materials
Article
Direct, Rapid Detection of Pathogens from Urine Samples
Sorin David 1,† , Raluca-Elena Munteanu 1,2,† , Ana-Maria Tit, oiu 1,† , Ionela-Cristina Petcu 1 ,
Ioana-Cristina Cernat 1 , Corina Leancu 3 , Mihaela Gheorghiu 1,2, * and Eugen Gheorghiu 1,2, *
1
2
3
*
†
Citation: David, S.; Munteanu, R.-E.;
Tit, oiu, A.-M.; Petcu, I.-C.; Cernat,
I.-C.; Leancu, C.; Gheorghiu, M.;
Gheorghiu, E. Direct, Rapid
Detection of Pathogens from
Urine Samples. Materials 2022, 15,
7640. https://doi.org/10.3390/
ma15217640
International Centre of Biodynamics, Intrarea Portocalelor 1B, 060101 Bucharest, Romania
Faculty of Biology, University of Bucharest, Splaiul Independent, ei 91-95, 050095 Bucharest, Romania
Laboratoarele SynLab, Bld. Tudor Vladimirescu nr.29, 050881 Bucharest, Romania
Correspondence:
[email protected] (M.G.);
[email protected] (E.G.)
These authors contributed equally to this work.
Abstract: The problem of rapidly detecting pathogens directly from clinical samples poses significant
analytical challenges. Addressing this issue in relation to urinary tract infections, we propose
an effective protocol and related immunomagnetic test kits enabling versatile screening for the
presence of pathogenic bacteria in unprocessed urine samples. To achieve this, the components of
a typical immunomagnetic separation protocol were optimized towards the sensitive assessment of
the aggregates formed out of immunomagnetically tagged target pathogens collected from clinical
samples. Specifically, a dedicated immunomagnetic material was developed via the functionalization
of standardized, micron-sized magnetic beads with generic antibodies against gram-specific bacterial
constituents with mannan binding lectin. As such, we demonstrate efficient procedures for achieving
the enhanced, specific, and pathogen-mediated cluster formation of these tailored affinity-coated
magnetic beads in complex samples. We further show how cluster analysis, in conjunction with
the use of nonspecific, inexpensive fluorescent dye, allows for a straightforward optical assessment
of the bacterial load directly from urine samples. The optimized sensing protocol and related kits
provide, in less than 60 min, qualitative (positive/negative) information on the bacterial load with
85% specificity and 96% sensitivity, which is appropriate to empower clinical microscopy with
a new analytic dimension. The procedure is prone to automation, can be conveniently used in
clinical microbiology laboratories and, since it preserves the viability of the captured bacteria, can
be interfaced with downstream analyses and antimicrobial susceptibility testing. Moreover, the
study emphasizes a suite of practical validation assays that are useful for bringing the tool-box of
immunomagnetic materials outside the academic laboratory and into real-life applications.
Academic Editors: Leonid Gurevich
and Lucio Montanaro
Received: 10 August 2022
Keywords: UTI; immunomagnetic separation; aggregates of magnetically tagged pathogens;
rapid identification
Accepted: 26 October 2022
Published: 31 October 2022
Publisher’s Note: MDPI stays neutral
1. Introduction
with regard to jurisdictional claims in
The problem of the direct, rapid detection of pathogens from clinical samples is
a matter of intense scrutiny. Urinary tract infection (UTI), the condition caused by the
presence of pathogenic bacteria in the urinary tract (urethritis, cystitis, pyelonephritis),
remains one of the most common infections, with approximately 150 million people affected
each year [1]. UTIs can cause serious sequelae, including frequent recurrences, renal
damage in young children, pre-term birth in pregnant women, and complications caused by
the frequent use of antimicrobial drugs, including high-level antibiotic resistance. Moreover,
research has shown that the source of infection in 20–30% of all patients with sepsis is
localized in the urogenital tract and that urosepsis may cause mortality rates of 25% to
60% in certain patient groups [2]. Whereas gram-negative bacterial infections appear to
dominate the UTI spectrum, the bacterial species that can cause UTIs are numerous and
belong to both gram-negative and gram-positive genera such as Escherichia coli, Klebsiella
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Materials 2022, 15, 7640. https://doi.org/10.3390/ma15217640
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spp., Proteus spp., Pseudomonas aeruginosa (gram-negative), Streptococcus agalactiae, and
Staphylococcus saprophyticus (gram-positive).
To date, the gold standard for diagnosing UTIs in the presence of clinical symptoms is
the detection and quantification (determination of bacteriuria) of the pathogen via the urine
culture using the clean-catch midstream urine samples [3]. Identifying and quantifying the
pathogens present in a given sample by culture is time- and resource-consuming. Faster
(<24 h), orientating indirect methods (e.g., urine microscopy or dip sticks) are often used
in practice to detect the presence of bacteria or inflammation. However, the bacterial
count that may be assessed by urine microscopy or the optical density (OD) changes of
special media measured by spectrophotometry are often outside the relevant limits or
suffer from low specificity and sensitivity. The minimum level of bacteriuria demonstrating
an infection of the urinary tract depends on the type of bacteria detected, varying from
103 colony forming units (CFU)/mL to 105 CFU/mL urine (the typical threshold [4]), and
its rapid assessment is analytically challenging. These aspects often lead to the empirical
selection of antibiotics [4]. Lateral flow immunoassays (e.g., RapidBac test [5], which
can detect mostly gram-negative bacteria) are typically used as rapid assays in clinical
settings; however, their qualitative nature, limited sensitivity, and lack of bacterial recovery
options for further analysis are important drawbacks. Moreover, the clinical guidelines for
UTIs indicate that antibiotics should be selected only when the antimicrobial susceptibility
testing (AST) has been performed and the pathogen has been determined [6].
Thus, the problem of identifying bacteria early and in the lowest relevant concentrations while preserving bacterial integrity for subsequent AST is a pressing challenge for the
appropriate management of UTIs in order to have a proper medical phenotypic diagnosis
of complicated cases to reduce the empirical antimicrobial regimen of choice and effectively
prevent the emergence of multi-drug-resistant uropathogens.
Addressing this problem, we propose the deployment of an optimized immunomagnetic separation procedure coupled with a nonspecific fluorescent dye for direct use in urine
samples. Such an approach is able to provide the necessary boost for urine microscopy or
optical density OD assays in terms of specificity and sensitivity, and it could form the basis
for the development of fast pathogen detection and AST assays. To this end, we report
on the development, testing, and validation of real urine samples of an immunomagnetic
procedure comprising optimally functionalized magnetic particles for effective pathogen
capturing and the formation of aggregates of magnetically tagged cells, allowing for
a straightforward assessment of the bacterial load (positive/negative) via optical analysis.
