Biology subjects

Rondelez, Y.

Publications and source records attributed to Rondelez, Y..

7 recordsLinked to original sources

bioRxiv2025

Functional selection in a population of synthetic cells with a minimal metabolism

Various synthetic microcompartment systems have been developed to mimic key features of living cells. Here, we focus on artificial cells that capture their capacity to serve as vessels for Darwinian evolution. We assemble micro-compartmentalized In Vitro Transcription-Translation-Replication systems containing a minimal genome, a basic metabolic pathway, a reconstituted protein expression machinery, and a simple DNA replication module, wired in a positive feedback loop. The minimal genome encodes the enzyme deoxyribonucleoside kinase (DNK) whose expression, and then metabolic activity, is required for the genomes replication. We show that these compartments act as minimal Darwinian elements by filtering out non-functional genotypes. We track individual replicators from a library of 42 genetic variants to reveal the systems dynamics at both the population and the single replicator levels. At the population level, we extract the fitness function, which links a genomes metabolic efficiency to its selective success, considering co-encapsulation and hitch-hiking effects. At the individual replicator level, we observe a bimodal distribution of replication yields and propose a mixed model with an inter-droplet heterogeneity with presence or absence of a metabolic feedback loop on the replicator. In addition, we leverage this autonomous self-selection loop to generate a high-resolution mutational map of the DNK enzyme.

synthetic biology↗

bioRxiv2024

Darwinian Evolution of Self-Replicating DNA in a Synthetic Protocell

Replication, heredity, and evolution are characteristic of Life. We and others have postulated that the reconstruction of a synthetic living system in the laboratory will be contingent on the development of a genetic self-replicator capable of undergoing Darwinian evolution. Although DNA-based life dominates, the in vitro reconstitution of an evolving DNA self-replicator has remained challenging. We hereby emulate in liposome compartments the principles according to which life propagates information and evolves. Using two different experimental configurations supporting intermittent or semi-continuous evolution (i.e., with or without DNA extraction, PCR, and re-encapsulation), we demonstrate sustainable replication of a linear DNA template - encoding the DNA polymerase and terminal protein from the Phi29 bacteriophage - expressed in the protein synthesis using recombinant elements (PURE) system. The self-replicator can survive across multiple rounds of replication-coupled transcription-translation reactions in liposomes and, within only ten evolution rounds, accumulates mutations conferring a selection advantage. Combined data from next-generation sequencing with reverse engineering of some of the enriched mutations reveal nontrivial and context-dependent effects of the introduced mutations. The present results are foundational to build up genetic complexity in an evolving synthetic cell, as well as to study evolutionary processes in a minimal cell-free system.

synthetic biology↗

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↗

bioRxiv2021

Directed Evolution of Enzymes based on in vitro Programmable Self-Replication

High-throughput directed evolution, implemented in well-controlled in vitro conditions, provides a powerful route for enzyme engineering. Most existing technologies are based on activity screening and require the sequential observation and sorting of each individual variant. By contrast, approaches based on autonomous feedback loops, linking phenotype to genotype replication, enable autonomous selection without screening. However, these approaches are only possible in vivo, or applicable to very specific activities, such as polymerases or ligases. Here, we leverage synthetic molecular networks to create a programmable in vitro feedback loop linking a target enzymatic activity to gene amplification. After encapsulation and lysis of up to 107 transformed variants, the genes present in each droplet are amplified according to the activity of the encoded enzyme, resulting in the autonomous enrichment of interesting sequences. Applied to a nicking enzyme with thermal or kinetic selection pressures, this method reveals detailed mutational landscapes and provides improved variants.

bioengineering↗

bioRxiv2020

Accurate detection of single nucleotide polymorphisms using nanopore sequencing

Nanopore sequencing is a powerful single molecule DNA sequencing technology which offers high throughput and long sequence reads. Nevertheless, its high native error rate limits the direct detection of point mutations in individual reads of amplicon libraries, as these mutations are difficult to distinguish from the sequencing noise. In this work, we developed SINGLe (SNPs In Nanopore reads of Gene Libraries), a computational method to reduce the noise in nanopore reads of amplicons containing point variations. Our approach uses the fact that all reads are very similar to a wild type sequence, for which we experimentally characterize the position-specific systematic sequencing error pattern. We then use this information to reweight the confidence given to nucleotides that do not match the wild type in individual variant reads. We tested this method in a set of variants of KlenTaq, where the true mutation rate was well below the sequencing noise. SINGLe improves between 4 and 9 fold the signal to noise ratio, in comparison to the data returned by the basecaller guppy. Downstream, this approach improves variants clustering and consensus calling. SINGLe is simple to implement and requires only a few thousands reads of the wild type sequence of interest, which can be easily obtained by multiplexing in a single minION run. It does not require any modification in the experimental protocol, it does not imply a large loss of sequencing throughput, and it can be incorporated downstream of standard basecalling.

bioinformatics↗

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↗