Statistical Correlation Between SERS Intensity and Nanoparticle

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Statistical Correlation Between SERS Intensity and Nanoparticle Cluster Size Conor P. Shaw, Meikun Fan, Chelsey Lane, Garrett Barry, Andrew I. Jirasek, and Alexandre G. Brolo J. Phys. Chem. C, Just Accepted Manuscript • DOI: 10.1021/jp404250q • Publication Date (Web): 23 Jul 2013 Downloaded from http://pubs.acs.org on July 31, 2013

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The Journal of Physical Chemistry

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Statistical Correlation between SERS Intensity and 17

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Nanoparticle Cluster Size 20 21 2 23 24

Conor P. Shaw1, Meikun Fan2,3, Chelsey Lane2, Garrett Barry2, Andrew I. Jirasek1* and 26

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Alexandre G. Brolo2* 28 29 30

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Department of Physics and Astronomy, University of Victoria,

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Victoria, B.C., Canada V8P 5C2 35 36 37

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Department of Chemistry, University of Victoria, P.O. Box 3065,

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Victoria, B.C., Canada V8W 3V6 41 42 4

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Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University,

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610031, China 47 48 49 50 51 52 54

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Corresponding authors: [email protected] (Phone: 250 7217704) and [email protected] (Phone: 1 5 56

250 721 7167) 57 58 59 60 ACS Paragon Plus Environment

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Abstract. Surface enhanced Raman scattering (SERS) mapping of biomarkers has shown great 5

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promise in determining the distribution of proteins of interest in cells and tissues. Metallic 6 7

nanoparticle (NP) probes are generally used in such mapping. Since SERS intensities from NPs 10

9

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are dependent on size shape and interparticle distance/distribution, it is unclear if this method can 12

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provide reliable biomarker quantification. To address this problem, we investigated a statistical 13 14

approach to the quantification of SERS from SERS probe clusters. The investigation began by 17

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considering multiple biotinylated surfaces that had been exposed to pegylated NPs (designed for 19

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biological SERS mapping) functionalized with streptavidin (defined as SERS probes). The 20 21

surfaces were imaged with a scanning electron microscope (SEM) and SERS-mapped with a 24

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Raman microscope. Statistical distributions of the SERS probes clusters and mapped SERS 26

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intensities on the surfaces were developed. It was found that there was a smooth polynomial 27 28

relationship between SERS intensity and probe cluster size. Our result is in contrast to the sharp, 31

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highly variable intensity increases observed in studies of unmodified NPs. 3

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Based on the

polynomial relationship found, it is clear that pegylated NP SERS probes might be useful for 34 36

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quantification in the SERS mapping of biological material, as the SERS intensity can be 38

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potentially related back to the number of probes at the acquisition point. 39 40 42

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Keywords: plasmonics, hotspots, gold nanoparticles, SERS, SERS probes. 43 4 45 46 47 48 49 50 51 52 53 54 5 56 57 58 59 60 ACS Paragon Plus Environment

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Introduction 4 5

Surface enhanced Raman scattering (SERS) has proven to be a very useful technique in the 6 7

field of cellular imaging and bioanalytics due to its ability to detect low-level concentrations of 8 10

9

molecules with a high degree of specificity 1-12. SERS-based immunoassays have been used for 12

1

the detection of biomarkers in samples such as cells 14

13

29

17

16

15

13-20

, tissue 21-23 and human blood serum

24-

. Metallic nano-particles (NPs; typically silver or gold) are the SERS-enabling platform in

those assays. Typically, the NPs are coated with a Raman reporter molecule and functionalized 19

18

with an antibody for a particular biomarker of interest to impart selectivity to the assays 21

20

23,28

2 24

23

14,16,21-

. The NP-reporter-antibody platforms used in these types of applications are known as “SERS

probes”. In order to be comparable to more traditional immunoassay techniques, such as the 26

25

enzyme-linked immunosorbent assay (ELISA), quantification of the detected biomolecules is 27 28

necessary, and has been attempted in SERS with promising results in many cases 31

30

29

16,26,28-48

3

32

1,5,6,8,11,14-

. However, a well-known difficulty with SERS is the highly variable signal intensity,

due to its dependence on the structure of the SERS-active substrate 45,47,49-60. In the case of metal 34 35

nanoparticles, the size, shape, and inter-particle distance at the probed area all have a strong 38

37

36

influence on the observed SERS intensity 45,51-53,56. 40

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While modern techniques allow for a great degree of control over the size and shape of NPs 41 42 55,59

45

4

43

, the random degree of aggregation of SERS probes during an assay can potentially lead to

wild variations in SERS signal. If the SERS probes are introduced to a sample that is in solution 47

46

and assumed to have a relatively uniform target molecule (analyte) concentration, the variations 48 50

49

in measured SERS intensity can be addressed by simply performing spectral averaging 52

51

throughout the sample 8,14,22,28,30,32,34-37,39. Normalization using an internal standard to correct for 54

53

changes in the sample properties, SERS substrate, or laser beam intensity during the acquisition 5 56

period is also used for quantification 26,29,33,41. 58

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However, signal averaging might not be appropriate in attempts to use SERS probes to map an 5

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analyte that is non-uniformly distributed over a surface, as in the case of a planar assay platform 6 7

or in the in vitro detection of cell membrane proteins. When mapping a surface, the SERS 8 10

9

intensity at each acquisition point depends on the number of NPs at that point and how they are 12

1

grouped (aggregated) relative to each other. In order to quantify the analyte at a given point in a 13 14

sample, the measured SERS spectrum has to be related back to the number of SERS probes at the 17