Analytical technologies based on magnetic beads (MBs) coated with specific molecules
offer a rapid, effective, and specific way to capture, separate, collect, and concentrate
the target analytes from the sample matrix prior to detection. The method was proven
to be effective in separating various types of samples, from the preconcentration of ions
to the rapid, selective capture of organic compounds, biomolecules, and cells [7,8]. As
a result, immunomagnetic separation (IMS) techniques are widely used in many sensingrelated assays. For example, a method based on fluorescence microscopy that is capable
of detecting E. coli bacteria in a buffer with a system based on magnetic glycol-particles is
described by El-Boubbou and coworkers [9]. Another approach where magnetic particles
enabled an advantage over molecular methods is described by Dogan et al. [10]. In this
study, a combination of immunomagnetic separation and fluorescence techniques (based on
Quantum Dots, QD) was reported for the enumeration of E. coli from spiked urine samples,
with a total analysis time less than 120 min. Of note, immunomagnetic separation and
absorbance measurements for bacterial target analyte detection were, to our knowledge,
not decoupled from the enzymatic conversion of chromogenic substrates to optically
measured products [11–16], while an increased sensitivity and amenability to point of care
(POC) formats were demonstrated only when coupled to fluorescence assays and specially
designed immunomagnetic particles [16,17]. Our group’s previous results [18] showed,
at the proof-of-concept level in synthetic samples, avenues for the improved, selective
capture of the target bacteria from complex samples in addition to the formation of sizeable
Materials 2022, 15, 7640
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cells–magnetic beads clusters with morphologies and structures dependent on the target
cells number. Optimizing materials for the immunomagnetic isolation and microscopic
analysis of immunomagnetic clusters is an actual trend [19–21]; yet, their implementation
in minimally processed samples is as of yet an unmet need.
Particle-based configurations and immune-recognition not only allow for rapid, selective cell capture from clinical samples but are also effective for subsequent analysis
via microfluidic systems’ optical and electrical assays [22] or even matrix-assisted laser
desorption/ionization time-of-flight mass spectrometry, and they thus emerge as viable
alternatives to molecular approaches [23,24] and culture-based methods for quantifying the
amount of bacteria and performing physiomics analysis. Although IMS provides simple,
rapid, sensitive, and low-cost methods for the isolation of target organisms, the sample matrix always interferes with the capture of bacteria by immunomagnetic particles, resulting
in altered capture efficiencies (CE), reduced sensitivity, and a lack of validation. In most
reported assays, the actual identification and quantitation of the captured cells is subsequently performed by classical plate counts or microbiological assays. Thus, challenges
to overcome this concern the optimization of the capture efficiency of immunomagnetic
protocols, the evaluation of cell vitality (ability to proliferate) once immunomagnetically
captured, and method validation.
In this paper, we report on end-user (i.e., clinical microbiology laboratories)-oriented
ways to solve these challenges and provide a validated procedure for the rapid, selective
evaluation of the specific bacterial load of clinical samples related to UTI. The focus is
placed on the optimization of immunomagnetic materials, i.e., the smart functionalization of
commercial magnetic beads to cover a wide spectrum of causative agents (with both grampositive bacteria as well as yeasts that may be present in urine samples), and affordable
and clinically available set-ups coupled with tests in parallel with an accredited clinical
microbiology laboratory (SynLab, Romania) to validate the results. As such, the IMSproposed protocol (the use of the immunomagnetic procedure in conjunction with optical
evaluation) validated using actual clinical samples is more than an enrichment strategy
and an orientating, qualitative, method for rapid detection; it could also enable progress
towards a fast decision tool for antibiotic treatment selection in a timely manner and
facilitate its smooth clinical integration and acceptance.
2. Materials and Methods
2.1. Chemicals
Magnetic beads (Dynabeads™ M-270 Carboxylic Acid, 30 mg/mL) purchased from
Invitrogen Life Technologies (Waltham, MA, USA)were used for the development of
immunomagnetic particles in combination with three different antibodies for immune
recognition: Anti-E. coli O + E. coli K (ab31499) Rabbit polyclonal antibody against all O
and K antigenic serotypes of E.coli, Mouse monoclonal antibody against gram-positive
bacteria (ab267414/ab20344), which reacts with gram-positive bacteria Lipoteichoic acid
(LTA), and Mouse monoclonal antibody against gram-negative Endotoxin (ab41201) as
well as a Human Mannan Binding Lectin/MBL peptide (237–248) (Carboxyterminal end),
which were all purchased from Abcam, Cambridge, UK.
Bacto™ Peptone (from BD Biosciences, San Jose, CA, USA), yeast extract, NaCl (SigmaAldrich), 2-[N-morpholino] ethanesulfonic acid (MES), 1-ethyl-3-(3-dimethyl-aminopropyl)
carbodiimide (EDC), N-hydroxy-succinimide (NHS), Tween 20, Phosphate Buffer Saline
(PBS) pH 7.4, NaH2 PO4 , Na2 HPO4 , and KCl were purchased from Sigma Aldrich. Acridine orange hydrochloride hydrate (AO) was purchased from Merk. Ultrapure water
(18.2 MΩ·cm) was obtained from a Millipore Direct-Q system.
2.2. Reference Bacteria Culture
The bacterial reference strain used in the development of the assay was Escherichia coli
ATCC 25922 (serotype O6, Biotype 1), which was provided by the Microbiology Laboratory,
University of Bucharest. The cells were maintained on solid culture media and transferred
Materials 2022, 15, 7640
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to liquid media 24 h before the experiment. A minimal growth medium containing 10 g
Bacto Peptone, 5 g yeast extract, 3.5 g Na2 HPO4 , 1.5 g KH2 PO4 , and 5 g NaCl in 1 L of
ultrapure water was chosen for the reference E. coli cultivation. The pH of the cultivation
medium was adjusted at 7.2 ± 0.2 before sterilization in an autoclave. After inoculation,
the bacteria culture was grown for at least 16 h on a shaker at 37 ◦ C.
The turbidity of the cell cultures was adjusted based on McFarland standards using
a spectrophotometer (λ = 620 nm), and bacteria dilutions were prepared using sterile PBS.
