Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

A novel flow cytometry assay based on bacteriophage-derived proteins for Staphylococcus detection in blood

Abstract

Bloodstream infections (BSIs) are considered a major cause of death worldwide. Staphylococcus spp. are one of the most BSIs prevalent bacteria, classified as high priority due to the increasing multidrug resistant strains. Thus, a fast, specific and sensitive method for detection of these pathogens is of extreme importance. In this study, we have designed a novel assay for detection of Staphylococcus in blood culture samples, which combines the advantages of a phage endolysin cell wall binding domain (CBD) as a specific probe with the accuracy and high-throughput of flow cytometry techniques. In order to select the biorecognition molecule, three different truncations of the C-terminus of Staphylococcus phage endolysin E-LM12, namely the amidase (AMI), SH3 and amidase+SH3 (AMI_SH3) were cloned fused with a green fluorescent protein. From these, a higher binding efficiency to Staphylococcus cells was observed for AMI_SH3, indicating that the amidase domain possibly contributes to a more efficient binding of the SH3 domain. The novel phage endolysin-based flow cytometry assay provided highly reliable and specific detection of 1–5 CFU of Staphylococcus in 10 mL of spiked blood, after 16 hours of enrichment culture. Overall, the method developed herein presents advantages over the standard BSIs diagnostic methods, potentially contributing to an early and effective treatment of BSIs.

Introduction

Bloodstream infections (BSIs) are severe diseases caused by the presence of microorganisms, mainly bacteria, in blood and are characterized by high morbidity and mortality1,2. The BSIs and associated organ dysfunctions (sepsis or septic shock) remain a life-threating disease due, partially, to the inability to rapidly detect and identify the responsible pathogens3,4.

Staphylococcus spp. are Gram-positive facultative anaerobic bacteria that frequently colonize the human body5,6. These pathogens are becoming increasingly resistant to antibiotics and are well-established in both community and healthcare environments, being commonly isolated in intensive care units (ICU)6,7. Staphylococcus aureus is a common cause of a variety of infections, from superficial skin infections to life-threatening diseases, including necrotizing pneumonia8, infective endocarditis9 and BSIs10. Coagulase-negative staphylococci (CoNS) have also been described as harmful to humans, causing several infections, particularly in patients with implanted medical devices6.

The empirical antibiotic therapy remains the standard of BSIs treatments11 and its correct use within the first hour after the recognition of the BSI is recommended by the Surviving Sepsis Campaign Guidelines11 and was reported as having a great impact on the patient survival rate12. Nevertheless, the extensive use of broad-spectrum antibiotics and the large number of patients having negative blood culture samples and thus receiving unnecessary antibiotic treatment, are important contributors to the increase of antimicrobial resistance13,14,15. Thus, sensitive, rapid, cost-efficient and specific detection of pathogens in blood, followed by antimicrobial testing, is critical to de-escalate empirical antibiotic therapy and decrease the negative impact of BSIs2,14,16.

Blood cultures remain the reference standard for the detection of bacteria causing sepsis17. Generally, blood samples are collected and aseptically inoculated in bottles with specific media for aerobic and anaerobic microorganisms. These bottles are then incubated either in manual or in automatic systems that continuously monitor microbial growth17.

The conventional culture methods for diagnosis of BSIs involve sub-culturing and Gram staining upon blood-culture positivity, followed by phenotypic methodologies for bacterial identification and antibiotic susceptibility testing. These procedures can be accurate and reliable but are laborious and time-consuming18. In the last decade, other detection techniques have emerged as alternatives to conventional culture methods for the detection of BSIs, directly from positive blood cultures or from whole blood, and have been improved the time needed for pathogen identification. These include the Polymerase Chain Reaction (PCR)19,20, Peptide Nucleic Acid Fluorescence In Situ Hybridisation (PNA-FISH)21,22, Matrix-Assisted Laser Desorption Ionization Time-of-Flight Mass Spectrometry (MALDI-TOF MS)23 and DNA microarrays24. However, these methods present some drawbacks, namely: PCR-associated amplification problems (such as PCR inhibitors)25, unspecific hybridization, which can be caused by the human DNA interference with primers and probes25,26, infidelity in DNA replication, interference of non-microbial material17,25, limited number of available probes18, the results obtained are complex and difficult to interpret26, and are unable to distinguish between live and dead cells leading to the occurrence of false positives25,26. Moreover, pathogen detection directly from blood samples remains a challenge due to the innumerable blood components that can interfere in the analysis25,26 and to the low bacterial load normally present in the blood from patients with BSIs (1 to 100 CFU mL−1)26,27. Consequently, most of the detection methods for BSIs are dependent on blood cultures to increase the number of pathogens before the diagnostic test can be conducted17.

A promising approach for bacterial detection is the use of bacteriophages (phages) or phage-derived proteins as specific probing elements in conjugation with measurement techniques or biosensors. Phages are viruses that infect bacteria with high host specificity28. At the end of their life cycle, phages produce enzymes, called endolysins, to degrade the bacterial cell wall for the release of progeny virions. These proteins have been considered valuable tools to detect and control bacterial infections29,30,31,32,33. Endolysins from phages infecting Gram-positive bacteria present a modular structure composed of at least one enzymatic catalytic domain (ECD) and one cell binding domain (CBD)29. Most staphylococcal phage endolysins have three distinct domains: two ECDs, namely an N-terminal cysteine histidine-dependent amidohydrolase/peptidase (CHAP) domain and a central N-acetylmuramoyl-L-alanine amidase (Ami_2 or Ami_3) domain; and a C-terminal bacterial src-homology 3 (SH3b) domain as CBD34,35. Generally, the C-terminal CBD is responsible for directing the enzyme to its substrate by recognizing specific ligands on the bacterial peptidoglycan or other cell wall-associated molecules with extreme specificity and affinity30,36. Therefore, CBDs have been used as probing elements for the rapid detection or concentration of bacteria32,37,38, mainly foodborne pathogens31. The CBDs binding spectra are usually broader than the host ranges of the corresponding phage and can encompass entire bacterial genera39 and their binding affinity to bacterial cells is equal or even higher than antibodies36. Moreover, phage proteins have shown increased stability to temperature and pH variations, less propensity to aggregation and a faster, easier and less expensive production in comparison with antibodies40,41.

Flow cytometry is a multiparametric high-throughput technique which enables the detection and quantification of cells or particles individually in a flow, allowing a rapid and effective analysis of their physical and chemical properties within a population42. The cells are often labelled with fluorescent markers, therefore allowing the discrimination of different populations in a sample42. In the past years, this technique has been widely used for pathogen detection purposes, although the assays that have been described present some drawbacks, such as being laborious and expensive43 or lack the ability to detect pathogens in biological samples44,45.

In this study, we describe a novel flow cytometry assay based on phage-derived proteins for the detection of Staphylococcus in blood. For this, we exploited different domains at the C-terminus of the S. aureus phage endolysin E-LM1246 (Amidase, SH3 and Amidase+SH3) in order to select the truncation that presents the higher binding affinity and specificity for Staphylococcus spp. to be used as a specific probe in the detection assay. To the best of our knowledge, this is the first detection method described in the literature, in which a CBD was used as a recognition molecule in a flow cytometry assay, enabling the sensitive and specific detection of Staphylococcus in blood.

Results

Bioinformatics analysis of E-LM12

After identifying the endolysin gene E-LM12 (gp159) from the S. aureus vB_SauM-LM12 phage genome46, a BLAST analysis revealed that E-LM12 shows high similarity with endolysins from several staphylococcal phages, including Staphylococcus phage MCE-2014 (100% coverage, 95% identity)47, Staphylococcus phage phiIPLA-RODI (100% coverage, 94% identity)48 and Staphylococcus phage vB_SauM_0414_108 (99% coverage, 95% identity)49. Also, no similarity was found with endolysins from phages infecting other bacterial genera. The search for functional domains predicted the existence of three domains (Fig. 1): an N-terminal CHAP catalytic domain, a central Amidase_2 catalytic domain and a C-terminal SH3b_5 cell binding domain46. In the same region of the Amidase_2, a peptidoglycan recognition protein (PGRP) domain was also predicted.

