Biology subjects

Simon, N.

Publications and source records attributed to Simon, N..

At least 19 recordsLinked to original sources

bioRxiv2026

A sensitive and specific microchimerism detection method using custom designed genotyping and companion qPCR assays

Since first reports of the presence of a small number of cells from one individual persisting in another, researchers have developed a number of methods to detect microchimerism. Molecular based detection platforms range from gel electrophoresis to quantitative PCR to Next-Gen Sequencing. Central to all approaches is the need for informative polymorphic loci to effectively distinguish microchimeric cells from the host. However, we observed in our studies of maternal microchimerism that currently published approaches can limit the number of samples available for assessment due to the inability to identify an informative marker of the donor in the recipient. This was most striking in our studies of populations of African descent in which the use of HLA-based markers, a common approach, prevented the testing of 30-50% of participants. Other potential options were cost prohibitive or lacked sufficient sensitivity. To address this challenge, we developed a novel, simple, and low-cost approach that leverages global population frequency databases for polymorphism selection, reduces cost by amplifying multiple targets in one multiplex assay to complete genotyping, and has high sensitivity and specificity using rigorously designed qPCR assays to quantify microchimerism. Herein, we outline our design process, detailed assay protocol, and assessment of maternal microchimerism using this approach in two different populations of infants from the United States and South Africa.

molecular biology↗

bioRxiv2026

Constructing microbiome co-occurrence networks with confidence: A conditional, nonparametric, inference-based approach

Constructing microbial association networks is a common strategy for exploring relationships among taxa in microbiome studies. Although marginal correlation methods are easy to implement and allow formal inference, they can produce spurious edges driven by indirect associations through other taxa. Conditional graphical-modeling methods aim to recover direct associations, but many rely on Gaussian or linear assumptions and often provide limited uncertainty quantification. We propose a conditional, nonparametric approach based on the scaled expected conditional covariance (SEcov). SEcov measures population-level conditional association by residualizing each taxon with respect to the remaining taxa and scaling the resulting expected conditional covariance. The resulting estimator can incorporate flexible machine-learning methods for conditional-mean estimation and admits asymptotic normal inference, enabling p-values and confidence intervals for taxon-pair associations. We demonstrate through simulation studies that our proposed approach improves network recovery relative to other methods, and we illustrate the new method via construction of a co-occurrence network for the vaginal microbiome during pregnancy. IMPORTANCEHigh-throughput sequencing has made it possible to characterize microbial communities at large scale, and network analysis is widely used to summarize relationships among taxa. However, networks based on marginal correlations may include indirect associations, whereas many conditional graphical models rely on assumptions that may be difficult to justify for sparse, zero-inflated, compositional microbiome data. SEcov offers a practical alternative by estimating conditional associations nonparametrically and attaching inferential uncertainty to individual edges. This allows investigators to construct microbiome networks using statistically interpretable evidence for taxon-pair associations, rather than relying solely on arbitrary correlation cutoffs or regularization tuning parameters.

bioinformatics↗

bioRxiv2026

Seasonal patterns in Synechococcus pigment diversity at two temperate sites with contrasting oceanic regimes

Competition for light has driven extensive pigment diversification among phytoplankton species, yet how this diversity shapes their spatiotemporal distribution in the field has been little studied so far. The cyanobacterium Synechococcus is an ideal model for addressing this issue, since this group has colonized most light spectral niches in marine environments. Here, we used an approach based on marker read recruitment from metagenomes to analyze the seasonal succession of Synechococcus pigment types (PTs) at two time-series stations off French coasts exhibiting contrasting oceanic regimes. Marked seasonality was observed at both sites. The shallow, permanently mixed English Channel site SOMLIT-Astan was characterized by an alternation between green-light specialists (PT 3a) peaking in spring, and chromatic acclimaters type A (PT 3dA) accounting for most of the Synechococcus community in winter. In contrast, the pigment diversity was much higher at the deep Mediterranean station BOUSSOLE. In the upper layer, the two main PTs were the blue light specialists (PT 3c), which dominated the community in summer and fall, and PT 3dA cells, which were more abundant in spring. The third most abundant PT was chromatic acclimaters type B (PT 3dB), which accounted for up to 15% of the surface community in late fall. Strikingly, PT 3dA was dominant at depth during most of the year. Multivariate analyses between PT abundances, clade abundances and environmental factors, notably water color indexes, suggested new associations between PTs to specific clades and ecological niches. This study provides novel insights for refining distribution models of Synechococcus PTs and phytoplankton groups in general.

