Biology subjects

Partipilo, G.

Publications and source records attributed to Partipilo, G..

8 recordsLinked to original sources

bioRxiv2026

Eggerthella lenta evades bacteriophage through reversible megabase-scale inversions of capsular polysaccharide gene clusters

Bacteriophages are a promising tool for microbiome editing, yet their development has been constrained by limited insights into bacteriophage-host interactions within their shared mammalian body habitat. We isolated a lytic phage {Phi}KL11 that efficiently targets a disease-associated member of the human gut microbiota, Eggerthella lenta, during in vitro growth. However, {Phi}KL11 selects for a pre-existing and reversible bacteriophage-resistant sub-population in mice. Long-read sequencing revealed a massive genomic inversion event, representing >50% of the E. lenta genome, enriched in response to bacteriophage infection. Transcriptomics linked this inversion to the altered expression of three capsular polysaccharide synthesis (CPS) gene clusters and transmission electron microscopy confirmed differential capsule production. Finally, we show that {Phi}KL11 has a broad host range attributable to CPS and other strain-variable genes. These findings suggest a previously unrecognized strategy for phage evasion in the gut, involving megabase-scale genomic inversions and reversible capsule variation driving phage resistance.

microbiology↗

bioRxiv2025

Shifts in the human gut microbiome during cancer chemotherapy are diet-dependent

Numerous studies have implicated both dietary intake and the human gut microbiome in colorectal cancer (CRC) treatment outcomes. However, little is known about how patients adjust their dietary intake during cancer chemotherapy or if these dietary changes contribute to treatment-associated alterations in the gut microbiome. We performed paired longitudinal diet and microbiome analysis during CRC treatment with oral fluoropyrimidines (NCT04054908) and validated key associations using cell culture assays. At each timepoint, diet was measured by averaging up to 3 consecutive days of 24-hour dietary records (NCI ASA24; 35 patients; 2.5{+/-}1.1 timepoints per patient), while microbiome composition was measured from stool (16S rRNA gene sequencing, metagenomics, qPCR; 40 patients; 5.6{+/-}1.4 timepoints per patient). Diet quality significantly decreased during chemotherapy. Carbohydrate and refined grain intake increased, accompanied by decreased consumption of fats, nuts and seeds, and fat-soluble micronutrients. Multiple individual dietary components were strongly linked to the gut microbiome. Decreases in theobromine intake correlated with decreases in overall microbial diversity and more gastrointestinal toxicities. Diet shifts partly explained changes in bacterial abundance during chemotherapy, including more severe depletion of Faecalibacterium prausnitzii in patients with decreased vitamin K1 intake. Changes in diet were correlated with multiple bacterial gene families involved in micronutrient metabolism and drug sensitivity. Increased copper intake was linked to decreased Fusobacterium nucleatum in patients and inhibited F. nucleatum in cell assays. Together, these data suggest that changes in diet during chemotherapy contribute to changes in gut bacterial diversity, taxonomic composition, and gene abundance. Our approach may generalize to other cancer therapies and emphasizes the need for collecting more robust dietary data in clinical microbiome studies.

microbiology↗

bioRxiv2024

A Linear Mixed Effects Model for Evaluating Synthetic Gene Circuits

A significant advancement in synthetic biology is the development of synthetic gene circuits with predictive Boolean logic. However, there is no universally accepted or applied statistical test to analyze the performance of these circuits. Many basic statistical tests fail to capture the predicted logic (OR, AND, etc.) and most studies neglect statistical analysis entirely. As synthetic gene circuits shift toward advanced applications, primarily in computing, biosensing, and human health, it is critical to standardize the statistical methods used to evaluate gate success. Here, we propose the application of a linear mixed effects model to analyze and quantify genetic Boolean logic gate performance. First, we analyzed 144 currently published Boolean logic gates for trends and used unsupervised machine learning (k-means clustering) to validate the statistical model. Next, we utilized the model to generate estimates for the fixed effect of the ON state, {beta}, as a general descriptor of the Boolean nature of a circuit and used Monte Carlo simulations to recommend sample sizes for evaluating gate performance. Finally, we examined {beta} as a holistic metric for circuit performance using a series of nested repressor OR gates with intentionally degraded performance. We observed a linear correlation between {beta} and the predicted translation rate, highlighting the use of {beta} for the forward design of new Boolean gates. In summary, we utilized a linear mixed effects model to describe synthetic gene circuits and determined that the fixed effect, {beta}, is an appropriate descriptor of gate behavior that can be used to statistically evaluate performance. Significance statementThere is no standard method for statistically evaluating the success of biological Boolean logic gates and common statistical tests are not used or incorrectly applied. We propose the use of a linear mixed effects model to estimate the value for {beta}, a parameter which describes the difference between ON and OFF gate states. A null hypothesis of {beta} = 0 can then be tested to determine if there is a statistically significant difference between the two states.

