Biology subjects

Ceroni, F.

Publications and source records attributed to Ceroni, F..

12 recordsLinked to original sources

bioRxiv2025

Quantitative profiling of millions of nucleotides reveals sequence-encoded interactions that govern plasmid propagation

Plasmids are central to modern biotechnology, especially therapeutic development, yet their propagation in Escherichia coli remains difficult to predict. Although expression-induced burden is well understood and can be mitigated, the impact of foreign DNA segments that do not function in bacteria on plasmid propagation and stability remains largely unknown. Here we developed a pooled, sequencing-based framework that performs quantitative profiling across millions of bases, enabling high-resolution assessment of plasmid fitness at scale and revealing cryptic, sequence-encoded interactions between foreign DNA elements and bacterial hosts. Promoter-like motifs, transcription factor binding site homology, and recombination-prone architectures emerge as major determinants of propagation efficiency, with context dependent effects demonstrating that plasmid behaviour arises from higher-order interactions between parts rather than isolated elements. Extending this framework, we introduce TRACE, a neural network model trained on degenerate sequence libraries that predicts plasmid propagation directly from sequence. TRACE generalises across plasmid architectures and can be fine-tuned on experimental datasets to improve predictions of manufacturability and host compatibility. These advances establish a generalisable, data-driven framework for understanding and designing host-aware plasmids, transforming plasmid production from an empirical process into a predictable property of DNA sequence.

synthetic biology↗

bioRxiv2025

STAMPS: Signal-peptide Transformer for Augmenting Mammalian Protein Secretion

While secretion plays a key role in the diverse applications of cell engineering, to date only a handful of mammalian signal peptides have been characterised in depth and systematic efforts to build novel variants remain sporadic. We present STAMPS (Signal-peptide Transformer for Augmenting Mammalian Protein Secretion), a generative, autoregressive transformer fine-tuned on [~]6,000 mammalian signal peptides to design de novo sequences that modulate and enhance secretion across proteins and hosts. We show that STAMPS can be used to identify candidate signal peptides that outperform the widely used IgG {kappa} light-chain leader (IgKL) when used to secrete EGFP in HEK293T and CHO cells, and hEPO in HEK293T cells. When incorporated in an industrial cell line development framework, STAMPS leads to the generation of signal peptides that yield [~]2.3-fold gain in secretion of a VHH-Fc compared to the internal industrial benchmark in CHO G22 cells, with the same candidates ranking highly in both CHO and HEK293T hosts. Sequence-to-function analysis highlights a longer, strongly hydrophobic core and a tightly positioned cleavage site as drivers of this strong performance. Together, these results establish data-driven, generative design of mammalian signal peptides as a practical route to tune and improve secretion for bioproduction and cell engineering applications.

synthetic biology↗

bioRxiv2025

Billion-Scale Deciphering of Human Gene Regulatory Grammar

Predicting how DNA sequence specifies gene expression remains a core challenge across regulatory genomics. Most predictive assays and models depend on native genomic DNA, constraining the full biochemical engineering space for assessing and designing new sequences. Here, we address this gap with a scalable experimental-computational platform that rapidly generates million-scale sequence-to-expression datasets that directly link degenerate sequences to their function in human cells. We built degenerate libraries of 200-bp promoter cassettes and performed pooled stable integration of up to 1012 unique constructs, enabling the curation of million-scale sequence-to-expression datasets by fluorescently sorting billions of human cells. Biophysical modeling of transcription-factor occupancy on the data using position weight matrices reveals a broad spectrum of correlations between factor abundance and expression levels, with some co-abundances reaching Pearsons r {approx} 0.99, consistent with cooperative and probabilistic regulation. Leveraging the dataset, we trained sequence-to-expression deep learning models that predict held-out expression with Pearson r {approx} 0.4, converge on shared sequence determinants, and agree strongly with each other (Pearsons r = 0.93), indicating reproducible sequence-expression relationships. Finally, with minimal retraining the models generalize to an independently generated dataset collected under distinct sorting conditions, transferring sequence rules across contexts. Our platform enables repeated, rapid studies and supports deeper mechanistic insight while providing baseline models for forward design of human regulatory elements, advancing prediction beyond genomic-DNA-anchored methods.

synthetic biology↗

bioRxiv2024

Design of an intracellular aptamer-based fluorescent biosensor to track burden in E. coli

