Biology subjects

Martin, A.

Publications and source records attributed to Martin, A..

At least 91 records · Page 5Linked to original sources

bioRxiv2024

Rapid, automatic typing of Clostridioides difficile Ribotypes Using MALDI-TOF MS

Clostridioides difficile is a major cause of hospital-acquired diarrhea, posing significant clinical challenges due to its high morbi-mortality rates and its involvement in nosocomial outbreaks. Detecting its toxigenic ribotypes rapidly and accurately is crucial for effective outbreak control. This study aimed to create a rapid diagnostic methodology based on MALDI-TOF MS and Machine Learning algorithms to differentiate toxigenic C. difficile RTs. MALDI-TOF spectra were acquired from 379 clinical isolates sourcing from 10 Spanish hospitals and analysed using Clover MSDAS, a specific software for MALDI-TOF spectra analysis, considered as the state-of-the-art tool for this purpose, and AutoCdiff, an ad hoc software developed in this study. Seven biomarker peaks were found to differentiate epidemic RT027 and RT181 strains from other RTs (2463, 3353, 4933, 4993, 6187, 6651 and 6710 m/z). Two peaks (2463 and 4993 m/z) were specifically found in RT027 isolates while combinations of the other 5 peaks allowed the differentiation of RT181 from other ribotypes. Automatic classification tools developed in Clover MSDAS and AutoCdiff using the specific peaks and the entire protein spectra, respectively, showed up to 100% balanced accuracy. Both methods allowed correct ribotype assignment for isolates sourcing from real-time outbreaks. The developed models, available from Clover MSDAS and the AutoCdiff website -https://bacteria.id-offer researchers a valuable tool for quick C. difficile ribotype determination based on MALDI-TOF spectra analysis. Although further validation of the models is still required, they represent rapid and cost-effective methods for standardized C. difficile ribotype assignment.

microbiology↗

bioRxiv2023

EGFR-dependent actomyosin patterning coordinates morphogenetic movements between tissues

The movements that give rise to the bodys structure are powered by cell shape changes and rearrangements that are coordinated at supracellular scales. How such cellular coordination arises and integrates different morphogenetic programs is unclear. Using quantitative imaging, we found a complex pattern of adherens junction (AJ) levels in the ectoderm prior to gastrulation onset in Drosophila. AJ intensity exhibited a double- sided gradient, with peaks at the dorsal midline and ventral neuroectoderm. We show that this dorsal-ventral AJ pattern is regulated by epidermal growth factor (EGF) signaling and that this signal is required for ectoderm cell movement during mesoderm invagination and axis extension. We identify AJ levels and junctional actomyosin as downstream effectors of EGFR signaling. Overall, our study demonstrates a mechanism of coordination between tissue folding and convergent extension that facilitates embryo-wide gastrulation movements.

cell biology↗

bioRxiv2023

A functional parcellation of the whole brain in individuals with autism spectrum disorder reveals atypical patterns of network organization

BACKGROUNDResearchers studying autism spectrum disorder (ASD) lack a comprehensive map of the functional network topography in the ASD brain. We used high-quality resting state functional MRI (rs-fMRI) connectivity data and a robust parcellation routine to provide a whole-brain map of functional networks in a group of seventy individuals with ASD and a group of seventy typically developing (TD) individuals. METHODSThe rs-fMRI data were collected using an imaging sequence optimized to achieve high temporal signal-to-noise ratio (tSNR) across the whole-brain. We identified functional networks using a parcellation routine that intrinsically incorporates stability and replicability of the networks by keeping only network distinctions that agree across halves of the data over multiple random iterations in each group. The groups were tightly matched on tSNR, in-scanner motion, age, and IQ. RESULTSWe compared the maps from each group and found that functional networks in the ASD group are atypical in three seemingly related ways: 1) whole-brain connectivity patterns are less stable across voxels within multiple functional networks, 2) the cerebellum, subcortex, and hippocampus show weaker differentiation of functional subnetworks, and 3) subcortical structures and the hippocampus are atypically integrated with the neocortex. CONCLUSIONSThese results were statistically robust and suggest that patterns of network connectivity between the neocortex and the cerebellum, subcortical structures, and hippocampus are atypical in ASD individuals.

