Autonomous Capillary Biochip to perform multiplexing ... · Diogo, Chu V., Aires-Barros MR, 2016). The mask was designed in a CAD software and transferred to an aluminum mask using

1 Autonomous Capillary Biochip to perform multiplexing immunoassays

Autonomous Capillary Biochip to perform multiplexing immunoassays

J.M.D. Machado INESC Microsistemas e Nanotecnologias and IN-Institute of Nanoscience and Nanotechnology, Lisbon, Portugal

Abstract

Microfluidics being strongly associated with nanotechnology leads with small amounts of reactants and

samples. This way, microfluidics devices have been used in medicine and biology. Probably, the most promising

aspect of microfluidics is the possibility of lab-on-a-chip allowed by capillary microfluidics since these devices are

portable, user-friendly, equipment-free and allow a straight control of the fluid dynamics.

In this project a colorimetric autonomous capillary chip able to perform a multiplexed quantitative

immunodetection is described. The performance of this device was tested through the detection of 3 mycotoxins

simultaneously (OTA, AFB1 and DON) at the required regulatory limits, within less than 8 minutes. The detection

limits obtained were 0.183, 0.153 and 0.1 ng/mL for OTA, AFB1 and DON respectively. Cross-reactivity assays were

performed to validate the system in question. Even more, corn-based feed samples spiked with the three toxins were

successfully analyzed.

This chip proved be adequate for the propose since it is user-friendly (the user only loads the reactants

near to the inlets), portable and provides a fast response. The device can be adapted to detect other analytes.

Keywords: microfluidics, capillary, multiplexing, colorimetry, smartphone, mycotoxins, capillary based

capillary systems, self-pumping lab-on-a-chip.

1. Introduction

The development of microfluidic

devices, comprehending the manipulation of

fluids in the range of tens to hundreds of

micrometers (1-100 micrometers), provide

several key advantages within the field of

analytical chemistry.

Resorting to properties such as high

surface-to-volume ratios, low reagent

consumption, prevalence of viscous and

capillary forces and laminar flow, several

strategies have been developed aiming at

implementing features such as portability, high

sensitivity, integration of several multi-functional


modules, low-cost per test, short response

times, reproducibility and high-throughput

(Bhushan, 2010)(Mark, Haeberle, Roth, von

Stetten, & Zengerle, 2010)(Zheng et al., 2012).

Taking advantage of these properties, this type

of devices can be ideally used directly at the

point-of-need, which is critical in developing

countries or even in laboratories. However, the

adoption of microfluidics has bed hindered

mostly due to the complexity in the handling of

liquids and signal acquisition(Ng, Uddayasankar,

& Wheeler, 2010) or even the autonomous

insertion of liquids(Novo, Chu, & Conde,

2014)(Juncker et al., 2002). For this reason,

many approaches are currently being explored

aiming at overcoming these challenges, such as

the integration of photosensors, the

development of new channel network designs

and valves and the simplification of the

immunoassay architecture (Kang, Chung,

Langer, & Khademhosseini, 2008), thus

rendering these systems simpler and more user-

friendly. In particular, the use and optimization of

passive liquid flow systems based on capillary

forces are generally simpler approaches where

the flow dynamics are controlled by the

microchip design, surface hydrophilicity and

liquid properties such as viscosity and

hydrophobicity(Volpatti&Yetisen,2014)(Zimmerm

ann,Schmid,Hunziker,&Delamarche,2007)(DeM

ello, 2006)(Zimmermann, Schmid, Hunziker, &

Delamarche, 2007). Furthermore, unlike the

classical paper-based lateral flow assays which

have been under development and

commercialized for several decades, (Haeberle

& Zengerle, 2007)(Gervais, Hitzbleck, &

Delamarche, 2011) microfluidics presents the

advantages of enhanced scalability of

multiplexing analysis, precise and easily

adjustable control of flow conditions under a

laminar regime, minimization of the consumption

of reagents and samples, while still being

portable, potentially low-cost and providing short

times of analysis. (Temiz, Lovchik, Kaigala, &

Delamarche, 2015) (Gervais et al., 2011). Along

these lines, there have been a number of recent

reports on the development of capillary driven

devices, particularly regarding the performance

of immunoassays. Examples of this are paper

based capillary systems(Ahmed, Bui, & Abbas,

2016) and PDMS chips(Anfossi et al., 2012).

(Novo, Volpetti, Chu, Conde, & Innovation,

2013)(Novo, Chu, & Conde, 2014)(Lillehoj & Ho,

2010)(Mohammed & Desmulliez, 2014 (Gervais

& Delamarche, 2009).

