Sensitive and rapid detection of pathogenic bacteria from urine samples using multiplex recombinase polymerase amplification

Junge Chen a, Youchun Xu ab, He Yan a, Yunzeng Zhu a, Lei Wang bc, Yan Zhang c, Ying Lu a and Wanli Xing *ab
aState Key Laboratory of Membrane Biology, School of Medicine, Tsinghua University, Beijing 100084, China. E-mail: wlxing@tsinghua.edu.cn
bNational Engineering Research Center for Beijing Biochip Technology, Beijing 102206, China
cCollaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou 310003, China

Received 17th April 2018 , Accepted 25th June 2018

First published on 2nd July 2018


Bacterial infections may cause severe diseases such as tuberculosis, sepsis, nephritis and cystitis. The rapid and sensitive detection of bacteria is a prerequisite for the treatment of these diseases. The current gold standard for bacterial identification is bacteriological culture. However, culture-based identification takes 3–7 days, which is time-consuming and laborious. In this study, bacteria in urine samples were enriched using a portable filter-based pipette. Then, a centrifugal chip was constructed to detect multiple pathogenic bacteria from urine samples by integrating the DNA extraction, multiplex recombinase polymerase amplification (RPA) and fluorescent detection together. This eliminated the time-consuming cultivation step, and thus accelerated the diagnosis of the urinary tract infections (UTIs). The five major pathogenic bacteria in UTIs were detected in this study, which are Escherichia coli, Proteus mirabilis, Pseudomonas aeruginosa, Staphylococcus aureus and Salmonella typhimurium. Escherichia coli, Proteus mirabilis, Pseudomonas aeruginosa and Staphylococcus aureus were successfully detected with limits of detection of 100 CFU mL−1 from urine samples within 40 min. Salmonella typhimurium was successfully detected with a limit of detection of 1000 CFU mL−1 from urine samples. The chip-based bacteria detection proposed in this study is a promising tool for sensitive, accurate, and multiplex identification of bacteria in clinical urine samples of UTIs and bacteriuria.


Introduction

Urinary tract infections (UTIs) are some of the most common infectious diseases, affecting 150 million people each year worldwide.1 They occur more commonly in women than men. About 40% of women and 12% of men have a urinary tract infection at some time in their life.2 Serious sequelae of UTIs include frequent recurrences, pyelonephritis with sepsis, renal damage in young children, pre-term birth and complications caused by frequent antimicrobial use.3,4 Clinically, UTIs are categorized as uncomplicated or complicated.3 Complicated UTIs are defined by a urine bacterial concentration >105 CFU mL−1 in women and 104 CFU mL−1 in men. While for an uncomplicated UTI a bacterial concentration of 103 CFU mL−1 is considered to be clinically relevant.5 According to previous reports, bacterial infections account for approximately 90% of all UTIs.1,2,6Escherichia coli (E. coli) is the most common pathogenic microorganism of UTIs.7 However, other Gram-negative bacteria such as Enterococcus species, Proteus species, Klebsiella species, Pseudomonas species, and Salmonella species also play important roles in UTIs.8–10 The most common Gram-positive bacteria in UTIs is Staphylococcus aureus (S. aureus).11 Bacteriuria with S. aureus can occur through catheterization, urologic procedures, or seeding of the genitourinary tract. The treatment of UTIs usually relies on antibacterial medicine,12 but the choice of medication and the treatment period mainly depend on the types of pathogenic microorganisms and the patients' response to treatment.12 Therefore, the detection of pathogenic microorganisms in urine samples is essential for the diagnosis and treatment of UTIs. Currently, the gold standard of bacterial identification in urine samples is the urine bacteriological culture, which requires at least 3–7 days to identify the bacteria present.9 To reduce the diagnosis time, several approaches, such as flow cytometry, mass-spectrometry, capillary electrophoresis, DNA electrochemical detection, PCR and sequencing methods, have been used.13–16 However, these methods require tedious manual operations, specially trained personnel, and expensive laboratory instrumentation.14,17 These shortcomings limit the application of these methods in resource-constrained environments. Moreover, there is no effective way to simultaneously detect multiple pathogenic bacteria in the urine at the moment. Therefore, there is an urgent need to develop a point-of-care testing (POCT) device to provide a rapid, accurate, and multiplex detection of bacteria from pre-treated or even raw biomaterials without tedious manual operations. Such technology could be used both in laboratories to alleviate labor-consuming work and in hospitals and in the field for on-site detection.

Currently, several isothermal nucleic acid amplification technologies have been developed for the detection of pathogens, functioning as good alternatives to PCR-based diagnostics in laboratories with limited resources and point-of-care (POC) settings.18–26 RPA is a new isothermal nucleic acid amplification technology that employs recombinase-primer complexes to scan double-stranded DNA and facilitate strand exchange at cognate sites.21,24,27,28 Gp32 (single-stranded DNA binding protein) interacts with the displaced template strand to prevent the ejection of the primer by branch migration. Then, the primers are extended by Bsu polymerase.21 Thus, RPA does not require template denaturation and can be performed at a relatively low and constant temperature (37–42 °C). RPA can detect <10 copies of DNA in 30 min.21,27 Further, the sensitivity of RPA is similar to PCR.20 Therefore, RPA is a good choice for the rapid identification of pathogenic bacteria in UTIs.