Live E. coli cells at a concentration of 109 CFU/mL are optionally mixed with AO
(2 µg/mL concentration), and the cells are resuspended in PBS pH 7.4, with the supernatant
removed by centrifugation. Successive 1:10 test dilutions in PBS were made from 108 down
100 CFU/mL.
2.3. Immunomagnetic Materials Preparation: Magnetic Beads Functionalization and
Antibody Immobilization
For the synthesis of the immunomagnetic material, functionalization with different
antibodies—Anti-E. coli O157:H7, Anti gram-positive, Anti gram-negative and a generic
lectin Manan (Mannose Binding Lectin—MBL, hereafter)—was carried out, and specific
blocking procedures were devised and implemented on commercial Magnetic beads, Dynabeads™ (30 mg/mL) with a 2.8 µm diameter, and carboxylic acid group M-270 Carboxylic
Acid (CMB, hereafter)- or tosyl (TMB, hereafter)-activated surfaces. Adjusted manufacturer
protocols (https://www.thermofisher.com/order/catalog/product/14305D, accessd on
10 July 2022) were followed to prepare stock solutions containing specific bioaffinity compounds. These include common steps and, for carboxylic acid group surfaces, an activation
one. All MB-270 particles were vortexed for 30 s and submitted to ultrasonication for 30 min
to ensure a very good dispersion of the suspension, followed optionally by an EDC/NHS
surface activation step.
For the tosyl MB, the EDC/NHS activation step is not necessary; for M-270 Carboxylic
Acid, this step consists of two rounds of MES 25 mM, pH = 5 washing followed by the
30 min-long activation step of carboxylic groups, using a mixture of 1:1 EDC/NHS
(50 mg/mL in MES 25 mM) in a volume of 100 µL. The activated MBs are washed twice
with MES and incubated for 30 min in a solution of protein G (1 mg/mL in MES). Upon
two more rounds of washing with MES, the 30 min incubation in a solution of the desired
bioaffine compound follows. Then, for the blocking step, we use 1 mg/mL of BSA solution
in PBS: the magnetic particles are washed two times with the blocking solution and incubated for 60 min under agitation in 100 µL of the same solution. Finally, the functionalized
MBs were washed and resuspended in PBS to a final 100 µL volume test stock. For every
sample, a fixed 5 µL MB volume (corresponding to 107 beads) was used. Immunomagnetic
capture is acquired in 1.5 mL centrifuge vials and a bench top rotating mixer (Phoenix
RS-RD-5 from Phoenix Instrument, Garbsen, Germany). To separate the magnetic particles
from the solution, the vials are placed for 1 min next to a neodymium magnet. Further
processing steps, characteristic of each employed analysis method, are described in the
following sections.
The amount of bioaffinity compound (antibody) and the incubation time are set upon
optimization for high-efficiency analyte capturing and for the formation of specific clusters.
2.4. Experiments for Assessing the Efficiency of the Immunomagnetic Capture
To determine the capture rate of the advanced immunomagnetic materials and the support method optimization, a high-throughput assay was implemented based on
96-well plate absorbance-derived growth curves of reference cultures. Measurements
were performed on an Infinite F200 Pro plate reader (Tecan, Männedorf, Switzerland).
The reference test samples undergo Scheme 1 steps prior to optical evaluation. According
to these steps, the optimized immunomagnetic materials (e.g., MBs functionalized with
affinity compounds) are incubated with reference samples (used as the control), undergo
Materials 2022, 15, 7640
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magnetic separation and the growth curves based on the absorbance changes of the cells in
the supernatant, and are affinity-bound on the immunomagnetic materials.
Scheme 1. Steps of the protocol for the validation of MBs capture.
To achieve IMS, the optimized immunomagnetic materials (e.g., MBs functionalized
with specific E. coli antibody) are mixed with the reference samples, placed on a rotating
mixer, and separated from the supernatant with a fixed magnet. Next, the growth curves
of known (reference) E. coli concentrations, of the collected MB-E. coli clusters, and of
the supernatant withdrawn before MB-E. coli clusters collection are evaluated based on
absorbance data. The OD at 620 nm is assessed every 15 min for 16 h of cultivation in
1:1 diluted growth medium with PBS buffer, with the microplate continuously shaken
between measurements, under a 37 ◦ C incubation temperature.
Additionally, to evaluate the capture efficiency for E. coli cells in specific MB clusters,
we used end-point assays and a fluorescence method based on AO staining evaluation
with a Multimodal GloMax 20/20 Reader (Promega from Madison, WI, USA) luminometer
equipped with a Blue fluorescence module (excitation, 460 nm; emission, 515–575 nm).
CE is typically defined as the percentage of the total number of cells retained on
immunomagnetic particles versus a known concentration of the test culture, according to
Fsup
Equation (1) [25]:
Fcells
Fsup
Csup
× 100 or alternatively CE% = 1 −
× 100
(1)
CE% = 1 −
Ccells
Fcells
where Csup is the concentration of the cells that were not immunomagnetically separated
(remaining in the sample), and Ccells is the concentration of cells in the reference sample.
These amounts are typically evaluated by plate count, i.e., a procedure that is both
time-consuming and imprecise. In contrast, a rapid fluorescence assay involving AO
staining and the assessment of Fsup (the fluorescence of the cells that were not immunomagnetically separated) versus Fcells (the fluorescence of the cells undergoing immunomagnetic
separation) is deployed to quantitatively evaluate these distinct parameters of immunomagnetic beads synthesis towards method optimization. To this end, specific calibration
curves based on bacterial test cultures of different concentrations are constructed based on
fluorescence signals of AO-stained bacterial test cultures evaluated with the luminometer
according to a protocol previously reported [18] for every parameter to be optimized.
2.5. Urine Samples Preparation and Detection of Pathogenic Bacteria
Unprocessed, anonymized urine samples (Synlab, Bucharest, Romania) are analyzed
on the day of their reception. A total of 1 mL of the urine sample diluted 1:1 with PBS,
pH 7.4, is mixed with 5 µL of MB stock, with MBs functionalized with different biorecogni-
Materials 2022, 15, 7640
μ
6 of 20
tion compounds (antibodies or lectin). To facilitate target analyte binding on specifically
functionalized MBs with an active biomolecule, the urine samples are incubated for 45 min
under continuous mixing (rotary mixer) in 1.5 mL Eppendorf tubes at room temperature.
After this step, the formed clusters/aggregates are separated from the sample by applying a magnet to the outside of the tube wall and washed three times in PBS and with
PBS + 0.2% Tween 20 to reduce non-specific clustering. Subsequently, the microscopic
analysis is performed by adding AO for staining (Scheme 2).
Scheme 2. Steps of the protocol, from receiving urine samples to identifying pathogenic cells.
2.6. Fluorescence Microscopy
AO-stained MB clusters were deposited onto a glass microscope slide and covered
with a microslide. Fluorescence and bright field images were recorded with an Eclipse 600,
Nikon microscope (Nikon, Tokyo, Japan), 40× objective, a B2A fluorescence filter optimal
for AO investigation, and a digital camera, Nikon D40X (Nikon, Tokyo, Japan).
