A Novel Three-Dimensional Nanosensing Array for the Discrimination

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A Novel Three-Dimensional Nano Sensing Array for the Discrimination of Sulfur Containing Species and Sulfur Bacteria Jian-Yu Yang, Ting Yang, Xiao-Yan Wang, Yi-Ting Wang, MengXian Liu, Ming-Li Chen, Yong-Liang Yu, and Jian-Hua Wang Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.9b00476 • Publication Date (Web): 09 Apr 2019 Downloaded from http://pubs.acs.org on April 14, 2019

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Analytical Chemistry

A Novel Three-Dimensional Nano Sensing Array for the Discrimination of Sulfur Containing Species and Sulfur Bacteria

Jian-Yu Yang†, Ting Yang†, Xiao-Yan Wang, Yi-Ting Wang, Meng-Xian Liu, Ming-Li Chen, Yong-Liang Yu*, Jian-Hua Wang Research Center for Analytical Sciences, Department of Chemistry, Colleges of Sciences, Box 332, Northeastern University, Shenyang 110819, China

Corresponding Author *E-mail: [email protected] (Y.-L. Yu) Tel: +86 24 83688944; Fax: +86 24 83676698

ABSTRACT: The discrimination of various sulfur containing species helps us to deeply understand how sulfur affects cellular signaling and other physiological events. Herein, we present a three-dimensional sensor array based on simultaneous variation of the optical properties (fluorescence, light scattering and UV-vis absorption) of gold-silver alloy nanocluster (AuAgNCs)-gold nanoparticle (AuNPs) composite for the rapid identification of 13 sulfur-containing species and sulfur oxidizing bacteria. The sensor array is fabricated based on the strong coordination interactions between sulfur-containing compounds and AuAgNCs on the surface of AuNPs. The sulfur species of interest exhibit different affinities towards AuAgNCs and generate unique 1

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Analytical Chemistry 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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optical properties. These response patterns could divide the analytes into three categories including organic sulfide, inorganic sulfide and thiols. 13 types of sulfur species including cystine, methionine, GSSG, S2-, SO32-, S2O32-, S2O72-, S2O82-, S4O62-, GSH, N-acetyl-L-cysteine, homocysteine and cysteine can be well distinguished by the sensor array with principal component analysis (PCA) at 0.5 A

Moreover,

sulfur oxidizing bacteria and non-sulfur bacteria can also be well discriminated at a level of OD600=0.005.

KEYWORDS: sensor array, three-dimensional, sulfur containing species, sulfur bacteria.

2


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INTRODUCTION Sulfur is widely spread in nature and is one of the essential elements that constitute a living organism. It is involved in cell energy and other substances metabolism such as protein, vitamins and antibiotics.1 Naturally, sulfur exists in a variety of chemical states ranging from -2 to +6, i.e., elemental sulfur, reductive sulfides, sulfate and sulfur-containing organics. Common reductive sulfides include H2S, sulphide, thiosulfate salt (S2O32-) and sulfite (SO32-), whereas sulfur-containing organics mainly refer to the sulfur-containing amino acids such as cysteine, methionine, cystine, glutathione and their derivatives. The speciation of sulfur is closely related to the biochemical process including the cycling of nutrient and detoxification of toxic elements. Sulfur oxidation is an important part of the biogeochemical sulfur cycle, referring to the oxidation process of elemental sulfur and inorganic sulfur-containing compounds by various sulfur oxidizing bacteria (SOB).2 SOBs are highly diverse, with large variation on their genes, enzymes and pathways of sulfur oxidation. SOBs can oxidize elemental sulfur or reducing sulfide into sulfates, which provides a more economic and effective way for biological desulfurization and biohydrometallurgy.3-6 Hence, distinguishing different species of sulfur and SOBs will not only provide deep insight into the biogeochemical cycle of sulfur elements, but also provide a solid theoretical basis for the application of SOBs in environmental engineering and metallurgical industry. Array-based sensing techniques have emerged as a powerful approach toward detection and discrimination of diverse analytes.7-9 Currently, the sulfur speciation 3



