Ki Soo Park1,2, Chen-Han Huang1,2, Kyungheon Lee1,2, Yeong-Eun Yoo3, Cesar M Castro1,4, Ralph Weissleder1,2,5, Hakho Lee1,2. 1. Center for Systems Biology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA. 2. Department of Radiology, Harvard Medical School, Boston, MA 02114, USA. 3. Department of Nanomanufacturing Technology, Korea Institute of Machinery and Materials, Daejeon 305-343, Korea. 4. Department of Medicine, Harvard Medical School, Boston, MA 02114, USA. 5. Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA.
Abstract
Health care-associated infections (HAIs) and drug-resistant pathogens have become a major health care issue with millions of reported cases every year. Advanced diagnostics would allow clinicians to more quickly determine the most effective treatment, reduce the nonspecific use of broad-spectrum antimicrobials, and facilitate enrollment in new antibiotic treatments. We present a new integrated system, polarization anisotropy diagnostics (PAD), for rapid detection of HAI pathogens. The PAD uses changes of fluorescence anisotropy when detection probes recognize target bacterial nucleic acids. The technology is inherently robust against environmental noise and economically scalable for parallel measurements. The assay is fast (2 hours) and performed on-site in a single-tube format. When applied to clinical samples obtained from interventional procedures, the PAD determined the overall bacterial burden, differentiated HAI bacterial species, and identified drug resistance and virulence status. The PAD system holds promise as a powerful tool for near-patient, rapid HAI testing.
Health care-associated infections (HAIs) and drug-resistant pathogens have become a major health care issue with millions of reported cases every year. Advanced diagnostics would allow clinicians to more quickly determine the most effective treatment, reduce the nonspecific use of broad-spectrum antimicrobials, and facilitate enrollment in new antibiotic treatments. We present a new integrated system, polarization anisotropy diagnostics (PAD), for rapid detection of HAI pathogens. The PAD uses changes of fluorescence anisotropy when detection probes recognize target bacterial nucleic acids. The technology is inherently robust against environmental noise and economically scalable for parallel measurements. The assay is fast (2 hours) and performed on-site in a single-tube format. When applied to clinical samples obtained from interventional procedures, the PAD determined the overall bacterial burden, differentiated HAI bacterial species, and identified drug resistance and virulence status. The PAD system holds promise as a powerful tool for near-patient, rapid HAI testing.
Health care–associated infections (HAIs) and the emergence of drug-resistant
pathogens are major health care issues. On any given day, 1 of 25 hospitalized patients
becomes infected and as many as 1 of 9 succumb to death (). HAIs incur a significant socioeconomic burden arising
from prolonged hospital stays, lasting disability, and demand for new antimicrobials. In
the United States, it is estimated that more than 600,000 patients develop HAIs every
year (), and HAI-related costs
amount to $100 billion to $150 billion per year (). Rapid, sensitive detection of pathogenic bacteria is
a key to initiating timely treatment with proper antibiotics, preventing disease spread,
and identifying infection sources in hospitals, homes, and other field settings (–).Although bacterial culture is the clinical gold standard, it has drawbacks including
long process times (up to several days), personnel cost, and the need for specialized
equipment and species-specific protocols. As an alternative, nucleic acid (NA) testing
has been increasingly adopted in clinical laboratories. On the basis of polymerase chain
reaction (PCR) amplification of bacterial nucleotides, NA tests allow for comprehensive
pathogen identification. The target sequence library is also rapidly expanding to
empower these tests, aided by advances in bacterial whole-genome sequencing (). Technical challenges, however,
still remain in translating NA tests into routine clinical workflows. First, system
operation can be complex, requiring trained operators. Although fully automated systems
are available, they tend to be bulky and expensive. Second, assay costs are often higher
than those for conventional screening. For example, in sequence-specific detection (for
example, TaqMan, Molecular Beacon, and LightCycler), specialized probes for each NA
target should be designed. Finally, NA tests are susceptible to false positives due to
accidental contamination by amplified products. To minimize the potential for
cross-contamination, it is necessary to have the pre- and post-PCR areas in different
spaces or PCR workstations. These constraints limit the penetration of NA tests to
centralized hospital laboratories. For prompt, effective HAI control, assay platforms
that can bring NA testing to the patient level (for example, community clinics and
doctor’s offices) are needed.Here, we report a new detection system designed for rapid, cost-effective HAI
diagnostics. Termed polarization anisotropy diagnostics (PAD), the system measures
changes in fluorescence anisotropy when detection probes recognize target bacterial NAs
(). The detection is
ratiometric, independent of fluorescence intensity, which makes the assay robust against
environmental factors. We advanced the PAD to enable multilevel, on-site HAI
diagnostics. Specifically, we have (i) developed a compact device with a disposable
cartridge for sample preparation and multiwell detection, (ii) optimized the assay to
perform NA amplification and detection without washing steps, (iii) embedded
contamination control in the assay protocol, and (iv) created a library of
sequence-specific probes to assess bacterial burden, pathogen types, antibiotic
resistance, and virulence. As proof of concept, we applied PAD to detect clinically
relevant HAI pathogens (, ): Gram-negative
Escherichia coli, Klebsiella pneumoniae,
Acinetobacter baumannii, and Pseudomonas aeruginosa
and Gram-positive Staphylococcus aureus. The PAD demonstrated detection
sensitivity down to the single bacterium level and determined drug resistance and
virulence status. With clinical samples, the PAD achieved an accuracy comparable to that
of bacterial culture; however, the PAD had a much shorter turnaround time (~2 hours) and
allowed for on-site operation.
