Biology subjects

Hebestreit, K.

Publications and source records attributed to Hebestreit, K..

6 recordsLinked to original sources

bioRxiv2023

Unravelling cell type specific response to Parkinson's Disease at single cell resolution

Parkinsons Disease (PD) is the second most common neurodegenerative disorder and is generally characterized by impaired motor functions. It currently affects 6.3 million people aged 60 years and more, worldwide. The pathological hallmarks of PD are Lewy bodies (abnormal aggregation of -synuclein inside cells), which are observed primarily in the substantia nigra (SN) region of the midbrain. It is yet not known how different cell types in SN respond during PD and what are the molecular mechanisms underlying neurodegeneration. To address this question, we generated a large-scale single cell transcriptomics dataset from human post-mortem SN tissue of 29 donors including 15 sporadic cases and 14 controls. We obtained data for a total of [~]80K nuclei, representing major cell types of the brain (including neurons, astrocytes, microglia and oligodendrocytes). Pathway and differential gene expression analysis revealed multicellular character of PD pathology involving major cellular response from neuronal and glial cells.

bioinformatics↗

bioRxiv2022

Single-nucleus co-expression networks of dopaminergic neurons support iron accumulation as a plausible explanation to their vulnerability in Parkinson's disease

Motivationgene co-expression networks have been widely applied to identify critical genes and pathways for neurodegenerative diseases such as Parkinsons and Alzheimers disease. Now, with the advent of single-cell RNA-sequencing, we have the opportunity to create cell-type specific gene co-expression networks. However, single-cell RNA-sequencing data is characterized by its sparsity, amongst some other issues raised by this new type of data. ResultsWe present scCoExpNets, a framework for the discovery and analysis of cell-type specific gene coexpression networks (GCNs) from single-cell RNA-seq data. We propose a new strategy to address the problem of sparsity, named iterative pseudo-cell identification. It consists of adding the gene expression of pairs of cells that belong to the same individual and the same cell-type while the number of cells is over 200, thus creating multiple matrices and multiple scGCNs for the same cell-type, all of them seen as alternative and complementary views of the same phenomena. We applied this new tool on a snRNA-seq dataset human post-mortem substantia nigra pars compacta tissue of 13 controls and 14 Parkinsons disease (PD) cases (18 males and 9 females) with 30-99 years. We show that one of the hypotheses that support the selective vulnerability of dopaminergic neurons in PD, the iron accumulation, is sustained in our dopaminergic neurons network models. Moreover, after successive pseudo-celluling iterations, the gene groups sustaining this hypothesis remain intact. At the same time, this pseudo-celulling strategy also allows us to discover genes whose grouping changes considerably throughout the iterations and provides new insights. Finally, since some of our models were correlated with diagnosis and age at the same time, we also developed our own framework to create covariate-specific GCNs, called CovCoExpNets. We applied this new software to our snRNA-seq dataset and we identified 11 age-specific genes and 5 diagnosis-specific genes which do not overlap. Availability and implementationThe CoExpNets implementations are available as R packages: scCoExpNets for creating single-cell GCNs and CovCoExpNets for creating covariate-specific GCNs. Users can either download the development version via github https://github.com/aliciagp/scCoExpNets and https://github.com/aliciagp/CovCoExpNets Contactalicia.gomez1@um.es Supplementary informationsupplementary data is available online.

bioinformatics↗

bioRxiv2022

Identification of protein aggregates in the aging vertebrate brain with prion-like andphase separation properties

Protein aggregation, which can sometimes spread in a prion-like manner, is a hallmark of neurodegenerative diseases. However, whether prion-like aggregates form during normal brain aging remains unknown. Here we use quantitative proteomics in the African turquoise killifish to identify protein aggregates that accumulate in old vertebrate brains. These aggregates are enriched for prion-like RNA binding proteins, notably the ATP-dependent RNA helicase DDX5. We validate that DDX5 forms mislocalized cytoplasmic aggregates in the brains of old killifish and mice. Interestingly, DDX5s prion-like domain allows these aggregates to propagate across many generations in yeast. In vitro, DDX5 phase separates into condensates. Mutations that abolish DDX5 prion propagation also impair the proteins ability to phase separate. DDX5 condensates exhibit enhanced enzymatic activity, but they can mature into inactive, solid aggregates. Our findings suggest that protein aggregates with prion-like properties form during normal brain aging, which could have implications for the age-dependency of cognitive decline.