3. Results
3.1. Optimization of Immunomagnetic Particles Synthesis Based on the Quantitative, Rapid
Evaluation of the Capture Efficiency
The capture efficiency (CE) in IMS procedures is dependent on the quality of the
immunomagnetic beads synthesis as well as on the dimension and number (i.e., MB/target
cells ratio) of carrier beads used in the assay. The quality of the immunomagnetic beads
is tailored by the type, concentration, and recognition potential of the affinity compound
used in the functionalization of the immunomagnetic particles. A rapid fluorescence
assay involving AO staining and the assessment of Fsup (the fluorescence of the cells
that were not immunomagnetically separated) versus Fcells (the fluorescence of the cells
undergoing immunomagnetic separation) was deployed to quantitatively evaluate these
distinct parameters of immunomagnetic beads synthesis towards method optimization. To
this end, specific calibration curves based on 108 , 107 , 106 , 105 , and 104 CFU/mL bacterial
test cultures are constructed based on fluorescence signals of AO-stained bacterial test
cultures evaluated [18] with a luminometer (Table 1).
A total of 500 µL of each individual cell concentration is mixed with the optimized
immunomagnetic particles (MBs functionalized with affinity compounds of various concentrations with or without prior orientation), incubated for different intervals (10, 15, 30, 45,
and 60 min), and captured with a magnet on the vial’s side walls. The successful immunomagnetic separation (i.e., capture of the AO-stained cells with the formation of specific MBs
Materials 2022, 15, 7640
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clusters) corresponds to a decrease in the fluorescence signal of the supernatant and can
be used to assess CE. Csup is associated with Fsup , the fluorescence of the supernatant that
contains cells that were not immunomagnetically separated, and Fcells is the fluorescence
of the original cell suspension spiked with specific bacteria at a controlled concentration
(Table 1). The results represent the averaged data of three individual experiments, each
with three fluorescence recording/measurement points. The background signal is around
50 FSU; the same time points were used for all fluorescence recordings to avoid AO fluorescence quenching effects. Accordingly, the specific calibration curves enable the precise
quantitation of CE.
Table 1. Characteristic fluorescence signals of AO-stained suspensions of magnetically tagged
bacterial cells of various concentrations (i.e., Fcells ).
Concentration (CFU/mL)
Fluorescence Fcells (FSU)
108
107
106
105
632,053 ± 90
71,861 ± 50
8511 ± 30
1105 ± 10
The data in Table 1, corresponding to E. coli as a model strain for gram-negative bacteria, are used to derive useful
calibration curves (Figure 1) for the characterization of the capture efficiency of the IMS protocols, but similar
results can be acquired for gram-positive bacteria and fungi models (data not shown).
Fluorescence of AO stained E. coli
Linear fit of data
Fluorescence (FSU)
100,000
10,000
1,000
100
104
105
106
107
108
E. coli concentration (CFU/mL)
Figure 1. Calibration curve for suspensions of magnetically tagged cells AO-stained with the fluorescence signal as a function of the bacterial load.
To quantitatively determine the capture efficiency of specifically functionalized MBs,
the 106 cells/mL concentration was selected as the reference. Growth media spiked with
106 E. coli cells/mL are stained with AO, and their fluorescence is measured prior to (Fcells )
and after IMS (Fsup ) with specifically functionalized MBs, i.e., after the MB clusters were
removed; only the supernatant (containing free cells) is assessed.
For the immunomagnetic material synthesis, the 2.8 µm dimension MBs were selected
based on a previous study [18], and the 5 µL volume of immunomagnetic particles was
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selected in preliminary tests (data not shown) that were performed in parallel for MBs
with carboxyl and tosyl (p-toluene sulphonyl) groups. As a rule of thumb, the smallest
volume, giving, for both types of surfaces, a CE above 40%, was further considered in the
optimization stages. To avoid interferences due to steric hindrances, all optimization steps
involved the oriented binding of the affinity compound via protein G as an intermediate
linker. Protein G’s major binding site in IgG is located in the Fc part of the antibody [26]
and can be conveniently attached on materials’ surfaces with various activations.
Table 2 summarizes the optimization steps concerning the amount of immunoaffinity
compound used for functionalization, the incubation time, and the characterization of the
cross-reactivity, bacterial concentration, and live/dead status towards real sample tests.
Table 2. Summary of optimization steps.
Amount of
immunoaffinity
compound (µg)
(carboxyl MB)
0.5
1
2
5
Estimated CE%
50
45
41
39
Incubation time (min)
(carboxyl MB)
10
15
30
45
Estimated CE%
29
35
42
60
Type of MB surface
Functionalization
with 0.5 µg
Carboxyl (CMB)
Tosyl (TMB)
Estimated CE%
>65%
>75%
Live/dead status and
cell concentration
Carboxyl (CMB)
Tosyl (TMB)
105
Cell concentration
106
105
106
Cell status
dead
alive
dead
alive
dead
alive
dead
alive
Estimated CE%
0
60
21
61
27
75
56
78
Cross-reactivity
(CMB + Anti E. coli)
E. coli
Nonspecific
Listeria mon.
Nonspecific
Salmonella typ.
Estimated CE%
60
3
12
Cross-reactivity was tested by incubating MBs coated with antibodies specific to
E. coli with the specific target E. coli, the nonspecific gram-negative target Salmonella
typhimurium, and the nonspecific gram-positive target Listeria monocytogenes. The
results show adequate binding efficiencies of the MB-antibody complexes (Table 2) for both
types of surface functionalization (carboxyl—CMB and tosyl—TMB). The high capture
efficiency of both live and dead cells for tosyl-activated immunomagnetic material indicates
caution for their use, without more optimization of the blocking conditions, in clinical
samples due to a potentially high nonspecific capture and increased sensitivity to the
matrix/urine composition.
Based on the equation and the Fcells and Fsup values in Table 1 provided by the
fluorescence method (luminometer) using AO staining and optimized MB, one can estimate
the capture efficiency for the IMS protocol for relatively high bacterial loads (concentrations).
To confirm these data and evaluate the utility of captured cells in subsequent growth
protocols (e.g., their relevance for the foreseen fast AST protocols on immunomagnetically
enriched samples), the real-time recording of E. coli cells growth was performed using
absorbance assays.
Materials 2022, 15, 7640
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3.2. Optical Density Measurements and Real-Time Recording of E. coli Cells Growth
The relationship between the growth dynamics of bacterial cell suspensions as
a function of the initial cell concentration and the capture efficiency of the newly synthesized materials for IMS, as part of process optimization, is evaluated through optical
density measurements and the real-time recording of bacterial growth (E. coli chosen as
the model). Suspensions of different E. coli concentrations were mixed (1:1) with a nutrient
medium in a 96-well microplate and incubated for at least 12 h at 37 ◦ C with shaking, and
the corresponding absorbance values were recorded on a 15 min interval. Figure 2 reveals
the characteristic growth dynamics of E. coli cultures, with starting concentrations in the
range 1–106 CFU/mL. For improved clarity, the growth curves highlight the lag and part
of the exponential growth phases, and it is evident that the growth duration leading to
a measurable signal that is robustly deviating from the baseline is inversely dependent on
the concentration of the inoculum and can be used to derive the viable cell concentration
with an appropriately constructed calibration curve.
