Iago
Pereiro
abc,
Amel
Bendali‡
abc,
Sanae
Tabnaoui‡
ab,
Lucile
Alexandre‡
abc,
Jana
Srbova
d,
Zuzana
Bilkova
d,
Shane
Deegan
e,
Lokesh
Joshi
f,
Jean-Louis
Viovy
abc,
Laurent
Malaquin
abc,
Bruno
Dupuy
*g and
Stéphanie
Descroix
*abc
aLaboratoire Physico Chimie Curie, Institut Curie, PSL Research University, CNRS UMR168, 75005 Paris, France. E-mail: stephanie.descroix@curie.fr
bSorbonne Universités, UPMC Univ Paris 06, 75005 Paris, France
cInstitut Pierre-Gilles de Gennes, 75005 Paris, France
dDept. of Biological and Biochemical Sciences, Faculty of Chemical Technology, University of Pardubice, 53210 Pardubice, Czech Republic
eAquila Bioscience Limited, Business Innovation Centre, National University of Ireland Galway, Galway, Ireland
fGlycoscience Group, National Centre for Biomedical Engineering Science, National University of Ireland Galway, Galway, Ireland
gLaboratory Pathogenesis of Bacterial Anaerobes, Dept. Microbiology, Institut Pasteur, 75724 Paris, France. E-mail: bruno.dupuy@pasteur.fr
First published on 10th October 2016
A microfluidic method to specifically capture and detect infectious bacteria based on immunorecognition and proliferative power is presented. It involves a microscale fluidized bed in which magnetic and drag forces are balanced to retain antibody-functionalized superparamagnetic beads in a chamber during sample perfusion. Captured cells are then cultivated in situ by infusing nutritionally-rich medium. The system was validated by the direct one-step detection of Salmonella Typhimurium in undiluted unskimmed milk, without pre-treatment. The growth of bacteria induces an expansion of the fluidized bed, mainly due to the volume occupied by the newly formed bacteria. This expansion can be observed with the naked eye, providing simple low-cost detection of only a few bacteria and in a few hours. The time to expansion can also be measured with a low-cost camera, allowing quantitative detection down to 4 cfu (colony forming unit), with a dynamic range of 100 to 107 cfu ml−1 in 2 to 8 hours, depending on the initial concentration. This mode of operation is an equivalent of quantitative PCR, with which it shares a high dynamic range and outstanding sensitivity and specificity, operating at the live cell rather than DNA level. Specificity was demonstrated by controls performed in the presence of a 500× excess of non-pathogenic Lactococcus lactis. The system's versatility was demonstrated by its successful application to the detection and quantitation of Escherichia coli O157:H15 and Enterobacter cloacae. This new technology allows fast, low-cost, portable and automated bacteria detection for various applications in food, environment, security and clinics.
This is critically true in the food industry, for which, due to the long time required by existing detection methods, products carrying pathogenic bacteria can be widespread before alert, resulting in disease outbreaks with high risks for consumers and important economic costs. In the developing world, production and consumption mostly remain local, so testing should be able to accommodate non-centralized and low-technicity environments. The cost and technicity of current analysis techniques often make them unsuitable or unaffordable where analysis would be needed. The present paper focuses on foodborne pathogens, but of course the same issue exists for diagnostic issues.
Plating and colony-counting is still considered the “Gold Standard” for bacteria detection. The protocol starts with an overnight or even longer enrichment phase conducted in liquid broth in agitated flasks. Then, cultures are plated on Petri dishes containing agar-based growth medium and incubated for durations that may range from 12 hours to several days before counting. Finally, additional molecular or immunological typing methods may be needed, for specific strain identification. This protocol is highly sensitive and specific, but it typically requires several days, skilled personnel and large volumes of consumables. Hence, a great diversity of alternative analytical methods, based either on metabolic properties (biochemical identification techniques, chromogenic agar broth3), protein constitution (MALDI-TOF4), antibody targeting (ELISA,5 flow cytometry,6 immune-separation7), nucleic acid techniques (hybridization,8 PCR,9 microarrays10) or microfluidics,11 has been developed. For the sole case of Salmonella, the first cause of non-diarrheal foodborne deaths in the world, several tens of kits are commercially available, the majority being based on immunorecognition.12,13 The cost and complexity of current detection methods, either based on plating or on molecular assays, however, still strongly limit their extended use in routine practice.
