Biology subjects

Gagnon, J.

Publications and source records attributed to Gagnon, J..

11 recordsLinked to original sources

bioRxiv2026

Optimization of DNA Transformation in Mesoplasma florum and Identification of a Candidate Recipient Strain for Genome Transplantation

Genome transplantation is a key technology for synthetic genomics, enabling entire genomes to be transferred into recipient cells. Despite its importance, genome transplantation remains confined to a small number of wall-less Mollicute species and is often characterized by low efficiencies, limiting the development and testing of synthetic genomes. Because genome transplantation relies on the same polyethylene glycol mediated DNA delivery process used for plasmid transformation, improving DNA uptake is an important step toward more efficient transplantation systems. Here, we systematically optimized polyethylene glycol-mediated transformation in Mesoplasma florum, a fast-growing, non-pathogenic Mollicute with a reduced genome that represents an attractive chassis for synthetic genomics. We evaluated 20 parameters spanning cell physiology, DNA preparation, membrane conditioning, and recovery conditions. DNA topology emerged as the strongest determinant of transformation efficiency, with highly compacted DNA preparations producing up to three orders of magnitude more transformants than conventional plasmid preparations. Growth phase and polyethylene glycol concentration also strongly influenced transformation outcomes. To identify potential recipients for future genome transplantation experiments, we further screened ten strains belonging to the Mesoplasma lineage. Transformation efficiencies varied widely among strains, and Mesoplasma entomophilum W17 emerged as a particularly promising candidate. Moreover, W17 supported replication of plasmids carrying the M. florum oriC, suggesting compatibility between the replication systems of the two species. Together, these results establish an improved transformation workflow for M. florum, identify DNA topology as a major determinant of DNA uptake, and reveal a new candidate recipient for future genome transplantation studies. These advances provide practical tools and biological insights for synthetic genome engineering in Mollicutes.

synthetic biology↗

bioRxiv2026

Reducing growth-medium complexity reveals nutrient-responsive programs in a near-minimal bacterium

Mesoplasma florum is a fast-growing, near-minimal bacterium and an emerging model for systems and synthetic biology. However, its dependence on complex serum-containing media limits experimental control and complicates the interpretation of cellular phenotypes. Here, we developed CMRL-AT, a serum-free, quasi-defined medium that supports rapid growth comparable to the commonly used ATCC 1161 medium. Despite supporting similar biomass, CMRL-AT profoundly reshaped the M. florum transcriptome, with approximately one-third of the annotated protein-encoding genes being differentially expressed relative to ATCC 1161. These changes revealed distinct physiological programs associated with rapid growth in complex medium and higher nutrient acquisition in CMRL-AT, illustrating how medium composition alters the functional priorities of a near-minimal cell. Transcriptome profiling across six energy sources further uncovered distinct sugar-responsive expression programs. Combining these responses with transcription-unit organization, protein-domain predictions, and metabolic context resolved fructose- and sucrose-responsive modules, and allowed the assignment of previously ambiguous phosphotransferase system components to specific sugar-utilization pathways. CMRL-AT provides an experimental framework to help resolving gene functions, refining metabolic models, and designing reduced genomes adapted to defined environments.

systems biology↗

bioRxiv2026

Leveraging quadplexed digital PCR to characterize gene therapy vectors

Currently there is a lack of high-throughput, low material-input methods to screen early-stage product quality of viral and non-viral gene therapy products. Here we propose using multiplex droplet digital PCR (dPCR) to screen and characterize vector sequences. We describe the adaptation of a Poisson-multinomial model to quantitate integrity of any combination of 4 targets in multiplexed ddPCR. We show the success and limitations of model employment and provide some suggested best practices.

