Biology subjects

Ricci, D. P.

Publications and source records attributed to Ricci, D. P..

5 recordsLinked to original sources

bioRxiv2025

Rapid Antibody Fragment Production and Binding Analysis Using Cell-Free Protein Synthesis Combined with Fluorescence Correlation Spectroscopy

This study investigates the efficient development and production of single-chain variable fragments (scFvs) and antibody fragments (Fabs) using an E. coli-based cell-free protein synthesis system. Validation of the methodology was performed using a fluorescence correlation spectroscopy (FCS)-based assay to determine binding equilibrium constants (KD) between antibodies and the receptor binding domain (RBD) of SARS-CoV-2 Spike protein. An initial assessment employed two conventionally cell-produced anti-RBD antibodies. To optimize cell-free production, folding strategies were developed to enhance the solubility and yields of scFvs, including a two-stage refolding protocol that successfully recovered active proteins from misfolded precipitates. Fab fragments were also produced and characterized, with their binding properties analyzed to assess functionality. This study highlights the potential of cell-free systems for the rapid and efficient production of functional antibody fragments. The integration of advanced techniques, such as FCS-based kinetic measurements, underscores the versatility and applicability of cell-free platforms for antibody development and high-throughput screening. These findings offer a promising avenue for accelerating therapeutic antibody research and production. SIGNIFICANCE of WORKThis study highlights the transformative potential of integrating cell-free protein synthesis (CFPS) with fluorescence correlation spectroscopy (FCS) for the rapid and scalable production and characterization of functional antibody fragments. By leveraging an E. coli-based CFPS platform, we successfully designed and optimized the production of single-chain variable fragments (scFvs) compared to Fab fragments, addressing some common challenges of low solubility and yield. The development of a cost-efficient two-stage refolding strategy further enhanced the scalability and functionality of scFvs, enabling higher recovery of active proteins from the unfolded state. Additionally, FCS provided a sensitive, rapid method for accurately quantifying antigen-antibody binding kinetics across a range of affinities. This work establishes CFPS and FCS as versatile and complementary tools, offering a robust framework for accelerating antibody fragment development, particularly in time-sensitive scenarios like infectious disease outbreaks.

biophysics↗

bioRxiv2025

Synthetic communities as a model for determining interactions between a biofertilizer chassis organism and native microbial consortia

Biofertilizers are critical for sustainable agriculture since they can replace ecologically disruptive chemical fertilizers while improving the trajectory of soil and plant health. Yet, to continue improving deployment, the persistence of designer biofertilizers within native soil consortia must be elucidated and enhanced. Here, we describe a high-throughput, modular, and automation-friendly in vitro approach to screen for biofertilizer organism persistence within soil-derived consortia after co-cultivation with stable synthetic soil microbial communities (SynComs) obtained through a top-down cultivation process. We profiled [~]1200 SynComs isolated from various soil sources and cultivated in divergent media types, and detected significant phylogenetic diversity (e.g., Shannon index > 4) and richness (Observed richness > 400) across these communities. We observed high reproducibility in SynCom community structure from common soil and media types, which provided a testbed for assessing biofertilizer persistence within representative native consortia. Furthermore, we demonstrate the screening method described herein can be coupled with microbial engineering to efficiently identify soil-derived SynComs where an engineered biofertilizer organism (i.e. Bacillus subtilis) persists. Additionally, our approach enables an analysis of the ecological impact of B. subtilis inoculation on SynCom structure and profile alterations in community diversity and richness (or lack thereof) associated with the presence of a genetically modified model bacterium. Ultimately, this work establishes a modular pipeline that could be integrated into a variety of microbiology/microbiome-relevant workflows or related applications that would benefit from assessing persistence and interaction of a specific organism of interest with native consortia.

systems biology↗

bioRxiv2023

GENTANGLE: integrated computational design of gene entanglements

SummaryThe design of two overlapping genes in a microbial genome is an emerging technique for adding more reliable control mechanisms in engineered organisms for increased safety. The design of functional gene pairs is a challenging procedure and computational design tools are used to improve the efficiency to deploy successful designs in genetically engineered systems. GENTANGLE (Gene Tuples ArraNGed in overLapping Elements) is a high performance containerized pipeline for the computational design of two overlapping genes translated in different reading frames of the genome. This new software package can be used to design and test gene entanglements for microbial engineering projects using arbitrary sets of user specified gene pairs. Availability and ImplementationThe GENTANGLE source code and its submodules are freely available on GitHub at https://github.com/BiosecSFA/gentangle. The DATANGLE (DATA for genTANGLE) repository contains related data and results, and is freely available on GitHub at https://github.com/BiosecSFA/datangle. The GENTANGLE repository wiki contains detailed instructions on how to use the container and the different components of software and data, including reproducing the results. The code is licensed under the GNU Affero General Public License version 3 (https://www.gnu.org/licenses/agpl.html). Contactmartimartine1@llnl.gov and allen99@llnl.gov

bioinformatics↗

bioRxiv2023

Prolonging Genetic Circuit Stability through Adaptive Evolution of Overlapping Genes

The development of synthetic biological circuits that maintain functionality over application relevant timescales remains a significant challenge. Here, we employed synthetic overlapping sequences in which one gene is encoded or "entangled" entirely within an alternative reading frame of another gene. In this design, the toxin-encoding relE was entangled within ilvA, which encodes threonine deaminase, an enzyme essential for isoleucine biosynthesis. A functional entanglement construct was obtained upon modification of the ribosome binding site of the internal relE gene. Using this optimized design, we found that the selection pressure to maintain functional IlvA stabilized the production of burdensome RelE for over 130 generations, which compares favorably with the most stable kill-switch circuits developed to date. This stabilizing effect was achieved through a complete alteration of the mutational landscape such that mutations inactivating the entangled genes were disfavored. Instead, the majority of lineages accumulated mutations within the regulatory region of ilvA. By reducing baseline relE expression, these more benign mutations lowered circuit burden, which suppressed the accumulation of relE inactivating mutations, thereby prolonging kill-switch function. Overall, this work demonstrates the utility of sequence entanglement paired with an adaptive laboratory evolution campaign to increase the evolutionary stability of burdensome synthetic circuits.

synthetic biology↗

bioRxiv2022

Comprehensive analysis of kill switch toxins in plant-beneficial Pseudomonas fluorescens reveals drivers of lethality, stability, and escape

Kill switches provide a biocontainment strategy in which unwanted growth of an engineered microorganism is prevented by expression of a toxin gene. A major challenge in kill switch engineering is balancing evolutionary stability with robust cell killing activity in application relevant host strains. Understanding host-specific containment dynamics and modes of failure helps to develop potent yet stable kill switches. To guide the design of robust kill switches in the agriculturally relevant strain Pseudomonas fluorescens SBW25, we present a comparison of lethality, stability, and genetic escape of eight different toxic effectors in the presence of their cognate inactivators (i.e., toxin-antitoxin modules, polymorphic exotoxin-immunity systems, restriction endonuclease-methyltransferase pair). We find that cell killing capacity and evolutionary stability are inversely correlated and dependent on the level of protection provided by the inactivator gene. Decreasing the proteolytic stability of the inactivator protein can increase cell killing capacity, but at the cost of long-term circuit stability. By comparing toxins within the same genetic context, we determine that modes of genetic escape increase with circuit complexity and are driven by toxin activity, the protective capacity of the inactivator, and the presence of mutation-prone sequences within the circuit. Collectively, our study reveals that circuit complexity, toxin choice, inactivator stability, and DNA sequence design are powerful drivers of kill switch stability and valuable targets for optimization of biocontainment systems.

synthetic biology↗