Biology subjects

Siciliano, V.

Publications and source records attributed to Siciliano, V..

8 recordsLinked to original sources

bioRxiv2026

p53 knockout drives stage-specific long non-coding RNA reprogramming during human neural differentiation and glioma organoid tumorigenesis.

Background: Long non-coding RNAs (lncRNAs) are emerging regulators of tumor initiation and progression through their effects on stemness, lineage commitment, and transcriptional plasticity. The contribution of lncRNA reprogramming during early p53-deficient gliomagenesis remains poorly understood. Methods: Human induced pluripotent stem cells (iPSCs) carrying a complete TP53 knockout were differentiated into neural progenitor cells (NPCs) and cerebral organoids. Bulk RNA sequencing was performed at multiple differentiation stages and compared with established glioblastoma cell lines (U87 and U118) to identify lncRNA expression changes associated with p53 loss and tumor-like transformation. Results: p53 deficiency induced a progressive and stage-specific remodeling of the lncRNA landscape, with the most pronounced transcriptional shift observed in 40-day NPCs. This late-stage profile partially overlapped with glioblastoma-like cell lines and was characterized by the upregulation of five lncRNAs enriched in both p53-deficient neural models and glioma cells. Principal component analysis showed that these lncRNAs clustered with tumor-associated samples and were strongly co-expressed with mitotic cell-cycle genes. In particular, LINC00973 and LINC01583 were highly expressed in primary glioblastoma datasets, while RP5-875H18.9 and RP11-1094H24.4 emerged as previously unrecognized glioma-associated transcripts. Conclusion: Loss of p53 drives stage-dependent lncRNA reprogramming during neural differentiation and promotes the emergence of glioma-associated transcriptional features. These findings identify candidate lncRNAs that may contribute to early gliomagenesis and represent potential biomarkers or therapeutic targets in glioblastoma.

cancer biology↗

bioRxiv2026

Engineering a PD-L1-sensing synthetic receptor for programmable macrophage-mediated phagocytosis

Macrophages are abundant immune cells within the tumor microenvironment with intrinsic phagocytic capabilities, yet their antitumor functions are frequently suppressed by inhibitory signals. Synthetic biology enables the rational design of ligand-responsive genetic circuits to reprogram immune cell behavior. Here, we report the engineering of a synthetic Notch-based receptor that detects PD-L1, an immune-checkpoint broadly expressed by cancer cells. Upon PD-L1 engagement, the circuit triggers programmable outputs, including expression of a fluorescent reporter or CV1-Fc, that locally blocks the CD47 "dont eat me" signal. We show that circuit activation scales with PD-L1 levels, partially attenuates PD-1/PD-L1 signaling, and that conditional CV1-Fc expression enhances engulfment of SKOV-3 ovarian cancer cells by THP-1-derived macrophages in vitro. Collectively, this work reframes PD-L1 from an end-point therapeutic target to a primary input signal for synthetic circuit activation and establishes a modular framework for engineering macrophage behaviour through spatially confined, ligand-responsive control. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/700810v1_ufig1.gif" ALT="Figure 1"> View larger version (60K): org.highwire.dtl.DTLVardef@1cbb391org.highwire.dtl.DTLVardef@7a0900org.highwire.dtl.DTLVardef@1e4f6d6org.highwire.dtl.DTLVardef@109838d_HPS_FORMAT_FIGEXP M_FIG Graphical abstract. A novel -PDL1 SNIPR receptor to program macrophage outputs. PD-L1 expressed on cancer cells is detected by -PD-L1 SNIPR-engineered macrophages, triggering release of the GAL4-VP64 transcription factor and activation of a programmable actuator. Circuit activation leads to customized outputs, including biosensing and enhanced macrophage phagocytosis via CD47 blockade, as well as immunomodulatory effects through interference with the PD-1/PD-L1 checkpoint axis. This sensor-actuator framework enables spatially confined and ligand-dependent reprogramming of macrophage function. C_FIG

synthetic biology↗

bioRxiv2025

Model-independent reorganization of translation in TDP-43 Amyotrophic Lateral Sclerosis

The RNA-binding protein TDP-43 is a major contributor and a pathological hallmark of Amyotrophic Lateral Sclerosis (ALS), yet how TDP-43 dysregulation mechanistically alters protein synthesis across neuronal compartments and disease models remains unclear. Here, we dissected TDP-43-driven translational alterations in both in vitro and in vivo TDP-43 models of ALS. Through ribosome and polysome profiling, computational, and biochemical analyses, we observed robust TDP-43-associated translational remodelling at cellular and subcellular resolution. Our findings reveal a conserved mechanism across models, characterized by enhanced ribosome recruitment on polysomes, elongation impairment, axonal downregulation and instability of TDP-43 target mRNAs and redistribution toward non-target transcripts. Notably, TDP-43 dysregulation alters ribosome dynamics and selectively impairs translation of TDP-43 target mRNAs, whilst favouring the translation of other transcripts. This process reflects a compensatory but maladaptive response to TDP-43-induced mRNA destabilization. Together, these data demonstrate that alterations in TDP-43 disrupts neuronal proteostasis through ribosome reorganization and loss of mRNA homeostasis, providing a unifying mechanistic framework for translational imbalance in ALS and revealing early molecular events that may underlie motor neuron vulnerability.