Figure 1
figure1

Prediction of E-LM12 endolysin domains and schematic representation of the different fragments that were cloned. The endolysin contains a N-terminal CHAP catalytic domain, a central Amidase-2 domain, and a C-terminal SH3b_5 binding domain.

Functional analysis of the E-LM12 endolysin C-terminus

Three different fragments from the C-terminus of the E-LM12 endolysin46 were cloned (AMI, SH3 and AMI_SH3) fused to a green fluorescent protein (GFP), originating the recombinant proteins GFP-AMI, GFP-SH3 and GFP-AMI_SH3 (Fig. 1). The binding ability of these proteins was assessed by epifluorescence microscopy through the observation of cells emitting green fluorescence. The results showed that the fusion proteins GFP-SH3 and GFP-AMI_SH3 were capable of binding to S. aureus cells, with the GFP-AMI_SH3 clearly displaying a higher binding ability than the GFP-SH3, as observed by the intensity of the green fluorescence at the microscope (Fig. 2A,B). Conversely, no fluorescent cells were observed when the GFP-AMI protein (Amidase domain) was added to the host bacteria (Fig. 2C).

Figure 2
figure2

Fluorescence microscopy images of the different domains of E-LM12 endolysin and specificity assay of GFP-AMI_SH3. S. aureus Sa12 cells incubated with: GFP-SH3 (A), GFP-AMI_SH3 (B) and GFP-AMI (C). Assessment of the binding affinity of GFP-AMI_SH3 protein after incubation with: S. aureus Sa26 (D), Staphylococcus epidermidis M129 (E) and Klebsiella pneumoniae 37 (F). Observations were made in bright field and under FITC filter with the same exposure time to detect the presence/absence of fluorescing cells. Scale bar represents 10 µm.

Specificity and sensitivity of GFP-AMI_SH3 and comparison with the lytic activity of LM12 phage and E-LM12 endolysin

Considering that the GFP-AMI_SH3 revealed a higher binding ability to S. aureus cells, the binding spectrum and specificity of this protein was evaluated by epifluorescence microscopy. For this, the protein was incubated with strains of Staphylococcus spp. and other Gram-positive and Gram-negative bacteria (Table 1). Simultaneously, bacterial cell samples without GFP-AMI_SH3 and the GFP individually were used as negative controls. All the strains tested and the respective results are summarized in Table 1.

Table 1 Lytic spectrum of LM12 phage and binding affinity of GFP-AMI_SH3 protein obtained by flow cytometry and epifluorescence microscopy assays.

The results demonstrated that the GFP-AMI_SH3 binding spectrum covered all staphylococcal strains tested including 12 S. aureus (representative example in Fig. 2D) and 10 other staphylococcal species (example in Fig. 2E), including CoNS. Some weak binding was visualized for Enterococcus faecium LMV-0-42, Enterococcus faecalis LMV-0-39 and Streptococcus pneumoniae R6st (see examples in Supplementary Fig. S1 online). In these cases, the fluorescence intensities were lower than the obtained for Staphylococcus species and its distribution was not homogeneous along the bacterial cell wall surfaces, with some intense dots randomly distributed along the cells. In contrast, no fluorescent cells were detected on the other 17 non-Staphylococcus spp. strains tested with GFP-AMI_SH3, including Gram-positive and Gram-negative bacteria (example in Fig. 2F). Also, control experiments with unlabelled cells and GFP individually did not display green fluorescence.

The binding affinity of GFP-AMI_SH3 was compared with the lytic activity of LM12 phage using the same strains (Table 1). The phage showed a lytic effect against all Staphylococcus spp. strains tested, presenting “lysis from without” (LFW)50 on five Staphylococcus strains, and was unable to lyse the S. haemolyticus strain. The phage also revealed LFW when tested against E. faecalis LMV-0-39 and E. faecium LMV-0-42 but did not lyse the other non-staphylococcal strains (Table 1). The E-LM12 endolysin showed a lytic activity similar to the binding affinity of GFP-AMI_SH3, being able to lyse all the Staphylococcus strains tested (Table 1) when concentrations equal to or higher than 5 µM were used.

Flow cytometry assays

Exploitation of the C-terminus E-LM12 endolysin domains as recognition molecules

In order to select the recognition molecule to be used on the flow cytometry assays, the three fusion proteins (GFP-AMI, GFP-AMI_SH3 and GFP-SH3) were incubated with S. aureus cells and samples were analysed using a flow cytometer equipped with a laser capable of exciting the GFP. The cells that were decorated with the proteins emitted green fluorescence, which was detected on the channel FL1, therefore allowing for the discrimination between labelled and unlabelled cells.

The results indicate that the GFP-AMI_SH3 showed the highest binding efficiency, decorating most of the S. aureus cells (about 99% of the population was in the positive quadrant) (Fig. 3A) when compared with the GFP-SH3 that stained only 39% of the population (Fig. 3B). Moreover, the intensity of the green fluorescence (FL1) of the positive population when using the GFP-AMI_SH3 protein was much higher compared with that using the GFP-SH3 protein, corroborating the results of the fluorescence microscopy assays. Conversely, the GFP-AMI revealed a negligible binding (about 16% of the population) (Fig. 3C), which was probably due to some sample residues or free protein that was not completely washed since no green fluorescent cells were detected by fluorescence microscopy (Fig. 2C).

Figure 3
figure3

Flow cytometry analysis of the different domains of E-LM12 endolysin. Dot plots showing side scattering (SS) and green fluorescence (FL1) of S. aureus Sa12 cells after incubation with: GFP-AMI_SH3 (A), GFP-SH3 (B) and GFP-AMI (C).

Considering that the GFP-AMI_SH3 revealed a higher binding ability to S. aureus cells than the other fragments tested, this protein was chosen for further experiments.

Evaluation of detection parameters

Several detection parameters were assessed on the flow cytometry assays, using the GFP-AMI_SH3 as a recognition molecule. These comprised the specificity and sensitivity against staphylococcal and other Gram-positive and Gram-negative strains (Table 1) and the detection limit.

The assays clearly demonstrated that the developed method was able to specifically detect all the Staphylococcus spp. strains tested, including S. aureus, S. epidermidis, S. equorum, S. haemolyticus, S. hominis and S. warneri (Table 1). As depicted in Fig. 4A, the histograms of the Staphylococcus spp. strains were in the right side with fluorescence values beginning in 100 a.u. while the histogram of a non-staphylococcal bacteria was shifted to the left. Moreover, the fluorescence intensity means were similar for S. aureus Sa12 and other staphylococcal strains (means of 2,142.4 ± 373.2 a.u. and 1,665.4 ± 241.2 a.u., respectively), but were considerable different from the non-Staphylococcus strains tested (mean of 7.7 ± 4.4 a.u.) (Fig. 4B). Also, mean fluorescence intensity from labelled Staphylococcus spp. strains was around 200-fold higher than the value obtained from unlabelled S. aureus cells (NL), used as negative control (mean of 7.4 ± 2.1 a.u.) (Fig. 4B).

