Thrilled to share our @CellCellPress paper with Shosei Yoshida & Ben Simons, led by @ChakraArun:
1) spatial geometry can resolve temporal dynamics
2) Sertoli cells run an intrinsic cycle coupled to germline, suggesting oscillator coupling as a principle of tissue organization
Our paper is finally out in Cell! Years of work on one of biology's most beautiful tissue clocks, and finding an intrinsic oscillator that helps organize tissue dynamics. From my PhD work at @LongCai_Lab, with Shosei Yoshida and Ben Simons!
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https://t.co/fRFxG3rbo2
Our paper is finally out in Cell! Years of work on one of biology's most beautiful tissue clocks, and finding an intrinsic oscillator that helps organize tissue dynamics. From my PhD work at @LongCai_Lab, with Shosei Yoshida and Ben Simons!
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https://t.co/fRFxG3rbo2
Very proud to finally publish Giotto Suite after many years of hard work. It's a big milestone for our lab and will be a massive stepping stone for our ongoing projects and ideas. Take a look at https://t.co/OqYpzxaqKy and feel free to share feedback and ideas for improvement.
I'm excited to share our new preprint on LagTag, a method that recovers both past and present chromatin states from the same mammalian cells.
https://t.co/GEGQpN0Ff0
Excited to share our new paper out in @Nature revealing cell-type specific nuclear organization and its link to gene regulation using new spatial multi-omics technologies! https://t.co/0LC2GlEpQs
Released my preprint! Here, we leverage spatial information to resolve temporal dynamics in male germ cell development! We reveal that Sertoli cells are precisely synchronized with periodic germ cell development and have an innate cyclic program independent of the germ cells!
Our new preprint with S.Yoshida and B.Simons! Led by @ChakraArun, we leverage spatial information to resolve temporal dynamics in spermatogenesis!
https://t.co/S5hhzqMi3g
Also check out a complementary preprint by S.Y. and B.S using live imaging! https://t.co/rrbxyFYylk
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Thrilled to share our latest work on lipid nanoparticle (LNP) delivery of a stable CRISPR-Cas9 ribonucleoprotein (RNP) for in vivo genome editing, now published @NatureBiotech! ๐งฌ
https://t.co/rX2bBKFMka
In this paper, we first engineered robust, efficient, and stable CRISPR-Cas9 genome-editing enzymes, iGeoCas9s, through #directedevolution of Cas9 from Geobacillus stearothermophilus (GeoCas9). We then developed an LNP-based delivery platform that successfully encapsulates and delivers iGeoCas9 RNP to various cell lines, achieving high-efficiency genome editing in vitro, including homology-directed repair (HDR) via codelivery of RNP and ssDNA templates. In the end, we demonstrated that different LNP formulations enabled tissue-specific genome editing in the liver and lungs after single intravenous injections of iGeoCas9 RNPโLNP complexes without triggering detectable immune responses. Overall, our results show that stable Cas9 RNPโLNP complexes can be a robust alternative to mRNAโLNP delivery and expand the therapeutic potential of CRISPR genome editing.
Our previous study @CellCellPress illustrated why our engineered iGeoCas9 exhibits dramatic improvements in its genome editing function. The high protein stability and desired negative charge density are the key to the successful development of the LNP delivery strategy for iGeoCas9 RNPs, which outperforms mRNA+sgRNA codelivery by LNPs for genome editing. We believe this LNP delivery platform can be further extended to other editing tools, such as base editors and prime editors.
Huge thanks to my collaborators @doudna_lab and in the Murthy lab for making this possible! @igisci@berkeleyMCB
๐จ๐๐ ๐๐๐ job opportunity @UCSF ๐จ:
I'm hiring TWO postdocs - an experimentalist and a computational biologist. Join us to use cutting-edge single-cell and spatial technologies to unravel the mysteries of human tissues.
https://t.co/QJqxMmrxGi
Just posted a preprint on our new spatial genomic recording system, baseMEMOIR.
https://t.co/ef5i8FnIOw
Motivation: Cells divide, differentiate, and migrate to form exquisitely organized tissues. Reconstructing the dynamic histories of individual cells, including their lineage relationships and ancestral states, is essential for understanding how intrinsic and extrinsic signals generate tissues during development and in regenerative medicine.
Engineered genomic recording systems can reconstruct cell lineage histories from endpoint measurements. However, existing methods either require sequencing (disrupting spatial organization) or have been limited in memory size and scalability.
To address this need, @ChadlyDuncan, Kirsten Frieda, and others in the lab created a high memory capacity image-readable recording system termed baseMEMOIR.