microbiology↗

bioRxiv2025

Neutrophil-neuronal crosstalk drives arthritis-induced pain

Pain in rheumatoid arthritis (RA) often persists despite effective control of inflammation, suggesting distinct mechanisms driving nociception. In both patients and animal models, pain severity does not strongly correlate with the degree of inflammation1,2. Sensory neurons, with cell bodies located in the dorsal root ganglia (DRG), innervate peripheral tissues, including joints, and transmit pain signals to the central nervous system. Crosstalk between sensory neurons and immune cells occurs at all of these sites. While sensory neurons can be directly activated by immune mediators, it remains unclear whether pain-like behaviour in antibody-induced arthritis models arises independently of immune cell activity, or which immune cell populations and mediators are required to activate pronociceptive mechanisms. Through temporal profiling of the CAIA joint-DRG transcriptomic axis, we identified SEMA4D and OSM signalling as candidate molecular mediators of neutrophil-neuron communication and neuronal sprouting. The joint-DRG atlas also revealed persistent changes in the fibroblast-immune cellular composition of the joint, along with molecular changes in DRG neurons. We showed that mechanical and cold hypersensitivity, as well as sprouting of CGRP+ nociceptive fibers in synovial tissue of mice with collagen antibody-induced arthritis (CAIA), require neutrophils but not macrophages. Analysis of publicly available datasets showed that neutrophils from the synovium of RA patients express high levels of SEMA4D and OSM, and corresponding expression of their receptors, PLEXINB1 and OSMR, in human DRG neurons, underscoring the translational relevance of this axis. Both murine and human-derived DRG neurons sprout in response to OSM. Our findings demonstrate that neutrophils produce molecules that act as cues for nociceptor sensitization and structural remodelling. Targeting these molecules could improve the efficacy of RA treatments by reducing pain while simultaneously preventing disease progression.

immunology↗

bioRxiv2025

A novel method to sort and enrich sensory neurons

Peripheral sensory neurons, residing in the dorsal root ganglia (DRG), relay sensory information from the periphery to the central nervous system. Although single-cell transcriptomic studies have identified over 20 distinct sensory neuron subtypes, functional analysis and assessment of subtype-specific pathological changes remain difficult. Effective isolation and enrichment of sensory neurons are challenging yet essential for functional studies. Therefore, we used single-cell transcriptomic data from DRG to identify a panel of neuronal surface markers, including Nrxn2 and Pirt. Using these markers, we developed a fluorescence-activated cell sorting (FACS) panel for neuronal enrichment and analysis that does not rely on transgenic mouse strains and can be broadly applied. The panel was validated by microscopy and single-cell RNA (scRNA) sequencing, which also revealed broad representation of neuronal subtypes. Expression of these markers in human DRG underscores the translational value of this isolation method for sensory and pain studies. Overall, this study provides a valuable tool for isolating DRG neurons, advancing research on sensory neuron function and pain biology, and facilitating neuroimmune studies.

neuroscience↗

bioRxiv2025

OligoN-design: A simple and versatile tool to design specific probes and primers from large heterogeneous datasets