Microfluidic-based technologies can offer platforms for faster and more automated detection systems, while reducing testing costs. A variety of microfluidic separation methods for bacteria can be found in the literature, based e.g. on size sorting through inertial microfluidics,11,14 electrophoresis15 or antibody capture.16 For bacterial identification, these methods are often coupled with nucleic acid amplification techniques or further immuno-recognition protocols, increasing the complexity of the system. In addition, due to their low initial input volume, most microfluidic methods require a preliminary enrichment cultivation step to reach the sensitivity level required for most food pathogen detection standards. This is usually performed by conventional, non-microfluidic protocols, limiting the gain brought by the use of microfluidics. The specific challenges raised by clogging and need for pre-concentration were identified as early as 2007.17 Recently, an interesting article reported a single-step detection of bacteria, using an integrated on-chip culture on antibody arrays and label-free detection.18 This study was an important step towards global assay acceleration, achieving a sensitivity of around 140 cfu (colony forming units) ml−1 in 10 hours for Salmonella spiked in raw milk, but it retained some limitations, such as baseline drift in the presence of real samples, a need for sample pre-treatment, and the cost of the surface plasmon resonance technology used for detection. Also, specificity versus other commensal bacteria in excess was not assessed. Kang et al. alternatively proposed a system combining DNAzymes, microfluidic droplets and 3D optical detection, reaching sensitivities between 10 and 100 cfu ml−1, but this method is also prone to false positive results in the case of dead or lysed bacteria.19
Here, we present an original and compact microfluidic device allowing sensitive, fast and low-cost pathogen detection directly from a complex raw liquid sample, down to a few cfu in a few hours. It relies on a new microfluidic technology: a microfluidic fluidized bed in which superparamagnetic beads bearing specific ligands of the pathogens of interest recirculate continuously while the raw sample is passed through. To our knowledge, this is the first time the concept of a magnetic fluidized bed has been transferred to the microfluidic scale.20–22 This approach ensures a high density of beads and specific surface to improve target capture, combined with low working pressures and high resistance to clogging. Therefore, the system is ideal for analyte pre-concentration.
We apply it here for the efficient extraction of bacteria from raw milk, but go further by showing how the same system can be employed for their subsequent label-free detection with no added complexity. This is simply obtained by amplifying the bacteria in situ by flowing a nutritious medium through the fluidized bed. Importantly, the volume occupied by the newly formed bacteria leads to modifications of the physical properties of the fluidized magnetic bed (expansion phenomena) that can be directly monitored to perform a highly specific quantification of the initial number of microorganisms in the sample. This unique detection method presents no direct macroscopic equivalent and allows for very simple and low-cost detections. We applied and characterized it here with Salmonella enterica serovar Typhimurium, with a sensitivity down to bacteria numbers in the single digits, and with 5 orders of magnitude in dynamic range. The behavior was equivalent even in real application conditions of unskimmed milk and the presence of natural flora more concentrated by several orders of magnitude. We further expanded its use to the detection of Escherichia coli, the second most common cause of non-diarrheal foodborne deaths in the world after Salmonella.2 The successful detection of Enterobacter cloacae, a major cause of nosocomial diseases, with a non-antibody ligand was also characterized to further demonstrate the versatility of the system. Regarding the latter, finally, we considered here only foodborne pathogens, but the technology also has strong potential for diagnosis at the point of care, notably thanks to its capacity for automation and reduction of contamination risk.