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measurement point. It is then possible to determine the amount of analyte, assuming a linear 19

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relationship between the number of target molecules and the number of adsorbed SERS probes. 20 21

However, determining the number of NPs that resulted in a particular SERS intensity is not 24

23

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straightforward and requires a specific understanding of the variability in SERS efficiency 26

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provided by differing groupings of clusters. 27 28

The variation in SERS intensity with NP aggregation is well known, and previous studies have 31

30

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monitored changes in intensity caused by the chemically induced aggregation of nanorods 3

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aggregation due to the deposition of multiple NP monolayers 34

62-64

61

and

. In general, it was found that

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an increase in particle aggregation leads to an increase in the average SERS intensity. A few 38

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groups have studied the SERS enhancement provided by individual NP clusters of varying size 40

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51-53,57

41

. For instance, Wustholz et al. 53 achieved a degree of control over the NP aggregations by

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42

using field flow fractionation 45

4

65

and stabilized the resulting clusters by individually encasing

them in SiO2 shells. After identifying individual clusters with transmission electron microscopy 47

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(TEM) and acquiring SERS and localized surface plasmon resonance (LSPR) measurements, 48 50

49

they discovered that there is not necessarily an increase in SERS enhancement with the cluster 52

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size 53. The results showed that a NP dimer can provide SERS intensities as high as that of a NP 54

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heptamer, with the enhancement much more dependent on the size of the inter-particle gap. 5 57

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Crevices formed in the junction between adjacent NPs act as “hot spots” dominating the overall 58 59 60 ACS Paragon Plus Environment

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enhancement provided by the cluster, and can result in signal over 108 times larger than that of 5

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normal Raman scattering. 6 7

In practice, the strong dependence on the inter-particle gap can be very problematic when 8 10

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attempting to quantify the results of SERS mapping. However, a popular type of NP probe 12

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typically used in SERS imaging of cells and tissues has a NP core protected by a coating of 14

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polyethylene glycol (PEG)17, which should control the gap distance between the Au-NP cores 17

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upon aggregation, leading to smaller variations in SERS intensities. The potential of these SERS 19

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probes to reduce SERS intensity variation warrants further investigation. Furthermore, despite 20 21

the success of Wustholz et al. 24

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2

53

in isolating and analyzing a variety of NP aggregates, their

sample size of 89 individual nanoclusters represents only a small fraction of the NP cluster sizes 26

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that could be encountered in, for instance, a cell imaging experiment. 27

In order to more

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completely characterize the relationship between SERS intensity and NP cluster size, we have 31

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developed a statistical approach that enables sampling of thousands of NP aggregates. Also, this 3

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approach helps to mitigate the time consuming efforts of attempting to obtain images of the 34 35

probe clusters (taken via scanning electron microscope (SEM) 38

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(AFM) 40

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, or TEM

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20

, atomic force microscopy

) and SERS data from the exact same regions of the sample. Through the

analysis of SEM images and SERS maps acquired from randomly chosen regions of a gold 41 43

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surface coated with SERS probe clusters of varying size, a relationship between SERS intensity 45

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and cluster size is determined. 47

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By implementing this statistical approach, a large sample size is achieved with as many as 48 50

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20000 SERS intensities and 1500 individual clusters included in the analysis for a single 52

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incubation time, and four different NP incubation times considered in all. Furthermore, the use 54

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of pegylated SERS probes, instead of uncoated Au NPs, provides information on how SERS 5 57

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intensity varies for probes that are specifically designed for target applications involving SERS 58 59 60 ACS Paragon Plus Environment

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imaging of biological cells. As a result, analysis of the SERS intensities of clusters formed by 5

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these SERS probes will provide information that could be directly applicable in vitro, allowing, 7

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for example, the identification and quantification of protein cancer-markers within cells17. 8 10

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Experimental Methods 12

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Chemicals. 13

Ultrapure water (UP-H2O) was used throughout the experiment (Barnstead

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Nanopure ultrapure water purification system, 18.2 MOhm-cm resistivity; Thermo Scientific, 17

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Ottawa, Ontario, Canada). Gold (III) chloride trihydrate (HAuCl4*3H20; ≥ 99.9+% trace metals 19

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basis), sodium citrate dehydrate (≥ 99%, FG), sodium azide (ReagentPlus®, ≥ 99.5%), Nile Blue 20 21

A perchlorate (dye content 95%), streptavidin (essentially salt-free, lyophilized powder, ≥ 13 24

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units/mg protein), bovine serum albumin (BSA; ≥ 98% (agarose gel electrophoresis), lyophilized 26

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powder), Polysorbat 20 (Tween®20) and acetone (ACS reagent, ≥ 99.5%) were purchased from 27 28

Sigma Aldrich (Saint Louis, MO, USA). Polyethylene glycols (PEG) were obtained from Rapp 31

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Polymere (Tuebingen, Germany; HS-PEG-COOH, Molecular Weight: 3000 Da) and Jenkem 3

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Technology (Allen, Texas, USA; Methoxy PEG-Thiol, Molecular Weight: 5000 Da). Ethyl 34 36

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dimethylaminopropyl carbodiimide (EDC) and sulfo-N-Hydroxysuccinimide (sulfo-NHS) were 38

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purchased from ProteoChem (Cheyenne, Wyoming, USA). 40

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Anhydrous ethyl alcohol was

purchased from Commercial Alcohols (Brampton, Ontario, Canada); HPLC grade methanol from 41 43

