Biology subjects

Khalil, A. S.

Publications and source records attributed to Khalil, A. S..

At least 19 recordsLinked to original sources

bioRxiv2026

Rational design of T-DNA vectors enables predictable, single-copy integration in Arabidopsis thaliana

Agrobacterium-mediated transformation is the dominant method for plant transgenesis, yet it frequently produces multi-copy, structurally complex T-DNA insertions associated with transgene silencing, unpredictable expression, and genome instability. Here, leveraging a high-throughput phenotypic reporter, we systematically dissect how T-DNA vector architecture, plasmid biology, and regulatory element choice shape transformation outcomes in Arabidopsis thaliana. We discover a pronounced trade-off between transformation efficiency and T-DNA copy number, uncovering the virulence enhancing overdrive sequence as a major determinant of this relationship. Guided by these insights, we engineered a new T-DNA vector that balances efficient transformation with predominantly single-copy integration. Additionally, we replaced viral elements, such as the widely used CaMV 35S promoter, with Arabidopsis-derived regulatory elements to minimise undesired enhancer effects, and developed a streamlined workflow for efficient T-DNA insertion mapping in the genome. Together, these advances form the T1 vector series, an Arabidopsis-optimised T-DNA vector system that enables clean, single-copy, and readily mappable transgene integration with predictable expression in the first generation after transformation.

plant biology↗

bioRxiv2026

Synthetic cell-cell adhesion provides benefits of proximity without diffusion-related costs

Multicellularity provides many advantages over unicellularity, but accessing those benefits with synthetic biology approaches is challenging due to potential tradeoffs. The same diffusion limitations that exclude toxins can limit nutrient transport, and small intercellular spaces that facilitate sharing also increase local competition. To isolate when and how cell aggregation, an essential feature of multicellularity, is useful, we compared yeast strains differing only in expression of a single adhesion gene. Unexpectedly, aggregates containing thousands of cells showed no signs of diffusion limitations, growing as well as unicellular strains in both rich and toxic media, likely because reversible cell adhesion allows cells to exchange positions. Aggregating cells also grew better than unicellular strains in the limiting carbon conditions expected to increase diffusion limitations. In mixtures of different genotypes, these benefits were specific to cells expressing the adhesion protein. Together, these results suggest key design principles for engineering aggregates: reformable bonds provide a mechanism to sidestep the fitness costs of increased size, and the benefits within such groups may arise more from nutrient sharing than from diffusion limitations.

synthetic biology↗

bioRxiv2025

Systematic characterization of existing and novel inducible transgenic systems in human pluripotent stem cells after prolonged differentiation

The ability to control transgene expression both temporally and quantitatively in human-relevant cells and tissues is a cornerstone of biomedical research. Additionally, precise transgene control is crucial for optimizing human cell-based gene therapies. Human pluripotent stem cells (hPSCs) have facilitated major advances in disease modeling and the potential for regenerative medicine. Still, they are significantly limited by the lack of inducible transgenic systems that avoid silencing but maintain robust inducibility after differentiation to defined cell lineages. Here we systematically characterize the leakiness, inducibility, and tunability of multiple existing and novel transgenic systems in hPSCs and differentiated macrophages and microglia. Notably, we report the application of a small molecule-mediated splicing switch (Xon) that allows for tunable transgene expression both before and after differentiation, without the large protein tags required for current state-of-the-art degron-based methods. We use Xon to achieve tight control of reporter genes, overexpression of multiple neurodegeneration-associated genes, and Cas9-mediated genome editing. We also characterize the current limitations of this system and describe approaches that can alleviate some of these limitations. By assessing multiple transgenic systems whose inducibility spans the transcriptional, post-transcriptional, and post-translational levels, we highlight and improve upon a major technical challenge that hinders basic, translational, and clinical research in physiological human-based systems.

bioengineering↗

bioRxiv2025

Human progenitor T-cell differentiation regulated by the mechanical resistance of thymus-mimetic extracellular matrices