neuroscience↗

bioRxiv2020

Males deploy multifaceted strategies and hijack longevity pathways to induce premature demise of the opposite sex

Interactions between the sexes negatively impact health in many species, including mammals1–9. In mice, sexual interactions induce weight gain and shorten lifespan in females, independent of fertilization6,9. In Caenorhabditis, males shorten the lifespan of the opposite sex (females or hermaphrodites)1–3,8. However, the mechanisms underlying the negative influence of males on lifespan – and their overlap with known longevity pathways – are still largely unknown. Here, we use transcriptomic profiling and targeted screens to systematically uncover new conserved genes involved in male-induced demise. Interestingly, deficiency of these genes individually, and especially in combination, induces strong protection, highlighting the benefit of combining interventions to extend lifespan. Some genes (e.g. acbp-3, col-43) only extend hermaphrodite lifespan when knocked-down in the presence of males, suggesting specific protective mechanisms against male-induced demise. However, we also uncover two previously unknown longevity genes (sri-40 and delm-2) that, when knocked-down, extend hermaphrodite lifespan both with and without males, which points to new broad mechanisms of resistance. In sharp contrast, many classical long-lived mutants are actually short-lived in the presence of males, suggesting that males hijack and suppress known longevity pathways. This systematic analysis reveals striking differences in longevity in single sex versus mixed sex environments and uncovers the elaborate network of functional regulation elicited by sexual interactions, which could extend to other species.Competing Interest StatementThe authors have declared no competing interest.View Full Text

genetics↗

bioRxiv2019

A Framework for Integrating Directed and Undirected Annotations to Build Explanatory Models of cis-eQTL Data.

1A longstanding goal of regulatory genetics is to understand how variants in genome sequences lead to changes in gene expression. Here we present a method named Bayesian Annotation Guided eQTL Analysis (BAGEA), a variational Bayes framework to model cis-eQTLs using directed and undirected genomic annotations. In a use case, we integrated directed genomic annotations with eQTL summary statistics from tissues of various origins. This analysis revealed epigenetic marks that are relevant for gene expression in different tissues and cell types. We estimated the predictive power of the models that were fitted based on directed genomic annotations. This analysis showed that, depending on the underlying eQTL data used, the directed genomic annotations could predict up to 1.5% of the variance observed in the expression of genes with top nominal eQTL association p-values < 10-7. For genes with estimated effect sizes in the top 25% quantile, up to 5% of the expression variance could be predicted. Based on our results, we recommend the use of BAGEA for the analysis of cis-eQTL data to reveal annotations relevant to expression biology.

genetics↗

bioRxiv2018

Old fibroblasts secrete inflammatory cytokines that drive variability in reprogramming efficiency and may affect wound healing between old individuals

Age-associated chronic inflammation (inflammaging) has emerged as a central hallmark of aging1-3, but its impact on specific cells is still largely unknown. Fibroblasts are present in all tissues and contribute to wound healing4-6. They are also the cell type that is mostly used for induced pluripotent stem cell (iPSC) reprogramming7 - a process that has implications for regenerative medicine and rejuvenation strategies8-17. Here we show that primary fibroblasts from old mice secrete inflammatory cytokines and that there is an increased variability in reprogramming efficiency between fibroblast cultures from old individuals. Individual-to-individual variability is emerging as a key feature of old age18-21, which could reflect distinct aging trajectories, but the underlying causes remain unknown. To identify drivers of this variability, we perform a multi-omic assessment of young and old fibroblast cultures with different reprogramming efficiency. This approach, coupled with single cell transcriptomics, reveals that old fibroblast cultures are heterogeneous and show a greater proportion of activated fibroblasts that secrete inflammatory cytokines, which correlates with reprogramming efficiency. We experimentally validate that activated fibroblasts express inflammatory cytokines in vivo and that their presence is linked to enhanced reprogramming efficiency in culture. Conditioned-media swapping experiments show that extrinsic factors secreted by activated fibroblasts are more critical than intrinsic factors for the individual-to-individual variability in reprogramming efficiency, and we identify TNF as a key inflammatory cytokine underlying this variability. Interestingly, old mice also exhibit variability in wound healing efficiency in vivo and old wounds show an increased subpopulation of activated fibroblasts with a unique TNF signature. Our study shows that a switch in fibroblast composition, and the ratio of inflammatory cytokines they secrete, drives variability in reprogramming in vitro and may influence wound healing in vivo. These findings could help identify personalized strategies to improve iPSC generation and wound healing in older individuals.

cell biology↗