RESULTS
Polarization anisotropy diagnostics
Figure 1A shows the assay scheme. Following
bacterial lysis, target NAs [for example, regions in 16S ribosomal
RNA (rRNA) or mRNA] are amplified via asymmetric reverse transcription PCR (RT-PCR).
Next, an all-in-one PAD mix is added. The mix consists of two reagents: (i) a
detection key that is derived from an aptamer (specific to DNA polymerase) adjoined
with a complementary sequence to target NAs () and (ii) a reporter DNA with a fluorophore. The
detection key, stabilized through hybridization with the target NA, locks into DNA
polymerase and deactivates its enzymatic activity. The reporter DNA then retains its
structure and assumes high fluorescence anisotropy (r) due to slow
diffusional motion. Conversely, the anisotropy is low in the absence of the NA
targets, because unlocked DNA polymerase cleaves the reporter’s fluorophore
during the extension reaction. The assay is fast (2 hours for completion) and is
performed without any washing steps.
Fig. 1
PAD system.
(A) Assay procedure. Bacteria are lysed, and total RNA is
extracted. Following the RT-PCR amplification, samples containing amplicons and
DNA polymerase are incubated with an all-in-one master mix that has the
detection key and the reporter. The resulting fluorescence anisotropy of the
sample is then measured. (B) Photograph of a disposable RNA
extraction cartridge made in plastic. The device has an RNA extraction chamber
packed with glass beads (inset). (C) Photograph of a portable
system for fluorescence anisotropy detection. Four separate optical cubes can
be plugged into an electronic base station. (D) PAD measurement is
controlled through a custom-designed application in a smartphone. The PAD
device and the smartphone communicate via Bluetooth.
PAD system.
(A) Assay procedure. Bacteria are lysed, and total RNA is
extracted. Following the RT-PCR amplification, samples containing amplicons and
DNA polymerase are incubated with an all-in-one master mix that has the
detection key and the reporter. The resulting fluorescence anisotropy of the
sample is then measured. (B) Photograph of a disposable RNA
extraction cartridge made in plastic. The device has an RNA extraction chamber
packed with glass beads (inset). (C) Photograph of a portable
system for fluorescence anisotropy detection. Four separate optical cubes can
be plugged into an electronic base station. (D) PAD measurement is
controlled through a custom-designed application in a smartphone. The PAD
device and the smartphone communicate via Bluetooth.
PAD system
To enable on-site HAI detection, we implemented a compact PAD system (Fig. 1, B and C). The system had two major parts: a
disposable sample-processing cartridge and a compact reader for fluorescence
anisotropy detection. The cartridge was used to extract bacterial NAs (see fig. S1
for the device structure). It had a fluidic chamber packed with glass beads
(diameter, 30 μm) to create an on-chip filter (fig. S1A) (): negatively charged NAs
could be adsorbed to the positively charged bead surface under high-salt condition
and then be eluted by changing the salt concentration. We implemented the device in
poly(methylmethacrylate) via injection molding (see Materials and Methods for
details). When compared to a commercial column filter, the fluidic cartridge showed
comparable performance, extracting RNA with good quality (fig. S2). The RNA integrity
numbers (RINs), ranging from 1 (poor) to 10 (best), were 9.6 ± 0.3 (fluidic
cartridge) and 9.5 ± 0.2 (column filter). By using the on-chip cartridge,
however, we could remove centrifugal washing steps.The detection system was designed for portable, parallel PAD assays. It had a modular
structure consisting of a base unit for signal processing and four plug-in optical
cubes (Fig. 1C and fig. S3). Each optical cube
could be customized to accommodate differently sized sample containers and
fluorescence optics. The packaged PAD system had a small form factor (8 × 8
× 8 cm3) and weighed ~400 g. The system wirelessly communicated
with a computer or a smartphone through Bluetooth connection, which further improved
system portability and simplified the assay setup. We designed a smartphone
application for system operation as well as for data logging with geographic
information (Fig. 1D and fig. S4).
PAD optics
Figure 2A shows the schematic of an optical cube
in the PAD system. We used a light-emitting diode (LED) as an affordable light
source. The illumination light passed through a linear polarizer and focused onto a
sample to excite fluorophore (Fig. 2A, inset).
The intensity of emission light was then measured by a pair of photodiodes. We
measured both the parallel (Ix) and perpendicular
(Iy) components relative to the polarized excitation
light and calculated the fluorescence anisotropy (r) as
r = (Ix –
Iy)·(Ix +
2Iy)−1. The optics was encased into
an opaque plastic body to minimize the interference from adjacent modules (fig.
S3B).
Fig. 2
Optical detection design.
(A) Schematic of an optical cube. The optical excitation module
has an LED, a linear polarizer, and a focusing lens. The emission light is
measured by a pair of detector sets, each consisting of a lens, a polarization
filter, and a photodiode (PD). (B) Circuit diagram. The on-board
computer controls the entire system and communicates with a smartphone. To
enhance the signal-to-noise ratio (SNR), the system uses the optical lock-in
detection scheme. The intensity of the excitation light is amplitude-modulated,
and the resulting emission intensities are mixed with the carrier frequency.
