Synthetic Gene Circuits for Regulation of Next-Generation Cell-Based Therapeutics

Arming human cells with synthetic gene circuits enables to expand their capacity to execute superior sensing and response actions, offering tremendous potential for innovative cellular therapeutics. This can be achieved by assembling components from an ever-expanding molecular toolkit, incorporating switches based on transcriptional, translational, or post-translational control mechanisms. This review provides examples from the three classes of switches, and discusses their advantages and limitations to regulate the activity of therapeutic cells in vivo. Genetic switches designed to recognize internal disease-associated signals often encode intricate actuation programs that orchestrate a reduction in the sensed signal, establishing a closed-loop architecture. Conversely, switches engineered to detect external molecular or physical cues operate in an open-loop fashion, switching on or off upon signal exposure. The integration of such synthetic gene circuits into the next generation of chimeric antigen receptor T-cells is already enabling precise calibration of immune responses in terms of magnitude and timing, thereby improving the potency and safety of therapeutic cells. Furthermore, pre-clinical engineered cells targeting other chronic diseases are gathering increasing attention, and this review discusses the path forward for achieving clinical success. With synthetic biology at the forefront, cellular therapeutics holds great promise for groundbreaking treatments.

Optically stimulated luminescence dosimeters for simultaneous measurement of point dose and dose-weighted LET in an adaptive proton therapy workflow

Purpose

To demonstrate the suitability of optically stimulated luminescence detectors (OSLDs) for accurate simultaneous measurement of the absolute point dose and dose-weighted linear energy transfer (LETD) in an anthropomorphic phantom for experimental validation of daily adaptive proton therapy.

Methods

A clinically realistic intensity-modulated proton therapy (IMPT) treatment plan was created based on a CT of an anthropomorphic head-and-neck phantom made of tissue-equivalent material. The IMPT plan was optimized with three fields to deliver a uniform dose to the target volume covering the OSLDs. Different scenarios representing inter-fractional anatomical changes were created by modifying the phantom. An online adaptive proton therapy workflow was used to recover the daily dose distribution and account for the applied geometry changes. To validate the adaptive workflow, measurements were performed by irradiating Al2O3:C OSLDs inside the phantom. In addition to the measurements, retrospective Monte Carlo simulations were performed to compare the absolute dose and dose-averaged LET (LETD) delivered to the OSLDs.

Results

The online adaptive proton therapy workflow was shown to recover significant degradation in dose conformity resulting from large anatomical and positioning deviations from the reference plan. The Monte Carlo simulations were in close agreement with the OSLD measurements, with an average relative error of 1.4% for doses and 3.2% for LETD. The use of OSLDs for LET determination allowed for a correction for the ionization quenched response.

Conclusion

The OSLDs appear to be an excellent detector for simultaneously assessing dose and LET distributions in proton irradiation of an anthropomorphic phantom. The OSLDs can be cut to almost any size and shape, making them ideal for in-phantom measurements to probe the radiation quality and dose in a predefined region of interest. Although we have presented the results obtained in the experimental validation of an adaptive proton therapy workflow, the same approach can be generalized and used for a variety of clinical innovations and workflow developments that require accurate assessment of point dose and/or average LET.

Alone you go faster, together you go farther

The metastatic process is an extraordinarily complex step-by-step procedure, characterized by many analogies with migratory patterns of humans or animals across our planet. The ongoing interrogation of circulating tumor cells (CTCs), caught in the act of spreading from one location to another, is revealing distinct behaviors including biological, physical, and mechanical features that impact on their likelihood to form metastasis. In this viewpoint, I will discuss some of these findings and provide a perspective on the metastatic journey, open questions and opportunities to exploit some of the most recent discoveries for the development of antimetastasis medicines.

