Composition of Conditioned Media from Radioresistant and Chemoresistant Cancer Cells Reveals miRNA and Other Secretory Factors Implicated in the Development of Resistance.

Resistance to chemo- or radiotherapy is the main obstacle to consistent treatment outcomes in oncology patients. A deeper understanding of the mechanisms driving the development of resistance is required. This review focuses on secretory factors derived from chemo- and radioresistant cancer cells, cancer-associated fibroblasts (CAFs), mesenchymal stem cells (MSCs), and cancer stem cells (CSCs) that mediate the development of resistance in unexposed cells. The first line of evidence considers the experiments with conditioned media (CM) from chemo- and radioresistant cells, CAFs, MSCs, and CSCs that elevate resistance upon the ionizing radiation or anti-cancer drug exposure of previously untreated cells. The composition of CM revealed factors such as circular RNAs; interleukins; plasminogen activator inhibitor; and oncosome-shuttled lncRNAs, mRNAs, and miRNAs that aid in cellular communication and transmit signals inducing the chemo- and radioresistance of sensitive cancer cells. Data, demonstrating that radioresistant cancer cells become resistant to anti-neoplastic drug exposure and vice versa, are also discussed. The mechanisms driving the development of cross-resistance between chemotherapy and radiotherapy are highlighted. The secretion of resistance-mediating factors to intercellular fluid and blood brings attention to its diagnostic potential. Highly stable serum miRNA candidates were proposed by several studies as prognostic markers of radioresistance; however, clinical studies are needed to validate their utility. The ability to predict a treatment response with the help of the miRNA resistance status database will help with the selection of an effective therapeutic strategy. The possibility of miRNA-based therapy is currently being investigated with ongoing clinical studies, and such approaches can be used to alleviate resistance in oncology patients.

Population genomics of the honey bee reveals strong signatures of positive selection on worker traits.

Most theories used to explain the evolution of eusociality rest upon two key assumptions: mutations affecting the phenotype of sterile workers evolve by positive selection if the resulting traits benefit fertile kin, and that worker traits provide the primary mechanism allowing social insects to adapt to their environment. Despite the common view that positive selection drives phenotypic evolution of workers, we know very little about the prevalence of positive selection acting on the genomes of eusocial insects. We mapped the footprints of positive selection in Apis mellifera through analysis of 40 individual genomes, allowing us to identify thousands of genes and regulatory sequences with signatures of adaptive evolution over multiple timescales. We found Apoidea- and Apis-specific genes to be enriched for signatures of positive selection, indicating that novel genes play a disproportionately large role in adaptive evolution of eusocial insects. Worker-biased proteins have higher signatures of adaptive evolution relative to queen-biased proteins, supporting the view that worker traits are key to adaptation. We also found genes regulating worker division of labor to be enriched for signs of positive selection. Finally, genes associated with worker behavior based on analysis of brain gene expression were highly enriched for adaptive protein and cis-regulatory evolution. Our study highlights the significant contribution of worker phenotypes to adaptive evolution in social insects, and provides a wealth of knowledge on the loci that influence fitness in honey bees.

Mathematical Model of Antibiotic Resistance Determinants' Stability Under Space Flight Conditions.

Increasing antibiotic resistance (AR) poses dangers of treatment complications and even treatment failure to astronauts. An AR determinant is a gene of resistance carried by bacteria. This article considers the issue of the stability of AR determinants and the influence of manned spaceflight conditions on this characteristic. A phenomenological model has been developed that makes it possible to evaluate the integral value of the stability of determinants of AR in bacteria as a function of time. Based on experimental results obtained during implementation of the SALYUT 7 space program, the stability of determinants of AR in Escherichia coli strains isolated before and after a spaceflight in 16 astronauts was evaluated. In addition, an assessment was made of the integral value of the stability of determinants of AR in bacteria during in vitro experiments, both in spaceflight and terrestrial conditions, after preincubation in space. The calculation using the developed phenomenological model showed that the stability of AR determinants in E. coli bacteria isolated from astronauts before the spaceflight is 33% higher than after the flight. The in vitro experiment carried out on board the International Space Station showed the opposite situation-an increase in the stability of AR determinants by 33% in cultures that have been in space compared with terrestrial control. This indicates an additional influence on the stability of determinants and of the astronaut's immune system, as well as space conditions. The common result in these two types of studies is the experimental fact that the largest number of bacteria, in space conditions, had two determinants of AR. The importance of fighting bacteria with two determinants is that at least three different antibiotics are required to have an effect. This circumstance makes it possible to predict a possible strategy for the use of antibiotics in autonomous spaceflights.

Residual Foci of DNA Damage Response Proteins in Relation to Cellular Senescence and Autophagy in X-Ray Irradiated Fibroblasts.

DNA repair (DNA damage) foci observed 24 h and later after irradiation are called "residual" in the literature. They are believed to be the repair sites for complex, potentially lethal DNA double strand breaks. However, the features of their post-radiation dose-dependent quantitative changes and their role in the processes of cell death and senescence are still insufficiently studied. For the first time in one work, a simultaneous study of the association of changes in the number of residual foci of key DNA damage response (DDR) proteins (γH2AX, pATM, 53BP1, p-p53), the proportion of caspase-3 positive, LC-3 II autophagic and SA-ß-gal senescent cells was carried out 24-72 h after fibroblast irradiation with X-rays at doses of 1-10 Gy. It was shown that with an increase in time after irradiation from 24 h to 72 h, the number of residual foci and the proportion of caspase-3 positive cells decrease, while the proportion of senescent cells, on the contrary, increases. The highest number of autophagic cells was noted 48 h after irradiation. In general, the results obtained provide important information for understanding the dynamics of the development of a dose-dependent cellular response in populations of irradiated fibroblasts.

Pleiotropy constrains the evolution of protein but not regulatory sequences in a transcription regulatory network influencing complex social behaviors.

It is increasingly apparent that genes and networks that influence complex behavior are evolutionary conserved, which is paradoxical considering that behavior is labile over evolutionary timescales. How does adaptive change in behavior arise if behavior is controlled by conserved, pleiotropic, and likely evolutionary constrained genes? Pleiotropy and connectedness are known to constrain the general rate of protein evolution, prompting some to suggest that the evolution of complex traits, including behavior, is fuelled by regulatory sequence evolution. However, we seldom have data on the strength of selection on mutations in coding and regulatory sequences, and this hinders our ability to study how pleiotropy influences coding and regulatory sequence evolution. Here we use population genomics to estimate the strength of selection on coding and regulatory mutations for a transcriptional regulatory network that influences complex behavior of honey bees. We found that replacement mutations in highly connected transcription factors and target genes experience significantly stronger negative selection relative to weakly connected transcription factors and targets. Adaptively evolving proteins were significantly more likely to reside at the periphery of the regulatory network, while proteins with signs of negative selection were near the core of the network. Interestingly, connectedness and network structure had minimal influence on the strength of selection on putative regulatory sequences for both transcription factors and their targets. Our study indicates that adaptive evolution of complex behavior can arise because of positive selection on protein-coding mutations in peripheral genes, and on regulatory sequence mutations in both transcription factors and their targets throughout the network.