One particular application that has not

been currently approached resorting to capillary

microfluidics is the detection of mycotoxins in

food and feed samples. These toxins, produced

by fungi during transport or storage, are highly

relevant contaminants at a worldwide scale

since they are associated with many harmful

effects to both human and animal health

including carcinogenic, genotoxic and

hepatotoxic effects and have also reported

synergetic effects, making the multiplexing

analysis particularly relevant.(Marin, Ramos, &

Sanchis, 2013)(Anfossi, Giovannoli, & Baggiani,

2016) Within the scope of food-safety, a novel

colorimetric autonomous capillary chip is

reported, able to perform the rapid multiplexed

immunodetection of three mycotoxins, namely

ochratoxin A (OTA), aflatoxin B1 (AFB1) and

deoxynivalenol (DON), at relevant limits within


less than 8 minutes. Furthermore, aiming at

simplifying the assay towards point-of-use

applications, the colorimetric signal transduction

was performed resorting to a mid-range

smartphone camera coupled to a simple image

processing procedure.

2. Experimental methods

2.1. Chemicals and biologicals

OTA, AFB1, DON PBS and toxins-BSA

conjugates were purchase from Sigma-Aldrich.

α-toxins-HRP affinity purified rabbit polyclonal

antibodies were purchased from ImmuneChem

(Burnaby, Canada) as a 250 g/mL solution.

TMB was purchase from ThermoFisher

Scientific.

Solutions were prepared by diluting the

stock in PBS. The surface blocking agent, a 4%

(w/w) BSA solution in PBS was prepared from a

Sigma-Aldrich A7906 stock.

Solutions were stored in the fridge at

5ᵒC and used in several experiments. Sodium

phosphate monobasic, potassium phosphate

dibasic and Polyethylene glycol with an average

MW of 8000 g/mol were purchased from Sigma-

Aldrich (Sintra, Portugal).

2.2. PDMS structures microfabrication

PDMS structures were fabricated in

polydimethylsiloxane (PDMS) using common

soft lithography (Soares R. R. G., Ramadas

Diogo, Chu V., Aires-Barros MR, 2016). The

mask was designed in a CAD software and

transferred to an aluminum mask using a

Heidelberg DWLII direct write lithography system

followed by wet chemical etching of the Al

pattern with a commercial Al etchant. The mask

was then used to pattern SU-8 (50 formulation,

Microchem, Newton, MA, USA), spin-coated on

a clean Si substrate to an average height of

50μm by exposure to UV light. Non-exposed

regions were developed for 5–10 min in

propylene glycol monomethyl ether acetate

(PGMEA) (99.5%, Sigma-Aldrich, Sintra,

Portugal) and hard baked at 150◦C for 15 min. A

Sylgard 184 silicon elastomer kit (Dow-Corning,

Midland, MI, USA) with a curing agent ratio of

1:10 was used to reproduce PDMS structures by

pouring the solution over the molds and then

baking in an oven for 1h30min at 70ºC.

After this, the chambers were spotted

with 0.4 μL of α-mouse in a concentration of 0.1

mg/mL and 1 mg/mL of the three respective

conjugates toxins-BSA (bovine serum albumin).

Subsequently to evaporation, the structures

were sealed against clean glass treated using

PDC-002-CE Harrick Plasma (800 mTorr, 1 min)

leaving the inlets and outlets opened to the air.


2.3. Immunoassay experiments

5-10 mins after the sealing of the

structure, 4μL of BSA 4% were delivered to the

system in order to block the surface and

minimize the signal due to unspecific

adsorptions. When BSA was exhausted 2μL of a

mixture containing 5 μg/mL of α-OTA and α-

AFB1, 10 μg/mL of α-DON labeled with HRP and

defined concentrations of free toxins were

added. To conclude the immunoassay were

added 4-6μL of TMB (Figure 2).

2.4. Corn based feed sample processing

using aqueous two-phase separation

(ATP)

400 mg of corn based feed were spiked

with 1μL of toxins prepared in ethanol (OTA: 80

μg/mL, AFB1: 8μg/mL, DON: 0.8 mg/mL) to

obtain final concentrations of 50 ppb OTA, 20

ppb AFB1 and 500 ppb DON. The Eppendorf

was submitted to vortex and left open during 5

min to evaporate the toxins. 75μL of PEG 8000

50% (w/w) and 1200μL of phosphate 15% (w/w)

were added. Again, it was performed a rapid

vortex and then a vigorous vortex during 3

minutes. After this, it was performed a

centrifugation for 15 minutes. 40μL of

supernatant were collected and submitted to

centrifugation for 5 minutes. 1μl of this clean

phase was mixed with 14μL of a solution holding

α-toxins (α-OTA: 2.50 μg/mL, α-AFB1: 5 μg/mL,

α-DON: 5μg/mL). Then, the sample was

analyzed according to the procedure indicated in

section 2.3.2.