neuroscience↗

bioRxiv2023

Substrate-interacting pore loops of two ATPase subunits determine the degradation efficiency of the 26S proteasome

The 26S proteasome is the major eukaryotic protease responsible for protein quality control, proteostasis, and the modulation of numerous vital processes through the degradation of regulatory proteins. Commitment to degradation occurs when conserved pore loops in the proteasomal heterohexameric ATPase motor engage the flexible initiation region of a polyubiquitinated protein substrate for subsequent mechanical unfolding and translocation into a proteolytic chamber. Here, we used in vitro biochemical and single-molecule FRET-based assays with mutant reconstituted 26S proteasomes from yeast to characterize how the pore-1 loops of individual ATPase subunits in the AAA+ motor contribute to the different steps of substrate degradation and affect the proteasome conformational dynamics. We found that the pore-1 loop of the Rpt6 ATPase subunit plays particularly important roles in substrate capture, engagement, and unfolding, while the pore-1 loop of the Rpt4 ATPase is critical for providing sufficient grip for substrate unraveling and maintaining a processing-competent state of the proteasome. Interestingly, these pore-1-loop contributions correlate with their positions in the spiral-staircase arrangements of ATPase subunits in the substrate-free and substrate-degrading proteasome, providing new insights into the mechanisms of substrate processing by the 26S proteasome and related hexameric ATPase motors.

biochemistry↗

bioRxiv2023

Digital telomere measurement by long-read sequencing distinguishes healthy aging from disease

Telomere length is an important biomarker of organismal aging and cellular replicative potential, but existing measurement methods are limited in resolution and accuracy. Here, we deploy digital telomere measurement by nanopore sequencing to understand how distributions of human telomere length change with age and disease. We measure telomere attrition and de novo elongation with unprecedented resolution in genetically defined populations of human cells, in blood cells from healthy donors and in blood cells from patients with genetic defects in telomere maintenance. We find that human aging is accompanied by a progressive loss of long telomeres and an accumulation of shorter telomeres. In patients with defects in telomere maintenance, the accumulation of short telomeres is more pronounced and correlates with phenotypic severity. We apply machine learning to train a binary classification model that distinguishes healthy individuals from those with telomere biology disorders. This sequencing and bioinformatic pipeline will advance our understanding of telomere maintenance mechanisms and the use of telomere length as a clinical biomarker of aging and disease.

genetics↗

bioRxiv2023

Chikungunya virus infection disrupts lymph node lymphatic endothelial cell composition and function via MARCO

Infection with chikungunya virus (CHIKV) causes disruption of draining lymph node (dLN) organization, including paracortical relocalization of B cells, loss of the B cell-T cell border, and lymphocyte depletion that is associated with infiltration of the LN with inflammatory myeloid cells. Here, we find that during the first 24 h of infection, CHIKV RNA accumulates in MARCO-expressing lymphatic endothelial cells (LECs) in both the floor and medullary LN sinuses. The accumulation of viral RNA in the LN was associated with a switch to an antiviral and inflammatory gene expression program across LN stromal cells, and this inflammatory response, including recruitment of myeloid cells to the LN, was accelerated by CHIKV-MARCO interactions. As CHIKV infection progressed, both floor and medullary LECs diminished in number, suggesting further functional impairment of the LN by infection. Consistent with this idea, we find that antigen acquisition by LECs, a key function of LN LECs during infection and immunization, was reduced during pathogenic CHIKV infection.

immunology↗

bioRxiv2023

Admix-kit: An Integrated Toolkit and Pipeline for Genetic Analyses of Admixed Populations

SummaryAdmixed populations, with their unique and diverse genetic backgrounds, are often underrepresented in genetic studies. This oversight not only limits our understanding but also exacerbates existing health disparities. One major barrier has been the lack of efficient tools tailored for the special challenges of genetic study of admixed populations. Here, we present admix-kit, an integrated toolkit and pipeline for genetic analyses of admixed populations. Admix-kit implements a suite of methods to facilitate genotype and phenotype simulation, association testing, genetic architecture inference, and polygenic scoring in admixed populations. Availability and implementationAdmix-kit package is open-source and available at https://github.com/KangchengHou/admix-kit. Additionally, users can use the pipeline designed for admixed genotype simulation available at https://github.com/UW-GAC/admix-kit_workflow.

