Biology subjects

Garcia-Diaz, P.

Publications and source records attributed to Garcia-Diaz, P..

3 recordsLinked to original sources

bioRxiv2026

A network of bZIP transcription factors and inhibitors enforces differentially proliferative and cytotoxic states in T cells

The bZIP family of transcription factors (TFs) plays a central role in regulating T-cell exhaustion. Their complex dimeric interactions obscure the roles of individual members, which genetic knockout or overexpression alone poorly resolve. Here, we use overexpression of full-length bZIP family TFs alongside genetically encoded, protein-based inhibitors to probe the effect of increased or decreased bZIP TF activity on CAR T-cell expansion under exhausting conditions. Enrichment of inhibitors of pro-exhaustion TFs (CREM, NFIL3) illustrated the utility of this approach. The screen enriched full-length TFs of established anti-exhaustion relevance and identified underappreciated bZIP TFs such as BATF2. Detailed comparison of several bZIP TFs and inhibitors revealed distinct effects on proliferation, persistence, and cytotoxicity. We investigated combinations of pro-cytotoxic JUN, pro-proliferative BATF2, and a novel inhibitor (AEL-CREM) of pro-dysfunction CREM. Distinct pairs were more advantageous for maintenance of cytotoxicity or proliferation, revealing relationships between BATF2, JUN-, and CREB1-family bZIPs. Using a combination of epistasis, transcriptome, proteome, and AP-MS interactome analyses of BATF2 and AEL-CREM, we discovered functional overlap in their inhibition of pro-dysfunction CREB1-family activity, potentially driven by unexpected binding of CREB1-family members by overexpressed BATF2. Their function diverged in BATF2's early promotion of pro-proliferation AP-1 activity and later physical and functional interactions with BACH2, contributing to persistence. These findings were mirrored in murine chronic viral infection and syngeneic tumor models, where BATF2 or AEL-CREM overexpression were notably pro-proliferative and anti-exhaustion. Together, these results illuminate new connections and functional roles enabled by bZIP family perturbations, with implications for modulating T-cell state.

immunology↗

bioRxiv2026

Sense-and-response to intracellular signaling via nucleocytoplasmic localization control of a synthetic transcription factor platform

Many therapeutically relevant signaling pathways are sensed inside the cell, yet a modular synthetic biology platform for responding to intracellular signaling at the post-translational level is lacking. Signaling pathways control the nuclear localization and activity of native transcription factors via phosphorylation of nuclear localization/export or cytoplasmic anchor sequences. Here, we apply this concept to develop a platform of nucleocytoplasmic localization tags (NCtags) that control the nuclear translocation of a synthetic transcription factor (synTF) for transgene induction in engineered cells. We identify human-based synTF components that are basally cytoplasmic and induce transgenes under the control of NCtags with minimal background. We demonstrate the modular nature of this platform through transcriptional reporter induction in response to a calcium-inducible NFAT-derived NCtag, and development of novel NCtags responsive to hyperosmolarity, cAMP, or logical combinations of cAMP and calcium. Multiple factors in the tumor microenvironment elevate cAMP in T cells, leading to reduced function. We demonstrate that NCtag-synTF fusions expressed in T cells can respond to endogenous sources of cAMP or calcium in breast cancer spheroids to induce transgene expression. Our use of human components and an all-in-one lentiviral vector encoding the NCtag-synTF-transgene system establishes this as a novel platform for sense-and-response inside therapeutic cells.

synthetic biology↗

bioRxiv2020

Modeling CRISPR gene drives for suppression of invasive rodents

Invasive rodent populations pose a threat to biodiversity across the globe. When confronted with these new invaders, native species that evolved independently are often defenseless. CRISPR gene drive systems could provide a solution to this problem by spreading transgenes among invaders that induce population collapse. Such systems might be deployed even where traditional control methods are impractical or prohibitively expensive. Here, we develop a high-fidelity model of an island population of invasive rodents that includes three types of suppression gene drive systems. The individual-based model is spatially explicit and allows for overlapping generations and a fluctuating population size. Our model includes variables for drive fitness, efficiency, resistance allele formation rate, as well as a variety of ecological parameters. The computational burden of evaluating a model with such a high number of parameters presents a substantial barrier to a comprehensive understanding of its outcome space. We therefore accompany our population model with a meta-model that utilizes supervised machine learning to approximate the outcome space of the underlying model with a high degree of accuracy. This enables us to conduct an exhaustive inquiry of the population model, including variance-based sensitivity analyses using tens of millions of evaluations. Our results suggest that sufficiently capable gene drive systems have the potential to eliminate island populations of rodents under a wide range of demographic assumptions, but only if resistance can be kept to a minimal level. This study highlights the power of supervised machine learning for identifying the key parameters and processes that determine the population dynamics of a complex evolutionary system.

ecology↗