Digitizing bioprocesses.in

We bring advanced pathogen detection in pocket-size instruments directly to the production site, enabling seamless process monitoring and control.

Today’s bio-analytical methods are confined to remote laboratories. Our sensor technology uses light-emitting µBeads as a messenger to provide in-line, real-time pathogen detection inside liquid products along the entire process chain. Our µBeads work in vitro and in situ and can be tailored to be highly target-specific.

Thus, we enhance food safety and help improve production processes.

Basic Technology

Biosensors

Conventional biosensors (Figure 1 left) are based on a microchannel, in which a wall isfunctionalized using antibodies, so that only certain targets may selectively bind. The binding reactions are then converted into electrical signals via some physical effect.

Drawbacks of conventional biosensors:
1. Laminar flow impedes the movement of targets towards the sensor area
2. Unspecific binding to the sensor area is not effectively flushed away
3. The cost of these sensors is high, and they are difficult to regenerate or replace

Biosensors based on the Fluorescent Resonator Signature (FRS) (Figure 1 right) principle, on the other hand, use freely moving sensor particles. The sensor particles can also be coated with antibodies to bind specific target molecules in the sample. However, binding events are read out optically contact-less and subsequently converted into electrical signals.

Disruptive characteristics of Fluorescence Resonator Signature (FRS):
1. High number of freely floating µBeads scan entire analyte volume
2. Spherical sensing surface avoids non-specific binding as well as specific re-binding
3. Optical technology allows for contact-less read-out of each individual µBead sensor

Figure 1: Comparison of a common biosensor (left) with biosensor based on Fluorescent Resonator Signature (right).

µBeads as free-floating sensor particles

SpheroScan® makes use of a novel approach to label-free bacterial and fungal detection. It
is based on fluorescent, specifically functionalized polymer µBeads, which bind to their
target organism while freely floating in the analyte. In contrast to state-of-the-art label free
biosensors, which are mostly embodied as microfluidic devices with the bio-functionalized
surface formed on one of the channel walls, the µBeads cruise through the analyte and thus
raise the chance of hitting their specific targets.

Figure 2: left: illustration of µBead functionalization and target binding; right: SEM micrograph of 10 µm µBead decorated with specifically bound legionella

Depending on the application, the surface of the µBeads can be functionalized with different
capture molecules such as peptides, aptamers, or antibodies. The µBeads find their targets
even in complex media.

Figure 3: Examples for surface functionalization depending on sensing application

Remote read-out of the µBeads

Sensor read-out is performed remotely by optical means, i.e., fluorescent excitation of the organic dye embedded into the polymer beads and recording of their fluorescent emission (Fig. 4 left). As illustrated in Fig. 4, right, this fluorescent emission undergoes characteristic changes upon binding of the target species on the sensor surface (Fluorescent Resonator Signature, FRS). A numeric algorithm based on Mie theory is then applied to the resultant fluorescence spectra for quantification of the bound target. Since only the spectral position of the optical resonances is evaluated and not the fluorescence intensity, the signal is very
robust so that measurements can also be made in optically turbid or dense media.

Figure 4: Schematic of Fluorescent Resonator Signature (FRS) Sensing: (left) optical set-up for excitation and readout of FRS of the freely floating sensor beads; (right) illustration of the change in FRS by specific binding of some targeted microbe to the µBead surface.

Results

The algorithm first calculates the µBead radius and the layer thickness (see Figure 5) of the
connected target on the surface. The signal can then be converted to the concentration of
the target in the medium (e.g. CFU, ppm or µg/l) using a stored calibration.

Figure 5: Basic results of FRS proprietary Algorithm: bead size distribution (left) and surface load upon protein adsorption (right)

Fields Of Application

A sensor right where quality matters the most.

Healthcare

Diagnostics
in vivo or in vitro
coming soon…

FluIDect GmbH

If you have any questions, please contact us.

Address

Winzerlaer Str. 2, 07745 Jena, Germany

Call Us

+49 (0) 3641 / 55 41 380

Email Us

info@fluidect.com