bioRxiv Science⌕ Search

bioRxiv · 10.64898/2026.10.12.758106

Microfluidic Extraction of Extracellular Vesicle-Associated Nucleic Acids for Downstream Molecular Analysis

Abstract

Aim: To develop a microfluidic workflow for extracting extracellular vesicle (EV)-associated nucleic acids (NAs) from biofluids, such as blood plasma and serum, for downstream molecular analysis. Methods: Healthy serum and plasma samples were spiked with EVs obtained from Hec-1-A cells carrying defined mutations and characterized in accordance with MISEV guidelines. The spiked samples were then processed using either the standard centrifugation-based ExoGAG protocol or a microfluidic workflow. The latter combines ExoGAG mediated aggregation of EVs with mechanical entrapment of the resulting EV aggregates in a microfluidic filtration device (EVNA-chip). The retained material was washed and on-chip lysed to release its NA cargo. NAs were subsequently purified using a commercial silica column, producing an output suitable for molecular analysis through droplet digital PCR (ddPCR). Results: The EVNA-chip recovery yield was 42.0 +/- 4.28% and 38.1 +/- 1.46% for double-stranded DNA (dsDNA) and microRNA respectively. The recovered dsDNA remained compatible with ddPCR detection of the KRAS p.G12D variant (c.35G>A) and with the assessment of MSI-associated alterations using BAT25, BAT26, NR21, NR24, and MONO27. The method was demonstrated for pilot cohort of patients with endometrial cancer. The RNA workflow supported reverse transcription and was demonstrated for the quantification of miR-X, a potential marker of Fabry disease, using patient samples and healthy controls. Conclusion: Although recovery was lower than with the standard protocol (~45% for DNA and for RNA), the centrifugation-free EVNA-chip workflow demonstrates the compatibility of the method with downstream NA molecular analyses and is advantageous for the development of an integrated, automated platform for EV-based liquid biopsy applications.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Lage, T., Macedo, D., Silva, H. I., Teixeira, A., Moreira, D., Fiorenza, N., Lago Leston, R., Vilar, A., Sampaio Marques, B., Pierantoni, L., Rodriguez, A., Azevedo, O., Ludovico, P., Muinelo Romay, L., Abal, M., Dieguez, L., Honrado, C., Ainla, A.. 2026-10-14. Microfluidic Extraction of Extracellular Vesicle-Associated Nucleic Acids for Downstream Molecular Analysis. https://doi.org/10.64898/2026.10.12.758106

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Development of a Low-cost Extrusion Multi-nozzle 3D Bioprinter for Complex Constructs

Extrusion-based multi-material bioprinting is a promising approach for fabricating complex tissue constructs, but current systems often require expensive hardware or support only one or a few numbers of bioinks. In this study, a low-cost, compact, and versatile multi-nozzle bioprinter (MNB) system was developed for pneumatic extrusion of up to 10 different inks using a rotational head. The system was integrated with a commercial 3D printer platform and controlled using custom G-code commands. Backlash compensation and nozzle-specific calibrations were experimentally determined to minimize positioning errors and airflow misalignment. The developed system showed stable repeatability in both clockwise and counterclockwise movements. Lines and various structures were successfully printed with different nozzle-switching directions and printing sequences. Representative structures including a diamond pattern, a multilayer scaffold, a pyramid structure, and a kidney-like construct were successfully fabricated. These results demonstrate that the proposed MNB system can produce complex 2D and 3D multi-material structures with good positional accuracy and repeatability.

bioengineering↗

FluOpti: an open-source system for programmable whole-plate optogenetics and multi-fluorescence imaging

Bacteria are able to self-organize into complex spatial communities, such as colonies, biofilms and swarms. Probing cells and gene networks with dynamic stimuli while preserving their spatial organization is therefore essential for understanding how bacterial communities organize across spatial and temporal scales. Optogenetics offers a powerful approach for such a task given the precise control of stimulus delivery without the perturbations normally associated with the addition of liquid inducers. However, most optogenetics devices have been developed to work with liquid cell cultures or to deliver a spatial pattern without the concurrent recording of gene responses and colony growth. Here, we describe FluOpti, an open source, low-cost device for controlling gene expression, through programmable light inputs, and recording multi-fluorescence responses and colony growth across whole petri dishes. White light LEDs are used for brightfield imaging while green and red LEDs are used as optogenetic inputs to activate and inactivate target genes via the CcaS/R two component system in E. coli. Low cost blue and orange acrylic are used as excitation and emission filters for fluorescence imaging, respectively. We developed custom software to analyze colony growth and optogenetic responses from 72-hour time-lapse experiments. A mathematical model was developed to predict gene expression levels in response to green-to-red light ratio stimuli. We use FluOpti to reveal a spatially structured response to optogenetic stimuli, with gene activation rates differing in cells located at the center and edge of colonies. to validate its use at a whole petri dish scale, FluOpti was used to depict how Voronoi territories can act as predictors of colony size, in congruence with previous studies. Together, these results demonstrate the utility of the device for studying gene networks at multiple spatio-temporal scales, from individual colonies to the whole petri dish. Performing optogenetics studies in whole petri dishes while preserving spatial arrangements could offer valuable insights into the spatial biology of gene networks in microbial populations.

bioengineering↗

Denoising broadband CARS hyperspectral images on variance-stabilized data: a unified benchmark

Broadband coherent anti-Stokes Raman scattering (BCARS) enables label-free hyperspectral chemical imaging, but weak signal components are often obscured by heteroscedastic noise. Here, we develop a physics-based variance stabilization transform and benchmark six hyperspectral denoising methods to identify effective strategies for BCARS noise reduction. The transform yields nearly intensity-independent noise variance while preserving the dispersive Raman response. Within this framework, we compare singular value decomposition, BM4D, Noise2Noise, deep image prior, self-supervised diffusion, and a cross-covariance-based singular value decomposition method (CCV) introduced here, using a shared phase-retrieval pipeline. Evaluation includes five simulated hyperspectral cubes with exact ground truth and experimental measurements of glycerol, polystyrene beads, and Caenorhabditis elegans. In simulations, variance stabilization reduces the ratio of maximum to minimum channel noise variance from approximately 72 to 1.2. Deep image prior and self-supervised diffusion achieve the highest mean foreground peak signal-to-noise ratios. CCV matches the mean foreground structural similarity of deep image prior with substantially shorter runtime and no per-cube rank tuning. Experimental comparisons reveal sample-dependent performance. These results establish physics-based variance stabilization as a common framework for adapting and evaluating hyperspectral denoisers for BCARS, with CCV offering a practical balance of reconstruction fidelity, computational speed, and automated operation.

bioengineering↗