genetics↗

bioRxiv2023

Optimizing data integration improves Gene Regulatory Network inference in Arabidopsis thaliana

MotivationsGene Regulatory Networks (GRN) are traditionnally inferred from gene expression profiles monitoring a specific condition or treatment. In the last decade, integrative strategies have successfully emerged to guide GRN inference from gene expression with complementary prior data. However, datasets used as prior information and validation gold standards are often related and limited to a subset of genes. This lack of complete and independent evaluation calls for new criteria to robustly estimate the optimal intensity of prior data integration in the inference process. ResultsWe address this issue for two common regression-based GRN inference models, an integrative Random Forest (weigthedRF) and a generalized linear model with stability selection estimated under a weighted LASSO penalty (weightedLASSO). These approaches are applied to data from the root response to nitrate induction in Arabidopsis thaliana. For each gene, we measure how the integration of transcription factor binding motifs influences model prediction. We propose a new approach, DIOgene, that uses model prediction error and a simulated null hypothesis for optimizing data integration strength in a hypothesis-driven, gene-specific manner. The resulting integration scheme reveals a strong diversity of optimal integration intensities between genes. In addition, it provides a good trade-off between prediction error minimization and validation on experimental interactions, while master regulators of nitrate induction can be accurately retrieved. Availability and implementationThe R code and notebooks demonstrating the use of the proposed approaches are available in the repository https://github.com/OceaneCsn/integrative_GRN_N_induction.

systems biology↗

bioRxiv2023

Exposure to aldehyde cherry e-liquid flavouring and its vape by-product disrupts pulmonary surfactant biophysical function

Over the last decade there has been a surge in vaping device usage, especially among adolescents, raising concerns for potentially related lung damage. Notoriously, there have been many e-cigarette or vaping-related lung injury (EVALI) cases resulting in hospitalisations and deaths. Although the vaping component vitamin E acetate has been linked to a large proportion of EVALI cases resulting in its widespread banning, one fifth of the cases remain unexplained. Furthermore, the overall long-term impact of vaping on respiratory health is poorly understood. A likely driver behind EVALI is pulmonary surfactant disruption, as it is the first point of contact for any inhaled toxicant in the alveoli, and abnormalities of its function are linked to some symptoms presented in EVALI cases. Aberrant biophysical function of the surfactant results in alveolar surface tension increase, causing alveolar collapse. Vaping chemicals with the potential to disrupt surfactant function must be hydrophobic molecules able to interact with surfactant components at the alveolar air-liquid interface. Recent findings have recorded the synthesis of highly hydrophobic acetal by-products of the base vaping chemical propylene glycol and common flavouring aldehydes, including the cherry flavouring benzaldehyde, not identified in preliminary e-liquid safety tests. This study provides evidence that benzaldehyde and its by-product, benzaldehyde propylene glycol acetal, have the potential to significantly disrupt surfactant biophysical function via interactions with surfactant proteins SP-B and/or SP-C, which may provide stable interactions within the surfactant film by forming associations with the sublayer of surfactant three-dimensional structure present at high lateral compression, i.e., expiration breathing. Data also suggest considerable vaping chemical loss to the experimental subphase, indicating potential further implications to the alveolar epithelial layer beneath.