Therapeutic T-cell engineering ex vivo from human hematopoietic stem cells (HSCs) focuses on recapitulating notch1-signaling and 4{beta}1-integrin-mediated adhesion within the thymic niche with supportive stromal cell feeder-layers or surface-immobilized recombinant protein-based engineered thymic niches (ETNs). The relevant Notch1-DLL-4 and 4{beta}1-integrin-VCAM-1 interactions are known to respond to mechanical forces that regulate their bond dissociation behaviors and downstream signal transduction, yet manipulating the mechanosensitive features of these key receptor-ligand interactions in thymopoiesis has been largely ignored in current ETN designs. Here, we demonstrate that human T-cell development from cord blood-derived CD34+ HSCs is regulated via molecular cooperativity in notch1 and integrin-mediated mechanotransduction. Mechanically confining interpenetrating network (IPN) hydrogel-based 3D cell culture comprised of collagen type I and alginate polysaccharides functionalized with DLL-4 and VCAM-1 is used as a model viscoelastic 3D ETN to manipulate human progenitor (pro)T-cell differentiation. This ETN enables orthogonal control of the mechanical and biomolecular features of the thymic niche, including thymopoietic ligand density, modulus, and viscoelastic properties (e.g., stress relaxation kinetics). We identify that soft, viscous matrices that enhance activation of the notch1-pathway, and subsequently notch1 intracellular domain (NICD) nuclear import sustain the T-cell development gene regulatory network during proT-cell differentiation. Conversely, stiff, elastic matrices inhibit HSC commitment to the T-lineage, and rather promotes Myeloid-cell differentiation. Our observations indicate mechanical reciprocity in signaling pathways indispensable to thymopoiesis, and highlights extracellular matrix mechanics as a variable in controlling hematopoietic stem cell fate decisions.

bioengineering↗

bioRxiv2025

Exploring C1 substrate cofeeding in Eubacterium limosum with AneVO, a low-cost anaerobic parallel bioreactor platform

Acetogenic bacteria have emerged as attractive biocatalysts for renewable biochemical production, using the highly efficient Wood-Ljungdahl pathway to convert a range of sustainable single-carbon (C1) feedstocks. The major challenge is their energy-constrained anaerobic lifestyle, which results in slow growth and limits the product spectrum. To overcome this limitation, here we investigate substrate co-metabolism in the acetogen Eubacterium limosum, cofeeding either carbon monoxide (CO) or glucose alongside the primary C1 substrate (methanol or formate). To increase experimental throughput, we developed AneVO, a parallel mini bioreactor system based on eVOLVER that enables benchtop anaerobic batch and fed-batch cultivation, along with continuous delivery of anaerobic gas blends. With all substrate pairs tested, E. limosum grew faster and reached 52-254% higher cell densities with cofeeding, while maintaining or improving the volumetric uptake rate of the main C1 substrate. Product formation also improved, with an increase in volumetric acetate productivity from glucose cofeeding of 2.2-fold with formate and 2.4-fold with methanol, and 3-fold from CO cofeeding with methanol. Together these results validate AneVO as a low-cost platform for convenient benchtop cultivation of strict anaerobic microbes in multiple growth modes, and present a strategy for enhancing C1 bioconversion rates in E. limosum, an emerging model acetogen.

microbiology↗

bioRxiv2023

Nanoscale Structural Mapping of Protein Aggregates in Live Cells Modeling Huntington's Disease