To achieve nucleic acid analysis of bacteria, cell lysis is a primary and necessary step for the analysis of intracellular components.29,30 Currently, various microfluidic devices have been constructed to perform cell lysis.29–38 Chemical lysis is achieved through utilization of lysis buffer containing surfactants to damage lipids and proteins in the membrane.29 However, the lysis efficiency of chemical methods is not sufficient, especially for Gram-positive bacteria that have thicker cell walls than Gram-negative bacteria.39 In contrast, mechanical lysis is the most effective method for lysing cells that have thick cell walls.29,40

Centrifugal chips make it possible to integrate multiple analysis steps on a single disc. A variety of centrifugal chips have been used to detect viruses and bacteria. For instance, several fully integrated centrifugal microfluidic platforms have been constructed for the detection of the influenza A virus by using loop-mediated isothermal amplification (LAMP)22 and the identification of Bacillus by a microarray.37 Tae-Hyeong Kim used magnetic beads coated with antibodies to capture S. typhimurium, then lysed the bacteria by laser irradiation, and finally, directly amplified the lysate with RPA and detected the results by commercial strips.19 However, all of these methods only detect one type of bacteria or virus on a chip. For multiple target detection, Focke et al. successfully developed a polymer film for sensitive genotyping by real-time PCR on a centrifugal chip.41 Czilwik et al. developed a fully integrated “LabDisk” system using real-time PCR for identification of S. warneri, S. agalactiae, E. coli, and H. influenzae from serum samples.42 However, PCR-based detection takes a long time (up to 3 h and 45 min), which is not ideal for POCT applications.

In this study, bacteria in urine samples were enriched using a portable filter-based pipette. Then, a centrifugal chip was constructed to detect E. coli, S. aureus, S. typhimurium, P. mirabilis, and P. aeruginosa from urine samples by integrating the DNA extraction, multiplex recombinase polymerase amplification and fluorescent detection together. E. coli, S. aureus, P. mirabilis, and P. aeruginosa were detected with limits of detection (LODs) of 102 CFU mL−1 from urine samples. S. typhimurium was detected with a LOD of 103 CFU mL−1 from urine samples. The chip-based bacteria detection proposed in this study is a promising tool for sensitive, accurate, and multiplex identification of bacteria in clinical urine samples of UTIs and bacteriuria, which may accelerate the diagnosis of the UTIs.

Experimental

Bacterial culture and counting

E. coli (ATCC25922), S. aureus (ATCC 25923), S. typhimurium (ATCC 14028), P. mirabilis (CMCC 49005), P. aeruginosa (CVCC 3359), B. subtilis (ATCC 6633), and L. monocytogenes (ATCC 19119) were kindly gifted by the CapitalBio Corporation. E. coli, B. subtilis, and L. monocytogenes were cultured in 10 mL Luria-Bertani (LB) medium (Beijing, China) at 37 °C for 16–18 h at 200 rpm. Meanwhile, S. aureus, S. typhimurium, P. mirabilis, and P. aeruginosa were cultured in 10 mL Brain Heart Infusion (BHI) medium (AoBoXing Bio-Tech, Beijing, China) at 37 °C for 16–18 h at 200 rpm. To determine the concentration of the bacteria, bacteria were harvested by centrifugation, re-suspended in ddH2O, and then counted by serial dilution plating on solid agar media (LB agar for E. coli and BHI agar for S. aureus, S. typhimurium, P. mirabilis, and P. aeruginosa). Subsequently, the bacteria were diluted with sterile ddH2O to different concentrations for the following experiments.

The structure of the centrifugal chip

The structure of the centrifugal chip is illustrated in Fig. 1. The custom-made instrument for spinning, temperature control, and fluorescence detection is shown in Fig. 1A. The chip (diameter of 120 mm) was designed with AutoCAD 2015. The centrifugal chip was made of polymethyl methacrylate (PMMA) and fabricated by computer-controlled (CNC) milling (Hongyang Chensheng, Beijing, China). Fig. 1C shows an enlarged schematic of the centrifugal chip, which consists of the lysis chamber (depth: 1.5 mm), storage chamber (depth: 1.5 mm), quantitative chamber (depth: 1.5 mm), mixing chamber (depth: 1.5 mm), siphon valves (width: 300 μm, depth: 300 μm), and amplification chambers (1.3 mm depth). For multiplex bacterial detection, the amplification chamber was first preloaded with RPA primers and Mg(OAc)2 and dried at room temperature. Then, a stir bar and zirconia beads were placed into the lysis chamber. The siphon valves were modified to be hydrophilic using the hydrophilic reagent (2% Tween-20 in ethanol), while the hydrophobic valves were modified with EGC-1700 (3M, Shanghai, China). Then, the engraved side of the chip was sealed with pressure-sensitive adhesives (PSA, Adhesive Research, Shanghai, China). After that, the centrifugal chip was stored at 4 °C until use.
image file: c8lc00399h-f1.tif
Fig. 1 Schematic illustration of the microfluidic chip. (A) The custom-made instrument for spinning, temperature control, and fluorescence detection. (B) The 3D structure of the centrifugal chip. (C) Enlarged schematic of each unit containing a cell lysis chamber, storage chamber, quantitative chamber, mixing chamber, capillary valve, and amplification chamber.

Pre-preparation of urine samples and bacterial enrichment

This study was approved by the Institutional Review Board (IRB) of Tsinghua University of China (No. 20180026). All urine samples were collected following IRB guidelines. Consent was obtained for any experimentation with human subjects. The urine samples (5 mL) were collected from healthy donors. Sterile urine was obtained by filtering the urine through 0.22 μm filters. To test our chip, bacteria (E. coli, S. aureus, S. typhimurium, P. mirabilis, and P. aeruginosa) were spiked in the sterile urine to varying final concentrations (103, 104, 105, and 106 CFU mL−1) to simulate real UTI urine samples. For detection, bacteria in urine samples were enriched by a home-made pipette to improve the sensitivity and practicability of our centrifugal chip. The bacterial enrichment is illustrated in Fig. S1 and Movie S1. First, we pressed the white syringe and immersed the filter-based pipette into the urine sample. Once we released the white syringe, 5 mL urine steadily flowed through a 0.22 μm filter with the bounce of the spring in white syringe, and the bacteria were thus captured and enriched on the membrane (Fig. S1B). After that, we rotated the three-way valve 90° to turn on the connection of the tip with the washing chamber (Fig. S1C). The bacterial suspension was injected into the chip by pushing the blue syringe (Fig. S1D). The recovery efficiency (%) was calculated by Nenriched/Ninitial × 100%, where Ninitial is the number of bacteria before enrichment, and Nenriched is the number of bacteria after enrichment.

