Paper-based genetic assays with bioconjugated gold nanorods and an automated readout pipeline

Abstract

BackgroundPaper-based biosensors featuring immunoconjugated gold nanoparticles have gained extraordinary momentum in recent times as the platform of choice in key cases of field applications, including the so-called rapid antigen tests for SARS-CoV-2. Here, we propose a revision of this format, one that may leverage on the most recent advances in materials science and data processing. In particular, we focus on an amplifiable DNA rather than a protein target, and we assess the replacement of gold nanospheres with anisotropic nanorods, which are about 10-fold brighter and multiplexable. ResultsBy comparison with a gold-standard method for dot-blot readout with digoxigenin, we show that gold nanorods entail much faster and easier processing, at the cost of a higher detection limit (from below 1 to 10 ppm in the case of plasmid DNA containing a target transgene). In addition, we test a complete workflow for systematic acquisition and machine-learning regression of photographs of dotblot membranes as a tool to gain more analytical sensitivity and potential for quantification. A leaveone-out strategy for training and validation with as few as 36 sample instances already improves the detection limit reached by the naked eye by a factor around 2. ConclusionsTaken together, we conjecture that the synergistic combination of new materials and innovative tools for data processing may bring the analytical sensitivity of paper-based biosensors to approach the level of lab-grade molecular tests.

Exploring the complexity of African populations variability with Machine Learning

“…Machine Learning (ML) algorithms, in particular, are the core of many successful applications, covering nowadays every field of knowledge, from engineering [6], physics [7] and nanophotonics [8]- [10], up to medicine [11]- [14] and cultural heritage [15], [16].…”