Biology subjects

Martin, J.

Publications and source records attributed to Martin, J..

At least 55 records · Page 3Linked to original sources

bioRxiv2024

Thermal Adaptation of Cytosolic Malate Dehydrogenase Revealed by Deep Learning and Coevolutionary Analysis

Protein evolution has produced enzymes that maintain stability and function across various thermal environments. While sequence variation, structural dynamics, and intermolecular interactions are known to influence an enzymes thermal adaptation, how these factors collectively govern stability and function across diverse temperatures remains unresolved. Cytosolic malate dehydrogenase (cMDH), a citric acid cycle enzyme, is an ideal model for studying these mechanisms due to its temperature-sensitive flexibility and broad presence in species from diverse thermal environments. In this study, we employ techniques inspired by deep learning and statistical mechanics to uncover how sequence variation and structural dynamics shape patterns of cMDHs thermal adaptation. By integrating coevolutionary models with variational autoencoders (VAE), we generate a latent generative landscape (LGL) of cMDH sequence space, enabling us to explore evolutionary pathways and predict fitness using direct coupling analysis (DCA). Structural predictions via AlphaFold and molecular dynamics simulations further illuminate how variations in hydrophobic interactions and conformational flexibility contribute to the thermal stability of warm- and cold-adapted cMDH orthologs. The integrative computational framework employed in this study provides powerful insights into protein adaptation at both sequence and structural levels, offering new perspectives on the evolution of thermal stability and creating avenues for the rational design of proteins with optimized thermal properties for biotechnological applications.

biophysics↗

bioRxiv2024

The effect of circulating neutralizing antibodies on the replication of SARS-CoV-2 variants following post-vaccination infections.

The impact of pre-existing neutralizing antibodies (NAbs) titers on SARS-CoV-2 viral shedding dynamics in post-vaccination infection (PVI) are not well understood. We characterized viral shedding longitudinally in nasal specimens in relation to baseline (pre/peri-infection) serum neutralizing antibody titers in 125 participants infected with distinct SARS-CoV-2 variants. Among 68 participants who had received vaccinations, we quantified the effect of baseline serum NAb titers on maximum viral RNA titers and on the duration of infectivity. Baseline NAb titers were higher and efficiently targeted a broader range of variants in participants who received one or two monovalent ancestral booster vaccinations compared to those with a full primary vaccine series. In participants with Delta variant infections, baseline NAb titers targeting Delta were negatively correlated with maximum viral RNA copies. Per log10 increase in baseline NAb IC50, maximum viral load was reduced -2.43 (95% confidence interval [CI] -3.76, -1.11) log10 N copies and days of infectious viral shedding were reduced -2.79 [95% CI: -4.99, -0.60] days. By contrast, in those with Omicron infections (BA.1, BA.2, BA.4 or BA.5 lineages) baseline NAb responses against Omicron lineages did not predict viral outcomes. Our results provide robust estimates of the effect of baseline NAbs on the magnitude and duration of nasal viral replication after PVI (albeit with an unclear effect on transmission) and show how immune escape variants efficiently evade these modulating effects.

immunology↗

bioRxiv2024

Alpha Synuclein Induced Immune Response Triggers Parkinson's Disease Like Symptoms

Increasing evidence suggests that Parkinsons disease is an autoimmune disorder, with findings of elevated peripheral blood mononuclear cell in patients, and antigenic properties of -synuclein driving both the innate and adaptive immunity. Yet, how the interaction of -synuclein and a specific immune response participates to Parkinsons disease ontogenesis has remained unanswered. Here, we reveal that autoimmune response to an -synuclein antigen underlies Parkinsons disease. We demonstrate that autoimmunity mediated by CD4+T cell activation with -synuclein -syn61-75 antigen is required to lead to immune cell infiltration and localized inflammation in the substantia nigra, triggering dopaminergic cell neurodegeneration and deficits in locomotion and gait kinematics. This study offers the first immune-induced mouse model that recapitulates all features of Parkinsons disease to study the mechanisms triggering disease onset. It provides the basis for temporally tracking symptom development, exploring preventive strategies and prodromal therapeutic interventions in Parkinsons Disease. In briefPeripheral -synuclein immunization causes Parkinsons disease-like symptoms in mice. Highlights- Both CD4+ T cells and -synuclein are essential for Parkinsons disease ontogenesis. - Peripheral injection of -syn61-75 induces significant CD4+ T cell infiltration in the mouse brain. - -syn61-75 immunization is associated with inflammation, -synuclein aggregation and dopaminergic cell loss in the substantia nigra pars compacta. - Levodopa-sensitive motor symptoms are detected 8 weeks following -syn61-75 immunization in mice. - This study offers a novel autoimmune -synuclein induced mouse model of Parkinsons disease.

neuroscience↗

bioRxiv2024

Targeting a shared neoepitope derived from non-canonical translation of c-MYC oncogene in cancer cells

Cancer cells rely on alternative modes of translation for protein synthesis, promoting internal ribosome entry site (IRES)-dependent translation of mRNA encoding pro-oncogenic factors. Furthermore, ribosomes translate mRNA with lower fidelity in tumor cells. We proposed that these translational modifications in cancer produce shared tumor-specific epitopes derived from IRES-containing oncogenes. To identify such neoepitopes, we developed an in silico-based method that we applied to c-MYC. We showed that the non-canonical translation of c-MYC mRNA in cancer cells, involving a (+1) ribosomal frameshift, generates a shared neoepitope which induces high-avidity T cells able to kill tumor cells in vitro and in vivo while sparing normal cells. Our data provide preclinical rationale for developing immunotherapies targeting this c-MYC-derived neoepitope and validate a new type of shared translation-associated neoantigens.

immunology↗

bioRxiv2024

Frequency-dependence in multidimensional diffusion-relaxation correlation MRI of the brain: overfitting or meaningful parameter?

Time- or frequency-dependent ("restricted") diffusion potentially provides useful information about cellular-scale structures in the brain but is challenging to interpret because of the intravoxel tissue heterogeneity. Frequency-dependence was recently incorporated in a multidimensional diffusion-relaxation correlation MRI framework relying on tensor-valued diffusion encoding at multiple frequencies, as well as variable echo and repetition times, to give model-free characterization of intravoxel heterogeneity by Monte Carlo data inversion into nonparametric distributions of frequency-dependent diffusion tensors and nuclear relaxation rates. While microimaging equipment with high-amplitude magnetic field gradients allows exploration of frequencies from tens to hundreds of Hz, clinical scanners with more moderate gradient capabilities are limited to a narrow frequency range, which may be insufficient to observe effects of restricted diffusion for brain tissues. We here investigate the effects of including or omitting frequency-dependence in the data inversion from isotropic and anisotropic liquids, excised tumor tissue, ex vivo mouse brain, and in vivo human brain. For microimaging measurements covering a wide frequency range, from 35 to 320 Hz at b-values over 4{middle dot}109 sm-2, the inclusion of frequency-dependence drastically reduces the fit residuals and avoids bias in the diffusion metrics for tumor and brain voxels with micrometer-scale structures. Conversely, for the case of in vivo human brain investigated in the narrow frequency range from 5 to 11 Hz at b = 3{middle dot}109 sm-2, analyses with and without inclusion of frequency-dependence yield similar fit residuals and diffusion metrics for all voxels. These results indicate that frequency-dependent inversion may be generally applied to diffusion-relaxation correlation MRI data with and without observable effects of restricted diffusion.

biophysics↗

bioRxiv2024

GenoTools: An Open-Source Python Package for Efficient Genotype Data Quality Control and Analysis

GenoTools, a Python package, streamlines population genetics research by integrating ancestry estimation, quality control (QC), and genome-wide association studies (GWAS) capabilities into efficient pipelines. By tracking samples, variants, and quality-specific measures throughout fully customizable pipelines, users can easily manage genetics data for large and small studies. GenoTools "Ancestry" module renders highly accurate predictions, allowing for high-quality ancestry-specific studies, and enables custom ancestry model training and serialization, specified to the users genotyping or sequencing platform. As the genotype processing engine that powers several large initiatives, including the NIHs Center for Alzheimers and Related Dementias (CARD) and the Global Parkinsons Genetics Program (GP2). GenoTools was used to process and analyze the UK Biobank and major Alzheimers Disease (AD) and Parkinsons Disease (PD) datasets with over 400,000 genotypes from arrays and 5000 sequences and has led to novel discoveries in diverse populations. It has provided replicable ancestry predictions, implemented rigorous QC, and conducted genetic ancestry-specific GWAS to identify systematic errors or biases through a single command. GenoTools is a customizable tool that enables users to efficiently analyze and scale genotype data with reproducible and scalable ancestry, QC, and GWAS pipelines.

genomics↗

bioRxiv2024

hoodscanR: profiling single-cell neighborhoods in spatial transcriptomics data

Understanding complex cellular niches and neighborhoods have provided new insights into tissue biology. Thus, accurate neighborhood identification is crucial, yet existing methodologies often struggle to detect informative neighborhoods and generate cell-specific neighborhood profiles. To address these limitations, we developed hoodscanR, a Bioconductor package designed for neighborhood identification and downstream analyses using spatial data. Applying hoodscanR to breast and lung cancer datasets, we showcase its efficacy in conducting detailed neighborhood analyses and identify subtle transcriptional changes in tumor cells from different neighborhoods. Such analyses can help researchers gain valuable insights into disease mechanisms and potential therapeutic targets.

bioinformatics↗

bioRxiv2024

AlphaFold-Multimer struggles in predicting PROTAC-mediated protein-protein interfaces

Proteolysis Targeting Chimeras (PROTACs) are heterobifunctional molecules composed by ligands binding to a target protein and a E3-ligase complex, connected by a linker, that induce proximity-based target protein degradation. PROTACs are promising alternatives to conventional drugs against cancer. Predicting PROTAC-mediated complexes is often the first step for in silico PROTAC design pipelines. AlphaFold2 (AF2) revolutionized structural biology, enabling the prediction of multimeric protein structures. However, we previously noted that AF2 fails to predict PROTAC-mediated complexes. Here, we investigate the potential causes of this limitation. We consider a set of 326 protein heterodimers orthogonal to the AF2 training set, and evaluate AF2 models focusing on the interface size and presence of interface ligand. Our results show that AF2-multimer predictions are sensitive to the size of the interface to predict even in the absence of ligands, with the majority of models being incorrect for the smallest interfaces. We also benchmark both AF2 and AF3 on a set of 28 PROTAC-mediated dimers and show that AF3 does not significantly improve upon the accuracy of AF2. The low accuracy of AF2 on complexes with small interfaces has strong implications for computational pipelines for PROTAC design, as these stabilize typically small interfaces, and more generally on any prediction task that involves small interfaces.

bioinformatics↗

bioRxiv2024

R6G narrows BmrA conformational spectrum for a more efficient use of ATP

Multidrug ABC transporters harness the energy of ATP binding and hydrolysis to change conformation and thereby translocate substrates out of the cell to detoxify them. While this general access mechanism scheme is well accepted, molecular details of this interplay is still elusive. Rhodamine6G binding on a catalytic mutant of the homodimeric multidrug ABC transporter BmrA triggers a cooperative binding of ATP on the two identical nucleotide-binding-sites, otherwise Michaelian. We investigated this asymmetric behavior via a structural-enzymology approach, solving cryoEM structure of BmrA at defined ATP ratio along the enzymatic transition, highlighting the plasticity of BmrA as it undergoes the transition from inward to outward facing conformations. Analysis of continuous heterogeneity within cryoEM data and structural dynamics, revealed that Rhodamine6G narrows the conformational spectrum explored by the nucleotide-binding-domains, describing the allosteric effect of drug binding that optimizes the ATP-dependent conversion of the transporter to the outward-facing state. Following on these findings, the effect of drug-binding showed an ATPase stimulation and a maximal transport activity of the wild-type protein at the concentration-range where the allosteric transition occurs. Drug diffusion rate is the likely rate-limiting step of the reaction, while drug transport and ATPase activities are in effect uncoupled.

biochemistry↗

bioRxiv2024

Identification of novel Bromodomain inhibitors of Trypanosoma cruzi Bromodomain Factor 2 (TcBDF2) using a fluorescence polarization-base high-throughput assay

Bromodomains are structural folds present in all eukaryotic cells that bind to other proteins recognizing acetylated lysines. Most proteins with bromodomains are part of nuclear complexes that interact with acetylated histone residues and participate in regulating DNA replication, transcription, and repair through chromatin structure remodeling. Bromodomain inhibitors are small molecules that bind to the hydrophobic pocket of bromodomains, interfering with the interaction with acetylated histones. Using a fluorescent probe, we have developed an assay to select inhibitors of the bromodomain factor 2 of Trypanosoma cruzi (TcBDF2) using fluorescence polarization. Initially, a library of 28,251 compounds was screened in an endpoint assay. The top 350 ranked compounds were further analyzed in a dose-response assay. From this analysis, 7 compounds were obtained that had not been previously characterized as bromodomain inhibitors. Although these compounds did not exhibit significative trypanocidal activity, all showed bona fide interaction with TcBDF2 with dissociation constants between 1 and 3 M validating these assays to search for bromodomain inhibitors.

microbiology↗

bioRxiv2024

The relationship between gut and nasopharyngeal microbiome composition can predict the severity of COVID-19

Coronavirus disease 2019 (COVID-19) is a respiratory illness caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that displays great variability in clinical phenotype. Many factors have been described to be correlated with its severity, and microbiota could play a key role in the infection, progression, and outcome of the disease. SARS-CoV-2 infection has been associated with nasopharyngeal and gut dysbiosis and higher abundance of opportunistic pathogens. To identify new prognostic markers for the disease, a multicenter prospective observational cohort study was carried out in COVID-19 patients divided into three cohorts based on symptomatology: mild (n=24), moderate (n=51), and severe/critical (n=31). Faecal and nasopharyngeal samples were taken, and the microbiota was analyzed. Linear discriminant analysis identified M. salivarium, P. dentalis, and H. parainfluenzae as biomarkers of severe COVID-19 in nasopharyngeal microbiota, while P. bivia and P. timonensis were defined in faecal microbiota. Additionally, a connection between faecal and nasopharyngeal microbiota was identified, with a significant ratio between P. timonensis (faeces) and P. dentalis and M. salivarium (nasopharyngeal) abundances found in critically ill patients. This ratio could serve as a novel prognostic tool for identifying severe COVID-19 cases.

microbiology↗

bioRxiv2023

SARS-CoV-2 NSP13 suppresses the Hippo pathway downstream effector YAP

The Hippo pathway controls organ development, homeostasis, and regeneration primarily by modulating YAP/TEAD-mediated gene expression. Although emerging studies report Hippo-YAP dysfunction after viral infection, it is largely unknown in the context of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Here, we analyzed RNA sequencing data from induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) and SARS-CoV-2-infected human lung samples, and observed a decrease in YAP target gene expression. In screening SARS-CoV-2 nonstructural proteins, we found that nonstructural protein 13 (NSP13), a conserved coronavirus helicase, inhibits YAP transcriptional activity independent of the upstream Hippo kinases LATS1/2. Consistently, introducing NSP13 into cardiomyocytes suppresses an active form of YAP (YAP5SA) in vivo. Subsequent investigations on NSP13 mutants revealed that NSP13 helicase activity, including DNA binding and unwinding, is crucial for suppressing YAP transactivation. Mechanistically, TEAD4 serves as a platform to recruit NSP13 and YAP. NSP13 likely inactivates the YAP/TEAD4 transcription complex by remodeling chromatin to recruit proteins, such as transcription termination factor 2 (TTF2), to bind the YAP/TEAD/NSP13 complex. These findings reveal a novel YAP/TEAD regulatory mechanism and uncover molecular insights into Hippo-YAP regulation after SARS-CoV-2 infection.

cell biology↗

bioRxiv2023

Deep learning and direct sequencing of labeled RNA captures transcriptome dynamics

Quantification of the dynamics of RNA metabolism is essential for understanding gene regulation in health and disease. Existing methods rely on metabolic labeling of nascent RNAs and physical separation or inference of labeling through PCR-generated mutations, followed by short-read sequencing. However, these methods are limited in their ability to identify transient decay intermediates or co-analyze RNA decay with cis-regulatory elements of RNA stability such as poly(A) tail length and modification status, at single molecule resolution. Here we use 5-ethynyl uridine (5EU) to label nascent RNA followed by direct RNA sequencing with nanopores. We developed RNAkinet, a deep convolutional and recurrent neural network that processes the electrical signal produced by nanopore sequencing to identify 5EU-labeled nascent RNA molecules. RNAkinet demonstrates generalizability to distinct cell types and organisms and reproducibly quantifies RNA kinetic parameters allowing the combined interrogation of RNA metabolism and cis-acting RNA regulatory elements.

bioinformatics↗

bioRxiv2023

The dynamics of protein-RNA interfaces using all-atom molecular dynamics simulations

Facing the current challenges raised by human health diseases requires the understanding of cell machinery at a molecular level. The interplay between proteins and RNA is key for any physiological phenomenon, as well protein-RNA interactions. To understand these interactions many experimental techniques have been developed, spanning a very wide range of spatial and temporal resolutions. In particular, the knowledge of tridimensional structures of protein-RNA complexes provides structural, mechanical and dynamical pieces of information essential to understand their functions. To get insights into the dynamics of protein-RNA complexes, we carried out all-atom molecular dynamics simulations in explicit solvent on nine different protein-RNA complexes with different functions and interface size by taking into account the bound and unbound forms. First, we characterized structural changes upon binding and for the RNA part the change in the puckering. Second, we extensively analyzed the in-terfaces, their dynamics and structural properties, and the structural waters involved in the binding, as well as the contacts mediated by them. Based on our analysis, the interfaces rearranged during the simulation time showing alternative and stable residue-residue contacts with respect to the experimental structure.

biochemistry↗

bioRxiv2023

Butyrate-producing bacteria as probiotic supplement: beneficial effects on metabolism and modulation of behavior in an obesity mouse model

Obesity is a risk factor for cardio-metabolic and neurological disease. The contribution of gut microbiota to derangements of the gut-brain axis in the context of obesity has been acknowledged, particularly through physiology modulation by short-chain fatty acids (SCFAs). Thus, probiotic interventions and administration of SCFAs have been employed with the purpose of alleviating symptoms in both metabolic and neurological disease. We have tested the effects of four butyrate-producing bacteria from the Lachnospiraceae family on the development of metabolic syndrome and behavioural alterations in a mouse model of diet-induced obesity. Male mice were fed either a high-fat diet (HFD) or an ingredient-matched control diet for 2 months, and bacteria cultures or culture medium were given by gavage to HFD-fed mice every second day. Assessment of the mice through a battery of metabolic and behaviour tests revealed that one of the administered bacteria affords some degree of protection against the development of obesity and its complications.