Bacterial lysis

Our group have developed a bead-beating method for bacteria lysis.43 For the detection of target bacteria, 60 μL of bacteria suspension concentrated from a urine sample was injected into the lysis chamber. Then, the inlets/outlets were sealed with PSA. Following that, the chip was placed on a custom-made magnetic stirrer. Bacteria were lysed by on-chip bead-beating mechanical lysis (Fig. 2B). The lysis unit was composed of an iron stir bar (6 mm in length, 1 mm in diameter) and zirconia beads (100 μm in diameter; Zhimo Technology, Shanghai, China) as illustrated in Fig. 2B-I. When the magnetic stirrer was turned on, the stir bar started rotating, and the zirconia beads rotated with the stir bar, leading to collisions with the bacteria disrupting their cell walls and membranes (Fig. 2B-II). Subsequently, the lysate was transferred into the quantitative chamber via centrifugation, and the cell debris was precipitated in lysis buffer during the process (Fig. 2B-III). Lysis efficiency was calculated the by plate counting method (Fig. S4). The lysis efficiency (%) = (1 − Nlysed/Ninitial) × 100%. Ninitial is the number of bacteria (S. aureus) before lysis. Nlysed is the number of bacteria (S. aureus) after lysis. The bacterial lysis time was optimized. As shown in Fig. S4, the lysis efficiency at 3, 4, and 5 min were all >97%. There was no obvious improvement of lysis efficiency when the lysis time increased from 3 min to 5 min (Fig. S4A). Genome fragmentation may occur if the bead-beating proceeds for too long. So 3 min was the best bacterial lysis time in our study.
image file: c8lc00399h-f2.tif
Fig. 2 Illustration of the filter-based enrichment and bead-beating lysis of bacteria. (A) Recovery efficiency of E. coli, S. aureus, S. typhimurium, P. mirabilis, and P. aeruginosa. (B) Photos of the lysis chamber, zirconia beads, and stir bar. Picture I shows the addition of the zirconia beads and the stirring bar, and then, the bacteria sample (red dye) and RPA master mix (blue bye) are injected into the chip (II). Next, the chip is placed above a custom-made magnetic stirrer, and the rotary motor is actuated (III). (C) Optimization of the rotation speed of the magnet for Gram-positive bacteria (S. aureus). (D) Optimization of the lysis time for Gram-positive bacteria (S. aureus).

Off-chip RPA reaction

A TwistAmp exo kit (TwistDX, Cambridge, U.K.) was used for the real time detection of five target bacteria. The genomic sequences of E. coli, S. aureus, S. typhimurium, P. mirabilis, and P. aeruginosa were obtained from GenBank. RPA primers for these bacteria were designed using the Primer 3 program and synthesized by Sangon Biotech (Shanghai, China). The sequences of RPA primers and probe for different bacteria are listed in Table S1. The fluorescence detection is accomplished by using fluorophore/quencher probes which are specific for each bacterium. The probe for each bacterium consists of an oligonucleotide with homology to the target amplicon that contains a THF, sometimes referred to as a ‘dSpacer’. The probe is blocked from any potential polymerase extension by a C6 Spacer at 3′. Any fluorescent signal generated by the fluorophore-5′ FAM will normally be quenched by the quencher BHQ-1. In a double stranded context, the THF residue represents a ‘gap’ in the probe. Exonuclease III will cleave the probe at the THF position, thereby separating the fluorophore and the quencher and generating a fluorescent signal. Critically, the nuclease activity requires the probe to be annealed to the target sequence within the amplification product. The cutting of the probe is therefore indicative of the specific target amplification event and can be used to monitor specific amplicon accumulation. The excitation wavelength was 492 nm and the emission wavelength was 518 nm.

The RPA reaction mixture was composed of 29.5 μL of rehydration buffer, 2.1 μL of each primer (10 μM), and 0.3 μL probe. For on-tube detection, 13.2 μL of the bacterial lysate was added into the RPA mixture. Then, the total mixture was added to a freeze-dried pellet (a mixture of recombinase, Bsu polymerase, Exonuclease III and single-strand binding protein Gp32). A solution of Mg(OAc)2 (280 mM) was added into the tube. Finally, the RPA reaction was performed at 39 °C for 30 min on a real-time PCR instrument (RT-Cycler™ 136, CapitalBio, China).

Real-time RPA of bacteria on the centrifugal chip

For the real-time RPA of bacteria on the centrifugal chip, the specific primers and probe for E. coli, S. aureus, S. typhimurium, P. mirabilis, and P. aeruginosa were preloaded into the 10 reaction chambers and dried at room temperature. Two reaction chambers were used for detection of each bacterium, specific primers and probe for E. coli were preloaded in reaction chambers 1–2. Specific primers and probe for S. aureus were preloaded in reaction chambers 3–4. Specific primers and probe for S. typhimurium were preloaded in reaction chambers 5–6. Specific primers and probe for P. mirabilis were preloaded in reaction chambers 7–8. Specific primers and probe for P. aeruginosa were preloaded in reaction chambers 9–10. The Mg(OAc)2 solution was also preloaded into each amplification chamber to prevent aberrant initiation of amplification. The final concentration of each RPA primer in our experiments was 0.42 μM (Table S2). After that, the chip was stored at −20 °C for use. In addition, a volume of 2 μL bovine serum albumin (50 mg mL−1) was added into 69.4 μL of the rehydration buffer. Then, the mixture was gently mixed with reaction pellets to generate the RPA master mix and stored at −20 °C for use.