The dotted box indicates an optical cube. BPF, band-pass filter; LPF, low-pass
filter; AMP, amplifier. (C) The lock-in method significantly
improved the signal-to-noise ratio (630 times, 28 dB). (D) The
accuracy of the PAD was benchmarked against a commercial plate reader. The
measured values show excellent agreements (R2 =
99%). Experiments were performed in triplicate, and the data were displayed as
means ± SD. Horizontal and vertical error bars were from the plate
reader and the PAD measurements, respectively.
Optical detection design.
(A) Schematic of an optical cube. The optical excitation module
has an LED, a linear polarizer, and a focusing lens. The emission light is
measured by a pair of detector sets, each consisting of a lens, a polarization
filter, and a photodiode (PD). (B) Circuit diagram. The on-board
computer controls the entire system and communicates with a smartphone. To
enhance the signal-to-noise ratio (SNR), the system uses the optical lock-in
detection scheme. The intensity of the excitation light is amplitude-modulated,
and the resulting emission intensities are mixed with the carrier frequency.
The dotted box indicates an optical cube. BPF, band-pass filter; LPF, low-pass
filter; AMP, amplifier. (C) The lock-in method significantly
improved the signal-to-noise ratio (630 times, 28 dB). (D) The
accuracy of the PAD was benchmarked against a commercial plate reader. The
measured values show excellent agreements (R2 =
99%). Experiments were performed in triplicate, and the data were displayed as
means ± SD. Horizontal and vertical error bars were from the plate
reader and the PAD measurements, respectively.For robust signal detection, we adopted the lock-in measurement technique. Exploiting
the fact that r is intensity-independent, we modulated the intensity
of the excitation light at the carrier frequency of 1 kHz. The emission signals were
then frequency-locked through the homodyne signal path (Fig. 2B). The scheme significantly improved the signal-to-noise ratio
(>28 dB; Fig. 2C) and allowed for reliable
system operation under ambient light. Data acquisition was directed by a
microcontroller unit (MCU; Arduino). A multichannel digital-to-analog converter (DAC)
was used to deliver a tunable, modulating signal to the driver in each optical cube.
The signal from a photodetector was amplified by a current amplifier, passed through
an analog lock-in circuit, and digitized by a multichannel analog-to-digital
converter (ADC). The MCU was programmed to serially poll the optical cubes, control
all peripheral components, and communicate with external devices via Bluetooth (fig.
S5).We benchmarked the PAD system against a commercial plate reader (Sapphire 2, Tecan).
To prepare samples of different fluorescence anisotropy, we varied the ratio between
free fluorescein-labeled DNA (FAM-DNA; high fluorescence anisotropy) and
template-bound FAM-DNA (low anisotropy; see Materials and Methods). The observed
r values showed agreement (R2 >
99%) between the plate reader and the PAD, which served to confirm the accuracy of
the PAD system (Fig. 2D).
Universal key to measure bacterial load
We first used the PAD to detect the overall bacterial burden. We designed a single,
universal key (UNI key) that targets a conserved region of 16S rRNA
in different bacterial species (Fig. 3A and
Table 1). We also prepared a common
reporter probe that was composed of FAM-DNA, its primer, and its template (Fig. 3A). The PAD output was defined as
Δr = r –
r0, where r0 is the
fluorescence anisotropy of control samples containing DNA polymerase and the reporter
only.
Fig. 3
Universal bacteria detection.
(A) The universal capture key (UNI key) detects a conserved
bacterial sequence (N = A for Escherichia,
Klebsiella, and Acinetobacter; N = T for
Pseudomonas and Staphylococcus). The
reporter is composed of a primer, a template, and FAM-DNA. (B)
Five different HAI pathogens (106 CFU/ml) were detected with the
PAD. The signal levels were statistically identical among concentration-matched
bacterial samples. (C) Detection sensitivity. Samples with
different bacterial concentrations (E. coli,
10–1 to 108 CFU/ml) were prepared through
serial dilution. The limit of detection (LOD) was at the level of a single
bacterium. The threshold was set at 3× SD above background signal of the
sample without bacteria. All experiments were performed in triplicate and the
graphs are displayed as means ± SD.
Table 1
Sequence of detection keys designed for the PAD (see table S1 for other
targets).
PVL, Panton-Valentine leukocidin.
Category
Target
DNA sequence (5′ to
3′)
UNI
Universal
CAATGTACAGTATTGTGGAGCATGTGGTTTAATTCGA
HAI
Escherichia
CAATGTACAGTATTGTGGAGGAAGGGAGTAAAGTTAAT
Klebsiella
CAATGTACAGTATTGTGGAGGCAAGGCGATAAGGT
Acinetobacter
CAATGTACAGTATTGTTCTAGTTAATACCTAGGGATAGTG
Pseudomonas
CAATGTACAGTATTGTGGAGGAAGGGCAGTAAGTTAA
Staphylococcus
CAATGTACAGTATTGTGGGAAGAACATATGTGTAAGTAAC
ARV
nuc
CAATGTACAGTATTGTTGCTTCAGGACCATATTTCTCTAC
femB
CAATGTACAGTATTGTCCAGAAGCAAGGTTTAGAATTG
mecA
CAATGTACAGTATTGTCTGCTATCCACCCTCAAACAG
PVL
CAATGTACAGTATTGTCGGTAGGTTATTCTTATGGTGGAG
Universal bacteria detection.