Figure 4
figure4

Graphical representation of the specificity and detection limit of the flow cytometry assays. (A) Overlay of the different histograms obtained by flow cytometry after incubation of GFP-AMI_SH3 with different bacterial strains. In black: A. baumannii 13; blue: S. aureus Sa12; green: S. warneri SECOMF16; purple: S. aureus Sa26; and yellow: S. epidermidis RP62A. (B) Mean of the fluorescence intensity (in arbitrary units (a.u.)) after incubation of GFP-AMI_SH3 with: S. aureus Sa12 at different concentrations (104 CFU mL−1 to 108 CFU mL−1); “OS”- Other Staphylococcus - S. warneri SECOMF16, S. aureus Sa26 and S. epidermidis RP62A (108 CFU mL−1); and “NS” - non-staphylococcal bacteria- A. baumannii 13, K. pneumoniae 35 and P. aeruginosa PA3 (108 CFU mL−1). Error bars represent standard deviations from three independent experiments performed in duplicate. *Statistically significant (p value <0.05) differences of fluorescence intensity mean values from the unlabelled S. aureus Sa12 (NL).

For the determination of the detection limit, different concentration of S. aureus Sa12 cells (ranging from 1 × 104 CFU mL−1 to 1 × 108 CFU mL−1) incubated with GFP-AMI_SH3 were analysed through the flow cytometer. Based on these assays, the minimum concentration of bacteria for which it was possible to consider a positive signal, significantly different from the controls (unlabelled cells and labelled non-Staphylococcus strains), was 105 CFU mL−1 (Fig. 4B).

Detection of S. aureus in spiked blood samples

The flow cytometry assay was adapted and optimized in order to assess its ability to specifically detect S. aureus in artificially seeded blood samples. For this, as a proof-of-concept, horse blood was inoculated with 1 to 5 CFU mL−1 of S. aureus Sa12, followed by an enrichment for 16 hours. Samples were processed following an optimized procedure, which included treatment with water to deplete the red blood cells followed by centrifugations. Samples were then incubated with GFP-AMI_SH3 and analysed by flow cytometry. As a negative control, blood was mixed with medium without bacteria and submitted to the same procedure as the spiked samples, to evaluate unspecific binding of the fusion protein. In addition, unlabelled S. aureus Sa12 and a blood sample without protein were used as controls for the autofluorescence of bacterial cells and blood components, respectively.

The results represented in Fig. 5 revealed that the GFP-AMI_SH3 combined with flow cytometry was successfully able to detect S. aureus cells in blood cultures. The protein was capable of decorating S. aureus cells, allowing the detection of about 99% of that population (Fig. 5A). On the contrary, blood samples incubated with GFP-AMI_SH3 showed a negligible signal (about 0.35%) (Fig. 5B). In addition, the blood samples without GFP-AMI_SH3 (Fig. 5C) and the unlabelled S. aureus cells (Fig. 5D) did not emit a detectable fluorescence.

Figure 5
figure5

Graphical representation of blood samples analysis by flow cytometry. Representative dot plots showing side scattering (SS) and green fluorescence intensity (FL1) of: blood culture with S. aureus Sa12 decorated with GFP-AMI_SH3 (A); blood with GFP-AMI_SH3 (B); blood (C); blood culture with S. aureus Sa12 (D); blood culture with K. pneumoniae 35 (Kp35) incubated with GFP-AMI_SH3 (E); and blood culture with K. pneumoniae 35 (Kp35) (F).

A specificity test was performed with K. pneumoniae 35 as negative control bacteria, following the same procedure used for S. aureus cells. The biparametric dot plot is displayed in Fig. 5E, demonstrating that only a minor number of events were recorded as positives (0.03% of the population), which was similar to the unlabelled K. pneumoniae cells (Fig. 5F). Moreover, since under the epifluorescence microscopy, GFP-AMI_SH3 showed a slight binding to E. faecalis LMV-0-39 and E. faecium LMV-0-42, these bacteria were further spiked in blood and the fluorescence was measured by flow cytometry. The results demonstrated that only a low percentage of the bacterial population (<5%) was plotted as positive (see Supplementary Fig. S2 online), which can be interpreted as a negligible signal.

Overall, the fluorescence signal obtained from the S. aureus samples decorated with GFP-AMI_SH3 was clearly distinguishable from the background signal (Fig. 6). The mean fluorescence intensity of labelled S. aureus cells (Fig. 6A) was 10-fold higher than the mean value obtained from the blood samples with GFP-AMI_SH3 (Fig. 6B) (means of 2,136.8 ± 145.6 and 204.6 ± 99.8 a.u., respectively). The weak fluorescence signal measured on the labelled blood samples can be attributed to the presence of free protein that has not been completely washed or to the incomplete lysis of erythrocytes which are known to have some autofluorescence43. The blood sample (Fig. 6C) and the unlabelled S. aureus cells (Fig. 6D) displayed minimal fluorescence intensity means (6.7 ± 4.4 and 42.8 ± 6.2 a.u., respectively). Also, the signal obtained for K. pneumoniae (Fig. 6E) was significantly (p < 0.001) lower than the one obtained for S. aureus (Fig. 6A) and similar to the mean value obtained from unlabelled K. pneumoniae cells (Fig. 6F). Pairwise multiple comparisons were performed between all tested samples, and the results revealed that the mean fluorescence intensity of the signal emitted from S. aureus Sa12 cells labelled with GFP-AMI_SH3 was significantly different (p < 0.001) comparing with the mean value of fluorescence signal from the control samples namely blood, blood with GFP-AMI_SH3, unlabelled S. aureus and K. pneumoniae cells, and K. pneumoniae with GFP-AMI_SH3. Moreover, no statistically significant differences (n.s) were obtained when comparing these control samples (Fig. 6).

Figure 6
figure6

Graphical representation of the mean of the fluorescence intensity of blood samples analysed by flow cytometry. Mean of the fluorescence intensity of: blood culture with S. aureus Sa12 decorated with GFP-AMI_SH3 (A); blood with GFP-AMI_SH3 (B); blood (C); blood culture with S. aureus Sa12 (D); K. pneumoniae 35 blood culture with GFP-AMI_SH3 (E); and K. pneumoniae 35 blood culture (F). All the strains were at 108 CFU mL−1, after a 16 hours inoculum (approximately 1 CFU mL−1) in blood. Error bars represent standard deviations from three independent experiments. Statistically highly significant differences (p < 0.001) of pairwise comparisons between the mean of the fluorescence intensity of labelled S. aureus Sa12 cells among all possible conditions (***) were determined by one-way ANOVA with a post-hoc Tukey’s multiple comparisons test.

Discussion

BSIs and sepsis are the leading causes of human mortality among hospitalized patients and thus have a great impact on healthcare systems. Staphylococci are frequently isolated bacteria from BSIs and therefore their rapid identification from blood would allow the early diagnosis of a possible septicaemia7,10.

In this study, a new endolysin-based flow cytometry assay was developed for the early detection of Staphylococcus in blood. Firstly, different domains at C-terminus of S. aureus E-LM12 endolysin were cloned fused to GFP, expressed and functionally analysed. The results revealed that the GFP-SH3 protein was able to bind to S. aureus cells, which is in accordance with previous studies that reported that SH3 is the binding domain of endolysins in general29,39,51 and of Staphylococcus phage endolysins in particular39,52. Interestingly, GFP-AMI_SH3 protein, which contains the amidase and SH3 domains, presented a higher binding efficiency to S. aureus cells than the GFP-SH3, suggesting that the amidase domain contributes to a more efficient binding of the SH3. This might be explained by the PGRP domain that was predicted in the same region of the Amidase_2, and that comprises conserved pattern recognition molecules that bind to bacterial peptidoglycan53. However, when the Amidase_2 domain (GFP-AMI) was used alone with S. aureus cells did not present any binding capacity. A previous study also showed that the amidase domain improved the binding affinity of a staphylococcal CBD to target bacterial cells, which resulted in an enhanced lytic activity of the endolysin54.