For chip use, the bacterial suspension (60 μL) and RPA master mix (72 μL) were added separately into the lysis chamber and the storage chamber, respectively, through the inlets on the back of the chip (Fig. 3A). After that, all of the inlets and outlets were sealed by adhesive tape. Then we placed the chip on the custom-made magnetic stirrer. Bacteria were lysed by on-chip bead-beating lysis. Then we put the chip into the fully automatic custom-made nucleic acid analysis instrument. The entire flow control of the centrifugal chip and on-chip real time RPA was completed in the instrument. The on-chip RPA was performed at 39 °C for 30 min. The Tp for each sample was measured from the time at which the fluorescence exceeds a threshold value equal to three times the standard deviation of the negative controls (urine with no bacteria).


image file: c8lc00399h-f3.tif
Fig. 3 Illustration of the entire flow control of the centrifugal chip. (A) The initial state of the centrifugal chip with the bacterial suspension (red dye), RPA master mix (blue bye), and dried primers. Bacteria in the urine were lysed by bead beating. (B) The RPA master mix was primed into the first siphon valve by the capillary action at 100 rpm. (C) The bacterial lysate was transferred into the quantitative chamber at 3000 rpm. Then the rotation speed was decreased to 50 rpm. The RPA master mix was primed into the second siphon valve. Simultaneously, the lysate was also primed into a siphon valve. (D) Both of the bacterial lysate and the RPA master mix were transferred into the mixing chamber and mixed by cyclic variation of the spinning speed (shake-mode) between 500 and 4000 rpm. (E) The mixture was transferred into 10 separated sub-volumes (each 10 μL) at 1000 rpm. (F) The mixture was distributed into the 10 reaction chambers at 4000 rpm.

Results and discussion

Efficiency of filter-based bacteria enrichment

Urine samples contain several RPA inhibitors: urea and nucleases. Urea may cause inhibition by denaturing polymerases.44 Nucleases (DNAse and RNase) can degrade target nucleic acids and/or oligonucleotide primers and can lead to amplification failure.45 Since urea and proteins in urine can suppress nucleic acid amplification, and the concentration of bacteria in urine is quite low, it is difficult to directly detect rare bacteria in a large volume of urine. To overcome this issue, an enrichment and purification step is needed. Bacteria enrichment was achieved through a filter-based pipette (Fig. S1 and Movie S1). The recovery efficiency was above 75% in E. coli-spiked urine samples, P. mirabilis-spiked urine samples, and P. aeruginosa-spiked urine samples, with the bacteria ranging from 103 to 105 CFU mL−1. For S. aureus-spiked urine samples and S. typhimurium-spiked urine samples, the recovery efficiency was above 60% (Fig. 2A). Impurities in urine samples that may inhibit nucleic acid amplification (such as urea and proteins) were dramatically decreased after this filter-based treatment. Therefore, the bacterial suspensions concentrated from urine samples could be directly used for on-chip processing.

Optimization of the conditions for bacterial lysis

Cell lysis is a primary and necessary step for nucleic acid analysis of bacteria, especially for Gram-positive bacteria such as S. aureus.29 Bacteria were lysed by on-chip bead-beating mechanical lysis (Fig. 2B). The influence of the rotation speed of the magnet and lysis time on the lysis efficiency was examined by real-time PCR (Fig. 2C and D). First, purified bacterial (S. aureus) suspension was injected into the lysis chamber, and then lysed by on-chip bead-beating (Fig. 2B). Then the lysate was analyzed with real-time PCR. The highest lysis efficiency could be obtained when the rotation speed of the magnet was 4000 rpm (Fig. 2C). the rotation speed of the magnet was chosen as 4000 rpm for the following lysis experiments. Next, the bacterial lysis time was optimized. As shown in Fig. 2D, the Ct valves at 3, 4, and 5 min were all <18. There was no obvious improvement of lysis efficiency when the lysis time was increased from 3 min to 5 min (Fig. 2D). However, genome fragmentation may occur if the bead-beating proceeds for too long. So 3 min was the best bacterial lysis time in our study. Lysis efficiency was calculated by the real time PCR (Fig. 2B and D). In addition, we have also calculated the efficiency of bacterial lysis by the plate counting method. Fig. S4 shows that the efficiency of bacterial lysis is above 96% at 4000 rpm for 3 min. Thus, lysis at 4000 rpm for 3 min was optimal and was used in the following experiments.

