Biology subjects

Luppino, F.

Publications and source records attributed to Luppino, F..

4 recordsLinked to original sources

bioRxiv2026

A microbial growth-coupled platform for in vivo interrogation of Rubisco oxygenase activity

Rubisco catalyzes the primary CO2-fixing reaction of the biosphere, yet its competing oxygenation reaction reduces net global carbon fixation and has resisted direct exploration in living cells. Here, we engineer an auxotrophic Escherichia coli strain in which 2-phosphoglycolate, the direct product of Rubisco oxygenation, becomes essential for growth, making bacterial fitness a quantitative proxy for oxygenation flux in vivo. This provides direct access to catalytic selectivity, something previously inaccessible to carboxylation-coupled assays. The platform enables screening of phylogenetically diverse Form II Rubisco and phosphoribulokinase (Prk) variants circumventing protein purification and extensive in vitro characterization. Adaptive laboratory evolution under oxygenation-selective pressure identified two mutations: Rubisco M115I genetically rebalances the in vivo carboxylation/oxygenation trade-off (resulting in 6-fold reduction in kcat,C), while Prk N216T improves overall flux without altering selectivity. This platform makes Rubiscos least-studied catalytic function selectable and evolvable in vivo, opening the carboxylation/oxygenation trade-off to systematic genetic dissection and engineering.

synthetic biology↗

bioRxiv2024

CIFR (Clone-Integrate-Flip-out-Repeat): a toolset for iterative genome and pathway engineering of Gram-negative bacteria

Advances in genome engineering enable precise and customizable modifications of bacterial species. Toolsets for metabolic engineering that exhibit broad-host compatibility are particularly valued owing to their portability. Tn5 transposon vectors have been widely used to establish random integrations of desired DNA sequences into bacterial genomes. However, the iteration of the procedure remains challenging because of the limited availability of selection markers. Here, we present CIFR, a mini-Tn5 integration system for iterative genome engineering. The pCIFR vectors incorporate attP and attB sites flanking an antibiotic resistance marker used to select for the insertion. Subsequent removal of these antibiotic determinants is facilitated by the Bxb1 integrase, and a user-friendly counter-selection marker, both encoded in auxiliary plasmids. Hence, CIFR delivers engineered strains harboring stable DNA insertions and free of any antibiotic resistance cassette, allowing for the reusability of the tool. The system was validated in Pseudomonas putida, Escherichia coli, and Cupriavidus necator, underscoring its portability across diverse industrially-relevant hosts. The CIFR toolbox was calibrated through combinatorial integrations of chromoprotein genes in P. putida, generating strains displaying a diverse color palette. Next, we introduced a carotenoid biosynthesis pathway in P. putida in a two-step engineering process, showcasing the potential of the tool for pathway balancing. The broad utility of the toolbox expands the synthetic biology toolkit for metabolic engineering, allowing for the construction of complex phenotypes, while opening new possibilities in bacterial genetic manipulations.

synthetic biology↗

bioRxiv2022

DeMAG predicts the effects of variants in clinically actionable genes by integrating structural and evolutionary epistatic features

Despite an increasing use of genomic sequencing in clinical practice, interpretation of rare genetic variants remains challenging even in well-studied disease genes, resulting in many patients with Variants of Uncertain Significance (VUSs). Computational Variant Effect Predictors (VEPs) are currently used to provide valuable evidence in variant classifications, but they often misclassify benign variants, contributing to potential misdiagnoses. Here, we developed Deciphering Mutations in Actionable Genes (DeMAG), a supervised classifier for interpreting missense variants in actionable disease genes with improved performance over existing VEPs (20% decrease of false positive rate). Our tool has balanced specificity (82%) and sensitivity (94%) on clinical data, and the lowest misclassification rate on putatively benign variants among evaluated tools. DeMAG takes advantage of a novel epistatic feature, the partners score, which is based on evolutionary and structural partnerships of residues as estimated by evolutionary information and AlphaFold2 structural models. The partners score as a general framework of epistatic interactions, can integrate not only clinical but functional information. We anticipate that our tool (demag.org) will facilitate the interpretation of variants and improve clinical decision-making.

genetics↗

bioRxiv2021

A combined transcriptional and dynamic roadmap of single human pancreatic endocrine progenitors reveals proliferative capacity and differentiation continuum

Basic helix-loop-helix genes, particularly proneural genes, are well-described triggers of cell differentiation, yet limited information exists on their dynamics, notably in human development. Here, we focus on Neurogenin 3 (NEUROG3), which is crucial for pancreatic endocrine lineage initiation. Using a double reporter to monitor endogenous NEUROG3 transcription and protein expression in single cells in 2D and 3D models of human pancreas development, we show peaks of expression for the RNA and protein at 22 and 11 hours respectively, approximately two-fold slower than in mice, and remarkable heterogeneity in peak expression levels all triggering differentiation. We also reveal that some human endocrine progenitors proliferate once, mainly at the onset of differentiation, rather than forming a subpopulation with sustained proliferation. Using reporter index-sorted single-cell RNA-seq data, we statistically map transcriptome to dynamic behaviors of cells in live imaging and uncover transcriptional states associated with variations in motility as NEUROG3 levels change, a method applicable to other contexts.

developmental biology↗