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Caledon Laboratory Chemicals (Caledon Laboratories Ltd., Georgetown (Halton Hills), Ontario, 45

4

Canada). 47

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Biotinylated tri(ethylene glycol) undecane thiol was purchased from Whitesides

Monothiol (Nanoscience Instruments, Inc., Phoenix, AZ, USA). 48 50

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Synthesis of Au NPs. Colloidal gold nanoparticles were synthesized by the reduction of 52

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HAuCl4 with sodium citrate in a glass beaker62,66-68. To begin, 1 mL of a 1% solution of 53 54

HAuCl4*3H20 was added to 99mL of ultrapure water (UP-H2O), and the resulting solution was 5 57

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brought to a boil while stirring. Once boiling, 1mL of a 1% trisodium citrate dihydrate solution 58 59 60 ACS Paragon Plus Environment

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was added dropwise to the mixture. After boiling for another 5 minutes, the heat was turned off, 5

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and 1mL of a 5% sodium azide solution was added dropwise to the beaker. The mixture 6 7

continued to stir as it was allowed to cool for about half an hour, after which point it could be 8 10

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stored in the refrigerator. 12

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Preparation of SERS Probes. SERS probes were produced by modifying the NPs of the 13 14

preceding section according to an amended version of the method described by Qian et al. 17

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17

.

The nanoparticles were first coated with NBA dye, followed by a PEG shell to which a targeting 19

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molecule was attached (see the schematic in figure 1(a)). The PEG coating acts to reduce the 20 21

non-specific binding of the SERS probes to sites other than the target. 24

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To begin, 250-300μL of a 5μM NBA solution was slowly added, dropwise, to 2mL of a 26

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vigorously stirring NP suspension. The dye was allowed to mix with the NPs for 15 minutes, 27 28

after which time 320μL of a mixed PEG solution was added to the rapidly stirring mixture. The 31

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mixed PEG solution was comprised of 0.5mL of a 200μM solution of HS-PEG-COOH (MW: 3

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3000 Da) and 0.25mL of a 200μM methoxyl PEG-Thiol solution (PEG-SH, MW: 5000 Da), 34 36

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diluted to 1mL with UP-H2O. The heterofunctional linker HS-PEG-COOH was included to 38

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attach to the streptavidin (targeting molecule), while the PEG-SH was to coat any areas of the 40

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gold NPs not covered by the linker. 41 43

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After stirring for 20 minutes, the NP/NBA/PEG suspension was centrifuged twice at 13000 45

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rpm for 7 minutes each time, and resuspended in 2mL UP-H2O. To activate the COOH groups 47

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on the NP surfaces, 40μL of a 20mg/mL solution of EDC was added, rapidly followed by 40μL 48 50

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of a 55mg/mL solution of sulfo-NHS. Following 40 minutes of stirring, 0.5 mL of a PBS buffer 52

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containing 1% Tween®20 (PBST) was added to the NP mixture to improve its solubility, and the 54

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suspension was stirred for a further 5 minutes. Excess reagent was then removed by two rounds 5 57

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of centrifugation (13000rpm for 7 minutes) and resuspension in 2mL PBST. At this point, 58 59 60 ACS Paragon Plus Environment

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140μL of a 0.5mg/mL streptavidin solution was added to the nanoparticle suspension, resulting 5

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in a protein concentration of approximately 35μg/mL. The mixture was left to react overnight in 7

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the refrigerator at 4oC. 8 10

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After 24 hours, 0.5mL of PBST was added to the suspension before centrifuging (13000 rpm 12

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for 7 minutes) and re-suspending in 2mL of a PBS buffer with 0.1% Tween®20 and 100μg/mL of 13 14

BSA. The purpose of the BSA was to cap any unreacted activated COOH groups. After reacting 17

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for 20 minutes, the solution was centrifuged once more and resuspended in 2mL of PBST. 19

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Characterization of the SERS probes. Particle characterization is vital to guarantee that 20 21

samples from different batches used in the experiments had comparable physical and chemical 24

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properties. In fact, several characterization techniques must be employed in this type of research 26

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to also assure that enough information about the samples are available for eventual assessment of 27 28

the results by other laboratories. The SERS probes were characterized at diverse stages during 31

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the synthesis by dynamic light scattering (DLS), ultraviolet/visible (UV/Vis) and surface 3

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enhanced Raman spectroscopy (SERS). These measurements were performed at four stages 34 36

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during the probe production – on unmodified Au NPs; NPs after the addition of NBA and PEG; 38

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NPs with NBA/PEG/streptavidin; NPs with NBA/PEG/streptavidin/BSA. 40

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Results of the

characterization process are available as supporting information. 41 43

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Particle diameter was measured by DLS using a 90Plus Particle Size Analyzer (Brookhaven 45

4

Instruments Corporation, Holtsville, New York). The DLS technique yields the hydrodynamic 47

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diameter, which included contributions from molecules attached to the NP surface, so it was 48 50

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possible to observe increases in the effective probe diameter as the NBA, PEG and BSA were 52

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attached to the NP core. 54

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The stability of the NPs during synthesis was monitored by UV/Vis spectroscopy, performed 5 57

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on the probe sample at each stage, using a Varian Cary 50 Scan Spectrophotometer (Agilent 58 59 60 ACS Paragon Plus Environment

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Technologies Canada Inc., Mississauga, Ontario). Unmodified NPs exhibited a characteristic 5

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spectral peak at approximately 530 nm. The probes were discarded at any stage if the 530 nm 6 7

peak presented large red-shifts or broadening, since these are indicative of particle aggregation. 8 10