High-throughput environmental DNA sequencing has ushered ecological and evolutionary studies into the big data era. With thousands to millions of DNA sequences, designing taxon-specific oligonucleotides is a current bottleneck of molecular studies that rely on primers for Polymerase Chain Reactions (PCRs) or probes for Fluorescence in situ Hybridization (FISH). No software currently exists to design specific oligonucleotides starting from a custom set of sequences. Existing tools rely on specific databases, alignments or phylogenetic trees, or cannot accommodate increasingly large molecular environmental datasets. Here we present oligoN-design, a versatile tool to design oligonucleotides specific to a set of target sequences while minimizing predicted binding to non-target sequences. OligoN-design is simple, reproducible, and adaptable to high-throughput sequencing data analyses. It requires only two fasta files as input, one containing target taxa and the other containing non-target taxa. Using standard bioinformatic formats, it integrates easily with other tools such as BLAST, VSEARCH or MAFFT. OligoN-design allows a range of strategies that we present in detail, from an unsupervised end-to-end usage all the way to a detailed and thorough expert usage. Starting with large, comprehensive ribosomal databases that are widely used by the community (i.e., PR2, SILVA) and the unsupervised function, we were able to replicate known taxa-specific oligonucleotides in under 30 minutes and up to 6 Gb of RAM on a personal laptop. OligoN-design v1, available at github.com/MiguelMSandin/oligoN-design under GNU General Public License version 3.0, is easily installed via bioconda bioconda.github.io/recipes/oligon-design/README.html.

bioinformatics↗

bioRxiv2025

The JEDI marker as a universal measure of planetary biodiversity

Despite its critical importance in the formation and maintenance of ecosystems and homeostasis on Earth, biodiversity remains a complex and non-unified concept. Consequently, standards for measuring global biodiversity are lacking, hindering our capacity to document Earths biota and track its change. Here, we propose the Joint, cellular life-Encompassing DIversity (JEDI) marker as a simple, effective and quantitative measure to assess and monitor biodiversity. The JEDI marker is a ribosomal RNA gene fragment that can be amplified from all domains of life using a single pair of PCR primers. We demonstrate the applicability and effectiveness of this approach for assessing biodiversity across ecological and biological scales, from holobionts to diverse ecosystems. In addition, we provide an automated bioinformatic workflow to support the standardised and reproducible analysis of the JEDI marker in future studies. While this approach is not free from trade-offs, we argue that its advantages outweigh its limitations by providing a unique, operational and scalable solution that builds on established infrastructure to integrate the microbial majority into biodiversity assessments and provide fundamental insights into organismal dynamics and associations across domains of life. Thus, the JEDI marker approach addresses the urgent need for a universal and standardised framework to effectively measure and monitor biodiversity at planetary scales in an era of profound global change.

ecology↗

bioRxiv2024

Temperature-driven biogeography of marine giant viruses infecting the picoeukaryote Micromonas

Climate shapes the biogeography of microbial and viral communities in the ocean. Among abiotic factors, temperature is one of the main drivers of microbial community distribution. However, we lack knowledge on how temperature shapes the life history traits, population dynamics, and the biogeography of marine viruses. This study integrates mathematical modeling with in situ observations to investigate the temperature-driven biogeography of marine viruses. We focused on prasinoviruses, a group of giant viruses that infect the picoeukaryote Micromonas, a widespread phytoplankton with thermotypes adapted from poles to tropics. Analyzing the Tara Oceans and Polar Circle databases, we found that temperature is the primary determinant of Micromonas virus (MicV) distribution in the surface ocean. Phylogenetic reconstruction of MicV-s revealed that these viruses form several groups with cryophile or cryo-mesophile preferences. We applied a mechanistic model to describe temperature-driven population dynamics, allowing us to predict the global presence and absence of MicV-s. Lysis and infection emerged as reliable predictors of MicV distribution, indicating that temperature-driven cellular mechanisms significantly shape viral community structure and distribution. This study provides new insights into the role of temperature in regulating viral populations, emphasizing the importance of integrating modeling with observations to understand marine viral ecology.

