Beta-Hemolytic Bacteria Selectively Trigger Liposome Lysis, Enabling

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Beta-Hemolytic Bacteria Selectively Trigger Liposome Lysis, Enabling Rapid and Accurate Pathogen Detection Rongji Sum,† Muthukaruppan Swaminathan,†,‡ Sahil Kumar Rastogi,†,# Obdulio Piloto,§ and Ian Cheong*,†,‡ †

Department of Molecular Pathogenesis, Temasek Life Sciences Laboratory, Singapore 117604, Singapore Department of Biological Sciences, National University of Singapore, Singapore 117558, Singapore § Protean Labs LLC, Medley, Florida 33166, United States ‡

S Supporting Information *

ABSTRACT: For more than a century, blood agar plates have been the only test for beta-hemolysis. Although blood agar cultures are highly predictive for bacterial pathogens, they are too slow to yield actionable information. Here, we show that beta-hemolytic pathogens are able to lyse and release fluorophores encapsulated in sterically stabilized liposomes whereas alpha and gamma-hemolytic bacteria have no effect. By analyzing fluorescence kinetics, beta-hemolytic colonies cultured on agar could be distinguished in real time with 100% accuracy within 6 h. Additionally, end point analysis based on fluorescence intensity and machine-extracted textural features could discriminate between beta-hemolytic and cocultured control colonies with 99% accuracy. In broth cultures, betahemolytic bacteria were detectable in under an hour while control bacteria remained negative even the next day. This strategy, called beta-hemolysis triggered-release assay (BETA) has the potential to enable the same-day detection of beta-hemolysis with single-cell sensitivity and high accuracy. KEYWORDS: hemolysis, sensor, liposome, blood agar, erythrocyte, bacteria, pathogen, image analysis

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eta-hemolytic bacteria are pathogens as a general rule.1−4 Indeed, it is rare to find nonpathogenic bacteria which are also beta-hemolytic, and hence, beta-hemolysis is a highly predictive indication that a bacterium is pathogenic. Despite enormous progress in microbial diagnostics,5,6 the blood agar plate, invented in 1903, is still the only means for detecting beta-hemolysis. Regrettably, however, blood agar cultures take far too long to be relevant in most situations. In short, the diagnostic value of blood agar is defeated by the lateness of its results. Two examples illustrate this problem. Only a minority of pediatric pharyngitis episodes are caused by bacteria, with Group A Streptococci being the common culprit.7 Throat cultures on blood agar are the gold standard assay for making this diagnosis but results are not timely enough for antibiotic treatment decisions. Hence, they are only used to confirm a negative rapid antigen detection test.8,9 Similarly, a same-day test for beta-hemolysis is currently unavailable for food safety monitoring. If it existed, it would allow food microbiologists to quickly exclude the three foodborne pathogens with the highest estimated death rates: Listeria monocytogenes (15.9%), Vibrio vulnificus (34.8%), and Clostridium botulinum (17.3%).10 Listeria alone is responsible for ∼30% of foodborne pathogen-related deaths in the United States. As a bonus, such a test would also © XXXX American Chemical Society

detect other beta-hemolytic foodborne pathogens including Bacillus cereus, Clostridium perfringens, Staphylococcus aureus, Vibrio cholera, and Vibrio parahemolyticus. As one might expect, tests do exist for the detection of particular beta-hemolytic species. However, these approaches are commonly based on the detection of genetic or antigenic determinants and not beta-hemolysis. Examples include the antibody−antigen tests,11−13 nucleic acid-based assays,14−16 and more recent approaches using bacteriophages engineered with reporters.17−19 These methods require a priori information about the pathogen and are hence useful only insofar as one has a specific hypothesis of what pathogen to test for. Further, most of these assays require enrichment to achieve sufficient sensitivity for low numbers of target pathogens. The limitations described here emphasize the need for a broad assay that will not only detect beta-hemolysis but also outperform blood agar in speed and scalability while retaining the advantages of culture-based methods. In this work, we describe an assay based on the principle that it is easier for bacterial cells to trigger the release of fluorescent molecules Received: May 19, 2017 Accepted: September 1, 2017

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Figure 1. Beta-hemolytic colonies are accurately differentiated by BETA. The following abbreviations for bacteria are used. BC: Bacillus cereus, SPY: Streptococcus pyogenes, SA: Staphylococcus aureus, CP: Clostridium perfringens, LM: Listeria monocytogenes, SPN: Streptococcus pneumoniae, SS: Streptococcus salivarius, SO: Streptococcus oralis, SE: Staphylococcus epidermidis, LL: Lactococcus lactis, EC: Escherichia coli. β+ and β- refer to beta and non-beta-hemolytic bacteria, respectively. (A) Fluorescent and bright-field images of bacterial colonies in BHI agar with L-Hoechst. Scale bar, 50 μm. (B) Reported colony fluorescence values are normalized to background fluorescence. The dashed line is a visual aid to highlight the separation between β+ and β-. (C) Normalized fluorescence of colonies in an overnight time lapse experiment. (D) Beta and non-beta-hemolytic bacteria can be linearly separated by the intensity (Colony Fluorescence) and texture (Average Dissimilarity) of L-Hoechst staining using SVM as the classifier. Data represents the means ± s.d. *** P < 0.0001. Sciences Laboratory Institutional Biosafety Committee (Reference# IBC-050413-15-IC). Bacterial strains obtained from the above sources were streaked on sheep blood agar and incubated at 37 °C overnight to check for hemolytic activity. Single colonies were then inoculated into 3 mL of sterile BHI (BD Bacto) and incubated at 37 °C without shaking overnight. The overnight cultures were further diluted 1:100 into 5 mL of fresh BHI media and allowed to grow to an OD600 of 0.35−0.6. These early exponential phase cultures were diluted 1:1 in 30% glycerol and stored at −80 °C in aliquots. L. monocytogenes, and the laboratory E. coli strains, XL1-blue and DH5α, were cultured the same way, except with shaking at 180 rpm. Likewise, the anaerobic bacterium C. perfringens was cultured in the same way except that incubation was performed in the BD GasPak 100 system for agar cultures or with Oxyrase and no shaking in the case of broth cultures. These frozen stocks were used in subsequent experiments. Passive Encapsulation of Sulforhodamine B into Liposomes. A mixture of HEPC:Cholesterol:DSPE-PEG2000 at a molar ratio of 50:45:5 was solubilized in chloroform. This solution was dried to a thin film under rotary evaporation and then under vacuum overnight. Hydration buffers were prepared fresh prior to use. Sulforhodamine B (SRB, Sigma-Aldrich) hydration buffer was prepared as follows: SRB was dissolved in PBS with NaOH added to aid dissolution to give a final solution of 100 mM SRB, PBS pH 8.0−8.5. The film was hydrated with the hydration buffer and submerged in an Elma S30H water bath sonicator at 70 °C for 10 min to form multilamellar vesicles. These vesicles were further downsized by sonicating the solution with a Qsonica Misonix probe sonicator to afford a clear solution (3−5 cycles of 2 min with 1 min rest in