molecular biology↗

bioRxiv2025

SpaceSequest: A unified pipeline for spatial transcriptomics data analysis

BackgroundSpatial transcriptomics has emerged as one of the most powerful tools for gaining biological insights, enabling researchers to uncover intricate relationships between gene expression patterns and tissue architecture. Recent advances in the field have resulted in a variety of new platforms, including Visium, Visium HD, and Xenium from 10x Genomics, as well as GeoMx and CosMx from NanoString Technologies, which has now been acquired by the Bruker Corporation. However, the existence of diverse spatial transcriptomics platforms and various data formats poses challenges in standardizing data analysis. Thus, there remains a critical gap in the availability of a comprehensive pipeline capable of conducting end-to-end analysis that is necessary to extract biological insights from multiple spatial transcriptomics platforms. ResultsHere, we present SpaceSequest, a tailored pipeline that utilizes cutting-edge computational methodologies to conduct a thorough analysis, enabling the extraction of crucial biological insights from five major spatial transcriptomics technologies. SpaceSequest performs (1) standardized quality control and general data processing, (2) key analyses customized for each spatial platform, (3) automated cell type annotation and deconvolution, and (4) high-quality figure and analysis result generation. In addition, SpaceSequest allows for smooth integration with cellxgene VIP and Quickomics for user-friendly data access and interactive visualization. ConclusionsSpaceSequest is a unified and comprehensive pipeline designed for the analysis, visualization, and publication of spatial transcriptomics data from various platforms. The source code is available at https://github.com/interactivereport/SpaceSequest. To facilitate seamless installation and usage, we have also created a detailed Bookdown tutorial that can be accessed through https://interactivereport.github.io/SpaceSequest/tutorial/docs/index.html.

bioinformatics↗

bioRxiv2025

Spatial transcriptomics reveals heterogeneous cell-cell interactions among brain regions in a cuprizone model consistent with multiple sclerosis lesions

The cuprizone (CPZ) model is widely used for modeling demyelination in multiple sclerosis (MS) and for testing potential remyelination therapies. We integrated single-cell and spatial transcriptomics (ST) to fine map the spatial cellular and molecular responses during de and remyelination. ST revealed global demyelination and neuroinflammation in the brain beyond the corpus callosum, with region-specific differences. We identified oligodendroglia and microglia as two major cell types with significant transcriptomic changes in the model. Ligand receptor pairing analyses predicted growth factor and phagocytic pathway enrichment during demyelination, which is consistent with changes in MS lesions. During remyelination, while mature oligodendrocytes nearly reversed their phenotype back to the control state, microglia remained associated with the demyelination phenotype. Finally, astrocytes in the CPZ model had the greatest preservation of disease-associated modules to MS lesions, while the MOL, OPC, and microglia showed moderate to low preservation, which overall suggested that the CPZ model had moderate translatability to chronically active MS lesions.

neuroscience↗

bioRxiv2025

ScaleSC: A superfast and scalable single cell RNA-seq data analysis pipeline powered by GPU.

The rise of large-scale single-cell RNA-seq data has introduced challenges in data processing due to its slow speed. Leveraging advancements in GPU computing ecosystems, such as CuPy, and building on Scanpy and rapids-singlecell package, we developed ScaleSC, a GPU-accelerated solution for single-cell data processing. ScaleSC delivers over a 20x speedup through GPU computing and significantly improves scalability, handling datasets of 10-40 million cells with over 1000 batches by overcoming the memory bottleneck on a single A100 card- far surpassing rapids-singlecells capacity of processing only 1 million cells without multi-GPU support. We also resolved discrepancies between GPU and CPU algorithm implementations to ensure consistency. In addition to core optimizations, we developed new advanced tools for marker gene identification, cluster merging, and more, with GPU-optimized implementations seamlessly integrated. Designed for ease of use, the ScaleSC package is compatible with Scanpy workflows, requiring minimal adaptation from users. The ScaleSC package (https://github.com/interactivereport/ScaleSC) promises significant benefits for the single-cell RNA-seq computational community.

