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bioRxiv2022

Mathematical Modeling Of Systems Biology

A modeling is a mathematical tool, like a microscope, which allows consequences to logically follow from a set of assumptions by which a real world problem can be described by a mathematical formulation. It has become indispensable tools for integrating and interpreting heterogeneous biological data, validating hypothesis and identifying potential diagnostic markers. The modern molecular biology that is characterized by experiments that reveal the behaviours of entire molecular systems is called systems biology. A fundamental step in synthetic biology and systems biology is to derive appropriate mathematical model for the purposes of analysis and design. This manuscript has been engaged in the use of mathematical modeling in the Gene Regulatory System (GRN). Different mathematical models that are inspired in gene regulatory network such as Central dogma, Hill function, Gillespie algorithm, Oscillating gene network and Deterministic vs Stochastic modelings are discussed along with their codes that are programmed in Python using different modules. Here, we underlined that the model should describes the continuous nature of the biochemical processes and reflect the non-linearity. It is also found that the stochastic model is far better than deterministic model to calculate future event exactly with low chance of error.

systems biology↗

bioRxiv2020

In Silico Design and Analysis of Genetic Circuit-Based Whole-Cell Biosensors for Detecting Groundwater Contaminants

Contaminants of emerging concern (CEC) such as tetracycline, erythromycin, and salicylic acid in groundwater can seriously endanger the environment and human health due to their widespread and everlasting harmful effects. Thus, continuous monitoring of various CEC concentrations in groundwater is essential to ensure the safety, security, and biodiversity of natural habitats. CECs can be detected using whole-cell biosensors for environmental surveillance and monitoring purposes, as they provide a cheaper and more robust alternative to traditional and expensive analytical techniques. In this study, various genetic circuit designs are considered to model three biosensors using the genetic design automation (GDA) software, iBioSim. The genetic circuits were designed to detect multiple CECs, including atrazine, salicylic acid, and tetracycline simultaneously to produce quantitative fluorescent outputs. The biosensor responses and the viability of the genetic circuit designs were further analysed using ODE-based mathematical simulations in iBioSim. The designed circuits and subsequent biosensor modelling presented here, thus, not only show the usefulness and importance of GDA tools, but also highlight their limitations and shortcomings that need to overcome in the future; thereby, providing a practical guidance for further improvement of such tools, so that they can be more effectively and routinely used in synthetic biology research.

synthetic biology↗

bioRxiv2021

A Biosensor for Detection of Indole Metabolites

The lack of diverse health-related biosensors limits the progress towards our understanding of how the microbiome metabolism impacts health. Microbially produced indole-3-aldehyde (I3A) has been associated with reducing inflammation in diseases such as ulcerative colitis by stimulating the aryl hydrocarbon receptor (AhR) pathway. We mined the protein database for gut microbiome metabolites sensors and developed a biosensor for I3A. We engineered E. coli embedded with a single plasmid carrying a chimeric two-component system that detects I3A. Our I3A receptor characterization identified residues that contribute to the sensors high specificity in a range of 0.1-10 {micro}M. The I3A biosensor opens the door to sensing indole metabolites produced at the host-microbe interface and provides new parts for synthetic biology applications.

synthetic biology↗

bioRxiv2025

Biomanufacturability of Squid Ring Teeth Protein Library via Orthogonal High-Throughput Screening