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SERS of the probe suspension was carried out in all stages after the addition of the NBA to 12

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ensure that the spectral characteristics of the dye, including a strong peak at 600cm-1, were 13 14

always present. 17

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Raman spectroscopy was performed using an InVia Renishaw microscope

(Renishaw Inc., Hoffman Estates, IL) with a 5x dry objective (Leica Microsystems, Wetzlar, 19

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Germany) and 1200 lines/mm diffraction grating. A 633nm Helium Neon Laser (Renishaw plc, 20 21

Transducer Systems Division, Gloucestershire, UK)) was used for sample excitation, and was 24

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focused on a drop of the SERS probe suspension centred on a glass slide. Spectra were acquired 26

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with a 5s exposure and a laser power of ~1 mW at the sample. Laser power through the objective 27 28

was measured using a Coherent FieldMax-TOP Laser Power/Energy Meter (Coherent Inc., 31

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Portland, Oregon, USA). 3

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Biotinylation of Gold Slides and SERS Probe Incubation. Glass slides coated with 100 nm 34 36

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gold films through a 5nm chromium (Cr) adhesion layer (EMF Corporation, Ithaca, New York, 38

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USA) were chemically modified with biotin in order to provide a surface to which the 40

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streptavidin-modified SERS probes could attach. Each slide was first annealed, thoroughly 41 43

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rinsed with acetone and ethanol, and placed in a clean 50mL glass beaker. A 1mM solution of 45

4

biotinylated tri(ethylene glycol) undecane thiol was then prepared in 2mL of ethanol and added to 47

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the beaker. The beaker was sealed with Parafilm® M (Bemis Company, Inc., Neenah, Wisconsin, 48 50

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USA) as a monolayer self-assembled on the Au surface for 12 hours. 52

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The slide was then removed from the biotin solution, rinsed thoroughly with ethanol and UP54

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H2O, and placed in a sealed beaker containing the SERS probe suspension for either 1, 2, 3, or 12 5 56 57 58 59 60 ACS Paragon Plus Environment

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hours. After the incubation, the surface was washed thoroughly with PBST and UP-H20 before 5

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being left to air-dry. 6 7

SERS Mapping and SEM Imaging 8 9 10

SERS Microscopy. Raman spectroscopy was performed with the InVia Renishaw microscope 12

1

using a 100x dry objective (N.A. = 0.9) (Leica Microsystems, Wetzlar, Germany), 1200 lines/mm 13 14

diffraction grating, and 633nm Helium Neon Laser. Maps of three randomly chosen regions 17

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were acquired on the gold slide corresponding to each SERS probe incubation time. To ensure 19

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rapid scanning without compromising signal-to-noise ratio, StreamlineTM Plus Raman imaging 20 21

(Renishaw Inc., Hoffman Estates, IL) was used. The resolution of the maps was 1μm x 0.5μm, 24

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2

with each point exposed to ~1 mW of laser power for 3 seconds. Each map covered an area of 26

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about 4000μm2 and took approximately 15 minutes to complete. Two-dimensional SERS map 27 28

data was presented with each pixel corresponding to the area under the NBA dye peak at 600 cm31

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1

3

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. The three SERS maps for each slide were also combined and presented as a histogram of

SERS intensity. In these histograms, SERS intensity refers to the area of the NBA dye peak at 34 35

600 cm-1. 38

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SEM Imaging. A Hitachi S-4800 field emission scanning election microscope (FESEM; 40

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Hitachi High-Technologies Canada, Inc., Toronto, Ontario) was used to acquire high resolution, 41 43

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high magnification images of the SERS probes on the surface of the gold slides. All images were 45

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obtained using an acceleration voltage of 1.0kV and a magnification of 20 000 x, covering an 47

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area of about 30 μm2. A sampling of images of the SERS probes was acquired on the slide 48 50

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corresponding to each incubation time. At least 5 images were taken of each slide, with any 52

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differences in the imaged area of the slides accounted for in the analysis. 53 54 5 56 57 58 59 60 ACS Paragon Plus Environment

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Data Analysis and Statistical Approach 5

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An overview of the statistical approach is provided in Figure 1. A detailed description of each 7

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step is provided as supporting information. The SERS probes were pegylated gold NPs 17, coated 8 10

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with SERS-active NBA dye, and functionalized with streptavidin in order to target a biotin 12

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monolayer deposited on a gold slide (figure 1(a)). Several different incubation times were used 13 14

to allow for the production of SERS probe clusters of a great variety of sizes, from single probes 17

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to clusters as large as 15 probes or more. The clusters were identified and categorized through 19

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the analysis of SEM images and the SERS intensities were determined from two-dimensional 20 21

SERS maps of multiple regions on the slide (figure 1(b)). Previous investigations in the 24

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correlation between SERS intensities and NP cluster sizes relied on using the same region for 26

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imaging (AFM52, TEM53, or SEM20) and SERS and a direct, individualized, comparison between 27 28

SERS intensities and cluster sizes. In contrast, we developed an approach where the correlation 31

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between the SERS intensity mappings and the SEM images was based on the distributions of 3

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SERS intensities under each laser illuminated spot and the distribution of SERS probe cluster 34 35

sizes under a similar area. Representative histograms of the SERS probe cluster size and SERS 38

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intensity for a given incubation time were generated (figure 1(c)), and the two distributions were 40

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related through a series of equations describing the total SERS intensity acquired at a given point 41 43

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(figure 1(d)). Solutions of the empirical formulae provided a relationship between NP cluster 45

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size and the average SERS intensity resulting when the cluster was probed with the Raman 47