The specificity and sensitivity assays performed with the GFP-AMI_SH3 revealed that this protein was able to bind to all Staphylococcus spp. tested. This constitutes an advantage of this biorecognition molecule once these pathogens have been frequently isolated from ICU infections55, being the CoNS and S. aureus responsible for 20.5% and 8.7% of ICU-acquired BSIs in Europe, respectively55. Other authors also reported a binding spectrum at the genus level for other CBDs from Staphylococcus endolysins39,52,56. Some studies suggested that CBDs recognize conserved binding ligands such as the glycine-rich inter-peptide bridge common to most staphylococcal strains57,58,59, as it has been reported for the SH3b-like cell wall targeting domain of lysostaphin60, which can explain their broad host range. Curiously, the GFP-AMI_SH3 protein demonstrated some binding affinity to two Enterococcus strains and one S. pneumoniae strain. Although the binding affinity of GFP-AMI_SH3 was not high and only few Enterococcus and Streptococcus cells were recognized, it can be hypothesized that the GFP-AMI_SH3 binds to ligands of peptidoglycan in the bacterial cell wall that are conserved among these bacteria genera. In fact, although these bacterial species are members of two distinct phylogenetic orders namely Bacillales for Staphylococcus and Lactobacillales for Streptococcus and Enterococcus, they present peptidoglycan structures relatively similar apart from their cross-bridges that vary widely in composition and length59. Other authors also reported a broader binding affinity of endolysins and CBDs, showing recognition to other bacterial species61,62, such as the enterococcal PlyV12 endolysin which kills enterococcal, streptococcal and staphylococcal strains62 and the Staphylococcus SH3b domain of endolysin LysF1 that binds to Staphylococcus and Streptococcus species58. We can also hypothesise that the amidase domain plays a role in the binding of SH3b to other bacterial species. Further investigations into the nature of the SH3 receptor molecules and the amidase domain are needed, which may be important for the understanding of the binding mechanisms of other endolysin CBDs as well.

The endolysin E-LM12 demonstrated capability to lyse all the Staphylococcus strains tested, including CoNS. These results are in agreement with other studies that report that Staphylococcus phage endolysins present a broad lytic activity covering all the Staphylococcus genus and commonly their spectrum is similar to the one from their CBD56,63. Also, the amino acid sequence of E-LM12 is very conserved, being closely related to several staphylococcal endolysins, namely LysK, which was described to be effective against S. aureus and CoNS64.

Regarding the LM12 phage, it exhibited a lytic effect against most of the Staphylococcus spp., although in some strains “lysis from without” was observed, which indicates the absence of phage infection50. On the other hand, the GFP-AMI_SH3 protein bound to all the staphylococcal strains tested, demonstrating its higher potential as a recognition probe for Staphylococcus spp. when compared with the phage particle.

Regarding the flow cytometry assays, the results indicate that this methodology was able to specifically detect all the Staphylococcus species tested and no false positives or false negatives were obtained. In this study, the developed assay revealed to be capable of detecting 105 CFU mL−1 of S. aureus cells without enrichment, which was expected since the minimal concentration of bacteria detectable by flow cytometry is reported to be in the range of 103 to 104 CFU mL−1, using viability stains65. The detection around these limits affects the precision of the measurements due to the relatively poor analytical sensitivity65.

The flow cytometry assay had to be adapted and optimized for the detection of Staphylococcus in blood samples since the number of microorganisms present in circulation during a BSI ranges from 1 to 100 CFU mL−1 26,27. Therefore, a sample preparation method was designed to include a pre-enrichment step, allowing the effective detection of 1–5 CFU of Staphylococcus in 10 mL of blood. The enrichment procedure also assures the detection of viable cells66, preventing the occurrence of false positives. Moreover, the developed method avoided the occurrence of positive signals derived from the autofluorescence of blood components26,43,67 and revealed a good analytical reproducibility with results that were easily and objectively interpreted.

The conventional culture methods for the detection of Staphylococcus in blood are time-consuming and laborious. In fact, the mean time to blood culture positivity of S. aureus is reported to be between 12 to 16 hours68,69,70 and after this, the phenotypic tests must be implemented to identify the specific pathogen which takes about 12 to 36 hours17. The assay described herein took less than 2 hours to perform after a pre-enrichment step, and therefore provides a rapid, highly sensitive and reliable methodology for the detection of pathogens in blood, outstanding the standard method of BSI diagnosis. Moreover, in this case, the extensive time required for bacterial enrichment was due to the initial bacterial load of 1 CFU per 10 mL of blood. Considering that the time to blood culture positivity is inversely proportional to the initially inoculated concentration71, the turnaround time of our assay can be significantly reduced if a higher concentration of Staphylococcus is present in patient blood samples.

Very few phage-based assays have been described in the literature for the detection of bacteria directly from blood72,73,74. Our implemented method presents several advantages over others which require extensive sample pre-treatment74,75,76, genetic manipulation of phage genomes73, complex instrumentation22,75,76,77, expensive biorecognition molecules22,43,77,78 or entail nucleic acids extraction to complete the detection74,75,76.

In summary, in this study, we have identified the C-terminal fragment of a Staphylococcus endolysin that presents a high binding affinity and specificity, which is composed not only of the obvious SH3b domain but also of the Amidase_2 domain. Moreover, we developed a novel and highly reliable endolysin-based flow cytometry assay that allows the rapid and specific detection and identification of Staphylococcus spp. from blood cultures.

The designed flow cytometry assay presents several advantages over other bacterial detection methods described in the literature, such as the high specificity rendered by the use of specific phage proteins, simple and inexpensive sample preparation, and the possibility to be tailored to detect other pathogens by using target-specific CBDs. Furthermore, the method can be adapted to a multiplex assay, if specific CBDs are fused with different coloured fluorescent proteins, allowing the simultaneous detection of pathogens prevalent in BSIs. The developed method can also be easily adapted to different clinical samples and types of bacterial infections, by adjusting the sample preparation methodology.

This work is a proof-of-concept that this novel phage endolysin-based flow cytometry assay can be employed in blood samples for the specific detection of bacterial cells. We envisage its validation in blood samples from septic patients in order to be implemented in a clinical environment.

Material and Methods

Bacterial strains and growth conditions

The bacterial collection strains were obtained from the Spanish Type Culture Collection (CECT) and clinical isolates were provided by the Hospital of Braga (Portugal). To complete the binding spectrum, additional Gram-positive and Gram-negative species from private collections were used. This accounts for a total of 42 strains used (Table 1), including 12 S. aureus, 10 non-S. aureus staphylococcal strains, and 9 representative Gram-positive and 11 Gram-negative bacteria.

The strains were routinely grown in Tryptic Soy Broth (TSB) (VWR Chemicals) and in Luria Bertani (LB) (Liofilchem) at 37 °C under agitation (120 rpm) or in solid plates, obtained by adding 12 g L−1 of agar (Liofilchem). Escherichia coli BL21 (DE3) cells were grown in LB supplemented with kanamycin 50 μg mL−1 (NZYTech). The bacterial growth was determined by measuring the optical density at 620 nm (OD620 nm) in 96-well plates (Orange Scientific) using a Multiskan™ FC Microplate Photometer (Thermo Fisher Scientific).

In Silico analysis of staphylococcal endolysin

The E-LM12 (NCBI Reference Sequence: AUV56903.1) was previously identified as an endolysin belonging to the S. aureus vB_SauM-LM12 phage (NCBI Reference Sequence: MG721208.1)46. The sequence was analysed through BLAST79 to find possible homologous sequences. The search for functional domains was carried using Pfam80, HHpred81 and InterProScan82. The molecular weight and isoelectric point of the proteins were calculated using the Compute pI/Mw program ExPASy83.