(A) The universal capture key (UNI key) detects a conserved
bacterial sequence (N = A for Escherichia,
Klebsiella, and Acinetobacter; N = T for
Pseudomonas and Staphylococcus). The
reporter is composed of a primer, a template, and FAM-DNA. (B)
Five different HAI pathogens (106 CFU/ml) were detected with the
PAD. The signal levels were statistically identical among concentration-matched
bacterial samples. (C) Detection sensitivity. Samples with
different bacterial concentrations (E. coli,
10–1 to 108 CFU/ml) were prepared through
serial dilution. The limit of detection (LOD) was at the level of a single
bacterium. The threshold was set at 3× SD above background signal of the
sample without bacteria. All experiments were performed in triplicate and the
graphs are displayed as means ± SD.
Sequence of detection keys designed for the PAD (see table S1 for other
targets).
PVL, Panton-Valentine leukocidin.We applied the designed assay (UNI-PAD) to detect representative HAI pathogens
(E. coli, K. pneumoniae, A.
baumannii, P. aeruginosa, and S.
aureus). Across different bacterial species, we observed consistent
Δr values in concentration-matched samples [Fig. 3B; P = 0.8857, one-way
analysis of variance (ANOVA)]; this result supported the use of the UNI-PAD in
estimating total bacterial load. We next performed titration experiments with
serially diluted bacterial samples (Fig. 3C; see
Materials and Methods for details). The PAD assay achieved the dynamic range spanning
>104 colony-forming units (CFU); the limit of detection was down to
single-digit CFU.
Assay optimization for point-of-care operation
We optimized the PAD system for its point-of-care (POC) applications. One major issue
in POC NA testing is to control false positives caused by sample contamination with
PCR products (that is, carryover contamination) (, ). To minimize such effects, we adopted the
uracil-DNA glycosylase (UDG) method (, ). By substituting deoxythymidine triphosphate
(dTTP) with deoxyuridine triphosphate (dUTP) during PCR, we rendered all amplicons to
have a uracil-containing DNA backbone. Applying UDG cleaved these amplicons, which
selectively destroyed carryover contaminants from PCRs while keeping bona fide DNA
templates (Fig. 4A). We confirmed that the
method was compatible with the PAD assay. The signal level remained the same when
dUTP replaced dTTP in DNA targets (fig. S6). We next tested the efficacy of this
contamination control. As a carryover contaminant, dUTP-containing PCR products
(107 amplicons) were spiked into samples. Without UDG treatment, the
negative control with no bacterial targets showed false positives (Fig. 4B). This signal was eliminated with the
addition of UDG, and only samples containing true bacterial targets yielded high
Δr (Fig. 4B).
Fig. 4
Assay optimization for POC operation.
(A) Schematic illustration of UDG-mediated control on carryover
contamination. Uracil-containing carryover contaminant was specifically broken
down by UDG, which allows for the amplification of the true target DNA only.
(B) Uracil-containing contaminants (107 copies) were
added to all samples. Contaminated samples produced high signal even in the
absence of target bacteria. When samples were treated with UDG, the
false-positive signal was eliminated. (C) The PAD reagents were
lyophilized to facilitate their transport and extend their shelf life. After 4
weeks of storage in ambient condition, the reagents were used for bacterial
detection. No difference was observed between fresh and lyophilized reagents.
Bacterial samples in (B) and (C) contained E. coli
(106 CFU/ml). All experiments were performed in triplicate, and
the data are displayed as means ± SD. RT, room temperature.
Assay optimization for POC operation.
(A) Schematic illustration of UDG-mediated control on carryover
contamination. Uracil-containing carryover contaminant was specifically broken
down by UDG, which allows for the amplification of the true target DNA only.
(B) Uracil-containing contaminants (107 copies) were
added to all samples. Contaminated samples produced high signal even in the
absence of target bacteria. When samples were treated with UDG, the
false-positive signal was eliminated. (C) The PAD reagents were
lyophilized to facilitate their transport and extend their shelf life. After 4
weeks of storage in ambient condition, the reagents were used for bacterial
detection. No difference was observed between fresh and lyophilized reagents.
Bacterial samples in (B) and (C) contained E. coli
(106 CFU/ml). All experiments were performed in triplicate, and
the data are displayed as means ± SD. RT, room temperature.To maximize system portability, we further combined the PAD with a miniaturized
thermocycler (miniPCR, Amplyus) (). The performance of the POC system matched that of
conventional benchtop equipment (fig. S7). We also lyophilized all
chemical reagents (for example, detection keys and reporters) to facilitate their
transport and storage (see Materials and Methods for details). The reagents retained
their activity after >2 weeks of storage in ambient conditions; we observed
statistically identical Δr values (P >
0.64, two-tailed t test) with fresh and stored agents (Fig. 4C and fig. S8).
