Biology subjects

Hansen, M. B.

Publications and source records attributed to Hansen, M. B..

4 recordsLinked to original sources

bioRxiv2023

Tuning the double lipidation of salmon calcitonin to introduce a pore-like membrane translocation mechanism

A widespread strategy to increase the transport of therapeutic peptides across cellular membranes has been to attach lipid moieties to the peptide backbone (lipidation) to enhance their intrinsic membrane interaction. Efforts in vitro and in vivo investigating the correlation between lipidation characteristics and peptide membrane translocation efficiency have traditionally relied on end-point read-out assays and trial-and-error-based optimization strategies. Consequently, the molecular details of how therapeutic peptide lipidation affects its membrane permeation and translocation mechanisms remain unresolved. Here we employed salmon calcitonin as a model therapeutic peptide and synthesized nine double lipidated analogs with varying lipid chain lengths. We used single giant unilamellar vesicle (GUV) calcein influx time-lapse fluorescence microscopy to determine how tuning the lipidation length can lead to an All-or-None GUV filling mechanism, indicative of a peptide mediated pore formation. Finally, we used a GUVs-containing-inner-GUVs assay to demonstrate that only peptide analogs capable of inducing pore formation show efficient membrane translocation. Our data provided the first mechanistic details on how therapeutic peptide lipidation affects their membrane perturbation mechanism and demonstrated that fine-tuning lipidation parameters could induce an intrinsic pore-forming capability. These insights and the microscopy based workflow introduced for investigating structure-function relations could be pivotal for optimizing future peptide design strategies. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=197 SRC="FIGDIR/small/548826v1_ufig1.gif" ALT="Figure 1"> View larger version (87K): org.highwire.dtl.DTLVardef@23430org.highwire.dtl.DTLVardef@b06145org.highwire.dtl.DTLVardef@1c22579org.highwire.dtl.DTLVardef@12a56eb_HPS_FORMAT_FIGEXP M_FIG C_FIG Highlights- Lipidating the therapeutic peptide salmon calcitonin alters its biophysical characteristics, including oligomer size, hydrophobicity and membrane activity. - Fluorescent microscopy of single GUVs enables the determination of peptide mediated reporter dye influx behavior as either graded or All-or-None, which is coupled to either smaller membrane perturbations or peptide pore formation. - Modulating the number of hydrocarbons constituting the lipidation moieties determines the membrane permeation mechanism. - By increasing the lipid chain length lipidated of salmon calcitonin goes from displaying smaller membrane perturbations to a peptide pore formation mechanism. - Effective membrane translocation of lipidated salmon calcitonin requires a peptide mediated pore forming mechanism.

biophysics↗

bioRxiv2020

A systematic, unbiased mapping of CD8+ and CD4+ T cell epitopes in Yellow Fever vaccinees

1.Examining CD8+ and CD4+ T cell responses after primary Yellow Fever vaccination in a cohort of 210 volunteers, we have identified and tetramer-validated 92 CD8+ and 50 CD4+ T cell epitopes, many inducing strong and prevalent (i.e. immunodominant) T cell responses. Restricted by 40 and 14 HLA-class I and II allotypes, respectively, these responses have wide population coverage and might be of considerable academic, diagnostic and therapeutic interest. The broad coverage of epitopes and HLA overcame the otherwise confounding effects of HLA diversity and non-HLA background providing the first evidence of T cell immunodomination in humans. Also, double-staining of CD4+ T cells with tetramers representing the same HLA-binding core, albeit with different flanking regions, demonstrated an extensive diversification of the specificities of many CD4+ T cell responses. We suggest that this could reduce the risk of pathogen escape, and that multi-tetramer staining is required to reveal the true magnitude and diversity of CD4+ T cell responses. Our T cell epitope discovery approach uses a combination of 1) overlapping peptides representing the entire Yellow Fever virus proteome to search for peptides containing CD4+ and/or CD8+ T cell epitopes, 2) predictors of peptide-HLA binding to suggest epitopes and their restricting HLA allotypes, 3) generation of peptide-HLA tetramers to identify T cell epitopes, and 4) analysis of ex vivo T cell responses to validate the same. This approach is systematic, exhaustive, and can be done in any individual of any HLA haplotype. It is all-inclusive in the sense that it includes all protein antigens and peptide epitopes, and encompasses both CD4+ and CD8+ T cell epitopes. It is efficient and, importantly, reduces the false discovery rate. The unbiased nature of the T cell epitope discovery approach presented here should support the refinement of future peptide-HLA class I and II predictors and tetramer technologies, which eventually should cover all HLA class I and II isotypes. We believe that future investigations of emerging pathogens (e.g. SARS-CoV-2) should include population-wide T cell epitope discovery using blood samples from patients, convalescents and/or long-term survivors, who might all hold important information on T cell epitopes and responses.