Protein aggregation, in the form of amyloid fibrils, is intimately correlated with many neurodegenerative diseases. Despite recent advances in structural biology, it remains challenging to acquire structural information of proteins in live cells. Tagging with fluorescent proteins, like green fluorescent protein (GFP), is routinely used for protein visualization. Yet, this method alone cannot provide detailed structural information on the protein system of interest, and tagging proteins has the potential to perturb native structure and function. Here, by fluorescence-detected as well as label-free scattering-based mid-infrared photothermal (MIP) microscopy, we demonstrate nanoscale mapping of secondary structure of protein aggregates in a yeast model of Huntingtons disease. We first used GFP as a highly sensitive photothermal reporter to validate {beta}-sheet enrichment in huntingtin (htt) protein aggregates. We then obtained label-free structural maps of protein aggregates. Our data showed that the fluorescent protein tag indeed perturbed the secondary structure of the aggregate, evident by a spectral shift. Live cell MIP spectroscopy further revealed the fine spatial distribution of structurally distinct components in protein aggregates, featuring a 246-nm diameter core highly enriched in {beta}-sheet surrounded by a [a]-helix-rich shell. Interestingly, this structural partition exists only in presence of the [RNQ+] prion, a prion that acts to facilitate the formation of other amyloid prions. Indeed, when htt is induced to aggregate in the absence of this prion ([rnq-] state), it forms non-toxic amyloid aggregates exclusively. These results showcase the potential of MIP for unveiling detailed and subtle structural information on protein systems in live cells. SignificanceProtein aggregation is a hallmark of neurodegenerative diseases, such as Huntingtons Disease. Understanding the nature of neurotoxic aggregates could lead to better therapeutic approaches. The limited progress in this direction is partly due to the lack of tools for extracting structural information in the physiological context of the aggregates. Here, we report a photothermally detected mid-infrared micro-spectroscopy technique able to dissect the secondary structure of aggregates of the huntingtin protein in live cells. We describe for the first time a nanoscale partition of secondary structures between {beta}-rich core and [a]-rich shell of the aggregates. This work demonstrates the potential of mid-infrared photothermal microscopy for structural and functional mapping of proteins in live cells.

biophysics↗

bioRxiv2023

Mapping the dynamics of epigenetic adaptation

A classical and well-established mechanism that enables cells to adapt to new and adverse conditions is the acquisition of beneficial genetic mutations. Much less is known about epigenetic mechanisms that allow cells to develop novel and adaptive phenotypes without altering their genetic blueprint. It has been recently proposed that histone modifications, such as heterochromatin-defining H3K9 methylation (H3K9me), normally reserved to maintain genome integrity, can be redistributed across the genome to establish new and potentially adaptive phenotypes. To uncover the dynamics of this process, we developed a precision engineered genetic approach to trigger H3K9me redistribution on-demand in fission yeast. This enabled us to trace genome-scale RNA and chromatin changes over time prior to and during adaptation in long-term continuous cultures. Establishing adaptive H3K9me occurs over remarkably slow time-scales relative to the initiating stress. During this time, we captured dynamic H3K9me redistribution events ultimately leading to cells converging on an optimal adaptive solution. Upon removal of stress, cells relax to new transcriptional and chromatin states rather than revert to their initial (ground) state, establishing a tunable memory for a future adaptive epigenetic response. Collectively, our tools uncover the slow kinetics of epigenetic adaptation that allow cells to search for and heritably encode adaptive solutions, with implications for drug resistance and response to infection.

genetics↗

bioRxiv2023

Deep neural networks for predicting single cell responses and probability landscapes

Engineering biology relies on the accurate prediction of cell responses. However, making these predictions is challenging for a variety of reasons, including the stochasticity of biochemical reactions, variability between cells, and incomplete information about underlying biological processes. Machine learning methods, which can model diverse input-output relationships without requiring a priori mechanistic knowledge, are an ideal tool for this task. For example, such approaches can be used to predict gene expression dynamics given time-series data of past expression history. To explore this application, we computationally simulated single cell responses, incorporating different sources of noise and alternative genetic circuit designs. We showed that deep neural networks trained on these simulated data were able to correctly infer the underlying dynamics of a cell response even in the presence of measurement noise and stochasticity in the biochemical reactions. The training set size and the amount of past data provided as inputs both affected prediction quality, with cascaded genetic circuits that introduce delays requiring more past data. We also tested prediction performance on a bistable auto-activation circuit, finding that our initial method for predicting a single trajectory was fundamentally ill-suited for multimodal dynamics. To address this, we updated the network architecture to predict the entire distribution of future states, showing it could accurately predict bimodal expression distributions. Overall, these methods can be readily applied to the diverse prediction tasks necessary to predict and control a variety of biological circuits, a key aspect of many synthetic biology applications.

synthetic biology↗

bioRxiv2023

Human Herpesvirus 8 ORF57 protein is able to reduce TDP-43 pathology: Network analysis Identifies Interacting Pathways

