Biology subjects

Albers, C.

Publications and source records attributed to Albers, C..

4 recordsLinked to original sources

bioRxiv2026

Top-down Sequencing of Intact Proteoforms using the timsOmni mass spectrometer: Accurate Determination of Co-occurring Histone Modifications

Deep characterization of intact proteoforms remains an analytical challenge in functional proteomics, particularly for heterogenous multi-site post-translational modifications at distinct amino acid residues. Histones are among the most dynamically and diversely post-translationally modified proteins in eukaryote cells, carrying multiple, co-occurring and reversible modifications that can give rise to isomeric proteoform species. Tandem mass spectrometry with multimodal fragmentation capabilities is a promising approach for deep characterization of intact proteoforms, such as modified histones. We applied the novel timsOmni mass spectrometer, which incorporates the Omnitrap platform enabling multimodal MS workflows, for residue-level mapping of histone modifications, including acetylation and methylation. Recombinant histones H3.1 and H4 were in vitro acetylated by enzymes GCN5, PCAF and p300 to generate mono- and multi-acetylated proteoforms. Complementary MS2 electron- and collision-based dissociation (ECD, EID, RCID and ECciD), together with MS3 strategies, produced complete or near-complete backbone fragmentation of intact protein ions (>92% amino acid sequence coverage). For monoacetylated species generated by the more site-selective lysine acetyltransferases, the dominant proteoform matched the known catalytic preferences of the enzymes (H3.1K14ac for GCN5 and PCAF, and H4K8ac for PCAF), while minor positional isomers were also identified and their relative abundance estimated. In contrast, the broader substrate specificity of p300 produced a wide distribution of H4 proteoforms bearing up to seven acetylated lysine residues. Species carrying six and seven acetylations were characterized by multimodal MS2/MS3 experiments, enabling localization of individual acetylation sites and discrimination of positional isomers. Finally, endogenous histone proteoforms from liver extracts were analyzed, yielding sequence coverages of 92-93% for the most abundant species and enabling confident localization of multiple PTMs (acetylation and methylation). These results illustrate that multimodal MSn fragmentation of intact proteins supports residue-level assignment of combinatorial histone marks and coexisting positional isomers. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=165 HEIGHT=200 SRC="FIGDIR/small/722147v1_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@387ab5org.highwire.dtl.DTLVardef@2410org.highwire.dtl.DTLVardef@13fc392org.highwire.dtl.DTLVardef@140e054_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIMultimodal MS{superscript 2}/MS3 maps histone PTMs on intact proteins. C_LIO_LIECD, EID, RCID, and ECciD provide complete or near-complete sequence coverage. C_LIO_LIMS3 localizes acetylation sites, distinguishes positional isomers. C_LIO_LIEndogenous H4 proteoforms are assigned with site-specific PTM mapping. C_LI

biochemistry↗

bioRxiv2024

Bio-inspired augmented reality: an interactive, digital twin of C. elegans

This work presents a digital twin of the nematode Caenorhabditis elegans (C. elegans), an organism whose biology has been extensively studied. The digital twin can emulate neuronal activity and the corresponding muscle activity, and performs basic locomotion movement. The underlying mathematical model of C. elegans can be realized directly as an electronic circuit and is additionally implemented as a ready-to-use simulation in software. We implemented the digital twin in augmented reality (AR) as a novel format that extends the content of a traditional paper with an interactive visualization in the real world. The figures in the paper are the anchor point for the AR that can be accessed by the readers via an open-source app, which is freely available for tablets, phones, and AR glasses. This enables immersive experiences of the three-dimensional visualization in the real world from a perspective chosen by the reader, supplementing the traditional, flat figure layout of the paper. For researchers, the digital twin further provides a useful tool that is highly relevant and versatile for future developments. At the same time, its manifold possibilities for scientific outreach also aim at making the topic more engaging for a broader audience.

bioengineering↗

bioRxiv2023

De novo genome assemblies reveal structural variations between laboratory and natural isolates of C. elegans