Differential keys for pathogen classification
To differentiate HAI-causing pathogens, we designed a set of detection keys (HAI
keys) in which each key targets the hypervariable region of 16S rRNA
in different bacterial species (Table 1; see
table S1 for extended targets). The sequence homology among genus types was kept
<50% to minimize nonspecific binding. When tested, the HAI keys assumed high
specificity. For example, the Escherichia key (Fig. 5A) showed high signal (Δr) only with
its intended target, whereas off-target signals were negligible even in high
biological background (106 CFU of other bacterial species; Fig. 5B). Similarly, other HAI keys displayed
excellent specificity with minimal crosstalk (Fig.
5C). Electrophoretic band-shift analysis confirmed that the detection keys,
in the presence of complementary target amplicon, bound to DNA polymerase and
inhibited its catalytic activity (fig. S9).
Fig. 5
Bacteria typing with PAD.
(A) A set of detection keys specific for HAI pathogens was
designed (HAI keys). An Escherichia key is shown as an
example. (B) The specificity of HAI keys was tested. The signal
was high only in the presence of the target species even in the mixture of
other bacterial species. An example of E. coli (106
CFU/ml) detection is shown. (C) Heat map of
Δr values obtained for HAI detection. Bacterial
concentration was 106 CFU/ml. (D) Detection keys for
antibiotic resistance and virulence (ARV keys) were designed for further
typing. Two types of methicillin-resistant S. aureus (MRSA;
106 CFU/ml), health care–associated MRSA (HA-MRSA) and
community-acquired MRSA (CA-MRSA), were identified by targeting the specific
regions in mecA and PVL genes. Three pathogens
[methicillin-sensitive S. aureus (MSSA), E.
coli, and P. aeruginosa;
106 CFU/ml] were included as controls. All experiments were
performed in triplicate. The heat map displays mean values and the bar graphs
display means ± SD.
Bacteria typing with PAD.
(A) A set of detection keys specific for HAI pathogens was
designed (HAI keys). An Escherichia key is shown as an
example. (B) The specificity of HAI keys was tested. The signal
was high only in the presence of the target species even in the mixture of
other bacterial species. An example of E. coli (106
CFU/ml) detection is shown. (C) Heat map of
Δr values obtained for HAI detection. Bacterial
concentration was 106 CFU/ml. (D) Detection keys for
antibiotic resistance and virulence (ARV keys) were designed for further
typing. Two types of methicillin-resistant S. aureus (MRSA;
106 CFU/ml), health care–associated MRSA (HA-MRSA) and
community-acquired MRSA (CA-MRSA), were identified by targeting the specific
regions in mecA and PVL genes. Three pathogens
[methicillin-sensitive S. aureus (MSSA), E.
coli, and P. aeruginosa;
106 CFU/ml] were included as controls. All experiments were
performed in triplicate. The heat map displays mean values and the bar graphs
display means ± SD.We next prepared probes for antibiotic resistance and virulence (ARV keys) for
further bacterial phenotyping. These keys targeted bacterial genes that make
pathogens antibiotic-resistant or highly virulent. As a model system, we profiled
samples for mecA, PVL, nuc, and
femB genes. mecA is the determining factor
conferring MRSA, a common multidrug-resistant HAI pathogen (). PVL, nuc, and
femB are virulence factors that contribute to the pathogenicity
of S. aureus. We used two representative MRSA strains that have the
following known genotypes: health care–associated MRSA
(mecA+, PVL–) and community-acquired
MRSA (mecA+, PVL+). Control samples were MSSA
(mecA–), E. coli
(mecA–, PVL–,
nuc–,
femB–), and P. aeruginosa
(mecA–, PVL–,
nuc–, femB–)
(table S2) (–). The ARV-PAD correctly
genotyped bacteria, agreeing with a quantitative real-time PCR (qPCR) (Fig. 5D and fig. S10).
Clinical application
Finally, we applied the PAD for clinicalHAI diagnostics. The assay started with
bacterial lysis, followed by the NA collection using the plastic cartridge. Following
the NA amplification, the samples were analyzed in parallel for total bacterial
burden (UNI key), HAI pathogens (HAI keys), and antibiotic resistance and virulence
status (ARV keys) (fig. S11). The total assay time was ~2 hours, and the required
sample volume was ~40 μl.We acquired patient samples and aliquoted them for the PAD test (2 hours) and
conventional culture (3 to 5 days) in a clinical microbiology laboratory. Test
results for all detection keys (UNI, HAI, and ARV) are shown in Fig. 6A and fig. S12. Samples negative with UNI-PAD were also
negative with HAI-PAD, suggesting the potential use of universal detection for sample
triaging. Among six UNI-PAD–positive samples, the HAI-PAD detected HAI
pathogens in five samples, and the differentiation results matched the bacterial
culture readouts (Fig. 6B). One patient (no. 6)
was positive with bacterial load but was negative with HAI keys; the patient was
later found to be infected with Providencia rettgeri (nontargeted in
the current HAI-PAD). For the sample positive for S. aureus (patient
no. 2), the ARV-PAD showed mecA– status (that is,
MSSA); this result matched the MRSA-negative pathology report and qPCR (Fig. 6 and fig. S13).
Fig. 6
Clinical application of PAD for HAI detection.