physiology↗

bioRxiv2023

Lipid discovery enabled by sequence statistics and machine learning

Bacterial membranes are complex and dynamic, arising from an array of evolutionary pressures. One enzyme that alters membrane compositions through covalent lipid modification is MprF. We recently identified that Streptococcus agalactiae MprF synthesizes lysyl-phosphatidylglycerol (Lys-PG) from anionic PG, and a novel cationic lipid, lysyl-glucosyl-diacylglycerol (Lys-Glc-DAG), from neutral glycolipid Glc-DAG. This unexpected result prompted us to investigate whether Lys-Glc-DAG occurs in other MprF-containing bacteria, and whether other novel MprF products exist. Here, we studied protein sequence features determining MprF substrate specificity. First, pairwise analyses identified several streptococ-cal MprFs synthesizing Lys-Glc-DAG. Second, a restricted Boltzmann machine-guided approach led us to discover an entirely new substrate for MprF in Enterococcus, diglucosyl-diacylglycerol (Glc2-DAG), and an expanded set of organisms that modify glycolipid substrates using MprF. Overall, we combined the wealth of available sequence data with machine learning to model evolutionary constraints on MprF sequences across the bacterial domain, thereby identifying a novel cationic lipid.

microbiology↗

bioRxiv2023

In vivo disentanglement of diffusion frequency-dependence, tensor shape, and relaxation using multidimensional MRI

Diffusion MRI with free gradient waveforms, combined with simultaneous relaxation encoding, referred to as multidimensional MRI (MD-MRI), offers microstructural specificity in complex biological tissue. This approach delivers intravoxel information about the microstructure, local chemical composition, and importantly, how these properties are coupled within heterogeneous tissue containing multiple microenvironments. Recent theoretical advances incorporated diffusion time dependency and integrated MD-MRI with concepts from oscillating gradients. This framework probes the diffusion frequency,{omega} , in addition to the diffusion tensor, D, and relaxation, R1, R2, correlations. A D({omega})-R1-R2 clinical imaging protocol was then introduced, with limited brain coverage and 3 mm3 voxel size, which hinder brain segmentation and future cohort studies. In this study, we introduce an efficient, sparse in vivo MD-MRI acquisition protocol providing whole brain coverage at 2 mm3 voxel size. We demonstrate its feasibility and robustness using a well-defined phantom and repeated scans of five healthy individuals. Additionally, we test different denoising strategies to address the sparse nature of this protocol, and show that efficient MD-MRI encoding design demands a nuanced denoising approach. The MD-MRI framework provides rich information that allows resolving the diffusion frequency dependence into intravoxel components based on their D({omega})-R1-R2 distribution, enabling the creation of microstructure-specific maps in the human brain. Our results encourage the broader adoption and use of this new imaging approach for characterizing healthy and pathological tissues.

neuroscience↗

bioRxiv2023

Variants in the DDX6-CXCR5 autoimmune disease risk locus influence the regulatory network in immune cells and salivary gland

Fine mapping and bioinformatic analysis of the DDX6-CXCR5 genetic risk association in Sjogrens Disease (SjD) and Systemic Lupus Erythematosus (SLE) identified five common SNPs with functional evidence in immune cell types: rs4938573, rs57494551, rs4938572, rs4936443, rs7117261. Functional interrogation of nuclear protein binding affinity, enhancer/promoter regulatory activity, and chromatin-chromatin interactions in immune, salivary gland epithelial, and kidney epithelial cells revealed cell type-specific allelic effects for all five SNPs that expanded regulation beyond effects on DDX6 and CXCR5 expression. Mapping the local chromatin regulatory network revealed several additional genes of interest, including lnc-PHLDB1-1. Collectively, functional characterization implicated the risk alleles of these SNPs as modulators of promoter and/or enhancer activities that regulate cell type-specific expression of DDX6, CXCR5, and lnc-PHLDB1-1, among others. Further, these findings emphasize the importance of exploring the functional significance of SNPs in the context of complex chromatin architecture in disease-relevant cell types and tissues.

genetics↗