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study based on array-sensing techniques is mainly focused on the discrimination of thiols.10-15 A study of the thiols discrimination based on urease-metal ion pairs has been reported, with six types of thiol distinguished at a concentration of 1 A

level.10

Recently, a novel Raman probe has been developed to simultaneously discriminate and quantify three biothiols at the single cell level.12 Our group has also developed a multichannel fluorescent sensor array for the discrimination of seven types of thiols based on the affinity difference between thiols and carbon dots-metal ion pairs.15 Although these methods can accurately discriminate thiols, they cannot distinguish other sulfur species. Moreover, most of these array-based sensors need to prepare a series of sensing units to create multiple signal readout, which is costly, time-consuming, and in many cases not reliable. On the other hand, multidimensional sensing devices which can provide multidimensional information from an individual sensor unit can effectively solve this problem.16-19 For instance, the Mn-doped ZnS quantum dots and carbon-dots have been used as the single probe for multidimensional sensing to distinguish proteins,16 antibiotics17 and cells.18 However, special sensing materials that generate multiple signals are still rare and sophisticated design of the interactions between sensing materials and analytes are always required, which restricted their practical applications. In this work, we developed a three-dimensional (fluorescence, UV-vis absorbance, light scattering) model array sensor by coupling the plasmon resonance absorbance of AuNPs and the fluorescence property of AuAgNCs. In addition, AuNPs are capable of scattering the incident light which exhibits an increase upon the 4


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aggregation of AuNPs.20 The multidimensional sensing unit was constructed by simply associating positively charged AuNPs with negatively charged AuAgNCs through electrostatic interaction, and no additional coupling process is required. The three optical signals of the sensor array are changed simultaneously upon the addition of different sulfur species. As shown in Scheme 1, various sulfur species show different affinities toward the FA-AuAgNCs. Therefore, the fluorescence, UV-vis absorbance and light scattering signal of the system change in diverse degree. We first applied the array sensor for the purpose of sulfur speciation, i.e., thirteen different species of sulfur-containing compounds can be discriminated at a concentration of 0.5 A

Furthermore, SOBs that produce different species of sulfur in the periplasmic

space and cytoplasm during the metabolic process are also well distinguished from non-sulfur bacteria at a low level of OD600=0.005. In comparison with other multidimensional sensing devices, the present sensing unit exhibits obvious advantages. (1) It is fabricated with common materials which are ease of preparation; (2) by simply combining two materials together, a new composite with three-dimensional signal readout can be created; (3) a single spectrofluorometer with different detection modes suffices data acquisition for the two significant factors (fluorescence and light scattering channel) for plotting principal component analysis (PCA) diagram, which largely simplified the operation; (4) this universal strategy can be further applied in other multiple analytes, e.g., by taking advantage of the affinity difference towards AuAgNCs between aptamer decorated AuNPs and analytes of interest (proteins, biomarkers, cancer cells), it opens a new avenue for the 5




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China). Acidithiobacillus caldus SM-1, originally isolated from bioreactor treating gold-bearing concentrates, is a gift kindly donated by Professor Da-Ke Xu, College of Materials Science and Engineering, Northeastern University.5 Apparatus. The microstructure of FA-AuAgNCs was characterized by a JEM-ARM 200F transmission electron microscope (JEOL Ltd., Japan) operating at 200 kV. The morphology of (+) AuNPs was acquired on a G20 transmission electron microscope at an accelerate voltage of 200 kV (FEI Ltd., USA). X-ray photoelectron spectroscopy (XPS) scanning curve was obtained from an ESCALAB 250 X-ray photoelectron spectrometer (Thermo Instruments Inc., USA). The zeta potential and hydrodynamic diameter of FA-AuAgNCs and (+) AuNPs were investigated by Malvern Nano ZS90 nanosizer in citrate buffer (pH 4.0, 10 mM) at 25 °C (Malvern Instruments Ltd., England). Fluorescence and light scattering measurements were performed on an F-7000 fluorescence spectrophotometer (Hitachi High-Technologies Corporation, Japan) equipped with a quartz cell (optical path: 4 mm×4 mm) under the conditions listed in Table S1. The colorimetric measurements were obtained from a U-3900 UV-vis spectrophotometer (Hitachi High-Technologies Corporation, Japan). Preparation of FA-AuAgNCs. All the glassware was thoroughly washed with aqua regia (caution: Aqua regia is a powerful oxidizing reagent, and it should be handled with extreme care) and rinsed extensively with ultrapure water before use. FA-AuAgNCs were prepared based on a previously reported procedure with minor modifications.21 First, 80 A of 50 mM folic acid was added in 3.12 mL of ultrapure water (final concentration: 1 mM). To this mixture, 200 A of 5 mM HAuCl4 was 7



added (final concentration: 0.25 mM) followed by the addition of 400 AL of 0.5 M citrate buffer (pH 6, final concentration: 50 mM). Then the mixture was incubated at 80°C in a water bath for 30 min followed by the addition of 200 A of 2 mM AgNO3 (final concentration: 0.1 mM). FA-AuAgNCs were formed after heating for another 4 h under 80 °C. The solution was filtered through a 0.22- m filter membrane to remove the insoluble aggregates. To remove excessive folic acid and citrate, the solution was further purified by adding 12 mL ethanol (Vethanol:Vwater=3:1) and centrifuged at 8000 rpm for 20 min. FA-AuAgNCs were precipitated from the solution, while the free FA and citrate remained in aqueous solution. The precipitates were then resuspended in ultrapure water to obtain the final solution. Preparation of (+)AuNPs. CTAB capped AuNPs were prepared according to the literature with minor revision.22 Briefly, 2 mL of 10 mM CTAB was added in 15 mL of 1.0 mM HAuCl4 and stirred for 9@P