bioinformatics↗

bioRxiv2024

O-GlcNAcylation of FOXK1 orchestrates the E2F pathway and promotes oncogenesis

Gene transcription is a highly regulated process, and deregulation of transcription factors activity underlies numerous pathologies including cancer. Albeit near four decades of studies have established that the E2F pathway is a core transcriptional network that govern cell division in multi-cellular organisms1,2, the molecular mechanisms that underlie the functions of E2F transcription factors remain incompletely understood. FOXK1 and FOXK2 transcription factors have recently emerged as important regulators of cell metabolism, autophagy and cell differentiation3-6. While both FOXK1 and FOXK2 interact with the histone H2AK119ub deubiquitinase BAP1 and possess many overlapping functions in normal biology, their specific functions as well as deregulation of their transcriptional activity in cancer is less clear and sometimes contradictory7-13. Here, we show that elevated expression of FOXK1, but not FOXK2, in primary normal cells promotes transcription of E2F target genes associated with increased proliferation and delayed entry into cellular senescence. FOXK1 expressing cells are highly prone to cellular transformation revealing important oncogenic properties of FOXK1 in tumor initiation. High expression of FOXK1 in patient tumors is also highly correlated with E2F gene expression. Mechanistically, we demonstrate that FOXK1, but not FOXK2, is specifically modified by O-GlcNAcylation. FOXK1 O-GlcNAcylation is modulated during the cell cycle with the highest levels occurring during the time of E2F pathway activation at G1/S. Moreover, loss of FOXK1 O-GlcNAcylation impairs FOXK1 ability to promote cell proliferation, cellular transformation and tumor growth. Mechanistically, expression of FOXK1 O-GlcNAcylation-defective mutants results in reduced recruitment of BAP1 to gene regulatory regions. This event is associated with a concomitant increase in the levels of histone H2AK119ub and a decrease in the levels of H3K4me1, resulting in a transcriptional repressive chromatin environment. Our results define an essential role of O-GlcNAcylation in modulating the functions of FOXK1 in controlling the cell cycle of normal and cancer cells through orchestration of the E2F pathway.

molecular biology↗

bioRxiv2023

A novel method for quantitation of AAV genome integrity and residual DNAs using duplex digital PCR

Recombinant adeno-associated virus (rAAV) vectors have become a reliable strategy for delivering gene therapies. As rAAV capsid content is known to be heterogeneous, assays for rAAV characterization are critical for assessing the efficacy and safety of drug products. Multiplex droplet digital PCR (ddPCR) has emerged as a popular molecular approach for characterizing capsid content due to its high level of throughput, accuracy, and replicability. Despite growing popularity, tools to accurately analyze multiplexed data are scarce. Here, we introduce a novel model to estimate genome integrity from duplex ddPCR assays. This work demonstrates that use of a Poisson-multinomial mixture distribution significantly improves the accuracy and quantifiable range of duplex ddPCR assays over currently available models.

molecular biology↗

bioRxiv2023

TDP-43-stratified single-cell proteomic profiling of postmortem human spinal motor neurons reveals protein dynamics in amyotrophic lateral sclerosis

Unbiased proteomics has been employed to interrogate central nervous system (CNS) tissues (brain, spinal cord) and fluid matrices (CSF, plasma) from amyotrophic lateral sclerosis (ALS) patients; yet, a limitation of conventional bulk tissue studies is that motor neuron (MN) proteome signals may be confounded by admixed non-MN proteins. Recent advances in trace sample proteomics have enabled quantitative protein abundance datasets from single human MNs (Cong et al., 2020b). In this study, we leveraged laser capture microdissection (LCM) and nanoPOTS (Zhu et al., 2018c) single-cell mass spectrometry (MS)-based proteomics to query changes in protein expression in single MNs from postmortem ALS and control donor spinal cord tissues, leading to the identification of 2515 proteins across MNs samples (>900 per single MN) and quantitative comparison of 1870 proteins between disease groups. Furthermore, we studied the impact of enriching/stratifying MN proteome samples based on the presence and extent of immunoreactive, cytoplasmic TDP-43 inclusions, allowing identification of 3368 proteins across MNs samples and profiling of 2238 proteins across TDP-43 strata. We found extensive overlap in differential protein abundance profiles between MNs with or without obvious TDP-43 cytoplasmic inclusions that together point to early and sustained dysregulation of oxidative phosphorylation, mRNA splicing and translation, and retromer-mediated vesicular transport in ALS. Our data are the first unbiased quantification of single MN protein abundance changes associated with TDP-43 proteinopathy and begin to demonstrate the utility of pathology-stratified trace sample proteomics for understanding single-cell protein abundance changes in human neurologic diseases.

