Biology subjects

de Lannoy, C. V.

Publications and source records attributed to de Lannoy, C. V..

4 recordsLinked to original sources

bioRxiv2023

iMAX FRET (Information Maximized FRET) for multipoint single-molecule structural analysis

Understanding the structure of biomolecules is vital for deciphering their characteristics and roles in biological systems. While current structural analysis techniques like nuclear magnetic resonance and X-ray crystallography excel in many aspects, they fall short in capturing comprehensive single-molecule information. To address this limitation and to better capture the heterogeneity and dynamic range of biomolecular reactions, there is a need for single-molecule structural analysis tools. To achieve this, we introduce iMAX FRET, a one-pot FRET-based single-molecule method integrated with geometrical 3D reconstruction, offering comprehensive ab initio structural analysis. Through the stochastic exchange of fluorescent weak binders, iMAX FRET allows simultaneous assessment of multiple spatial coordinates on a biomolecule within a few minutes of time to generate distinct FRET fingerprints for 3D structural profiling. We demonstrate a mathematical approach for de novo structural prediction using iMAX data, opening avenues for native biomolecule analysis. Furthermore, this method facilitates the investigation of conformational changes in individual molecules, illuminating single-molecule structural dynamics. Our technique has the potential to emerge as a powerful approach to advance our understanding of biomolecular structures.

biophysics↗

bioRxiv2022

baseLess: Lightweight detection of sequences in raw MinION data

AO_SCPLOWBSTRACTC_SCPLOWWith its candybar form factor and low initial investment cost, the MinION brought affordable portable nucleic acid analysis within reach. However, translating the electrical signal it outputs into a sequence of bases still requires high-end computer hardware, which remains a caveat when aiming for deployment of many devices at once or usage in remote areas. For applications focusing on detection of a target sequence, such as infectious disease or GMO monitoring, the computational cost of analysis may be reduced by directly detecting the target sequence in the electrical signal instead. Here we present baseLess, a computational tool that enables such target-detection-only analysis. BaseLess makes use of an array of small neural networks, each of which efficiently detects a fixed-size subsequence of the target sequence directly from the electrical signal. We show that baseLess can accurately determine the identity of reads between three closely related fish species and can classify sequences in mixtures of twenty bacterial species, on an inexpensive single-board computer. AvailabilitybaseLess and all code used in data preparation and validation is available on Github at https://github.com/cvdelannoy/baseLess, under an MIT license. Used validation data and scripts can be found at https://doi.org/10.4121/20261392, under an MIT license.

bioinformatics↗

bioRxiv2020

FRETboard: semi-supervised classification of FRET traces

AO_SCPLOWBSTRACTC_SCPLOWForster resonance energy transfer (FRET) is a useful phenomenon in biomolecular investigations, as it can be leveraged for nano-scale measurements. The optical signals produced by such experiments can be analyzed by fitting a statistical model. Several software tools exist to fit such models in an unsupervised manner, but their operating system-dependent installation requirements and lack of flexibility impede wide-spread adoption. Here we propose to fit such models more efficiently and intuitively by adopting a semi-supervised approach, in which the user interactively guides the model to fit a given dataset, and introduce FRETboard, a web tool that allows users to provide such guidance. We show that our approach is able to closely reproduce ground truth FRET statistics in a wide range of simulated single-molecule scenarios, and correctly estimate parameters for up to eleven states. On in vitro data we retrieve parameters identical to those obtained by laborious manual classification in a fraction of the required time. Moreover, we designed FRETboard to be easily extendable to other models, allowing it to adapt to future developments in FRET measurement and analysis. Availabilitysource code is available at https://github.com/cvdelannoy/FRETboard. The FRETboard classification tool is also available as a browser application at https://www.bioinformatics.nl/FRETboard.

biophysics↗

bioRxiv2017

A Sequencer Coming Of Age: De Novo Genome Assembly Using MinION Reads

Nanopore technology provides a novel approach to DNA sequencing that yields long, label-free reads of constant quality. The first commercial implementation of this approach, the MinION, has shown promise in various sequencing applications. The presented literature review gives an up-to-date overview of the MinIONs utility as a de novo sequencing device. It is argued that the MinION may allow for portable and affordable de novo sequencing of even complex genomes in the near future, despite the currently error-prone nature of its reads. Through continuous updates to the MinION hardware and the development of new assembly pipelines, both sequencing accuracy and assembly quality have already risen rapidly. However, this fast pace of development has also lead to a lack of oversight in the expanding landscape of analysis tools, as performance evaluations are outdated quickly. Now that the MinION is approaching a state of maturity, a thorough comparative benchmarking effort of de novo assembly pipelines may be at place.

genetics↗