A Spectrofluorometric Method for Real-Time Graft Assessment and Patient Monitoring

Biomarkers are powerful clinical diagnostics and predictors of patient outcome. However, robust measurements often require time and expensive laboratory equipment, which is insufficient to track rapid changes and limits direct use in the operating room. Here, this study presents a portable spectrophotometric device for continuous real-time measurements of fluorescent and non-fluorescent biomarkers at the point of care. This study measures the mitochondrial damage biomarker flavin mononucleotide (FMN) in 26 extended criteria human liver grafts undergoing hypothermic oxygenated perfusion to guide clinical graft assessment. Real-time data identified seven organs unsuitable for transplant that are discarded. The remaining grafts are transplanted and FMN values correlated with post-transplant indicators of liver function and patient recovery. Further, this study shows how this device can be used to monitor dialysis patients by measuring creatinine in real-time. Our approach provides a simple method to monitor biomarkers directly within biological fluids to improve organ assessment, patient care, and biomarker discovery.

Finding food in a changing world: Small-scale foraging habitat preferences of an insectivorous passerine in the Alps

Organisms living in high-elevation habitats are usually habitat specialists who occupy a narrow ecological niche. To envision the response of alpine species to a changing environment, it is fundamental to understand their habitat preferences on multiple spatial and temporal scales. However, information on small-scale habitat use is still widely lacking. We investigated the foraging habitat preferences of the migratory northern wheatear Oenanthe oenanthe during the entire presence at a breeding site in the central Alps. We repeatedly observed 121 adult and juvenile individuals. We applied Bayesian logistic regression models to investigate which habitat characteristics influenced foraging habitat selection on a fine spatial scale, and how habitat use varied temporally. Throughout their presence on the breeding grounds, northern wheatears showed a consistent preference for a mosaic of stones and bare ground patches with slow-growing, short vegetation. The proximity of marmot burrows was preferred, whereas dense and low woody vegetation was avoided. After arrival at the breeding site, short vegetation, preferably close to the snow, was favored. The preference for open habitat patches that provide access to prey underlines the critical role of small-scale habitat heterogeneity for northern wheatears. The strong and consistent preference for a habitat that is under pressure from land-use and climate change suggests that this alpine bird species may be sensitive to habitat loss, leading to a potential range contraction. We highlight the need to conserve habitat diversity on a small spatial scale to ensure the long-term availability of suitable habitat for northern wheatears in the Alps.

In Situ Regolith Seismic Velocity Measurement at the InSight Landing Site on Mars

Interior exploration using Seismic Investigations, Geodesy and Heat Transport's (InSight) seismometer package Seismic Experiment for Interior Structure (SEIS) was placed on the surface of Mars at about 1.2 m distance from the thermal properties instrument Heat flow and Physical Properties Package (HP³) that includes a self-hammering probe. Recording the hammering noise with SEIS provided a unique opportunity to estimate the seismic wave velocities of the shallow regolith at the landing site. However, the value of studying the seismic signals of the hammering was only realized after critical hardware decisions were already taken. Furthermore, the design and nominal operation of both SEIS and HP³ are nonideal for such high-resolution seismic measurements. Therefore, a series of adaptations had to be implemented to operate the self-hammering probe as a controlled seismic source and SEIS as a high-frequency seismic receiver including the design of a high-precision timing and an innovative high-frequency sampling workflow. By interpreting the first-arriving seismic waves as a P-wave and identifying first-arriving S-waves by polarization analysis, we determined effective P- and S-wave velocities of v P = 11 9 - 21 + 45  m/s and v S = 6 3 - 7 + 11  m/s, respectively, from around 2,000 hammer stroke recordings. These velocities likely represent bulk estimates for the uppermost several 10s of cm of regolith. An analysis of the P-wave incidence angles provided an independent v _P /v _S ratio estimate of 1.8 4 - 0.35 + 0.89 that compares well with the traveltime based estimate of 1.8 6 - 0.25 + 0.42 . The low seismic velocities are consistent with those observed for low-density unconsolidated sands and are in agreement with estimates obtained by other methods.