Aggregation of TAR DNA-binding protein 43kDa (TDP-43) is thought to drive the pathophysiology of ALS and some Frontotemporal dementias. TDP-43 is normally a nuclear protein that in neurons translocates to the cytoplasm and forms insoluble aggregates upon activation of the integrated stress response (ISR). Viruses evolved to control the ISR. In the case of Herpesvirus 8, the protein ORF57 acts to bind protein kinase R, inhibit phosphorylation of eIF2 and reduce activation of the ISR. We hypothesized that ORF57 might also possess the ability to inhibit aggregation of TDP-43. ORF57 was expressed in the neuronal SH-SY5Y line and its effects on TDP-43 aggregation characterized. We report that ORF57 inhibits TDP-43 aggregation by 55% and elicits a 2.45-fold increase in the rate of dispersion of existing TDP-43 granules. These changes were associated with a 50% decrease in cell death. Proteomic studies were carried out to identify the protein interaction network of ORF57. We observed that ORF57 directly binds to TDP-43 as well as interacts with many components of the ISR, including elements of the proteostasis machinery known to reduce TDP-43 aggregation. We propose that viral proteins designed to inhibit a chronic ISR can be engineered to remove aggregated proteins and dampen a chronic ISR.

neuroscience↗

bioRxiv2023

Long-term evolution of proliferating yeast cells using the eVOLVER platform

Experimental evolution using fast-growing unicellular organisms is a unique strategy for deciphering the principles and mechanisms underlying evolutionary processes as well as the architecture and wiring of basic biological functions. Over the past decade, this approach has benefited from the development of powerful systems for the continuous control of the growth of independently evolving cultures. While the first devices compatible with multiplexed experimental evolution remained challenging to implement and required constant user intervention, the recently-developed eVOLVER framework represents a fully automated closed-loop system for laboratory evolution assays. However, it remained difficult to maintain and compare parallel evolving cultures in tightly controlled environments over long periods of time using eVOLVER. Furthermore, a number of tools were lacking to cope with the various issues that inevitably occur when conducting such long-term assays. Here we present a significant upgrade of the eVOLVER framework, providing major modifications of the experimental methodology, hardware and software as well as a new standalone protocol. Altogether, these adaptations and improvements make the eVOLVER a versatile and unparalleled setup for long-term experimental evolution.

evolutionary biology↗

bioRxiv2023

Effects of Antibiotic Interaction on Antimicrobial Resistance Development in Wastewater

While wastewater is understood to be a critically important reservoir of antimicrobial resistance due to the presence of multiple antibiotic residues from industrial and agricultural runoff, there is little known about the effects of antibiotic interactions in the wastewater on the development of resistance. We worked to fill this gap in quantitative understanding of antibiotic interaction in constant flow environments by experimentally monitoring E. coli populations under subinhibitory concentrations of combinations of antibiotics with synergistic, antagonistic, and additive interactions. We then used these results to expand our previously developed computational model to account for the complex effects of antibiotic interaction. We found that while E. coli populations grown in additively interacting antibiotic combinations grew predictably according to the previously developed model, those populations grown under synergistic and antagonistic antibiotic conditions exhibited significant differences from predicted behavior. E. coli populations grown in the condition with synergistically interacting antibiotics developed less resistance than predicted, indicating that synergistic antibiotics may have a suppressive effect on antimicrobial resistance development. Furthermore E. coli populations grown in the condition with antagonistically interacting antibiotics showed an antibiotic ratio-dependent development of resistance, suggesting that not only antibiotic interaction, but relative concentration is important in predicting resistance development. These results provide critical insight for quantitatively understanding the effects of antibiotic interactions in wastewater and provide a basis for future studies in modelling resistance in these environments. ImportanceAntimicrobial resistance (AMR) is a growing global threat to public health expected to impact 10 million people by 2050, driving mortality rates globally and with a disproportionate effect on low- and middle-income countries. Communities in proximity to wastewater settings and environmentally contaminated surroundings are at particular risk due to resistance stemming from antibiotic residues from industrial and agricultural runoff. Currently, there is a limited quantitative and mechanistic understanding of the evolution of AMR in response to multiple interacting antibiotic residues in constant flow environments. Using an integrated computational and experimental methods, we find that interactions between antibiotic residues significantly affect the development of resistant bacterial populations.