0.30
100
101
102
103
104
105
106
medium
absorbance λ = 620nm
0.25
0.20
0.15
0.10
0.05
0
2
4
6
8
10
12
Time, h
Figure 2. Growth dynamics of E. coli cells (starting concentrations 100 –106 CFU/mL) in nutrient medium.
The time needed for each of the serially diluted E. coli suspensions to reach the same
absorbance level/OD value (i.e., the same cell concentration) is derived based on growth
curve fitting (dose response function) and can be used to obtain quantitative information
from growth curves, even in the absence of plateau values that occur after long periods.
We set this OD analytical threshold to 0.14 to ensure an appropriate signal/noise level
for the optical density data of the actively growing cultures. The noise level in the OD
determinations sets, in principle, the limit of detection, and the OD threshold can be
lowered down to three times the noise level, with potentially faster detection/quantitation
results. As shown in Figure 2, the time t0 (the time required to reach the set threshold—AL)
varies in a manner that is inversely proportional with the initial cell concentration. For the
highest concentration (106 cells/mL), the cells reach AL after approximately 2 h, and for the
lowest tested concentration in our set-up, it is achieved after more than 9 h. The calibration
curve (Figure 3) derived from this time interval to reach the specific AL, evaluated in the
concentration range of 101 –106 , was further used to determine the concentration of bacteria
Materials 2022, 15, 7640
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in samples with unknown bacterial loads and validate the capture efficiency. Monitoring
E. coli cultures over time is especially useful for the low-concentration range, where direct
evaluation is challenging, according to Table 1 data.
Time to reach the threshold, h
10
y = 9.59 − 1.14 x ci
R2 = 0.963
8
6
4
2
0
101
102
103
104
cells/mL
105
106
Figure 3. Calibration plot based on OD measurements (logarithmic representation) recorded in the
concentration range of 101 –106 cells/mL, indicated as ci . The exact durations are derived upon the
automatic fit with a dose response function of every growth curve. Error bars indicate standard
deviations for three independent measurements per initial cell concentration.
3.3. Optical Density Assay for the Evaluation of Captured Cells via the Real-Time Recording of
E. coli Cells Growth
Similar to the fluorescence assay (Table 1) that indirectly provides the information on
captured cells via the specific signal related to cells remaining in the solution upon IMS, the
capture efficiency of the synthesized materials can be quantitatively assessed based on the
growth curves of cells that are not immunomagnetically
λ=6
. 10 E. separated (e.g., the supernatant).
The IMS resulting supernatant was diluted by ½ in the growth medium, and 100 µL of
this suspension was added in the microplate and evaluated via a time lapse absorbance
assay. Moreover, after washing thoroughly three times with PBS, the collected MB clusters
were added to 100 µL of the growth medium in the microplate to test whether the absorbance assay of the growth dynamics of cells collected in MB clusters can be also applied
for the direct assessment of bacterial load (Figure 4).
We estimated growth rates in triplicate using the same conditions on different days.
The curve of the supernatant containing uncaptured cells in the IMS process shows
a delayed growth compared with the growth curve of the unprocessed sample, with
a time lag that is close to a 1:10 sample dilution. These data show that one can calculate the
capture efficiency of the MB even at low target cell concentrations. Using the calibration
curve (Figure 3), we estimated a CE of ~90% for this low concentration of cells.
However, evaluating the growth dynamics of the cells undergoing IMS, i.e., the
cells affinity-bound to the immunomagnetic materials using the same absorbance asμ a modest cell load for every type of immunofunctionalization,
say (Figure 5), highlights
which is indicative of the altered dynamics of the immunomagnetically captured cells
(Anti-E. coli and Anti gram-negative synthetized materials). Accordingly, the absorbance
Materials 2022, 15, 7640
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Normalized absorbance, arbitrary units
assay of the growth dynamics of the cells collected in MB clusters (for cells immunomagnetically separated) must be approached with care when applied for the direct assessment
of bacterial load.
3.0
102 cells/mL
supernatant from MB-clusters
with 102 cells/mL
101 cells/mL
2.5
2.0
1.5
1.0
0.5
0
2
4
6
8
10
Time, h
Figure 4. Cell growth profiles for E. coli cells assayed by recording the optical density of the sam2
ples (absorbance at λ =λ 620
= 6 nm). 10
. 10 E.
E. coli cells/mL, supernatant after the IMS of E. coli cells at
Normalized absorbance, arbitrary units
a concentration of 102 and diluted by ½ in the nutrient medium, 101 E. coli cells/mL. Data referenced
λ
at the first value.
Non functionalized TMB
CMB Anti E. coli
CMB Anti Gram negative
E. coli 103 CFU/mL
Non functionalized CMB
3
2
1
0
2
4
6
8
10
Time, h
Figure 5. Growth curves of magnetically tagged E. coli upon capture from 103 CFU/mL cell suspensions using CMB functionalized with Anti E. coli (red dots), Anti gram-negative antibodies (blue
triangles), non-functionalized TMB (empty squares), and non-functionalized CMBs (arrow heads)
compared with the growth curves of the untagged 103 E. coli (green diamonds) cell suspension.
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Nevertheless, the growth of the cells captured by MB (Figure 5) shows that the bacteria are maintaining their viability after the capture and can be further analyzed and
characterized by complementary methods.
The MBs were also tested for nonspecific adsorption, and the signal (Figure 5) showed
the absence of bacterial growth for E. coli upon capture from 103 CFU/mL cell suspensions
using non-functionalized CMBs, which is indicative of a very low nonspecific binding
as well as a high non-specific binding for TMBs. The growth curve of the magnetically
tagged E. coli upon capture from 103 CFU/mL cell suspensions using non-functionalized
TMBs is similar to that of the magnetically tagged E. coli with CMB, with highly specific
functionalization. The high nonspecific binding for tosylated beads (Table 2) is thus also
confirmed in absorbance assays (Figure 5). Due to the observed non-specific binding of the
MBs, experiments on real samples were conducted using only the carboxylated MB, with
a mixture of AO staining and a direct, microscopy assay on IMS clusters.