2.5. Signal acquisition and data analysis

The colorimetric signal was acquired

using a smartphone camera (Samsung Galaxy

Grand Prime Value Edition SM-G531F, 8 MP,

3264 x 2448 pixels). Pictures were taken

manually, at a focal distance of 30 cm, using an

amplification of 3,6X. Afterwards, they were

analyzed using ImageJ software (National

Institutes of health). The background was

subtracted and a square area of 600 pixels2 was

defined, corresponding on average to about half

the total area of the obtained spots, on the

center of the spot. The measured signal is

proportional to the transmittance after computing

the difference between maximum and minimum

color intensity values. Additionally, to normalize

the signal, the value was divided by the signal

provided by the internal control (reference

chamber). To better distinguish the spot area

was applied grayscale (32-bit). Similarly, isolines

maps and 3D profile plots were also obtained

using the same software (figure 2).

Figure 1 – 600 pixels2 square centered in

the spot and respective analysis in which it is obtained the isolines map and the 3D

profile.


3. Results

3.1. Multiplexed competitive immunoassay design

The design of the competitive immunoassay used to detect specific mycotoxins in solution is

described in figure 2. Considering the competitive nature of the assay, antigens (toxins conjugated with

BSA) are immobilized on the solid phase by physisorption only manually spotting BSA-mycotoxin

conjugate solutions prepared in PBS in the defined chamber. Then, higher concentrations of toxins in

solution compete with the toxins immobilized on the PDMS surface for binding to the α-mycotoxin IgG

molecules in solution, resulting in a signal that is inversely proportional to the concentration of free toxins.

It is important to highlight that the simple physisorption-based approach selected to immobilize the

molecules avoids unfavorable spatial orientations during immobilization, which can lead to lower

sensitives(Trilling & Zuilhof, 2013). To further simplify the assay, primary antibodies were directly labeled

with HRP and a colorimetric substrate, namely a blotting TMB solution, was used to generate a

measurable signal.

Figure 2 – Schematic representation of the dcELISA, using a non-contaminated sample (A) and a sample spiked with a certain

concentration of OTA, AFB1 and DON(B). The blue circle in the final step represents the colored precipitates accumulated in the

chamber while flowing TMB in conditions where the anti-toxin-HRP molecules are immobilized on the surface via affinity

interactions with the mycotoxin-BSA molecules.

3.2. Microfluidic structure design

3.2.1. Autonomous and sequential fluid delivery

The microfluidic structure design (figure 3) can be divided in two main parts according to their

proposes (autonomous fluid delivery and control of fluid dynamics).

In order to develop an autonomous and more user-friendly device, a sequential module (figure 3

C) based on the work of Pedro Novo and co-workers(Novo et al., 2013) was integrated in the microfluidic

structure as schematized. Each inlet drains into a 300μm wide microchannel. The inlets 1st and 2nd

BSA 4% BSA 4%


comprise a 40μm wide channel that connects to inlets 2nd and 3rd respectively. Inlet 1st delivers directly to

a common microchannel which extends to the reaction chambers and consequently to the capillary

pumps. The channels that drain solutions from inlets 2nd and 3rd are associated with the common channel

through a series of 50×50μm2 passageways separated by 200μm. The 300μm channel prevents liquids to

flow spontaneously from the inlets to the common microchannel (which would result in inter-inlet

contamination). The 40 μm thin channel, due to the negative pressure, acts as a valve that avoids the

flow in either directions (e.g., from inlet 1st to 2nd and vice-versa) and it is used as a trigger valve.

The number of inlets of this module can be increased, allowing the performance of more complex

assays.

3.2.2. Control of fluid dynamics during the immunoassay

Figure 3 – Events sequence related with the autonomous insertion of liquids (A). (A1) Empty inlets open to air; (A2) red solution placed at inlet 1st, (A3) solution from inlet 1st flows to common microchannel while the remaining are blocked by an entrapped air bubble; (A4) when the solution from inlet 1st is emptied, the fluid from inlet 2nd flows to the common microchannel; (A5) when solution from inlet 2nd is exhausted, the fluid from inlet 3rd flows to common microchannel. Detailed dimensions of final fast pump (B), sequential module (C) and fast pump (E). top view of the entire non-sequential structure of the capillary chip (D).

