We are very excited to present the development of Zman-seq (“Zman”, Hebrew for “time”), the 1st technology that measures single-cell transcriptomes and physical time in vivo, led by @D_Birschenkaum, @CuriousKX, @FlorianIngelfi1, @AssafWeiner
. (1/19) sciencedirect.com/science/articl…
Biology is utterly complex. Luckily, scientists are continuously inventing tools to achieve higher and higher granularity to describe tissues>> cells >> molecules.
Will an ultimate level of granularity lead to the understanding of biology? (2/19)

We're thrilled to share our recent @NatureMedicine study, cracking the decades-old mystery surrounding the identity of cells responsible for producing erythropoietin (Epo) - the key regulator of erythropoiesis and oxygen homeostasis in our bodies. nature.com/articles/s4159… (1/16) Epo is probably most famous – or infamous – for its illegal use as a doping agent in sports, most notably by the cyclist Lance Armstrong. But the hormone’s huge therapeutic potential goes far beyond enhancing stamina & it has fascinated researchers for more than a century (2/16)

We are excited to share our @NatureCancer paper showing how interactions between subtypes of T and dendritic cells shape the tumor microenvironment in patients with different types of cancers and can enhance the response to checkpoint blockade therapy nature.com/articles/s4301… We discovered this crosstalk between myeloid and T cells using RNA sequencing of physically interacting cells (PIC-seq) of samples from the tumor microenvironment (TME) and healthy lung tissue of non-small cell lung carcinoma (NSCLC) patients

We are very excited to share our new multi-resolution deconvolution approach for spatial transcriptomics (ST) measurements, DestVI, a joint work by @YosefLab and @IdoAmitLab led by @_romain_lopez, @lbgbox, and @HadasKerenShaul on bioRxiv: biorxiv.org/content/10.110… (1/12) A major limitation in ST data is the need to deconvolute cell aggregates (spots) into defined cell states. Current approaches are mostly successful for discrete cell types but are less effective when cell states display continuous variations within cell types (2/12)

We are very excited to share our new study identifying resistance pathways and therapeutic targets in relapsed multiple myeloma lead by @MorZada3, @MoonspiriTYin, and @AssafWeiner @WeizmannScience nature.com/articles/s4159… (1/14). A joint work with our long-lasting collaborator, Prof. Yael Cohen and Prof. Irit Avivi from @tasmc1, Prof. Moshe Gat from @Hadassah and ALL hematology departments in Israel (2/14).

We are very excited to present INs-seq, a new technology for massively parallel single-cell RNA-sequencing (scRNA-seq) integrated with recording of intracellular protein activities. Developed by @YonatanKatza @FadiSheban @AdamYalin and @AssafWeiner cell.com/cell/fulltext/… (1/14) Integrating scRNA-seq with surface protein measurement is a routine now. But how can we know what’s happening *inside* the cell? INs-seq allows for detection of intracellular protein events combined with transcriptome profiling in single cells! (2/14)

We are excited to share ‘Host-viral infection maps reveal signatures of severe COVID-19 patients’ cell.com/cell/fulltext/… led by @bost_pierre and @AmirGiladi. Collab with the Zheng Lab from the Shenzhen Third People’s Hospital and Benno Schwikowski from @institutpasteur 1/13 Emerging viral infections are a constant threat to global health, as shown by the current COVID-19 outbreak, and tools to molecularly dissect host-viral interactions are lacking. 2/13

We are excited to present PIC-seq, a novel single cell technology for investigating cell-cell interactions, developed by @AmirGiladi and @meravcohen8, in collaboration with Amos Tanay. (1/11) nature.com/articles/s4158… PIC-seq combines flow cytometry with single cell RNA-seq to molecularly profile physically interacting cells (PICs), identify interaction preferences of different cell types, and reveal alterations in gene expression and signaling unique to the interaction. (2/11)

Super excited to share our work on microglia diversity across evolution by @microgliaandme Eyal David @HadasKerenShaul @AssafWeiner and co. Now in @CellCellPress ! cell.com/cell/fulltext/… With the help of our great collaborators, we tracked microglia across 450 million years of evolution by collecting brains from 18 different species, such as blind mole rat, fish, chicken, sheep, monkeys and humans. (2/10)