Biology subjects

Zhu, R.

Publications and source records attributed to Zhu, R..

4 recordsLinked to original sources

bioRxiv2018

Penalized matrix decomposition for denoising, compression, and improved demixing of functional imaging data

Calcium imaging has revolutionized systems neuroscience, providing the ability to image large neural populations with single-cell resolution. The resulting datasets are quite large (with scales of TB/hour in some cases), which has presented a barrier to routine open sharing of this data, slowing progress in reproducible research. State of the art methods for analyzing this data are based on non-negative matrix factorization (NMF); these approaches solve a non-convex optimization problem, and are highly effective when good initializations are available, but can break down e.g. in low-SNR settings where common initialization approaches fail.\n\nHere we introduce an improved approach to compressing and denoising functional imaging data. The method is based on a spatially-localized penalized matrix decomposition (PMD) of the data to separate (low-dimensional) signal from (temporally-uncorrelated) noise. This approach can be applied in parallel on local spatial patches and is therefore highly scalable, does not impose non-negativity constraints or require stringent identifiability assumptions (leading to significantly more robust results compared to NMF), and estimates all parameters directly from the data, so no hand-tuning is required. We have applied the method to a wide range of functional imaging data (including one-photon, two-photon, three-photon, widefield, somatic, axonal, dendritic, calcium, and voltage imaging datasets): in all cases, we observe ~2-4x increases in SNR and compression rates of 20-300x with minimal visible loss of signal, with no adjustment of hyperparameters; this in turn facilitates the process of demixing the observed activity into contributions from individual neurons. We focus on two challenging applications: dendritic calcium imaging data and voltage imaging data in the context of optogenetic stimulation. In both cases, we show that our new approach leads to faster and much more robust extraction of activity from the video data.

neuroscience↗

bioRxiv2018

EZH2 co-opts gain-of-function p53 mutants to promote cancer growth and metastasis

With the unfolding of more and more cancer-driven gain-of-function (GOF) mutants of p53, it is important to define a common mechanism to systematically target different mutants rather than develop strategies tailored to inhibit each mutant individually. Here, using RNA immunoprecipitation sequencing (RIP-seq) we identified EZH2 as a p53 mRNA-binding protein. EZH2 bound to the internal ribosome entry site (IRES) in the 5 untranslated region (5UTR) of p53 mRNA and enhanced p53 protein translation in a methyltransferase-independent manner. EZH2 augmented p53 GOF mutant-mediated cancer growth and metastasis by increasing p53 GOF mutant protein level. EZH2 overexpression associated with the worse outcome only in patients with p53-mutated cancer. Depletion of EZH2 by antisense oligonucleotides inhibited p53 GOF mutant-mediated cancer growth. Our findings reveal a non-methyltransferase function of EZH2 that controls protein translation of p53 GOF mutants, inhibition of which causes synthetic lethality in cancer cells expressing p53 GOF mutants.

cancer biology↗

bioRxiv2018

Complete guide RNA design for CRISPR-mediated regulation of human long noncoding RNA transcription

Transcription inhibition and activation of long noncoding RNAs (lncRNAs) mediated by clustered regularly interspaced short palindromic repeat (CRISPR)/Cas9 technology provides potential advantages in high-throughput functional genomics studies over RNA interference or overexpression platforms. In this work, we identify over 90,000 lncRNA transcription start sites (TSSs) based on the MiTranscriptome human genome annotation and design single guide RNA (sgRNA) libraries with strong predicted activities and low off-target effects for CRISPR-mediated inhibition and activation (CRISPRi/a) of their transcription. A large fraction of these TSSs correspond to putative genes that are not annotated in common reference genome annotations and have never been functionally studied. Our CRISPRi/a libraries, or their context-dependent subsets, are potentially useful in genome-scale functional studies of human lncRNAs.

bioengineering↗

bioRxiv2017

Relevance of host cell surface glycan structure for cell specificity of influenza A virus

Influenza A viruses (IAV) initiate infection via binding of the viral hemagglutinin (HA) to sialylated glycan receptors on host cells. HAs receptor specificity towards sialic acid (SA) is well studied and clearly critical for virus infection, but the contribution of the highly complex cellular plasma membrane to the cellular specificity remains elusive. In addition, some studies indicated that other host cell factors such as the epidermal growth factor receptor might contribute to the initial virus-cell contact and further downstream signaling1.\n\nHere we use two complementary methods, glycan arrays and single-virus force spectroscopy (SVFS) to compare influenza virus receptor specificity with actual host cell binding. Unexpectedly, our study reveals that HAs receptor binding preference does not necessarily reflect virus-cell specificity. We propose SVFS as a tool to elucidate the cell binding preference of IAV thereby including the complex environment of sialylated receptors within the plasma membrane of living cells.

microbiology↗