Biology subjects

Galletti, G.

Publications and source records attributed to Galletti, G..

7 recordsLinked to original sources

bioRxiv2026

A zebrafish leprosy model identifies interferon and plasminogen signaling as survival determinants in mycobacterial infection

Although many genes are associated with leprosy, a skin and nerve infection by Mycobacterium leprae, the function of most of these genes in infection remains unknown. This is partly due to a paucity of animal models that are genetically malleable and recapitulate features of the human disease. Zebrafish, a recent leprosy model, have human-like responses to M. leprae, including macrophage-mediated inflammation and neurodegeneration. We confirm this at the transcriptional level, using RNA sequencing (RNAseq) of chronic M. leprae infection of adult zebrafish. This identified regulated zebrafish orthologs of human leprosy-associated genes, including {beta}- and {gamma}-interferon, IL-6, IL-10, IL-4, and TNF superfamily members. Other regulated genes have not been previously associated with leprosy. Genes associated with tuberculoid leprosy (T-lep) were largely downregulated, while lepromatous leprosy (L-lep) genes were upregulated. Pathways relevant to leprosy, such as phagocytosis and antiviral responses, differed between early and late stages of infection. In infected rag1 mutant zebrafish, which lack T and B cells, T-lep genes were downregulated, suggesting that adaptive immunity is required for their expression. Key pathways and genes were validated by qPCR using zebrafish infection with M. marinum:PGL-1, a model pathogen that can express M. leprae genes. This system allowed for the identification of validated M. leprae-regulated genes that alter infection outcomes, by using multiplex CRISPR to simultaneously mutate many zebrafish genes. 17 genes were screened and 2 were identified that increased mortality infection: isg15 (interferon-stimulated gene 15) and serpine1 (plasminogen activator inhibitor-1). This work confirms that, in humans and zebrafish, type I interferon and plasminogen activation are required for survival of mycobacterial disease, and demonstrates that multiplex CRISPR can identify mediators of host defense in vivo.

microbiology↗

bioRxiv2026

Proteostasis sustains T cell differentiation potential and tumor-infiltrating lymphocyte function

Tumor-infiltrating lymphocytes (TIL) often fail to restrain tumor growth due to progressive differentiation to an exhausted state. In healthy tissues, tissue-resident memory T cells (TRM) maintain protection for years, and patient tumors that contain TIL with TRM features are associated with better prognosis. Proteomic and transcriptomic profiling of T cell populations identified proteostasis as a significant factor distinguishing TRM and progenitor-exhausted TIL from terminally-exhausted TIL, including loss of E3 ubiquitin ligases NEURL3, RNF149, and WSB1, with accumulation of unfolded proteins in spite of functional proteasome activity. Enforced expression of these ligases by TIL preserved stem-like TCF1+ populations and improved anti-tumor function, whereas their knockout impaired TIL and altered T cell differentiation in acute infection. Sustained ligase expression rescued accumulation of unfolded proteins in TIL and improved immunotherapy outcome in preclinical models, highlighting the critical role of proteostasis in TIL function and identifying new avenues for advancing cancer immunotherapy.

immunology↗

bioRxiv2026

The CD8 immgenT framework as a universal reference of mouse CD8 Tαβ cell differentiation states

Mouse CD8+ T cell differentiation has been studied extensively in models of infections and tumors, yet no unified framework spans the full spectrum of immunological contexts. Within the immgenT project, we profiled RNA, surface markers, and TCR clonotypes in conventional CD8+ T cells across >600 samples, spanning multiple perturbations, tissues, and timepoints. Twenty-one clusters across naive, effector, circulating memory, tissue-resident memory, progenitor-exhausted, and terminally-exhausted CD8+ T cell compartments emerged, with striking molecular convergence across acute and chronic infections, tumors, autoimmunity, aging, and homeostasis, illustrating that shared transcriptional states support protective or dysfunctional outcomes depending on developmental history and microenvironment. We validate immgenT as a comprehensive reference by integrating external datasets from conditions not represented in immgenT and by defining a flow cytometry panel spanning the CD8+ T cell landscape. Thus, immgenT-CD8 provides a molecular framework for harmonizing CD8+ T cell literature and clarifies relationships across diverse immune challenges.

immunology↗

bioRxiv2026

immgenT: A Comprehensive Reference of Convergent T-cell States in the Mouse

The immgenT collaborative project generated a comprehensive molecular atlas of T cells spanning virtually all mouse organs and disease states, profiling ~800,000 cells from 750 samples with RNA, 128-plex surface protein, and {beta}TCR sequence. Applying a deep generative model to joint RNA and protein data defined the landscape of T-cell states organized into eight lineages and 107 robust clusters, integrating similar cells from different contexts, and resolving prior nomenclatures. Analysis of effector molecules, transcription factors and modules showed that both immunological functions and regulatory programs are shared across cell states. This framework provides a stable, reusable reference, demonstrated by computationally integrating 16 external datasets from diverse biological contexts. A set of public web tools supports browsing of these data and mapping of any dataset onto the immgenT framework. These results propose a molecular classification of T cells organized around a set of shared states reused across immunological contexts.