Cloning of E-LM12 endolysin domains

Primers containing specific restriction cloning sites (Table 2) were designed to amplify different fragments of the E-LM12 C-terminus (Fig. 1) and insert them into the pET_GFP plasmid32 (plasmid pET28a(+) from Novagen with the Aequorea coerulescens GFP gene inserted between the NdeI and BamHI restriction sites). Three different fragments (Supplementary Material S3) were amplified by PCR: a fragment containing only the Amidase domain (referred as GFP-AMI); another containing only the SH3 domain (GFP-SH3); and one containing both domains (GFP-AMI_SH3). Primer melting temperatures were calculated using OligoCalc84. The fragments were amplified with Phusion DNA Polymerase (Thermo Fisher Scientific) with vB_SauM-LM12 phage as template DNA. The PCR protocol consisted of an initial denaturation step at 98 °C for 30 s; followed by 35 cycles of: denaturation at 98 °C for 10 s, annealing at 60 °C for 30 s and elongation at 72 °C for 1 min; and a final extension step at 72 °C for 10 min. The products were then digested with the restriction enzymes (Table 2), inserted into the pET_GFP (in order to fuse them with the GFP upstream) and ligated with the T4 ligase (New England Biolabs) to obtain the different constructions. The ligation was transformed into competent E. coli BL21 (DE3). Colonies were screened through colony PCR and positives were used for plasmid extraction and further confirmation through Sanger sequencing.

Table 2 Oligonucleotide primers used for cloning and the respective restriction enzyme used. Enzyme restriction sites are underlined.

Expression and purification of GFP fused proteins

E. coli BL21 cells harbouring each recombinant plasmid were grown at 37 °C in LB medium supplemented with 50 μg mL−1 of kanamycin until reaching an OD620nm = 0.5. Recombinant protein expression was induced with 1 mM isopropyl-β-D-thiogalactopyranoside (IPTG, Sigma-Aldrich), followed by incubation overnight on an orbital shaker at 16 °C, 120 rpm. In the case of E. coli BL21 pET28a‐GFP, the expression was carried out at 37 °C, 120 rpm, overnight.

Cells were harvested by centrifugation (9,000 × g, 15 min, 4 °C) and further resuspended in phosphate lysis buffer (20 mM sodium dihydrogen phosphate, 500 mM sodium chloride, pH 7.4). Cells were submitted to freezing (−80 °C) and thawing (30 °C) cycles (3 times) and disrupted by sonication at 40% power (Ultrasonic Processor, Cole Parmer CP 750) for 5 min (30 s ON / 30 s OFF). The cells were centrifuged (9,000 × g, 15 min, 4 °C) to recover the supernatant containing soluble proteins, which was passed through a nickel - nitrilotriacetic acid (Ni-NTA) column (Thermo Fisher Scientific). After washing steps (lysis buffer supplemented with 30 mM imidazole), the proteins were eluted with 300 mM imidazole. The purified proteins were analysed through SDS-PAGE (12% (w/v) acrylamide), followed by Blue Safe staining (NZYTech). The purified proteins were concentrated and dialyzed against 0.1 M phosphate buffer pH 7.2 (PB) using the centrifugal filters Amicon Ultra − 0.5 mL MWCO 10 KDa (Merck Millipore) and stored at 4 °C. Protein concentration was determined using the BCA Protein Assay Kit (Thermo Fisher Scientific) with bovine serum albumin (BSA) as standard.

Functional analysis of the E-LM12 endolysin C-terminus and specificity assays by epifluorescence microscopy

The binding ability of the different constructions of the E-LM12 endolysin C-terminus fused to GFP (GFP-AMI, GFP-AMI_SH3 or GFP-SH3) was inferred by fluorescence microscopy observations of S. aureus Sa12 cells after incubation with the fused proteins. Briefly, bacterial cells were grown in 10 mL of liquid LB or TSB at 37 °C until mid-log phase (OD620nm = 0.6) and then the culture was centrifuged for 5 min at 6,000 × g, followed by resuspension in 10 mL of PB. A volume of 500 µL of each bacterial suspension was centrifuged at 6,000 × g for 5 min. The pellet was resuspended in 20 µL of purified GFP fused protein (at a concentration of 5 µM) and incubated for 30 min at room temperature. The cells were washed three times with PB by centrifugation (6,000 × g, 5 min) to remove the unbound protein. The washed pellet was resuspended in 10 µL of PB and observed at the epifluorescence microscope equipped with U-RFL-T light source (Olympus BX51, Magnification 1,000×) in bright field and under the FITC filter (Excitation BP 470–490 nm; Emission: LP 516 nm). Control samples of bacterial cells without addition of the recombinant proteins were prepared simultaneously. GFP alone was used as a negative control.

For the assessment of the specificity and sensitivity of GFP-AMI_SH3, bacterial species listed in Table 1 were incubated with this protein, following the same procedure described above and observed at the epifluorescence microscope.

Phage lytic spectra

The host range specificity of the LM12 phage was screened against all strains listed in Table 1. Bacterial lawns were made on Tryptic Soy Agar (TSA) plates by mixing 100 µL of exponential-phase cell cultures of each strain with 3 mL of TSA soft overlays (TSB with 0.4% (w/v) of agar). The bacterial lawns were spotted with 10 µL drops of the phage solution (109 PFU mL−1). LM12 phage lysis was assessed by adding 10 µL drops of serial 10-fold dilutions of phage stock to the bacterial lawns. After 16–18 hours incubation at 37 °C, plates were inspected for lysis zones and results were scored as: “positive” for clear lysis areas; “negative” for the absence of lysis areas; and “lysis from without” (LFW) when clear areas were observed with high phage titers but no plaques appeared when lower phage concentrations were spotted50.

E-LM12 lytic activity

The E-LM12 lytic activity was carried out by the spot lysis test against all Staphylococcus strains listed in Table 1. Bacterial lawns were made on TSA plates by mixing 100 µL of exponential-phase cell cultures (OD620 nm = 0.4) of each strain with 3 mL of TSA soft overlays. The bacterial lawns were spotted with 10 µL drops of E-LM12 at different concentrations (2, 5, 8, 10 and 15 µM).

Flow cytometry assays

For the flow cytometry assays, the three different C-terminus domains of E-LM12 (GFP-AMI, GFP-AMI_SH3 or GFP-SH3) were initially tested against S. aureus Sa12 cells. Bacterial cells were grown in 10 mL of liquid LB or TSB at 37 °C until mid-log phase (OD620nm = 0.6). Briefly, 1 mL of each bacterial suspension was centrifuged at 6,000 × g for 5 min and the pellet resuspended in 20 µL of purified GFP fused protein at a concentration of 5 µM and incubated for 30 min at room temperature. The cells were washed twice with PB by centrifugation (6,000 × g for 5 min) to remove the unbound protein and cells were resuspended in 200 µL. The samples were analysed using an EC 800 flow cytometer equipped with a diode blue laser (excitation at 488 nm) (Sony Biotechnology). A total of 45,000 events were acquired with a sample flow rate of 10 μL min−1. The fluorescence was detected through a 525/50 nm band-pass filter on the channel FL1. Data analysis was performed using FCS Express 6 RUO software (De Novo Software).

For the evaluation of the specificity and sensitivity of GFP-AMI_SH3, this protein was incubated with the bacterial strains listed in Table 1, following the same procedure described above. Control samples of bacterial cells without addition of the recombinant protein were prepared simultaneously. The detection limit of the method was assessed by using different concentrations of S. aureus Sa12 ranging from 1 × 104 to 1 × 108 CFU mL−1, following the procedure described above. The bacterial loads were quantified by flow cytometry and by Colony-forming units (CFU) counting.

Detection of S. aureus in spiked blood samples

For the detection of S. aureus in artificially seeded blood, 10 mL of defibrinated horse blood (Thermo Fisher Scientific) was mixed with 90 mL of TSB culture medium. The blood sample was then inoculated with a concentration of 1 to 5 CFU mL−1 of S. aureus Sa12 and incubated 16 hours at 37 °C, 120 rpm. A non-inoculated sample was prepared in parallel and exposed to the same conditions to be used as a control. One millilitre of each sample was recovered, diluted 10 times in sterile water to promote the lysis of erythrocytes by osmotic stress, centrifuged at 6,000 × g for 10 min, washed twice with PB and then incubated with GFP-AMI_SH3 (at a concentration of 10 µM), following the procedure described before. To confirm the specificity of the assay, the strain Klebsiella pneumoniae 35 was used as a negative control, following the same procedure described for S. aureus. Moreover, since by epifluorescence microscopy, GFP-AMI_SH3 showed a weak binding to E. faecalis LMV-0-39 and E faecium LMV-0-42, these strains were tested by flow cytometry and E. faecalis CECT 184 was used as a negative control.