molecular biology↗

bioRxiv2025

Design of novel synthetic promoters to tune gene expression in T cells

Transcriptional control of transgene expression can be linked to dynamic changes in cellular states if this is accompanied by differential expression of transcription factors (TFs). Synthetic promoters (SPs) designed to respond to the desired TFs can provide this regulation with compactness, specificity, and orthogonality. T cells display differentially expressed TFs according to the functional state. In solid tumors, the highly immunosuppressive TME and the chronic exposure to antigens lead to a progression of T cells from a functional to a dysfunctional state known as exhaustion (Tex), in which their power against cancer cells is strongly compromised. Importantly, this transition is accompanied by a marked increase of several TFs, among other factors, that drive targeted genetic programs. Strategies to detect and mitigate Tex are extremely needed. Here, we design SPs that respond to TFs differentially expressed in activated and exhausted T cells to enable new classifiers of the functional/dysfunctional states. We developed a library of over 80 SPs responsive to 7 TFs. The SPs showed broad strength of activation of reporter genes or immunomodulatory molecules in HEK293 and Jurkat T cell lines. Moreover, using a transfer learning strategy we show SPs strength predictability. By combining SPs responding to different TFs, we created Boolean logic gates and implemented a feed-forward design that was previously shown to reduce noise in the OFF-state. Finally, as proof of principle, we demonstrate the dynamic activation of the NR4A2-responsive SP according to the T cell state in primary human CD8+ T cells. Collectively we present a sensing platform that provides a versatile tool to study and monitor the dynamic changes occurring in T cells. In perspective the biosensors coupled to therapeutic genes can be used to reprogram the TME and reinvigorate the T cell anti-tumoral functionality, preventing or reverting the exhausted phenotype. Graphical AbstractCreated with BioRender.com. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=108 SRC="FIGDIR/small/632034v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@136e147org.highwire.dtl.DTLVardef@22e5org.highwire.dtl.DTLVardef@f2e863org.highwire.dtl.DTLVardef@176c02c_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2024

Computational identification of small molecules for increased gene expression by synthetic circuits in mammalian cells

Engineering mammalian cells with synthetic circuits is leading the charge in next generation biotherapeutics and industrial biotech innovation. However, applications often depend on the cells productive capacity, which is limited by the finite cellular resources available. We have previously shown that cells engineered with incoherent feedforward loops (iFFL-cells) operate at higher capacity than those engineered with the open loop (OL). Here, we performed RNA-sequencing on cells expressing the iFFL and utilized DECCODE, an unbiased computational method, to match our data with thousands of drug-induced transcriptional profiles. DECCODE identified compounds that consistently enhance expression of both transiently and stably expressed genetic payloads across various experimental scenarios and cell lines, while also reducing external perturbations on integrated genes. Further, we show that drug treatment enhances the rate of AAV and lentivirus transduction, facilitating the prototyping of genetic devices for gene and cell therapies. Altogether, despite limiting intracellular resources is a pervasive, and strongly cell-dependent problem, we provide a versatile tool for a wide range of biomedical and industrial applications that demand enhanced productivity from engineered cells.

synthetic biology↗

bioRxiv2022

Resource-aware construct design in mammalian cells

Resource competition can be the cause of unintended coupling between co-expressed genetic constructs. Here we report quantification of the resource load imposed by different mammalian genetic components and identify construct designs with increased performance and reduced resource footprint. We use these to generate improved synthetic circuits and optimise the co-expression of co-transfected cassettes, shedding light on how this can be useful for bioproduction and biotherapeutic applications. This work provides the scientific community with a framework to take resource demand into consideration when designing mammalian constructs to achieve robust and optimised gene expression.

synthetic biology↗

bioRxiv2019

An endoribonuclease-based incoherent feedforward loop for decoupling resource-limited genetic modules

Synthetic biology has the potential to bring forth advanced genetic devices for applications in healthcare and biotechnology. However, accurately predicting the behavior of engineered genetic devices remains difficult due to lack of modularity, wherein a devices output does not depend only on its intended inputs but also on its context. One contributor to lack of modularity is competition among genes for shared cellular resources, such as those required for transcription and translation, which can induce coupling among otherwise independently-regulated genes. Here, we quantify the effects of resource sharing on engineered genetic systems in mammalian cells and develop an endoribonuclease-based incoherent feedforward loop (iFFL) to make gene expression levels robust to changes in resource availability. Our iFFL accurately controls gene expression levels in various cell lines and in the presence of significant resource sequestration by transcriptional activators. In addition to mitigating resource sharing, our iFFL also adapts gene expression to multiple log decades of DNA copy number variation, substantially improving upon previously-described miRNA-based iFFLs. Ultimately, our iFFL device will enable predictable, robust, and context-independent control of gene expression in mammalian cells.

synthetic biology↗

bioRxiv2019

Characterization, modelling and mitigation of gene expression burden in mammalian cells

Despite recent advances in genome engineering, the design of genetic circuits in mammalian cells is still painstakingly slow and fraught with inexplicable failures. Here we demonstrate that competition for limited transcriptional and translational resources dynamically couples otherwise independent co-expressed exogenous genes, leading to diminished performance and contributing to the divergence between intended and actual function. We also show that the expression of endogenous genes is likewise impacted when genetic payloads are expressed in the host cells. Guided by a resource-aware mathematical model and our experimental finding that post-transcriptional regulators have a large capacity for resource redistribution, we identify and engineer natural and synthetic miRNA-based incoherent feedforward loop (iFFL) circuits that mitigate gene expression burden. The implementation of these circuits features the novel use of endogenous miRNAs as integral components of the engineered iFFL device, a versatile hybrid design that allows burden mitigation to be achieved across different cell-lines with minimal resource requirements. This study establishes the foundations for context-aware prediction and improvement of in vivo synthetic circuit performance, paving the way towards more rational synthetic construct design in mammalian cells.

synthetic biology↗