The microfluidic fluidized bed involves a microchamber, partially filled with micrometric magnetic particles, an external permanent magnet and a fluid flow controller (Fig. 1a). The triangular shape of the microfluidic chamber serves two purposes. First, in contrast to gravitational fluidized beds, here the force opposing drag is derived from a gradient, and it cannot be kept constant over large areas. We thus chose a monotonously decreasing magnetic force along the main axis of the chamber, compensated by a decrease of the drag force along the same axis thanks to the triangular shape of the chamber. The divergences of the field and of the flow were also optimized to favor a stable and continuous recirculation of beads for optimal capture (Fig. 1b, Movie S1 & 2†). The obtained particle trajectory pattern is comparable to the spouting regimes sometimes employed in macroscopic fluidized beds.24 We hypothesize that in the central part, drag forces are dominant over magnetic forces, resulting in particles being dragged towards the exit of the chamber. When reaching the front of the fluidized bed, a sudden drop in flow velocity, due to the end of the solid fraction, leads to the equilibrium of drag and magnetic forces. A lateral displacement of particles then takes place. This is the combined consequence of the particle inflow, which maintains the mass transfer balance, and of the no slip boundary condition near the walls: in this region, the fluid velocity decreases significantly, so that the magnetic forces dragging particles upstream become dominant. As a result, a flow of particles is formed back to the channel entrance. Thus, this new geometry avoids the formation of a narrow open pathway of the percolating liquid through the magnetic beads bed, or “bed fracture”, a phenomenon that usually occurs with magnetic packed beds at high flow rates.22 We thus obtain a completely dynamic and almost homogeneous bed of magnetic microparticles. As visible in Movie S2† & Fig. 1d, beads are organized by dipole–dipole interactions into small columns oriented mostly along the flow, a feature also contributing to decreasing flow resistance. Upon flow rate increase, the effective friction coefficient of each bead decreases due to the increased spacing between the beads, so the system is intrinsically stable for a large range of flow rates (flow rates ranging from 0.5 to 5 μL min−1 were used here). This flow rate can then be optimized for each given application, higher flow rates leading to a longer total length of the fluidized bed and consequently to a higher bed porosity (Fig. 1c).
Fig. 1 Scheme of the microfluidic fluidized bed. An external permanent magnet creates a magnetic field gradient inside a triangle-shaped chamber, resulting in magnetic forces globally oriented towards the chamber inlet, applied on superparamagnetic beads (a). Fluids are passed into the chamber through the inlet located on the magnet side, using a pressure-based flow controller (MFCS Fluigent). If no pressure is applied, the beads remain in a packed-bed configuration due to magnetic forces (scale bar = 1 mm) (b); under flow, the beads are also subject to drag forces oriented upstream, and above a flow threshold a new, steady-state dynamic equilibrium, called the fluidized bed regime, is achieved, favoring high percolation rates and internal recirculation of the beads (indicated with arrows). The total length of the fluidized bed is directly dependent on the applied flow rate due to a change in the porosity of the bed (c). The bed in the fluidized state is shown in the micrograph (d) and in Movie S2,† showing the high bead density and the multiple percolation paths leading to efficient and uniform capture (scale bar = 200 μm). |
Interestingly, these experiments also showed a physical change in the fluidized bed during culture, revealed by an expansion of the bed, apparent as a progressive increase of area (Fig. 3a and b and Movie S4†). The area increase roughly follows that of fluorescence, with an initial plateau, an exponential-looking growth, a linear zone and a saturation plateau. This behavior is typical of nonlinear reaction kinetics with reagent saturation. Towards the end of the bed expansion an important flow of bacteria leaves the fluidized bed, dragged by the flow of nutritious medium (Fig. 3c and Movie S5, ESI Fig. 5 and 6†). This is a consequence of the saturation of the fluidized bed capacity to capture all the newly produced bacteria, a fact that could also explain the observed final plateau in the total fluorescence intensity, and the limited extent of bed expansion. Overall, the device can be used for the direct processing and analysis of samples containing only a few bacteria and allows to obtain, in a few hours, amplification factors of typically 106, thus avoiding the need of flask-based pre-enrichment. Further, the modification of the chip aspect, in the presence of living bacteria, is indeed large enough to be detected by the naked eye, opening the possibility to assess, with a high specificity, in a few hours and without any complex or expensive detection means, the presence of only a few infectious bacteria in a raw liquid sample (Fig. 4b). To evaluate the dynamic range of the assay, the expansion of the bed was measured (Fig. 4c and ESI† Experimental) as a function of time for different initial concentrations of bacteria. This yields a series of similar curves shifted along the horizontal axis, reminiscent of the DNA quantity plots obtained in PCR (Fig. 4c). We defined an expansion threshold at 200 μm, corresponding to the onset of the quasi-linear expansion phase. The intersection of growth curves with this threshold defines for each initial concentration an expansion time. When plotted against the logarithm of the initial bacteria number, this expansion time follows a linear behavior (Fig. 4d, blue), providing a calibration curve for the quantitation of the initial bacteria concentration with a wide dynamic range (from 4 to 106 cfu per 50 μl). The time required to reach an observable expansion ranges from 60 min for 60000 cfu per 50 μl (1.2 × 106 cfu ml−1) to approximately 7 hours for 4 cfu per 50 μl (80 cfu ml−1). To confirm the method specificity regarding S. Typhimurium quantification, cultures with the same beads were performed after flowing L. lactis in the device; no expansion of the bed occurred for subsequent cultures. Similar experiments were performed, starting from whole UHT milk spiked with bacteria. The results (Fig. 4d) yield very similar outcomes, showing the applicability of the technology to complex, real-life food samples. Expansion times seem slightly shorter in milk than in PBS, maybe due to the fact that the bacteria were kept in milk for 50 minutes during the capture step, and could thus start to grow in this medium.