Statistical analysis

All results were analysed by One-way ANOVA test. The data are presented as means and standard deviations. Differences between samples were considered statistically significant for p-values lower than 0.05.

Accession number

The NCBI Reference Sequence of the endolysin E-LM12 is AUV56903.1.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

References

  1. 1.

    Walkey, A. J., Wiener, R. S. & Lindenauer, P. K. Utilization patterns and outcomes associated with central venous catheter in septic shock: a population-based study. Crit. Care Med. 41, 1450–7 (2013).

    PubMed  PubMed Central  Article  Google Scholar 

  2. 2.

    Mayr, F. B., Yende, S. & Angus, D. C. Epidemiology of severe sepsis. Virulence 5, 4–11 (2014).

    PubMed  Article  PubMed Central  Google Scholar 

  3. 3.

    Angus, D. C. & van der Poll, T. Severe Sepsis and Septic Shock. N. Engl. J. Med. 369, 840–851 (2013).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  4. 4.

    Martinez, R. M. & Wolk, D. M. Bloodstream Infections. Microbiol. Spectr. 4, 1–34 (2016).

    CAS  Google Scholar 

  5. 5.

    Lindsay, J. A. & Holden, M. T. G. Staphylococcus aureus: superbug, super genome? Trends Microbiol. 12, 378–385 (2004).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  6. 6.

    Becker, K., Heilmann, C. & Peters, G. Coagulase-negative staphylococci. Clin. Microbiol. Rev. 27, 870–926 (2014).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  7. 7.

    Vincent, J.-L. et al. International Study of the Prevalence and Outcomes of Infection in Intensive Care Units. JAMA 302, 2323 (2009).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  8. 8.

    Tong, S. Y. C. et al. Staphylococcus aureus infections: epidemiology, pathophysiology, clinical manifestations, and management. Clin. Microbiol. Rev. 28, 603–61 (2015).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  9. 9.

    Bergin, S. P., Holland, T. L., Fowler, V. G. & Tong, S. Y. C. Bacteremia, Sepsis, and Infective Endocarditis Associated with Staphylococcus aureus. In Current Topics in Microbiology and Immunology 409, 263–296 (2015).

    Google Scholar 

  10. 10.

    Le Moing, V. et al. Staphylococcus aureus Bloodstream Infection and Endocarditis - A Prospective Cohort Study. PLoS One 10, e0127385 (2015).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  11. 11.

    Rhodes, A. et al. Surviving Sepsis Campaign: International Guidelines for Management of Sepsis and Septic Shock: 2016. Intensive Care Med. 43, 304–377 (2017).

    PubMed  Article  PubMed Central  Google Scholar 

  12. 12.

    Kumar, A. et al. Duration of hypotension before initiation of effective antimicrobial therapy is the critical determinant of survival in human septic shock. Crit. Care Med. 34, 1589–1596 (2006).

    PubMed  Article  PubMed Central  Google Scholar 

  13. 13.

    Lockhart, G. C., Hanin, J., Micek, S. T. & Kollef, M. H. Pathogen-Negative Sepsis—An Opportunity for Antimicrobial Stewardship. Open Forum Infect. Dis. 6 (2019).

  14. 14.

    Lambregts, M. M. C., Bernards, A. T., van der Beek, M. T., Visser, L. G. & de Boer, M. G. Time to positivity of blood cultures supports early re-evaluation of empiric broad-spectrum antimicrobial therapy. PLoS One 14, e0208819 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  15. 15.

    Pogue, J. M., Kaye, K. S., Cohen, D. A. & Marchaim, D. Appropriate antimicrobial therapy in the era of multidrug-resistant human pathogens. Clinical Microbiology and Infection 21, 302–312 (2015).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  16. 16.

    Guo, Y., Gao, W., Yang, H., Ma, C. & Sui, S. De-escalation of empiric antibiotics in patients with severe sepsis or septic shock: A meta-analysis. Hear. Lung J. Acute Crit. Care 45, 454–459 (2016).

    Article  Google Scholar 

  17. 17.

    Opota, O., Croxatto, A., Prod’hom, G. & Greub, G. Blood culture-based diagnosis of bacteraemia: State of the art. Clin. Microbiol. Infect. 21, 313–322 (2015).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  18. 18.

    Florio, W., Morici, P., Ghelardi, E., Barnini, S. & Lupetti, A. Recent advances in the microbiological diagnosis of bloodstream infections. Crit. Rev. Microbiol. 44, 351–370 (2018).

    PubMed  Article  PubMed Central  Google Scholar 

  19. 19.

    Lehmann, L. E. et al. A multiplex real-time PCR assay for rapid detection and differentiation of 25 bacterial and fungal pathogens from whole blood samples. Med. Microbiol. Immunol. 197, 313–324 (2008).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  20. 20.

    Chang, S.-S. et al. Multiplex PCR System for Rapid Detection of Pathogens in Patients with Presumed Sepsis – A Systemic Review and Meta-Analysis. PLoS One 8, e62323 (2013).

    ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

  21. 21.

    Parcell, B. J. & Orange, G. V. PNA-FISH assays for early targeted bacteraemia treatment. J. Microbiol. Methods 95, 253–255 (2013).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  22. 22.

    Almeida, C., Azevedo, N. F., Fernandes, R. M., Keevil, C. W. & Vieira, M. J. Fluorescence in situ hybridization method using a peptide nucleic acid probe for identification of salmonella spp. in a broad spectrum of samples. Appl. Environ. Microbiol. 76, 4476–4485 (2010).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  23. 23.

    Verroken, A. et al. Reducing time to identification of positive blood cultures with MALDI-TOF MS analysis after a 5-h subculture. Eur. J. Clin. Microbiol. Infect. Dis. 34, 405–413 (2015).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  24. 24.

    Laakso, S., Kirveskari, J., Tissari, P. & Mäki, M. Evaluation of High-Throughput PCR and Microarray-Based Assay in Conjunction with Automated DNA Extraction Instruments for Diagnosis of Sepsis. PLoS One 6, e26655 (2011).

    ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

  25. 25.

    Opota, O., Jaton, K. & Greub, G. Microbial diagnosis of bloodstream infection: towards molecular diagnosis directly from blood. Clin. Microbiol. Infect. 21, 323–331 (2015).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  26. 26.

    Skvarc, M., Stubljar, D., Rogina, P. & Kaasch, A. J. Non-culture-based methods to diagnose bloodstream infection: Does it work? Eur. J. Microbiol. Immunol. 3, 97–104 (2013).

    Article  Google Scholar 

  27. 27.

    Faridi, M. A. et al. Elasto-inertial microfluidics for bacteria separation from whole blood for sepsis diagnostics. J. Nanobiotechnology 15 (2017).

  28. 28.

    Schmelcher, M. & Loessner, M. J. Application of bacteriophages for detection of foodborne pathogens. Bacteriophage 4, e28137 (2014).

    PubMed  PubMed Central  Article  Google Scholar 

  29. 29.

    Loessner, M. J. Bacteriophage endolysins — current state of research and applications. Curr. Opin. Microbiol. 8, 480–487 (2005).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  30. 30.

    Schmelcher, M., Donovan, D. M. & Loessner, M. J. Bacteriophage endolysins as novel antimicrobials. Future Microbiol. 7, 1147–71 (2012).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  31. 31.

