moreover, many physiological complications such as septic shock, which is associated with antibiotic released endotoxins (LPS), can be identified and understood. G
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Figure 10. Different mechanisms of action of the tested antibiotics and the corresponding data for 18 h incubation (where final responses are indicated as bar graph) and real time measurements (where live trace is shown before and after the addition of antibiotics).
sensor surface by exposing it to 5 × 108 cells/mL solution resulting in coinciding sensing signal, after which, antibiotic samples were introduced to study the alteration in binding. Immediately, the binding started to be reversed for all antibiotic samples, which were clearly distinguishable from each other after just 2 h of monitoring. Though the response was quite smaller than the initial 18 h incubation experiment, the pattern of response for various antibiotics was the same as that obtained after 18 h. This response was used to determine the binding kinetics, which was done by calculating the relaxation time (τ) from the curve fitting of frequency shift values obtained during the binding and unbinding. The relaxation times for various scenarios are given in Table 3 where a higher τ value means longer time required for the binding interaction.
The glycosylated polythiophene interface allowed us to study bacterial cell antibiotic resistance by monitoring the antibiotic effects on the LPS properties as a function of alteration in carbohydrate−protein binding signals. Three antibiotics (ciprofloxacin, ceftriaxone, and tetracycline) can attack the bacterial cells in different formats, either by changing or releasing the LPS structures or by inducing cell lysis (Figure 10). To apply the developed biointerface for an antimicrobial susceptibility test against these antibiotics, fresh LB cultures of the bacterial cells (2 × 105cells/mL) were incubated with antibiotics at clinically relevant concentrations for 18 h. When the binding profiles of the resulting samples were studied against QCM and electrochemical readouts in comparison to the blank sample without antibiotics, the blank sample showed the highest binding (largest frequency shift of QCM) because the bacterial cell surface LPSs in this sample are at their fully functional state. Contrarily, the samples incubated with various antibiotics showed lesser binding that quantitatively depended upon the decreased adhesion structures related to the antibiotic used. Normalization of these affects against blank sample provided conclusive evidence that the bacterial binding was reduced to 38%, 27%, and 23% with tetracycline, ceftriaxone, and ciprofloxacin, respectively. These results suggested that the antibiotics inhibited the growth of E. coli in log phase by affecting LPS integrity and function at the bacterial cell surface. The pattern of the responses from electrochemical data was also related to what was obtained from QCM (i.e., 7.2-, 4.8-, and 2.0-fold increase of normalized square-wave voltammetry (SWV) signal from the respective antibiotics), thereby providing internal validation and reliability, using the multimode function of the biosensor. After establishing that the variability in antibiotic actions can be studied using this sensor based on an alteration of LPS properties, which subsequently affect the cell binding, we further tested the sensor’s ability to quantitatively measure the same parameters in real time. Here, bacterial cells were captured on the
Table 3. Relaxation Time (min) against Different Concentrations of Selected Antibiotics conc (mg/L)
ceftriaxone
ciprofloxacin
tetracycline
1 10 30
15.5 18.4 22.5
21 23.5 23.6
11.2 13.9 19.8
This kinetic analysis showed that ciprofloxacin has the longest relaxation time and is more active in bacterial inhibition than the other two counterparts at the same concentration. The efficiency of this multimodal interface, thus, helped us to obtain the relevant bioinformation rapidly, allowing the health providers to make judgements and decisions more timely and accurately and to avoid empiric, rather broad spectrum use of antibiotics. But even more importantly, this work sets up the example of applying carbohydrate−protein recognitions using the versatile CP platform for the investigation of the antibiotic actions. Furthermore, the trends shown were consistent with minimum inhibitory concentration (MIC) values, which are generally regarded as the H
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Accounts of Chemical Research most standard laboratory measurements of the activity of an antimicrobial agent against an organism. Once we can determine these effects in real time, we can quantitatively determine the most effective drug, its time of response, and even its effective concentration to use, for the best therapeutic management using such protocols. Multiple of such applications can be designed for cellular interactions with drug molecules, cell biomarker interactions with sensors, and even cell−cell interactions exploring carbohydrate−protein profiling with the CP based biosensor platforms.
chemistry Ph.D. program. He is currently a Ph.D. student at Oakland University, majoring in biomedical science, under the guidance of Professor Zeng. His research interests involve conductive polymeric materials and their bioanalytical applications. Abdul Rehman obtained his Ph.D. in Chemistry (University of Vienna, Austria) from Prof. Dickert’s lab and completed postdoctoral research in the groups of both Dr. Mark Meyerhoff (University of Michigan) and Dr. Zeng’s lab (Oakland University). Currently he is an assistant professor of chemistry at KFUPM (Saudi Arabia) and an adjunct assistant professor at Chemistry Department at Oakland University. His research interests include material/interface designs and integration for various chemical and biosensing platforms and protocols.
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CONCLUDING REMARKS Despite tremendous progress in developing label free biosensors, the methods available have limitations. In this Account, we illustrated that glycosylated CP-based biosensors using polyaniline and polythiophene as examples are promising label-free multimodal biosensor platforms to study carbohydrate−protein interactions with the following benefits. First, the CPs decorated with the carbohydrates could provide larger surface area, being beneficial to the exploration of their multivalent binding with the target proteins. Second, CPs are reasonably stable in ambient environments and can be readily made by conventional solution polymerization with the appropriate oxidants, more controlled electropolymerization, or transition-metal mediated coupling polymerization. The parameters of the polymeric films, such as the film thickness, can be controlled and altered systematically with the polymerization methods. Functionalized CP monomers can be designed systematically, allowing the study of the carbohydrate orientation variation to offer some structural insights into their binding processes. Third, in contrast to a traditional electrochemical biosensor, in which a redox probe (i.e., K3Fe(CN)6/K4Fe(CN)6) is often added that is not desirable especially for high throughput systems, the CP approach can realize label-free, reagentless transduction of the biological binding events into electric, optical, and mass signals, rendering multimodal sensing with low cost and simple readout instruments. The multimodal sensing with the flexibility and control of the glycosylated CPs allows cross-validation of the measurements and renders complementary information regarding the binding reactions such as thermodynamics, kinetics, hydration, molecular conformation, and structural complementarity to be obtained. They can easily provide multiplexed detection capability by forming CP arrays for simultaneous analysis of multiple samples, making this approach very powerful for fundamental and applied glycobiology research.
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ACKNOWLEDGMENTS X. Zeng thanks Oakland University REF for support of this work. REFERENCES
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[email protected]. Notes
The authors declare no competing financial interest. Biographies Xiangqun Zeng is a Professor of Chemistry at Oakland University, Rochester, MI. She obtained her Ph.D. in electrochemistry and surface chemistry from SUNY at Buffalo with Stanley Bruckenstein in 1997. Her lab focuses on the fundamental and applied research of ionic liquids and conductive polymers at solid electrodes, development of new analytical techniques, and chemical and biosensors. Ke Qu obtained his B.Sc. in chemistry from Sichuan University (China) and M.S. in organic chemistry from Michigan State University. He then attended The University of Texas at Austin to study organic synthesis in I
DOI: 10.1021/acs.accounts.6b00181 Acc. Chem. Res. XXXX, XXX, XXX−XXX
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DOI: 10.1021/acs.accounts.6b00181 Acc. Chem. Res. XXXX, XXX, XXX−XXX
