Biology subjects

Mutaher, M.

Publications and source records attributed to Mutaher, M..

3 recordsLinked to original sources

bioRxiv2026

One-carbon metabolism sustains effector T cell function through cell-surface glycosylation

Folate is a driver of one-carbon metabolism that is essential in T cells. The cellular consequences of its deprivation in CD8+ T cells and impact on anti-tumor function are unknown. Single cell RNA-seq analysis of primary central nervous system lymphoma (PCNSL) patients' tumor samples revealed exhaustion in T cells with high folate metabolism gene expression signature. Functional genomics, metabolite profiling, and glycomics identified disrupted cell surface glycosylation as a major consequence of folate deprivation in CD8+ T cells. Mechanistically, folate deprivation reduced nucleotide sugar levels, perturbed glycosylation, and triggered the apoptotic unfolded protein response. Overexpressing folate transporters in adoptively transferred CD8+ T cells increased intratumoral T cell numbers and reduced exhaustion. Therefore, our data draw a mechanistic line between one-carbon metabolism, cell-surface glycosylation, and anti-tumor T cell function, and support a hypothesis that increased folate uptake can enhance CD8+ T cell function including ex vivo and in vivo CAR-T cells.

cell biology↗

bioRxiv2026

Discovery of Tcf7 regulators with clonally-resolved CRISPR screens identifies Trim28 as a mediator of CD8 T cell differentiation in tumors

Stem-like TCF7+ CD8 T cells sustain anti-tumor responses and support immune checkpoint blockade. We systematically identified regulators of this cell state using genome-wide CRISPR screens in primary T cells in vitro. Using random barcodes to link clonal relationships with guide identity and transcriptional states in single cells, we inferred differentiation trajectories and differentiation rates of CD8 T cells in tumors, while mitigating confounding clonal bias. We found that Trim28-deficient T cells in tumors were enriched in the TCF7+ cell state, depleted in cycling and terminal effector states, and uniquely generated a tissue-resident memory (TRM)-like state with increased chromatin accessibility at known TRM loci as well as repeat elements. Despite the increase in TCF7+ CD8 T cells, loss of Trim28 did not improve tumor control, likely because of reduced effector differentiation, highlighting the need for tuning the balance and dynamics of stem-like versus effector states for effective tumor clearance.

immunology↗

bioRxiv2026

A community machine learning challenge to predict the effects of gene perturbations on T cell differentiation for cancer immunotherapy

Perturbations of genes with functional importance in T cells could be used to change the distribution of CD8 T cell states to enhance anti-tumor functions for cancer immunotherapies. We launched a world-wide computational challenge to predict the effects of gene perturbations and to devise objective functions for prioritizing gene perturbations that lead to desired T-cell state distributions. We supported the challenge by generating a single-cell Perturb-seq dataset profiling the effect of knocking out 73 individual expert-defined genes in T cells transferred into a mouse melanoma model. We compared the top algorithms developed by participants, and found that performance was primarily determined by the prior data used for gene feature representation, with perturbational data derived features, proving most effective. Experimental validation of the top 61 genes nominated by the algorithms revealed that perturbation of Ndufv2 and Dimt1 reached the defined objective and biased T cell differentiation toward desired states.

bioinformatics↗