The entire flow control of the chip

The workflow of the chip is illustrated in Fig. 3, and the corresponding spinning program is shown in Table S3. For bacterial detection, bacterial suspension (60 μL) and RPA master mix (72 μL) were separately injected into the lysis chamber and the storage chamber, respectively, through the inlets on the back of the chip (Fig. 3A). Then, all of the inlets and outlets were sealed and placed onto a custom-made magnetic stirrer for bacterial lysis. Subsequently, the chip was transferred into a custom-made nucleic acid analysis instrument for spinning, temperature control, and fluorescent detection (Fig. 3B–F). A low spin speed of 100 rpm is used, allowing the serial siphon to prime up to, but not past, the inline capillary valve. (Fig. 3B). After that, 30 μL bacterial lysate was transferred into the quantitative chamber at 3000 rpm. The redundant liquid flows into the waste chamber. Meanwhile, a high spin speed allows the double siphon to overcome the inline capillary valve. Then the rotation speed was decreased to 50 rpm. The RPA master mix was primed into the second siphon valve. Simultaneously, the lysate was also primed into a siphon valve (Fig. 3C). Next, the bacterial lysate and RPA master mix were transferred to the mixing chamber at 2000 rpm for 30 s. And the lysate and RPA master mix were mixed by cyclic variation of the spinning speed (shake-mode) between 500 and 4000 rpm for five cycles (Fig. 3D). Following that, the rotation speed was decreased to 50 rpm for 5 s so that the liquid could be primed into the siphon valve. The mixture was pre-distributed into the aliquotting chambers at 1000 rpm for 10 s (Fig. 3E). Finally, the mixture was distributed into the 10 reaction chambers at 4000 rpm for 40 s and mixed with pre-filled primers and Mg(OAc)2 (Fig. 3F). The RPA reaction was initiated at 39 °C, and the fluorescence signal of each reaction chamber was measured every 30 s. It took 30 min to complete the RPA reaction and fluorescence detection. Thus, the time needed to complete the entire assay was approximately 40 min.

Sensitivity test of on-chip RPA

The sequences of the RPA primers for different bacteria are listed in Table S1. The specificity of the RPA primers was tested by off-chip RPA. Only the primers mixed with the target bacteria successfully amplified products (Fig. S2 and S3). Rapid and sensitive detection of bacteria in urine is very important for the diagnosis and treatment of UTIs. To verify the detection sensitivity of our centrifugal chip, limit of detection (LOD) studies were performed. E. coli, S. aureus, S. typhimurium, P. mirabilis, and P. aeruginosa were spiked into 5 mL filtered human urine at varying final concentrations (10, 102, 103, 104, 105, and 106 CFU mL−1) to test the LOD of the on-chip RPA. Fig. 4 presents the real-time RPA profiles of different concentrations of the five bacteria. The real-time fluorescence signals were significantly increased when the concentrations of E. coli were 102, 103, 104, 105, and 106 CFU mL−1 (Fig. 4A). We could detect 102 CFU mL−1 of E. coli from urine samples within 15 min. The time to positivity (Tp) for each bacterium was measured from the time at which the fluorescence exceeds a threshold value equal to three times the standard deviation of the negative controls (urine with no bacteria). A linear regression is plotted for each bacterium showing that the Tp is approximately proportional to the logarithm of density of bacteria (Fig. 5). When the concentration of E. coli was 10 CFU mL−1, the real-time fluorescence signals were lower than the threshold value. So we couldn't detect 10 CFU mL−1E. coli from urine samples. Therefore, the LOD of E. coli was 102 CFU mL−1. All experiments were repeated at least three times and the calculated standard deviation was expressed by the error bars. Similarly, S. aureus, P. mirabilis and P. aeruginosa showed a LOD of 102 CFU mL−1 (Fig. 4B–E and 5B–E). Meanwhile, S. typhimurium showed a LOD of 103 CFU mL−1 (Fig. 4C and 5C).
image file: c8lc00399h-f4.tif
Fig. 4 Sensitivity test of the on-chip RPA reaction for targeting (A) E. coli, (B) S. aureus, (C) S. typhimurium, (D) P. mirabilis, and (E) P. aeruginosa.

image file: c8lc00399h-f5.tif
Fig. 5 Plot of average Tp of on-chip RPA reactions against the logarithm of the density of bacteria spiked into filtered human urine (N = 3). A linear regression is plotted for each bacterium showing that the Tp is approximately proportional to the logarithm of density of bacteria (A–E). The LOD for (A) E. coli, (B) S. aureus, (C) S. typhimurium, (D) P. mirabilis, and (E) P. aeruginosa.

Specificity and multiplicity tests of on-chip RPA

For accurate and sensitive detection of bacteria in urine, specificity and multiplicity tests were also essential. Therefore, different combinations of bacteria were tested with our chip. Two detection units were patterned on a chip, and each of them had 10 reaction chambers. For the specificity tests, different target specific primers for E. coli, S. aureus, S. typhimurium, P. mirabilis, and P. aeruginosa were preloaded and dried in the 10 reaction chambers of each unit (Fig. 6A). The cultured bacteria were diluted to a concentration of 103 CFU mL−1 and spiked in urine to make five artificial samples with different combinations. The specificity and multiplicity tests of the on-chip real-time RPA are shown in Fig. 6. Specifically, as shown in Fig. 6B, the detected sample contains only 103 CFU mL−1E. coli. Only two chambers that contain primers for E. coli had a significant fluorescence increase, demonstrating the specificity for E. coli. Moreover, B. subtilis and E. coli (103 CFU mL−1, respectively) were spiked into the urine and detected with the chip, and the fluorescence curves of on-chip RPA are similar with those of Fig. 6B (Fig. S5). Only two chambers that contain primers for E. coli had a significant fluorescence increase. The Tp of E. coli is also similar with that of Fig. 6B, indicating the specific amplification.
image file: c8lc00399h-f6.tif
Fig. 6 Specificity and multiplicity tests of on-chip real-time RPA. (A) Image of the centrifugal chip with different target-specific primers in each reaction chamber. (B) Specificity test for detecting 103 CFU mL−1 of E. coli. (C) Duplex test for detecting 103 CFU mL−1 of S. typhimurium and P. aeruginosa. (D) Triple test for detecting 103 CFU mL−1 of E. coli, S. aureus, and S. typhimurium. (E) Quadruple test for detecting 103 CFU mL−1 of E. coli, S. aureus, S. typhimurium, and P. aeruginosa. (F) Quintuple test for detecting 103 CFU mL−1 of E. coli, S. aureus, S. typhimurium, P. mirabilis, and P. aeruginosa (reaction chamber 1–2: E. coli; reaction chamber 3–4: S. aureus; reaction chamber 5–6: S. typhimurium; reaction chamber 7–8: P. mirabilis; reaction chamber 9–10: P. aeruginosa; RFU: relative fluorescence unit).