from nanoscale liposomes than to create a transparent zone of lysis through a column of large erythrocytes. Here, we demonstrate that this assay, called beta-hemolysis triggeredrelease assay (BETA), can accurately distinguish beta-hemolytic bacteria from alpha or gamma-hemolytic bacteria.

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MATERIALS AND METHODS

Materials and Bacterial Strains. Hydrogenated egg phosphatidylcholine (HEPC), 1,2-distearoyl-sn-glycero-3-phosphoethanolamineN-[amino(polyethylene glycol)-2000], sodium salt (DSPE-PEG2000) were purchased from Lipoid AG, Switzerland. Fetal bovine serum (FBS), 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES), cholesterol, and Brain Heart Infusion (BHI) were purchased from Sigma-Aldrich. Hoechst 33342 (H33342) was purchased from Life Technologies. BD GasPak 100 System was purchased from Biomed Diagnostics, Singapore. Oxyrase was purchased from Oxyrase, Inc. The bacteria strains used in this study were Bacillus cereus (ATCC 10987), Clostridium perfringens (ATCC 13124), Listeria monocytogenes (MBL.0129E3-CRM, Microbiologics ATCC 13932), Streptococcus salivarius (ATCC 13419), Streptococcus oralis (ATCC 9811), Lactococcus lactis subsp. lactis (ATCC 11454), Streptococcus pyogenes, Streptococcus pnuemoniae (both strains generously provided by National University Hospital Singapore), Staphylococcus epidermis, Staphylococcus aureus, Pseudomonas aeruginosa (kind gifts from Department of Biological Sciences, National University of Singapore), laboratory E. coli strains XL1-blue and DH5α (Table S1). All work with these bacteria was reviewed and approved by the Temasek Life B

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ACS Sensors between). The mixture was kept on ice throughout sonication to prevent overheating of the suspension. Finally, the liposome suspension was passed through a HiTrap desalting column (GE Healthcare) with PBS to remove unencapsulated dye. Fractions with a signal/background ratio of >50 were pooled together and stored at 4 °C. Remote Loading of H33342 Dye into Liposomes. Remote loading of molecules into liposomes was performed according to the method described by Haran et al.20 Briefly, the liposomal suspension was prepared as described above with the exception of a 300 mM (NH4)2SO4 (Merck) solution used as the hydration buffer. To form a H+ proton gradient for the loading of H33342, the liposome solution was dialyzed against 2 changes of saline solution (0.15 M NaCl) at 2 and 4 h and then left to dialyze overnight at 4 °C. H33342 was dissolved in saline and added to the liposome solution at a ratio of 10:1 (mol lipid: mol H33342) and incubated in an oven at 70 °C for 2 h. The liposome solution was passed through a HiTrap desalting column with PBS to remove unencapsulated H33342. Fractions with a signal/background ratio of >100 were pooled together and stored at 4 °C. Sizing of Liposomes. Liposome size was measured by quasielastic light scattering using a Brookhaven 90Plus Particle Size Analyzer (Brookhaven Instruments Corporation, NY). Measurement of Erythrocyte Clearing in Agar. The experimental setup was identical to “Visualization of Hemolytic Colonies” except that erythrocytes (10% v/v in final volume) were substituted for liposomes. Quantitative analysis of zone of clearing was performed using FIJI.21 Images were stacked together and the region of interest (ROI) was fitted to the area of clearing to the best of our ability. These steps were performed for every time point in time lapse experiments where relevant. Measurement of Erythrocyte Clearing in Broth. 1 mL of overnight bacterial cultures were centrifuged at 17 000g for 5 min. The supernatant was added to BHI (BD Bacto), FBS, and erythrocytes in a total volume of 50 μL in 384 well clear plates (Greiner). An adhesive clear plastic seal (Sigma-Aldrich) was placed over the plate to prevent evaporation over the course of the experiment. The assay was carried out in a Tecan M200 Pro plate reader (Tecan Group Ltd.). Erythrocyte clearing was measured by OD600 at 37 °C every 5 min for 220 min. Visualization of Hemolytic Colonies. Assay medium was prepared by mixing BHI, FBS, agarose, and purified H33342 liposomes in the following quantities in a final volume of 100 μL: 1 × BHI, 10% FBS (v/v), 1% (w/v) agarose, 4 μL H33342 liposomes. Thawed cultures (102−103 CFU) were added this assay medium and this mixture was then vortexed and spun briefly to reconsolidate the mixture. 70 μL of this mixture was pipetted onto a concave slide and a coverslip was placed on top of it. The samples were then incubated overnight in a humidified chamber at 37 °C. Colonies were visualized at 10× magnification on a Zeiss Axiovert 200 M microscope. For fluorescence visualization, colonies were excited with UV light (365 nm) and the emission (LP at 395 nm) was captured with a CoolSnap HQ CCD camera. Quantitative analysis of fluorescence images in Figure 1C was performed using FIJI.21 The images were first stacked together and a fixed region of interest (ROI) was defined in the colony at 4 h for S. pyogenes and B. cereus, and 6 h for E. coli and S. epidermidis. Background readings were obtained by using the same defined dimensions to measure the fluorescence intensity outside the colony. The signal/background ratio was calculated by taking the mean intensity of the ROI in the colony divided by the mean intensity of the background. Four colonies were selected from every experiment. These steps were performed for every time point in time lapse experiments where relevant. For visualization of cocultured hemolytic S. pyogenes or S. aureus with alpha-hemolytic S. pneumoniae colonies, the procedure was similar as above except colonies were probed with anti-S. pneumoniae antibodies to identify S. pneumoniae colonies. Briefly, after incubation, the coverslip was removed, and the gel was washed once with 1× PBS pH 7.4. Next, the gel was blocked with 5% BSA (Sigma-Aldrich) for 3 h and probed with mouse anti-S. pneumoniae (1:50, AbD Serotec)