Cell burden impacts the performance of engineered synthetic systems. For this reason, there is great interest toward the development of tools to track burden and improve biotechnology applications. Fluorogenic RNA aptamers are excellent candidates for live monitoring of burden because their production is expected to impose a negligible load on transcription resources. Here we characterise the performance of a library of aptamers when expressed from different promoters in E. coli. We find that aptamer relative performance is dependent on the promoter and the strain, and that, contrary to expectation, aptamer expression impacts host fitness. By selecting two of the aptamers with brighter output and lower impact, we then design an intracellular biosensor able to report on the activation of the burden response in engineered cells. The sensor developed here adds to the collection of tools available for burden mitigation and may support bioprocessing applications where improved host performance is sought.

synthetic biology↗

bioRxiv2024

Engineered Transcription Factor Binding Arrays for DNA-based Gene Expression Control in Mammalian Cells

Manipulating gene expression in mammalian cells is critical for cell engineering applications. Here we explore the potential of transcription factor (TF) recognition element arrays as DNA tools for modifying free TF levels in cells and thereby controlling gene expression. We first demonstrate proof-of-concept, showing that Tet TF-binding recognition element (RE) arrays of different lengths can tune gene expression and alter gene circuit performance in a predictable manner. We then open-up the approach to interface with any TF with a known binding site by developing a new method called Cloning Troublesome Repeats in Loops (CTRL) that can assemble plasmids with up to 256 repeats of any RE sequence. Transfection of RE array plasmids assembled by CTRL into mammalian cells show potential to modify host cell gene regulation at longer array sizes by sequestration of the TF of interest. RE array plasmids built using CTRL were demonstrated to target both synthetic and native mammalian TFs, illustrating the ability to use these tools to modulate genetic circuits and instruct cell fate. Together this work advances our ability to assemble repetitive DNA arrays and showcases the use of TF-binding RE arrays as a method for manipulating mammalian gene expression, thus expanding the possibilities for mammalian cell engineering.

synthetic biology↗

bioRxiv2024

Degradation Bottlenecks and Resource Competition in Transiently and Stably Engineered Mammalian Cells

Degradation tags, otherwise known as degrons, are portable sequences that can be used to alter protein stability. Here, we report that degron-tagged proteins compete for cellular degradation resources in engineered mammalian cells leading to coupling of the degradation rates of otherwise independently expressed proteins when constitutively targeted human degrons are adopted. By adopting inducible bacterial and plant degrons we also highlight how orthogonality and uncoupling of synthetic construct degradation from the native machinery can be achieved. We show the effect of this competition to be dependent on the context of the degrons where C-terminal degradation appears to impact competition the most across our tested settings. We then build a genomically integrated capacity monitor tagged with different degrons and confirm resource competition between genomic and transiently expressed DNA constructs. This work expands the characterisation of resource competition in engineered mammalian cells to degradation also including integrated systems, providing a framework for the optimisation of heterologous expression systems to advance applications in fundamental and applied biological research.

synthetic biology↗

bioRxiv2023

Mammalian cell characterisation by non-invasive plate reader assay

Automated and non-invasive mammalian cell analysis is currently lagging behind due to a lack of methods suitable for a variety of cell lines and applications. Here, we report the development of a high throughput non-invasive method for tracking mammalian cell growth and performance based on plate reader measurements. We show the method to be suitable for both suspension and adhesion cell lines, and we demonstrate it can be adopted when cells are grown under different environmental conditions. We establish that the method can inform on effective drug treatment to be used depending on the cell line considered, and that it can support characterisation of engineered mammalian cells over time. This work provides the scientific community with a novel approach to mammalian cell screening, also contributing to the current efforts towards high throughput and automated mammalian cell engineering.

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↗

bioRxiv2021

Genome-wide association analyses of individual differences in quantitatively assessed reading- and language-related skills in up to 34,000 people