Structural proteins are valued by materials engineers for their mechanical properties, chemical functionalities, and biodegradability. Several studies focus on high-throughput screening of structural proteins, which is crucial for understanding and improving proteins by analyzing entire sequence spaces, as demonstrated in directed evolution. A major challenge is the poor biomanufacturability of recombinant structural proteins, often due to toxicity issues (e.g., aggregation, cell stress, inclusion bodies) limiting yield. High-throughput screening can help solve these issues and improve the biomanufacturability of structural proteins. Based on naturally observed squid ring teeth proteins, we introduce a structural protein library, enabling us to explore a broad sequence space. We selected 33 amino acid fragments with four repeats from six different native squid species, creating a recombinant protein library of about 1.2 million variants (i.e., 334). We demonstrated an orthogonal screening method that combines fluorescent- assisted cell sorting (FACS) and fluorescent microcapillary-array-based screening to establish correlations from genotype to single cells and ensembles. This optical high-throughput approach enables screening across the spectrum from individual cells to groups, facilitating the enrichment of desired clones. Our workflow distinguishes between expression and growth traits, supporting systematic genetic design studies focused on biomanufacturability. We observed that brighter clones tend to contain self-similar sequences (i.e., perfect repeats of fragments), whereas dimmer clones in the library have less similarity (i.e., imperfect repeats). The ability to screen large structural protein libraries not only accelerates research and development but also creates new opportunities for materials research and advanced biotechnological processes, underscoring its importance in modern synthetic biology.

synthetic biology↗

bioRxiv2025

Vesicle-templated self-assembly of freestanding multi-μm DNA shells

In the quest to create increasingly complex synthetic cell-mimicking systems, a wide range of DNA nanostructures have been developed to coat, permeabilize, sculpt, or otherwise functionalize lipid vesicles. In a complementary strategy, DNA architectures have been used as scaffolds to direct the growth of lipid membrane vesicles. Here we introduce a simple and broadly applicable method to realize freestanding, membrane-mimicking DNA shells: DNA shells are first assembled on the outer surface of giant unilamellar vesicles and then liberated by surfactant-mediated liposome removal. The resulting structures faithfully retain the geometry of their membrane template. We demonstrate the approach with two distinct classes of DNA tectons: a complex barrel-shaped DNA origami with programmable inter-subunit interactions, and a simple nanostar-inspired motif composed of only eleven oligonucleotides. The site-specific addressability of the former enable the rational design of binding interfaces, as demonstrated by controlled multilayer formation. The success of both strategies underscores the generality of our approach and the feasibility of creating shell-like compartments from different DNA architectures. This method enables the construction of tunable, DNA-only containers spanning the size range of eukaryotic cells, offering a fundamentally new type of compartmentalization for bottom-up synthetic biology.

synthetic biology↗

bioRxiv2021

Directed evolution of colE1 plasmid replication compatibility: a fast tractable tunable model for investigating biological orthogonality.

Plasmids of the ColE1 family are among the most frequently used plasmids in molecular biology. They were adopted early in the field for many biotechnology applications, and as model systems to study plasmid biology. The mechanism of replication of ColE1 plasmids is well understood, involving the interaction between a plasmid-encoded sense-antisense gene pair (RNAI and RNAII). Because of its mechanism of replication, bacterial cells cannot maintain two different plasmids with the same origin, with one being rapidly lost from the population - a process known as plasmid incompatibility. While mutations in the regulatory genes RNAI and RNAII have been reported to make colE1 plasmids more compatible, there has been no attempt to engineer compatible colE1 origins, which can be used for multi-plasmid applications and that can bypass design constrains created by the current limited plasmid origin repertoire available. Here, we show that by targeting sequence diversity to the loop regions of RNAI (and RNAII), it is possible to select new viable colE1 origins that are compatible with the wild-type one. We demonstrate origin compatibility is not simply determined by sequence divergence in the loops, and that pairwise compatibility is not an accurate guide for higher order interactions. We identify potential principles to engineer plasmid copy number independently from other regulatory strategies and we propose plasmid compatibility as a tractable model to study biological orthogonality. New characterised plasmid origins increase flexibility and accessible complexity of design for challenging synthetic biology applications where biological circuits can be dispersed between multiple independent genetic elements.

synthetic biology↗

bioRxiv2018

Tuning gene expression variability and multi-gene regulation by dynamic transcription factor control

