Biology subjects

Lorenzo, G.

Publications and source records attributed to Lorenzo, G..

6 recordsLinked to original sources

bioRxiv2026

Genome-Scale Codon Deoptimization Enables Attenuation of Rift Valley Fever Virus

Rift Valley Fever Virus (RVFV) is a mosquito-borne zoonotic pathogen responsible for severe disease in domestic and wild ungulates as well as humans, representing a major threat to livestock production and human public health. RVFV is endemic in many African countries and has the potential to spread to new geographical regions. Current vaccines have limitations in safety and efficacy, highlighting the need for strategies to develop new vaccines candidates. In this study, we explored the use of codon deoptimization (CD) as a novel attenuation approach for the development of live-attenuated vaccine (LAV) against RVFV. CD exploits the redundancy of the genetic code by replacing frequently used codons with synonymous, less-preferred codons, thereby reducing translational efficiency without altering the amino acid sequence. We recoded parts of the M and S genome segments of RVFV using the least frequently used codons in mammalian cells, ensuring complete preservation of protein functionality and immunogenicity. Using reverse genetics, we rescued a panel of recombinant (r)RVFV encoding codon-deoptimized S-segment NSs gene (rNScd), M-segment Gn/Gc genes (rMcd), or both (rMcd/NScd). These recombinant CD viruses were characterized in vitro in mammalian and insect cell lines and in vivo using wild-type and immunocompromised mice. Results demonstrated varying degrees of attenuation among the three CD rRVFV, with the one deoptimized in both viral segments, rMcd/NScd, as a promising LAV based on the safety profiles. This study provides proof of concept for the use of CD as a rational strategy to generate attenuated RVFV, for the development of next-generation vaccines against this zoonotic threat.

microbiology↗

bioRxiv2026

75 Years of Mathematical Oncology

Constructing a comprehensive overview of any scientific field requires accurate literature selection, yet conventional keyword-based searches are susceptible to false positives. This problem is magnified in growing or interdisciplinary fields such as mathematical modeling in oncology that contain a rich but heterogeneous body of literature. Here, a generalizable, context-enriched artificial intelligence pipeline based on large language models (LLMs) curates large scientific corpora according to a user-defined field: mathematical modeling in oncology (>35k publications). Benchmarking against expert evaluation demonstrates high accuracy (ROC AUC[~]0.95) and agreement with human judgement (correlation[~]0.68), outperforming zero-shot LLM curation Analysis of the curated corpus ([~]14k) suggests that Mathematical Oncology s distinct from either Systems Biology and Pharmacokinetics/Pharmacodynamics despite employing overlapping methods. Co-occurring citation network analysis defines nine research clusters focused on a range of applications including drug delivery, optimal control, stochastic modeling, tumor microenvironment, radiation, cancer evolution, and spatial multiscale modeling. Significance StatementA generalizable, context-enriched artificial intelligence pipeline accurately curates large scientific corpora Analysis of the curated dataset applied to the se of mathematics n oncology provides comprehensive view of mathematical modeling in oncology across 140 years, revealing its shift from fundamental cancer biology towards therapeutic modelling.

cancer biology↗

bioRxiv2025

Generation and characterization of an ovine cell line derived from peripheral blood and its potential use to study livestock and zoonotic viral infections

BackgroundMesenchymal stromal cells (MSCs) are a population of undifferentiated non-hematopoietic fibroblast-like cells isolated from several tissues with multipotent differentiation capacity in vitro. This study focused on the establishment and characterization of a mesenchymal stromal cell line derived from ovine peripheral blood mononuclear cells (PBMCs). MethodsMSC were isolated from ovine blood and used to develop a cell line. The characterization of the cell line to confirm its mesenchymal origin was carried out by different assays. First at all, cells were characterized by flow cytometry (FACS) using monoclonal antibodies specific for MSC and hematopoietic non-stromal cell surface antigens. Real-time quantitative PCR (RT-qPCR) was performed using gene primer pairs specific for hematopoietic and mesenchymal cell surface markers. In addition, we assayed the potential of the cell line to differentiate in vitro to other lineages such as osteoblasts and neurons and confirmed that by specific staining with Alizarin Red (AR) and RT-qPCR and immunofluorescence (IFA). Finally, we assayed the susceptibility of the cell line to various livestock, animal and human viruses. ResultsFACS and RT-qPCR analyses revealed that the ovine cell line expressed mesenchymal markers and was negative for hematopoietic markers assayed. MSC were able to differentiate to osteoblasts and neurons, these results were confirmed by quantitative analyses of AR staining and RT-qPCR and IFA assays. The cell line showed susceptibility to infection with all viruses assayed confirmed by IFA asssays. ConclusionsIn this work, we used isolated MSCs from peripheral blood to establish a new ovine cell line. The characterization and the osteogenic and neuronal differentiation carried out confirmed that the cell line had a mesenchymal stromal origin. In fact, the new established ovine cell line was permissive to all viruses studied in this work. The new sheep cell line could be a useful tool for isolating and characterizing viruses and studying virus-host interactions.