Then, 2 mL of 0.1 M NaBH4 was

added dropwise to the mixture and kept stirring for 30 min. The color of the solution turned from pale yellow to orange red. The solution was filtered through a 0.22- m filter membrane and stored in brown glass bottle at 4°C for future use. Due to the positively charged feature, the CTAB capped AuNPs were labeled as (+) AuNPs. The Discrimination of Different Sulfur Species. First, 100 AL of the prepared FA-AuAgNCs (0.05 mg mL-1, pH 4.0, 10 mM citrate buffer) was first added into 100 A of the positively charged (+)AuNPs (2.5 nM) solution and incubated for 30 min at room temperature, resulting in (+)AuNPs/FA-AuAgNCs composite. Then, 100 A of sulfur-containing compounds at various concentration levels (Cys, Met, S2-, SO32-, 8


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S2O32-, S2O72-, S2O82-, S4O62-, GSH, GSSG, NAC, Hcy and Cys-Cys) were added into the mixed solution separately. After incubation at room temperature for 30 min, the fluorescence intensity ((ex/em 280 nm/440 nm), UV-vis absorbance ((max 535 nm) and light scattering signal (( 370 nm) of the solution were measured. All measurements were repeated to generate 4 replicates of each analyte, so that for a given concentration, a 3 channels×13 analytes×4 replicates data matrix could be generated. The raw data were normalized, i.e., (I-I0)/I0, (A-A0)/A0 for absorbance measurement, to eliminate the potential bias caused by the difference in the original signal intensity. Finally, the obtained data were processed using principal component analysis (PCA) in SPSS V 17.0 software. Bacteria Identification. The culture process of each bacteria is described in detail in Supporting Information. Before the test, the bacteria were collected by centrifugation at 6000 rpm for 10 min, followed by washing with PBS buffer (pH 7.4, 10 mM) for three times. The bacteria solution was then adjusted to a final concentration of OD600 0.03 and 0.015. Then, 100 A of bacteria suspension was added to 200 A of (+)AuNPs/FA-AuAgNCs solutions. After incubating for 30 min, the fluorescence intensity, UV-vis absorbance, and light scattering signal of the solution were measured. The obtained data were treated as the same as mentioned above.

RESULTS AND DISCUSSION Characterization of FA-AuAgNCs and (+)AuNPs. FA is a commonly used ligand for the synthesis of AuNPs due to the formation of Au-N bond between FA 9



molecule and Au atoms.23 Smaller sized AuNCs capped with FA were also successfully prepared with the assistance of reducing agent NaBH4 by our group.24 In this work, by doping suitable amount of Ag and replacing NaBH4 with citrate, an Au-Ag alloy nanocluster (FA-AuAgNCs) with strong blue luminescence were obtained. For the purpose of obtaining FA-AuAgNCs with highest fluorescence emission, the experimental conditions were optimized as shown in Figure S1A-C, and an Au: Ag molar ratio of 5:2, pH 6.0 for the reaction system, and a reaction time of 4 h were chosen. It is worth noting that the FA-AuAgNCs have the same fluorescence feature with FA-AuNCs, with the maximum wavelength at QexIQem 280/440 nm (as illustrated in Figure S2A). However, the fluorescence intensity was much stronger with the doping of Ag atoms, which might be attributed to the synergistic effect between Au and Ag.25,26 High resolution transmission electron microscopy (HRTEM) images (Figure S3A) illustrated that FA-AuAgNCs were well-dispersed spheres, with an average core size of 1.99±0.06 nm (Figure S3B). Considering the capping of FA on the surface of FA-AuAgNCs, the hydrodynamic diameter obtained from dynamic light scattering (DLS) measurement was a little larger (3.82 nm) (Figure S4A). As illustrated from X-ray photoelectron spectroscopy (XPS) results, Au showed a dominant Au0 metallic state with the binding energy of 83.6 eV for Au 4f7/2 and 87.15 eV for Au 4f5/2 (Figure S5A).27 The broad peak (Ag 3d5/2) at 367.5 eV was decomposed into two distinct components centered at the binding energies of 367.25 eV and 367.85 eV (Figure S5B), which were assigned to Ag(0) and Ag(I), respectively.28 The atomic ratio of Ag(0) and Ag(I) in FA-AuAgNCs was further 10


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calculated to be 1:1. Meanwhile, C (1s), O (1s) and N (1s) core-level photoemission spectra indicated that AuAgNCs were protected by FA (Figure S5C). The (+)AuNPs displayed a strong surface plasmon resonance at 520 nm (Figure S2B), leading to a wine-red color in visible light. As shown in Figure S3C, the (+)AuNPs exhibited good monodispersity and uniform structure, and the average size of these spherical particles was measured to be 13.6±1.1 nm (Figure S3D). The presence of CTAB on the surface of (+)AuNPs lead to an increase of the average hydrodynamic diameter of the (+)AuNPs from 13.6 to 33.78 nm (Figure S4B). The zeta potentials of FA-AuAgNCs and (+)AuNPs were measured in citrate buffer solution (pH 4.0, 10 mM) and the values were -17.81 mV and +24.67 mV, respectively (Figure S6D). Thus, (+)AuNPs could associate with FA-AuAgNCs by electrostatic attraction, resulting in the (+)AuNPs/FA-AuAgNCs composite (Figure S3E). As shown in Figure S6A, the fluorescence intensity of FA-AuAgNCs was quenched after the addition of (+)AuNPs due to the nanoscale surface energy transfer (NSET).29 In comparison with (+)AuNPs, the SPR absorption band of (+)AuNPs /FA-AuAgNCs also displayed a 15 nm redshift (Figure S6B), which was consistent with the increased hydrodynamic diameter from 33.78 nm to 130.12 nm (Figure S4C). The increased particle size is due to the adsorption of FA-AuAgNCs on the surface of the (+)AuNPs. Besides, the increased particle size can also be reflected by a stronger light scattering signal compared with that of (+)AuNPs alone (Figure S6C). In this regard, suitable analytes with stronger coordination properties may replace (+)AuNPs via a competitive way, which would disrupt the NSET process between (+)AuNPs 11



and FA-AuAgNCs and change the particle size as well; these changes can be reflected by the variation in fluorescence intensity, UV-vis absorption and light scattering signal, which can be used as multiple signal channels for the construction of biosensing arrays. Sulfur-Containing Compounds Discrimination by Principal Components Analysis (PCA). As a proof of concept, Met and Cys were chosen as analyte model in the preliminary experiment, as they are expected to competitively bind to either (+)AuNPs or FA-AuAgNCs through strong Au-S bond and lead to the disassembly of the composite. ICP-MS analysis and DLS results indicated that the addition of Met and Cys resulted in an increased amount of isolated FA-AuAgNCs (Figure S7A) and smaller average hydrodynamic diameter (Figure S7B), and Met seems to induce more FA-AuAgNCs peeling off from the composite than Cys. Correspondingly, the fluorescence of the composite both recovered upon addition of Met and Cys (Figure S7C). However, the fluorescence recovery induced by Cys was much higher than Met, indicating that the disassembly of the composite is not the only reason responsible for the fluorescence enhancement. We speculate that the interaction between Met/Cys and FA-AuAgNCs or (+)AuNPs may also contribute to the fluorescence change. The fact that UV-vis absorption spectra of (+)AuNPs in the presence of Met/Cys remained unchanged (Figure S8A) indicated that Met/Cys barely interact with (+)AuNPs. On the other hand, the fluorescence of FA-AuAgNCs was enhanced in the presence of Met/Cys, with Cys gave rise to a stronger enhancement effect (Figure S8B). In fact, not only Met and Cys, all thirteen types of sulfur-containing compounds we tested 12


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lead to the fluorescence enhancement of FA-AuAgNCs to various extent, i.e., inorganic sulfur (S2-, SO32-, S2O32-, S2O72-, S2O82-, S4O62-), organic sulfur (cystine, GSSG, methionine) and thiols (GSH, N-acetyl-L-cysteine, homocysteine and cysteine). The order of fluorescence enhancement was thiols>inorganic sulfur >organic sulfur. Similar results were also reported recently, in which non-luminescent AuNCs prepared with nonthiolated ligands such as phosphine-containing ligands and folic acid exhibited luminescent after ligand exchange with sulfide-containing molecules.30 The ligand substituent group altered the electronic structure of luminophore itself via changes to the Au-S binding motif and the ligand geometry.

