shalev itzkovitz
@SItzkovitz
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Systems Biology of mammalian tissues
Joined January 2018
Great work by Tal Barkai. Thank you @LorenzAdlung and @KilianChristoph for highlighting our work:
embopress.org
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Check out our new paper in @MolSystBiol: Transcriptomic profiling of shed cells enables spatial mapping of cellular turnover in human organs https://t.co/CT3ZyjETlw We combine spatial and shed cell transcriptomics to reconstruct dynamic turnover maps of digestive tract tissues.
embopress.org
imageimageThis study combines transcriptomics of tissues and shed cells to create spatial organ maps highlighting the turnover rates of cells and tissue zones. Transcriptomics of both gastrointesti...
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Happy to share our new paper in @SciReports: Stool shed cell transcriptomics mirrors tumor biology and enables colorectal cancer diagnosis https://t.co/1e1qtyECa1 Great work by @KerenBaHa, @Oran_Yakubovsky, @ilan_kent, @sheba_medical, @WeizmannScience
nature.com
Scientific Reports - Stool shed cell transcriptomics mirrors tumor biology and enables colorectal cancer diagnosis
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Registration for our "Advances in Single-Cell Technologies" meeting is still open and we invite abstract submissions until October 30th. Join us in beautiful Freiburg together with an excellent line-up of single-cell technology experts! https://t.co/TjOS0UBrTr
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With the emergence of VisiumHD and other spatial transcriptomics datasets, HiVis can facilitate exploration of intra-cellular mRNA localization patterns across tissues and conditions. Great work by @RoyNovoselsky and @OfraGolani. @WeizmannScience.
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HiVis enables automated nucleus and cytoplasmic segmentation from H&E images, facilitating extraction of nuclear-cytoplasmic localization.
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We also performed VisiumHD measurements of mouse liver sections and identified mRNAs that are polarized towards the sinusoidal facing basal cell compartment.
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HiVis facilitates both tissue-level zonation reconstruction, and automated or guided detection of sub-cellular compartments to extract intra-cellular mRNA localization patterns. We demonstrate this by resolving apical-basal mRNA polarization in mouse intestinal epithelium.
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Intracellular mRNA polarization is hard to study. We developed HiVis: https://t.co/haSdlTVyr5, a computational Python package that combines image processing with transcriptomics to extract these features from VisiumHD datasets.
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Happy to share our new preprint: Subcellular mRNA localization patterns across tissues resolved with spatial transcriptomics: https://t.co/ejJMnMaYQF We utilize VisiumHD to extract intra-cellular mRNA polarization patterns in epithelial tissues.
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Stop the doom scrolling! A new 🗞️ from my lab, describing one of our flagship projects of many years we are super excited to share: "Inducible formation of fusion transcripts upregulates haploinsufficient CHD2 gene expression". A 🧵 https://t.co/935AvtPL8S
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Super excited to finally see this published! Our new method to use combinatorial staining and deep learning to push the multiplexing boundaries of spatial proteomics!
High-dimensional imaging using combinatorial channel multiplexing and deep learning https://t.co/balOMNQew0
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We asked @MoffitLab, @DrMingyaoLi, Qing Nie @uci_cmcf, @kazukane, @teichlab, Daniel Dar @WeizmannScience, @ltkagohara, @SItzkovitz, @roserventotormo, @ItaiYanai, @FertigLab, and @fabian_theis about the main bottlenecks facing Spatial Transcriptomics
cell.com
Image-based approaches to single-cell transcriptomics offer the exciting ability to directly image gene expression at the transcriptome scale within intact tissue slices, defining, discovering, and...
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@AlyagorLiat, @HadasKerenShaul, Inna Goliand, Yoseph Addadi, Merav Kedmi, Dana Hirsch, Chen Mayer, Ron Pery, @WeizmannScience, @MayoClinic, @sheba_medical #SpatialTranscriptomics #LiverBiology
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7/ Huge shoutout to the amazing team behind this, including: @Oran_Yakubovsky, @timucin_taner, @IdoNachman32521 & @NPencovich, @AfriatAmichay, @AdiEgozi, @KerenBaHa, Tal Barkai, Yael Korem Kohanim, @yotamharnik, @RoyNovoselsky, @OfraGolani,
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6/ Our data, including Loupe files for Visium & VisiumHD, is open access for exploration Zenodo: https://t.co/LYb4TBldOF Web browser: https://t.co/aw8YnCOeVs code: https://t.co/Sj78PP2TBu
github.com
A spatial transcriptomics atlas of live donors reveals unique zonation patterns in the healthy human liver. - OranYak/Human-liver
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5/ We also developed AI-based lipid classification for Visium spots, revealing dynamic expression changes in early steatosis: Early steatotic hepatocytes build lipids (↑ FASN, MLXIPL). Then, they shift to increased insulin & adiponectin receptor expression.
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4/ Key hepatic functions show pericentral shifts in humans, including Mitochondrial gluconeogenesis (PCK2), Urea cycle (NAGS, OTC), Respiration genes, and the Key TF HNF4A.
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3/ Most human hepatocyte genes are zonated, but zonation patterns in humans strongly differ from those in mice and even large mammals (cow, pig, boar), which we also profiled.
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2/ Using Visium, VisiumHD, and MERFISH on 16 patients, we uncovered striking differences between live donor liver and the commonly used 'adjacent normal' liver samples. Live donor livers show lower immune and higher hepatocyte expression programs.
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