cell biology↗

bioRxiv2025

The hyper-attenuated RVFV 40Fp8 strain can be safely administered to pregnant ewes to protect them from a virulent challenge

In the present study, we evaluated the immunogenicity, safety and protective efficacy of the attenuated RVFV-40Fp8 strain in natural hosts (non-pregnant ewes) and in a highly susceptible host infection model such as pregnant ewes in the first third of pregnancy. Our results confirm the immunogenicity of 40Fp8 administration in non-pregnant and pregnant ewes, as well as the absence of foetal damage even after a high-dose vaccination regime in pregnant ewes. In addition, the ewes and their foetuses were protected against a virulent RVFV-56/74 strain challenge, as shown by comparative histopathological evaluation of tissue samples from vaccinated and non-vaccinated pregnant ewes. These results confirm the potential use of 40Fp8 as a RVF live-attenuated vaccine candidate and pave the way for further clinical developments.

microbiology↗

bioRxiv2024

Novel replication-competent reporter-expressing Rift Valley fever viruses for molecular studies

Rift Valley fever virus (RVFV) is a mosquito-borne zoonotic disease that causes severe disease in both domestic and wild ungulates and humans, making it a significant threat to livestock and public health. The RVFV genome consists of three single-stranded, negative-sense RNA segments differing in size: Small (S), Medium (M) and Large (L). Segment S encodes the virus nucleoprotein N and the virulence-associated factor non-structural (NSs) protein in opposite orientations, separated by an intergenic region (IGR). To overcome the current need of using secondary techniques to detect the presence of RVFV in infected cells, we used T7-driven polymerase plasmid-based reverse genetics to generate replication-competent recombinant (r)RVFV expressing Nanoluciferase (Nluc) or Venus fluorescent proteins. These reporter genes were used as valid surrogates to track the presence of RVFV in mammalian and insect cells. Notably, we explored the genome plasticity of RVFV and compared four different strategies by modifying the viral segment S in order to introduce the reporter gene foreign sequences. The reporter-expressing rRVFV were stable and able to replicate in cultured mammalian and insect cells, although to a lesser extent than the recombinant wild-type (WT) counterpart. Moreover, rRVFV expressing reporter genes were validated to identify neutralizing antibodies or compounds with antiviral activity. In vivo, all mice infected with the reporter-expressing rRVFV displayed an attenuated phenotype, although at different levels. These rRVFV expressing reporter genes provide a novel approach to better understand the biology and pathogenesis of RVFV, and represent an excellent biotechnological tool for developing new therapeutics against RVFV infections. IMPORTANCERift Valley fever virus (RVFV) is a mosquito-borne virus and zoonotic agent threat that can be deadly to domestic or wild ungulates, and humans. In this work, we used reverse genetics approaches to explore the genome plasticity of RVFV by generating a set of recombinant rRVFV that express fluorescent or luminescent proteins to track viral infection. All the generated reporter-expressing rRVFV were able to propagate in mammalian or insect cells, and in a mouse model of infection. Our studies may contribute to advances in research on RVFV and other bunyaviruses and pave the way for the development of novel vaccines and the identification of new antivirals for the prophylactic and therapeutic treatment, respectively, of RVFV infections.

microbiology↗

bioRxiv2021

Mathematical characterization of population dynamics in breast cancer cells treated with doxorubicin

The development of chemoresistance remains a significant cause of treatment failure in breast cancer. We posit that a mathematical understanding of chemoresistance could assist in developing successful treatment strategies. Towards that end, we have developed a model that describes the effects of the standard chemotherapeutic drug doxorubicin on the MCF-7 breast cancer cell line. We assume that the tumor is composed of two subpopulations: drug-resistant cells, which continue proliferating after treatment, and drug-sensitive cells, which gradually transition from proliferating to treatment-induced death. The model is fit to experimental data including variations in drug concentration, inter-treatment interval, and number of doses. Our model recapitulates tumor growth dynamics in all these scenarios (as quantified by the concordance correlation coefficient, CCC > 0.95). In particular, superior tumor control is observed with higher doxorubicin concentrations, shorter inter-treatment intervals, and a higher number of doses (p < 0.05). Longer inter-treatment intervals require adapting the model parameterization after each doxorubicin dose, suggesting the promotion of chemoresistance. Additionally, we propose promising empirical formulas to describe the variation of model parameters as functions of doxorubicin concentration (CCC > 0.78). Thus, we conclude that our mathematical model could deepen our understanding of the effects of doxorubicin and could be used to explore practical drug regimens achieving optimal tumor control.

cancer biology↗