overnight. The antibodies were removed, washed thrice with 1× PBS pH 7.4 for 1 h, and then probed again with an Alexa Fluor 488 conjugated goat antimouse antibody (1:200, Life Technologies) overnight. The secondary antibodies were removed and washed thrice with 1× PBS pH 7.4 for 1 h. All washing and probing steps were done in a humidified chamber at room temperature. Colonies were visualized with a 5× magnification lens on a Zeiss Axiovert 200 M microscope. For fluorescence visualization, colonies were excited with UV or blue light (365 or 488 nm) and the emission (BP 445/50 nm, BP 525/50 nm) was captured using a CoolSnap HQ CCD camera. All experiments above were carried out with the same exposure time with respect to the experiment and repeated three times. Uptake of Free H33342 by Bacteria. The uptake of free H33342 was investigated by repeating the experiment as above but replacing liposomal H33342 with free H33342 dye (final concentration, 160 nM). Sodium hexametaphosphate (Sigma-Aldrich) was added to a concentration of up to 0.3% for membrane permeabilization experiments. Image Processing and Pattern Recognition. For the detection of colonies in images, we applied a top-hat transform for background subtraction followed by thresholding using Otsu’s method.22 Morphological opening was used to remove small blobs after thresholding. Next, we employed the marker-controlled watershed algorithm to separate the overlapping objects in the image. Finally, the connected component labeling algorithm was utilized to extract the foreground objects and background pixels. To build the feature data set for classification purpose, we measured the fluorescence intensity of a fixed circular area (radius: 20 pixels) from the centroid of the colony. If colonies were too small to accommodate a 20-pixel radius, a radius of 5 was used instead. The average of these intensities is referred to as “colony fluorescence” in the main text. Further, the background intensity refers to the average of the background pixels. We also performed textural analysis by extracting the Gray-Level Co-occurrence Matrix (GLCM).23 The co-occurrence matrix provides the probability that a pixel with the intensity value i occurs at a predefined distance and direction with another pixel of intensity value j. This joint probability density function Pd,θ(i,j) can be used to extract the image textural features. In this work, we estimated the cooccurrence matrices for a distance of d = 1 pixel in horizontal, vertical, and diagonal directions (0, 45, 90, and 135). These matrices were obtained using a computational window size of 20 pixels in an 8-bit quantized image. The average of the four co-occurrence matrices results in the nondirectional GLCM. We used this nondirectional GLCM to extract the dissimilarity texture feature, which is similar to contrast but the weights increase linearly. It is given as N−1

∑ P(i , j)|i − j| i,j=0

where N refers to the number of levels specified for quantization. The support vector machine (SVM) classifier with linear kernel was used to classify beta-hemolytic and non-beta-hemolytic organisms from admixture samples. 10-fold stratified cross-validation was performed to determine classification performance. The algorithm was implemented in Python 2.7.3. Morphological operations for colony detection and calculation of image features (intensity and dissimilarity) were carried out using scikit-image 0.10.0 module. We used SVM as implemented in the scikit-learn 0.15.0 module.24 Liposome Pull Down Assay. Frozen S. pyogenes and B. cereus cultures were inoculated into 25 mL of BHI media and incubated overnight at 37 °C. The samples were then centrifuged at 3900g for 10 min. 20 mL of supernatant were collected and concentrated by centrifugation in spin columns at 3900g for 10 min. This was repeated once. Next, PBS was added to the concentrate to a final volume of 1.5 mL for both samples. 40 μL of SRB liposomes were added to 900 μL of the concentrate and continuously inverted at 37 °C for 1 h. This solution was then centrifuged at 16000g for 30 min, washed with 1 mL of 1× PBS, and centrifuged at the same speed again. 960 μL of C

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Statistical Analysis. Unless otherwise stated, all statistical tests were performed in Graphpad Prism 5.0. We used a two tailed Mann− Whitney test for the comparison of nonparametric independent samples. A two tailed Student’s t-test was used to analyze the SVM probabilities of test colonies belonging to either the beta-hemolytic class (S. pyogenes and S. aureus) or the alpha-hemolytic class (S. pneumoniae). TTD curves were generated by comparing the bacteria in question to alpha-hemolytic S. pneumoniae using P values from the single tailed Student’s t-test computed in Microsoft Excel 2007.

supernatant was then removed and the pellet was dissolved in the remaining wash solution by light vortexing. The samples were separated by a 10% Bis Tris gel 1.0 mm × 12 well (NP0302-Box, Life Technologies) running in 1× MOPS buffer (NP0001, Life Technologies). For visualization of protein bands, the gel was stained according to the Colloidal Coomassie protocol.25 Briefly, the gel was fixed in 30% ethanol +2% phosphoric acid for 1 h and stained overnight with shaking. The stain was then disposed of, and the gel was washed thrice in ultrapure water, each lasting 10 min. Bands were excised with a scalpel. In-gel reduction, alkylation, and digestion were performed with Montage In-Gel digestion ziptip kit (LSKG DZT 96, Millipore) according to manufacturer instructions. Subsequent protein identification steps are described as in Supporting Information H33342 Liposome Leakage Assay. H33342 liposomes were added to media (10% FBS in 1× BHI) and incubated at 37 °C. The mixture was pipetted into a 384 well black plate at specific time points. Triton X-100 (final concentration, 0.2%) was added to lyse the liposomes to find the maximum fluorescence (F100%) value of H33342 in the well. The stability of the liposomes at time t was defined by the following formula: %Leakage =