pharmacology and toxicology↗

bioRxiv2023

The Pex6 N1 domain is required for Pex15 binding and proper assembly with Pex1

The heterohexameric AAA-ATPase Pex1/Pex6 is essential for the formation and maintenance of peroxisomes. Pex1/Pex6, similar to other AAA-ATPases, uses the energy from ATP hydrolysis to mechanically thread substrate proteins through its central pore, thereby unfolding them. In related AAA-ATPase motors, substrates are recruited through binding to the motors N-terminal domains or N-terminally bound co-factors. Here we use structural and biochemical techniques to characterize the function of the N1 domain in Pex6 from budding yeast, S. cerevisiae. We found that although Pex1/{Lambda}N1-Pex6 is an active ATPase in vitro, it does not support Pex1/Pex6 function at the peroxisome in vivo. An X-ray crystal structure of the isolated Pex6 N1 domain shows that the Pex6 N1 domain shares the same fold as the N terminal domains of PEX1, CDC48, or NSF, despite poor sequence conservation. Integrating this structure with a cryo-EM reconstruction of Pex1/Pex6, AlphaFold2 predictions, and biochemical assays shows that Pex6 N1 mediates binding to both the peroxisomal membrane tether Pex15 and an extended loop from the D2 ATPase domain of Pex1 that influences Pex1/Pex6 heterohexamer stability. Given the direct interactions with both Pex15 and the D2 ATPase domains, the Pex6 N1 domain is poised to coordinate binding of co-factors and substrates with Pex1/Pex6 ATPase activity.

biochemistry↗

bioRxiv2023

Cis-regulatory modes of Ultrabithorax inactivation in butterfly forewings

Hox gene clusters encode transcription factors that drive regional specialization during animal development: e.g. the Hox factor Ubx is expressed in the insect metathoracic (T3) wing appendages and differentiates them from T2 mesothoracic identities. Hox transcriptional regulation requires silencing activities that prevent spurious activation and regulatory crosstalks in the wrong tissues, but this has seldom been studied in insects other than Drosophila, which shows a derived Hox dislocation into two genomic clusters that disjoined Antennapedia (Antp) and Ultrabithorax (Ubx). Here we investigated how Ubx is restricted to the hindwing in butterflies, amidst a contiguous Hox cluster. By analysing Hi-C and ATAC-seq data in the butterfly Junonia coenia, we show that a Topologically Associated Domain (TAD) maintains a hindwing-enriched profile of chromatin opening around Ubx. This TAD is bordered by a Boundary Element (BE) that separates it from a region of joined wing activity around the Antp locus. CRISPR mutational perturbation of this BE releases ectopic Ubx expression in forewings, inducing homeotic clones with hindwing identities. Further mutational interrogation of two non-coding RNA encoding regions and one putative cis-regulatory module within the Ubx TAD cause rare homeotic transformations in both directions, indicating the presence of both activating and repressing chromatin features. We also describe a series of spontaneous forewing homeotic phenotypes obtained in Heliconius butterflies, and discuss their possible mutational basis. By leveraging the extensive wing specialization found in butterflies, our initial exploration of Ubx regulation demonstrates the existence of silencing and insulating sequences that prevent its spurious expression in forewings.

genomics↗

bioRxiv2023

Human Th17- and IgG3-associated autoimmunity induced by a translocating gut pathobiont

Extraintestinal autoimmune diseases are multifactorial with translocating gut pathobionts implicated as instigators and perpetuators in mice. However, the microbial contributions to autoimmunity in humans remain largely unclear, including whether specific pathological human adaptive immune responses are triggered by such pathobionts. We show here that the translocating pathobiont Enterococcus gallinarum induces human IFN{gamma}+ Th17 differentiation and IgG3 subclass switch of anti-E. gallinarum RNA and correlating anti-human RNA autoantibody responses in patients with systemic lupus erythematosus and autoimmune hepatitis. Human Th17 induction by E. gallinarum is cell-contact dependent and involves TLR8-mediated human monocyte activation. In murine gnotobiotic lupus models, E. gallinarum translocation triggers IgG3 anti-RNA autoantibody titers that correlate with renal autoimmune pathophysiology and with disease activity in patients. Overall, we define cellular mechanisms of how a translocating pathobiont induces human T- and B-cell-dependent autoimmune responses, providing a framework for developing host- and microbiota-derived biomarkers and targeted therapies in extraintestinal autoimmune diseases. One Sentence SummaryTranslocating pathobiont Enterococcus gallinarum promotes human Th17 and IgG3 autoantibody responses linked to disease activity in autoimmune patients.