bioengineering↗

bioRxiv2022

Cooperative assembly confers regulatory specificity and long-term genetic circuit stability

In eukaryotes, links in gene regulatory networks are often maintained through cooperative self-assembly between transcriptional regulators (TRs) and DNA cis-regulatory motifs, a strategy widely thought to enable highly specific regulatory connections to be formed between otherwise weakly-interacting, low-specificity molecular components. Here, we directly test whether this regulatory strategy can be used to engineer regulatory specificity in synthetic gene circuits constructed in yeast. We show that circuits composed of artificial zinc-finger TRs can be effectively insulated from aberrant misregulation of the host cell genome by using cooperative multivalent TR assemblies to program circuit connections. As we demonstrate in experiments and mathematical models, assembly-mediated regulatory connections enable mitigation of circuit-driven fitness defects, resulting in genetic and functional stability of circuits in long-term continuous culture. Our naturally-inspired approach offers a simple, generalizable means for building evolutionarily robust gene circuits that can be scaled to a wide range of host organisms and applications.

synthetic biology↗

bioRxiv2022

Development of a physiological insulin resistance model in human stem cell-derived adipocytes

Adipocytes are key regulatory cells of human metabolism, and their dysfunction in insulin signaling is central to metabolic diseases such as type II diabetes mellitus (T2D). However, the progression of insulin resistance that leads to T2D is still poorly understood. This limited understanding is due, in part, to the dearth of suitable models of insulin signaling in human adipocytes. Traditionally, in vitro adipocyte models fail to recapitulate in vivo insulin signaling, possibly due to exposure to supraphysiological nutrient and hormone conditions. Here, we have developed a sensitization protocol for human pluripotent stem cell-derived adipocytes that uses physiologically relevant nutrient conditions to produce a potent signaling response comparable to in vivo adipocytes. After systematically optimizing conditions, this protocol allows for robust insulin-stimulated glucose uptake and transcriptional insulin response. Furthermore, exposure of these sensitized adipocytes to physiologically relevant hyperinsulinemic conditions dampens insulin-stimulated glucose uptake and dysregulates transcription of insulin-responsive genes. Overall, this sensitization methodology provides a novel platform for the mechanistic study of insulin signaling and resistance using human pluripotent stem cell-derived adipocytes. TeaserA new protocol to generate hPSC-adipocytes that respond to physiological insulin levels and can model diabetes.

cell biology↗

bioRxiv2021

Design and modular assembly of synthetic intramembrane proteolysis receptors for custom gene regulation in therapeutic cells

Synthetic biology has established powerful tools to precisely control cell function. Engineering these systems to meet clinical requirements has enormous medical implications. Here, we adopted a clinically driven design process to build receptors for the autonomous control of therapeutic cells. We examined the function of key domains involved in regulated intramembrane proteolysis and showed that systematic modular engineering can generate a class of receptors we call SyNthetic Intramembrane Proteolysis Receptors (SNIPRs) that have tunable sensing and transcriptional response abilities. We demonstrate the potential transformative utility of the receptor platform by engineering human primary T cells for multi-antigen recognition and production of dosed, bioactive payloads relevant to the treatment of disease. Our design framework enables the development of fully humanized and customizable transcriptional receptors for the programming of therapeutic cells suitable for clinical translation.

synthetic biology↗

bioRxiv2021

Clinically-Driven Design of Synthetic Gene Regulatory Programs in Human Cells

Synthetic biology seeks to enable the rational design of regulatory molecules and circuits to reprogram cellular behavior. The application of this approach to human cells could lead to powerful gene and cell-based therapies that provide transformative ways to combat complex diseases. To date, however, synthetic genetic circuits are challenging to implement in clinically-relevant cell types and their components often present translational incompatibilities, greatly limiting the feasibility, efficacy and safety of this approach. Here, using a clinically-driven design process, we developed a toolkit of programmable synthetic transcription regulators that feature a compact human protein-based design, enable precise genome-orthogonal regulation, and can be modulated by FDA-approved small molecules. We demonstrate the toolkit by engineering therapeutic human immune cells with genetic programs that enable titratable production of immunotherapeutics, drug-regulated control of tumor killing in vivo and in 3D spheroid models, and the first multi-channel synthetic switch for independent control of immunotherapeutic genes. Our work establishes a powerful platform for engineering custom gene expression programs in mammalian cells with the potential to accelerate clinical translation of synthetic systems.

