Biology subjects

Liem, C. R.

Publications and source records attributed to Liem, C. R..

5 recordsLinked to original sources

bioRxiv2026

Structural Determinants of Ligand-Mediated Hmg2 Mallostery

The sterol pathway is a conserved eukaryotic process that produces essential metabolites. Hmg-CoA reductase (HMGR) is a key rate limiting enzyme of the sterol pathway and is the most successful clinical target for managing cholesterol levels. However, determination of the structural features that are essential for its regulation remains elusive. Because of the conservation between mammals and yeast, for many years we have studied the structural features of a yeast Hmg2 isozyme of HMGR. Hmg2 is regulated by the mevalonate pathway isoprenoid GGPP. GGPP acts similarly to an allosteric ligand and appears to bind to a specific site on Hmg2, causing Hmg2 to undergo reversible misfolding. Misfolded Hmg2 is then recognized by the protein quality control mechanism known as the HRD pathway. Due to its similarity to allosteric regulation we have termed this ligand-dependent misfolding mallostery. In this work, we systematically probe each residue of the Hmg2 lumenal domain as well as assess the transmembrane domain and lumenal domain as independent domains and use in vivo and in vitro techniques to assess what regions are important for GGPP response. We identified stabilizing mutations within each loop of the lumenal domain but did not find mutants that were completely unresponsive to GGPP. When assessing the transmembrane domain and lumenal domain as two independent structures, we found that only the transmembrane domain responded to GGPP specifically in vitro. Our results suggest that GGPP binding occurs within the Hmg2 transmembrane domain and that the loops in the lumenal domain are required for transducing a mallosteric response to GGPP. Taken together, these data suggest a new model of Hmg2 regulation.

cell biology↗

bioRxiv2022

Maximizing CRISPRi efficacy and accessibility with dual-sgRNA libraries and optimal effectors

CRISPR interference (CRISPRi) enables programmable, reversible, and titratable repression of gene expression (knockdown) in mammalian cells. Initial CRISPRi-mediated genetic screens have showcased the potential to address basic questions in cell biology, genetics, and biotechnology, but wider deployment of CRISPRi screening has been constrained by the large size of single guide RNA (sgRNA) libraries and challenges in generating cell models with consistent CRISPRi-mediated knockdown. Here, we present next-generation CRISPRi sgRNA libraries and effector expression constructs that enable strong and consistent knockdown across mammalian cell models. First, we combine empirical sgRNA selection with a dual-sgRNA library design to generate an ultra-compact (1-3 elements per gene), highly active CRISPRi sgRNA library. Next, we rigorously compare CRISPRi effectors to show that the recently published Zim3-dCas9 provides the best balance between strong on-target knockdown and minimal nonspecific effects on cell growth or the transcriptome. Finally, we engineer a suite of cell lines with stable expression of Zim3-dCas9 and robust on-target knockdown. Our results and publicly available reagents establish best practices for CRISPRi genetic screening.

genomics↗

bioRxiv2020

Selective Targeting of Ras Mutant Cancers via a New Small Molecule

Mutations in the Ras family of oncogenes are implicated in 33% of human cancers, making Ras an intensely pursued target in drug discovery. As an alternative to direct pharmacological inhibition of Ras, we looked for sensitivities in RAS mutant cells. Using a small molecule screen in cell lines with mutations in Ras and its effector Raf, we discovered 249C as a Ras-mutant selective cytotoxic agent against a spectrum of RAS-mutant cancers. By combining CRISPR chemical-genetic screening, comparative profiling and chemoproteomics, we identified that 249C binds to a unique subunit on vacuolar (V)-ATPase with nanomolar affinity, inhibiting its biochemical activity and, unexpectedly, altering V-ATPase translocation in Ras-induced macropinocytosis. Via binding to V-ATPase, 249C prevents lysosomal acidification and inhibits autophagy and macropinocytosis pathways that several Ras-driven cancers rely on for survival. In characterizing 249Cs mechanism, we show that potency varies with the identity of the RAS driver mutation highlighting a mutant-specific dependence on autophagy and macropinocytosis. Indeed, 249C potently inhibits tumor growth without adverse side effects in a mouse xenograft model of KRAS-driven non-small cell lung cancer. These data establish proof-of-concept for targeting V-ATPase as a way to indirectly target specific Ras mutants, and provide a fundamental link between V-ATPase localization and specific Ras mutant tumor-related activity.

cancer biology↗

bioRxiv2020

High-content Imaging-based Pooled CRISPR Screens in Mammalian Cells

CRISPR (clustered regularly interspaced short palindromic repeats) -based gene inactivation provides a powerful means of linking genes to particular cellular phenotypes. CRISPR-based screening has mostly relied upon using large genomic pools of single guide RNAs (sgRNAs). However, this approach is limited to phenotypes that can be enriched by chemical selection or FACS sorting. Here, we developed a microscopy-based approach, which we name optical enrichment, to computationally select cells displaying a particular CRISPR-induced phenotype, mark them by photo-conversion of an expressed photo-activatable fluorescent protein, and then isolate the fluorescent cells using fluorescence-activated cell sorting (FACS). A plugin was developed for the open source software Manager to automate the phenotypic identification and photo-conversion of cells, allowing ~1.5 million individual cells to be screened in 8 hr. We used this approach to screen 6092 sgRNAs targeting 544 genes for their effects on nuclear size regulation and identified 14 bona fide hits. These results present a highly scalable approach to facilitate imaging-based pooled CRISPR screens.

cell biology↗

bioRxiv2019

Titrating gene expression with series of systematically compromised CRISPR guide RNAs

Biological phenotypes arise from the degrees to which genes are expressed, but the lack of tools to precisely control gene expression limits our ability to evaluate the underlying expression-phenotype relationships. Here, we describe a readily implementable approach to titrate expression of human genes using series of systematically compromised sgRNAs and CRISPR interference. We empirically characterize the activities of compromised sgRNAs using large-scale measurements across multiple cell models and derive the rules governing sgRNA activity using deep learning, enabling construction of a compact sgRNA library to titrate expression of [~]2,400 genes involved in central cell biology and a genome-wide in silico library. Staging cells along a continuum of gene expression levels combined with rich single-cell RNA-seq readout reveals gene-specific expression-phenotype relationships with expression level-specific responses. Our work provides a general tool to control gene expression, with applications ranging from tuning biochemical pathways to identifying suppressors for diseases of dysregulated gene expression.

genomics↗