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Kondylis, V.

Publications and source records attributed to Kondylis, V..

2 recordsLinked to original sources

Single-cell resolution unravels spatial alterations in metabolism, transcriptome and epigenome of ageing liver

Epigenetic ageing clocks have revealed that tissues within an organism can age with different velocity. However, it has not been explored whether cells of one type experience different ageing trajectories within a tissue depending on their location. Here, we employed lipidomics, spatial transcriptomics and single-cell ATAC-seq in conjunction with available single-cell RNA-seq data to address how cells in the murine liver are affected by age-related changes of the microenvironment. Integration of the datasets revealed zonation-specific and age-related changes in metabolic states, the epigenome and transcriptome. Particularly periportal hepatocytes were characterized by decreased mitochondrial function and strong alterations in the epigenetic landscape, while pericentral hepatocytes - despite accumulation of large lipid droplets - did not show apparent functional differences. In general, chromatin alterations did not correlate well with transcriptional changes, hinting at post-transcriptional processes that shape gene expression during ageing. Together, we provide evidence that changing microenvironments within a tissue exert strong influences on their resident cells that can shape epigenetic, metabolic and phenotypic outputs.

cell biology↗

Single organoid RNA-sequencing reveals high organoid-to-organoid variability

Over the last decades, organoids have been established from the majority of tissue resident stem and iPS cells. They hold great promise for our understanding of mammalian organ development, but also for the study of disease or even personalized medicine. In recent years, several reports hinted at intraculture organoid variability, but a systematic analysis of such a heterogeneity has not been performed before. Here, we used RNA-seq of individual organoids to address this question. Importantly, we find that batch-to-batch variation is very low, even when prepared by different researchers. On the other hand, there is organoid-to-organoid variability within a culture. Using differential gene expression, we did not identify specific pathways that drive this variability, pointing towards possible effects of the microenvironment within the culture condition. Taken together, our study provides a framework for organoid researchers to properly consider experimental design.

cell biology↗