Periodic Reporting for period 4 - LSO (Liver Spatial Omics)
Okres sprawozdawczy: 2023-05-01 do 2024-04-30
The mammalian liver is a heterogeneous, yet highly structured organ, which performs diverse functions to maintain organismal homeostasis. Hepatocytes operate in repeating hexagonally shaped units termed lobules that are polarized by centripetal blood flow and morphogens. This polarized microenvironment facilitates optimal function by localizing specific processes to distinct lobule layers, a phenomenon known as ‘liver zonation’. Our lab discovered that about 50% of hepatocyte genes are zonated. This surprisingly broad spatial heterogeneity raises a fundamental question - do hepatocytes form a uniform population that differs due to spatially graded inputs or are hepatocytes at different zones rather distinct cell types? An additional important question is whether zonation can be observed for other cellular features beyond mRNA. Reconstructing Omics maps of the liver and consequently also other zonated mammalian tissues can enable a refined view of the cell types that make up our body and how local niches dictate their states.
To tackle these questions we are developing techniques for sorting massive amounts of hepatocytes from defined tissue coordinates with high spatial resolution using zonated surface markers. We have been performing deep and comprehensive profiling of the hepatocyte genome, methylome, epigenome, transcriptome, proteome and other features at each zone to characterize liver zonation at all relevant cellular scales.
The objectives of the project are:
1) Develop methodologies for spatial sorting of hepatocytes and other zonated mammalian cell types.
2) Reconstruct Omics maps of the liver and other tissues in physiological and pathological states.
3) Infer modes of zonated post-transcriptional gene regulation based on our omics zonation atlases.
To tackle these questions we are developing techniques for sorting massive amounts of hepatocytes from defined tissue coordinates with high spatial resolution using zonated surface markers. We have been performing deep and comprehensive profiling of the hepatocyte genome, methylome, epigenome, transcriptome, proteome and other features at each zone to characterize liver zonation at all relevant cellular scales.
The objectives of the project are:
1) Develop methodologies for spatial sorting of hepatocytes and other zonated mammalian cell types.
2) Reconstruct Omics maps of the liver and other tissues in physiological and pathological states.
3) Infer modes of zonated post-transcriptional gene regulation based on our omics zonation atlases.
We have previously uncovered broad zonation patterns of both parenchymal cells and non-parenchymal cells at the transcriptional level along the liver lobule axis. An outstanding question that guided us in the current ERC grant is whether cells at different tissue locations are inherently the same cell types, and exhibit transcriptional differences because they are exposed to spatially varying levels of morphogens, oxygen and nutrients, or rather whether they are epigenetically distinct cell types. For example, if I were to “pluck out” a periportal hepatocyte and insert it into the pericentral zone, would it behave as a pericentral hepatocyte or rather would remember its periportal identity. Addressing these questions requires measuring the zonal features of cells that go beyond mRNA, including DNA and chromatin methylations. Moreover, an outstanding question is whether proteins exhibit similar zonation patterns to their encoding mRNAs.
Given these fundamental questions in tissue biology, we set out to develop a generic approach that we termed ‘spatial sorting’ to measure any cellular feature along the tissues’ recurring axes. Spatial sorting is based on the usage of transcriptomics-based zonation atlases to identify zonated surface markers. Upon tissue dissociation, cells are incubated with a cocktail of spatially informative zonated surface markers, and gated so that hundreds of thousands of cells can be obtained in a spatially stratified manner (Ben-Moshe et al., Nature Metabolism 2019).
In the liver, we applied transcriptomics, microRNA (miRNA) array measurements and mass spectrometry proteomics on these spatially sorted populations to reconstruct spatial atlases of multiple zonated features.
We have also applied the spatial sorting approach to the small intestine - another zonated metabolic tissue. We developed a spatial sorting surface marker cocktail that we optimized to isolate six spatially stratified enterocyte populations along the intestinal villus axis. We measured both mRNAs and proteins along these villus zones. Surprisingly, unlike the liver, we found that around 40% of the genes had anti-correlated zonation profiles of mRNAs and their encoded proteins along the villus axis (Harnik et al., Nature Metabolism 2021). Since space and time are analogous along the villus, we developed a Bayesian approach to infer translation and protein degradation rates from the combined zonation profiles. We showed that the discordances between mRNAs and proteins are not borne out of zone-dependent post-transcriptional rates, but can rather be attributed to variable protein lifetimes.
The liver is not only spatially heterogeneous; it is also subject to extensive temporal regulation, orchestrated by the interplay of the circadian clock, systemic signals and feeding rhythms. To explore the interplay between gene regulation in space and time we extended our study and performed scRNAseq of 20,000 hepatocytes from 10 mice sacrificed at four time points along the day. We used our landmark-reconstruction approach to obtain the temporally varying zonation profiles of hepatocyte genes on a global scale (Droin et al., Nature Metabolism 2021). In collaboration with Felix Naef from EPFL, we developed a mixed-effect mathematical model to assess the joint impact of space and time on hepatocyte zonation and found that most hepatocyte genes show a multiplicative space-time effect. We found that the circadian clock machinery is largely non-zonated and that zonation profiles are varying at different time points by a multiplicative zone-independent factor. We also identified circadian expression of Wnt ligands, secreted from pericentral non-parenchymal cells (NPCs), potentially accounting for the circadian rhythms of hepatocyte Wnt target genes.
To extend our work to human tissues, we reconstructed a human spatially resolved single cell atlas in healthy states and in cancer, and a developmental atlas of the human small intestine, uncovering novel cellular states such as the appearance of insulin producing intestinal cells (Egozi et al. Nat Med 2021). We also explored the impact of liver zonation on regeneration (Ben-Moshe et al., Cell Stem Cell 2022) and on the malaria liver stage (Afriat et al., Nature 2022).
Given these fundamental questions in tissue biology, we set out to develop a generic approach that we termed ‘spatial sorting’ to measure any cellular feature along the tissues’ recurring axes. Spatial sorting is based on the usage of transcriptomics-based zonation atlases to identify zonated surface markers. Upon tissue dissociation, cells are incubated with a cocktail of spatially informative zonated surface markers, and gated so that hundreds of thousands of cells can be obtained in a spatially stratified manner (Ben-Moshe et al., Nature Metabolism 2019).
In the liver, we applied transcriptomics, microRNA (miRNA) array measurements and mass spectrometry proteomics on these spatially sorted populations to reconstruct spatial atlases of multiple zonated features.
We have also applied the spatial sorting approach to the small intestine - another zonated metabolic tissue. We developed a spatial sorting surface marker cocktail that we optimized to isolate six spatially stratified enterocyte populations along the intestinal villus axis. We measured both mRNAs and proteins along these villus zones. Surprisingly, unlike the liver, we found that around 40% of the genes had anti-correlated zonation profiles of mRNAs and their encoded proteins along the villus axis (Harnik et al., Nature Metabolism 2021). Since space and time are analogous along the villus, we developed a Bayesian approach to infer translation and protein degradation rates from the combined zonation profiles. We showed that the discordances between mRNAs and proteins are not borne out of zone-dependent post-transcriptional rates, but can rather be attributed to variable protein lifetimes.
The liver is not only spatially heterogeneous; it is also subject to extensive temporal regulation, orchestrated by the interplay of the circadian clock, systemic signals and feeding rhythms. To explore the interplay between gene regulation in space and time we extended our study and performed scRNAseq of 20,000 hepatocytes from 10 mice sacrificed at four time points along the day. We used our landmark-reconstruction approach to obtain the temporally varying zonation profiles of hepatocyte genes on a global scale (Droin et al., Nature Metabolism 2021). In collaboration with Felix Naef from EPFL, we developed a mixed-effect mathematical model to assess the joint impact of space and time on hepatocyte zonation and found that most hepatocyte genes show a multiplicative space-time effect. We found that the circadian clock machinery is largely non-zonated and that zonation profiles are varying at different time points by a multiplicative zone-independent factor. We also identified circadian expression of Wnt ligands, secreted from pericentral non-parenchymal cells (NPCs), potentially accounting for the circadian rhythms of hepatocyte Wnt target genes.
To extend our work to human tissues, we reconstructed a human spatially resolved single cell atlas in healthy states and in cancer, and a developmental atlas of the human small intestine, uncovering novel cellular states such as the appearance of insulin producing intestinal cells (Egozi et al. Nat Med 2021). We also explored the impact of liver zonation on regeneration (Ben-Moshe et al., Cell Stem Cell 2022) and on the malaria liver stage (Afriat et al., Nature 2022).
Our project yielded unique technologies (spatial sorting for assessing omics features of any zonated tissue, paired-cell RNA sequencing for the analysis of zonated transcriptomes of paired cells), unique single cell and zonated data browsers that are highly used by the communities. More globally, our project made multiple contributions to the global effort to reconstruct a single cell atlas.