synthetic biology↗

bioRxiv2024

Single-Cell Phenotyping of Extracellular Electron Transfer via Microdroplet Encapsulation

Electroactive organisms contribute to metal cycling, pollutant removal, and other redox-driven environmental processes. Studying this phenomenon in high-throughput is challenging since extracellular reduction cannot easily be traced back to its cell of origin within a mixed population. Here, we describe the development of a microdroplet emulsion system to enrich EET-capable organisms. We validated our system using the model electroactive organism S. oneidensis and describe the tooling of a benchtop microfluidic system for oxygen-limited processes. We demonstrated enrichment of EET-capable phenotypes from a mixed wild-type and EET-knockout population. As a proof-of-concept application, bacteria were collected from iron sedimentation from Town Lake (Austin, TX) and subjected to microdroplet enrichment. We observed an increase in EET-capable organisms in the sorted population that was distinct when compared to a population enriched in a bulk culture more closely akin to traditional techniques for discovering EET-capable bacteria. Finally, two bacterial species, C. sakazakii and V. fessus not previously shown to be electroactive, were further cultured and characterized for their ability to reduce channel conductance in an organic electrochemical transistor (OECT) and to reduce soluble Fe(III). We characterized two bacterial species not previously shown to exhibit electrogenic behavior. Our results demonstrate the utility of a microdroplet emulsions for identifying putative EET-capable bacteria and how this technology can be leveraged in tandem with existing methods.

bioengineering↗

bioRxiv2023

Rewiring native post-transcriptional carbon regulators to build multi-layered genetic circuits and optimize engineered microbes for bioproduction

As the bioprocessing and synthetic biology spaces rapidly expand, post-transcriptional regulation is emerging as driver for maximizing signal response rate and for minimizing cost per protein within cells. Designing robust post-transcriptional control systems that have precise tunability and can achieve diverse regulatory outcomes are paramount to advance the field. Herein, we develop a new approach for engineered post-transcriptional control in bacteria by rewiring a native regulatory system in Escherichia coli, the Carbon Storage Regulatory (Csr) Network, to create tunable, complex genetic circuits. First, by co-opting native components of the Csr Network to regulate translation of a target mRNA transcript, we establish a Csr-regulated Buffer Gate. Next, by rationally engineering the interactions between our synthetic construct and the native components of the Csr Network, we expand our original design into a genetic toolbox of 12 Buffer Gates that achieve precise tunability across a 10-fold range of target gene expression. Subsequently, to further regulatory capabilities using this approach, we develop a Csr-regulated NOT Gate through engineering a Csr-activated sequence into our synthetic constructs. We then build upon the Csr Buffer and Not Gates to create post-transcriptional dual input Boolean OR, NOR, AND and NAND Logic Gates, as well as a genetic pulse circuit. As a third step, we demonstrate portability of our Csr-regulated Buffer Gates into three industrially relevant bacteria by recapitulating Buffer Gate activity simply by leveraging the conserved homologous Csr Network in each species. Lastly, as a demonstration of downstream application, we apply our system to a proof-of-concept synthetic mevalonate pathway. Using our engineered constructs, we optimize mevalonate production in E. coli resulting in a three-fold increase in production relative to a transcriptionally controlled mevalonate pathway. As a whole, we establish a novel approach to rewire post-transcriptional regulatory networks for complex bacterial computation that can be utilized for efficient bioproduction in engineered microbes.