    Schmelcher, M. & Loessner, M. J. Bacteriophage endolysins: applications for food safety. Curr. Opin. Biotechnol. 37, 76–87 (2016).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  32. 32.

    Santos, S. B., Oliveira, A., Melo, L. D. R. & Azeredo, J. Identification of the first endolysin Cell Binding Domain (CBD) targeting Paenibacillus larvae. Sci. Rep. 9, 1–9 (2019).

    ADS  PubMed  PubMed Central  Article  CAS  Google Scholar 

  33. 33.

    Santos, S. B., Costa, A. R., Carvalho, C., Nóbrega, F. L. & Azeredo, J. Exploiting Bacteriophage Proteomes: The Hidden Biotechnological Potential. Trends Biotechnol. 36, 966–984 (2018).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  34. 34.

    Schmelcher, M. et al. Evolutionarily distinct bacteriophage endolysins featuring conserved peptidoglycan cleavage sites protect mice from MRSA infection. J. Antimicrob. Chemother. 70, 1453–1465 (2015).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  35. 35.

    Sass, P. & Bierbaum, G. Lytic activity of recombinant bacteriophage phi11 and phi12 endolysins on whole cells and biofilms of Staphylococcus aureus. Appl. Environ. Microbiol. 73, 347–52 (2007).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  36. 36.

    Loessner, M. J., Kramer, K., Ebel, F. & Scherer, S. C-terminal domains of Listeria monocytogenes bacteriophage murein hydrolases determine specific recognition and high-affinity binding to bacterial cell wall carbohydrates. Mol. Microbiol. 44, 335–49 (2002).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  37. 37.

    Kretzer, J. W. et al. Use of high-affinity cell wall-binding domains of bacteriophage endolysins for immobilization and separation of bacterial cells. Appl. Environ. Microbiol. 73, 1992–2000 (2007).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  38. 38.

    Schmelcher, M. et al. Rapid multiplex detection and differentiation of Listeria cells by use of fluorescent phage endolysin cell wall binding domains. Appl. Environ. Microbiol. 76, 5745–5756 (2010).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  39. 39.

    Gu, J. et al. LysGH15B, the SH3b domain of staphylococcal phage endolysin LysGH15, retains high affinity to staphylococci. Curr. Microbiol. 63, 538–42 (2011).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  40. 40.

    Wang, W., Singh, S., Zeng, D. L., King, K. & Nema, S. Antibody Structure, Instability, and Formulation. J. Pharm. Sci. 96, 1–26 (2007).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  41. 41.

    Singh, A., Arutyunov, D., Szymanski, C. M. & Evoy, S. Bacteriophage based probes for pathogen detection. Analyst 137, 3405 (2012).

    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

  42. 42.

    Davey, H. M. Flow cytometric techniques for the detection of microorganisms. Methods Cell Sci. 24, 91–97 (2002).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  43. 43.

    Azevedo, N. F. et al. Application of flow cytometry for the identification of Staphylococcus epidermidis by peptide nucleic acid fluorescence in situ hybridization (PNA FISH) in blood samples. Int. J. Gen. Mol. Microbiol. 100, 463–470 (2011).

    CAS  Google Scholar 

  44. 44.

    Shrestha, N. K., Wilson, D. A., Scalera, N. M., Oppedahl, A. & Procop, G. W. Immuno-flow cytometry for the rapid identification of Staphylococcus aureus and the detection of methicillin resistance. Eur. J. Clin. Microbiol. Infect. Dis. 31, 1879–1882 (2012).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  45. 45.

    Meng, X. et al. Sensitive Detection of Staphylococcus aureus with Vancomycin-Conjugated Magnetic Beads as Enrichment Carriers Combined with Flow Cytometry. ACS Appl. Mater. Interfaces 9, 21464–21472 (2017).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  46. 46.

    Melo, L. D. R., Brandão, A., Akturk, E., Santos, S. B. & Azeredo, J. Characterization of a new Staphylococcus aureus Kayvirus harboring a lysin active against biofilms. Viruses 10, 182 (2018).

    PubMed Central  Article  CAS  Google Scholar 

  47. 47.

    Alves, D. R. et al. Combined Use of Bacteriophage K and a Novel Bacteriophage To Reduce Staphylococcus aureus Biofilm Formation. Appl. Environ. Microbiol. 80, 6694–6703 (2014).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  48. 48.

    Gutiérrez, D. et al. Two Phages, phiIPLA-RODI and phiIPLA-C1C, Lyse Mono- and Dual-Species Staphylococcal Biofilms. Appl. Environ. Microbiol. 81, 3336–3348 (2015).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  49. 49.

    Philipson, C. et al. Characterizing Phage Genomes for Therapeutic Applications. Viruses 10, 188 (2018).

    PubMed Central  Article  CAS  Google Scholar 

  50. 50.

    Abedon, S. T. Lysis from without. Bacteriophage 1, 46–49 (2011).

    PubMed  PubMed Central  Article  Google Scholar 

  51. 51.

    Schmelcher, M., Tchang, V. S. & Loessner, M. J. Domain shuffling and module engineering of Listeria phage endolysins for enhanced lytic activity and binding affinity. Microb. Biotechnol. 4, 651–662 (2011).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  52. 52.

    Linden, S. B. et al. Biochemical and biophysical characterization of PlyGRCS, a bacteriophage endolysin active against methicillin-resistant Staphylococcus aureus. Appl. Microbiol. Biotechnol. 99, 741–52 (2014).

    PubMed  Article  CAS  PubMed Central  Google Scholar 

  53. 53.

    Dziarski, R. Peptidoglycan recognition proteins (PGRPs). Mol. Immunol. 40, 877–886 (2004).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  54. 54.

    Son, B., Kong, M. & Ryu, S. The auxiliary role of the amidase domain in cell wall binding and exolytic activity of staphylococcal phage endolysins. Viruses 10, 1–12 (2018).

    Article  CAS  Google Scholar 

  55. 55.

    European Centre for Disease Prevention and Control. Healthcare-associated infections acquired in intensive care units - Annual Epidemiological Report 2016 (2018).

  56. 56.

    Chang, Y. & Ryu, S. Characterization of a novel cell wall binding domain-containing Staphylococcus aureus endolysin LysSA97. Appl. Microbiol. Biotechnol. 101, 147–158 (2017).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  57. 57.

    Mitkowski, P. et al. Structural bases of peptidoglycan recognition by lysostaphin SH3b domain. Sci. Rep. 9, 5965 (2019).

    ADS  PubMed  PubMed Central  Article  CAS  Google Scholar 

  58. 58.

    Benešík, M. et al. Role of SH3b binding domain in a natural deletion mutant of Kayvirus endolysin LysF1 with a broad range of lytic activity. Virus Genes 54(1), 130–139 (2018).

  59. 59.

    Schleifer, K. H. & Kandler, O. Peptidoglycan types of bacterial cell walls and their taxonomic implications. Bacteriol. Rev. 36, 407–77 (1972).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  60. 60.

    Grundling, A. & Schneewind, O. Cross-Linked Peptidoglycan Mediates Lysostaphin Binding to the Cell Wall Envelope of Staphylococcus aureus. J. Bacteriol. 188, 2463–2472 (2006).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  61. 61.

    Becker, S. C., Foster-Frey, J., Stodola, A. J., Anacker, D. & Donovan, D. M. Differentially conserved staphylococcal SH3b_5 cell wall binding domains confer increased staphylolytic and streptolytic activity to a streptococcal prophage endolysin domain. Gene 443, 32–41 (2009).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  62. 62.

    Yoong, P., Schuch, R., Nelson, D. & Fischetti, V. A. Identification of a broadly active phage lytic enzyme with lethal activity against antibiotic-resistant Enterococcus faecalis and Enterococcus faecium. J. Bacteriol. 186, 4808–12 (2004).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  63. 63.