1.2 FL LS UV-vis 0.8

(I-I0) / I0

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


0.4

0.0

SO32-

Cys 22Cys NAC Hcy GSH S2- S2O32- S2O7 S4O62- S2O8 Met GSSG -Cys

Figure 1. Fingerprints of thirteen different sulfur-containing compounds at 1 A based on the patterns for corresponding values of (I-I0)/I0 obtained from fluorescence intensity, UV-vis absorbance and light scattering signal of the (+)AuNPs/FA-AuAgNCs composite. As can be expected, the interaction between (+)AuNPs/FA-AuAgNCs composite 13



and these sulfide-containing molecules would also lead to the variations on the fluorescence intensity, UV-vis absorbance as well as light scattering signals of the composite at different extent. As a proof-of-concept, we selected thirteen different sulfur-containing compounds as the sensing targets, which have diverse structural characteristics and different molecular weight (Table S2). Figure 1 illustrated the fluorescence intensities at (ex/em 280/440 nm, UV-vis absorbance at 535 nm and light scattering signal at 370 nm for the composite in citrate buffer (pH 4.0, 10 mM) in the presence of 13 types of sulfur-containing compounds, where diverse responses to the tested sulfur-containing compounds were observed. It is seen that all 13 sulfur-containing compounds cause enhancement on the fluorescence intensity and decrement on the light scattering signal, whereas most sulfur-containing compounds give rise to slight decrease on UV-vis absorbance with exception of S2-, SO32- and S2O82-. The decrease of light scattering intensity indicated a smaller average particle size of the composite after the addition of sulfur-containing compounds. In comparison with the electrostatic interaction between FA-AuAgNCs and (+)AuNPs, sulfur-containing compounds had a much stronger coordination interaction with either FA-AuAgNCs or (+)AuNPs. Therefore, the interaction between sulfur-containing compounds and (+)AuNPs/FA-AuAgNCs composite will separate FA-AuAgNCs from the (+)AuNPs, leading to the blocking of NSET and the reduction of particle size. For UV-vis absorbance response, the decrease on UV-vis absorbance is due to the blue shift of the absorption band of (+)AuNPs caused by the isolation of FA-AuAgNCs from the surface of (+)AuNPs. Different sulfur-containing 14


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compounds had various affinities to FA-AuAgNCs, thus exhibit various degrees of shift in UV-vis absorption (Figure S9). The fluorescence enhancement was attributed to two reasons, i.e., the recovery of fluorescence that was originally quenched by (+)AuNPs; the fluorescence enhancement of FA-AuAgNCs due to the interaction between sulfur-containing compounds and FA-AuAgNCs. The fluorescence enhancement of inorganic sulfur was stronger than that caused by organic sulfur and thiols, presumably due to the fact that the interaction between inorganic sulfur and FA-AuAgNCs was the strongest which leads to the highest fluorescence recovery. These signal changes, which act as “fingerprints”, encouraged us to exploit a pattern recognition approach for the discrimination of sulfur-containing compounds/species. In order to get the best analytical performance, the sensing conditions, including the ratio of FA-AuAgNCs and (+)AuNPs and reaction time were optimized with S2- as the representative of sulfur compounds. As shown in Figure S10A, with the increase of (+)AuNPs concentration, the fluorescence of FA-AuAgNCs decreased gradually. A saturated quenching efficiency can be obtained when 0.05 mg mL-1 FA-AuAgNCs were incubated with 2.5 nM (+)AuNPs in citrate buffer at pH 4. Meanwhile, the triple signal response of (+)AuNPs/FA-AuAgNCs composite to S2- with different concentration of (+)AuNPs were also investigated. As can be seen in Figure S10B, 2.5 nM of AuNPs gave rise to the largest signals. Therefore, the optimal concentration ratio between FA-AuAgNCs and AuNPs was 0.05 mg mL-1 vs 2.5 nM. The three-dimensional optical responses of the (+)AuNPs/FA-AuAgNCs composite to sulfide (S2-) can reach equilibrium within 30 15



min. Unless otherwise noted, the following experiments were performed under these conditions. To evaluate the precision of the response, the composite was incubated with S2- containing samples (1 A ! at pH 4.0. The experiments were repeated for six times, and the relative standard deviation (RSD) of fluorescence response, UV-vis absorption and light scattering response were derived to be 1.15%, 2.89% and 0.57%, respectively. The stability of (+)AuNPs/FA-AuAgNCs composite at pH 4.0 was further studied by measuring the triple signals of freshly prepared (+)AuNPs/FA-AuAgNCs composite for 5 days and plotting the results as fingerprint diagram (Figure S11). As can be seen in Figure S11, the fluctuation of the signal measured every day was less than 10%, indicating that the composite are stable and the variation between the blank signals do not result in changes in the initial pattern. The selectivity of this sensor was also investigated by comparing the triple signal response of the composite to some potentially coexisting compounds, i.e., common amino acids, metal cations, anions, uric acid and glucose (Figure S12). These commonly encountered co-existing compounds exhibit neglectable response to the composite, indicating that the composite had high selectivity towards sulfur-containing compounds. To explore the fingerprints more clearly, principal component analysis (PCA) was used to differentiate the fluorescence intensity, UV-vis absorbance and light scattering signal of the composite added with sulfur-containing compounds. For each analyte, we tested the three types of signals for four times, generating a matrix of 3 channels×13 analytes×4 replicates. The data were normalized [(I-I0)/I0] to eliminate 16