bioengineering↗

bioRxiv2023

A Hybrid Transistor with Transcriptionally Controlled Computation and Plasticity

Organic electrochemical transistors (OECTs) are ideal devices for translating biological signals into electrical readouts and have applications in bioelectronics, biosensing, and neuromorphic computing. Despite their potential, developing programmable and modular methods for living systems to interface with OECTs has proven challenging. Here we describe hybrid OECTs containing the model electroactive bacterium Shewanella oneidensis that enable the transduction of biological computations to electrical responses. Specifically, we fabricated planar p-type OECTs and demonstrated that channel de-doping is driven by extracellular electron transfer (EET) from S. oneidensis. Leveraging this mechanistic understanding and our ability to control EET flux via transcriptional regulation, we used plasmid-based Boolean logic gates to translate biological computation into current changes within the OECT. Finally, we demonstrated EET-driven changes to OECT synaptic plasticity. This work enables fundamental EET studies and OECT- based biosensing and biocomputing systems with genetically controllable and modular design elements.

bioengineering↗

bioRxiv2021

Transcriptional Regulation of Synthetic Polymer Networks

Individual cells direct non-equilibrium processes through coordinated signal transduction and gene expression, allowing for dynamic control over multicellular, system-wide behavior. This behavior extends to remodeling the extracellular polymer matrix that encases biofilms and tissues, where constituent cells dictate spatiotemporal network properties including stiffness, pattern formation, and transport properties. The majority of synthetic polymer networks cannot recreate these phenomena due to their lack of autonomous centralized actuators (i.e., cells). In addition, non-living polymer networks that perform computation are generally restricted to a few inputs (e.g., light, pH, enzymes), limiting the logical complexity available to a single network chemistry. Toward synergizing the advantages of living and synthetic systems, engineered living materials leverage genetic and metabolic programming to establish control over material-wide properties. Here we demonstrate that a bacterial metal respiration mechanism, extracellular electron transfer (EET), can control metal-catalyzed radical cross-linking of polymer networks. Linking metabolic electron flux to a synthetic redox catalyst allows dynamic, tunable, and predictable control over material formation and bulk polymer network mechanics using genetic circuits. By programming key EET genes with transcriptional Boolean logic, we rationally design computational networks that sense-and-respond to multiple inputs in biological contexts. Finally, we capitalize on the wide reactivity of EET and redox catalyses to predictably control another class of living synthetic materials using copper(I) alkyne-azide cycloaddition click chemistry. Our results demonstrate the utility of EET as a bridge for controlling abiotic materials and how the design rules of synthetic biology can be applied to emulate physiological behavior in polymer networks.

synthetic biology↗

bioRxiv2021

Extracellular Electron Transfer Enables Cellular Control of Cu(I)-catalyzed Alkyne-Azide Cycloaddition

Extracellular electron transfer (EET) is an anaerobic respiration process that couples carbon oxidation to the reduction of metal species. In the presence of a suitable metal catalyst, EET allows for cellular metabolism to control a variety of synthetic transformations. Here, we report the use of EET from the model electroactive bacterium Shewanella oneidensis for metabolic and genetic control over Cu(I)-catalyzed Alkyne-Azide Cycloaddition (CuAAC). CuAAC conversion under anaerobic and aerobic conditions was dependent on live, actively respiring S. oneidensis cells. In addition, reaction progress and kinetics could be further manipulated by tailoring the central carbon metabolism of S. oneidensis. Similarly, CuAAC activity was dependent on specific EET pathways and could be manipulated using inducible genetic circuits controlling the expression of EET-relevant proteins including MtrC, MtrA, and CymA. EET-driven CuAAC also exhibited modularity and robustness in ligand tolerance and substrate scope. Furthermore, the living nature of this system could be exploited to perform multiple reaction cycles without requiring regeneration, something inaccessible to traditional chemical reductants. Finally, S. oneidensis enabled bioorthogonal CuAAC membrane labelling on live mammalian cells without affecting cell viability, suggesting that S. oneidensis can act as a dynamically tunable biocatalyst in complex environments. In summary, our results demonstrate how EET can expand the reaction scope available to living systems by enabling cellular control of CuAAC.

bioengineering↗