Biology subjects

Albrecht, B.

Publications and source records attributed to Albrecht, B..

3 recordsLinked to original sources

bioRxiv2025

Anionic Phospholipids Modulate Hepatitis C Virus Core Protein Assembly on Lipid Membranes

Hepatitis C virus (HCV) genome codes for various proteins essential to its replication cycle. Among these, the core protein (HCC) forms the capsid via organised multimerization, thereby guiding viral assembly. This process depends on the dynamic localisation of HCC between the endoplasmic reticulum bilayer membrane and the lipid droplet monolayer. While past studies have examined the role of some HCC structural properties and other viral and host proteins in the assembly process, the contribution of lipid molecules was not thoroughly investigated yet. Since specific lipids are upregulated during HCV infection, it is reasonable that these molecules might play an important role for virus fitness and infection progression. In this study, we have addressed this topic and, specifically, how HCC-lipid interactions might impact HCC-HCC interactions. Using in vitro models and quantitative fluorescence microscopy techniques, we investigated HCC binding affinity to lipid membranes, multimerization and lateral diffusivity. Our results reveal the effect of HCC interactions with anionic phospholipids (PLs) on the binding to monolayers and bilayers. Furthermore, our analysis shows that PI(4)P enhances HCC multimerization and, therefore, might drive lateral assembly for capsid formation. These results not only provide insights into the lipid-driven regulation of HCV assembly and identify anionic PLs as potential modulators of the viral replications cycle, but also highlight a previously unrecognised role of PL composition in HCC-membrane interaction. SignificanceHepatitis C virus (HCV) remains a major global health challenge and is associated with substantial mortality. In certain regions, HCV infection reaches epidemic proportions. Despite its prevalence, targeted and cost-effective therapeutic options remain limited, largely due to an incomplete understanding of the viral life cycle. A critical - yet poorly characterized - step in this cycle is the assembly of the HCV core (HCC) protein into the viral capsid, which is essential for replication. Here, we use quantitative fluorescence microscopy to investigate the role of specific lipid species in HCC assembly on model membranes. Our findings show that distinct lipid environments modulate HCC assembly and that HCC, in turn, induces measurable changes in the biophysical properties of the host membrane.

biophysics↗

bioRxiv2019

Anti-consensus: detecting trees that have an evolutionary signal that is lost in consensus

AO_SCPLOWBSTRACTC_SCPLOWIn phylogenetics, a set of gene trees is often summarized by a consensus tree, such as the majority consensus, which is based on the set of all splits that are present in more than 50% of the input trees. A \"consensus network\" is obtained by lowering the threshold and considering all splits that are contained in 10% of the trees, say, and then computing the corresponding splits network. By construction and in practice, a consensus network usually shows the majority tree, extended by a number of rectangles that represent local rearrangements around internal nodes of the consensus tree. This may lead to the false conclusion that the input trees do not differ in a significant way because \"even a phylogenetic network\" does not display any large discrepancies. To harness the full potential of a phylogenetic network, we introduce the new concept of an anti-consensus network that aims at representing the largest interesting discrepancies found in a set of gene trees. We provide an efficient algorithm for computing an anti-consensus and illustrate its application using a set of gene trees from species and strains in the genus Kosakonia.

bioinformatics↗

bioRxiv2017

MEGAN-LR: New algorithms allow accurate binning and easy interactive exploration of metagenomic long reads and contigs

BackgroundThere are numerous computational tools for taxonomic or functional analysis of microbiome samples, optimized to run on hundreds of millions of short, high quality sequencing reads. Programs such as MEGAN allow the user to interactively navigate these large datasets. Long read sequencing technologies continue to improve and produce increasing numbers of longer reads (of varying lengths in the range of 10k-1M bps, say), but of low quality. There is an increasing interest in using long reads in microbiome sequencing and there is a need to adapt short read tools to long read datasets.\n\nMethodsWe describe a new LCA-based algorithm for taxonomic binning, and an interval-tree based algorithm for functional binning, that are explicitly designed for long reads and assembled contigs. We provide a new interactive tool for investigating the alignment of long reads against reference sequences. For taxonomic and functional binning, we propose to use LAST to compare long reads against the NCBI-nr protein reference database so as to obtain frame-shift aware alignments, and then to process the results using our new methods.\n\nResultsAll presented methods are implemented in the open source edition of MEGAN and we refer to this new extension as MEGAN-LR (MEGAN long read). We evaluate the LAST+MEGAN-LR approach in a simulation study, and on a number of mock community datasets consisting of Nanopore reads, PacBio reads and assembled PacBio reads. We also illustrate the practical application on a Nanopore dataset that we sequenced from an anammox bio-rector community.

bioinformatics↗