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RESULTS Evaluation of Miniaturized Red Blood Cell Based Methods. Beta-hemolysis on blood agar plates has been welldocumented in other studies and typically requires overnight incubation (SI Figure 1). Miniaturization of the blood agar format and the use of microscopy to detect hemolysis could in theory speed up hemolysis detection. To investigate, we inoculated various bacterial strains (SI Table 1) into BHI agar media admixed with red blood cells in concave well slides. After overnight incubation, the slides were visualized under brightfield microscopy. As expected, alpha and gamma-hemolytic bacterial colonies grew in the midst of the easily visible erythrocytes and no zone of clearing was observed (SI Figure 2). In contrast, four out of five beta-hemolytic bacteria tested (B. cereus, S. pyogenes, C. perfringens, and L. monocytogenes) exhibited zones of clearing which were unambiguously devoid of erythrocytes. The lone exception, S. aureus, was a false negative for this approach. Notably, L. monocytogenes, which is often described as “subtly” hemolytic on blood agar plates, was easily identified as beta-hemolytic in our setup. Next, we studied the kinetics of red blood cell lysis by imaging the growth of B. cereus, S. pyogenes, S. epidermidis, and E. coli DH5α at 15 min intervals in the same experimental setup (SI Figure 3). Beta-hemolytic zones were observed as early as 4.5 h for B. cereus and 7.5 h for S. pyogenes but not for S. epidermidis and E. coli DH5α. In short, one can visually detect beta-hemolysis much more quickly through a miniaturized version of the red blood agar assay than through a conventional red blood agar plate. We further investigated if the same principle would work in broth as opposed to semisolid agar. Here, we incubated the culture supernatant of various bacteria with suspended red blood cells and tracked absorbance readings over time (SI Figure 4). While all beta-hemolytic bacteria tested (B. cereus, S. pyogenes, S. aureus, L. monocytogenes) exhibited a dramatic drop in absorbance, alpha-hemolytic S. pneumoniae also produced a drop in absorbance which was far more rapid than S. aureus and almost equivalent to the positive control for lysis, Triton X-100. To summarize, we found that miniaturization of red blood cell-based methods enabled the unambiguous overnight detection for four out of five beta-hemolytic bacteria tested in agar, and yielded quicker detection times compared to conventional blood agar plates. Tracking red blood cell absorbance in broth was however unable to differentiate between alpha and beta-hemolysis, rendering red blood cells unsuitable for this purpose. Liposomes as Blood Substitutes. Liposomes have traditionally been used to achieve controlled release in drug delivery26,27 and membrane studies. Since phospholipases and pore formers secreted by beta-hemolytic microorganisms are known to bind and disrupt them, we wondered if liposomes could be a direct replacement for erythrocytes in blood agar. An ideal substitute for erythrocytes should be optically clear, cost-effective to produce, stable when suspended in rich growth

Ft − F0% × 100% F100% − F0%

where Ft was the fluorescence reading at a specific time point, F0% was the reading at T0 when the liposomes were first added to the mixture, and F100% was the reading at T0 when Triton X-100 was added to the mixture. The experiment was conducted three times and each time point in triplicate. Fluorescent Plate Reading Assay. Dilutions of frozen bacterial stocks in PBS were inoculated with SRB liposomes, BHI (BD Bacto), and FBS in a total volume of 50 μL in a 384 well black plates (Greiner). An adhesive clear plastic seal (Sigma-Aldrich) was placed over the plate to prevent evaporation over the course of the experiment. The assay was carried out in a Tecan M200 Pro plate reader (Tecan Group Ltd.). The excitation and emission was set to 526/584, with a gain of 70. Absorbance readings (OD600) were also monitored for confirmation of bacterial growth in the wells. The plate was continuously measured at 37 °C every 10 min for 15 h. Colony forming units (CFUs) were determined by plating the dilutions used in the assay on BHI plates and counting the number of colonies formed after overnight incubation. L-SRB lysis was calculated by the following formula

⎛ F − F0% ⎞ %Lysis = ⎜ t × 100%⎟ ⎝ F100% − F0% ⎠ where Ft is the fluorescence reading at a specific time point, F0% is the average of four blank wells filled with media + L-SRB but no Triton X100 and bacteria, and F100% is the average of four blank wells with Triton X-100 added. The experiment was conducted three times with every concentration of bacteria tested in four replicates. Admixture experiments were conducted similarly as above except the experiment was stopped at 12 h. Immunofluorescence Labeling of Cells in 384 Well Plates. Cells from four wells were collected, washed once in 1× PBS pH 7.4, and normalized to a fixed number before heat fixing on glass slides. The cells were fixed again with 10% Neutral Buffered Formalin (HT501128, Sigma-Aldrich) for 10 min and washed thrice in 1× PBS pH 7.4. Next, fixed cells were blocked with 5% BSA in PBS for 1 h, washed thrice in 1× PBS pH 7.4, and probed with FITC conjugated mouse anti-S. pneumoniae antibody (1:50, ab35165, Abcam) for 1 h. The cells were washed again in 1× PBS pH7.4 and mounted with Fluoromount (F4680, Sigma-Aldrich). The cells were imaged on the same day using a Zeiss Axiovert 200 M microscope. For fluorescence visualization, cells were excited with blue light (488 nm) and the emission (BP 525/50 nm) was captured on a CoolSnap HQ CCD camera. D

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Figure 2. Beta-hemolytic colonies are distinguishable in agar cocultures with alpha hemolytic S. pneumoniae. (A) Fluorescent and bright-field images of pure and admixed bacterial colonies in BHI agar with L-Hoechst. Scale bars, 200 μm (B) Classification of beta-hemolytic S. pyogenes/S. aureus and the non-beta-hemolytic S. pneumoniae. Using the lack or presence of green fluorescence as ground truth for identifying S. pyogenes/S. aureus (n = 46) versus S. pneumoniae (n = 49) colonies, both colony classes were randomly partitioned into training and testing sets. The training set was used to establish an SVM computed 1-dimensional hyperplane (shown as a dotted line) to separate the classes based on colony fluorescence and average dissimilarity of L-Hoechst staining. The testing set was used to validate the accuracy of the trained SVM classifier. In this typical example, classification accuracy is 100%. (C) The experiment in (B) was repeated using a 10-fold cross validation framework. Mean SVM probabilities (the probability of beta-hemolysis) and standard deviations are reported. (D) Summary SVM classification results from (C) are shown in tabular form. Data represents the means ± s.d. *** P < 0.0001.