Many natural transcription factors are regulated in a pulsatile fashion, but it remains unknown whether synthetic gene expression systems can benefit from such dynamic regulation. Using a fast-acting, light-responsive transcription factor in Saccharomyces cerevisiae, we show that dynamic pulsatile signals reduce cell-to-cell variability in gene expression. We then show that by encoding such signals into a single input, expression mean and variability can be precisely and independently tuned. Further, we construct a light-responsive promoter library and demonstrate how pulsatile signaling also enables graded multi-gene regulation at fixed expression ratios, despite differences in promoter dose-response characteristics. Pulsatile regulation can thus lead to highly beneficial functional behaviors in synthetic biological systems, which previously required laborious optimization of genetic parts or complex construction of synthetic gene networks.

synthetic biology↗

bioRxiv2018

Role of communication network topology in controlling microbial population in consortia

Engineering microbial consortia is an important new frontier for synthetic biology given its efficiency in performing complex tasks and endurance to environmental uncertainty. Most synthetic circuits regulate populational behaviors via cell-to-cell communications, which are affected by spatially heterogenous environments. Therefore, it is important to understand the limits on controlling system dynamics that are determined by interconnections among cell agents and provide a control strategy for engineering consortia. Here, we build a network model for a fractional population control circuit in two-strain consortia, and characterize the cell-to-cell communication network by topological properties, such as symmetry, locality and connectivity. Using linear network control theory, we relate the network topology to system outputs tracking performance. We analytically and numerically demonstrate that the minimum network control energy for accurate tracking depends on locality difference between two cell populations spatial distributions and how strongly the controller node contributes to communication strength. To realize a robust consortia, we can manipulate the communication network topology and construct strongly connected consortia by altering chemicals in environments. Our results ground the expected cell population dynamics in its spatially organized communication network, and inspire directions in cooperative control in microbial consortia.

synthetic biology↗

bioRxiv2014

Regulatory RNA design through evolutionary computation and strand displacement

The discovery and study of a vast number of regulatory RNAs in all kingdoms of life over the past decades has allowed the design of new synthetic RNAs that can regulate gene expression in vivo. Riboregulators, in particular, have been used to activate or repress gene expression. However, to accelerate and scale up the design process, synthetic biologists require computer-assisted design tools, without which riboregulator engineering will remain a case-by-case design process requiring expert attention. Recently, the design of RNA circuits by evolutionary computation and adapting strand displacement techniques from nanotechnology has proven to be suited to the automated generation of DNA sequences implementing regulatory RNA systems in bacteria. Herein, we present our method to carry out such evolutionary design and how to use it to create various types of riboregulators, allowing the systematic de novo design of genetic control systems in synthetic biology.

Synthetic Biology↗

bioRxiv2020

Automated Classification of Bacterial Cell Sub-Populations with Convolutional Neural Networks.

Quantification of phenotypic heterogeneity present amongst bacterial cells can be a challenging task. Conventionally, classification and counting of bacteria sub-populations is achieved with manual microscopy, due to the lack of alternative, high-throughput, autonomous approaches. In this work, we apply classification-type convolutional neural networks (cCNN) to classify and enumerate bacterial cell sub-populations (B. subtilis clusters). Here, we demonstrate that the accuracy of the cCNN developed in this study can be as high as 86% when trained on a relatively small dataset (81 images). We also developed a new image preprocessing algorithm, specific to fluorescent microscope images, which increases the amount of training data available for the neural network by 72 times. By summing the classified cells together, the algorithm provides a total cell count which is on parity with manual counting, but is 10.2 times more consistent and 3.8 times faster. Finally, this work presents a complete solution framework for those wishing to learn and implement cCNN in their synthetic biology work.

synthetic biology↗

bioRxiv2023

Self-driving laboratories to autonomously navigate the protein fitness landscape

Protein engineering has nearly limitless applications across chemistry, energy, and medicine, but creating new proteins with improved or novel functions remains slow, labor-intensive, and inefficient. In this work, we present the Self-driving Autonomous Machines for Protein Landscape Exploration (SAMPLE) platform for fully autonomous protein engineering. SAMPLE is driven by an intelligent agent that learns protein sequence-function relationships, designs new proteins, and sends designs to a fully automated robotic system that experimentally tests designed proteins and provides feedback to improve the agents understanding of the system. We deployed four SAMPLE agents with the goal of engineering glycoside hydrolase enzymes with enhanced thermal tolerance. Despite showing individual differences in their search behavior, all four agents quickly converged on thermostable enzymes that were at least 12 {degrees}C more stable than the starting sequences. Self-driving laboratories automate and accelerate the scientific discovery process and hold great potential for the fields of protein engineering and synthetic biology.