immunology↗

bioRxiv2019

DeepCLIP: Predicting the effect of mutations on protein-RNA binding with Deep Learning

Nucleotide variants can cause functional changes by altering protein-RNA binding in various ways that are not easy to predict. This can affect processes such as splicing, nuclear shuttling, and stability of the transcript. Therefore, correct modelling of protein-RNA binding is critical when predicting the effects of sequence variations. Many RNA-binding proteins recognize a diverse set of motifs and binding is typically also dependent on the genomic context, making this task particularly challenging. Here, we present DeepCLIP, the first method for context-aware modeling and predicting protein binding to nucleic acids using exclusively sequence data as input. We show that DeepCLIP outperforms existing methods for modelling RNA-protein binding. Importantly, we demonstrate that DeepCLIP is able to reliably predict the functional effects of contextually dependent nucleotide variants in independent wet lab experiments. Furthermore, we show how DeepCLIP binding profiles can be used in the design of therapeutically relevant antisense oligonucleotides, and to uncover possible position-dependent regulation in a tissue-specific manner. DeepCLIP can be freely used at http://deepclip.compbio.sdu.dk.\n\nHighlightsO_LIWe have designed DeepCLIP as a simple neural network that requires only CLIP binding sites as input. The architecture and parameter settings of DeepCLIP makes it an efficient classifier and robust to train, making high performing models easy to train and recreate.\nC_LIO_LIUsing an extensive benchmark dataset, we demonstrate that DeepCLIP outperforms existing tools in classification. Furthermore, DeepCLIP provides direct information about the neural networks decision process through visualization of binding motifs and a binding profile that directly indicates sequence elements contributing to the classification.\nC_LIO_LITo show that DeepCLIP models generalize to different datasets we have demonstrated that predictions correlate with in vivo and in vitro experiments using quantitative binding assays and minigenes.\nC_LIO_LIIdentifying the binding sites for regulatory RNA-binding proteins is fundamental for efficient design of (therapeutic) antisense oligonucleotides. Employing a reported disease associated mutation, we demonstrate that DeepCLIP can be used for design of therapeutic antisense oligonucleotides that block regions important for binding of regulatory proteins and correct aberrant splicing.\nC_LIO_LIUsing DeepCLIP binding profiles, we uncovered a possible position-dependent mechanism behind the reported tissue-specificity of a group of TDP-43 repressed pseudoexons.\nC_LIO_LIWe have made DeepCLIP available as an online tool for training and application of proteinRNA binding deep learning models and prediction of the potential effects of clinically detected sequence variations (http://deepclip.compbio.sdu.dk/). We also provide DeepCLIP as a configurable stand-alone program (http://www.github.com/deepclip).\nC_LI

bioinformatics↗

bioRxiv2018

Genome-wide Association Study of Anxiety and Stress-related Disorders in the iPSYCH Cohort

Anxiety and stress-related disorders (ASRD) are among the most common mental disorders with the majority of patients suffering from additional disorders. Family and twin studies indicate that genetic and environmental factors are underlying their etiology. As ASRD are likely to configure various expressions of abnormalities in the basic stress-response system, we conducted a genome-wide association study including 12,655 cases with various anxiety and stress-related diagnoses and 19,225 controls. Standard association analyses were performed supplemented by a framework of sensitivity analyses. Variants in PDE4B showed consistent association with ASRD across a wide range of our analyses. In mice models, alternations in PDE4B expression were observed in those mice displaying anxious behavior after exposure to chronic stress. We also showed that 28% of the variance in ASRD was accounted for by common variants and that the genetic signature of ASRD overlapped with psychiatric traits, educational outcomes, obesity-related phenotypes, smoking, and reproductive success.

genetics↗