the two Gram-negative bacteria we tested were observed to fluoresce blue. This result showed that H33342, once released from its encapsulated form (SI Figure 6B), could be assimilated by Gram-positive beta-hemolytic colonies to create a nondiffusible signal (Figure S2B). However, the results also suggested that H33342 might not be a suitable indicator for beta-hemolytic Gram-negative colonies. One possible explanation for this lack of uptake was that H33342 is highly hydrophobic and Gram-negative bacteria in particular are well-known to have limited permeability to hydrophobic small molecules.30 We tested the idea that sodium hexametaphosphate, an outer membrane permeabilizing agent, would improve the permeability of Gram-negative bacteria to H33342. We observed that although outer membrane permeabilization did indeed increase the fluorescence of E. coli and S. pyogenes colonies significantly, the concentrations of sodium hexametaphosphate required to increase E. coli colony fluorescence by a mere 80% turned out to be lethal to the Gram-positive bacterium S. pyogenes (SI Figure 6C). Thus, we focused our L-Hoechst experiments on Gram-positive bacteria, using the Gram-negative E. coli only as a control for colony fluorescence. L-Hoechst was created by acidifying the liposomal interior relative to the exterior.20,31 H33342 is membrane-permeant at physiological pH but becomes preferentially charged and hence entrapped upon diffusing into the liposomal interior. High intraliposomal concentrations were achieved using this remote loading procedure. Various bacterial strains (SI Table 1) were then inoculated into BHI agar media admixed with L-Hoechst

media, resistant to alpha-hemolysis, and easily detected when lysed. To meet these criteria, we formulated liposomes at the nanoscale using PEGylation for steric-stabilization28 and saturated phosphatidylcholine coupled with high cholesterol content to decrease membrane permeability.29 To enable detection, we encapsulated fluorescent dyes at self-quenching concentrations within the internal aqueous liposomal compartment. Upon disruption of the liposomes, these dyes are released and consequently dequenched, producing a signal many times above their encapsulated fluorescence. We created two flavors of BETA: one based on liposomal Hoechst 33342 (L-Hoechst) and the other using liposomal Sulforhodamine B (L-SRB). PEGylation of the liposomes was paramount for stability; PEGylated L-SRB liposomes leaked 0.2% of their contents over 16.7 h in bacterial growth media whereas the non-PEGylated version leaked more than 5.8 times that amount within the same period (SI Figure 5). BETA Detects Beta-Hemolytic Microcolonies in Agar. Both Sulforhodamine B and Hoechst 33342 (H33342) have very different physicochemical properties. At physiological pH, SRB is ineffective for visualizing hemolytic bacterial colonies because it is hydrophilic and thus unable to penetrate bacterial cell membranes. In contrast, H33342 is an amphiphilic, membrane-permeable nuclear stain ideal for colony visualization. First, we tested the ability of bacterial colonies to associate with H33342 by culturing a variety of bacteria on Brain Heart Infusion (BHI) agar with a nonlethal concentration of H33342 (SI Figure 6A). Interestingly, all Gram-positive bacteria but not E

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Figure 3. (A) Beta-hemolytic bacteria (B. cereus, S. aureus, L. monocytogenes, C. perfringens, S. pyogenes) are rapidly detectable in broth media with BETA. Effect of inoculum size of of B. cereus (B), S. aureus (C), L. monocytogenes (D), C. perfringens (E), and S. pyogenes (F) on the lysis of L-SRB. (G) Time-to-Detection (TTD) for each S. pyogenes time-series (P < 0.01) is marked by an *. (H) Consolidated TTDs for all beta-hemolytic bacteria in log(CFU/mL). All exponents stated in the legends refer to the inoculum size in CFUs. Data represents the means ± s.d.

coli XL1 which had the lowest background fluorescence. S. aureus, which was a false negative in our red blood cell assay, produced the second highest signal among our beta-hemolytic panel. BETA’s results can perhaps be attributed to the relative ease of creating a fluorescent signal as compared to the destruction of large red blood cells in sufficient quantities to enable light transmittance. We used BETA to study the kinetics of beta-hemolytic activity by imaging individual colonies of B. cereus, S. pyogenes, S. epidermidis, and E. coli DH5α at 15 min intervals. The fluorescence of B. cereus and S. pyogenes colonies both exhibited

and incubated on concave well slides for microscopic visualization. After overnight incubation, colonies of all five beta-hemolytic bacteria tested (B. cereus, S. pyogenes, S. aureus, C. perfringens, and L. monocytogenes) turned fluorescent. In contrast, colonies of the alpha or gamma-hemolytic bacteria used as controls remained low in fluorescence (Figure 1A). Beta-hemolytic activity measured by colony fluorescence was able to perfectly separate beta-hemolysis from controls (Figure 1B). Even in the worst case comparison, the weakest betahemolysis from L. monocytogenes was 2-fold above the highest background signal from Lactococcus lactis. In the best case, the strongest beta-hemolysis from S. pyogenes was 30-fold above E. F

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Figure 4. Comparison of TTD in broth (A) and lysis of L-SRB (B) for B. cereus and admixed B. cereus and S. pneumoniae. Effects of inoculum size of B. cereus (C) and admixed B. cereus and S. pnuemoniae (D) on the lysis of L-SRB. Data represent the means ± s.d.

BETA Rapidly Detects Beta-Hemolytic Bacteria in Broth Culture. To determine if beta-hemolytic bacteria could similarly be detected in broth, we inoculated pure populations of various bacteria into BHI broth with L-SRB (Figure 3A−F). L-Hoechst was not used here because autofluorescence from BHI media coincides with H33342’s emission range. When normalized to the fluorescence signal from 100% lysed L-SRB, alpha and gamma-hemolytic bacteria lysed only up to 0.5% of L-SRB despite highly turbid growth (Figure 3A−F, SI Figures 8−9). In contrast, beta-hemolytic bacteria lysed 10−65% of L-SRB, resulting in signal levels 26 to 125 times above S. pneumoniae. Importantly, L-SRB lysis by C. perfringens could be robustly detected when Oxyrase was added to create an anoxic environment (Figure 3F), demonstrating that BETA can be used to identify beta-hemolytic obligate anaerobes. To ascertain BETA’s limit of detection, we repeated the above experiment with serial dilutions of each individual bacterium. As expected, the time point when each bacterium hit exponential growth decreased monotonically with the number of CFUs inoculated (Figure 3A−F). Importantly, we could detect beta-hemolysis in wells with 1−10 CFUs, showing that BETA is sensitive even at limiting dilutions. We defined TimeTo-Detection (TTD) as the point when the fluorescence of a time-series significantly (P < 0.01) exceeded that of S. pneumoniae. This principle is illustrated for S. pyogenes where TTDs for each time-series are marked with asterisks (Figure 3G). We also observed a strong linear correlation (R2 > 0.9) between TTD and inoculum size for all beta-hemolytic bacteria (Figure 3H), suggesting that if a bacterium’s strain is known, TTD could be a quantitative estimator of inoculum size. TTD was found to range approximately from 1 to 5 h for 104 cells and 8 to 15 h for single cells. Further, TTD was not significantly affected by the status of the cell; frozen and live B.