pathology↗

bioRxiv2018

Existing host range mutations constrain further emergence of RNA viruses

RNA viruses are capable of rapid host shifting, typically due to a point mutation that confers expanded host range. As additional point mutations are necessary for further expansions, epistasis among host range mutations can potentially affect the mutational neighborhood and frequency of niche expansion. We mapped the mutational neighborhood of host range expansion using three genotypes of the dsRNA bacteriophage phi6 (wildtype and two isogenic host range mutants) on the novel host Pseudomonas syringae pv. atrofaciens (PA). Sanger sequencing of fifty PA mutant clones for each genotype and population Illumina sequencing both revealed the same high frequency mutations allowing infection of PA. Wildtype phi6 had at least nine different ways of mutating to enter the novel host, eight of which are in p3 (host attachment protein gene), and 13/50 clones had unchanged p3 genes. However, the two isogenic mutants had dramatically restricted neighborhoods: only one or two mutations, all in p3. Deep sequencing revealed that wildtype clones without mutations in p3 likely had changes in p12 (morphogenic protein), a region that was not polymorphic for the two isogenic host range mutants. Sanger sequencing confirmed that 10/13 of the wildtype phi6 clones had nonsynonymous mutations in p12 and two others had point mutations in p9 and p5 - none of these genes had previously been associated with host range expansion in phi6. We demonstrate, for the first time, epistatic constraint in an RNA virus due to host range mutations themselves, which has implications for models of serial host range expansion.\n\nImportanceRNA viruses mutate rapidly and frequently expand their host ranges to infect novel hosts, leading to serial host shifts. Using an RNA bacteriophage model system (Pseudomonas phage phi6), we studied the impact of pre-existing host range mutations on another host range expansion. Results from both clonal Sanger and Illumina sequencing show extant host range mutations dramatically narrow the neighborhood of potential host range mutations compared to wildtype phi6. This research suggests that serial host shifting viruses may follow a small number of molecular paths to enter additional novel hosts. We also identified new genes involved in phi6 host range expansion, expanding our knowledge of this important model system in experimental evolution.

microbiology↗

bioRxiv2017

Deep transcriptome annotation suggests that small and large proteins encoded in the same genes often cooperate

Recent studies in eukaryotes have demonstrated the translation of alternative open reading frames (altORFs) in addition to annotated protein coding sequences (CDSs). We show that a large number of small proteins could in fact be coded by altORFs. The putative alternative proteins translated from altORFs have orthologs in many species and evolutionary patterns indicate that altORFs are particularly constrained in CDSs that evolve slowly. Thousands of predicted alternative proteins are detected in proteomic datasets by reanalysis with a database containing predicted alternative proteins. Protein domains and co-conservation analyses suggest potential functional cooperation or shared function between small and large proteins encoded in the same genes. This is illustrated with specific examples, including altMID51, a 70 amino acid mitochondrial fission-promoting protein encoded in MiD51/Mief1/SMCR7L, a gene encoding an annotated protein promoting mitochondrial fission. Our results suggest that many coding genes code for more than one protein that are often functionally related.

biochemistry↗