3.4. Microscopy Assay for Urine Samples
Performing rapid, cost-, and labor-effective screening of clinical samples is highly
desirable since, typically, of the total number of samples analyzed daily, more than half
(~60%) are negative. Rapid screening in the urine sample can lead to a faster result,
which can lead to a better medical decision for patients. It can also limit the unnecessary
urine cultures.
While, from the clinical microbiology laboratory perspective, samples are characterized
as negative when less than 103 CFU/mL is present and positive for bacterial loads (of
a single type of pathogen) above 105 CFU/mL, when mixed populations are present
at detectable levels, the samples are usually disregarded as non-valid and assumed to
be contaminated.
The proposed procedure with the acridine orange staining of MB clusters formed
in urine samples spotted on a microscope slide and examined under a fluorescent microscope yields characteristic images with cluster sizes, morphologies, and structure in a fast
classification of bacterial load status.
A sample was considered positive when bead aggregates were found and bacteria
were evident in these clusters (Figure 6A). Similarly, for small sizes of clusters (Figure 6B)
or no bacteria being present in otherwise large clusters (Figure 6C), the samples are
considered negative.
Figure 6. Characteristic images of MB clusters derived from urine samples: positive urine sample
showing bacteria—E. coli captured with Anti E. coli MBs clusters (A), and negative urine samples
with limited cluster formation (B) or with large nonspecific clusters with no bacteria present (C).
According to clinical laboratory knowledge, most of the bacteria identified were
gram-negative/E. coli; thus, the MBs functionalized with a generic antibody against gramnegative bacteria can be given preference in the direct testing of urine samples. However,
cluster formation, as indicative of urine infection, was evaluated in parallel with MBs
functionalized with an antibody against gram-positive bacteria and with MBL for wider
Materials 2022, 15, 7640
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recognition (images not shown). The high price of the last compound limits, to a certain
extent, its applicability in routine analyses.
Urine samples have notoriously variable compositions and matrix effects on IMS quality and, accordingly, cluster formation. The urine samples are 1:1 diluted in PBS buffer and
undergo IMS without further purification steps. Characteristic images of nonspecific clusters formed due to the presence of epithelial cells (Figure 7A) or the highly heterogeneous
clusters for mixed flora (Figure 7B,C) are worth highlighting (images obtained when using
MB functionalized with MBL). These cases are nevertheless easy to discriminate—epithelial
cells and fungi are bigger and can be distinguished from bacteria; moreover, typically, the
mixed flora samples are deemed as non-compliant and are rejected by the test laboratory.
Figure 7. Nonspecific capture of non-target cells by MBL-MB. Epithelial cells present in urine
samples—an epithelial cell covered with MB is shown (A), Mixed flora—clusters of bacteria—bright
green—are surrounded by MB—dark red (B), Fungal presence—Candida spp. captured by the
MBL-MBs (C).
AO staining adds tremendously in terms of discriminatory power, as evident in Figure 8,
when comparing the transmission and fluorescence images of MBs with Anti-E. coli O & K
functionalization. Bacteria can be unequivocally identified against MB only in fluorescence
images. Moreover, effective cluster formation, visible bacteria (Figure 8B,C), and, hence,
positive samples according to microscopy standards are demonstrated even for concentrations lower than the clinical positivity threshold for bacterial load in urine; however,
in the further analysis, these types of results (Figure 8C), if occurring, are named “false
positive” in order to enable a comparison to the clinical laboratory results for the validation
and evaluation of the method’s performance.
3.5. Method Performance
Testing real urine samples is performed with multiple referencing, as enabled by
the optimized diverse MB functionalization: test set 1—Anti gram-positive, Anti gramnegative, or Anti E Coli antibodies, and test set 2—MBL and Anti E. Coli antibody. Examples
of the images obtained in the positive and negative samples are presented in Figure 9, with
nonfunctionalized MBs used as the urine sample quality reference and for assessing nonspecific clustering. Convenience, test relevance, and generic gram-specificity recommended
that the test set 1 composition be further used to assess the method’s performance.
The performance of our method was evaluated by individually comparing the positive
and negative samples according to the microscopy assays of AO-stained MB bacterial
clusters with test set 1 with the qualitative results provided with reference methods in
clinical laboratory tests and performing the related statistical analysis.
Statistics associated with the method’s specificity and sensitivity are defined according
to the standard definitions:
Speci f icity (%) =
N# o f true negative results × 100
N# o f true negative results + N# o f f alse positive results
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and
Sensitivity(%) =
No o f true positive results × 100
( No o f true positive results + No o f f alse negative results)
Figure 8. Comparison of transmission (A) and fluorescence microscopy (B) images of aggregates
of MB, with Anti-E. coli O & K functionalization, mediated by captured E coli bacteria. Example of
a “false positive” sample (C) according to clinical laboratory data, i.e., bacteria mediated clustering
for pathogens at concentrations below the positivity threshold set by the clinical laboratory.
Figure 9. Examples of test kit results on urine samples: (A–C) test kit 1 assay of a clinical sample with a dual catheter infection: Proteus and Enterococcus. Anti gram-negative functionalized
MB—green-stained bacteria are present in large clusters (A); Anti gram-positive functionalized
MB—yellow-green-stained bacteria are present in large clusters (B); reference non-functionalized
MB—no clusters and no bacteria present (C). (D–F) Test kit 2 sample—negative; Anti-E. coli
MB—no clusters and no bacteria present (D); MBL MB—no clusters and no bacteria present, although epithelial cells are present (E); reference non-functionalized MB—no clusters and no bacteria
present (F).
A total of 58 urine samples were analyzed using our method. Of these, 29 were found
to be true negative, 23 were found to be real positive, 5 were found to be false positive, and
𝑆𝑝𝑒𝑐𝑖𝑓𝑖𝑐𝑖𝑡𝑦 (%)
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1 was found to be false negative (Table 3). The positive samples were further processed
by the clinical lab and were found to contain bacteria from the species E. coli, Klebsiella
pneumoniae, Pseudomonas spp., Proteus spp. (gram-negative), Enterococcus, and Streptococcus
beta hemolytic group b (gram-positive). Given the high specificity (85.29%) and sensitivity
(95.83%), our method is demonstrated to be suitable for providing rapid results within the
primary care setting for emergency UTIs.
Table 3. Results obtained from the analysis of urine samples. Comparison with the method performed
in a clinical laboratory.
Positive
Negative
False
Positive
False
Negative
True
Positive
True
Negative
Our method
28
30
5
1
-
-
Clinical lab
24
34
-
-
-
-
Statistic data
Specificity
85%
5
-
-
29
Sensitivity
96%
-
1
23
-
4. Discussion
The culture-based method remains the gold standard for the detection of (pathogenic)
bacteria and even for the evaluation of the capture efficiency of most IMS procedures,
with turbidity, as determined by optical density or dye indicators (either colorimetry or
fluorescence) and individual cell counts (as in plate count methods), as the preferred assays.