a sharp exponential increase after a 5 h lag, reaching similar fluorescence levels after 24 h (Figure 1C). These kinetics were approximately similar to miniaturized red blood agar (SI Figure 3) with the majority of the signal increase occurring between 5 and 10 h. Nonhemolytic colonies also gained fluorescence at a basal level, likely due to the uptake of trace amounts of unencapsulated H33342. All bacterial colonies reached maximum fluorescence when they plateaued in colony size. Interestingly, we also noticed that colony fluorescence associated with beta-hemolysis was qualitatively different from background fluorescence associated with control bacteria. Specifically, the first looked uniform whereas the second had a granular texture. To quantitate this textural component, we computed the Dissimilarity parameter using the gray level cooccurrence matrix (GLCM) of the fluorescent microcolonies. Consistent with our visual intuition, beta-hemolysis was found to be inversely proportional to Dissimilarity, hence creating a second complementary axis to separate beta-hemolysis from controls (Figure 1D). BETA Identifies Beta-Hemolytic Colonies in Admixtures. Real-world scenarios involve bacterial populations in coexistence. Hence, we were curious to see if BETA could distinguish S. pyogenes and S. aureus, which are common betahemolytic human pathogens, from S. pneumoniae, a strongly alpha-hemolytic commensal often intermixed with them.4 After coculture on BHI agar with L-Hoechst, S. pneumoniae colonies were immunostained with green fluorescence to tell them apart from S. pyogenes or S. aureus. As expected, S. pyogenes and S. aureus were fluorescently labeled blue from lysis of L-Hoechst whereas S. pneumoniae showed no staining (Figure 2A). Similar to our prior experiments using GLCM, we found that the Dissimilarity parameter was also applicable to admixtures and could be used to distinguish S. pyogenes and S. aureus from S. pneumoniae in BHI agar cocultures (Figure 2B−D) with virtually perfect accuracy. G

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Figure 5. (A) L-SRB interacting proteins purified from the supernatant of B. cereus and S. pyogenes are isolated on a SDS-PAGE. (B) Identification of the isolated proteins by LC-ESI-MS.

cereus cells had similar TTDs except when the concentration of B. cereus cells was low (SI Figure 9). To exclude the possibility that secreted lytic agents in our bacterial stocks had an influence on TTD, we incubated the supernatant of our B. cereus and S. pyogenes stock suspensions with L-SRB for 4 h at 37 °C (SI Figure 10). No significant difference in signal was observed between B. cereus, S. pyogenes, and S. pneumoniae. In many scenarios, beta-hemolytic bacteria are heavily outnumbered by alpha and gamma-hemolytic commensal bacteria. To study how BETA’s limit of detection is affected by admixing, we inoculated a variable quantity of B. cereus together with a fixed quantity (105 CFU/mL) of S. pneumoniae. TTD was unaffected in wells with at least 1000 CFU/mL of B. cereus (Figure 4A). It was only at dilutions below 1000 CFU/ mL that S. pneumoniae was able to outcompete B. cereus growth and affect TTD (Figure 4B-D, SI Figure 11,12). Bacterial Membrane Interacting Proteins Copurify with PEGylated Liposomes. BETA’s underlying premise is that beta-hemolytic agents act directly on liposomal bilayers to lyse and release their contents. One way to corroborate this hypothesis is to examine if liposomes incubated with media

conditioned with the growth of beta-hemolytic microorganisms would physically associate with and hence enrich membranedisrupting proteins. Liposomes incubated in media conditioned by S. pyogenes growth and subsequently purified through ultracentrifugation were found to copellet with Streptolysin O, a canonical example of a beta-hemolysin (Figure 5). Four other proteins, oligopeptide binding proteins, ATP synthase, Elongation Factor Tu, and a putative secreted protein were also identified. These proteins are known to associate with or localize within membranes.32−34 We repeated the experiment using B. cereus conditioned media and found similarly that the liposomes copurified with the well-characterized membrane interacting proteins Alveolysin,35 Hemolytic Enterotoxin, and Enterotoxin B.36 These observations support the idea that liposomes are directly lysed by bacterially secreted hemolysins and are hence suitable agents for detecting beta-hemolysis.

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DISCUSSION In this work, we demonstrate that miniaturizing red blood cell methods can potentially decrease the detection time for betahemolysis. However, the fact that S. aureus (an important pathogen) is a false negative for agar and S. pneumoniae (a H

