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Biology subjects

Zandkarimi, F.

Publications and source records attributed to Zandkarimi, F..

3 recordsLinked to original sources

Colorectal cancer detection and treatment with engineered probiotics

Bioengineered probiotics enable new opportunities to improve colorectal cancer (CRC) screening, prevention and treatment strategies. Here, we demonstrate the phenomenon of selective, long-term colonization of colorectal adenomas after oral delivery of probiotic E. coli Nissle 1917 (EcN) to a genetically-engineered murine model of CRC predisposition. We show that, after oral administration, adenomas can be monitored over time by recovering EcN from stool. We also demonstrate specific colonization of EcN to solitary neoplastic lesions in an orthotopic murine model of CRC. We then exploit this neoplasia-homing property of EcN to develop early CRC intervention strategies. To detect lesions, we engineer EcN to produce a small molecule, salicylate, and demonstrate that oral delivery of this strain results in significantly increased levels of salicylate in the urine of adenoma-bearing mice, in comparison to healthy controls. We also assess EcN engineered to locally release immunotherapeutics at the neoplastic site. Oral delivery to mice bearing adenomas, reduced adenoma burden by [~]50%, with notable differences in the spatial distribution of T cell populations within diseased and healthy intestinal tissue, suggesting local induction of robust anti-tumor immunity. Together, these results support the use of EcN as an orally-delivered platform to detect disease and treat CRC through its production of screening and therapeutic molecules.

bioengineering↗

A cell state specific metabolic vulnerability to GPX4-dependent ferroptosis in glioblastoma

Glioma cells hijack developmental transcriptional programs to control cell state. During neural development, lineage trajectories rely on specialized metabolic pathways. However, the link between tumor cell state and metabolic programs is poorly understood in glioma. Here we uncover a glioma cell state-specific metabolic liability that can be leveraged therapeutically. To model cell state diversity, we generated genetically engineered murine gliomas, induced by deletion of p53 alone (p53) or with constitutively active Notch signaling (N1IC), a pathway critical in controlling cellular fate. N1IC tumors harbored quiescent astrocyte-like transformed cell states while p53 tumors were predominantly comprised of proliferating progenitor-like cell states. N1IC cells exhibit distinct metabolic alterations, with mitochondrial uncoupling and increased ROS production rendering them more sensitive to inhibition of the lipid hydroperoxidase GPX4 and induction of ferroptosis. Importantly, treating patient-derived organotypic slices with a GPX4 inhibitor induced selective depletion of quiescent astrocyte-like glioma cell populations with similar metabolic profiles.

cancer biology↗

Multimodal mass spectrometry imaging reveals single-cell metabolic states in mammalian liver

We have developed a powerful workflow to imaging endogenous metabolism in single cells on frozen tissue, allowing us to discover new cell subtypes in human liver. Performing spatially integrated multiomics in single cells within tissues is at the leading frontier in biology but has been prevented by technological challenges. We developed a critical new technology, cryogenic water cluster ion beam secondary ion mass spectrometry imaging ((H2O)n>28K-GCIB-SIMS)) at 1 {micro}m single-cell resolution. This allowed us to perform multi-modal mass spectrometry imaging (MSI) to detect metabolites, lipids, and proteins in single cells within functional liver zones and diverse cell types in the native tissue state. Our workflow utilizes the desorption electrospray ionization (DESI) mass spectrometry imaging (MSI) to build a reference map of metabolic heterogeneity and zonation across liver functional units. Then cryogenic (H2O)n>28K-GCIB-SIMS and C60-SIMS integrated metabolomics, lipidomic and proteomics, - characterizing the metabolic state in single cells on the same tissue section. We found for the first time that lipids and metabolites can classify liver metabolic zones and liver cell types beyond histological and protein-marker annotation. This provides a multi-modal workflow to define single-cell states in normal physiology and disease in mammalian tissue.

cell biology↗