Moreover, point of care (POC) microscopy, either to detect Pyuria (urine examined through
a microscope for the presence of white blood cells; samples may be centrifuged before
examination) or Bacteriuria (urine examined for the presence of bacteria; urine may be Gram
stained), can potentially become the standard for urine analysis in time-sensitive situations,
despite the fact that, currently, there is no evidence-based consensus regarding the use of
urinary microscopy in general practice [27]. It is a more convenient approach compared
to other methods (e.g., dipslide and rapid culture methods, colorimetric tests, impedance,
bio- and chemical luminescence, immunologic tests (e.g., ELISA), enzyme tests, bacterial
oxygen consumption) that currently meet a limited acceptance in clinical laboratories. It
enables the clinician to determine the morphology of the organisms (rod or cocci) and
describe their type of motility (non-motility, polar, or non-polar motility) in addition to
quantifying the number of bacteria seen per field of vision. As an overall note, pre-enriched
and/or spiked samples are typically used [28,29]. Moreover, while detection methods are
described in the literature (Table 4) to provide the rapid detection of pathogens, due to
the complexity of urine matrices, their standardization and direct application on clinical
samples are very difficult.
The objective of this study was to develop and optimize an analytic protocol, based on
specific cluster formation upon IMS, that does not require any sample pre-treatment for
the rapid detection of the presence of uropathogens in urine samples. This was achieved
via materials optimized for immunomagnetic separation and a microscopy assay of the
formed clusters due to the presence of target pathogens. The protocol enables subsequent
access to the bacterial culture for further phenotypic analysis (i.e., preserving cell viability).
In a previous study [18], we showed that the selective capture of the target analyte
and the formation of cell clusters can be revealed by measuring the oscillations of magnetically labelled analytes when applying a periodic magnetic field. A dependence of the
incubation time as well as on the limit of detection was demonstrated in conjunction with
the dimension of the MBs, with the 2.7 µm size providing the best performances.
We built on this knowledge and we optimized test MBs sets for immunomagnetic
selection (IMS) and specific cluster formation in clinical urine samples.
Materials 2022, 15, 7640
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Gram-negative bacterial infections appear to dominate the UTI spectrum, with many of
the bacterial infections reported to be caused by E. coli. However, the spectrum of causative
agents in UTIs is wide, with both gram-positive bacteria and fungi potentially present. The
bio-affine functionalization of magnetic beads is essential for the successful immunocapture.
Therefore, the study approached MB functionalization towards IMS in urine with a larger
range of affinity compounds. In addition to both highly specific antibodies (to easily identify the type of pathogens present in the urine samples) as well as compounds with wide
affinity (e.g., anti gram-type) antibodies, we tested, for immunomagnetic material synthesis,
the specific recognition based on mannan-binding lectin (MBL). MBL recognizes carbohydrate patterns found on the surface of a large number of pathogenic micro-organisms,
including bacteria, viruses, protozoa, and fungi. MBL is a protein belonging to the collectin
family that is produced by the liver and can initiate the complement cascade by binding to
pathogen surfaces. Diverse Candida species, Aspergillus fumigatus, Staphylococcus aureus, and
beta-hemolytic group A streptococci exhibit the strong binding of MBL, whereas Escherichia
coli, Klebsiella species, and Haemophilus influenzae type b are characterized by heterogeneous
binding patterns. In contrast, beta-hemolytic group B streptococci, Streptococcus pneumoniae,
and Staphylococcus epidermidis show low levels of binding [30–32].
To increase the discrimination potential of our method, we used Acridine Orange
(AO) staining. AO is a fluorochrome stain used for live cells and bacteria. The staining
mechanism is particular for DNA (intercalation interactions) and for RNA (mostly via
electrostatic interactions) [33]. AO is potentially superior to the Gram stain in the direct
microscopic examination of clinical specimens because it gives striking differential staining
between bacteria and background cells and debris [34] and was proven to be [21,33]
fast, accurate, inexpensive, and effective for various synthetic and clinical (urine) sample
analyses; hence, it is useful in UTIs.
Immunomagnetic selection, in combination with dynamic assessment, was progressively optimized, starting with synthetic samples. The results presented in Figures 2–5
show that the quantitative evaluation of capture efficiency is enabled by AO fluorescence and absorbance measurements of growth dynamics to support the optimization of
the IMS protocol. The procedure can be also applied to immunomagnetically separated
fractions (e.g., the supernatant, as well as to cells collected in MB clusters) and even to
cells washed from the clusters subsequent to repeated washing steps, if needed, when
optimizing various protocols.
While the capture efficiency is a suitable parameter to support protocol optimization,
our study revealed some significant details: (a) the capture efficiency is dependent on the
target cell concentration domain, (b) a high capture efficiency might be detrimental for
highly complex matrices (such as urine), (c) cell growth can be evaluated at the analytic
threshold (100 cells) via classical OD assays in hours, (d) the growth kinetics for cells
trapped on the MB and of cells free in the solution are not fully similar.
The microscopic analysis of immunomagnetic clusters, in conjunction with AO staining
and generic bioaffine functionalization (antibodies against the gram-specific cell wall components Lipoteichoic acid (LTA) and gram-negative Endotoxin, and mannan-binding lectin
recognizing carbohydrate patterns found on the surface of a large number of pathogenic
microorganisms), was demonstrated to be an effective solution for the direct, rapid detection of bacterial load in urine samples. However, MB cluster formation is the sole process
with analytic relevance, while AO staining is a mere indicator of the cluster formation
specificity. Moreover, our data demonstrate that the use of AO staining alone only allows
for the quantitation of capture efficiency in a concentration domain above the relevant
clinical threshold (104 –105 cell/mL), challenging the plethora of studies in the literature
building AO-mediated fluorescence assays.
A total of 58 urine samples were analyzed using our method. The results obtained
on the affinity-mediated clusters in unprocessed urine samples were compared with those
of the conventional culture-dependent method, and the developed method was proven
to be useful in identifying and assessing the presence of pathogens in urine samples in
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approximately 60 min, with a high specificity (85.29%) and sensitivity (95.83%). As such, it
provides significant progress beyond the reported assays (Table 4).
Table 4. Examples of different methods (marked with bold font) for E. coli and other bacteria detection.
UTI Pathogens
Complexity
Time to
Result (min)
Direct
Detection from
Clinical Samples
Ref.