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Interestingly, B. cereus and C. perfringens, both of which secrete phospholipases, give a much higher signal after an overnight incubation compared to S. pyogenes, L. monocytogenes, and S. aureus which secrete pore-forming hemolysins (SI Figure 13). We speculate that the decreased asymptotic maximum for pore-forming toxins as compared to phospholipases is due to differences in how these proteins interact with membranes. Pore-forming proteins, once assembled within the bilayer, do not transition easily into the bilayers of other intact liposomes. The enzymatic activity of a phospholipase on the other hand persists over its lifetime. Despite this difference in toxin class, the TTDs for all bacteria did not differ by more than a magnitude and the quickest TTD was observed with 104 CFUs of S. pyogenes, suggesting that hemolysin class is not the determining factor for TTD. Factors which could play a role in influencing TTD include variation in the susceptibility of the liposomal bilayer to particular lytic agents and also in the kinetics of toxin production as modulated by quorum sensing. Finally, we isolated liposomes incubated with media conditioned with the growth of B. cereus or S. pyogenes to see if we could isolate membrane interacting hemolysins. From S. pyogenes-conditioned media, we were able to isolate Streptolysin O, the main hemolysin in this bacterium and presumptive cause of liposomal lysis. Interestingly when we repeated this experiment with B. cereus, we were able to isolate three welldefined membrane interacting proteins, Alveolysin, Hemolytic Enterotoxin, and Enterotoxin B, but not the primary hemolysin which was Phospholipase C (Figure 5). This is consistent with the idea that pore forming proteins have higher affinities for bilayers compared to phospholipases. The fact that the PEGylation did not compromise interactions with membraneactive proteins is in agreement with previous studies42 and demonstrates the utility of PEGylated liposomes for investigating protein−bilayer interactions. In conclusion, BETA’s timeliness opens the door to applications once limited by the tardiness of blood agar cultures. With increased speed, gold standard throat cultures based on BETA can now be used as a first-choice diagnostic test (as opposed to a confirmatory assay) for bacterial pharyngitis. BETA’s scalable form-factor (multiwell plates) and low reagent costs (∼0.02 USD per assay) make it suitable as a sensitive high-throughput triage method for in-plant food safety testing to complement pathogen-specific assays such as phage detection.43 All L-SRB liposomes used in this work were made in January 2014 and continue to be stable under refrigeration. Two experiments with B. cereus performed 2 years apart showed no substantial difference in TTD performance, demonstrating BETA’s long shelf life (SI Figure 14). This compares favorably with red blood agar plates which expire within a few months. For many developing countries, the cost of a blood agar plate (∼0.40 USD) is an unaffordable luxury. In these countries, BETA’s cost effectiveness provides a safe and economically viable alternative to human blood which carries the well-documented risk of blood borne Hepatitis B and HIV infections.44,45 There are many ways in which BETA could be customized for particular applications, such as the use of hemolysin-specific phospholipids and selective growth media. Further improvements in TTD can be made through miniaturization (e.g., using microfluidic methods) and real time pattern recognition for the earliest possible detection of hemolytic samples. We hope that newfound relevance for beta-

ubiquitous commensal) is a false positive for broth greatly limits the usefulness of this idea. We turned instead to liposomes as a direct substitute for erythrocytes. The idea of perturbing lipid vesicles with hemolysins is not inherently new.37−39 What is novel is the general principle that liposomes are able to accurately distinguish beta-hemolysis from alpha and gamma-hemolysis. BETA’s results reported here show that liposomes can indeed be highly accurate biosensors for beta-hemolysis. This was proved two ways, by directly visualizing microscopic beta-hemolytic colonies on agar and by indirectly detecting beta-hemolytic activity in broth. In the first part, we showed that beta-hemolytic colonies lyse L-Hoechst on agar after overnight incubation, becoming fluorescent in the process. In comparison, nonhemolytic colonies had negligible baseline fluorescence from the uptake of trace H33342. Although H33342 was not taken up by the Gram-negative bacteria we tested, the principles described are equally applicable if a suitable dye that is assimilated by all Gram-negative bacteria is used. If required, individual colonies can be isolated from the agar for further downstream characterization. The use of the Dissimilarity parameter from GLCM creates a second dimension complementary to colony fluorescence. When plotted along both axes, all beta-hemolytic colonies were linearly separable from controls. This included L. monocytogenes which normally takes 24−48 h of enrichment on selective media and a total test time of 5−7 days for betahemolysis to be visible on blood agar plates.40 This zone of hemolysis is often described as not extending beyond the colony’s edge such that physical removal of the colonies is sometimes necessary to observe the zone of clearing. In comparison, an overnight incubation in generic BHI medium is all that is required to observe beta-hemolysis (Figure 1A,B). This technique also worked well with bacterial admixtures. In clinical settings, human pathogens such as S. pyogenes and S. aureus are often commingled with the commensal S. pneumoniae.4 We showed that both S. pyogenes and S. aureus could clearly be differentiated from fluorescently labeled S. pneumoniae (Figure 2). This selective fluorescent labeling of beta hemolytic colonies has not been described elsewhere. In the next part of the study, we detected beta-hemolysis in broth using a 384-well plate format. Here, beta-hemolytic bacteria were observed to generate a fluorescent signal at least 26-fold above baseline (Figure 3A). We chose S. pneumoniae as the baseline because it is strongly alpha-hemolytic and a common commensal. Using its fluorescence at each time point as our null hypothesis, the time-to-detection (TTD) for each of the five hemolytic bacteria tested was defined to be the time when its fluorescence significantly exceeded S. pneumoniae’s. These TTDs correlated linearly with inoculum size (Figure 3H). BETA’s detection limit which ranged from 1 to 10 CFUs for all five bacteria (B. cereus, S. pyogenes, C. perfringens, S. aureus, and L. monocytogenes) was far below their infectious doses (105, 103, 107, 105, and 103, respectively).1,2,41 Detection times ranged from 50 min for 104 CFUs of S. pyogenes to 14.3 h for a single CFU of S. aureus. Admixture experiments with B. cereus and S. pneumoniae prove that 10 CFUs of B. cereus (far below its infectious dose) are still detectable despite the presence of a 3-log excess of S. pneumoniae. In contrast, the culture of samples in a diagnostic setting usually requires the use of selective media to reduce background colonies which are not the target microbe. Our results demonstrate that such selection is unnecessary for BETA. I