synthetic biology↗

bioRxiv2024

Synthetic gene circuits that selectively target RAS-driven cancers

Therapies targeting mutated RAS, the most frequently mutated oncogene in human cancers, could benefit millions of patients. Recently approved RAS inhibitors represent a breakthrough, but are limited to a specific KRASG12C mutation and prone to resistance. Synthetic gene circuits offer a promising alternative by sensing and integrating cancer-specific biomolecular inputs, including mutated RAS, to selectively express therapeutic proteins in cancer cells. A key challenge for these circuits is achieving high cancer selectivity to prevent toxicity in healthy cells. To address this challenge, we present a novel approach combining multiple RAS sensors into RAS-targeting gene circuits, which allowed us to express an output protein in cells with mutated RAS with unprecedented selectivity. We implemented a modular design strategy and modelled the impact of individual circuit components on output expression. This enabled cell-line specific adaptation of the circuits to optimize selectivity and fine-tune expression. We further demonstrate the targeting capabilities of the circuits by employing them in different RAS-driven cancer cells and provide evidence for their therapeutic potential by linking them to the expression of a clinically relevant output protein, which induced robust killing of cancer cells with mutated RAS. This work highlights the potential of synthetic gene circuits as a novel therapeutic strategy for RAS-driven cancers, advancing the application of synthetic biology in oncology.

synthetic biology↗

bioRxiv2025

Streptomyces Autoregulator Biosensors from Natural Product Cluster-Situated Regulators

The soil dwelling bacteria Streptomyces is an abundant producer of numerous anticancer, antifungal, and antibiotic compounds (i.e. Natural Products, NPs). The sophisticated cellular machinery required to produce NPs is frequently regulated by quorum-sensing systems, consisting of cluster situated regulators (CSRs), such as TetR-like repressors, and small-molecule autoregulator (AR) ligands. Only a small fraction of bioinformatically predicted quorum-sensing AR circuits have been experimentally determined, and fewer still have been engineered as inducible expression systems for synthetic biology. This research details the development of eight CSR-based AR biosensors and the synthetic routes to their AR ligands. Overall, the AR biosensors exhibit a range of maximum activation, AR affinity, and AR selectivity. We examined crosstalk between noncognate CSRs and ARs, as well as the ability of CSRs to regulate alternative operators. Additionally, we establish these biosensors can be cocultured with Streptomyces for rapid analysis of AR production. Finally, we demonstrate the CSR-based biosensor vectors can be combined to create orthogonal signaling systems in bacterial coculturing or multi-input genetic circuits. Longterm, these Streptomyces AR biosensors will contribute to the elucidation of small molecule quorum sensing circuits employed by Streptomyces as well as increasing the complexity of genetic circuits used in industrial or agricultural settings.

synthetic biology↗

bioRxiv2026

Genome Position Does Not Impact Transgene Expression Efficiency in the Ancient Red Alga Cyanidioschyzon merolae