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the potential bias caused by the difference in the original intensity of the composite, where I0 and I represent the three optical signals in the absence and presence of sulfur-containing compounds. PCA analysis transforms the matrix into three canonical factors (51.7%, 37.04%, 11.26%). The fluorescence channel (51.7%) had better sensitivities than the light scattering (37.04%) and UV-vis absorbance channel (11.26%) for the most analytes used herein. The two significant factors, i.e., fluorescence and light scattering channel, were plotted in a two-dimensional diagram, in which each point indicated the response patterns for an individual sulfur-containing compound against the proposed sensor array (Figure 2). The target analytes were clearly clustered into thirteen groups that correspond to each specific sulfur-containing compound, demonstrating that the three-dimensional sensing device based on the optical properties of the (+)AuNPs/FA-AuAgNCs composite could effectively discriminate sulfur-containing compounds. PCA test for the sulfur-containing compound at the concentration of 0.5 A

indicated that all the 13

sulfur-containing compounds were clearly separated in the 2D canonical score. At an even lower concentration level of 0.25 A

11 out of 13 sulfur-containing compounds

could be identified clearly and only two of them exhibit a certain extent of overlap in canonical score plots (Figure S13). This observation well demonstrated that the present sensor array system had strong power for discriminating sulfur-containing compounds, and the thirteen sulfur-containing compounds at Y? @ A clearly distinguished.

17


could be


2.0

S2O821.5

Factor (2) 37.04%

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S2O72-

1.0 0.5 0.0

GSSG

S4O62-

GSH Cys Hcy

-0.5 -1.0

NAC

SO32-

S2O32Met Cys-Cys

-1.5 -1.5

-1.0

-0.5

0.0

0.5

S21.0

1.5

2.0

Factor (1) 51.70%

Figure 2. PCA for the discrimination of thirteen different sulfur-containing compounds at 0.5 A

by the (+)AuNPs/FA-AuAgNCs composite-based sensor array

(triple signals fluorescence, light scattering and UV-vis). The details of experimental conditions were described in the Experimental Section. To further evaluate the discriminative capability of this sensor array, we detected various concentrations of GSH and the mixture of GSH and Cys. Since PC2 in the PCA plots was smaller than 40%, it is acceptable to employ PC1 to correlate the concentration of GSH.31 As shown in Figure 3, GSH at concentration ranging from 0.5 to 5 A

were well discriminated on a two-dimensional PCA plot. Moreover, five

mixtures of GSH and Cys with different molar ratios (0/100, 25/75, 50/50, 75/25, 100/0) were chosen to evaluate the capability of the sensor array to distinguish the coexisting sulfur-containing compounds. Figure 4 indicated that these mixtures were distinctly discriminated from each other in the PCA plot, by proper arrangement of the order of ratios in the dimension of the first factor. Similarly, the mixtures of (S2and GSH), (Cys and Met), and (Cys and S2-) at different molar ratios (0/100, 25/75, 18


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50/50, 75/25, 100/0) can also be well discriminated with proper arrangement (Figure S14), confirming the potential of (+)AuNPs/FA-AuAgNCs composite to analyze samples with complicated ingredients. 2.0

A

5 2M 1.5

B

1.0 0.5

1.0

0.0

2.5 2M

0.5

PC1

Factor (2) 1.17%

0.0

-0.5

1.5 2M -1.0

-0.5

1 2M

-1.0 -1.5 -2.0

-1.5

0.5 2M

-2.0 -1.5

-1.0

-0.5

0.0

0.5

1.0

1

1.5

Factor (1) 98.52%

2

3

4

5

C GSH (2M)

Figure 3. (A) Canonical score plots for the three-dimensional response patterns obtained by the (+)AuNP/FA-AuAgNCs composite-based sensor array towards different concentrations of GSH (0.5, 1, 1.5, 2.5, 5 A ! by PCA. (B) The calibration curve between PC1 score and the concentration of GSH. 1.5