The second section of the hard mask (figure 3D) is constituted by 4 reaction chambers in which

an internal control (α-mouse) is spotted, followed by conjugates of OTA, AFB1 and DON with BSA (figure

3D, green square dots). Downstream of the chambers, two different types of channels were added in

series: slow pumps (figure 3D, black boxes) and fast pumps (figure 3D, orange boxes, E). The slow

pumps correspond to standard rectangular channels, 22mm long and 300μm wide. This type of capillary

pumps has the characteristic of accumulating hydraulic resistance over time, thus resulting in a

progressive decrease in flow rate. Slow pumps thus providing lower flow rates, are used in adsorption

steps. The slow pump communicates with the fast pumps through 50×50μm2 passageways separated by


200μm. The Fast pump is a long serpentine channel with 300μm wide and 120mm long, including

50×75μm2 passageways separated by 150μm. This allows the liquid proceeds to bypass the channel

walls after each turn, which dramatically reduces the hydraulic resistance along the microchannels.

The flow rates achieved with this pumps are higher and stable over the total length of the pump

which is critical to fully replace the solutions inside the detection chambers in between each of the

immunoassay steps. The last pump, henceforth named as final fast pump (figure 3D, blue square dots, E)

is based on the design by Delamarche and co-workers(Zimmermann, Schmid, Hunziker, & Delamarche,

2007). The capillary pump comprises posts of interlocked squares and can be considered an ultra-fast

pump since it is able to pump TMB at higher flow rates ( 3 μL/min) and accommodate a higher volume of

this substrate, thus approaching a reaction-limited rather than a substrate-limited regime.

In figure 4 and table 1, are presented the fluid behavior along the capillary chip and the conditions

established for this immunoassay after optimization, namely the flow rates along the different capillary

pumps and the volume of solution delivered in each step of the assay. The measurements presented

were experimentally obtained using the volumes of BSA 4% and PBS (phosphate buffer saline) indicated.

Figure 4 – Velocity profile and throughout the immunoassay (reactants volume, residence time and flow rate in each step). In the blocking step, BSA 4% is drained through all first pump. α-toxins interact with the immobilized toxins mainly in the second slow pump and the detection occurs with the delivery of TMB in the second fast pump and final fast pump (Measurements performed in non-sequential structure).


From the previous results (figure 4, table 1) it is perceptible that the flow rate achieved in slow

pumps is lower than the flow rate measured in fast pumps which indicates that the configuration of the

capillary chip is adequate for the performance of this dcELISA.

3.3. Calibration curves for OTA, AFB1 and DON

Since from previous studies was proved the absence of cross-reactivity, individual calibration

curves were obtained measuring the signals resulting from a non-contaminated sample and from samples

contaminated with increasing concentrations of free toxins. Considering the regulatory limits settled down

for each toxin were spiked 10, 20, 50, 80 and 100 ng/mL of OTA and DON. In the case of AFB1, since the

maximum concentration allowed is lower, were used solutions 10x less concentrated in this mycotoxin.

For the three toxins were obtained linear curves, which proves that the response is directly

proportional to the level of contamination. Regarding AFB1 it was obtained a curve described by the

equation y=-0.6x+0.789. OTA and DON presented a similar response, which can be defined by the

equation y=-0.32ln(x)+1.67 (figure 5).

Figure 5 – Data acquired with smartphone camera

for increasing concentrations of free-toxins (A),

corresponding to non-contaminated samples (i), 10

ng/mL (ii), 20 ng/mL (iii), 50 ng/mL (iv), 80 ng/mL (v)

and 100 ng/mL (vi) of OTA and DON. For AFB1 were

used concentrations 10 X lower. Individual

calibration curves for OTA (black squares), AFB1 (red

circles) and DON (blue triangles) (B). For each point

were measured 5 replicates and error bars

correspond to SD.


3.4. Evaluation of cross reactivity

After calibration curves have been obtained it is essential guarantee the accuracy of the assay

using this system, namely through cross-reactivity tests. Considering this, were analyzed samples

contaminated with one (figure 6 A and B) or two toxins (figure 6 C and D). According to the graphs A and

B (figure 6) it is concluded that the signal of each toxin is not affected by the presence of the other two

toxins, which is in agreement with the literature. The second assay was performed using a structure

coupled with the sequential module after have been conferred that the flow rates measured in this

structure are comparable to the flow rates previously obtained with non-sequential structure (figure S5).

