Biology subjects

Gines, G.

Publications and source records attributed to Gines, G..

3 recordsLinked to original sources

bioRxiv2022

Silicon as a microfluidic material for imaging and incubation of droplets

Droplet microfluidics has become a powerful tool in life sciences, underlying digital assays, single-cell sequencing or directed evolution, and it is making foray in physical sciences as well. Imaging and incubation of droplets are crucial, yet they are encumbered by the poor optical, thermal and mechanical properties of PDMS - the de facto material for microfluidics. Here we show that silicon is an ideal material for droplet chambers. Si chambers pack droplets in a crystalline and immobile monolayer, are immune to evaporation or sagging, boost the number of collected photons, and tightly control the temperature field sensed by droplets. We use the mechanical and optical benefits of Si chambers to image [~]1 million of droplets from a multiplexed digital assay - with an acquisition rate similar to the best in-line methods. Lastly, we demonstrate their applicability with a demanding assay that maps the thermal dependence of Michaelis-Menten constants with an array of [~]150,000. The design of the Si chambers is streamlined to avoid complicated fabrication and improve reproducibility, which makes Silicon a complementary material to PDMS in the toolbox of droplet microfluidics. Significance StatementAs the technological engine behind single-cell sequencing and digital assays, droplets microfluidics has revolutionized life science and molecular diagnosis, and is making foray into physical sciences as well. Observing droplets in a controlled manner is becoming crucial, but PDMS - the de facto material of microfluidics - hampers imaging and incubation. Here we revisit silicon as a microfluidic material and show that its superior mechanical, optical and thermal performances improve the throughput and operation of droplets assay.

biochemistry↗

bioRxiv2022

Neural coding of temperature with a DNA-based spiking chemical neuron

Complex organisms perceive their surroundings with sensory neurons which encode physical stimuli into spikes of electrical activities. The past decade has seen reports of DNA-based chemical neurons that mimic artificial neural networks with chemical reactions. Yet, they lack the physical sensing and temporal coding of sensory biological neurons. Here we report a thermosensory chemical neuron based on DNA and enzymes that spikes with chemical activity when exposed to cold. Surprisingly, this chemical neuron shares deep mathematical similarities with a toy model of a cold nociceptive neuron: they follow a similar bifurcation route between rest and oscillations and avoid artefacts associated with canonical bifurcations (such as irreversibility, damping or untimely spiking). We experimentally demonstrate this robustness by encoding - digitally and analogically - thermal messages into chemical waveforms. This chemical neuron could pave the way for implementing in DNA the third generation of neural network models (spiking networks), and opens the door for associative learning. One-Sentence SummaryA DNA-based chemical network mathematically mimics the sensing of cold by a biological neuron.

biochemistry↗

bioRxiv2019

Isothermal Digital Detection Of MicroRNA Using Background-Free Molecular Circuit

MicroRNA, a class of transcripts involved in the regulation of gene expression, are emerging as promising disease-specific biomarkers accessible from tissues or bodily fluids. However, their accurate quantification from biological samples remains challenging. We report a sensitive and quantitative microRNA method using an isothermal amplification chemistry adapted to a droplet digital readout. Building on molecular programming concepts, we design DNA circuit that converts, threshold, amplifies and report the presence of a specific microRNA, down to the femtomolar concentration. Using a leak-absorption mechanism, we were able to suppress non-specific amplification, classically encountered in other exponential amplification reactions. As a result, we demonstrate that this isothermal amplification scheme is adapted to digital counting of microRNA: by partitioning the reaction mixture into water-in-oil droplets, resulting in single microRNA encapsulation and amplification, the method provides absolute target quantification. The modularity of our approach enables to repurpose the assay for various microRNA sequences.

molecular biology↗