For multiple detection, urine samples containing different bacteria were tested with our chip, and Fig. 6C–F presents the results of the double, triple, quadruple, and quintuple bacterial detection on the microfluidic chip, respectively. For instance, as shown in Fig. 6C, when the urine sample contained 103 CFU mL−1 of S. typhimurium and P. aeruginosa, only the fluorescent signals of the reaction chambers with preloaded primers for S. typhimurium and P. aeruginosa detection showed a significant increase. Similarly, urine samples containing other bacterial combinations were also detected as expected (Fig. 6D–F). Overall, these results preliminarily demonstrate the performance of our chip for the accurate and multiplex detection of bacteria in urine samples.

Conclusions

In this study, a sensitive, rapid and multiple detection of E. coli, P. mirabilis, P. aeruginosa, S. aureus and S. typhimurium from urine samples was achieved by on-chip RPA. RPA is performed in a fully sealed chip with a high degree of automation, which greatly decreases the risks of product contamination and human error. This chip-based method for accurate and sensitive detection of multiple bacteria is quite simple to operate. The entire procedure, from bacterial enrichment to detection, was completed within 40 min. The LODs of E. coli, S. aureus, P. mirabilis, and P. aeruginosa were 102 CFU mL−1. The LOD of S. typhimurium was 103 CFU mL−1. In addition, the specificity and multiplicity of our chip were also demonstrated by analyzing samples with different combinations of bacteria. Complicated UTIs are defined by the concentration of bacteria >105 CFU mL−1 in women and 104 CFU mL−1 in men. For an uncomplicated UTI, a bacterial concentration of 103 CFU mL−1 is considered to be clinically relevant.44 Our on-chip RPA shows excellent performance in this concentration range.

E. coli, S. aureus, P. mirabilis and P. aeruginosa showed a LOD of 102 CFU mL−1. S. typhimurium showed a LOD of 103 CFU mL−1. Therefore, the on-chip RPA is suitable for clinical diagnosis of pathogens in complicated and uncomplicated UTIs. This can provide early and crucial information for physicians to conduct timely and effective therapies.

Our centrifugal chip has several advantages compared to other microfluidic systems.18,22,42 First, the bacteria in urine were enriched using a portable filter-based pipette. The operation of this device is as simple as a pipettor. Second, the RPA is performed in a fully sealed chip with a high degree of automation, which greatly decreases the risk of product contamination and human error. The entire analysis period was shortened to 40 min, which is much shorter than that of previous studies.18,22,42 RPA is an isothermal amplification technology that does not require complicated heating and cooling elements, making the construction of a portable detection instrument possible. Our chip can also be applied to other types of realistic samples, such as blood, plasma, serum, saliva, and river water, by changing the design of the filter-based pre-enrichment pipette.

Conflicts of interest

The authors declare no competing financial interests.

Acknowledgements

This study was supported by the National Key Research and Development Program of China (2016YFC0800703), the National Natural Science Foundation of China (31500691), the National Major Scientific Instrument and Equipment Development Project of China (2013YQ190467), the Beijing Municipal Science and Technology Commission (Z161100000116031), and the Beijing Lab Foundation.