As it was expected, the signal intensity decreases for contaminated samples, means that, the

quantification followed the trends revealed in the calibration curves.

Figure 6 – Data acquired with smartphone camera from a sample contaminated with one toxin (A) or two toxins (B) and

respective quantification displayed in bar graphs (B and D). Results concerns to 3 replicates and error bars refers to SD.

3.5. Detection of mycotoxins in spiked corn-based


feed samples after aqueous-two-phase extraction

One of the most important aspects in this type of quantification is the fact that usually the sample

under analysis has the interference of a complex matrix, which, frequently, leads with a loss of sensitivity.

A highly prominent example of this, is the case of wine samples, commonly contaminated with

OTA(Soares et al., 2014)(Anfossi et al., 2012). Several strategies based on sample processing have

been developed aiming a more precise detection. In this case, it was adopted a strategy developed by

our group and already optimized. This method comprises an aqueous-two-phase extraction promoted by

PEG(Soares et al., 2014). Corn-based feed samples were spiked with toxins and submitted to this

treatment. Then samples were analyzed according to the conditions referred previously. Two different

situations in which the sample was spiked with two toxins (500 ppb of OTA and 20 ppb of AFB1) or three

toxins (500 ppb of OTA, 20 ppb of AFB1 and 50 ppb of DON) (figure 7) were evaluated.

Although, in this situation, the analysis has been less sensitive (the signal decreasing was lower)

the analysis proves that it is possible detect the three toxins in complex matrices. The detection sensitivity

can be improved with future optimization of the extraction process or even using other method to process

the sample.

Figure 7 – Data acquired from cell phone using a corn mixture used to produce

salmon feed non-contaminated (i) or spiked with OTA and AFB1 (A ii, B Sample A)

or the three toxins (A iii, B sample B) and respective quantification displayed

in bar graph (B). The error bars correspond to SD.


4. Conclusion and discussion

Here is described a microfluidic capillary chip able to perform a multiplexed quantitative

dcELISA within less than 8 minutes.

Although this chip has shown be reproducible, some aspects could contribute to increase

its reproducibility. For instance, the control of the contact angle is limited (figures S1 and S2) and

the spotting was performed manually which leads with variations regarding the volume, uniformity

and spot area. The spatial arrangement of reaction chambers revealed be adequate since it

allows neglect variations related with TMB kinetics, different light sources and focal distances.

The number of reaction chambers can be increased allowing the detection of more

analytes, however, probably this should implicate a change in the configuration of the final fast

pump. Namely, the volume of TMB required should be higher and this possibly will implicate an

expansion of this pump. As well, the chip design can be changed, to carry out more complex

assays.

As proof of concept, thee relevant mycotoxins (OTA, AFB1 and DON) were detected in

spiked samples. Even more, corn-based feed samples spiked with the three toxins were

successfully analyzed. The detection limit obtained was 0.183, 0.153 and 0.1 ng/mL for OTA,

AFB1 and DON respectively.

The detection method, although efficient and simple, is a color intensity-based method

being, this way, dependent of the user's interpretations.

This device is adequate for point-of-use applications since doesn´t require external

equipments, the user only needs to load the reactants and the signal can be read by the naked

eye.

Although some improvements can be done. The most immediate enhancement, perhaps,

is the integration of photodiodes opening the possibility to fluorescence and chemiluminescence.

Other interesting perspective is the performance of sample processing directly in the chip.

Maybe, two more distant, however promising possibilities, are the incorporation

of loading regions in the inlets where the solutions can be stored until the beginning of the

experiments without evaporate (which implicates the performance of studies regarding the

stability of reactants at room temperature) and the development of an android application to

perform the same analysis than ImageJ software.


5. References

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Gervais, L., Rooij, N. De & Delamarche, E. Microfluidic Chips for Point-of-Care Immunodiagnostics. Adv. Healthc. Mater. 23, 151–176 (2011).

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6. Supplementary information

Figure S1 - Graphic representation of contact angle measured in untreated glass (square) and after treatment with UVO (circle) or plasma (triangle). The microfluidic chip was maintained 15 min in vacuum after sealing.

Figure S4 – Area containing the 4 spots area and respective Image J analysis (isolines map and 3D plot profile).

Figure S5 – Comparison of velocity profiles measured with Sequential Structure and non-sequential structure.

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Autonomous Capillary Biochip to perform multiplexing ... · Diogo, Chu V., Aires-Barros MR, 2016). The mask was designed in a CAD software and transferred to an aluminum mask using