The thermoacidophilic red alga Cyanidioschyzon merolae represents one of the simplest photosynthetic eukaryotes and an ancient divergent group in the primary endosymbiotic Viridiplantae. Because of its [~]16 Mbp genome, containing few introns, and capacity for transgene integration by homologous recombination, it is an emerging chassis for synthetic biology. However, genomic integration sites and scalable transformation methods have not been established to systematically investigate the effect of genome position on transgene expression. Here, we combined bioinformatic genome analysis, liquid-handling robotics, and assays of heterologous protein and metabolite production to establish a reproducible framework for nuclear genome engineering in C. merolae. We mapped and annotated 40 intergenic loci as candidate neutral sites across 16 out of 20 chromosomes and could validate 38 of them through robotic-assisted transformation. Reporter gene expression analysis revealed highly uniform expression at all integration sites across broad populations of transformants, indicating surprising minimal positional effects and transcriptional neutrality. The functional equivalence of these genomic landing pads was determined by expression of a heterologous isoprene synthase, and coupling algal photobioreactors to headspace analysis to quantify isoprene production driven by transgene expression from different integration sites. Single copy transgene integrants, regardless of genome position, exhibited comparable reporter signals and consequent isoprene production. Together, these results provide the first experimentally validated set of neutral integration sites in C. merolae and establish a high-throughput transformation protocol for its genetic engineering in the context of synthetic genome biology.

synthetic biology↗

bioRxiv2025

A Minimal Genetic Circuit for Cellular Anticipation

Living systems have evolved cognitive complexity to reduce environmental uncertainty, enabling them to predict and prepare for future conditions. Anticipation, distinct from simple prediction, involves active adaptation before an event occurs and is a key feature of both neural and aneural biological agents. Building on the moving average convergence-divergence principle from financial trend analysis, we propose an implementation of anticipation through synthetic biology by designing and evaluating experimentally testable minimal genetic circuits capable of anticipating environmental trends. Through deterministic and stochastic analyses, we demonstrate that these motifs achieve robust anticipatory responses under a wide range of conditions. Our findings suggest that simple genetic circuits could be naturally exploited by cells to prepare for future events, providing a foundation for engineering predictive biological systems.

synthetic biology↗

bioRxiv2023

Revealing the chassis-effect on a broad-host-range genetic switch and its concordance with interspecies bacterial physiologies

Broad-host-range synthetic biology is an emerging frontier that aims to expand our current engineerable domain of microbial hosts for biodesign applications. As more novel species are brought to "model status", synthetic biologists are discovering that identically engineered genetic circuits can exhibit different performances depending on the organism it operates within, an observation referred to as the "chassis-effect". It remains a major challenge to uncover which genome encoded and physiological biological determinants will underpin chassis effects that govern the performance of engineered genetic devices. In this study, we compared model and novel bacterial hosts to ask whether phylogenomic relatedness or similarity in host physiology is a better predictor of toggle switch performance. This was accomplished using comparative framework based on multivariate statistical approaches to systematically demonstrate the chassis-effect and characterize the performance dynamics of a genetic toggle switch operating within six Gammaproteobacteria. Our results solidify the notion that genetic devices are significantly impacted by host-context. Furthermore, we formally determined that hosts exhibiting more similar metrics of growth and molecular physiology also exhibit more similar toggle switch performance, indicating that specific bacterial physiology underpins measurable chassis effects. The result of this study contributes to the field of broad-host-range synthetic biology by lending increased predictive power to the implementation of genetic devices in less-established microbial hosts.

synthetic biology↗

bioRxiv2016

Regulation of cancer epigenomes with a histone-binding synthetic transcription factor

Chromatin proteins have expanded the mammalian synthetic biology toolbox by enabling control of active and silenced states at endogenous genes. Others have reported synthetic proteins that bind DNA and regulate genes by altering chromatin marks, such as histone modifications. Previously we reported the first synthetic transcriptional activator, the \"Polycomb-based transcription factor\" (PcTF), that reads histone modifications through a protein-protein interaction between the PCD motif and trimethylated lysine 27 of histone H3 (H3K27me3). Here, we describe the genome-wide behavior of PcTF. Transcriptome and chromatin profiling revealed PcTF-sensitive promoter regions marked by proximal PcTF and distal H3K27me3 binding. These results illuminate a mechanism in which PcTF interactions bridge epigenetic marks with the transcription initiation complex. In three cancer-derived human cell lines tested here, many PcTF-sensitive genes encode developmental regulators and tumor suppressors. Thus, PcTF represents a powerful new fusion-protein-based method for cancer research and treatment where silencing marks are translated into direct gene activation.

Synthetic Biology↗

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↗