X3 - Solid-state nanopore sensor as a sample quality control tool for cfDNA in point-of-need sequencing applications

Introduction: : Point-of-Need (PoN) sequencing devices like ONT’s MinION enable decentralized genomic analysis but lack compatible sample quality control (QC) tools. Rigorous QC is critical before library preparation for dependable, time-sensitive sequencing outcomes at PoN. For example, the quality of cell free (cf)DNA plasma samples determined by the quantity and percentage (%) of cfDNA can greatly impact the coverage and sequencing yield resulting in reduced sequencing efficiency. Traditional laboratory-based methods such as UV-Vis spectrophotometry and Qubit fluorometry quantify the total DNA only in sample, as compared to the capillary electrophoresis which can quantify the total cfDNA and %cfDNA. However, a capillary electrophoresis (CE) process requires complex instrumentation to drive high voltage electrophoresis, fluorescence/UV detectors, large input quantities of fluorescent labelled molecules, and trained staff to operate making it unsuitable for PoN applications. In this study, we demonstrate a label-free nanopore-based sample QC tool for plasma cfDNA samples, amendable for PoN settings. Using internal marker DNA and multi-Gaussian fitting of blockade amplitude distributions, our method measures the cfDNA concentration and %cfDNA by profiling size-specific translocation events. We validated the approach with mock samples containing 150 bp target DNA, 1 kbp marker DNA, and 10 kbp high molecular weight (HMW) gDNA contaminants, showing precise quantification and qualification. Application to aging plasma samples showed trends consistent with capillary electrophoresis results, with negligible differences in cfDNA concentration and %cfDNA between methods. Our results demonstrate the nanopore QC assay as a robust, field-deployable tool for cfDNA sample quality assessment, addressing a critical bottleneck in PoN sequencing workflows.

Materials and

Methods: : Quartz capillaries (0.5 mm ID, 1 mm OD; Q100-50-7.5, Sutter Instrument) were cleaned using piranha solution (H₂SO₄:H₂O₂, 3:1) at 85 °C for 30 min, rinsed with DI water, and vacuum-dried at 120 °C. Nanopores were fabricated using a laser pipette puller (P-2000, Sutter) with a two-line recipe: Line 1 (heat 750, filament 5, velocity 50, delay 140, pull 50); Line 2 (heat 715, filament 4, velocity 30, delay 145, pull 215). Pore diameter was estimated from open-pore conductance. Pulling parameters were tuned as needed for fabricating different size nanopores. Mock samples with various concentrations (10 – 200 pM) of 150 bp as representative cfDNA, and fixed concentrations (100 pM each) of 1 kbp as internal marker, and 10 kbp as representative HMW gDNA) were prepared in 4 M LiCl Tris-EDTA pH 8.0 buffer. cfDNA was extracted from a healthy donor plasma sample (BioCollections, USA) using the QIAamp Circulating Nucleic Acid Kit (QIAGEN, #55114). The vendor performed double centrifugation 2 h post-collection; plasma was shipped and stored at –80 °C. 1 mL of plasma was processed and eluted in 50 µL of elution buffer. Extracted cfDNA was analyzed by Agilent TapeStation 4150 CE, and nanopore-based QC assays. Nanopore ionic current data were acquired at 100 kHz using an Axopatch 200B amplifier, NI 6363 DAQ, and 5 kHz low-pass filter in LabVIEW. Data were recorded in triplicates for each 30 min of measurement. Event extraction and multi-Gaussian fitting of blockage amplitude histograms were performed in custom MATLAB and Python scripts.

Results, Conclusions, and Discussions:: The nanopore-based sample quality control (QC) assay presented here enables label-free quantification and qualification of cfDNA samples, offering a point-of-need (PoN) alternative to conventional lab-based capillary electrophoresis (CE), as illustrated in Figure 1a,b. Its PoN amendability supports rapid QC workflows compatible with field-deployable sequencing platforms. A known-concentration internal marker (1 kbp dsDNA) allows robust quantification of 150 bp dsDNA targets (as representative cfDNA) even in the presence of HMW DNA contaminants. This strategy mitigates variability arising from nanopore size heterogeneity. As shown in Figure 1c, current-time (I–t) traces and multi-Gaussian fitting were used to differentiate and quantify 150 bp targets in a mock sample mixture of 150, 1k, and 10k bp DNA fragments at 120, 100, and 100 pM, respectively, using nanopores with diameters in 5 to 20 nm rang. Figure 1d highlights minimal variation in measured 150 bp concentration and relative percentage (%150) across nanopores of varying diameters, with a coefficient of variation (CV) below 15%, underscoring the assay’s nanopore-size-independent performance. The correlation between measured and known 150 bp concentrations (10 – 200 pM), with constant 1 kbp marker and HMW DNA background, is presented in Figure 2a,b. The assay exhibits excellent linear correlation for both absolute and relative quantification of the 150 bp component.
To validate real-sample applicability, time-dependent degradation of plasma-derived cfDNA was analyzed. cfDNA was extracted on five different days following plasma separation and assessed using both the nanopore QC assay and a commercial TapeStation CE platform (Figure 3a). As shown in Figure 3b, the cfDNA concentration declined significantly between Day 8 and Day 34 after plasma separation, stabilizing at ~7 ng/mL afterwards. Both platforms demonstrated strong agreement in cfDNA quantification, supported by the correlation plot inset. Since no HMW genomic DNA was observed (Figure 3a), %cfDNA remained stable over time (Figure 3b).
The proposed label-free electronic nanopore sample QC assay demonstrates reliable and reproducible cfDNA quantification and qualification, making it highly suitable for PoN applications and pre-analytical QC in next-generation sequencing workflows.

Acknowledgements and/or References (Optional):: This work was partially supported by the National Science Foundation (2319913, 2045169) and the National Institute of Health (R33AI147419), and USDA (NIFA 2022-11225). Any opinions, findings, conclusions, or recommendations expressed in this work are those of the authors and do not necessarily reflect the views of the National Science Foundation, the National Institutes of Health, or the USDA.