immunology↗

bioRxiv2023

Parasite-Induced IFN-g Regulates Host Defense via CD115 and mTOR-Dependent Mechanism of Tissue-Resident Macrophage Death

Host resistance to a common protozoan parasite Toxoplasma gondii relies on a coordinated immune response involving multiple cell types, including macrophages. Embryonically seeded tissue-resident macrophages (TRMs) play a critical role in maintaining tissue homeostasis but their role in parasite clearance is poorly understood. In this study, we uncovered a crucial aspect of host defense against T. gondii mediated by TRMs. Through the use of neutralizing antibodies and conditional IFN-{gamma} receptor-deficient mice, we demonstrated that IFN-{gamma} directly mediated the elimination of TRMs. Mechanistically, IFN-{gamma} stimulation rendered macrophages unresponsive to macrophage colony-stimulating factor (M-CSF) and inactivated mTOR signaling by causing the shedding of CD115 (CSFR1), the receptor for M-CSF. Further experiments revealed the essential role of macrophage IFN-{gamma} responsiveness in host resistance to T. gondii. The elimination of peritoneal TRMs emerged as a host defense mechanism aimed at limiting the parasites reservoir. The identified mechanism, involving IFN-{gamma}-induced CD115 and mTOR-dependent cell death, provides insights into the adaptation of macrophage subsets during infection and highlights a crucial aspect of host defense against intracellular pathogens.

immunology↗

bioRxiv2023

Validation of de novo designed water-soluble and transmembrane proteins by in silico folding and melting

In silico validation of de novo designed proteins with deep learning (DL)-based structure prediction algorithms has become mainstream. However, formal evidence of the relationship between a high-quality predicted model and the chance of experimental success is lacking. We used experimentally characterized de novo designs to show that AlphaFold2 and ESMFold excel at different tasks. ESMFold can efficiently identify designs generated based on high-quality (designable) backbones. However, only AlphaFold2 can predict which sequences have the best chance of experimentally folding among similar designs. We show that ESMFold can generate high-quality structures from just a few predicted contacts and introduce a new approach based on incremental perturbation of the prediction ("in silico melting"), which can reveal differences in the presence of favorable contacts between designs. This study provides a new insight on DL-based structure prediction models explainability and on how they could be leveraged for the design of increasingly complex proteins; in particular membrane proteins which have historically lacked basic in silico validation tools.

bioinformatics↗

bioRxiv2023

Natural genetic variation underlying the negative effect of elevated CO2 on ionome composition in Arabidopsis thaliana

The elevation of atmospheric CO2 leads to a decline in the plant mineral content, which might pose a significant threat to food security in the coming decades. To date, very few genes have been identified as having a role in the negative effect of elevated CO2 on plant mineral composition. Yet, several studies have shown a certain degree of diversity in the ionomes response to elevated CO2, associated with genotypic variation. This suggests the existence of genetic factors controlling the effect of CO2 on ionome composition. However, no large-scale studies have been carried out to date to explore the genetic diversity of the ionome responses to elevated CO2. Here, we used six hundred Arabidopsis thaliana accessions, representing geographical distributions ranging from worldwide to regional and local environments, to analyze the natural genetic variation underlying the negative effect of elevated CO2 on the ionome composition in plants. We show that the growth under elevated CO2 leads to a global and important decrease of the ionome content whatever the geographic distribution of the population. We also observed a high range of genetic diversity in the response of the ionome composition to elevated CO2, and we identified sub-populations, showing effects on their ionome ranging from the most pronounced to resilience or even to a benefit in response to elevated CO2. Using genome-wide association mapping on the response of each mineral element to elevated CO2 or on integrative traits, we identified a large set of QTLs and genes associated with the ionome response to elevated CO2. Finally, we demonstrate that the function of one of these genes is associated to the negative effect of elevated CO2 on the plant mineral composition. This resource will contribute to understand the genetic mechanisms underlying the negative effect of elevated CO2 on plant mineral nutrition, and could help towards the development of crops adapted to a high-CO2 world.