Genomic structural variations (SVs) and transposable elements (TEs) can be significant contributors to genome evolution, altered gene expression, and risk of genetic diseases. Recent advancements in long-read sequencing have greatly improved the quality of de novo genome assemblies and enhanced the detection of sequence variants at the scale of hundreds or thousands of bases. Comparisons between two diverged wild isolates of Caenorhabditis elegans, the Bristol and Hawaiian strains, have been widely utilized in the analysis of small genetic variations. Genetic drift, including SVs and rearrangements of repeated sequences such as TEs, can occur over time from long-term maintenance of wild type isolates within the laboratory. To comprehensively detect both large and small structural variations as well as TEs due to genetic drift, we generated de novo genome assemblies and annotations for each strain from our lab collection using both long- and short-read sequencing and compared our assemblies and annotations with that of other lab wild type strains. Within our lab assemblies, we annotate over 3.1Mb of sequence divergence between the Bristol and Hawaiian isolates: 337,584 SNPs, 94,503 small insertion-deletions (<50bp), and 4,334 structural variations (>50bp). Further, we define the location and movement of specific DNA TEs between N2 Bristol and CB4856 Hawaiian wild type isolates. Specifically, we find the N2 Bristol genome has 20.6% more TEs from the Tc1/mariner family than the CB4856 Hawaiian genome. Moreover, we identified Zator elements as the most abundant and mobile TE family in the genome. Using specific TE sequences with unique SNPs, we also identify 38 TEs that moved intrachromosomally and 9 TEs that moved interchromosomally between the N2 Bristol and CB4856 Hawaiian genomes. By comparing the de novo genome assembly of our lab collection Bristol isolate to the VC2010 Bristol assembly, we also reveal that lab lineages display over 2 Mb of total variation: 1,162 SNPs, 1,528 indels, and 897 SVs with 95% of the variation due to SVs. Overall, our work demonstrates the unique contribution of SVs and TEs to variation and genetic drift between wild type laboratory strains assumed to be isogenic despite growing evidence of genetic drift and phenotypic variation. Author SummaryFor multiple model organisms, propagation of wild type strains in independent labs can lead to multiple phenotypic differences over time. To assess recombination, map mutations, and understand genomic changes during speciation, Caenorhabditis elegans researchers primarily use the wild type isolates Bristol and Hawaiian. Here, we map structural variations, transposable elements, and sequence divergence between the Bristol and Hawaiian natural isolates and between genomes of different lab lineages of these same strains.

genomics↗

bioRxiv2019

Bayesian Linear Mixed Models for Motif Activity Analysis

MotivationCellular identity and behavior is controlled by complex gene regulatory networks. Transcription factors (TFs) bind to specific DNA sequences to regulate the transcription of their target genes. On the basis of these TF motifs in cis-regulatory elements we can model the influence of TFs on gene expression. In such models of TF motif activity the data is usually modeled assuming a linear relationship between the motif activity and the gene expression level. A commonly used method to model motif influence is based on Ridge Regression. One important assumption of linear regression is the independence between samples. However, if samples are generated from the same cell line, tissue, or other biological source, this assumption may be invalid. This same assumption of independence is also applied to different, yet similar, experimental conditions, which may also be inappropriate. In theory, the independence assumption between samples could lead to loss in signal detection. Here we investigate whether a Bayesian model that allows for correlations results in more accurate inference of motif activities.\n\nResultsWe extend the Ridge Regression to a Bayesian Linear Mixed Model, which allows us to model dependence between different samples. In a simulation study, we in-vestigate the differences between the two model assumptions. We show that our Bayesian Linear Mixed Model implementation outperforms Ridge Regression in a simulation scenario where the noise, the signal that can not be explained by TF motifs, is uncorrelated. However, we demonstrate that there is no such gain in performance if the noise has a similar covariance structure over samples as the signal that can be explained by motifs. We give a mathematical explanation to why this is the case. Using two representative real data sets we show that at most[~] 40% of the signal is explained by motifs using the linear model. With these data there is no advantage to using the Bayesian Linear Mixed Model, due to the similarity of the covariance structure.\n\nAvailability & ImplementationThe project implementation is available at https://github.com/Sim19/SimGEXPwMotifs.

bioinformatics↗