We assessed the ability of our device to detect and quantify other relevant foodborne pathogens, in particular Enterobacter cloacae and Escherichia coli O157:H7. Fig. 4d shows that both bacteria species can be, similarly to S. Typhimurium, cultured and quantitatively detected in situ, except with different expansion times. Expansion times specifically depend on bacteria type and strain, but also on culture conditions, leaving room for speeding up the process by the specific optimization of the culture broth and temperature.27 Besides, these assays are also interesting regarding the versatility of the technology, since the ligand used to capture E. cloacae is a lectin specific to E. cloacae (GSL-I-B4), recently identified by a lectin array screen (for E. coli, commercial anti-E. coli 0157 Dynabeads® were employed). These experiments suggest that the fluidized bed expansion approach for bacteria detection will be applicable to a wide range of problems beyond the specific application of detecting Salmonella in dairy products. Finally, to further demonstrate the specificity of the device, reciprocal negative controls (S. Typhimurium with anti-E. coli beads and E. coli with anti-Salmonella beads) were performed and in both cases, as expected, no expansion was observed in the time scale of the experiments (up to 10 h).
(1) |
(2) |
Inserting into this equation the previously measured capture efficiency, and leaving division time and effective volume as free parameters, allowed fitting of the calibration data from Fig. 4d. The best fit doubling time, td = 23.7 min, is very close to the 24 min measured in batch (Fig. S4†). The best fit bacteria volume is Vbac = 4.8 × 10−9 μL, also consistent with the geometrical features of S. Typhimurium (ESI†). Inserting these values into eqn (1) with the initial amounts of analyzed bacteria yields a series of expansion curves (Fig. 4c), which agree well with the experimental data, except for the latest part of the curves. Deviations from the model at high expansions are probably due to the saturation of the available immunocapture sites, preventing the recapture of newly generated bacteria (see ESI† for details). As a second conclusion, the quasi-identity of the doubling time, as measured in our device and in batch, demonstrates that the flow rate use for LB infusion is sufficient to nourish bacteria adequately, since any starvation would result in an increase in doubling time, or growth arrest in most severe situations.
In order to reduce development costs and allow widespread development including wireless communication of results, the whole imaging and analysis process can be easily carried out on a smartphone, as suggested in ref. 30. The fluidized bed technology, however, achieves higher sensitivity and specificity, and is able to operate directly from raw samples. Due to the flat nature and small footprint of the device, one could also use ultra-low-cost detection concepts31,32 (see e.g. cost analysis details in ESI†). The system can accommodate the direct infusion of complex samples such as unskimmed milk. This robustness against clogging or matrix effects, a definite advantage with regards to micro-columns, filter-based or paper-based devices, is a consequence of the fluidized nature of the capture bed, which can be perfused by liquids containing debris or particles much bigger than the capture beads or targets, as long as these contaminating objects do not present at their surface antigens targeted by the beads. In comparison with methods based on PCR, this new approach is much simpler and thus less expensive to implement, and it detects only bacteria with a proliferative potential, whereas PCR-based methods, while very precise in terms of species identification, may yield false-positive results in the presence of dead bacteria or even residuals of lysed cells.
Live bacteria are released in important amounts during and after bed expansion, which is not the case with beads devoid of specific capture antibodies (ESI Fig. 6†). The fluidized bed could thus be used simultaneously as a first line rapid detection device, sensitive to proliferative bacteria only, and as a pre-amplification module, able to yield amplifications by typically 103 to 105 in one to two hours. Thanks to this spontaneous bacteria release, the enriched broth could be directly fed to a second microfluidic molecular characterization device, or collected and sterilized for storage or mailing to a central facility for molecular analysis, without requiring any additional elution step.
Footnotes |
† Electronic supplementary information (ESI) available. See DOI: 10.1039/c6sc03880h |
‡ These authors contributed equally to this work: Amel Bendali, Sanae Tabnaoui, Lucile Alexandre. |
This journal is © The Royal Society of Chemistry 2017 |