Notes and references

  1. S. Salvatore, S. Salvatore, E. Cattoni, G. Siesto, M. Serati, P. Sorice and M. Torella, Urinary tract infections in women, Eur. J. Obstet. Gynecol. Reprod. Biol., 2011, 156(2), 131–136 CrossRef PubMed.
  2. A. J. Wolfe, E. Toh, N. Shibata, R. Rong, K. Kenton, M. Fitzgerald, E. R. Mueller, P. Schreckenberger, Q. Dong, D. E. Nelson and L. Brubaker, Evidence of uncultivated bacteria in the adult female bladder, J. Clin. Microbiol., 2012, 50(4), 1376–1383 CrossRef PubMed.
  3. T. M. Hooton, Uncomplicated Urinary Tract Infection, N. Engl. J. Med., 2012, 366(11), 1028–1037 CrossRef PubMed.
  4. A. L. Flores-Mireles, J. N. Walker, M. Caparon and S. J. Hultgren, Urinary tract infections: epidemiology, mechanisms of infection and treatment options, Nat. Rev. Microbiol., 2015, 13(5), 269–284 CrossRef PubMed.
  5. L. Mody and M. Juthani-Mehta, Urinary tract infections in older women: a clinical review, JAMA, 2014, 311(8), 844–854 CrossRef PubMed.
  6. G. Schmiemann, E. Kniehl, K. Gebhardt, M. M. Matejczyk and E. Hummers-Pradier, The diagnosis of urinary tract infection: a systematic review, Dtsch. Arztebl. Int., 2010, 107(21), 361–367 Search PubMed.
  7. A. R. Manges, Escherichia coli and urinary tract infections: the role of poultry-meat, Clin. Microbiol. Infect., 2016, 22(2), 122–129 CrossRef PubMed.
  8. L. L. Poulsen, M. Bisgaard, N. T. Son, N. V. Trung, H. M. An and A. Dalsgaard, Enterococcus and Streptococcus spp. associated with chronic and self-medicated urinary tract infections in Vietnam, BMC Infect. Dis., 2012, 12, 320 CrossRef PubMed.
  9. N. Marcus, S. Ashkenazi, Z. Samra, A. Cohen and G. Livni, Community-acquired enterococcal urinary tract infections in hospitalized children, Pediatr. Nephrol., 2012, 27(1), 109–114 CrossRef PubMed.
  10. J. N. Schaffer and M. M. Pearson, Proteus mirabilis and Urinary Tract Infections, Microbiol. Spectrum, 2015, 3(5), 1–39 Search PubMed.
  11. O. Megged, Staphylococcus aureus urinary tract infections in children are associated with urinary tract abnormalities and vesico-ureteral reflux, Pediatr. Nephrol., 2014, 29(2), 269–272 CrossRef PubMed.
  12. J. W. Warren, E. Abrutyn, J. R. Hebel, J. R. Johnson, A. J. Schaeffer and W. E. Stamm, Guidelines for Antimicrobial Treatment of Uncomplicated Acute Bacterial Cystitis and Acute Pyelonephritis in Women, Clin. Infect. Dis., 1999, 29, 745–758 CrossRef PubMed.
  13. H. Li, Z. Sun, W. Zhong, N. Hao, D. Xu and H.-Y. Chen, Ultrasensitive Electrochemical Detection For DNA Arrays Based on Silver Nanoparticle Aggregates, Anal. Chem., 2014, 82, 5477–5483 CrossRef PubMed.
  14. K. J. Boonen, E. L. Koldewijn, N. L. Arents, P. A. Raaymakers and V. Scharnhorst, Urine flow cytometry as a primary screening method to exclude urinary tract infections, World J. Urol., 2013, 31(3), 547–551 CrossRef PubMed.
  15. L. Song, W. Li, G. Li, D. Wei, P. Ge, G. Li, F. Zheng and X. Sun, Rapid detection of bacteria in urine samples by the "three-plug-injection" method using capillary electrophoresis, J. Chromatogr. B: Anal. Technol. Biomed. Life Sci., 2013, 935, 32–35 CrossRef PubMed.
  16. K. Shigemura, T. Shirakawa, H. Okada, K. Tanaka, S. Kamidono, S. Arakawa and A. Gotoh, Rapid detection and differentiation of Gram-negative and Gram-positive pathogenic bacteria in urine using TaqMan probe, Clin. Exp. Med., 2005, 4(4), 196–201 CrossRef PubMed.
  17. K. Elberse, S. van Mens, A. J. Cremers, S. C. Meijvis, B. Vlaminckx, M. I. de Jonge, J. F. Meis, C. Blauwendraat, I. van de Pol and L. M. Schouls, Detection and serotyping of pneumococci in community acquired pneumonia patients without culture using blood and urine samples, BMC Infect. Dis., 2015, 15, 56 CrossRef PubMed.
  18. S. J. Oh, B. H. Park, J. H. Jung, G. Choi, D. C. Lee, H. Kim do and T. S. Seo, Centrifugal loop-mediated isothermal amplification microdevice for rapid, multiplex and colorimetric foodborne pathogen detection, Biosens. Bioelectron., 2016, 75, 293–300 CrossRef PubMed.
  19. T. H. Kim, J. Park, C. J. Kim and Y. K. Cho, Fully integrated lab-on-a-disc for nucleic acid analysis of food-borne pathogens, Anal. Chem., 2014, 86(8), 3841–3848 CrossRef PubMed.
  20. Z. Crannell, A. Castellanos-Gonzalez, G. Nair, R. Mejia, A. C. White and R. Richards-Kortum, Multiplexed Recombinase Polymerase Amplification Assay To Detect Intestinal Protozoa, Anal. Chem., 2016, 88(3), 1610–1616 CrossRef PubMed.
  21. O. Piepenburg, C. H. Williams, D. L. Stemple and N. A. Armes, DNA detection using recombination proteins, PLoS Biol., 2006, 4(7), e204 CrossRef PubMed.
  22. J. H. Jung, B. H. Park, S. J. Oh, G. Choi and T. S. Seo, Integrated centrifugal reverse transcriptase loop-mediated isothermal amplification microdevice for influenza A virus detection, Biosens. Bioelectron., 2015, 68, 218–224 CrossRef PubMed.
  23. M. Euler, Y. Wang, P. Otto, H. Tomaso, R. Escudero, P. Anda, F. T. Hufert and M. Weidmann, Recombinase polymerase amplification assay for rapid detection of Francisella tularensis, J. Clin. Microbiol., 2012, 50(7), 2234–2238 CrossRef PubMed.
  24. A. James and J. Macdonald, Recombinase polymerase amplification: Emergence as a critical molecular technology for rapid, low-resource diagnostics, Expert Rev. Mol. Diagn., 2015, 15(11), 1475–1489 CrossRef PubMed.