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microscope (figure 1(e)). 48 49 50 51 52 53 54 5 56 57 58 59 60 ACS Paragon Plus Environment

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Figure 1: Process outline showing the (a) SERS probes bound to the surface and a schematic of 35

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the SERS probes; (b) SEM and SERS data acquisition (M1 = Map 1, etc.); (c) statistical 37

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distributions generated from the SERS and SEM data; (d) general equation for the total SERS 38 39

intensity, generated using the distributions from (c); (e) relationship between SERS intensity and 42

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SERS probe cluster size. 43 45

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Results 46 47

SERS Mapping and histograms. Figure 2 shows the SERS mapping of the gold slides coated 50

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with SERS probes for 4 different incubations times (1-12hrs). The SERS probes (illustrated in 52

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Figure 1(a)) included streptavidin proteins that specifically attached to the gold surface decorated 53 54

with biotin. The SERS mapping at low incubation times (Figure 2(a)) shows a large spatial 57

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variation in SERS intensities, due to the sparse coverage of the gold surface by SERS probes. 58 59 60 ACS Paragon Plus Environment

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The intensity maps become more uniform as the incubation time increases (Fig. 2(b) – 2(d)). In 5

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those cases, the overall SERS probe surface coverage increases, as does the number of particles 6 7

illuminated in each mapped spot. These observations are corroborated in Figure 3, where the 8 10

9

distributions of SERS intensities corresponding to each incubation time are represented as 12

1

histograms. Each count in the histogram corresponds to the SERS intensity (integrated SERS 13 14

peak) obtained under a laser-illuminated area during mapping. The histograms were generated 17

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by combining the data from 3 large area (76 x 53 m2) maps obtained from random positions in 19

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every slide, leading to a large sample size of SERS intensities. Zero intensity events (defined by a 20 2

21

cutoff) were discarded in the construction of the histograms; hence, the sample sizes varied from 24

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approx. 7000 for the 1hr data to over 23000 for the 12 hour data. Following a common treatment 26

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of error on histograms, the measured number of counts in each bin (Nbin) is assumed to be the 27 28

mean of a Poisson distribution, with the error bars corresponding to +/- Nbin1/2 (1σ) 69,70. 31

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The results for the shortest incubation time (Fig. 3(a)) show a tailed distribution, with a 32 3

skewness of 10.1 (skewness values can provide a quantitative assessment regarding the symmetry 34 36

35

of the distribution 38

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71

), and a high number of low intensity events. These correspond to

illuminated areas that contained low efficiency probes that produced Raman signal near the 39 40

detection limit of the system. Even at this low coverage regime, however, a small number of 43

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events presented a relative high SERS intensity (~1000 counts). The distribution clearly spread to 45

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higher intensities as the incubation time increased (Fig. 3(b)) and the number of regions with low 46 47

SERS intensity decreased. When the incubation time reached 3 hours (Fig. 3(c)), the number of 50

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low signal events became small and a peak clearly develops in the distribution. This result is 52

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consistent with a larger coverage and a higher probability of SERS probes being found under 53 54

each laser illuminated area during mapping. Finally, in Figure 3(d), the least skewed distribution, 57

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a peak forms at higher intensities than in figure 3(c). The distribution in figure 3(d) can be said 58 59 60 ACS Paragon Plus Environment

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to be more symmetric than the others (figures 3(a)-(c)), based on its low skewness value, 5

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appearing almost Gaussian in shape 71. This result is consistent with a higher surface coverage of 6 7

SERS probes and, consequently, a larger probability of several NPs being interrogated by the 8 10

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laser in each particular mapped spot. 1 12 13 14 15 16 17 18 19 20 21 2 23 24

20 m

20 m

20 m

20 m

25 26 27 28 29 30 31 32 3 34 35 36 37 38 39 41

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Figure 2: SERS map of the gold slide surface after a SERS probe incubation of (a) 1hr; (b) 42 43

2hrs; (c) 3hrs; (d) 12hrs. 4 45 46 47 48 49 50 51 52 53 54 5 56 57 58 59 60 ACS Paragon Plus Environment

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Figure 3: Histogram of integrated SERS peak of Nile Blue-A (~600 cm-1) measured on the slide 31 32

surface incubated with SERS probes for (a) 1hr; (b) 2hrs; (c) 3hrs; (d) 12hrs. Error bars 3 35

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correspond to +/- 1σ (N1/2). 36 38

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SEM Imaging and histograms 40

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Sample SEM images of the gold slide incubated with SERS probes for different times are 41 43

42

shown in figure 4 (SEM images of individual clusters are provided in the supporting 45

4

information). The scale of the images in figure 4 was chosen so as to provide the largest surface 47

46

area possible, displaying a large number of clusters while still allowing for the identification of 48 50

49

individual probes. Single SERS probes were identified and a histogram of their pixel areas 52

51

(using data from all SEM images) was generated and fit with a Gaussian. From the Gaussian, the 53 54

average size of a single SERS probe was obtained, and using this value it was then possible to 5 57

56

produce a histogram, presented in Figure 5, of the SERS probe cluster size distribution for the 58 59 60 ACS Paragon Plus Environment

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slides corresponding to each incubation time. The histograms in Figure 5 were obtained using a 5

4

different number of SEM images for each incubation time. Therefore, the number of clusters 6 7

was normalized using the imaged area. The histograms in Figure 5 clearly show an increase in 8 10

9

the number of SERS probes in the aggregated clusters with the incubation time, although some 12