ecology↗

bioRxiv2024

Thrifty wide-context models of B cell receptor somatic hypermutation

Somatic hypermutation (SHM) is the diversity-generating process in antibody affinity maturation. Probabilistic models of SHM are needed for analyzing rare mutations, for understanding the selective forces guiding affinity maturation, and for understanding the underlying biochemical process. High throughput data offers the potential to develop and fit models of SHM on relevant data sets. In this paper we model SHM using modern frameworks. We are motivated by recent work suggesting the importance of a wider context for SHM, however, assigning an independent rate to each k-mer leads to an exponential proliferation of parameters. Thus, using convolutions on 3-mer embeddings, we develop "thrifty" models of SHM of various sizes; these can have fewer free parameters than a 5-mer model and yet have a significantly wider context. These offer a slight performance improvement over a 5-mer model, and other modern model elaborations worsen performance. We also find that a per-site effect is not necessary to explain SHM patterns given nucleotide context. Also, the two current methods for fitting an SHM model -- on out-of-frame sequence data and on synonymous mutations -- produce significantly different results, and augmenting out-of-frame data with synonymous mutations does not aid out-of-sample performance.

immunology↗

bioRxiv2024

Mitochondrial DNA Mutations Linking Leigh Syndrome and Carotid Atherosclerosis: A Study of Shared Genetic Pathways

Mitochondrial DNA encodes the genetic information necessary for mitochondrial function. In humans, mitochondrial DNA spans 16,569 base pairs while representing a small fraction of the genetic material in humans. Due to their higher mutation rates compared to nuclear DNA, Mitochondrial DNA mutations are emerging as promising biomarkers for assessing disease predisposition and progression. This in-silico analyzes the correlation between Mitochondrial DNA mutations and two conditions: Leigh syndrome, a severe neurodegenerative disorder, and carotid atherosclerosis, a major cardiovascular disease. We focus on five single nucleotide variants (SNVs) - m.14459G>A, m.13513G>A, m.12315G>A, m.1555A>G, and m.15059G>A - to explore their roles in both diseases. Our findings suggest that mutations m.14459G>A, m.1555A>G, and m.15059G>A contribute to the pathogenesis of both conditions. In contrast, m.12315G>A is linked to MELAS syndrome and carotid atherosclerosis. Interestingly, the m.13513G>A mutation is associated with Leigh syndrome but negatively correlated with atherosclerosis, suggesting a potential protective effect. These SNVs could serve as targets for diagnostic and therapeutic approaches, enhancing our understanding of the genetic basis of these diseases.

bioinformatics↗

bioRxiv2024

Differential Expression Analysis for Spatially Correlated Data

Differential expression is a key application of imaging spatial transcriptomics, moving analysis beyond cell type localization to examining cell state responses to microenvironments. However, spatial data poses new challenges to differential expression: segmentation errors cause bias in fold-change estimates, and correlation among neighboring cells leads standard models to inflate statistical significance. We find that ignoring these issues can result in considerable false discoveries that greatly outnumber true findings. We present a suite of solutions to these fundamental challenges, and implement them in the R package smiDE. spatial transcriptomics, differential expression, segmentation error mitigation, spatial correlation, spatial random effects model

genomics↗

bioRxiv2023

Social Context and Drug Cues Modulate Inhibitory Control in Cocaine Addiction: involvement of the STN evidenced through Functional Magnetic Resonance Imaging

BackgroundAddictions often develop in a social context, although the influence of social factors did not receive much attention in the neuroscience of addiction. Recent animal studies suggest that peer presence can reduce cocaine intake, an influence potentially mediated, among others, by the subthalamic nucleus (STN). However, there is to date no such neurobiological study in humans. MethodsThis study investigated the impact of social context and drug cues on brain correlates of inhibitory control in individuals with and without cocaine use disorder (CUD) using functional Magnetic Resonance Imaging (fMRI). Seventeen CUD participants and 17 healthy controls (HC) performed a novel fMRI Stop-Signal task in the presence and absence of an observer while being exposed to cocaine-related and neutral pictures as cues. ResultsThe results showed that CUD participants, while slower at stopping with neutral cues, recovered control level stopping abilities with cocaine cues, while HC did not show any difference. Neuroimaging revealed the involvement of frontal cortical regions and of the subthalamic nucleus (STN) in inhibitory control, which was modulated by both social context and drug cues in CUD participants but not in HC. ConclusionsThese findings highlight the impact of social context and drug cues on inhibitory control in CUD and suggest potential targets for intervention such as the STN, also emphasizing the importance of considering the social context in addiction research and treatment.