synthetic biology↗

bioRxiv2020

Engineering clinically-approved drug gated CAR circuits

Chimeric antigen receptor (CAR) T cell immunotherapy has the potential to revolutionize cancer medicine. However, excessive CAR activation, lack of tumor-specific surface markers, and antigen escape have limited the safety and efficacy of CAR T cell therapy. A multi-antigen targeting CAR system that is regulated by safe, clinically-approved pharmaceutical agents is urgently needed, yet only a few simple systems have been developed, and even fewer have been evaluated for efficacy in vivo. Here, we present NASCAR (NS3 ASsociated CAR), a collection of induc-ible ON and OFF switch CAR circuits engineered with a NS3 protease domain deriving from the Hepatitis C Virus (HCV). We establish their ability to regulate CAR activity using multiple FDA-approved antiviral protease inhibitors, including grazoprevir (GZV), both in vitro and in a xenograft tumor model. In addition, we have engineered several dual-gated NASCAR circuits, consisting of an AND logic gate CAR, universal ON-OFF CAR, and a switchboard CAR. These engineered receptors enhance control over T cell activity and tumor-targeting specificity. Together, our com-prehensive set of multiplex drug-gated CAR circuits represent a dynamic, tunable, and clinically-ready set of modules for enhancing the safety of CAR T cell therapy.

synthetic biology↗

bioRxiv2020

Transcriptional kinetic synergy: a complex landscape revealed by integrating modelling and synthetic biology

1Gene regulation involves synergistic interactions between transcription factors (TFs). Classical thermodynamic models offer a biophysical understanding of synergy based on binding cooperativity and regulated recruitment of RNA polymerase. However, transcription requires polymerase to transition through multiple states. Accordingly, recent work has suggested that "kinetic synergy" can arise through TFs differentially regulating distinct steps of the transcription cycle. Disentangling both sources of synergy has been challenging. Here, we combine theory and experiment to analyze TFs binding to a single shared site, thereby removing simultaneous specific DNA binding. Using the graph-based linear framework, we integrate TF binding with regulation of the transcription cycle, and reveal a complex kinetic synergy landscape dependent on TF concentration, DNA binding and transcriptional activity. We exploit synthetic zinc-finger TF fusions to experimentally interrogate these predictions. Our results confirm that transcription cycle regulation must be integrated with recruitment for a quantitative understanding of transcriptional control.

systems biology↗

bioRxiv2020

Environmental fluctuations reshape an unexpected diversity-disturbance relationship in a microbial community

Environmental disturbances have long been theorized to play a significant role in shaping the diversity and composition of ecosystems1,2. However, fundamental limitations in our ability to specify the characteristics of a disturbance in the field and laboratory have produced an inconsistent picture of diversity-disturbance relationships (DDRs) that shape the structure of ecosystems3. Here, using a recently developed continuous culture system with tunable environmental control4, we decomposed a dilution disturbance into intensity and fluctuation components5,6, and tested their effects on the diversity of a soil-derived bacterial community across hundreds of replicate cultures. We observed an unexpected U-shaped relationship between community diversity and disturbance intensity in the absence of fluctuations, an observation counter to classical intuition. Adding fluctuations erased the U-shape and increased community diversity across all disturbance intensities. All of these results are well-captured by a Monod consumer resource model, which further reveals how U-shaped DDRs emerge based on a novel "niche flip" mechanism in which competitive outcomes flip and coexistence regimes subsequently collapse at intermediate disturbance levels. Broadly, our results demonstrate how distinct features of an environmental disturbance can interact in complex ways to govern ecosystem assembly and produce all the major classes of DDRs, without invoking other organizational principles. With these findings, we construct a unifying framework that reconciles the disparate DDRs observed in nature, and propose strategies for predictively reshaping the compositional complexity of microbiomes and other ecosystems.

bioengineering↗