(A) Nine samples from different patients were processed by the PAD
for bacterial load (UNI), presence of the HAI species (HAI), and
resistance/virulence status (ARV). (B) The clinical samples were
also tested by a clinical pathology laboratory (culture and qPCR). The PAD and
pathology reports agreed with each other.
Clinical application of PAD for HAI detection.
(A) Nine samples from different patients were processed by the PAD
for bacterial load (UNI), presence of the HAI species (HAI), and
resistance/virulence status (ARV). (B) The clinical samples were
also tested by a clinical pathology laboratory (culture and qPCR). The PAD and
pathology reports agreed with each other.
DISCUSSION
HAIs have become a ubiquitous, recalcitrant, and costly problem in modern health care.
They increase the emergence of antibiotic resistance, cause significant morbidity and
mortality, and prolong hospital stays. One of the key mandates to control this endemic
is to equip local hospitals and community centers with more effective surveillance
systems. The PAD platform presented here could enable rapid HAI detection in those
settings. The detection system is compact and user-friendly with minimal operation
complexity. The assay is comprehensive, assessing for overall bacterial burden, pathogen
types, antibiotic resistance, and virulence factors.Several features make the PAD ideal for field operation. First, the sensing scheme
(fluorescence anisotropy) is inherently robust against environmental noise. We further
incorporated the optical lock-in technique to significantly enhance the sensitivity.
Second, the assay flow involves minimal complexity and hands-on time. A disposable
plastic chip is used to collect NAs, and the remaining processes are performed in a
single tube without washing steps. The assay protocol is also refined to automatically
dissolve carryover contaminants, thereby minimizing false positives. Third, the platform
is highly affordable. The PAD device has simple electronics and can readily be expanded
for parallel detection. Making an injection-molded cartridge brings advantages including
high performance reproducibility, less cross-contamination between samples, and lower
cost. Finally, the PAD is scalable for comprehensive screening. Decoupling detection and
signaling probes enables such assays to be cost-effective, because a common fluorescence
reporter can be used for all detection targets. We have already designed detection
probes for >35 targets (table S1); the incremental assay cost for additional targets
is ~$0.01.In a pilot clinical test, PAD accuracy was comparable to that of bacterial culture. In
contrast to the culture, the PAD assay was fast (~2 hours), multiplexed, and
cost-effective (<$2 per assay). However, we note the following limitations in the
current study. First, no clinical samples were found to contain drug-resistant strains.
Further studies with larger cohorts are needed to verify PAD’s capacity for drug
resistance screening. Second, the PAD may present ambiguous results when target NAs
overlap. For example, the current ARV keys would fail to discern community-acquired MRSA
(mecA+, PVL+) from the mixture of health
care–associated MRSA (mecA+, PVL–)
and MSSA (mecA–, PVL+). Such incomplete
classification is an inherent issue with NA-based tests. We expect that this issue would
be overcome as more bacteria genomic data are accrued from whole-genome sequencing
efforts.The current prototype system could be further improved. First, we envision a
self-contained, closed system in which sample preparation, thermocycling, and detection
functions are all housed in a single device. Such a system would effectively eliminate
erroneous results from sample contamination, user interference, or both and proffer
“sample-in and answer-out” tests. Second, the current assay time could be
shortened, particularly for DNA amplification. One promising direction is to adopt a
photonic thermocycling system, which can complete the entire PCR in <5 min (). Isothermal amplification is
also an alternative; some isothermal reactions can be completed in 20 min, which could
bring down the total assay time to <1 hour (). Using isothermal amplification would simplify the
hardware requirement and make a battery-powered device feasible. In the future, we plan
to expand the test library for broader pathogen and antibiotic resistance screening. The
modular nature of PAD probes should facilitate incorporating new targets such as
host-response factors (for example, interleukin-4, platelet-derived growth factor B
chain, monocyte chemoattractant protein-1, and C-X-C motif chemokine 10) (), as well as other viral,
fungal, and parasitic markers.
MATERIALS AND METHODS
Fabrication of the plastic cartridge
The device was made in plastic via injection molding. A metal block of the mold was
first machined to have surface structures such as channels, chambers, and ports
negatively shaped to those on the top and bottom parts of the plastic cartridge. To
confine microbeads in the RNA capture chamber, a weir-shaped physical barrier was
designed at the outlet side of the chamber. The top and bottom parts of the device
were injection-molded in a foundry (Korea Institute of Machinery and Materials). More
than two devices were produced per minute. The top and bottom parts were glued
together and the three-way valve was inserted. Fluidic connection was made by
inserting polyethylene tubes in the fluidic ports.
Device preparation
The fluidic cartridge was filled with glass beads (diameter, ~30 μm;
Polysciences). Beads were suspended in 75% ethanol (Sigma) and introduced through the
inlet. The beads were retained in the RNA capture chamber due to the weir-style
physical barrier in the outlet side of the chamber (fig. S1A). Following bead
capture, excess ethanol was collected and removed. The entire device was then flushed
with cycles of RNaseZap (Life Technologies), ribonuclease (RNase)–free water
(Life Technologies), and ethanol, and dried. All fluidic flow was generated by
manually operating syringes.