immunology↗

bioRxiv2024

Functional Diversity of Memory CD8 T Cells is Spatiotemporally Imprinted

Tissue-resident memory CD8 T cells (TRM) kill infected cells and recruit additional immune cells to limit pathogen invasion at barrier sites. Small intestinal (SI) TRM cells consist of distinct subpopulations with higher expression of effector molecules or greater memory potential. We hypothesized that occupancy of diverse anatomical niches imprints these distinct TRM transcriptional programs. We leveraged human samples and a murine model of acute systemic viral infection to profile the location and transcriptome of pathogen-specific TRM cell differentiation at single-transcript resolution. We developed computational approaches to capture cellular locations along three anatomical axes of the small intestine and to visualize the spatiotemporal distribution of cell types and gene expression. TRM populations were spatially segregated: with more effector- and memory-like TRM preferentially localized at the villus tip or crypt, respectively. Modeling ligand-receptor activity revealed patterns of key cellular interactions and cytokine signaling pathways that initiate and maintain TRM differentiation and functional diversity, including different TGF{beta} sources. Alterations in the cellular networks induced by loss of TGF{beta}RII expression revealed a model consistent with TGF{beta} promoting progressive TRM maturation towards the villus tip. Ultimately, we have developed a framework for the study of immune cell interactions with the spectrum of tissue cell types, revealing that T cell location and functional state are fundamentally intertwined.

immunology↗

bioRxiv2019

Imatinib overrides taxane resistance by selective inhibition of novel CLIP1 variant obstructing the microtubule pore

Despite its widespread use, the majority of patients with gastric cancer (GC) will not respond to taxane chemotherapy due to resistance mechanisms. Here, we report the discovery of a novel truncated variant of the microtubule plus-end binding protein (+TIP) CLIP-170, hereafter CLIP-170S, whose expression is enriched in taxane resistant cell lines and patients with GC. To establish causation, we knocked-down (KD) CLIP-170S which completely reversed taxane resistance. Mass-spec proteomics and 5-RACE further showed that CLIP-170S lacked the first 150 amino acids, including the Cap-Gly motif required for microtubule (MT) plus-end localization. Mechanistically, we show that CLIP-170S was mislocalized from the MT plus-end to the MT lattice obstructing the MT pore surface site required for taxane entry into the MT lumen. Computational analysis of RNA-seq data from taxane-sensitive and resistant GC cell lines, predicted imatinib as the top candidate drug to overcome drug resistance. Imatinib treatment completely reversed taxane resistance, as predicted, and did so unexpectedly by selective depletion of CLIP-170S. Importantly, CLIP170S was found to be highly prevalent in tumor biopsies from patients with GC. Taken together, these data identify CLIP-170S as a novel, clinically prevalent +TIP variant that obstructs the MT pore and confers taxane resistance. The discovery of this previously unrecognized variant together with the computational discovery of Imatinib as a selective CLIP-170S inhibitor, implicate the MT pore in clinical taxane resistance and provide new therapeutic opportunities for treatment of GC and beyond.

cancer biology↗

bioRxiv2017

A New Big-Data Paradigm For Target Identification And Drug Discovery

Drug target identification is one of the most important aspects of pre-clinical development yet it is also among the most complex, labor-intensive, and costly. This represents a major issue, as lack of proper target identification can be detrimental in determining the clinical application of a bioactive small molecule. To improve target identification, we developed BANDIT, a novel paradigm that integrates multiple data types within a Bayesian machine-learning framework to predict the targets and mechanisms for small molecules with unprecedented accuracy and versatility. Using only public data BANDIT achieved an accuracy of approximately 90% over 2000 different small molecules - substantially better than any other published target identification platform. We applied BANDIT to a library of small molecules with no known targets and generated [~]4,000 novel molecule-target predictions. From this set we identified and experimentally validated a set of novel microtubule inhibitors, including three with activity on cancer cells resistant to clinically used anti-microtubule therapies. We next applied BANDIT to ONC201 - an active anti- cancer small molecule in clinical development - whose target has remained elusive since its discovery in 2009. BANDIT identified dopamine receptor 2 as the unexpected target of ONC201, a prediction that we experimentally validated. Not only does this open the door for clinical trials focused on target-based selection of patient populations, but it also represents a novel way to target GPCRs in cancer. Additionally, BANDIT identified previously undocumented connections between approved drugs with disparate indications, shedding light onto previously unexplained clinical observations and suggesting new uses of marketed drugs. Overall, BANDIT represents an efficient and highly accurate platform that can be used as a resource to accelerate drug discovery and direct the clinical application of small molecule therapeutics with improved precision.

pharmacology and toxicology↗