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Abstract: The aim of our research was to develop a faster way to detect resistant bacteria. Incubation times are the main obstacle to overcome. Microfluidics is perfect, simply because the cell density increases rapidly in comparison to conventional techniques. The fluids, in our case droplets filled with growth medium, will contain antibiotics. If bacteria are resistant against this antibiotic then they proliferate and fill the droplet. It is our assumption that the viscosity and cell density are correlated, if true then droplets could be separated using a mechanism to sort the droplets based on their viscosity. Our research focused on 2 aspects; the justification of our assumption that the difference in viscosity between filled and empty droplets was significant and to try sorting the droplets using a self-designed chip.Samenvatting: Het streven van ons onderzoek is de detectie van resistente bacteriën te versnellen. Resistente bacteriën zijn immuun voor een groot scala aan antibiotica. Met behulp van microfluidics, het manipuleren van kleine volumes, kan de detectie van deze bacteriën vele malen sneller in vergelijking tot conventionele technieken. De cel dichtheid in een 80 nL druppel neemt vele malen sneller toeneemt dan in een 250 mL erlenmeyer. Onze verwachting is de viscositeit, stroperigheid van een vloeistof, samenhangt met de cel dichtheid. Aangezien druppels met resistente bacteriën na verloop van tijd gigantische hoeveelheden cellen bevatten zal er een significant verschil in viscositeit zijn tussen resistente druppels en niet-resistente druppels is de verwachting. Deze druppels kunnen vervolgens door middel van hun viscositeit van elkaar gescheiden worden. Het onderzoek was tweeledig; er moest een significant verschil tussen gevulde en lege druppels worden aangetoond en er werd getracht om met behulp van een zelfontworpen chip deze druppels te scheiden.

Introduction: Hospitals all over the world are ringing the alarm bells because of antibiotic resistant bacteria, the most infamous MRSA. These bacteria are hard to treat and can cause much harm when left unchecked. In 2005, 1.02 in 10,000 patients came in to contact with MRSA [1]. This is an exceptionally high number. Fast detection of antibiotic resistant bacteria would be a huge leap forward in the battle against bacteria such as MRSA.

Nowadays screening for MRSA can take up to 48 hours, which can be improved drastically with modern techniques. The critical point in detection time is the incubation time needed to increase the cell density in the sample to detectable levels. This problem can be solved by making use of microfluidics.

Microfluidics is an emerging field in which small volumes of fluid and their behaviour are studied. A practical application of microfluidics is a LOC, lab-on-a-chip. These LOC’s are basically chips in which a laboratory function is integrated and through this function a small amount of liquid can be manipulated as if it were in the macro world.

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Microfluidic screening for resistant bacteria based on viscosity

Alex Kolmus, Rebecca Wallrafen, Marilen Benner, Marloes van den Akker and Wouter Hetebrij

Supervisor: Dr. Bas van de Meerakker

From left to right: Alex Kolmus, Wouter Hetebrij, Marloes van den Akker, Rebecca Wallrafen and Marilen Benner

Figure 1: A few examples of LOC’s made out of glass, the largest chip is several centimetres long Photo courtesy Micronit.

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Research Proposal: A recent innovation in microfluidics is droplet sorting based on viscosity. This technique stands out because of its reliance on an intrinsic property of droplets, viscosity. Almost every other technique for sorting/detection is based on a non-inherent property of the droplet, for example fluorescence.

The central idea behind our LOC is that each droplet will contain antibiotics and few bacteria from a swap. When the bacteria are resistant against the antibiotics, it will flourish and multiply, otherwise it will die. After x doubling times, the droplets with living bacteria will differ greatly in viscosity in respect to the droplet without living bacteria. When sorted based on viscosity, see figure 2, droplets which do not contain bacteria will be sorted into the “low viscosity section”. If a droplet does not get sorted into this section, it can be concluded that it contains bacteria that are resistant against antibiotics.

To justify our assumption that the difference in viscosity between filled and empty droplets is significant, the viscosity of droplets with different concentrations in bacteria have to be determined. Measuring the viscosity of a droplet can be done using the deformation index, also known as the DI [2]. The DI is defined as the length to

width ratio of a droplet, it can be determined using a small setup [2]. Suppose a droplet was formed and guided towards the exit through a small tube. The droplet will be forced to stretch horizontally when entering a tube with a smaller radius than the droplets and therefore the DI of the droplet is increased, see figure 3a. At the end of the tube the droplet will regain full freedom and bounce back causing it to stretch vertically, see figure 3b, before becoming a sphere once again, see figure 3c.

Preliminary results: Figure 4 shows the correlation between the DI and the OD (optical density a measure for cell density). There is a significant difference in DI between the OD’s of 0.01 (quite empty droplet) and 1.08 (somewhat filled droplet). When figure 4 is compared with similar graphs [2], filled droplets have a higher viscosity which is in agreement with [3]. Outlook: Our preliminary results are promising and show great potential. The actual chip hasn’t successfully sorted droplets at an accurate rate, but this mainly due to the short timeframe we had to work in. We remain confident that detection of resistant bacteria using microfluidics is a viable alternative to traditional methods.

References[1] K. Kaier, N. T. Mutters, and U. Frank. Bed occupancy rates and hospital-acquired infections should beds be kept empty? Clinical Microbiology and Infection, 18(10):941:945, 2012.[2] J. C. A. Cluitmans, V. Chokkalingam, G. J. C. G. M. Bosman, W. T. S. Huck, and R. Brock. Alterations in red blood cell deformability during storage and disease: A microfluidic approach. Not published yet.[3] G.K. Batchelor. The effect of brownian motion on the bulk stress in a suspension of spherical particles. Journal of Fluid Mechanics, 83:97:117, 1977.

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Figure 3: Schematic viewing of the deformation steps. 1a; a sausage like droplet, all droplets have the same DI. 1b; the droplets bounces back to its original spherical shape, depending on the viscosity the droplet either forms a horizontal sausage or more of an egg like droplet. 1c; the droplet has returned to its spherical shape, with a DI of 1.

Figure 2: a simplistic view of a possible sorting mechanism

Figure 4: The correlation between the DI and the OD, it is clear that there is a strong correlation between the density (OD) and the viscosity (DI)