Factor (2) 27.97%

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


50% GSH 50% Cys

1.0 0.5 25% GSH 75%Cys

0.0 75% GSH 25% Cys

-0.5 -1.0 -1.5

100% Cys

-2.0 -2.0

-1.5

100% GSH

-1.0

-0.5

0.0

0.5

1.0

1.5

Factor (1) 67.96%

Figure 4. Canonical score plot against GSH and Cys mixtures by PCA. The total concentration of the mixture was set at 0.5 A 19



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Differentiation and Identification of Unknown Species of Sulfur. In order to test the efficiency of the proposed sensor array system, we conducted a blind test with randomly chosen species of sulfur-containing compounds. 52 unknown samples at the concentration level of 0.5 A

were tested by the sensor array. As shown in Table S3,

the discrimination results indicated that the identification accuracy rates of the unknown samples were 98%, only 1 out of 52 unknown samples was misclassified. As the concentration of sulfur-containing compounds was lower down to 0.5 A

the

discrimination accuracy for 52 unknown samples was still remarkable, indicating the great potential of the triple-dimensional sensing device for the identification of sulfur-containing compounds. Bacteria Discrimination. Sulfur-oxidizing bacteria (SOB) plays a crucial role in biogeochemical cycling of sulfur and carbon. They can be mainly divided into obligate autotrophs, facultative autotrophs and obligate heterotrophs. Due to the diversity of their sulfur oxidation pathway by SOB of different metabolic types, the sulfur-containing compounds existing in the periplasmic and cytoplasm space may vary among different strains of SOB.6,32 Since the sulfur content inside non-sulfur bacteria is relatively low compared with that in SOBs, it is expected to facilely distinguish SOBs from non-sulfur bacteria using the (+)AuNPs/FA-AuAgNCs composite-based sensor array. Three strains of sulfur-oxidation bacteria (SOB), i.e., a strain of autotrophic SOB Acidithiobacillus caldus (A. caldus) SM-1, two stains of heterotrophs SOB Citreicella thiooxidans (C. thiooxidans), and Thiobacimonas profunda (T. profunda), were 20


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chosen as model strains to demonstrate the usefulness of this sensor array in SOB discrimination, whereas two of the most widely studied human pathogens E. coli and S. aureus were chosen as the model strains for non-sulfur bacteria test.5,33,34 Figure S15 illustrated the triple signal (fluorescence intensity, UV-vis absorbance and light scattering signal) for the composite in citrate buffer (pH 4.0, 10 mM) in the presence of five types of bacteria. It can be seen that non-sulfur bacteria caused slight enhancement in fluorescence intensity and decrease in UV-vis absorbance and light scattering signal, whereas these responses raised by SOB were much higher than that by non-sulfur bacteria. The results is consistent with the confocal fluorescence microscopy results (Figure S16), in which C. thiooxidans cells incubated with the (+)AuNPs/FA-AuAgNCs composite emitted intense fluorescence, whereas E. coli cells treated with the same procedure produces negligible fluorescence. The decrease in LS and UV-vis signal indicated the disassembly of the (+)AuNPs/FA-AuAgNCs composite. At first glance, it seems that electrostatic interaction between negatively charged bacteria cells (Table S4) and positively charged (+)AuNPs might be responsible for the disassembly of the composite. However, although S. aureus was more negatively charged than A. caldus SM-1 (Table S4), the fluorescence enhancement raised by A. caldus SM-1 was much stronger than that by S. aureus. Considering the distinct content of sulfur-containing compounds in SOB cells, it is reasonable to conclude that affinity binding between sulfur-containing compounds on cells and (+)AuNPs or FA-AuAgNCs are the main reason for the disassembly of the composite. 21



2.0

2.5

A

2.0

non-sulfur bacteria

1.0

C. thiooxidans

Factor (2) 38.17%

1.5

Factor (2) 32.34%

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

0.5

SOB

0.0 -0.5

E. coli

T. profunda

S. aureus

-1.0 -1.5

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A. caldus SM-1

B

non-sulfur bacteria

T. profunda

1.5 1.0

SOB A. caldus SM-1

0.5

S. aureus

0.0 -0.5 -1.0

C. thiooxidans -2.0 -1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

-1.5 -2.0

2.0

-1.5

Factor (1) 55.12%

-1.0

-0.5

0.0

E. coli 0.5

1.0

1.5

2.0

Factor (1) 54.19%

Figure 5. Identification of bacteria with the (+)AuNPs/FA-AuAgNCs composite-based sensor array system. Bacteria concentrations of OD600 = 0.01 (A) and OD600 = 0.005 (B) are used, respectively. The triple signal of the composite added with the above mentioned five types of bacteria were further analyzed with PCA examination. As can be seen in Figure 5, these training cases were separated into five respective groups at the concentration level of 0.01 OD600 and 0.005 OD600, respectively, indicating that these bacteria were successfully discriminated. Then, we conducted a blind test with randomly chosen bacteria. 25 unknown samples randomly taken from the training set at the concentration level of OD600=0.01 were tested, and only 1 out of 25 was misclassified. The results in Table S5 clearly indicated that the proposed sensor array can accurately distinguish SOB from non-sulfur bacteria.