The use of spoken and written language is a capacity that is unique to humans. Individual differences in reading- and language-related skills are influenced by genetic variation, with twin-based heritability estimates of 30-80%, depending on the trait. The relevant genetic architecture is complex, heterogeneous, and multifactorial, and yet to be investigated with well-powered studies. Here, we present a multicohort genome-wide association study (GWAS) of five traits assessed individually using psychometric measures: word reading, nonword reading, spelling, phoneme awareness, and nonword repetition, with total sample sizes ranging from 13,633 to 33,959 participants aged 5-26 years (12,411 to 27,180 for those with European ancestry, defined by principal component analyses). We identified a genome-wide significant association with word reading (rs11208009, p=1.098 x 10-8) independent of known loci associated with intelligence or educational attainment. All five reading-/language-related traits had robust SNP-heritability estimates (0.13-0.26), and genetic correlations between them were modest to high. Using genomic structural equation modelling, we found evidence for a shared genetic factor explaining the majority of variation in word and nonword reading, spelling, and phoneme awareness, which only partially overlapped with genetic variation contributing to nonword repetition, intelligence and educational attainment. A multivariate GWAS was performed to jointly analyse word and nonword reading, spelling, and phoneme awareness, maximizing power for follow-up investigation. Genetic correlation analysis of multivariate GWAS results with neuroimaging traits identified association with cortical surface area of the banks of the left superior temporal sulcus, a brain region with known links to processing of spoken and written language. Analysis of evolutionary annotations on the lineage that led to modern humans showed enriched heritability in regions depleted of Neanderthal variants. Together, these results provide new avenues for deciphering the biological underpinnings of these uniquely human traits.

genomics↗

bioRxiv2019

Disruption of Capn15 in mice leads to brain and eye deficits

The Small Optic Lobe (SOL) family of calpains are intracellular cysteine proteases that are expressed in the nervous system and play an important role in neuronal development in both Drosophila, where loss of this calpain leads to the eponymous small optic lobes, and in mouse and human, where loss of this calpain leads to eye anomalies. Some human individuals with biallelic variants in CAPN15 also have developmental delay and autism. However, neither the specific effect of the loss of the Capn15 protein on brain development nor the brain regions where this calpain is expressed in the adult is known. Here we show using small animal MRI that mice with the complete loss of Capn15 have smaller brains overall with larger decreases in the thalamus and subregions of the hippocampus. These losses are not seen in Capn15 conditional KO mice where Capn15 is knocked out only in excitatory neurons in the adult. Based on {beta}-galactosidase expression in an insert strain where lacZ is expressed under the control of the Capn15 promoter, we show that Capn15 is expressed in adult mice, particularly in neurons involved in plasticity such as the hippocampus, lateral amygdala and Purkinje neurons, and partially in other non-characterized cell types. The regions of the brain in the adult where Capn15 is expressed do not correspond well to the regions of the brain most affected by the complete knockout suggesting distinct roles of Capn15 in brain development and adult brain function.

neuroscience↗

bioRxiv2019

Growth defects and loss-of-function in synthetic gene circuits

Synthetic gene circuits perturb the physiology of their cellular host. The extra load on endogenous processes shifts the equilibrium of resource allocation in the host, leading to slow growth and reduced biosynthesis. Here we built integrated host-circuit models to quantify growth defects caused by synthetic gene circuits. Simulations reveal a complex relation between circuit output and cellular capacity for gene expression. For weak induction of heterologous genes, protein output can be increased at the expense of growth defects. Yet for stronger induction, cellular capacity reaches a tipping point, beyond which both gene expression and growth rate drop sharply. Extensive simulations across various growth conditions and large regions of the design space suggest that the critical capacity is a result of ribosomal scarcity. We studied the impact of growth defects on various gene circuits and transcriptional logic gates, which highlights the extent to which cellular burden can limit, shape and even break down circuit function. Our approach offers a comprehensive framework to assess the impact of host-circuit interactions in silico, with wide-ranging implications for the design and optimization of bacterial gene circuits.

synthetic biology↗

bioRxiv2017

Burden-driven feedback control of gene expression

Cells use feedback regulation to ensure robust growth despite fluctuating demands on resources and different environmental conditions. Yet the expression of foreign proteins from engineered constructs is an unnatural burden on resources that cells are not adapted for. Here we combined multiplex RNAseq with an in vivo assay to reveal the major transcriptional changes in two E. coli strains when a set of inducible synthetic constructs are expressed. We identified that native promoters related to the heat-shock response activate expression rapidly in response to synthetic expression, regardless of the construct. Using these promoters, we built a CRISPR/dCas9-based feedback regulation system that automatically adjusts synthetic construct expression in response to burden. Cells equipped with this general-use controller maintain capacity for native gene expression to ensure robust growth and as such outperform unregulated cells at protein yields in batch production. This engineered feedback is the first example of a universal, burden-based biomolecular control system and is modular, tuneable and portable.

synthetic biology↗