Database of space life investigations and bioinformatics of microbiology in extreme environments

A Review: Multi-Omics Approach to Studying the Association between Ionizing Radiation Effects on Biological Aging

Multi-omics studies have emerged as powerful tools for tailoring individualized responses to various conditions, capitalizing on genome sequencing technologies' increasing affordability and efficiency. This paper delves into the potential of multi-omics in deepening our understanding of biological age, examining the techniques available in light of evolving technology and computational models. The primary objective is to review the relationship between ionizing radiation and biological age, exploring a wide array of functional, physiological, and psychological parameters. This comprehensive review draws upon an extensive range of sources, including peer-reviewed journal articles, government documents, and reputable websites. The literature review spans from fundamental insights into radiation effects to the latest developments in aging research. Ionizing radiation exerts its influence through direct mechanisms, notably single- and double-strand DNA breaks and cross links, along with other critical cellular events. The cumulative impact of DNA damage forms the foundation for the intricate process of natural aging, intersecting with numerous diseases and pivotal biomarkers. Furthermore, there is a resurgence of interest in ionizing radiation research from various organizations and countries, reinvigorating its importance as a key contributor to the study of biological age. Biological age serves as a vital reference point for the monitoring and mitigation of the effects of various stressors, including ionizing radiation. Ionizing radiation emerges as a potent candidate for modeling the separation of biological age from chronological age, offering a promising avenue for tailoring protocols across diverse fields, including the rigorous demands of space exploration.

Exploring outer space biophysical phenomena via SpaceLID

Extensive investigations in outer space have revealed not only how life adapts to the space environment, but also that interesting biophysical phenomena occur. These phenomena affect human health and other life forms (animals, plants, bacteria, and fungi), and to ensure the safety of future human space exploration need to be further investigated. This calls for joint research efforts between biologists and physicists, as these phenomena present cross-disciplinary barriers. Various national organizations provide useful forums for bridging this gap. Additional discussion avenues and database resources are helpful for facilitating the interdisciplinary investigations of these phenomena. In this paper, we present the newly established Space Life Investigation Database (SpaceLID, https://bidd.group/spacelid/ ) which provides information about biophysical phenomena occurring in space. Examples obtained using the database are given while discussing the underlying causes of these phenomena and their implications for the physiology and health of life in space.

Database of space life investigations and information on spaceflight plant biology

Extensive spaceflight life investigations (SLIs) have revealed observable space effects on plants, particularly their growth, nutrition yield, and secondary metabolite production. Knowledge of these effects not only facilitates space agricultural and biopharmaceutical technology development but also provides unique perspectives to ground-based investigations. SLIs are specialized experimental protocols and notable biological phenomena. These require specialized databases, leading to the development of the NASA Science Data Archive, Erasmus Experiment Archive, and NASA GeneLab. The increasing interests of SLIs across diverse fields demand resources with comprehensive content, convenient search facilities, and friendly information presentation. A new database SpaceLID (Space Life Investigation Database http://bidd.group/spacelid/ ) was developed with detailed menu search tools and categorized contents about the phenomena, protocols, and outcomes of 459 SLIs (including 106 plant investigations) of 92 species, where 236 SLIs and 57 plant investigations are uncovered by the existing databases. The usefulness of SpaceLID as an SLI information source is illustrated by the literature-reported analysis of metabolite, nutrition, and symbiosis variations of spaceflight plants. In conclusion, this study extensively investigated the impact of the space environment on plant biology, utilizing SpaceLID as an information source and examining various plant species, including Arabidopsis thaliana, Brassica rapa L., and Glycyrrhiza uralensis Fisch. The findings provide valuable insights into the effects of space conditions on plant physiology and metabolism.

Big Data for a Small World: A Review on Databases and Resources for Studying Microbiomes

Microorganisms are ubiquitous in nature and form complex community networks to survive in various environments. This community structure depends on numerous factors like nutrient availability, abiotic factors like temperature and pH as well as microbial composition. Categorising accessible biomes according to their habitats would help in understanding the complexity of the environment-specific communities. Owing to the recent improvements in sequencing facilities, researchers have started to explore diverse microbiomes rapidly and attempts have been made to study microbial crosstalk. However, different metagenomics sampling, preprocessing, and annotation methods make it difficult to compare multiple studies and hinder the recycling of data. Huge datasets originating from these experiments demand systematic computational methods to extract biological information beyond microbial compositions. Further exploration of microbial co-occurring patterns across the biomes could help us in designing cross-biome experiments. In this review, we catalogue databases with system-specific microbiomes, discussing publicly available common databases as well as specialised databases for a range of microbiomes. If the new datasets generated in the future could maintain at least biome-specific annotation, then researchers could use those contemporary tools for relevant and bias-free analysis of complex metagenomics data.