1

large clusters, with more than 10 SERS probes, were also observed in the 1hr incubation 13 14

experiment. Notice that the number of single particles and small clusters (less than 5 SERS 17

16

15

probes) still dominates the distribution even after 12 hrs. This is a strong indication that the 19

18

PEG-layer efficiently protects the SERS probes against aggregation; meaning that the SERS 20 21

probe adsorption is possibly driven by the specific interaction with the surface, rather than by 24

23

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particle-to-particle attraction. 25 26 27 28 29 30 31 32 3 34 35 36 37 38 39 40 41 42 43 4 45 46 47 48 49 50 51 52 53 54 5 56 57 58 59 60 ACS Paragon Plus Environment

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Figure 4: Sample SEM images of the gold slide surface after SERS probe incubation of (a) 5

4

1hr; (b) 2hrs; (c) 3hrs; (d) 12hrs. 6 7 8 9 10 1 12 13 14 15 16 17 18 19 20 21 2 23 24 25 26 27 28 29 30 31 32 3 34 35

Figure 5: Histogram showing the distribution of cluster sizes (measured in the number of SERS 38

37

36

probes per cluster) for the region of the slide incubated with SERS probes for (a) 1hr; (b) 2hrs; 40

39

(c) 3hrs; (d) 12hrs. The histograms are normalized by the area of the slide imaged with the 41 42

SEM (ASEM). Error bars indicate +/- 1σ ( (1/ASEM) * N1/2 ). 4

43

46

45

Our final goal is to correlate the SERS intensity from each illuminated spot obtained from the 48

47

SERS map histograms (Figure 3) with the number of SERS probe clusters at that spot. In order to 49 50

achieve that, a new set of histograms, shown in Figure 6 were obtained from the SEM images. In 53

52

51

the case of Figure 6, the histograms considered the number of SERS probes clusters illuminated 5

54

per acquisition (i.e., the number of SERS probe clusters in a 1 x 1 m2 SEM imaged area). As 56 57 58 59 60 ACS Paragon Plus Environment

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expected, the histograms in Figure 6 shows that each laser-illuminated area is mostly populated 5

4

with either 0, 1 or 2 SERS probe clusters for the lower incubation time (1 hr). On the other hand, 6 7

most of the mapped SERS intensities were generated by illuminating 2 to 5 SERS probe clusters 8 10

9

when the incubation was 12 hrs. 1 12 13 14 15 16 17 18 19 20 21 2 23 24 25 26 27 28 29 30 31 32 3 34 35 36 37 39

38

Figure 6: 41

40

Histograms showing the distribution of illuminated SERS probe clusters per

acquisition for the data corresponding to the (a) 1hr; (b) 2hr; (c) 3hr; (d) 12hr probe 42 43

incubation times. Error bars correspond to +/- 1σ (N1/2). 45

4

47

46

Finally, by sampling the histogram in Figure 3, a SERS intensity from a random 1 x 1 m2 spot 49

48

is obtained. The probability that the intensity is from a certain number of clusters is generated 50 52

51

from Figure 6 and the possible size of these clusters (number of SERS probes per cluster) is 54

53

revealed by sampling the distribution in Figure 5. Therefore, using the total SERS intensities of 5 56

Figure 3, and the histograms of Figures 5 and 6, a system of equations was then produced 57 58 59 60 ACS Paragon Plus Environment

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corresponding to the relationship between the SERS intensity and the number of clusters. This 5

4

approach allowed the use of thousands of sampled values from all histograms, generating a 6 7

statistically robust result. A more detailed description of this procedure, including examples, is 8 10

9

available as supplementary material. 12

1

Solving systems of equations for the SERS Intensity Ratios. As discussed in the previous 13 14

section, the SERS intensity at each illuminated area was correlated to the number of SERS probe 17

16

15

clusters and their size in that same area. In other words, the total SERS intensity from a 19

18

particular spot was treated as a linear sum of SERS intensity contributions from each cluster. 20 21

The individual intensities from each cluster were unknown. Therefore, for each incubation time, 24

23

2

the process was repeated to generate enough equations that would allow the unknown SERS 26

25

intensities, attributed to each SERS probe cluster size, to be evaluated. The system of equations 27 28

for each SERS data set was then an m x m matrix, with m being the maximum cluster size for a 31

30

29

particular set. Due to the fact that very large SERS probe clusters (> 15 probes) were rarely 3

32

detected, particularly for the shorter probe incubation times (see figure 5), it was decided that the 34 36

35

total SERS intensity distributions could be described by only considering SERS probe clusters up 38

37

to a maximum cutoff value, mmax. For each incubation time, a different value for mmax was 40

39

chosen, based on the cluster size distributions of Figure 5. 41 43

42

Starting with the 1hr incubation time, a value of mmax = 6 was chosen (based on where the 45

4

histogram begins to approach zero in figure 5(a)), and a 6x6 equation matrix was generated. This 47

46

procedure is illustrated in Figure 7. The solutions to the 6x6 matrix provided values for I1 to I6, 48 50

49

corresponding to the contributions to the total SERS intensity from 1 SERS probe (I1) and a 52

51

cluster containing 6 SERS probes (I6), respectively. To account for variability in these solutions, 54

53

500 6x6 equation matrices were generated for the 1hr data set and solved, giving 500 5 57

56

independent sets of solutions (figure 7(b)). All solutions for I1 to I6 were then averaged and the 58 59 60 ACS Paragon Plus Environment

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uncertainties on the mean values were calculated (figure 7(c)). To provide an idea of the 5