Detection system
The illumination source in the optical cube consisted of an LED (λ = 470 nm;
Thorlabs), a dichroic film polarizer (polarization efficiency, >99%; Thorlabs),
and a convex lens [focal length (ƒ) = 8 mm]. The detection part had a convex
lens (ƒ = 8 mm), a long-pass filter (EL0500, Thorlabs), a dichroic film
polarizer, and a photodiode (S1223, Hamamatsu). A 16-bit DAC (LTC1597, Linear
Technology) was used to deliver the modulated control signal to a custom-designed LED
driver (LF356, Texas Instrument). The signal from the photodiode was amplified by a
custom-designed current amplifier (AD549, Analog Devices). For the lock-in detection,
the amplified signal was passed through a band-pass filter (center frequency, 1 kHz;
bandwidth, 100 Hz), mixed with a carrier signal, and passed through a low-pass filter
(time constant, 1 ms). The conditioned signal was digitized by a 16-bit ADC (LTC1867,
Linear Technology). A microcontroller (Arduino MEGA 2560) was programmed to control
the light sources for multiplexing, to perform real-time data recording, and to
communicate with an external device (for example, computers and smartphones) via a
USB 2.0 or a Bluetooth interface. The entire system was powered by a 9-V battery
housed inside the base station. A typical power consumption during a single optical
measurement (one cube) was ~400 mW, and each test took ~30 s.
Smartphone application
We created a custom-designed Android application to facilitate system operation and
data recording. Control software was designed using MIT App Inventor 2. The
application connected the smartphone to the PAD system and sent the triggering signal
for the fluorescence anisotropy detection. The measured data were sent back to the
phone and combined with a time stamp and Global Positioning System coordinates.
Signal detection
Fluorescence anisotropy values were measured with the excitation and emission
wavelengths of 470 and 525 nm, respectively. Fluorescence anisotropy
(r) was calculated using the following equation:
r = (Ix –
Iy)·(Ix +
2Iy)–1, where
Ix and Iy are emission
intensities when the emission polarizers are in parallel with and perpendicular to
the excitation polarizer, respectively. The LOD was estimated by setting the
threshold at 3× SD above the background signal of samples without bacteria.
For comparison with the benchtop equipment (Sapphire 2, Tecan), we measured
Δr = r −
rFAM, where rFAM is the
fluorescence anisotropy only in the presence of FAM-DNA (62.5 nM) and
r is the fluorescence anisotropy in the presence of FAM-DNA (62.5
nM) along with its template. We varied the template concentrations (10, 20, 30, 40,
50, and 60 nM) to produce different amounts of hybridized FAM-DNA.
Probe design
DNA oligonucleotides were synthesized by Integrated DNA Technologies. The list of DNA
sequences is summarized in Table 1 and tables
S1 and S3. For the universal and species-specific detection of pathogenic bacteria,
individual 16S rRNA sequences of different bacterial genera [from
the National Center for Biotechnology Information (NCBI) nucleotide database] were
aligned using MegAlign software (DNASTAR), and both conserved and variable regions
were selected as target sequences (). To detect ARV factors, the specific regions of
nuc, femB, mecA, and PVL (from
the NCBI nucleotide database) were selected as target sequences (–). The detection keys were designed to have a
hairpin structure joined by a single-stranded capture sequence (~20 to 25 nucleotides
in length) (, ).
Lyophilization of master mix
An all-in-one PAD mix (20 μl) was concocted by mixing a detection key (400
nM), a reporter (150 nM), a primer (150 nM), and FAM-labeled DNA (125 nM) in 20 mM
tris-HCl (pH 8.3), 20 mM KCl, 5 mM (NH4)2SO4, and 6
mM MgCl2. The mixture was first frozen in liquid nitrogen and then dried
in VirTis Freezemobile 25EL Freeze Dryer (SP Scientific). The lyophilized reagents
were stored at room temperature and reconstituted before use by adding 20 μl
of UltraPure DNase/RNase-free distilled water (Life Technologies).
Experiment with cultured bacteria
All bacteria were purchased from the American Type Culture Collection (ATCC).
Bacterial cultures were grown to mid-log phase in vendor-recommended medium:
E. coli (#25922) in LB medium (BD Biosciences); P.
aeruginosa (#142), K. pneumoniae (#43816), and MRSA
(#BAA-1720 and #BAA-1707) in tryptic soy broth (BD Biosciences); A.
baumannii (#15149) in nutrient broth (BD Biosciences); and S.
aureus (#25923) in Staphylococcus broth (BD
Biosciences). Bacteria were collected via centrifugation (6000g, 10
min), and pellets were resuspended with the preheated TRIzol (Life Technologies). The
resuspended cells were transferred to 2-ml Safe-Lock tubes (Eppendorf) containing
sterilized disruptor beads (0.1 mm; Scientific Industries) and lysed using a vortex
mixer. After centrifugation, the supernatant was transferred to a new tube.
RNA extraction
Bacterial lysate mixed with an equal volume of ethanol was flown through the RNA
extraction chamber, in which RNA was captured by packed glass beads. Subsequent
flushing with Direct-zol RNA PreWash (Zymo Research) and RNA Wash Buffer (Zymo
Research) was done to remove traces of impurities and chaotropic salts. Finally, RNA
was eluted in RNase-free water. For comparison of the fluidic cartridge with a
commercial column (Zymo-Spin column, Zymo Research), bacterial lysate was divided
into two aliquots. One sample was processed by the commercial column and the other by
the fluidic cartridge. We checked the quality of the extracted RNA through an
electrophoretic assay (2100 Bioanalyzer, Agilent). RNA molecular weight ladder
provided in the kit (RNA 6000 Nano Chip, Agilent) was used as reference, and
electrophoretic runs were performed per the manufacturer’s protocol. The
analysis assigned RINs to samples, ranging from 1 to 10, where 1 indicates highly
degraded RNA and 10 completely intact RNA.