    Chang, Y., Kim, M. & Ryu, S. Characterization of a novel endolysin LysSA11 and its utility as a potent biocontrol agent against Staphylococcus aureus on food and utensils. Food Microbiol. 68, 112–120 (2017).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  64. 64.

    O’flaherty, S., Coffey, A., Meaney, W., Fitzgerald, G. F. & Ross, R. P. The Recombinant Phage Lysin LysK Has a Broad Spectrum of Lytic Activity against Clinically Relevant Staphylococci, Including Methicillin-Resistant Staphylococcus aureus. J. Bacteriol. 187, 7161–7164 (2005).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  65. 65.

    Clarke, R. G. & Pinder, A. C. Improved detection of bacteria by flow cytometry using a combination of antibody and viability markers. Journal of Applied Microbiology 84 (1998).

  66. 66.

    Gill, A. The Importance of Bacterial Culture to Food Microbiology in the Age of Genomics. Front. Microbiol. 8, 777 (2017).

    PubMed  PubMed Central  Article  Google Scholar 

  67. 67.

    Dineva, M. A., Mahilum-Tapay, L. & Lee, H. Sample preparation: a challenge in the development of point-of-care nucleic acid-based assays for resource-limited settings. Analyst 132, 1193 (2007).

    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

  68. 68.

    Khatib, R. et al. Time to positivity in Staphylococcus aureus bacteremia: possible correlation with the source and outcome of infection. Clin. Infect. Dis. an Off. Publ. Infect. Dis. Soc. Am. 41, 594–598 (2005).

    Article  Google Scholar 

  69. 69.

    Kim, J., Gregson, D. B., Ross, T. & Laupland, K. B. Time to blood culture positivity in Staphylococcus aureus bacteremia: Association with 30-day mortality. J. Infect. 61, 197–204 (2010).

    PubMed  Article  PubMed Central  Google Scholar 

  70. 70.

    Siméon, S. et al. Time to blood culture positivity: An independent predictor of infective endocarditis and mortality in patients with Staphylococcus aureus bacteraemia. Clin. Microbiol. Infect. 25, 481–488 (2019).

    PubMed  Article  PubMed Central  Google Scholar 

  71. 71.

    Haimi-Cohen, Y., Vellozzi, E. M. & Rubin, L. G. Initial concentration of Staphylococcus epidermidis in simulated pediatric blood cultures correlates with time to positive results with the automated, continuously monitored BACTEC blood culture system. J. Clin. Microbiol. 40, 898–901 (2002).

    PubMed  PubMed Central  Article  Google Scholar 

  72. 72.

    Bhowmick, T. et al. Controlled multicenter evaluation of a bacteriophage-based method for rapid detection of Staphylococcus aureus in positive blood cultures. J. Clin. Microbiol. 51, 1226–30 (2013).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  73. 73.

    Schofield, D. A. et al. Bacillus anthracis diagnostic detection and rapid antibiotic susceptibility determination using ‘bioluminescent’ reporter phage. J. Microbiol. Methods 95, 156–161 (2013).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  74. 74.

    Sergueev, K. V., He, Y., Borschel, R. H., Nikolich, M. P. & Filippov, A. A. Rapid and Sensitive Detection of Yersinia pestis Using Amplification of Plague Diagnostic Bacteriophages Monitored by Real-Time PCR. PLoS One 5, e11337 (2010).

    ADS  PubMed  PubMed Central  Article  CAS  Google Scholar 

  75. 75.

    Hassan, M. M., Ranzoni, A. & Cooper, M. A. A nanoparticle-based method for culture-free bacterial DNA enrichment from whole blood. Biosens. Bioelectron. 99, 150–155 (2018).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  76. 76.

    Lopes, A. L. K. et al. Development of a magnetic separation method to capture sepsis associated bacteria in blood. J. Microbiol. Methods 128, 96–101 (2016).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  77. 77.

    Shen, H. et al. Rapid and Selective Detection of Pathogenic Bacteria in Bloodstream Infections with Aptamer-Based Recognition. ACS Appl. Mater. Interfaces 8, 19371–19378 (2016).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  78. 78.

    Hartmann, H., Stender, H., Schäfer, A., Autenrieth, I. B. & Kempf, V. A. J. Rapid identification of Staphylococcus aureus in blood cultures by S. aureus PNA FISH TM using flow cytometry. 43, 4855–4857 (2005).

  79. 79.

    Altschul, S. F., Gish, W., Miller, W., Myers, E. W. & Lipman, D. J. Basic local alignment search tool. J. Mol. Biol. 215, 403–410 (1990).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  80. 80.

    Finn, R. D. et al. Pfam: the protein families database. Nucleic Acids Res. 42, D222–D230 (2014).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  81. 81.

    Zimmermann, L. et al. A Completely Reimplemented MPI Bioinformatics Toolkit with a New HHpred Server at its Core. J. Mol. Biol. 430, 2237–2243 (2018).

    CAS  Article  Google Scholar 

  82. 82.

    Jones, P. et al. InterProScan 5: genome-scale protein function classification. Bioinformatics 30, 1236–1240 (2014).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  83. 83.

    Artimo, P. et al. ExPASy: SIB bioinformatics resource portal. Nucleic Acids Res. 40, W597–W603 (2012).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  84. 84.

    Kibbe, W. A. OligoCalc: an online oligonucleotide properties calculator. Nucleic Acids Res. 35, W43–W46 (2007).

    PubMed  PubMed Central  Article  Google Scholar 

  85. 85.

    Oliveira, F., Lima, C. A., Brás, S., França, Â. & Cerca, N. Evidence for inter- and intraspecies biofilm formation variability among a small group of coagulase-negative staphylococci. FEMS Microbiol. Lett. 362, 1–20 (2015).

    Article  CAS  Google Scholar 

  86. 86.

    Sousa, C., Henriques, M., Teixeira, P. & Oliveira, R. Reduction of Staphylococcus epidermidis adhesion to indwelling medical devices: A simple procedure. Br. J. Biomed. Sci. 65, 184–190 (2008).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  87. 87.

    Freitas, A. I. et al. Comparative analysis between biofilm formation and gene expression in Staphylococcus epidermidis isolates. Future Microbiol. 13, 415–427 (2018).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  88. 88.

    Cerca, N., Oliveira, R. & Azeredo, J. Susceptibility of Staphylococcus epidermidis planktonic cells and biofilms to the lytic action of staphylococcus bacteriophage K. Lett. Appl. Microbiol. 45, 313–317 (2007).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

Download references

Acknowledgements

This study was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the project Phages-on-chip PTDC/BTM-SAL/32442/2017 (POCI-01-0145-FEDER-032442) and the strategic funding of UID/BIO/04469/2019 unit and BioTecNorte operation (NORTE-01-0145-FEDER-000004) funded by the European Regional Development Fund under the scope of Norte2020 - Programa Operacional Regional do Norte. Susana Costa was supported by the grant SFRH/BD/130098/2017 from FCT. We would also like to acknowledge Professor Hermínia de Lencastre, Doctor Carina Almeida, and Doctor Nuno Cerca for gently providing some of the strains used in this study. We acknowledge Professor Paulo Freitas for providing some of the infrastructures to perform the experiments.

Author information

Affiliations

Authors

Contributions

C.M.C., J.A. and S.B.S. conceived and designed the experiments. S.P.C., N.M.D., L.D.R.M. performed the laboratory work. S.P.C., S.B.S., L.D.R.M., N.M.D. and C.M.C. analysed the data. S.P.C. and C.M.C. wrote the manuscript. All authors read, reviewed and approved the final manuscript.

Corresponding author

Correspondence to Carla M. Carvalho.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Costa, S.P., Dias, N.M., Melo, L.D.R. et al. A novel flow cytometry assay based on bacteriophage-derived proteins for Staphylococcus detection in blood. Sci Rep 10, 6260 (2020). https://doi.org/10.1038/s41598-020-62533-7

Download citation

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing