Mouse genomic associations with in vitro sensitivity to simulated space radiation

Exposure to ionizing radiation is considered by NASA to be a major health hazard for deep space exploration missions. Ionizing radiation sensitivity is modulated by both genomic and environmental factors. Understanding their contributions is crucial for designing experiments in model organisms, evaluating the risk of deep space (i.e. high-linear energy transfer, or LET, particle) radiation exposure in astronauts, and also selecting therapeutic irradiation regimes for cancer patients. We identified single nucleotide polymorphisms in 15 strains of mice, including 10 collaborative cross model strains and 5 founder strains, associated with spontaneous and ionizing radiation-induced in vitro DNA damage quantified based on immunofluorescent tumor protein p53 binding protein (53BP1) positive nuclear foci. Statistical analysis suggested an association with pathways primarily related to cellular signaling, metabolism, tumorigenesis and nervous system damage. We observed different genomic associations in early (4 and 8 h) responses to different LET radiation, while later (24 hour) DNA damage responses showed a stronger overlap across all LETs. Furthermore, a subset of pathways was associated with spontaneous DNA damage, suggesting 53BP1 positive foci as a potential biomarker for DNA integrity in mouse models. Our results suggest several mouse strains as new models to further study the impact of ionizing radiation and validate the identified genetic loci. We also highlight the importance of future human in vitro studies to refine the association of genes and pathways with the DNA damage response to ionizing radiation and identify targets for space travel countermeasures.

Quantification of radiation-induced DNA double strand break repair foci to evaluate and predict biological responses to ionizing radiation

Radiation-induced foci (RIF) are nuclear puncta visualized by immunostaining of proteins that regulate DNA double-strand break (DSB) repair after exposure to ionizing radiation. RIF are a standard metric for measuring DSB formation and repair in clinical, environmental and space radiobiology. The time course and dose dependence of their formation has great potential to predict in vivo responses to ionizing radiation, predisposition to cancer and probability of adverse reactions to radiotherapy. However, increasing complexity of experimentally and therapeutically setups (charged particle, FLASH …) is associated with several confounding factors that must be taken into account when interpreting RIF values. In this review, we discuss the spatiotemporal characteristics of RIF development after irradiation, addressing the common confounding factors, including cell proliferation and foci merging. We also describe the relevant endpoints and mathematical models that enable accurate biological interpretation of RIF formation and resolution. Finally, we discuss the use of RIF as a biomarker for quantification and prediction of in vivo radiation responses, including important caveats relating to the choice of the biological endpoint and the detection method. This review intends to help scientific community design radiobiology experiments using RIF as a key metric and to provide suggestions for their biological interpretation.

Fundamental Biological Features of Spaceflight: Advancing the Field to Enable Deep-Space Exploration

Research on astronaut health and model organisms have revealed six features of spaceflight biology that guide our current understanding of fundamental molecular changes that occur during space travel. The features include oxidative stress, DNA damage, mitochondrial dysregulation, epigenetic changes (including gene regulation), telomere length alterations, and microbiome shifts. Here we review the known hazards of human spaceflight, how spaceflight affects living systems through these six fundamental features, and the associated health risks of space exploration. We also discuss the essential issues related to the health and safety of astronauts involved in future missions, especially planned long-duration and Martian missions.

Considering Cell Proliferation to Optimize Detection of Radiation-Induced 53BP1 Positive Foci in 15 Mouse Strains Ex Vivo

Due to high metabolic activity, proliferating cells continuously generate free radicals, which induce DNA double-strand breaks (DSB). Fluorescently tagged nuclear foci of DNA repair protein 53 binding protein-1 (53BP1) are used as a standard metric for measuring DSB formation at baseline and in response to environmental insults such as radiation. Here we demonstrate that the background level of spontaneous 53BP1+ foci formation can be modeled mathematically as a function of cell confluence, which is a metric of their proliferation rate. This model was validated using spontaneous 53BP1+ foci data from 72 cultures of primary skin fibroblasts derived from 15 different strains of mice, showing a ∼10-fold decrease from low to full confluence that is independent of mouse strain. On the other hand, the baseline level of spontaneous 53BP1+ foci in a fully confluent cell population was strain-dependent, suggesting genomic associations, and correlated with radiation sensitivity based on previous measurements in the same cell lines. Finally, we have developed an online open-access tool to correct for the effect of cell confluence on 53BP1+ foci-based quantification of DSB. This tool provides guidelines for the number of cells required to reach statistical significance for the detection of DSB induced by low doses of ionizing radiation as a function of confluence and time postirradiation.