CONCLUSIONS A novel sensor array for the identification of sulfur-containing compounds was developed, based on the fluorescence, UV-vis absorbance and light scattering signal of the (+)AuNPs/FA-AuAgNCs composite. Thirteen sulfur-containing compounds 22


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were distinguished at a concentration level of down to 0.5 A

The identification was

based on the fact that sulfur compounds could induce FA-AuAgNCs peeling from the surface of the (+)AuNPs and enhance the fluorescence of FA-AuAgNCs due to the ligand exchange and the wakening of nanoscale surface energy transfer. Moreover, model sulfur-oxidation bacteria can also be well distinguished from non-sulfur bacteria by the sensor array at a concentration level of OD600=0.005. In addition, this work opened a new avenue for the development of multifunctional sensing platforms for specific biological or elemental analysis.

ASSOCIATED CONTENT Supporting Information Additional information as noted in text. This material is available free of charge on the ACS Publications website. The effect of pH, molar ratio of Au: Ag and reaction time on the fluorescence intensity of FA-AuAgNCs. Fluorescence excitation and emission spectra of FA-AuAgNCs. The absorption spectrum of (+)AuNPs. HRTEM images of FA-AuAgNCs and (+)AuNPs/FA-AuAgNCs composite. TEM image of (+)AuNPs. The hydrodynamic diameters of FA-AuAgNCs, (+)AuNPs and (+)AuNPs/FA-AuAgNCs composite. XPS spectra of FA-AuAgNCs. Fluorescence spectra of FA-AuAgNCs and (+)AuNPs/FA-AuAgNCs composite. The hydrodynamic diameter, the concentration of Ag+ in the supernatant and the fluorescence intensity of the (+)AuNPs/FA-AuAgNCs composite in the absence and presence of 1 A

Met and Cys. The UV-vis absorption spectra and light-scatting 23



Page 24 of 31

spectra of (+)AuNPs and the (+)AuNPs /FA-AuAgNCs composite. The UV-vis absorption spectra of (+)AuNPs in the absence/presence of sulfur-containing compounds. The fluorescence enhancement of FA-AuAgNCs after addition of sulfur-containing compounds. The UV-vis absorption of (+)AuNPs, the (+)AuNPs/FA-AuAgNCs composite in absence/ presence of S2-, Met and Cys. Fluorescence spectra of FA-AuAgNCs with the addition of (+)AuNPs at various concentrations and the triple signals of the composite in the presence of 1 A

S2- at

different concentration of (+)AuNPs. The triple signals of the freshly prepared (+)AuNPs/FA-AuAgNCs composite in different days. The triple signals of the (+)AuNPs/FA-AuAgNCs composite in the presence of common amino acids, metal cations, anions, uric acid and glucose or Cys. PCA for the discrimination of the thirteen different sulfur-compounds at 0.25 A

by the (+)AuNPs/FA-AuAgNCs

composite. Canonical score plot against S2- and GSH, Cys and Met, and Cys and S2mixtures by PCA. The triple signals of the (+)AuNPs/FA-AuAgNCs composite after addition of five different kinds of bacteria (OD600=0.01). Microscopy images of the (+)AuNPs/FA-AuAgNCs composite with C. thiooxidans and E. coli in ultrapure water. Operation parameters of F-7000 spectrofluorometer. Basic properties of the thirteen sulfur compounds. Detection and identification of sulfur compound and bacteria using linear discriminant analysis. The charge properties of microorganisms in citrate buffer. Numbers of bacteria at OD600=0.01, counted under microscope.

AUTHOR INFORMATION Corresponding Author 24


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*E-mail: [email protected] (Y.-L. Yu) Tel: +86 24 83688944; Fax: +86 24 83676698 †Jian-Yu Yang and Ting Yang have equally contributed to this work. Notes The authors declare no competing financial interest.

ACKNOWLEDGEMENTS Financial support from the National Natural Science Foundation of China (21874014, 21727811, 21675019, 21874017, 21605161), the Fundamental Research Funds for the Central Universities (N170504017) are highly appreciated. Thanks to Prof. Da-Ke. Xu for providing the strains. Thanks to Dr. En-Ze Zhou for his guidance on the bacterial culture technology.

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A Novel Three-Dimensional Nanosensing Array for the Discrimination

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