4

variability in the values of these intensities, seven independent calculations of I1 to I6 for the 1 hr 6 7

incubation experiment have been overlaid in Figure 8. In Figure 8, the solution for I6 is seen to 10

9

8

have a high uncertainty compared to the first five SERS intensity solutions due to the fact that it 12

1

contains contributions from the relatively small number of NP clusters larger than 6 that form 13 14

after a 1hr incubation. As a result, I6 was recalculated from the equations for the 2hr incubation, 17

16

15

while I1-I5 were treated as known values. 18 19 20 21 2 23 24 25 26 27 28 29 30 31 32 3 34 35 36 37 38 39 40 41 42 43 4 45 46 47 49

48

Figure 7: Chart describing the method used to solve the system of equations for the SERS 50 51

intensities due to each SERS probe cluster size. 53

52 54 5 56 57 58 59 60


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1 2 3 4 5 6 7 8 9 10 1 12 13 14 15 16 17 18 19 20 21 2 23 24 25 26 27 28 29 30 31

Figure 8: Seven independent calculations of the SERS intensities due to the first six cluster 34

3

32

sizes. 35 37

36

For the 2hr incubation, a system of equations was generated with an mmax set to be equal to 9 38 39

(based on figure 5(b)), and, using the intensity solutions for clusters of 1 to 5 SERS probes as 40 42

41

known values, solutions for clusters up to 9 probes large were found (figure 7(d)). The process 4

43

was again repeated 500 times, as discussed in figure 7(e). The 3hr probe incubation data was 45 46

then similarly used to find intensity solutions for clusters up to 12 probes large (this time with I1 49

48

47

to I8 as known values), and the 12hr probe incubation data was used to find solutions for SERS 51

50

intensities produced by clusters up to 15 probes large (with I1 to I11 as known values). The final 52 53

results of the calculations are found in figure 9, where the average SERS intensities normalized 5

54 56 57 58 59 60


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to the intensity due to a single probe (I/I1) are plotted against the number of SERS probes per 5

4

cluster. 6 7 8 9 10 1 12 13 14 15 16 17 18 19 20 21 2 23 24 25 26 27 28 29 30 31 32 3 34 35 36 38

37

Figure 9: SERS intensity ratio solutions due to clusters from 1 to 15 SERS probes in size. The 40

39

data set used to calculate each of the values is indicated. A polynomial fit of the first 14 intensity 41 43

42

ratios is included. 4 46

45

High reproducibility of the calculated SERS intensities of figure 9 is suggested by the strong 48

47

agreement (p < 0.05) between the seven sets of independent calculations of the SERS intensities 49 50

for the first six cluster sizes shown in Figure 8. 53

52

51

Discussion 54 5 56 57 58 59 60 ACS Paragon Plus Environment

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When using NPs as a substrate in SERS, the specific enhancement to the Raman signal of the 5

4

sample provided by the NPs can be highly variable and difficult to control. In general, it is 6 7

known that an irregular surface allows for the greatest enhancement, and that a collection of NPs 8 10

9

provides greater enhancement than a single NP 60. Studies that observe the change in the SERS 12

1

intensity as a function of random NP aggregation have shown an increase in intensity with 13 14

aggregation 17

16

15

61-64

, and the polynomial relationship shown in Figure 9 supports this idea.

However, the gradual increase in SERS intensity with SERS probe cluster size is somewhat 19

18

unexpected considering that studies of multiple depositions of NP monolayers show a more rapid 20 21

increase in average SERS intensity as the number of layers (and thus NP aggregation) increases, 24

23

2

eventually reaching a plateau 62-64. Similarly, studies of individual NP clusters 52,53 found a very 26

25

sharp increase in intensity (as much as 4 orders of magnitude) between single and dimer NPs. 28

27

Although the results recently reported by Pazos-Peres et al57 showed a smaller enhancement of 31

30

29

the dimer relative to the single particle, the importance of inter-particle spacing when it comes to 3

32

SERS enhancement was also evident. However, an increase in the cluster size beyond the dimer 34 35

does not necessarily result in much larger increase in SERS efficienty. In fact, Wustholz et al. 53 38

37

36

suggest that a pair of NPs with a particular spacing can produce a “hot spot” which can 40

39

potentially result in a SERS enhancement as large as that provided by bigger clusters. 41 43

42

The slowly rising curve in Figure 9 seems to suggest that the type of “hot spot” that would 45

4

result in a 4 orders of magnitude increase in SERS intensity between a single and dimer SERS 47

46

probe was not observed in this work, or at least didn’t occur frequently enough to influence the 48 50

49

average SERS intensities for each cluster size. Likely, this is due to the fact that the distance 52

51

between the Au-NP cores of the SERS probes used to generate Figure 9 was controlled by the 54

53

PEG coating. The pegylation of the Au-NPs and their functionalization with streptavidin to form 5 57

56

the SERS probes provided a relatively “thick” coating that limited the distance of closest 58 59 60 ACS Paragon Plus Environment

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approach between the Au-NP cores which was not present on the Au-NPs used in the work of 5

4

Wustholz et al53. Due to this fundamental difference, we cannot expect that our work will 7

6

compare directly with that of Wustholz et al53. However, the systematic attempt to correlate 8 10

9

SERS intensities to NPs cluster sizes performed by Wustholz et al53 does mirror the study 12

1

described here. In our case, the molecular coating provided by the PEG seems to have prevented 13 14

the conditions necessary for the formation of the type of “hot-spots” formed in between the NPs 17

16

15

that provided such significant rises in SERS intensity53,57 , and likely had an effect on the rapid 19