PAD assay
The single-stranded complementary DNA (cDNA) was synthesized using random priming
with Promega’s Reverse Transcription System as per the manufacturer’s
protocol. The asymmetric PCR amplification was then carried out in a total reaction
volume of 25 μl containing 2.5 μl of cDNA, 0.8 μM excess primer,
0.08 μM limiting primer (table S3), 1× PCR buffer [20 mM tris-HCl, 20
mM KCl, 5 mM (NH4)2SO4, and 2 or 3 mM
MgCl2], 0.2 mM deoxyadenosine triphosphate (dATP), deoxyguanosine
triphosphate (dGTP), and deoxycytidine triphosphate (dCTP), 0.4 mM dUTP (Thermo
Scientific), 2 U of Antarctic Thermolabile UDG (New England Biolabs), and 2.5 U of
Maxima Hot Start Taq DNA polymerase (Thermo Scientific). For the asymmetric PCR on a
miniaturized thermocycler (miniPCR, Amplyus), we used the following cycling
conditions: 25°C for 10 min and 94°C for 4 min; 35 cycles of 30 s at
94°C, 30 s at 56°C, and 30 s at 72°C; and an extension step of
10 min at 72°C. With a benchtop thermocycler (MasterCycler, Eppendorf), the
reaction conditions were 25°C for 10 min and 94°C for 4 min; 35 cycles
of 5 s at 94°C, 15 s at 56°C, and 15 s at 72°C; and a final 10
min at 72°C. The PCR solution (20 μl) was mixed with an all-in-one PAD
mix composed of a detection key (200 nM) and a reporter that was preformed with a
template (75 nM), a primer (75 nM), and FAM-labeled DNA (62.5 nM) at room temperature
for 15 min, making a total volume of 40 μl in 20 mM tris-HCl (pH 8.3), 20 mM
KCl, 5 mM (NH4)2SO4, and 4 mM MgCl2.
UDG-mediated control of carryover contamination
To mimic the carryover contamination, we spiked dUTP-containing amplification
products (carryover contaminants) into new reaction samples. The copy number of
carryover contaminants was ~107; a single aerosol after PCR typically
contains as many as 106 amplification products (). The dUTP-containing amplicons were prepared
following the same procedures outlined above except that equal amounts of limiting
and excess primers were used. The obtained amplicons were purified using the
Zymoclean Gel DNA Recovery Kit (Zymo Research) and quantified by measuring the
absorbance at 260 nm with NanoDrop 1000 (Thermo Scientific). The copy number was
estimated on the basis of the conversion factor (26 kD per amplicon).
Clinical samples
This study was approved by the Partners Institutional Review Board. Excess and
discarded samples were collected from nine subjects with clinical suspicion for
infected bodily fluid or abscess and referred for drainage. Specimens were collected
using routine image-guided approaches by Massachusetts General Hospital
Interventional Radiology physicians and analyzed blindly using the PAD assay.
Specimens (500 μl) were mixed with 1.5 ml of TRIzol LS (Life Technologies)
which is more concentrated than TRIzol, and the same RNA extraction procedure was
applied as in pure bacterial cultures.
Electrophoretic band-shift experiment
Solution containing 100 or 200 nM detection key, PCR products, and 12.5 U of Taq DNA
polymerase (New England Biolabs) in 20 mM tris-HCl (pH 8.3), 20 mM KCl, 5 mM
(NH4)2SO4, and 4 mM MgCl2 was
incubated at room temperature for 20 min. The solution was mixed with 6×
loading buffer and subjected to electrophoresis on a 20% polyacrylamide gel (Life
Technologies). The analysis was carried out in 1× TBE (100 mM tris, 90 mM
borate, 1 mM EDTA) at 150 V for 160 min at 4°C. After GelRed (Biotium)
staining, gels were scanned using an ultraviolet transilluminator. DNA polymerase was
neither fluorescent nor stained by the dye ().
Quantitative real-time PCR
The cDNA derived from in vitro cultured bacteria or clinical samples was mixed with
1× PowerUp SYBR Green Master Mix (Life Technologies) and 0.4 μM
specific primers used in the PAD assay. Thermal cycling was then carried out on the
7500 Fast Real-Time PCR system (Life Technologies) with the following conditions: UDG
activation (50°C, 2 min), initiation (95°C, 2 min); 40 cycles of
denaturation (95°C, 5 s); annealing (56°C, 15 s); extension
(72°C, 30 s). The 7500 Fast software automatically calculates the
Ct value, which represents the first PCR cycle at
which the fluorescence signal exceeds the signal of a given uniform threshold.
No-template control (NTC) remained undetected, not crossing the established threshold
for 40 cycles, and was arbitrarily given a Ct value of
41. The ΔCt was generated by subtracting the
Ct value of the specimen from the
Ct value of NTC ().
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