  25. X. Pan, L. Jiang, K. Liu, B. Lin and J. Qin, A microfluidic device integrated with multichamber polymerase chain reaction and multichannel separation for genetic analysis, Anal. Chim. Acta, 2010, 674(1), 110–115 CrossRef PubMed.
  26. W. Song, H. Li, H. Liang, W. Qiang and D. Xu, Disposable electrochemical aptasensor array by using in situ DNA hybridization inducing silver nanoparticles aggregate for signal amplification, Anal. Chem., 2014, 86(5), 2775–2783 CrossRef PubMed.
  27. G. Choi, J. H. Jung, B. H. Park, S. J. Oh, J. H. Seo, J. S. Choi, H. Kim do and T. S. Seo, A centrifugal direct recombinase polymerase amplification (direct-RPA) microdevice for multiplex and real-time identification of food poisoning bacteria, Lab Chip, 2016, 16(12), 2309–2316 RSC.
  28. R. K. Daher, G. Stewart, M. Boissinot and M. G. Bergeron, Recombinase Polymerase Amplification for Diagnostic Applications, Clin. Chem., 2016, 62(7), 947–958 CrossRef PubMed.
  29. M. Mahalanabis, H. Al-Muayad, M. D. Kulinski, D. Altman and C. M. Klapperich, Cell lysis and DNA extraction of gram-positive and gram-negative bacteria from whole blood in a disposable microfluidic chip, Lab Chip, 2009, 9(19), 2811–2817 RSC.
  30. M. D. Dhawan, F. Wise and A. J. Baeumner, Development of a laser-induced cell lysis system, Anal. Bioanal. Chem., 2002, 374(3), 421–426 CrossRef PubMed.
  31. A. Berasaluce, L. Matthys, J. Mujika, M. Antoñana-Díez, A. Valero and M. Agirregabiria, Bead beating-based continuous flow cell lysis in a microfluidic device, RSC Adv., 2015, 5(29), 22350–22355 RSC.
  32. O. Strohmeier, S. Keil, B. Kanat, P. Patel, M. Niedrig, M. Weidmann, F. Hufert, J. Drexler, R. Zengerle and F. von Stetten, Automated nucleic acid extraction from whole blood, B. subtilis, E. coli, and Rift Valley fever virus on a centrifugal microfluidic LabDisk, RSC Adv., 2015, 5(41), 32144–32150 RSC.
  33. S. K. Ameri, P. K. Singh, M. R. Dokmeci, A. Khademhosseini, Q. Xu and S. R. Sonkusale, All electronic approach for high-throughput cell trapping and lysis with electrical impedance monitoring, Biosens. Bioelectron., 2014, 54, 462–467 CrossRef PubMed.
  34. H. Lu, M. A. Schmidt and K. F. Jensen, A microfluidic electroporation device for cell lysis, Lab Chip, 2005, 5(1), 23–29 RSC.
  35. J. Kim, M. Johnson, P. Hill and B. K. Gale, Microfluidic sample preparation: cell lysis and nucleic acid purification, Integr. Biol., 2009, 1(10), 574–586 RSC.
  36. L. Nan, Z. Jiang and X. Wei, Emerging microfluidic devices for cell lysis: a review, Lab Chip, 2014, 14(6), 1060–1073 RSC.
  37. E. Roy, G. Stewart, M. Mounier, L. Malic, R. Peytavi, L. Clime, M. Madou, M. Bossinot, M. G. Bergeron and T. Veres, From cellular lysis to microarray detection, an integrated thermoplastic elastomer (TPE) point of care Lab on a Disc, Lab Chip, 2015, 15(2), 406–416 RSC.
  38. J. Siegrist, R. Gorkin, M. Bastien, G. Stewart, R. Peytavi, H. Kido, M. Bergeron and M. Madou, Validation of a centrifugal microfluidic sample lysis and homogenization platform for nucleic acid extraction with clinical samples, Lab Chip, 2010, 10(3), 363–371 RSC.
  39. L. Brown, J. M. Wolf, R. Prados-Rosales and A. Casadevall, Through the wall: extracellular vesicles in Gram-positive bacteria, mycobacteria and fungi, Nat. Rev. Microbiol., 2015, 13(10), 620–630 CrossRef PubMed.
  40. M. S. Aly, M. Gauthier and J. Yeow, Lysis of gram-positive and gram-negative bacteria by antibacterial porous polymeric monolith formed in microfluidic biochips for sample preparation, Anal. Bioanal. Chem., 2014, 406, 5977–5987 CrossRef PubMed.
  41. M. Focke, F. Stumpf, B. Faltin, P. Reith, D. Bamarni, S. Wadle, C. Muller, H. Reinecke, J. Schrenzel, P. Francois, D. Mark, G. Roth, R. Zengerle and F. Stetten, Microstructuring of polymer films for sensitive genotyping by real-time PCR on a centrifugal microfluidic platform, Lab Chip, 2010, 10(19), 2519–2526 RSC.
  42. G. Czilwik, T. Messinger, O. Strohmeier, S. Wadle, F. von Stetten, N. Paust, G. Roth, R. Zengerle, P. Saarinen, J. Niittymaki, K. McAllister, O. Sheils, J. O'Leary and D. Mark, Rapid and fully automated bacterial pathogen detection on a centrifugal-microfluidic LabDisk using highly sensitive nested PCR with integrated sample preparation, Lab Chip, 2015, 15(18), 3749–3759 RSC.
  43. H. Yan, Y. Zhu, Y. Zhang, L. Wang, J. Chen, Y. Lu, Y. Xu and W. Xing, Multiplex detection of bacteria on an integrated centrifugal disk using bead-beating lysis and loop-mediated amplification, Sci. Rep, 2017, 7, 1640 CrossRef PubMed.
  44. L. El Bali, A. Diman, A. Bernard, N. H. Roosens and S. C. De Keersmaecker, Comparative study of seven commercial kits for human DNA extraction from urine samples suitable for DNA biomarker-based public health studies, J. Biomol. Tech., 2014, 25(4), 96–110 Search PubMed.
  45. R. Alaeddini, Forensic implications of PCR inhibition-A review, Forensic Sci. Int. Genet., 2012, 6(3), 297–305 CrossRef PubMed.

Footnotes

Electronic supplementary information (ESI) available. See DOI: 10.1039/c8lc00399h
Junge Chen and Youchun Xu contributed equally to this work.

This journal is © The Royal Society of Chemistry 2018