53BP1 Repair Kinetics for Prediction of In Vivo Radiation Susceptibility in 15 Mouse Strains

We present a novel mathematical formalism to predict the kinetics of DNA damage repair after exposure to both low- and high-LET radiation (X rays; 350 MeV/n 40Ar; 600 MeV/n 56Fe). Our method is based on monitoring DNA damage repair protein 53BP1 that forms radiation-induced foci (RIF) at locations of DNA double-strand breaks (DSB) in the nucleus and comparing its expression in primary skin fibroblasts isolated from 15 mice strains. We previously reported strong evidence for clustering of nearby DSB into single repair units as opposed to the classic "contact-first" model where DSB are considered immobile. Here we apply this clustering model to evaluate the number of remaining RIF over time. We also show that the newly introduced kinetic metrics can be used as surrogate biomarkers for in vivo radiation toxicity, with potential applications in radiotherapy and human space exploration. In particular, we observed an association between the characteristic time constant of RIF repair measured in vitro and survival levels of immune cells collected from irradiated mice. Moreover, the speed of DNA damage repair correlated not only with radiation-induced cellular survival in vivo, but also with spontaneous cancer incidence data collected from the Mouse Tumor Biology database, suggesting a relationship between the efficiency of DSB repair after irradiation and cancer risk.

In Situ Detection of Complex DNA Damage Using Microscopy: A Rough Road Ahead

Complexity of DNA damage is considered currently one if not the primary instigator of biological responses and determinant of short and long-term effects in organisms and their offspring. In this review, we focus on the detection of complex (clustered) DNA damage (CDD) induced for example by ionizing radiation (IR) and in some cases by high oxidative stress. We perform a short historical perspective in the field, emphasizing the microscopy-based techniques and methodologies for the detection of CDD at the cellular level. We extend this analysis on the pertaining methodology of surrogate protein markers of CDD (foci) colocalization and provide a unique synthesis of imaging parameters, software, and different types of microscopy used. Last but not least, we critically discuss the main advances and necessary future direction for the better detection of CDD, with important outcomes in biological and clinical setups.

Ionizing radiation-induced risks to the central nervous system and countermeasures in cellular and rodent models

PURPOSE

Harmful effects of ionizing radiation on the Central Nervous System (CNS) are a concerning outcome in the field of cancer radiotherapy and form a major risk for deep space exploration. Both acute and chronic CNS irradiation induce a complex network of molecular and cellular alterations including DNA damage, oxidative stress, cell death and systemic inflammation, leading to changes in neuronal structure and synaptic plasticity with behavioral and cognitive consequences in animal models. Due to this complexity, countermeasure or therapeutic approaches to reduce the harmful effects of ionizing radiation include a wide range of protective and mitigative strategies, which merit a thorough comparative analysis.

MATERIALS AND METHODS

We reviewed current approaches for developing countermeasures to both targeted and non-targeted effects of ionizing radiation on the CNS from the molecular and cellular to the behavioral level.

RESULTS

We focus on countermeasures that aim to mitigate the four main detrimental actions of radiation on CNS: DNA damage, free radical formation and oxidative stress, cell death, and harmful systemic responses including tissue death and neuroinflammation. We propose a comprehensive review of CNS radiation countermeasures reported for the full range of irradiation types (photons and particles, low and high linear energy transfer) and doses (from a fraction of gray to several tens of gray, fractionated and unfractionated), with a particular interest for exposure conditions relevant to deep-space environment and radiotherapy. Our review reveals the importance of combined strategies that increase DNA protection and repair, reduce free radical formation and increase their elimination, limit inflammation and improve cell viability, limit tissue damage and increase repair and plasticity.

CONCLUSIONS

The majority of therapeutic approaches to protect the CNS from ionizing radiation have been limited to acute high dose and high dose rate gamma irradiation, and few are translatable from animal models to potential human application due to harmful side effects and lack of blood-brain barrier permeability that precludes peripheral administration. Therefore, a promising research direction would be to focus on practical applicability and effectiveness in a wider range of irradiation paradigms, from fractionated therapeutic to deep space radiation. In addition to discovering novel therapeutics, it would be worth maximizing the benefits and reducing side effects of those that already exist. Finally, we suggest that novel cellular and tissue models for developing and testing countermeasures in the context of other impairments might also be applied to the field of CNS responses to ionizing radiation.

Peptide-siRNA Supramolecular Particles for Neural Cell Transfection

Small interfering ribonucleic acid (siRNA)-based gene knockdown is an effective tool for gene screening and therapeutics. However, the use of nonviral methods has remained an enormous challenge in neural cells. A strategy is reported to design artificial noncationic modular peptides with amplified affinity for siRNA via supramolecular assembly that shows efficient protein knockdown in neural cells. By solid phase synthesis, a sequence that binds specifically double-stranded ribonucleic acid (dsRNA) with a self-assembling peptide for particle formation is integrated. These supramolecular particles can be further functionalized with bioactive sequences without affecting their biophysical properties. The peptide carrier is found to silence efficiently up to 83% of protein expression in primary astroglial and neuronal cell cultures without cytotoxicity. In the case of neurons, a reduction in electrical activity is observed once the presynaptic protein synaptophysin is downregulated by the siRNA-peptide particles. The results demonstrate that the supramolecular particles offer an siRNA delivery platform for efficient nonviral gene screening and discovery of novel therapies for neural cells.

