Extracellular vesicles mediate radiation-induced systemic bystander signals in the bone marrow and spleen

Radiation-induced bystander effects refer to the induction of biological changes in cells not directly hit by radiation implying that the number of cells affected by radiation is larger than the actual number of irradiated cells. Recent in vitro studies suggest the role of extracellular vesicles (EV) in mediating radiation-induced bystander signals but in vivo investigations are still lacking. Here we report an in vivo study investigating the role of EVs in mediating radiation effects. C57BL/6 mice were total-body irradiated with X-rays (0.1, 0.25, 2 Gy), 24 hours later EVs were isolated from the bone marrow and were intravenously injected into unirradiated (so-called bystander) animals. EV-induced systemic effects were compared to radiation effects in the directly irradiated animals. Similarly to direct radiation EVs from irradiated mice induced complex DNA damage in EV-recipient animals, manifested in an increased level of chromosomal aberrations and the activation of the DNA damage response. However, while DNA damage after direct irradiation increased with the dose, EV-induced effects peaked at lower doses. A significantly reduced hematopoietic stem cell pool in the BM as well as CD4+ and CD8+ lymphocyte pool in the spleen was detected in mice injected with EVs isolated from animals irradiated with 2 Gy. These EV-induced alterations were comparable to changes present in the directly irradiated mice. The pool of TLR4-expressing dendritic cells was different in the directly irradiated mice, where it increased after 2 Gy and in the EV-recipient animals, where it strongly decreased in a dose-independent manner. A panel of 8 differentially expressed miRNAs were identified in the EVs originating from both low and high dose-irradiated mice, with a predicted involvement in pathways related to DNA damage repair, hematopoietic and immune system regulation, suggesting a direct involvement of these pathways in mediating radiation-induced systemic effects. ​ In conclusion, we proved the role of EVs in transmitting certain radiation effects, identified miRNAs carried by EVs potentially responsible for these effects and showed that the pattern of changes was often different in the directly irradiated and EV-recipient bystander mice, suggesting different mechanisms

Biodistribution Investigations of Technetium-Labelllled Murine Bone Marrow-Derived Extracellllular Vesicles by Nanospect/Ct

The in vivo tracing of the biodistribution of extracellular vesicles (EVs) is a pre-requisite in identifying their target cells and understanding their function. Although luorescent labelling of EVs is already used, radiolabelling can provide more details in understanding biodistribution of EVs. In the present paper we report radiolabelling of bone marrow-derived EVs and in vivo tracing of their biodistribution. EVs isolated from the bone marrow supernatant of űő7ŰL/6 mice were labelled with the technetium-99m (99mTc) isotope. Labelling was eficient and labelled EVs were stable during the 2Ő hours follow-up. Detection of labelled EVs after intravenous injection in mice was performed using ex vivo measurements and in vivo imaging. Ex vivo examinations revealed that at Ő hours post-injection, the highest accumulation rate was in the liver, kidney, spleen and femur epiphysis. In vivo imaging using nanoSPEűT/űT conirmed the ex vivo examinations and demonstrated slow elimination of the radioactivity, 2Ő hours post- injection the bone marrow-containing epiphysis and lymph nodes showed the highest retention values; liver, spleen and kidney were also clearly detectable. In summary, labelling of bone marrow-derived EVs with 99mTc coupled with SPEűT/űT detection was a reliable method for quantitative distribution studies of EVs in vivo

Long-term effects of medical management on growth and weight in individuals with urea cycle disorders

Low protein diet and sodium or glycerol phenylbutyrate, two pillars of recommended long-term therapy of individuals with urea cycle disorders (UCDs), involve the risk of iatrogenic growth failure. Limited evidence-based studies hamper our knowledge on the long-term effects of the proposed medical management in individuals with UCDs. We studied the impact of medical management on growth and weight development in 307 individuals longitudinally followed by the Urea Cycle Disorders Consortium (UCDC) and the European registry and network for Intoxication type Metabolic Diseases (E-IMD). Intrauterine growth of all investigated UCDs and postnatal linear growth of asymptomatic individuals remained unaffected. Symptomatic individuals were at risk of progressive growth retardation independent from the underlying disease and the degree of natural protein restriction. Growth impairment was determined by disease severity and associated with reduced or borderline plasma branched-chain amino acid (BCAA) concentrations. Liver transplantation appeared to have a beneficial effect on growth. Weight development remained unaffected both in asymptomatic and symptomatic individuals. Progressive growth impairment depends on disease severity and plasma BCAA concentrations, but cannot be predicted by the amount of natural protein intake alone. Future clinical trials are necessary to evaluate whether supplementation with BCAAs might improve growth in UCDs

Enhancing Genomic Prediction Models for Forecasting Days to Maturity in Soybean Genotypes Using Site-Specific and Cumulative Photoperiod Data

Genomic selection (GS) has revolutionized breeding strategies by predicting the rank performance of post-harvest traits via implementing genomic prediction (GP) models. However, predicting pre-harvest traits in unobserved environments might produce serious biases. In soybean, days to maturity (DTM) represents a crucial stage with a significant impact on yield potential; thus, genotypes must be carefully selected to ensure latitudinal adaptation in this photoperiod-sensitive crop species. This research assessed the use of daylength for predicting DTM in unobserved environments (CV00). A soybean dataset comprising 367 genotypes spanning nine families of the Soybean Nested Association Mapping Panel (SoyNAM) and tested in 11 environments (year-by-location combinations) was considered in this study. The proposed method (CB) returned a root-mean-square error (RMSE) of 5.2 days, a Pearson correlation (PC) of 0.66, and the predicted vs. observed difference in the environmental means (PODEM) ranged from −3.3 to 4.5 days; however, in the absence of daylength data, the conventional GP implementation produced an RMSE of 9 days, a PC of 0.66, and a PODEM range from −14.7 to 7.9 days. These results highlight the importance of dissecting phenotypic variability (G × E) based on photoperiod data and non-predictable environmental stimuli for improving the predictive ability and accuracy of DTM in soybeans