plant biology↗

bioRxiv2023

ENDO-LYSOSOME-TARGETED NANOPARTICLE DELIVERY OF ANTIVIRAL THERAPY FOR CORONAVIRUS INFECTIONS

SARS-CoV-2 can infect cells through endocytic uptake, a process which is targeted by inhibition of lysosomal proteases. However, clinically this approach to treat viral infections has afforded mixed results, with some studies detailing an oral regimen of hydroxychloroquine accompanied by significant off-target toxicities. We rationalized that an organelle-targeted approach will avoid toxicity while increasing the concentration of the drug at the target. Here we describe a lysosome-targeted, mefloquine-loaded poly(glycerol monostearate-co-{varepsilon}-caprolactone) nanoparticle (MFQ-NP) for pulmonary delivery via inhalation. Mefloquine is a more effective inhibitor of viral endocytosis than hydroxychloroquine in cellular models of COVID-19. MFQ-NPs are less toxic than molecular mefloquine, 100-150 nm in diameter, and possess a negative surface charge which facilitates uptake via endocytosis allowing inhibition of lysosomal proteases. MFQ-NPs inhibit coronavirus infection in mouse MHV-A59 and human OC43 coronavirus model systems and inhibit SARS-CoV-2-WA1 and its Omicron variant in a human lung epithelium model. This study demonstrates that organelle-targeted delivery is an effective means to inhibit viral infection.

bioengineering↗

bioRxiv2023

Frizzled2 receives the WntA morphogen during butterfly wing pattern formation

Butterfly color patterns provide visible and biodiverse phenotypic readouts of the patterning processes that occur in a developing epithelium. While the secreted ligand WntA was shown to instruct the color pattern formation in butterflies, its modes of reception and signal transduction remain elusive. Butterfly genomes encode four homologues of the Frizzled-family of Wnt receptors. Here we show that CRISPR mosaic knock-outs of frizzled2 (fz2) phenocopy the color pattern effects of WntA loss-of-function in multiple nymphalids. While WntA mosaic clones result in intermediate patterns of reduced size, consistently with a morphogen function, fz2 clones are cell-autonomous. Shifts in pupal expression in WntA crispants show that WntA and fz2 are under positive and negative feedback, respectively. Fz1 is required for Wnt-independent planar cell polarity (PCP) in the wing epithelium. Fz3 and Fz4 show phenotypes consistent with Wnt competitive-antagonist functions in vein formation (Fz3 and Fz4), wing margin specification (Fz3), and color patterning in the Discalis and Marginal Band Systems (Fz4). Overall, these data show that the WntA/Frizzled2 morphogen-receptor pair forms a signaling axis that instructs butterfly color patterning, and shed light on the functional diversity of insect Frizzled receptors.

developmental biology↗

bioRxiv2023

Adaptive therapy for ovarian cancer: An integrated approach to PARP inhibitor scheduling

Toxicity and emerging drug resistance are important challenges in PARP inhibitor (PARPi) treatment of ovarian cancer. Recent research has shown that evolutionary-inspired treatment algorithms which adapt treatment to the tumors treatment response (adaptive therapy) can help to mitigate both. Here, we present a first step in developing an adaptive therapy protocol for PARPi treatment by combining mathematical modelling and wet-lab experiments to characterize the cell population dynamics under different PARPi schedules. Using data from in vitro Incucyte Zoom time-lapse microscopy experiments and a step-wise model selection process we derive a calibrated and validated ordinary differential equation model, which we then use to test different plausible adaptive treatment schedules. Our model can accurately predict the in vitro treatment dynamics, even to new schedules, and suggests that treatment modifications need to be carefully timed, or one risks losing control over tumour growth, even in the absence of any resistance. This is because our model predicts that multiple rounds of cell division are required for cells to acquire sufficient DNA damage to induce apoptosis. As a result, adaptive therapy algorithms that modulate treatment but never completely withdraw it are predicted to perform better in this setting than strategies based on treatment interruptions. Pilot experiments in vivo confirm this conclusion. Overall, this study contributes to a better understanding of the impact of scheduling on treatment outcome for PARPis and showcases some of the challenges involved in developing adaptive therapies for new treatment settings.

cancer biology↗