Separation of Biological Particles in a Modular Platform of Cascaded Deterministic Lateral Displacement Modules

Deterministic lateral displacement (DLD) has been extensively implemented in the last decade for size-based sample preparation, owing to its high separation performances for a wide range of particle dimensions. However, separating particles from 1 μm to 10 μm in one single DLD device is challenging because of the required diversity of pillar dimensions and inherent fabrication issues. This paper presents an alternative approach to achieve the extraction of E. coli bacteria from blood samples spiked with prostate cancer cells. Our approach consists in cascading individual DLD devices in a single automated platform, using flexible chambers that successively collect and inject the sample between each DLD stage without any external sample manipulation. Operating DLD separations independently enables to maximize the sorting efficiency at each step, without any disturbance from downstream stages. The proposed two-step automated protocol is applied to the separation of three types of components (bacteria, blood particles and cancer cells), with a depletion yield of 100% for cancer cells and 93% for red blood cells. This cascaded approach is presented for the first time with two DLD modules and is upscalable to improve the dynamic range of currently available DLD devices.

Purification of complex samples: Implementation of a modular and reconfigurable droplet-based microfluidic platform with cascaded deterministic lateral displacement separation modules

Particle separation in microfluidic devices is a common problematic for sample preparation in biology. Deterministic lateral displacement (DLD) is efficiently implemented as a size-based fractionation technique to separate two populations of particles around a specific size. However, real biological samples contain components of many different sizes and a single DLD separation step is not sufficient to purify these complex samples. When connecting several DLD modules in series, pressure balancing at the DLD outlets of each step becomes critical to ensure an optimal separation efficiency. A generic microfluidic platform is presented in this paper to optimize pressure balancing, when DLD separation is connected either to another DLD module or to a different microfluidic function. This is made possible by generating droplets at T-junctions connected to the DLD outlets. Droplets act as pressure controllers, which perform at the same time the encapsulation of DLD sorted particles and the balance of output pressures. The optimized pressures to apply on DLD modules and on T-junctions are determined by a general model that ensures the equilibrium of the entire platform. The proposed separation platform is completely modular and reconfigurable since the same predictive model applies to any cascaded DLD modules of the droplet-based cartridge.

Anticipating Cutoff Diameters in Deterministic Lateral Displacement (DLD) Microfluidic Devices for an Optimized Particle Separation

Deterministic lateral displacement (DLD) devices enable to separate nanometer to micrometer-sized particles around a cutoff diameter, during their transport through a microfluidic channel with slanted rows of pillars. In order to design appropriate DLD geometries for specific separation sizes, robust models are required to anticipate the value of the cutoff diameter. So far, the proposed models result in a single cutoff diameter for a given DLD geometry. This paper shows that the cutoff diameter actually varies along the DLD channel, especially in narrow pillar arrays. Experimental and numerical results reveal that the variation of the cutoff diameter is induced by boundary effects at the channel side walls, called the wall effect. The wall effect generates unexpected particle trajectories that may compromise the separation efficiency. In order to anticipate the wall effect when designing DLD devices, a predictive model is proposed in this work and has been validated experimentally. In addition to the usual geometrical parameters, a new parameter, the number of pillars in the channel cross dimension, is considered in this model to investigate its influence on the particle trajectories.

Anticipating Cutoff Diameters in Deterministic Lateral Displacement (DLD) Microfluidic Devices for an Optimized Particle Separation

Deterministic lateral displacement (DLD) devices enable to separate nanometer to micrometer-sized particles around a cutoff diameter, during their transport through a microfluidic channel with slanted rows of pillars. In order to design appropriate DLD geometries for specific separation sizes, robust models are required to anticipate the value of the cutoff diameter. So far, the proposed models result in a single cutoff diameter for a given DLD geometry. This paper shows that the cutoff diameter actually varies along the DLD channel, especially in narrow pillar arrays. Experimental and numerical results reveal that the variation of the cutoff diameter is induced by boundary effects at the channel side walls, called the wall effect. The wall effect generates unexpected particle trajectories that may compromise the separation efficiency. In order to anticipate the wall effect when designing DLD devices, a predictive model is proposed in this work and has been validated experimentally. In addition to the usual geometrical parameters, a new parameter, the number of pillars in the channel cross dimension, is considered in this model to investigate its influence on the particle trajectories.