Tissue-Level Regeneration and Remodeling Dynamics are Driven by Mechanical Stimuli in the Microenvironment in a Post-Bridging Loaded Femur Defect Healing Model in Mice

Bone healing and remodeling are mechanically driven processes. While the generalized response to mechanical stimulation in bone is well-understood, much less is known about the mechanobiology-regulating tissue-scale bone formation and resorption during the reparative and remodeling phases of fracture healing. In this study, we combined computational approaches in the form of finite element analysis and experimental approaches by using a loaded femoral defect model in mice to investigate the role of mechanical stimulation in the microenvironment of bone. Specifically, we used longitudinal micro-computed tomography to observe temporal changes in bone at different densities and micro-finite element analysis to map the mechanics of the microenvironment to tissue-scale formation, quiescence (no change in bone presence between time points), and resorption dynamics in the late reparative and remodeling phases (post bridging). Increasing levels of effective strain led to increasing conditional probability of bone formation, while decreasing levels of effective strain led to increasing probability of bone resorption. In addition, the analysis of mineralization dynamics showed both a temporal and effective strain level-dependent behavior. A logarithmic-like response was displayed, where the conditional probability of bone formation or resorption increased rapidly and plateaued or fell rapidly and plateaued as mechanical strain increased.

Handheld Device for Selective Benzene Sensing over Toluene and Xylene

More than 1 million workers are exposed routinely to carcinogenic benzene, contained in various consumer products (e.g., gasoline, rubbers, and dyes) and released from combustion of organics (e.g., tobacco). Despite strict limits (e.g., 50 parts per billion (ppb) in the European Union), routine monitoring of benzene is rarely done since low-cost sensors lack accuracy. This work presents a compact, battery-driven device that detects benzene in gas mixtures with unprecedented selectivity (>200) over inorganics, ketones, aldehydes, alcohols, and even challenging toluene and xylene. This can be attributed to strong Lewis acid sites on a packed bed of catalytic WO₃ nanoparticles that prescreen a chemoresistive Pd/SnO₂ sensor. That way, benzene is detected down to 13 ppb with superior robustness to relative humidity (RH, 10-80%), fulfilling the strictest legal limits. As proof of concept, benzene is quantified in indoor air in good agreement (R² ≥ 0.94) with mass spectrometry. This device is readily applicable for personal exposure assessment and can assist the implementation of low-emission zones for sustainable environments.

Silica-encapsulated DNA tracers for measuring aerosol distribution dynamics in real-world settings

Aerosolized particles play a significant role in human health and environmental risk management. The global importance of aerosol-related hazards, such as the circulation of pathogens and high levels of air pollutants, have led to a surging demand for suitable surrogate tracers to investigate the complex dynamics of airborne particles in real-world scenarios. In this study, we propose a novel approach using silica particles with encapsulated DNA (SPED) as a tracing agent for measuring aerosol distribution indoors. In a series of experiments with a portable setup, SPED were successfully aerosolized, recaptured, and quantified using quantitative polymerase chain reaction (qPCR). Position dependency and ventilation effects within a confined space could be shown in a quantitative fashion achieving detection limits below 0.1 ng particles per m³ of sampled air. In conclusion, SPED show promise for a flexible, cost-effective, and low-impact characterization of aerosol dynamics in a wide range of settings.

Data-enabled predictive control for quadcopters

We study the application of a data-enabled predictive control (DeePC) algorithm for position control of real-world nano-quadcopters. The DeePC algorithm is a finite-horizon, optimal control method that uses input/output measurements from the system to predict future trajectories without the need for system identification or state estimation. The algorithm predicts future trajectories of the quadcopter by linearly combining previously measured trajectories (motion primitives). We illustrate the necessity of a regularized variant of the DeePC algorithm to handle the nonlinear nature of the real-world quadcopter dynamics with noisy measurements. Simulation-based analysis is used to gain insights into the effects of regularization, and experimental results validate that these insights carry over to the real-world quadcopter. Moreover, we demonstrate the reliability of the DeePC algorithm by collecting a new set of input/output measurements for every real-world experiment performed. The performance of the DeePC algorithm is compared to Model Predictive Control based on a first-principles model of the quadcopter. The results are demonstrated with a video of successful trajectory tracking of the real-world quadcopter.

Tree recruitment is determined by stand structure and shade tolerance with uncertain role of climate and water relations

Tree regeneration is a key process for long-term forest dynamics, determining changes in species composition and shaping successional trajectories. While tree regeneration is a highly stochastic process, tree regeneration studies often cover narrow environmental gradients only, focusing on specific forest types or species in distinct regions. Thus, the larger-scale effects of temperature, water availability, and stand structure on tree regeneration are poorly understood.We investigated these effects in respect of tree recruitment (in-growth) along wide environmental gradients using forest inventory data from Flanders (Belgium), northwestern Germany, and Switzerland covering more than 40 tree species. We employed generalized linear mixed models to capture the abundance of tree recruitment in response to basal area, stem density, shade casting ability of a forest stand as well as site-specific degree-day sum (temperature), water balance, and plant-available water holding capacity. We grouped tree species to facilitate comparisons between species with different levels of tolerance to shade and drought.Basal area and shade casting ability of the overstory had generally a negative impact on tree recruitment, but the effects differed between levels of shade tolerance of tree recruitment in all study regions. Recruitment rates of very shade-tolerant species were positively affected by shade casting ability. Stem density and summer warmth (degree-day sum) had similar effects on all tree species and successional strategies. Water-related variables revealed a high degree of uncertainty and did not allow for general conclusions. All variables had similar effects independent of the varying diameter thresholds for tree recruitment in the different data sets.Synthesis: Shade tolerance and stand structure are the main drivers of tree recruitment along wide environmental gradients in temperate forests. Higher temperature generally increases tree recruitment rates, but the role of water relations and drought tolerance remains uncertain for tree recruitment on cross-regional scales.

Learning from Nature: From a Marine Natural Product to Synthetic Cyclooxygenase-1 Inhibitors by Automated De Novo Design

The repertoire of natural products offers tremendous opportunities for chemical biology and drug discovery. Natural product-inspired synthetic molecules represent an ecologically and economically sustainable alternative to the direct utilization of natural products. De novo design with machine intelligence bridges the gap between the worlds of bioactive natural products and synthetic molecules. On employing the compound Marinopyrrole A from marine Streptomyces as a design template, the algorithm constructs innovative small molecules that can be synthesized in three steps, following the computationally suggested synthesis route. Computational activity prediction reveals cyclooxygenase (COX) as a putative target of both Marinopyrrole A and the de novo designs. The molecular designs are experimentally confirmed as selective COX-1 inhibitors with nanomolar potency. X-ray structure analysis reveals the binding of the most selective compound to COX-1. This molecular design approach provides a blueprint for natural product-inspired hit and lead identification for drug discovery with machine intelligence.

Serum deprivation limits loss and promotes recovery of tenogenic phenotype in tendon cell culture systems

Current knowledge gaps on tendon tissue healing can partly be ascribed to the limited availability of physiologically relevant culture models. An unnatural extracellular matrix, high serum levels and random cell morphology in vitro mimic strong vascularization and lost cell elongation in pathology, and discord with a healthy, in vivo cell microenvironment. The thereby induced phenotypic drift in tendon-derived cells (TDCs) compromises the validity of the research model. Therefore, this research quantified the extracellular matrix (ECM)-, serum-, and cell morphology-guided phenotypic changes in tendon cells of whole tendon fascicle explants with intact ECM and TDCs cultured in a controlled microenvironmental niche. Explanted murine tail tendon fascicles were cultured in serum-rich or serum-free medium and phenotype was assessed using transcriptome analysis. Next, phenotypic marker gene expression was measured in in vitro expanded murine tail TDCs upon culture in serum-rich or serum-free medium on aligned or random collagen I patterns. Freshly isolated fascicles or TDCs served as native controls. In both systems, the majority of tendon-specific genes were similarly attenuated in serum-rich culture. Strikingly, 1-week serum-deprived culture-independent of cell morphology-converged TDC gene expression toward native levels. This study reveals a dynamic serum-responsive tendon cell phenotype. Extracting fascicles or TDCs from their native environment causes large changes in cellular phenotype, which can be limited and even reversed by serum deprivation. We conclude that serum-derived factors override matrix-integrity and cell morphology cues and that serum-deprivation stimulates a more physiological microenvironment for in vitro studies.