Microscopic
Screening
Specific clusters
formation upon
immunomagnetic
capture;
Confirmatory Acridine
orange staining
Yes
(gram-positive and
gram-negative
bacteria,
some fungi)
- cheap, quick and
requires only
limited technical skill
- eliminates the need
for cultures
- minimal sample
preparation
- captured bacteria are
viable and can be
recovered and cultivated
for further analyses
45
Yes (uncentrifuged
urine samples)
Our work
Microscopic
Screening
Non-specific Acridine
orange staining
Yes (non-specific)
- rapid and cost-effective
- non-specific
N/A
Yes (smears)
[34]
20
Yes
[5]
<60
Clinical urine
samples with
3 × 107 CFU/mL
[23]
<40 min
No—spiked
-urine samples
[24]
[22]
Technology/Method
- similar to a home
pregnancy test
- rapid, does not require
sample processing
The test utilizes
a cocktail of monoclonal
antibodies targeting
a panel of bacterial
surface proteins
- easy preparation and
low cost
- 103 times
more sensitive
than traditional beacon
probes
Immunological-based
Assays
(RapidBac
test—a lateral flow
immunoassay
test strip)
Mostly
gram-negative
bacteria
Molecular method
Real-time PCR
(molecular
beacon–Au
nanoparticle)
E. coli
Molecular method
Centrifugal chip based
on DNA extraction,
multiplex recombinase
polymerase
amplification, and
fluorescent detection
E. coli, S. aureus, S.
typhimurium,
P. mirabilis,
and P. aeruginosa
- laborious technique
Microfluidic platform
Bead-based
biosensor via
fluorescence imaging
E. coli
- semi-automated
system and
relatively easy to operate
1h
No—spiked urine
samples at
a concentration
of 5 × 104
CFU/mL
SPR biosensor (surface
imprinting with
Au NPs)
E. coli
- rapid and
real-time detection
-
No—artificial
urine-spiked E. coli
[35]
E. coli
- rapid detection without
time-consuming
cell culturing
- capture efficiency
was 88%
45 min
No—E. coli
in buffer
[9]
Fluorescence
microscopy
system based on
magnetic
glycol-particles
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Table 4. Cont.
Technology/Method
IMS and fluorescence
techniques
(QDs nanoparticles)
Fluorescent
nanoparticle-based
indirect
immunofluorescence
microscopy
fluorescence
UTI Pathogens
Complexity
Time to
Result (min)
Direct
Detection from
Clinical Samples
Ref.
E. coli
- rapid detection
compared with
PCR methods
- laborious work;
many steps are
required
<120 min
No—E. coli-spiked
urine samples
[10]
M. tuberculosis
- higher luminescence
and higher
photostability
- can be a universal
method for
detecting a wide
variety of bacteria
240
No—mixed
bacteria and
spiked
sputum samples
[36]
LFI—lateral flow immunoassay; QD—Quantum Dots; Ab-MNP—antibody-conjugated magnetic nanoparticles;
CE SSCP—capillary electrophoresis single-strand conformational polymorphism; MLPA—multiplex ligationdependent probe amplification; IMS—immunomagnetic separation.
The limitations of the technique could reside in MB clustering in the absence of bacteria.
However, the use of AO staining and the tailored test kits enables multiple referencing,
eliminating, to a large extent, this issue.
Since the IMS method and procedure preserve the viability of the cells that are immunomagnetically enriched, the method could be conveniently extended towards the
development of rapid AST platforms, enabling the evaluation of the bacterial cell division
under antimicrobial conditions and, hence, drug resistance.
5. Conclusions
The problem of the direct, rapid detection of pathogens from clinical samples related to
urinary tract infections poses significant analytical challenges. While indirect methods (e.g.,
urine microscopy or dip sticks) are often used in practice to assess the presence/absence of
bacteria or inflammation, the gold standard for diagnosing UTIs in the presence of clinical
symptoms is the identification and quantification (determination of bacteriuria) of the
pathogen via the urine culture, a procedure both time- and resource-consuming. We address
these issues via materials optimized for immunomagnetic separation and a microscopy
assay of immunomagnetic clusters encompassing target pathogenic cells and magnetic
beads functionalized with bio-affine coatings. These bio-affine coatings were tailored
for the specific UTI pathogens to include a wide range of compounds, from antibodies
against E. coli or against gram-specific cell wall components to mannan-binding lectin
recognizing carbohydrate patterns found on the surface of a large number of pathogenic
microorganisms, including bacteria, viruses, protozoa, and fungi. The affinity-coated
magnetic beads play a double role—for capturing the target pathogenic cells from the
bio-sample and for mediating the formation of aggregates of specifically bound pathogens
and magnetic particles, the latter allowing for a straightforward assessment of the bacterial
load via optical analysis.
Analyzing the structure of the aggregates of magnetically tagged pathogens from
minimally processed urine samples, the assay provides, in less than 60 min, qualitative
(positive/negative) information on the bacterial load. The 85% specificity and 96% sensitivity of the assay are achieved by optimizing the immunomagnetic material, the selection
of generic anti-gram-negative antibodies and mannan binding lectin, as well as the use of
nonspecific, inexpensive fluorescent dye, enabling clinical microscopy with a new analytic
dimension, prone to automation. The limitations of the technique could reside in MB nonspecific self-clustering in the absence of bacteria, especially in complex matrices; however,
Materials 2022, 15, 7640
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as demonstrated in the study, upon careful design of the materials for immunoseparation
and the use of the fluorescence assay on clusters, it is possible to perform accurate analyses
in urine. This study proposes an effective sensing protocol to analyze real urine samples
that can be conveniently used in clinical microbiology laboratories for the prescreening
of samples. Moreover, the study emphasizes a suite of practical validation assays when
developing magnetic materials for immunocapture applications. The detection procedure
preserves the viability of the captured bacteria and, as a future avenue, can be interfaced
with downstream analyses and antimicrobial susceptibility testing.
Author Contributions: Conceptualization, E.G. and M.G.; methodology, E.G. and S.D.; investigation,
R.-E.M., A.-M.T., I.-C.P. and I.-C.C.; resources, C.L.; writing—original draft preparation, S.D., A.-M.T.
and M.G.; writing—review and editing, S.D., M.G. and E.G. All authors have read and agreed to the
published version of the manuscript.
Funding: This research was funded by the Romanian Executive Agency of Higher Education,
Research, Development, and Innovation Funding through the projects ERANET-M-SmartMatter,
PN-III-P2-2.1-PED-2019-5185, PN-III-P4-ID-PCE-2020-1433, PN-III-P2-2.1-PED-2019-5155, PN-III-P22.1-PED-2019-4932, PN-III-P2-2.1-PED-2021-2298, PN-III-P4-PCE-2021-1281.
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Data Availability Statement: The data generated during the present study are available from the
corresponding authors on reasonable request.
Conflicts of Interest: The authors declare no conflict of interest.
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