Biology subjects

Lewin, A.

Publications and source records attributed to Lewin, A..

8 recordsLinked to original sources

bioRxiv2026

Proteomic profiling across early postnatal development of midbrain dopamine axons innervating the dorsal striatum

Precise wiring and tuning of dopamine axons in the brain is crucial for normal development of basal ganglia circuits. This process takes place both pre and postnatally, with early postnatal windows reflecting important periods of terminal maturation. Protein expression and precise localization are vital to this process, underlying changes in axon structure and function. Yet, technical hurdles have prohibited mapping protein expression and localization as dopamine axons mature to form functional release sites. Here we employ targeted proximity labeling in midbrain dopamine neurons and track isolated distal axonal proteins in the striatum across development, from the neonatal period through adolescence. Our approach enabled high-precision evaluation of the axonal proteome, supported by a combination of Cre-recombinase based restriction and spatial separation. We map co-varying subpopulations of axonal proteins differentially expressed across development. Microtubule-associated proteins decreased over time, revealing temporal dynamics of dopaminergic axon stabilization at the proteomic level. Conversely, proteins supporting coordinated action potential firing increased over time, likely contributing to the characteristic tonic firing of dopamine neurons emerging over development. Intersecting our findings with recent GWAS of psychiatric and neurological disorders provided functional confirmation of disease and disorder risk. This analysis highlighted early expression and localization of risk gene products, providing spatial-temporal points of convergence for disease-associated variants specifically to the initial stages of postnatal neurodevelopment of dopamine neurons. Together, these findings provide the essential grounding for understanding postnatal dopaminergic axon development and contextualize neurodevelopmental functions for numerous risk gene products.

neuroscience↗

bioRxiv2023

Multi-response Mendelian randomization: Identification of shared and distinct exposures for multimorbidity and multiple related disease outcomes

The existing framework of Mendelian randomization (MR) infers the causal effect of one or multiple exposures on one single outcome. It is not designed to jointly model multiple outcomes, as would be necessary to detect causes of more than one outcome and would be relevant to model multimorbidity or other related disease outcomes. Here, we introduce Multi-response Mendelian randomization (MR2), a novel MR method specifically designed for multiple outcomes to identify exposures that cause more than one outcome or, conversely, exposures that exert their effect on distinct responses. MR2 uses a sparse Bayesian Gaussian copula regression framework to detect causal effects while estimating the residual correlation between summary-level outcomes, i.e., the correlation that cannot be explained by the exposures, and viceversa. We show both theoretically and in a comprehensive simulation study how unmeasured shared pleiotropy induces residual correlation. We also reveal how non-genetic factors that affect more than one outcome contribute to their correlation. We demonstrate that by accounting for residual correlation, MR2 has higher power to detect shared exposures causing more than one outcome. It also provides more accurate causal effect estimates than existing methods that ignore the dependence between related responses. Finally, we illustrate how MR2 detects shared and distinct causal exposures for five cardiovascular diseases in two applications considering cardiometabolic and lipidomic exposures and uncovers residual correlation between summary-level outcomes reflecting known relationships between cardiovascular diseases.

genetics↗

bioRxiv2021

Genetic diversification of persistent Mycobacterium abscessus within Cystic Fibrosis patients

Mycobacterium (M.) abscessus infections in Cystic Fibrosis (CF) patients cause a deterioration of lung function. Treatment of these multidrug-resistant pathogens is associated with severe side-effects, while frequently unsuccessful. Insight on M. abscessus genomic evolvement during chronic lung infection would be beneficial for improving treatment strategies. A longitudinal study enrolling 42 CF patients was performed at a CF center in Berlin, Germany, to elaborate phylogeny and genomic diversification of in-patient M. abscessus. Eleven of the 42 CF patients were infected with M. abscessus. Global human-transmissible M. abscessus cluster strains were isolated from five of these 11 patients. Phylogenetic analysis of 88 genomes from isolates of the 11 patients excluded occurrence of M. abscessus transmission among members of the study group. Genome sequencing and variant analysis of 30 isolates from 11 serial respiratory samples collected over four years from a chronically infected patient demonstrated accumulation of gene mutations. In total, 53 genes exhibiting non-synonymous variations were identified. Enrichment analysis emphasized genes involved in synthesis of glycopeptidolipids, genes from the embABC (arabinosyltransferase) operon, betA (glucose-methanol-choline oxidoreductase) and choD (cholesterol oxidase). Genetic diversity evolved in a variety of virulence- and resistance-associated genes. The strategy of M. abscessus populations in chronic lung infection is not clonal expansion of dominant variants, but to sustain simultaneously a wide range of genetic variants facilitating adaptation of the population to changing living conditions in the lung. Genomic diversification during chronic infection requires increased attention when new control strategies against M. abscessus infections are explored.

genomics↗

bioRxiv2020

High-throughput detection of antibodies targeting the SARS-CoV-2 Spike in longitudinal convalescent plasma samples

BackgroundThe SARS-CoV-2 virus is the cause of the ongoing coronavirus disease 2019 (COVID-19) pandemic, infecting millions of people and causing more than a million deaths. The SARS-CoV-2 Spike glycoproteins mediate viral entry and represent the main target for antibody responses. Humoral responses were shown to be important for preventing and controlling infection by coronaviruses. A promising approach to reduce the severity of COVID-19 is the transfusion of convalescent plasma. However, longitudinal studies revealed that the level of antibodies targeting the receptor-binding domain (RBD) of the SARS-CoV-2 Spike declines rapidly after the resolution of the infection. Study Design and MethodsTo extend this observation beyond the RBD domain, we performed a longitudinal analysis of the persistence of antibodies targeting the full-length SARS-CoV-2 Spike in the plasma from 15 convalescent donors. We generated a 293T cell line constitutively expressing the SARS-CoV-2 Spike and used it to develop a high-throughput flow cytometry-based assay to detect SARS-CoV-2 Spike specific antibodies in the plasma of convalescent donors. Results and ConclusionWe found that the level of antibodies targeting the full-length SARS-CoV-2 Spike declines gradually after the resolution of the infection. This decline was not related to the number of donations, but strongly correlated with the decline of RBD-specific antibodies and the number of days post-symptom onset. These findings help to better understand the decline of humoral responses against the SARS-CoV-2 Spike and provide important information on when to collect plasma after recovery from active infection for convalescent plasma transfusion.

microbiology↗

bioRxiv2020

Major role of IgM in the neutralizing activity of convalescent plasma against SARS-CoV-2

Characterization of the humoral response to SARS-CoV-2, the etiological agent of Covid-19, is essential to help control the infection. In this regard, we and others recently reported that the neutralization activity of plasma from COVID-19 patients decreases rapidly during the first weeks after recovery. However, the specific role of each immunoglobulin isotype in the overall neutralizing capacity is still not well understood. In this study, we selected plasma from a cohort of Covid-19 convalescent patients and selectively depleted immunoglobulin A, M or G before testing the remaining neutralizing capacity of the depleted plasma. We found that depletion of immunoglobulin M was associated with the most substantial loss of virus neutralization, followed by immunoglobulin G. This observation may help design efficient antibody-based COVID-19 therapies and may also explain the increased susceptibility to SARS-CoV-2 of autoimmune patients receiving therapies that impair the production of IgM.

microbiology↗

bioRxiv2020

Longitudinal analysis of the humoral response to SARS-CoV-2 spike RBD in convalescent plasma donors

Hema-Quebec, the blood supplier in the Province of Quebec, Canada, collects and tests convalescent plasma used in a clinical trial to determine the clinical efficacy of this product for the treatment of hospitalized COVID-19 patients. So far, we have collected 1159 plasma units from 282 COVID-19 convalescent donors. The presence of antibodies to the receptor binding domain (RBD) of SARS-CoV-2 spike protein in convalescent donors was established at the first donation. Seropositive donors were asked to donate additional plasma units every six days. Until now, 15 donors have donated at least four times and, in some cases, up to nine times. This allowed us to perform a longitudinal analysis of the persistence of SARS-CoV-2 RBD-specific antibodies in these repeat donors, with the first donation occurring 33-77 days after symptoms onset and donations up to 71-114 days after symptoms onset thereafter. In all donors, the level of antibodies remained relatively stable up to about 76 days after symptoms onset but then started to decrease more rapidly to reach, in some convalescent donors, a seronegative status within 100-110 days after symptoms onset. The decline in anti-RBD antibodies was not related to the number of donations but strongly correlated with the numbers of days after symptoms onset (r = 0.821). This suggests that de novo secretion of SARS-CoV-2 RBD antibodies by short-lived plasma cells stopped about 2-3 months after disease onset, an observation that has important implications for convalescent plasma collection and seroprevalence studies undertaken several months after the peak of infection.

immunology↗

bioRxiv2020

Cross-sectional evaluation of humoral responses against SARS-CoV-2 Spike

The SARS-CoV-2 virus is responsible for the current worldwide coronavirus disease 2019 (COVID-19) pandemic, infecting millions of people and causing hundreds of thousands of deaths. The Spike glycoprotein of SARS-CoV-2 mediates viral entry and is the main target for neutralizing antibodies. Understanding the antibody response directed against SARS-CoV-2 is crucial for the development of vaccine, therapeutic and public health interventions. Here we performed a cross-sectional study on 106 SARS-CoV-2-infected individuals to evaluate humoral responses against the SARS-CoV-2 Spike. The vast majority of infected individuals elicited anti-Spike antibodies within 2 weeks after the onset of symptoms. The levels of receptor-binding domain (RBD)-specific IgG persisted overtime, while the levels of anti-RBD IgM decreased after symptoms resolution. Some of the elicited antibodies cross-reacted with other human coronaviruses in a genus-restrictive manner. While most of individuals developed neutralizing antibodies within the first two weeks of infection, the level of neutralizing activity was significantly decreased over time. Our results highlight the importance of studying the persistence of neutralizing activity upon natural SARS-CoV-2 infection.

microbiology↗

bioRxiv2018

Sparse variable and covariance selection for high-dimensional seemingly unrelated Bayesian regression

MotivationOur work is motivated by the search for metabolite Quantitative Trait Loci (QTL) in a cohort of more than 5,000 people. There are 158 metabolites measured by NMR spectroscopy measured in the 31-year follow-up of the Northern Finland Birth Cohort 1966 (NFBC66). These metabolites, as with many multivariate phenotypes produced by high-throughput biomarker technology, exhibit strong correlation structures. Existing approaches for combining such data with genetic variants for multivariate QTL analysis generally ignore phenotypic correlations or make restrictive assumptions about the associations between phenotypes and genetic loci. ResultsWe present a computationally efficient Bayesian Seemingly Unrelated Regressions (SUR) model for high-dimensional data, with cell-sparse variable selection and sparse graphical structure for covariance selection. Cell-sparsity allows different phenotype responses to be associated with different genetic predictors and the graphical structure is used to represent the conditional dependencies between phenotype variables. To achieve feasible computation of the large model space, we exploit a factorisation of the covariance matrix. Applying the model to the NFBC66 data with 9,000 directly-genotyped Single Nucleotide Polymorphisms, we are able to simultaneously estimate genotype-phenotype associations and the residual dependence structure amongst the metabolites at the same time. Availability and implementationThe R package BayesSUR with full documentation is available at https://cran.r-project.org/web/packages/BayesSUR/ Contactalex.lewin@lshtm.ac.uk

bioinformatics↗