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(6) Cho, I. H.; Radadia, A. D.; Farrokhzad, K.; Ximenes, E.; Bae, E.; Singh, A. K.; Oliver, H.; Ladisch, M.; Bhunia, A.; Applegate, B.; Mauer, L.; Bashir, R.; Irudayaraj, J. Nano/micro and spectroscopic approaches to food pathogen detection. Annu. Rev. Anal. Chem. 2014, 7, 65−88. (7) Pichichero, M. E. Group A streptococcal tonsillopharyngitis: costeffective diagnosis and treatment. Ann. Emerg Med. 1995, 25 (3), 390− 403. (8) Shulman, S. T.; Bisno, A. L.; Clegg, H. W.; Gerber, M. A.; Kaplan, E. L.; Lee, G.; Martin, J. M.; Van Beneden, C. Clinical practice guideline for the diagnosis and management of group A streptococcal pharyngitis: 2012 update by the Infectious Diseases Society of America. Clin. Infect. Dis. 2012, 55 (10), 1279−82. (9) Mirza, A.; Wludyka, P.; Chiu, T. T.; Rathore, M. H. Throat culture is necessary after negative rapid antigen detection tests. Clin. Pediatr. (Philadelphia) 2007, 46 (3), 241−6. (10) Scallan, E.; Hoekstra, R. M.; Angulo, F. J.; Tauxe, R. V.; Widdowson, M. A.; Roy, S. L.; Jones, J. L.; Griffin, P. M. Foodborne illness acquired in the United States–major pathogens. Emerging Infect. Dis. 2011, 17 (1), 7−15. (11) Lee, W.; Kwon, D.; Chung, B.; Jung, G. Y.; Au, A.; Folch, A.; Jeon, S. Ultrarapid Detection of Pathogenic Bacteria Using a 3D Immunomagnetic Flow Assay. Anal. Chem. 2014, 86 (13), 6683−6688. (12) Afonso, A. S.; Pérez-López, B.; Faria, R. C.; Mattoso, L. H. C.; Hernández-Herrero, M.; Roig-Sagués, A. X.; Maltez-da Costa, M.; Merkoçi, A. Electrochemical detection of Salmonella using gold nanoparticles. Biosens. Bioelectron. 2013, 40 (1), 121−126. (13) Schiff, D.; Aviv, H.; Rosenbaum, E.; Tischler, Y. R. Spectroscopic Method for Fast and Accurate Group A Streptococcus Bacteria Detection. Anal. Chem. 2016, 88 (4), 2164−9. (14) Suo, B.; He, Y.; Paoli, G.; Gehring, A.; Tu, S. I.; Shi, X. Development of an oligonucleotide-based microarray to detect multiple foodborne pathogens. Mol. Cell. Probes 2010, 24 (2), 77−86. (15) Chen, Y.; Knabel, S. J. Multiplex PCR for simultaneous detection of bacteria of the genus Listeria, Listeria monocytogenes, and major serotypes and epidemic clones of L. monocytogenes. Appl. Environ. Microbiol. 2007, 73 (19), 6299−304. (16) Cui, H.-F.; Xu, T.-B.; Sun, Y.-L.; Zhou, A.-W.; Cui, Y.-H.; Liu, W.; Luong, J. H. T. Hairpin DNA as a Biobarcode Modified on Gold Nanoparticles for Electrochemical DNA Detection. Anal. Chem. 2015, 87 (2), 1358−1365. (17) Smartt, A. E.; Xu, T.; Jegier, P.; Carswell, J. J.; Blount, S. A.; Sayler, G. S.; Ripp, S. Pathogen detection using engineered bacteriophages. Anal. Bioanal. Chem. 2012, 402 (10), 3127−46. (18) Liu, P.; Han, L.; Wang, F.; Petrenko, V. A.; Liu, A. Gold nanoprobe functionalized with specific fusion protein selection from phage display and its application in rapid, selective and sensitive colorimetric biosensing of Staphylococcus aureus. Biosens. Bioelectron. 2016, 82, 195−203. (19) Martelet, A.; L’Hostis, G.; Nevers, M. C.; Volland, H.; Junot, C.; Becher, F.; Muller, B. H. Phage amplification and immunomagnetic separation combined with targeted mass spectrometry for sensitive detection of viable bacteria in complex food matrices. Anal. Chem. 2015, 87 (11), 5553−60. (20) Haran, G.; Cohen, R.; Bar, L. K.; Barenholz, Y. Transmembrane ammonium sulfate gradients in liposomes produce efficient and stable entrapment of amphipathic weak bases. Biochim. Biophys. Acta, Biomembr. 1993, 1151 (2), 201−15. (21) Schindelin, J.; Arganda-Carreras, I.; Frise, E.; Kaynig, V.; Longair, M.; Pietzsch, T.; Preibisch, S.; Rueden, C.; Saalfeld, S.; Schmid, B.; Tinevez, J. Y.; White, D. J.; Hartenstein, V.; Eliceiri, K.; Tomancak, P.; Cardona, A. Fiji: an open-source platform for biological-image analysis. Nat. Methods 2012, 9 (7), 676−82. (22) Otsu, N. A threshold selection method from gray-level histograms. Automatica 1975, 11 (285−296), 23−27. (23) Haralick, R. M.; Shanmugam, K. Textural features for image classification. IEEE Transactions on systems, man, and cybernetics 1973, 6, 610−621. (24) Pedregosa, F.; Varoquaux, G.; Gramfort, A.; Michel, V.; Thirion, B.; Grisel, O.; Blondel, M.; Prettenhofer, P.; Weiss, R.; Dubourg, V.

hemolysis after more than a century will spawn new possibilities for microbial diagnostics.

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ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acssensors.7b00333. Colonies of S. pyogenes and S. pnuemoniae streaked on Brucella sheep blood agar; time lapse experiments of S. pyogenes and B. cereus; effect of overnight supernatant of bacteria cultures on erythrocytes; effects of DSPE-PEG2000 on the stability of L-SRB in BHI media with FBS; comparison of bacterial colonies taking free H33342 in BHI/FBS agar; Properties of L-SRB as measured by DLS; bacterial growth curves; effects of bacterial stock supernatants; broth co-cultures of B. cereus and S. pneumoniae over 12 h; immunofluorescence images; bacterial strains used in this study (table); supplementary methods (PDF)

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. ORCID

Ian Cheong: 0000-0002-3062-6878 Present Address #

Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, USA. Author Contributions

The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript. Notes

The authors declare the following competing financial interest(s): Rongji Sum, Muthukaruppan Swaminathan and Ian Cheong are co-inventors of a pending provisional patent pertaining to the detection of beta-hemolytic pathogens.

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ACKNOWLEDGMENTS We thank Adrian Ng Chang Zhi, John Koh, and Liu Yanbin for insightful comments and technical assistance. We also thank Professor Chan Soh Ha (National University Hospital) and the Department of Microbiology, National University of Singapore for the generous gifts of S. pyogenes, S. pneumoniae, S. aureus, and S. epidermidis. This study was supported by Temasek Life Science Laboratories.

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REFERENCES

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