18

increase in SERS intensity found in the studies of multiple depositions of NP monolayers62-64 and 21

20

of nanorod aggregation61. Indeed, in high magnification SEM images of clusters of the SERS 24

23

2

probes (as can be seen in the supplementary information), there is a clear separation of 10-20 nm 26

25

between many of the probes within the clusters. It is possible that the separation between the 27 28

NPs in the SERS probe clusters causes the probes to provide surface-enhancement somewhat 31

30

29

independently of each other, and the intensity due to a cluster is the cumulative result of the 3

32

intensity due to each probe in the cluster. However, this would suggest a linear relationship, 34 35

which is not what is seen in Figure 9. While the exact reason for the non-linear nature of the 38

37

36

relationship in Figure 9 is unclear, it does imply that there may be some degree of “hot-spot” 40

39

interaction between the probes in the cluster. Similarly, it is possible that the SERS intensity 41 43

42

produced by the clusters is affected by a relationship between the gold slide surface and the 45

4

SERS probes, whether that be due to a “hot-spot” interaction, or simply reflection of Raman 47

46

scattered photons towards the objective that would otherwise have been lost. Nonetheless, the 48 50

49

polynomial relationship between SERS probe clusters and their resultant SERS intensity is 52

51

extremely well defined (R2 = 0.99812) and reproducible (see Figure 8), and a non-linear 54

53

component to the relationship is entirely possible. 5 56 57 58 59 60 ACS Paragon Plus Environment

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Given confidence in the reproducibility and accuracy of the results shown in Figure 9, the 5

4

polynomial relationship that the figure displays will prove to be useful in experiments that use 6 7

PEG NPs as SERS probes. The exhibited relationship between cluster size and the resultant 8 10

9

SERS intensity is unique to the PEG NP probes described in this work, and these probes, based 12

1

on those in the paper by Qian et al. 17 are specifically designed for targeted SERS imaging, such 13 14

as in the identification of proteins within cells and tissues. As discussed in the introduction, 17

16

15

determining the quantity and distribution of the target within the SERS maps of a sample remains 19

18

challenging. 20

However, considering the simple relationship between cluster size and SERS

21

intensity shown in Figure 9, PEG NP SERS probes seem ideally suited for quantifiable SERS 24

23

2

mapping. For example, using a calibration curve similar to Figure 9, the SERS intensity at a 26

25

given point would be known to be a multiple of the intensity due to an individual SERS probe. It 27 28

would then be simple to determine the number of clusters contributing to the total SERS intensity 31

30

29

at the given point and thus the number of targeted sites could be determined at that location. 3

32

Conclusion 34 35

This work provides a novel technique that relates 2D SERS intensity maps to SEM images of 38

37

36

NP probes on a biotinylated gold surface, allowing for the calculation of SERS intensities due to 40

39

NP probe clusters of varying size. In order to examine a variety of cluster sizes, targeted NP 41 43

42

probes were incubated with biotinylated surfaces for several time periods prior to the acquisition 45

4

of SEM and SERS images. Using the SEM images and SERS maps, statistical descriptions of 47

46

both the SERS probe cluster distribution and SERS intensities on the surface were developed. 48 50

49

Based on the statistical relationships, systems of equations for the total SERS intensity measured 52

51

at a given point were devised. Solutions to the equations provided the SERS intensities resulting 54

53

from enhancement due to clusters from 1 to 14 SERS probes in size. 5 56 57 58 59 60 ACS Paragon Plus Environment

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A simple polynomial relationship between SERS probe cluster size and resultant SERS 5

4

intensity was found, suggesting the utility of pegylated SERS probes in targeted SERS mapping. 6 7

By simply controlling the probe incubation time to limit the distribution of cluster sizes formed 8 10

9

in a targeted SERS sample, quantification of targeted sites within a sample would be relatively 12

1

straightforward. The ability to quantify targeted sites in a sample would make targeted SERS 13 14

mapping a viable technique for imaging protein distribution within cells and tissues, providing a 17

16

15

quantifiable, high-resolution alternative to methods such as immunohistochemistry. 18 19 20 21

AUTHOR INFORMATION 24

23

2

Corresponding Author 26

25

* [email protected] (Phone: 250 721 7704) and [email protected] (Phone: 1 250 721 7167) 27 28 30

29

ACKNOWLEDGMENT 31 3

32

This work was supported by the Canadian Foundation for Innovation, the British Columbia 35

34

Knowledge Development Fund and the Western Economic Diversification Fund. The authors 36 38

37

wish to thank Dr. Elaine Humphrey and Adam Schuetze for their assistance with the SEM 40

39

imaging, Dr. Quinn Matthews and Samantha Harder for the laser power measurements. 41 43

42

SUPPORTING INFORMATION AVAILABLE 45

4

Information regarding the characterization of the SERS probes; high magnification SEM images 46 48

47

of individual probe clusters; a detailed description of the data analysis. This material is available 50

49

free of charge via the Internet at http://pubs.acs.org. 51 53

52

REFERENCES 54 5 56 57 58 59 60 ACS Paragon Plus Environment

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Table of Contents Graphic (Small Size: 2in x 1.5in) 4 5 6 7 8 9 10 1 12 13 14 15 16 17 18 19 20 21 2 23 24 25 26 27 28 29 30 31 32 3 34 35 36 38

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Table of Contents Graphic (Full Size: 7in x 5.25in) 39 40 41 42 43 4 45 46 47 48 49 50 51 52 53 54 5 56 57 58 59 60 ACS Paragon Plus Environment

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Statistical Correlation Between SERS Intensity and Nanoparticle

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