neuroscience↗

bioRxiv2023

Dally is not essential for Dpp spreading or internalization but for Dpp stability by antagonizing Tkv-mediated Dpp internalization

Dpp/BMP acts as a morphogen to provide positional information in the Drosophila wing disc. Key cell-surface molecules to control Dpp morphogen gradient formation and signaling are heparan sulfate proteoglycans (HSPGs). In the wing disc, two HSPGs, the glypicans Division abnormally delayed (Dally) and Dally-like (Dlp) have been suggested to act redundantly to control these processes through direct interaction of their heparan sulfate (HS) chains with Dpp. Based on this assumption, a number of models on how glypicans control Dpp gradient formation and signaling have been proposed, including facilitating or hindering Dpp spreading, stabilizing Dpp on the cell surface, or recycling Dpp. However, how distinct HSPGs act remains largely unknown. Here we generate genome-engineering platforms for the two glypicans and find that only Dally is critical for Dpp gradient formation and signaling through interaction of its core protein with Dpp. We also find that this interaction is not sufficient and that the HS chains of Dally are essential for these functions largely without interacting with Dpp. We provide evidence that the HS chains of Dally are not essential for spreading or recycling of Dpp but for stabilizing Dpp on the cell surface by antagonizing receptor-mediated Dpp internalization. These results provide new insights into how distinct HSPGs control morphogen gradient formation and signaling during development.

developmental biology↗

bioRxiv2022

Statistical inference reveals the role of length, breathing, and nucleotide identity in V(D)J nucleotide trimming

To appropriately defend against a wide array of pathogens, humans somatically generate highly diverse repertoires of B cell and T cell receptors (BCRs and TCRs) through a random process called V(D)J recombination. Receptor diversity is achieved during this process through both the combinatorial assembly of V(D)J-genes and the junctional deletion and insertion of nucleotides. While the Artemis protein is often regarded as the main nuclease involved in V(D)J recombination, the exact mechanism of nucleotide trimming is not understood. Using a previously-published TCR{beta} repertoire sequencing data set, we have designed a flexible probabilistic model of nucleotide trimming that allows us to explore various mechanistically-interpretable sequence-level features. We show that local sequence context and the capacity for sequence-breathing, together, can most accurately predict the trimming probabilities of a given V-gene sequence. This model suggests that double-stranded DNA needs to be able to "breathe" for trimming to occur, and provides evidence of a sequence motif that appears to get preferentially trimmed, independent of breathing. Further, we find that the inferred mechanistic coefficients from this model provide accurate prediction for V- and J-gene sequences from other adaptive immune receptor loci. These results refine our understanding of how the Artemis nuclease may function to trim nucleotides during V(D)J recombination and provide another step towards understanding how V(D)J recombination generates diverse receptors and supports a powerful, unique immune response in healthy humans.

immunology↗

bioRxiv2022

eEF2 improves dense connective tissue repair and healing outcome by regulating cellular death, autophagy, apoptosis, proliferation and migration

Outcomes following human dense connective tissue (DCT) repair are often variable and suboptimal, resulting in compromised function and development of chronic painful degenerative diseases. Moreover, biomarkers and mechanisms that guide good clinical outcomes after DCT injuries are mostly unknown. Here, we characterize the proteomic landscape of DCT repair following human tendon rupture and its association with long-term patient-reported outcome. Moreover, the regulatory mechanisms of relevant biomarkers were assessed partly by gene silencing experiments. A Mass-Spectrometry based proteomic approach quantified a large number (769) of proteins, including 51 differentially expressed proteins among 20 good versus 20 poor outcome patients. A novel biomarker, elongation factor-2 (eEF2) was identified as being strongly prognostic of the 1-year clinical outcome. Further bioinformatic and experimental investigation revealed that eEF2 positively regulated autophagy, cell proliferation and migration, as well as reduced cell death and apoptosis, leading to improved DCT repair and outcomes. Findings of eEF2 as novel prognostic biomarker could pave the way for new targeted treatments to improve healing outcomes after DCT injuries.

cell biology↗

bioRxiv2022

Bayesian Pharmacometrics Analysis of Baclofen for Alcohol Use Disorder

Alcohol use disorder (AUD) also called alcohol dependence is a major public health problem, which affects almost 10% of the worlds population. Baclofen as a selective GABAB receptor agonist has emerged as a promising drug for the treatment of AUD, however, its optimal dosage varies according to individuals, and its exposure-response relationship has not been well established yet. In this study, we use a principled Bayesian workflow to estimate the parameters of a pharmacokinetic (PK) population model from Baclofen administration to patients with AUD. By monitoring various convergence diagnostics, the probabilistic methodology is first validated on synthetic longitudinal datasets and then, applied to infer the PK model parameters based on the clinical data that were retrospectively collected from outpatients treated with oral Baclofen. We show that state-of-the-art advances in automatic Bayesian inference using self-tuning Hamiltonian Monte Carlo (HMC) algorithms with a leveraged level of information in priors provide accurate predictions on Baclofen plasma concentration in individuals. This approach may pave the way to render non-parametric HMC sampling methods sufficiently easy and reliable to use in clinical schedules for personalized treatment of AUD.

pharmacology and toxicology↗

bioRxiv2022

Viral infection impacts the 3D subcellular structure of the abundant marine diatom Guinardia delicatula

Viruses are key players in marine ecosystems where they infect abundant marine microbes. RNA viruses are emerging as key members of the marine virosphere. They have recently been identified as a potential source of mortality in diatoms, a group of microalgae that accounts for roughly 40% of the primary production in the ocean. Despite their likely importance, their impacts on host populations and ecosystems remain difficult to assess. In this study, we introduce an innovative tool approach that combines automated 3D confocal microscopy with quantitative image analysis and physiological measurements to expand our understanding of viral infection. We followed different stages of infection of the bloom-forming diatom Guinardia delicatula by the RNA virus GdelRNAV-04 until the complete lysis of the host. From 20h after infection, we observed quantifiable changes in subcellular host morphology and biomass. Our microscopy monitoring also showed that viral infection of G. delicatula induced the formation of auxospores as a probable defense strategy against viruses. Our method enables the detection of discriminative morphological features on the subcellular scale and at high throughput for comparing populations, making it a promising approach for the detection quantification of viral infections in the field in the future.

microbiology↗

bioRxiv2022

Insight into diatoms diversity at two European coastal sites (LTER-MC in the Mediterranean Sea and SOMLIT-Astan in the Western English Channel) using a DNA metabarcoding approach

Diatoms are among the most successful marine eukaryotic phytoplankton groups. Their diversity has been investigated in the worlds oceans through expeditions and observations carried out from the equator to the poles. Traditionally, diatom species have been distinguished based on morphological characters of their frustules, but high-throughput sequencing offers new, high-resolution data that can be used to re-examine spatial and/or temporal patterns of diversity. Here we investigated diatoms genetic diversity using metabarcoding (18S V4 rRNA gene) obtained along the years 2011 to 2013 at two coastal time series stations (SOMLIT-Astan and LTER-MareChiara) installed respectively off Roscoff in the Western English Channel and in the Gulf of Naples in the Mediterranean Sea. Diatom species pools detected were different, which fitted with previous observations and with our expectations, since these stations are installed in two contrasted pelagic habitats (permanently-mixed versus stratified in summer). However, this analysis also shows a pool of common ASVs among which some are persistent and dominant in both sites. The observed synchronous variations in relative read abundances of shared ASVs assigned to Chaetoceros socialis, C. tenuissimus, Cyclotella, Mediolabrus comicus and Leptocylindrus aporus at the two geographically distant sites could indicate that internal controls of growth rate and sexual reproduction, rather that external environmental parameters are at work.

ecology↗